Interferon-gamma (IFN-γ) is an important cytokine in host defense against tuberculosis infection. In some cases, administration of IFN-γ during tuberculosis infection can promote faster cure. In the present work, we have shown that in a mouse model, human interferon-gamma, exhibits some anti-tuberculosis activity, especially in combination with isoniazid.

Obtaining a genetic diagnosis of a primary mitochondrial disease (PMD) is often framed as a diagnostic odyssey. Yet, even after receiving a diagnosis, parents of affected children experience ongoing therapeutic and prognostic uncertainty, and considerable psychosocial challenges. Semi-structured interviews (N= 24) were conducted with parents of 13 children (aged 2-19 years) with a genetically confirmed PMD. Paternal (N=11) and maternal (N=13) perspectives were obtained, and thematic analysis performed on all interviews. A genetic diagnosis was valuable and empowering for parents, despite eliciting varied emotional responses. While the diagnosis helped focus management decisions, families often felt overwhelmed and unsupported in navigating the healthcare system. Most parents reported a serious impact on their romantic relationship. The sources of social support varied with a preference for established friendship and family support networks over disease-specific community support groups. Most parents favored prenatal genetic testing in the event of a future pregnancy. This study provides insight into the lived experiences of parents after a genetic diagnosis of PMD in their children. The findings draw awareness to supportive care needs and highlight important gaps that should be addressed to ensure that parents feel supported within a holistic framework of management for PMDs.

Genomics has put prokaryotic rank-based taxonomy on a solid phylogenetic foundation. However, most taxonomic ranks were set long before the advent of DNA sequencing and genomics. In this concept paper, we thus ask the simple yet profound question: Should prokaryotic classification schemes besides the current phylum-to-species ranks be explored, developed, and incorporated into scientific discourse? Could such alternative schemes provide better solutions to the basic need of science and society for which taxonomy was developed, namely, precise and meaningful identification? A neutral genome-similarity based framework is then described that could allow alternative classification schemes to be explored, compared, and translated into each other without having to choose only one as the gold standard. Classification schemes could thus continue to evolve and be selected according to their benefits and based on how well they fulfill the need for prokaryotic identification.

Non-coding RNAs (ncRNAs) comprise a diverse class of non-protein coding transcripts that regulate critical cellular processes associated with cancer. Advances in RNA-sequencing (RNA-Seq) have led to the characterization of non-coding RNA expression across different types of human cancers. Through comprehensive RNA-Seq profiling, a growing number of studies demonstrate that ncRNAs, including long non-coding RNA (lncRNAs) and microRNAs (miRNA), play central roles in progenitor B-cell Acute Lymphoblastic Leukemia (B-ALL) pathogenesis. Furthermore, due to their central roles in cellular homeostasis and their potential as biomarkers, the study of ncRNAs continues to provide new insight into the molecular mechanisms of B-ALL. This article reviews the ncRNA signatures reported for all B-ALL subtypes, focusing on technological developments in transcriptome profiling and recently discovered examples of ncRNAs with biologic and therapeutic relevance in B-ALL.

：Non-Euclidean data, such as social networks, and citation relationships between documents, has node information and structural information. Graph Convolutional Network(GCN) can automatically learn node features and association information between nodes. The core ideology of the graph convolutional network is to aggregate node information by using edge information, thereby generating a new node feature. In the process of updating node features, there are two core influencing factors. One is the number of neighboring nodes of the central node, the other is the contribution of the neighboring nodes to the central node. Due to the previous GCN methods not simultaneously considering the numbers and different contributions of neighboring nodes to the central node, we design the Adaptive Attention Mechanism(AAM). To further enhance the representational capability of the model, we utilize Multi-Head Graph Convolution(MHGC). Finally, we adopt cross-entropy(CE) loss function to describe the difference between the predicted results of node categories and the ground truth (GT). Combined with backpropagation, this ultimately achieves accurate node classification. Based on AAM, MHGC and CE, we contrive the novel Graph Adaptive Attention Network (GAAN). Experiments show that the classification accuracy has achieved outstanding performances on Cora, Citeseer and Pubmed datasets.

The existing segmentation-based scene text detection methods mostly need complicated post-processing, and the post-processing operation is separated from the training process, which greatly reduces the detection performance. The previous method, DBNet successfully simplified post-processing and integrated the post-processing into a segmentation network. However, the training process of the model took a long time for 1200 epochs and the sensitivity to texts of various scales was lacking, leading to some text instances being missed. Considering the above two problems, we design the text detection Network with Binarization of Hyperbolic Tangent(HTBNet). First of all, we propose Binarization of Hyperbolic Tangent (HTB), optimized along with which, the segmentation network can expedite the initial convergent speed by reducing the amount of epochs from 1200 to 600. Because features of different channels in the same scale feature map focus on the information of different regions in the image, to better represent the important features of all objects in the image, we devise the Multi-Scale Channel Attention(MSCA). Meanwhile considering that multi-scale objects in the image cannot be simultaneously detected, we propose a novel module named Fused Module with Channel and Spatial(FMCS), which can fuse the multi-scale feature maps from channel and spatial dimension. Finally we adopt cross entropy as the loss function, which measures the difference between predicted values and ground truths. The experimental results show that HTBNet compared with lightweight models has achieved competitive performance and speed on Total-Text(F-measure:86.0%, FPS:30) and MSRA-TD500 (F-measure:87.5%, FPS:30).

Despite their prevalence in almost all publicly orientated conservation settings, sign design receives limited attention in the research literature. We used a remote eye-tracking device to test how visitors read educational signs, maps, and species signage. Three designs, plus a plain-text control sign, were tested for each sign type. Sign content was based on Brackenhurst Botanic Garden, Kenya and included four different information texts (156-256 words long) and a species information text (64 words long). Four presentations of extinction threat-status were also tested as were depictions of trail routes on maps. Data were collected from 51 participants at six cultural venues across Nottingham, UK. Signs positioned centre-left of an exhibit were read first. Information on the left-hand side of signs was read first and dwelled upon the longest. Signs with a single large image and a single block of text were generally preferred, and images were most frequently recalled. Extinction threat-status was most frequently viewed and best recalled from green-red thermometer diagrams and least from the IUCN red-list diagram. Map routes were clearest when presented as coloured solid lines. This study indicates the potential benefit of eye-tracking research for measuring sign use and assisting in sign design.

Intrusion Detection Systems (IDS) plays a part in modern cyber security, as a result of the increasing need for cyber security systems in the “real” world due to the increasing number of cyber attacks, more sophisticated systems are required in order to prevent these attacks - an IDS can provide this protection. Due to the sophistication of these systems, they must be properly understood, developed and analyzed - research papers can be used as a tool to improve IDS systems. This paper is composed of two main sections: a survey and a taxonomy, providing information, reviews and interpretations from relevant papers, a timeline of important papers, a discussion on the future of IDS and a classification on IDS and how to apply this.

Background: Pharmacologic and non-pharmacologic treatments for stroke are essential but could be costly or harmful whereas probiotic has been a promising alternative. This scoping review aimed to synthesize the in vitro and in vivo evidence of probiotics on stroke-related neurological, biochemical, and histochemical outcomes. Method: We searched in PubMed, Embase, and Cochrane Central Register of Clinical up to May 7, 2021, and screened by two independent reviewers. We included the use of probiotics, prebiotics, and symbiotics both in vitro and in vivo for the prevention or treatment of the stroke-related model. Result: Of 6,293 articles, 4,990 passed the initial screen, of which 36 theme-related full-texts were assessed and 13 were included in this review. Probiotics could ameliorate the neurological deficit and show their property as an anti-inflammation and anti-oxidative stress. Histopathologically decreased loss of cerebral volume and inhibition of neuronal apoptosis were found. Conclusion: There are potential cognitive benefits of probiotic supplementation, especially among animal models, on decreasing cerebral volume, increasing neurological score, and decreasing the inflammatory response. However, further investigation is needed to validate these conclusions in various populations.

BackgroundLiving donor liver transplantation offers comparable long-term results to cadaveric donor transplantation. This study analyzes the selection process of living liver donors at a Western transplant center that utilizes both donation forms. MethodsThis retrospective analysis examined potential living donors, collecting medical data and reasons for refusal, and divided patients by indication and urgency for transplantation. ResultsFrom January 2013 to December 2023, 594 potential living donors were assessed at Jena University Hospital. Of these, 124 living donor transplants were performed. During outpatient evaluation, 357 potential donors were excluded. Subsequently, 238 individuals underwent inpatient assessment, with 100 more being excluded. Main reasons for donor refusal included medical or psychological issues (n=160), disease progression in recipients (n=90), and recipient refusal or donor withdrawal (n=54). The evaluation process showed a trend towards considering more distant relatives and acquaintances as donor candidates with increasing severity of the recipient's disease.

This study explores the dynamics of transparency and accountability in supplier relationship management (SRM) within the e-commerce sector. It investigates how e-commerce platforms and their suppliers navigate complexities to foster trust, enhance collaboration, and ensure ethical practices in global supply chains. The research employs a qualitative approach, utilizing semi-structured interviews with industry stakeholders to gather insights into current practices, challenges, and strategies in SRM. Findings highlight transparency as pivotal for sharing critical information such as sales forecasts, inventory levels, and pricing strategies, enabling suppliers to align operations with market demands effectively. However, achieving transparency faces hurdles including data privacy concerns and competitive sensitivities, necessitating robust data security measures and clear communication protocols. Accountability mechanisms, such as formal agreements and governance frameworks, emerge as essential for mitigating risks, resolving disputes, and ensuring compliance with ethical and regulatory standards across diverse contexts. Technological innovations like AI, blockchain, and big data analytics are transforming SRM by enhancing supply chain visibility, operational efficiency, and decision-making capabilities. Cultural factors and regulatory compliance also significantly influence SRM practices, shaping communication styles, relationship dynamics, and legal considerations. Emerging trends such as sustainable sourcing practices and collaborative partnerships are reshaping SRM, emphasizing sustainability and responsible business practices. This study contributes to the understanding of effective SRM strategies, offering insights and recommendations for stakeholders navigating the complexities of e-commerce supply chains.

This qualitative study explores the dynamics of Supplier Relationship Management (SRM) and its impact on innovation within the e-commerce sector. Through in-depth interviews and documentary analysis of three case study firms known for their innovative practices, the study examines how collaborative SRM practices influence innovation outcomes, organizational resilience, and competitive advantage in dynamic market environments. Key themes include the pivotal role of trust, transparency, and joint problem-solving in fostering effective SRM relationships, enabling knowledge sharing and co-development of innovative products and services. Innovation outcomes observed encompass product innovation, process improvements, and technological advancements facilitated by close collaboration between e-commerce firms and their suppliers. Challenges such as managing supplier diversity, navigating regulatory complexities, and mitigating geopolitical risks highlight the complexities and strategic imperatives of SRM implementation in global supply chains. The study also emphasizes the transformative role of digital technologies, including real-time data exchange, predictive analytics, and agile supply chain management, in enhancing SRM effectiveness and innovation capabilities. Strategic alignment with organizational goals and market strategies further enhances the impact of SRM, enabling firms to prioritize innovation initiatives, allocate resources effectively, and sustain growth amidst economic uncertainties. The findings contribute to theoretical understanding and practical insights into SRM strategies that promote innovation excellence and competitive positioning within e-commerce. The implications for practice underscore the importance of fostering collaborative supplier relationships, investing in digital transformation, and adopting proactive strategies to manage risks and regulatory compliance.

This study investigates the critical factors of trust, commitment, and adaptation within supplier relationship management (SRM) in the context of e-commerce. Through qualitative research methods, including semi-structured interviews and documentary analysis, the study explores how these factors influence relationship dynamics and organizational outcomes in digital business environments. Trust is examined as foundational to effective SRM, encompassing integrity, reliability, and shared values between buyers and suppliers. Commitment is analyzed in terms of long-term orientation, resource allocation, and relationship-specific investments aimed at mutual growth and sustainability. Adaptation emerges as essential for navigating the dynamic e-commerce landscape, encompassing proactive strategies, flexibility, and innovation to respond to market changes and technological advancements. The findings highlight the interplay and mutual reinforcement among trust, commitment, and adaptation, contributing synergistically to relationship resilience and organizational performance. However, challenges such as information asymmetry, cybersecurity risks, and organizational inertia are identified as barriers to effective SRM. Practical implications include strategies for enhancing trust, fostering commitment, and cultivating adaptive capabilities through continuous learning, collaborative innovation, and technology integration. By integrating these insights, businesses can strengthen supplier relationships, drive sustainable growth, and achieve competitive advantage in the digital economy.

This qualitative study explores the pivotal roles of trust and communication in supplier relationship management (SRM) within the e-commerce sector. Drawing on interviews and thematic analysis, the study examines how trust, comprising dimensions of competence, benevolence, integrity, and reliability, underpins collaborative partnerships and operational resilience between e-commerce platforms and suppliers. Effective communication strategies, including proactive engagement, transparent feedback mechanisms, and real-time updates via digital platforms, are identified as critical enablers for enhancing information exchange and fostering mutual understanding in SRM. Challenges such as cultural differences, technological complexities, and regulatory compliance requirements are also discussed, highlighting the need for strategic management and investment to mitigate risks and maintain trust in supplier engagements. Relational competencies such as empathy, active listening, conflict resolution, and trust-building skills are recognized as essential for navigating interpersonal dynamics and fostering collaborative relationships in e-commerce SRM. Strategically, integrating these findings into comprehensive SRM frameworks is emphasized to cultivate a positive organizational culture characterized by openness, ethical integrity, collaboration, and adaptability. This approach aims to enhance supplier relationships, drive innovation, and achieve sustainable growth in a competitive marketplace.

This qualitative study explores the intricacies of building sustainable supplier relationships in the e-commerce sector, focusing on best practices and strategic approaches. Through in-depth interviews with procurement managers, supply chain experts, and supplier representatives, the research identifies four critical themes: trust, technology integration, ethical practices, and performance measurement. Trust is found to be the foundation of effective supplier relationships, fostering open communication and collaboration, which are essential for addressing challenges and co-creating solutions. The integration of digital technologies such as supply chain management software, blockchain, and the Internet of Things significantly enhances transparency, decision-making, and operational efficiency, providing a competitive edge. Ethical practices, including adherence to fair labor standards and environmental sustainability, are increasingly crucial as consumer and regulatory expectations evolve, necessitating alignment between e-commerce companies and their suppliers. Performance measurement and continuous improvement are vital for maintaining quality and efficiency, with clear metrics and regular evaluations driving constructive feedback and optimization of supply chain processes. The study underscores the interdependence of these elements in fostering resilient and adaptable supplier relationships. The findings offer practical guidance for e-commerce businesses and suppliers, emphasizing the need for a holistic approach to supplier management that balances trust, technology, ethics, and performance. This approach not only enhances operational effectiveness but also ensures the long-term sustainability of supplier relationships in the dynamic e-commerce landscape. The research contributes to the theoretical understanding of supplier relationship management, providing a comprehensive framework for future studies and practical applications in the e-commerce industry.

Few studies have examined the pros and cons of integrated TB and HIV service delivery in public healthcare facilities, and even fewer have proposed conceptual models for improved integration. This study intends to fill that vacuum by outlining the development of a facility-based paradigm for integrating TB, HIV and patients services. The design of the proposed model were in stages that involved the evaluation of existing TB-HIV integration model and synthesis of both quantitative and qualitative data from the study sites which were selected public healthcare facilities at both rural and peri-urban settings in Oliver Reginald (O.R) Tambo District Municipality in Eastern Cape, South Africa. Secondary data on 2009-2013 TB-HIV clinical outcomes were obtained from multiple sources for quantitative analysis. Qualitative data involved focus group discussions among patient and heath care staff, which was thematically analysed. The development of a possibly better model and validation of this model show that the district's health system was reinforced by the model's guiding principles, which placed a strong emphasis on inputs, processes, outcomes, and integration effects.The model is adaptable to different healthcare delivery systems but will require support from healthcare stakeholders and professionals to be successful.

This study investigates the critical role of Supplier Relationship Management (SRM) in enhancing the e-commerce user experience. In an increasingly competitive digital marketplace, effective SRM practices are essential for optimizing supply chain operations and meeting customer expectations. The research employs a qualitative approach, combining semi-structured interviews with industry stakeholders, extensive literature review, and case studies to explore various dimensions of SRM. Key findings reveal that strategic supplier selection criteria, including quality, cost efficiency, reliability, innovation, and sustainability, are pivotal in ensuring a robust and adaptable supply chain. Effective communication practices, such as transparency, frequent updates, and digital tools, foster strong supplier relationships and enable timely issue resolution. Performance management strategies, centered on KPI monitoring and continuous improvement, support operational excellence and customer satisfaction. Risk management practices, including diversification, contingency planning, and advanced analytics, are crucial for mitigating disruptions and ensuring supply chain resilience, as highlighted by the challenges posed during the COVID-19 pandemic. Technological integration with blockchain, AI, IoT, data analytics, and automation enhances efficiency, transparency, and decision-making capabilities in SRM. Furthermore, the study underscores the evolving integration of sustainability and ethical sourcing into SRM strategies, reflecting broader corporate responsibility goals. Ultimately, this research contributes to understanding how effective SRM strategies drive competitive advantage in e-commerce by enhancing supply chain reliability, responsiveness, and customer-centricity. As e-commerce continues to evolve, adapting and innovating SRM practices will be vital for companies aiming to sustain growth and meet the dynamic demands of global markets.

This study explores the influence of cultural differences on Supplier Relationship Management (SRM) within global e-commerce, examining communication styles, trust-building, negotiation strategies, and strategic alignment across diverse cultural contexts. Through qualitative research including interviews with e-commerce professionals, the study identifies how cultural factors shape SRM practices and outcomes, highlighting the importance of cultural sensitivity and adaptive strategies in fostering effective supplier relationships. Findings underscore the significance of communication preferences, trust norms, and strategic orientations in navigating cultural complexities to enhance operational efficiency and mitigate risks in global markets. Practical implications suggest integrating cultural dimensions into SRM frameworks, prioritizing cultural competence development, and leveraging cultural diversity for innovation and collaboration. Future research directions include exploring digitalization's impact on cross-cultural SRM and longitudinal studies on evolving cultural dynamics in global business. By advancing understanding in this area, e-commerce firms can enhance resilience, maintain competitive advantage, and achieve sustainable growth in the global marketplace.

This qualitative research explores Supplier Relationship Management (SRM) practices within the e-commerce fashion industry, aiming to uncover key strategies and their impacts. Through semi-structured interviews with supply chain managers, procurement officers, and supplier representatives, critical themes emerged: communication, trust, risk management, sustainability, and digital technologies. Effective communication, characterized by transparency and regular updates, emerged as pivotal for aligning expectations and resolving issues promptly. Trust-building practices, including fair dealings and formal agreements, were essential in fostering long-term partnerships, reducing transaction costs, and enhancing collaboration. Robust risk management strategies, such as supplier diversification and contingency planning, were identified as crucial for mitigating disruptions and ensuring supply chain resilience. Sustainability was highlighted as a strategic imperative, driven by ethical sourcing and environmental standards, supported by technologies like blockchain for transparency. The transformative role of digital technologies—supply chain management software, blockchain, IoT, and data analytics—was evident in enhancing visibility and decision-making across global supply chains. Viewing suppliers as strategic partners, rather than mere vendors, promoted collaborative innovation and mutual growth. Despite challenges like cultural differences and regulatory complexities, opportunities exist to enhance SRM through integrated best practices. By prioritizing effective communication, trust-building, risk management, sustainability, and digital innovation, companies can strengthen supplier relationships, optimize supply chain performance, and achieve competitive advantage in the e-commerce fashion sector.

There is a large potential for cost-effective solutions to reduce greenhouse gas emissions and to improve the sustainability of the transport sector that is yet unexploited, in particular in the urban context. Considering the cost-effectiveness and the potential for co-benefits, it is hard to understand why energy gains and mitigation action in the transport sector is still lagging behind the potential. Particularly interesting is the fact that there is substantial difference among countries with relatively similar economic performances, such as the OECD countries in the development of their transport CO2 emission over the past thirty years despite the fact that these countries had relatively similar access to efficient technologies and vehicles. This study aims to apply some well established political science theories on the particular example of climate change mitigation in the transport sector in order to identify some of the factors that could help explain the variations in success of policies and strategies in this sector. The analysis suggests that institutional arrangements that contribute to consensus building in the political process provide a high level of political and policy stability which is vital to long-term changes in energy end-use sectors that rely on long-term investments. However, there is no direct correlation between institutional structures, e.g. corporatism and success in reducing greenhouse gas emissions in the transport sector. Environmental objectives need to be built into the consensus-based policy structure before actual policy progress can be observed. This usually takes longer in consensus democracies than in politically more agile majoritarian policy environments, but the policy stability that builds on corporatist institutional structures is likely to experience changes over a longer-term, in this case to a shift towards low-carbon transport that endures.

Indoor crop cultivation systems such as vertical farms or plant factories necessitate artificial lighting. Light spectral quality can affect plant growth and metabolism and, consequently, the amount of biomass produced and the value of the produce. Conflicting results on the effects of light spectrum in different plant species and cultivars make it critical to implement a singular lighting solution. In this study we explored the response of green and red leaf lettuce cultivars (’Aquino’, CVg, or ‘Barlach’, CVr, respectively) to long-term blue-enriched light application (WB). Plants were grown for 30 days in a growth chamber with optimal environmental condi-tions (temperature: 20°C, relative humidity: 60%, ambient CO2, Photon Flux Density (PFD) of 260 µmol m-2 s-1 over an 18-h photoperiod). At 15 days after sowing (DAS) white spectrum LEDs (WW) were compared to WB (λPeak = 423 nm) maintaining the same PFD of 260 µmol m-2 s-1. At 30 DAS, both lettuce cultivars resulted adapted to the blue light variant, though the adaptive re-sponse was specific to the variety. Rosette weight, light use efficiency and maximum operating efficiency of PSII photochemistry in the light, Fv/Fm’, were comparable between the two light treatments. Significant light quality effect was detected on stomatal density and conductance (20% and 17% increase under WB, respectively, in CVg) and, on the modified anthocyanin re-flectance index (mARI) (40% increase under WB, in CVr). Net photosynthesis response was gen-erally stronger in CVg compared to CVr; e.g. net photosynthetic rate, Pn, at 1000 µmol m-2 s-1 PPFD increased from WW to WB by 23% in CVg, compared to 18% in CVr. Results obtained suggest the occurrence of distinct physiological adaptive strategies in green and red pigmented lettuce cultivars to adapt to the higher proportion of blue light environment.

Eco-labels are an instrument for enabling informed food choices and supporting a demand-sided change towards a more and urgently needed sustainable food system. Lately, novel eco-labels that depict a product’s environmental life-cycle assessment on a multi-level scale are being tested across Europe’s retailers. This study elicits consumers preferences and willingness to pay (WTP) for a multi-level eco-label. A Discrete Choice Experiment was conducted in Austria. Individual partworth utilities were estimated by means of Hierarchical Bayes. Results show higher WTP for a positive evaluated multi-level label, revealing consumers’ perceived benefits of colorful multi-level labels over binary black-and-white designs. Even a negative evaluated multi-level label showed higher WTP compared to no label, pointing towards limited effectiveness of eco-labels. Respondents’ preferences for eco-labels were independent from their subjective eco-label knowledge, health consciousness, and environmental concern. The attribute “protein source” was most important, and preferences for animal-based protein source (beef) was strongly correlated with consumers’ meat attachment, implying that a shift towards more sustainable protein sources is challenging and sustainability labels have only a small impact on the meat product choice of average consumers.

Land degradation is a serious impediment to improving rural livelihoods in Eastern Africa. This paper identifies major land degradation patterns and causes, and analyzes the determinants of sustainable land management (SLM) in three countries (Ethiopia, Malawi and Tanzania). The results show that land degradation hotspots cover about 51%, 41%, 23% and 23% of the terrestrial areas in Tanzania, Malawi and Ethiopia respectively. The analysis of nationally representative household surveys shows that the key drivers of SLM in these countries are biophysical, demographic, regional and socio-economic determinants. Secure land tenure, access to extension services and market access are some of the determinants incentivizing SLM adoption. The implications of this study are that policies and strategies that facilities secure land tenure and access to SLM information are likely to incentivize investments in SLM. Local institutions providing credit services, inputs such as seed and fertilizers, and extension services must also not be ignored in the development policies.

With the evolution of toxic chemicals continuing to progress, developing methods for the destruction of chemical warfare agents (CWAs) has become an increasingly important research topic. Metal-organic frameworks (MOFs) are a class of porous crystalline solids that have sparked interest in this area. Due to their exceptional porosities and large surface areas, MOFs possess superior adsorption, reactivity, and catalytic abilities, making them structurally ideal candidates for the capture and decomposition of target species. Additionally, the tunable networks of MOFs allow their chemical functionalities to be customized for various applications and operating conditions, making them practicable in personal protective equipment and adjustable to dynamic environments. This paper reviews experimental and computational studies on CWA removal by MOFs, with a special emphasis on nerve agent (GB, GD, and VX) removal via hydrolysis and sulfur mustard (HD) removal via selective photooxidation. With extraordinary structural stability and reusability, zirconium-based MOFs are the most promising materials for hydrolytic and photooxidative degradation of CWAs and are thus the primary focus of this work. First-principles approximations of the intrinsic catalytic reaction mechanisms towards different agents in Zr-MOFs are summarized, and developments in the structure-property relationships governing Zr-MOF design rules for efficient degradation in the aqueous and solid phases are discussed. We also examine recent progress in tuning and functionalizing MOFs to promote practical CWA removal under realistic battlefield conditions.

The consistently positive Australian economic environment and stable population increase have led to a higher demand for new houses in recent years. Prefabrication is a promising method to help alleviate the issues related to housing shortage and affordability due to reduced material wastage, construction delays due to weather conditions, unexpected costs, shortage in labour and onsite risks. With the advancements in automation and manufacturing methods such as Design for Manufacturing and Assembly (DfMA), the quality and precision of prefabricated materials is tightly controlled, and the fabrication and assembly period are reduced. However, the full potential of prefabricated construction is yet to be realised in part due to most of developments being focused on its superstructure. A review of the current available options suitable for houses is necessary to understand the present state of the residential footing industry, which will help evaluate the necessary innovations for the growth of the Australian construction industry considering the local reactive soil conditions. This paper presents a summary of existing footing systems and potential prefabricated footing solutions for low-rise residential structures with one storey to two storeys. This paper also reviews the benefits and challenges of designing, manufacturing, transporting, handling and installing of prefabricated footings on site, which have great influence on the acceptance of these innovative footing systems.

This qualitative study explores supplier collaboration in e-commerce product development, examining motivations, challenges, strategies, outcomes, and ethical considerations. Through in-depth interviews with stakeholders from diverse e-commerce sectors, the study identifies key themes shaping collaboration dynamics. Motivations include innovation, operational efficiency, and strategic partnerships, driving companies to integrate supplier expertise early in product development. Challenges such as global supply chain complexities, goal misalignment, and communication barriers underscore the need for robust governance and cultural sensitivity. Strategies for success include technology adoption, supplier development programs, and collaborative decision-making, enhancing supply chain visibility and mutual benefits. Effective collaboration yields improved product quality, cost efficiencies, and enhanced customer satisfaction, supporting competitive advantage. Ethical sourcing practices and sustainability initiatives are crucial for maintaining trust and regulatory compliance. Cultural and organizational factors, including leadership support and change management, significantly influence collaboration outcomes. The study concludes with implications for theory and practice, emphasizing the role of innovative strategies and continuous improvement in supplier relationships. Future research could explore digital transformation, sustainability trends, and technological impacts on supplier collaboration in e-commerce. Practical applications include optimizing supply chain strategies to navigate complexities and capitalize on market opportunities.

This qualitative research explores the impact of Supplier Relationship Management (SRM) on e-commerce brand reputation, focusing on the strategic imperatives, operational challenges, and economic implications within digital supply chains. Trust emerges as a foundational element in effective SRM practices, facilitating consistent product quality, timely delivery, and consumer trust, thereby enhancing brand credibility and loyalty. Strategic alignment of SRM with organizational goals enables e-commerce brands to leverage supplier capabilities for mutual growth and innovation. Operational challenges such as technological constraints and logistical complexities underscore the importance of digital integration and proactive risk management strategies to optimize SRM effectiveness. Digital technologies, including AI and blockchain, play a transformative role in enhancing transparency, efficiency, and resilience in SRM strategies, enabling e-commerce firms to mitigate risks and capitalize on market opportunities. Emotional intelligence (EI) competencies among supply chain professionals facilitate effective communication, conflict resolution, and sustainable supplier relationships that bolster brand reputation resilience. Economically, effective SRM practices yield cost efficiencies, improved financial performance, and resilience against supply chain disruptions, supporting sustainable growth in competitive digital markets. This study contributes valuable insights for practitioners and scholars aiming to enhance SRM strategies, optimize supplier relationships, and strengthen brand reputation management in e-commerce. By prioritizing trust, strategic alignment, digital innovation, EI competencies, and proactive risk management, e-commerce brands can navigate complexities, capitalize on opportunities, and foster positive brand reputations in the evolving landscape of digital commerce.

This qualitative research explores Supplier Relationship Management (SRM) within the context of subscription-based e-commerce models. Through in-depth interviews and thematic analysis, the study investigates key elements such as trust, collaboration, technology integration, sustainability, risk management, cultural alignment, innovation, cost management, globalization, supplier selection, and performance measurement. Findings reveal that trust is foundational in fostering reliable interactions and open communication between e-commerce businesses and suppliers. Collaboration emerges as crucial for innovation and operational efficiency, facilitating co-development and shared risk management. Technology integration, including AI and blockchain, enhances supply chain visibility and decision-making capabilities. Sustainability considerations drive businesses to engage with suppliers adhering to environmental standards, enhancing brand reputation and consumer loyalty. Effective risk management strategies mitigate disruptions and ensure supply chain resilience. Cultural alignment fosters harmonious partnerships and mutual understanding across diverse global markets. Innovation through supplier collaboration drives product development and market responsiveness. Cost management practices optimize operational efficiency and strategic supplier relationships. Globalization necessitates adaptive strategies to manage diverse cultural and regulatory landscapes. Strategic supplier selection and continuous performance measurement drive ongoing improvement and alignment with business objectives. This study contributes empirical insights and practical implications for enhancing SRM in subscription-based e-commerce, informing strategies to navigate challenges and leverage opportunities in a competitive marketplace.

This qualitative study explores the pivotal role of Supplier Relationship Management (SRM) in enhancing resilience within e-commerce supply chains. In an era marked by rapid digital transformation and global interconnectedness, the resilience of supply chains has become a strategic imperative for organizations striving to maintain operational efficiency and meet customer expectations. Through semi-structured interviews with supply chain managers, procurement officers, and strategic sourcing specialists across diverse industries, this research investigates the strategies, challenges, and outcomes associated with SRM practices. Findings reveal that effective communication and collaboration are fundamental to successful SRM, fostering trust, transparency, and responsiveness in supplier relationships. Strategic risk management through proactive identification and mitigation strategies enables organizations to navigate uncertainties such as economic fluctuations and geopolitical tensions. SRM implementation yields significant organizational benefits, including improved supply chain efficiencies, enhanced product quality, and increased customer satisfaction. However, challenges such as technological complexities, cultural differences among global suppliers, and regulatory compliance issues underscore the need for adaptive strategies and digital investments. The integration of digital technologies such as AI and blockchain enhances SRM effectiveness by enabling real-time data exchange, predictive insights, and decision-making capabilities. Ultimately, SRM emerges as a cornerstone of sustainable growth and competitive advantage in e-commerce, empowering organizations to optimize supply chain performance and resilience amidst dynamic market conditions.

This qualitative study explores Supplier Relationship Management (SRM) in the context of digital transformation within e-commerce businesses, focusing on the implications of emerging digital technologies. Through semi-structured interviews and documentary analysis, the study examines how organizations leverage technologies like artificial intelligence (AI), blockchain, and Internet of Things (IoT) to enhance SRM practices. Findings reveal that digitalization enables improved operational efficiencies, real-time data analytics, and expanded supplier networks through platforms such as Amazon Business and Alibaba. Strategic shifts are noted towards collaborative supplier relationships, emphasizing joint innovation, technology co-investment, and shared risk management strategies. However, the implementation of digital SRM strategies presents challenges, including data privacy concerns, integration complexities, cybersecurity threats, and regulatory compliance issues. Organizations must navigate these challenges by developing robust governance frameworks and cybersecurity protocols to protect sensitive information and ensure regulatory adherence. Key performance indicators (KPIs) such as supplier performance, cost savings, innovation impact, risk management effectiveness, and sustainability integration are critical for evaluating the success of digital SRM initiatives. Strategically, businesses are advised to prioritize leadership commitment, cross-functional collaboration, and continuous learning to optimize digital SRM practices effectively. Future research should explore emerging trends in digital SRM, investigate technological impacts on supplier dynamics and organizational performance, and examine ethical considerations in digitalization. By integrating these insights into strategic decision-making, businesses can enhance supplier relationships, mitigate operational risks, and achieve sustainable growth in the global marketplace.

This qualitative research investigates the influence of Corporate Social Responsibility (CSR) on Supplier Relationship Management (SRM) within the e-commerce sector. Through semi-structured interviews and secondary data analysis, the study explores motivations, challenges, impacts, and strategic outcomes of integrating CSR practices into supplier relationships. Motivations for adopting CSR include ethical considerations, regulatory compliance, and meeting stakeholder expectations, reflecting a strategic alignment with corporate values and societal demands. Challenges such as resource constraints, regulatory complexities, and cultural differences highlight operational hurdles and strategic considerations e-commerce firms face in implementing CSR initiatives effectively. The study reveals that CSR enhances trust, collaboration, and risk mitigation within e-commerce supply chains through transparent communication, shared values, and ethical practices. Strategically, CSR contributes to enhanced brand equity, competitive advantage, and long-term value creation by differentiating firms in competitive markets and attracting socially conscious consumers and investors. However, economic trade-offs, stakeholder divergence, and operational complexities require firms to adopt adaptive strategies that balance short-term financial goals with long-term sustainability objectives. The findings suggest avenues for future research exploring longitudinal impacts of CSR on supplier relationships, cross-sectoral comparisons, and technological advancements in CSR-driven SRM practices. Practically, e-commerce firms should prioritize strategic alignment of CSR initiatives with core business objectives, engage stakeholders in CSR strategy development, and embrace continuous improvement to foster ethical conduct, stakeholder trust, and sustainable business practices.

Supplier diversity has emerged as a critical strategy for enhancing e-commerce operations by fostering inclusivity and innovation within supply chains. This qualitative research explores the role of supplier diversity in e-commerce, examining its impact on organizational strategies, competitive advantage, and stakeholder perceptions. Through semi-structured interviews with procurement managers, diversity officers, and supply chain executives from diverse e-commerce platforms, this study identifies key themes related to the benefits, challenges, and strategic implications of supplier diversity initiatives. Findings indicate that supplier diversity significantly enhances innovation and creativity within supply chains by integrating diverse perspectives and expertise. This diversity not only enriches product development and market responsiveness but also strengthens corporate reputation and brand equity, demonstrating organizational commitment to ethical business practices and community engagement. However, the study reveals persistent challenges, including financial barriers, systemic biases, and scalability issues, which hinder the effective implementation and scalability of supplier diversity programs. Effective supplier relationship management emerges as critical for maximizing the benefits of supplier diversity, fostering trust, collaboration, and long-term partnerships with diverse suppliers. Looking forward, the future of supplier diversity lies in digital transformation, globalization of supplier networks, and integration of sustainable sourcing practices to enhance transparency, efficiency, and resilience in supply chain operations. This study contributes to the growing literature on supplier diversity by providing empirical insights and practical implications for organizations aiming to leverage diversity as a strategic asset in e-commerce and global supply chain management.

This qualitative research explores Supplier Relationship Management (SRM) as a pivotal driver of sustainable practices in the e-commerce sector. Through in-depth interviews with industry experts, practitioners, and scholars, the study investigates how SRM strategies integrate sustainability criteria into procurement processes, mitigate environmental and ethical risks, and enhance operational efficiencies. Key findings highlight the strategic importance of collaborative relationships with suppliers, technological innovations such as blockchain and data analytics in promoting transparency and accountability, and the influence of consumer preferences for sustainable products on market dynamics. Despite challenges such as regulatory complexities and global supply chain dynamics, businesses are increasingly adopting sustainable SRM practices to strengthen brand reputation, achieve cost savings, and align with evolving sustainability standards. The study underscores the interconnected nature of sustainability within e-commerce operations and calls for continued research to advance technological solutions, refine regulatory frameworks, and foster industry-wide collaboration. By embracing sustainability as a strategic imperative, businesses can navigate complexities, drive innovation, and contribute to a more resilient and sustainable future for the e-commerce industry.

This study explores the strategic importance of leveraging supplier relationships for competitive advantage in the e-commerce industry. Strong supplier relationships are crucial for enhancing operational efficiencies, cost management, quality assurance, innovation, sustainability, and overall supply chain resilience. Through collaborative partnerships, e-commerce companies can streamline logistics, reduce costs, ensure consistent product quality, and foster innovation through joint development initiatives. Ethical sourcing and sustainable practices play a pivotal role in supplier relationship management (SRM), aligning with consumer expectations and enhancing brand reputation. Advanced technologies such as AI, blockchain, and IoT further transform SRM practices by improving transparency, efficiency, and decision-making capabilities across the supply chain. The study also discusses challenges in managing global supplier relationships, emphasizing the importance of effective communication, cultural sensitivity, and strategic risk management. By addressing these challenges and nurturing trust-based relationships with suppliers, e-commerce firms can navigate market complexities and achieve sustainable growth. This research provides insights for e-commerce companies seeking to optimize their supplier relationships and maintain competitive advantage in a dynamic market environment.

This qualitative study investigates the management of supplier risks in e-commerce through relationship management strategies, focusing on trust-building, communication practices, digital technology integration, risk assessment methodologies, challenges, innovation initiatives, and ethical considerations. The research aims to provide nuanced insights into how e-commerce companies navigate the complexities of global supply chains to mitigate operational, financial, and reputational risks associated with supplier relationships. Through semi-structured interviews with 20 key stakeholders in the e-commerce sector, data were collected and analyzed using thematic analysis. The findings underscored the foundational role of trust in establishing resilient supplier relationships, facilitated by transparent communication, consistent performance evaluation, and mutual respect for contractual obligations. Effective communication practices, supported by digital platforms and technologies such as AI, blockchain, IoT, and cloud computing, enhanced operational transparency and decision-making capabilities across supply chains. The study identified diverse approaches to risk assessment, from qualitative evaluations to quantitative models utilizing predictive analytics and scenario planning. However, participants highlighted challenges including geopolitical uncertainties, trade disruptions, regulatory changes, and cultural barriers, necessitating adaptive strategies and diversified sourcing options. Innovation initiatives such as joint product development and technology adoption were crucial in enhancing supply chain agility and competitive advantage. Ethical considerations emerged as a critical aspect, influencing supplier selection criteria, CSR initiatives, environmental sustainability practices, and labor standards compliance. Integrating ethical guidelines into supplier contracts reinforced corporate values and enhanced brand reputation. Overall, this study contributes practical implications for e-commerce practitioners seeking to enhance supply chain resilience, mitigate supplier risks, and sustain competitive advantage in a dynamic global marketplace.

This research investigates the pivotal role of Supplier Relationship Management (SRM) in enhancing e-commerce scalability. SRM practices are essential for optimizing supply chain operations and fostering strategic partnerships with suppliers, crucial in the dynamic and competitive e-commerce landscape. Through a comprehensive analysis of case studies, expert interviews, and secondary data, the study examines how leading e-commerce companies such as Amazon and Alibaba implement effective SRM strategies to achieve scalability. Key findings reveal that strategic supplier selection based on capabilities and alignment with business goals, coupled with continuous evaluation and development programs, ensures consistent supply chain performance and customer satisfaction. Technological advancements, including data analytics, artificial intelligence, and blockchain, play a transformative role in modern SRM by enhancing transparency, efficiency, and decision-making capabilities. These technologies enable real-time monitoring, automated processes, and risk mitigation strategies that bolster supply chain resilience and operational efficiency. Best practices in SRM, such as clear performance metrics, a culture of continuous improvement, and ethical sourcing policies, are critical for driving supplier accountability, innovation, and sustainability. Moreover, sustainability emerges as a growing priority in SRM, with businesses integrating environmental and social considerations into supplier management strategies to meet regulatory requirements and stakeholder expectations. Theoretical frameworks like the Resource-Based View and Transaction Cost Economics provide insights into the strategic implications of SRM, emphasizing its role in fostering competitive advantage and long-term business success. As e-commerce continues to evolve, businesses must adapt and innovate in their SRM approaches to navigate global supply chain complexities effectively. By prioritizing effective SRM practices, leveraging advanced technologies, and embracing sustainability, businesses can enhance their scalability, resilience, and competitiveness in the digital economy.

Effective management of supplier relationships is crucial for e-commerce companies to navigate complex supply chain dynamics and mitigate risks associated with supplier disputes. This qualitative study explores the strategies and challenges involved in resolving supplier disputes through relationship management in the context of e-commerce. Through semi-structured interviews with supply chain managers, procurement officers, and executives from diverse e-commerce firms, the study investigates key themes including communication strategies, trust-building initiatives, negotiation dynamics, technological integration, organizational culture, and global supply chain alignment. Findings reveal that clear and transparent communication plays a foundational role in preventing misunderstandings and fostering collaboration with suppliers. Trust-building initiatives, such as consistency in commitments and transparency in business dealings, are essential for cultivating resilient supplier relationships. Negotiation strategies emphasizing principled negotiation and collaborative problem-solving facilitate the resolution of disputes while preserving long-term partnerships. Technological integration through data analytics, automation, and digital platforms enhances operational efficiency and decision-making capabilities in managing supplier relationships. Organizational culture characterized by collaboration, innovation, and leadership commitment to strategic alignment with global supply chains promotes resilience and responsiveness to market dynamics. Challenges including power dynamics, operational constraints, and cultural differences underscore the importance of proactive risk management and cultural sensitivity in supplier relationship management. This study contributes actionable insights for practitioners to enhance supplier relationship management practices, navigate disputes effectively, and foster sustainable competitive advantage in e-commerce. By integrating these findings into strategic planning, e-commerce firms can strengthen supplier partnerships, optimize supply chain performance, and mitigate risks in a dynamic business environment.

This qualitative research explores the transformative role of Artificial Intelligence (AI) in Supplier Relationship Management (SRM) within the e-commerce sector. SRM is critical for e-commerce platforms to maintain efficient supply chains, optimize supplier interactions, and ensure competitive advantage in a dynamic marketplace. AI technologies offer advanced capabilities such as predictive analytics, machine learning algorithms, and natural language processing, which revolutionize traditional SRM practices by enhancing decision-making accuracy, mitigating supply chain risks, and fostering personalized supplier relationships. Through semi-structured interviews with 20 e-commerce professionals and industry experts, this study investigates AI's impact on supplier selection, operational efficiencies, and strategic supplier relationships. Findings highlight AI's ability to streamline supplier evaluation processes, improve demand forecasting accuracy, and optimize inventory management strategies. AI also facilitates personalized supplier engagement through sentiment analysis and real-time insights, promoting collaboration and trust. Ethical considerations, including algorithmic bias and data privacy, emerge as significant concerns in AI adoption for SRM. Addressing these challenges is crucial to maintaining stakeholder trust and ensuring responsible AI deployment. Furthermore, technological integration barriers and organizational readiness are identified as critical factors influencing successful AI implementation. Looking forward, the study underscores the potential of AI to drive innovation and competitiveness in e-commerce SRM, emphasizing the importance of ethical AI practices, technological infrastructure investments, and organizational preparedness for sustainable growth.

This qualitative research explores the integration of digital technologies to enhance supplier engagement in e-commerce, examining the transformative impact of AI, blockchain, and IoT on supplier relationship management (SRM). Through semi-structured interviews and documentary analysis with 15 industry experts, the study reveals that digital technologies enable organizations to optimize supply chain operations, improve transparency, and foster collaborative partnerships with suppliers. Strategic initiatives such as co-development projects and joint innovation efforts are pivotal in accelerating product development cycles and enhancing market competitiveness. Emotional intelligence (EI) emerges as critical in cultivating trust, empathy, and effective communication, underscoring the human dimension of supplier relationships amidst technological advancements. Challenges identified include technological complexity, data privacy concerns, and resistance to change, necessitating robust cybersecurity measures and proactive compliance strategies. Economically, organizations benefit from significant cost savings, improved efficiency, and enhanced profitability through digital transformation initiatives in SRM. By leveraging digital platforms and data-driven insights, organizations can optimize procurement processes, streamline operations, and mitigate risks to achieve sustainable growth and resilience.

Supplier Relationship Management (SRM) plays a pivotal role in enhancing delivery performance within the e-commerce sector, yet understanding its nuanced impacts remains crucial for optimizing operational efficiencies and customer satisfaction. This qualitative research explores the intricate dynamics of SRM in e-commerce, focusing on strategic alignment, technological integration, trust, collaboration, and risk management as key determinants of delivery reliability. Through in-depth interviews and thematic analysis, the study reveals that strategic alignment of supplier capabilities with firm objectives is fundamental for maintaining a responsive and synchronized supply chain. Technological integration, including AI-driven analytics and blockchain applications, emerges as critical for real-time monitoring and adaptive decision-making, thereby improving delivery accuracy and efficiency. Trust and collaboration are identified as essential pillars for building resilient supplier relationships, fostering transparent communication and joint problem-solving. Effective risk management practices, such as supplier diversification and contingency planning, mitigate disruptions and ensure consistent delivery performance. Despite these benefits, challenges such as technological adoption barriers, cultural differences, communication complexities, resource constraints, and supplier reliability issues persist, necessitating strategic interventions. Recommendations include investing in advanced SRM technologies, promoting cultural understanding, enhancing communication protocols, allocating adequate resources, and fostering collaborative initiatives with suppliers. These strategies aim to overcome challenges and optimize SRM practices, ultimately enhancing delivery performance and competitiveness in the e-commerce landscape.

This qualitative study explores collaborative supplier relationships within the context of e-commerce, aiming to uncover the dynamics, challenges, strategies, impacts, and future trends shaping these partnerships. Through thematic analysis of interviews with e-commerce platform managers, supplier representatives, and industry experts, the study identifies three primary types of relationships: transactional, relational, and strategic. Critical factors influencing these relationships include trust, effective communication, technological integration, and regulatory compliance. Challenges such as information asymmetry, cultural differences, logistical complexities, and competitive pressures are examined, alongside strategies for enhancing collaboration, including clear communication protocols, performance evaluations, and technological advancements. The findings highlight the significant impact of collaborative supplier relationships on business performance, including cost efficiencies, supply chain resilience, innovation capacity, customer satisfaction, and market competitiveness. Looking forward, trends in digital transformation, sustainability initiatives, global supply chain networks, resilience-building strategies, and industry collaboration are discussed as shaping the future landscape of e-commerce partnerships. Embracing these trends presents opportunities for organizations to innovate, adapt, and sustain growth in the competitive digital marketplace.

Supplier Relationship Management (SRM) tools play a crucial role in enhancing efficiency and competitiveness within e-commerce supply chains. This qualitative research explores the effectiveness of SRM tools in optimizing procurement processes, mitigating risks, and fostering collaborative partnerships with suppliers. The study employs semi-structured interviews with key stakeholders in diverse e-commerce sectors to gather insights into the implementation and outcomes of SRM tools. Findings reveal that technological advancements, including AI, blockchain, and data analytics, facilitate real-time communication, decision-making, and supply chain visibility, thereby enabling organizations to achieve cost savings and operational efficiencies. Enhanced supplier relationships through SRM tools contribute to collaborative innovation, faster product development cycles, and improved customer satisfaction. However, challenges such as technological complexity, regulatory compliance, and supplier resistance necessitate strategic management and investment in cybersecurity and compliance frameworks. The research underscores the importance of executive sponsorship, stakeholder engagement, and continuous improvement in driving successful SRM implementations.

This qualitative research explores Supplier Relationship Management (SRM) strategies within the context of e-commerce customization, aiming to understand how businesses effectively manage relationships with suppliers to meet personalized consumer demands. Through semi-structured interviews with industry professionals, key themes such as trust, communication, technological integration, strategic alignment, sustainability, and collaboration emerged as critical factors influencing SRM effectiveness. Trust was found to be foundational, fostering cooperation and commitment between e-commerce businesses and suppliers through transparent interactions. Effective communication and the integration of advanced technologies like AI and blockchain enhanced operational efficiency and innovation capabilities, enabling businesses to deliver tailored customer experiences. Strategic alignment between businesses and suppliers proved essential for shared success and mutual benefit, while sustainability practices increasingly shaped consumer preferences and brand reputation. Collaboration facilitated joint innovation and accelerated product customization, underscoring the importance of partnerships in achieving strategic goals. However, challenges including supply chain complexity, managing consumer expectations, and regulatory compliance highlighted the need for continuous improvement and adaptive strategies. Overall, this research contributes valuable insights for e-commerce businesses seeking to optimize SRM strategies, enhance supply chain efficiency, and navigate the complexities of customization in a competitive digital marketplace. By leveraging trust, communication, technology, strategic alignment, sustainability, and collaboration, businesses can effectively meet evolving consumer demands and achieve sustainable growth.

This qualitative research investigates the impact of Supplier Relationship Management (SRM) on e-commerce innovation adoption. Through semi-structured interviews and document analysis, the study explores how SRM practices influence organizational capabilities to innovate in the context of digital commerce. Key themes emerged, emphasizing the critical role of trust, communication, collaboration, strategic alignment, technology integration, organizational culture, leadership, and external factors in shaping e-commerce innovation. Trust was found to be foundational, fostering transparent communication and collaborative relationships that facilitate innovation. Effective communication channels and collaborative initiatives enabled organizations and suppliers to leverage combined expertise, driving the development of innovative e-commerce solutions. Strategic alignment ensured that both parties worked towards shared goals, supported by technology integration that enhanced operational efficiency and decision-making. Organizational culture and leadership were identified as crucial in creating environments conducive to continuous innovation. External factors such as market dynamics, regulatory requirements, and technological advancements influenced innovation strategies, highlighting the need for adaptive and responsive SRM practices. The findings underscore the interconnectedness of these factors within the SRM framework, offering insights into how organizations can enhance their innovation capabilities and competitiveness in the digital economy. By strategically managing SRM practices and integrating sustainable initiatives, organizations can navigate challenges, seize opportunities, and achieve sustained success in e-commerce innovation.

This qualitative study explores how businesses are adapting their Supplier Relationship Management (SRM) strategies to address the challenges and capitalize on the opportunities presented by evolving e-commerce trends. Through in-depth interviews with key industry stakeholders, the research investigates the integration of advanced technologies such as artificial intelligence (AI), blockchain, and the Internet of Things (IoT) into SRM practices. Findings reveal that these technologies enhance efficiency, transparency, and responsiveness within supply chains, enabling businesses to navigate complexities such as supply chain dynamics, fluctuating consumer demand, and regulatory compliance. The study identifies effective strategies employed by businesses, including enhancing communication channels with suppliers, diversifying supplier bases, and investing in technological advancements. These strategies enable businesses to mitigate risks, improve collaboration, and drive innovation, thereby maintaining competitive advantage in the digital marketplace. Collaborative practices such as joint product development, shared risk management, and co-investment in technology emerge as critical drivers of successful SRM. Ultimately, this research contributes to a deeper understanding of SRM in the context of e-commerce, offering insights into how businesses can optimize their supply chain operations amidst technological disruptions and market fluctuations. The findings underscore the importance of proactive adaptation and strategic alignment with suppliers to foster resilient and agile supply chains. As e-commerce continues to evolve, businesses must leverage these insights to refine their SRM strategies and sustain growth in an increasingly competitive environment.

This qualitative study explores the transformative role of Supplier Relationship Management (SRM) in the context of e-commerce, focusing on the integration of digital technologies and evolving supplier interactions. As digital advancements such as artificial intelligence, blockchain, data analytics, cloud computing, and the Internet of Things (IoT) reshape traditional SRM practices, e-commerce companies are experiencing significant improvements in efficiency, transparency, and collaboration. This research employs semi-structured interviews, document analysis, and case studies to examine the impact of these technologies on SRM, identify key collaborative practices, and assess risk management strategies. Findings indicate that digital integration enhances decision-making, streamlines operations, and fosters deeper, trust-based supplier relationships. AI facilitates predictive analytics and automates processes, while blockchain provides transparency and reduces fraud. Data analytics supports informed sourcing decisions and risk mitigation, and cloud platforms improve real-time collaboration. IoT enhances supply chain visibility, allowing for better inventory management. Despite these benefits, challenges such as high implementation costs, integration difficulties, data privacy concerns, and security risks remain significant barriers. Collaboration practices, including joint development, shared resources, and coordinated marketing, contribute to innovation and mutual growth, emphasizing the need for effective communication and trust. Risk management strategies, such as scenario planning and supplier diversification, are crucial for maintaining supply chain resilience. Strategic alignment between e-commerce companies and suppliers, including goal congruence and capability matching, is essential for seamless coordination and competitive advantage. The study underscores the importance of a holistic approach to SRM, integrating technology, collaboration, risk management, and strategic alignment to navigate the complexities of supplier relationships in the digital age. These insights provide a framework for e-commerce companies to optimize their SRM practices and achieve sustainable growth in a dynamic marketplace.

Transient receptor potential melastatin-8 (TRPM8) is a cation channel that is activated by cold and “cooling agents” such as menthol and icilin, which induce a cold sensation. Stimulation of TRPM8 activates an intracellular signaling cascade that ultimately leads to a change in the gene expression pattern of the cells. Here, we investigated the TRPM8-induced signaling pathway that links TRPM8 channel activation to gene transcription. Using a pharmacological approach, we show that inhibition of phosphatidylinositol 4-phosphate 5 kinase alpha (PIP5K), an enzyme essential for the biosynthesis of phosphatidylinositol 4,5-bisphosphate, attenuated TRPM8-induced gene transcription. Analyzing the link between TRPM8 and Gq proteins, we show that pharmacological inhibition of the beta gamma subunits impairs TRPM8 signaling. In addition, genetic studies showed that TRPM8 requires an activated Galpha subunit for signaling. In the nucleus, the TRPM8-induced signaling cascade triggers an activation of the transcription factor AP-1, a complex consisting of a dimer of basic region leucine zipper (bZIP) transcription factors. Here, we identified the bZIP protein c-Jun as an essential component of AP-1 within the TRPM8-induced signling cscade. In summary, with PIP5K, Gq subunits and c-Jun we have identified key molecules in the TRPM8-induced signaling from the plasma membrane to the nucleus.

High temperatures (HT) and high hydrostatic pressures (HHP) are characteristic of deep-sea hydrothermal vents and other deep crustal settings. These environments host vast and diverse microbial populations, yet only a small fraction of those populations have been successfully cultured. This is due, in part, to the difficulty of sampling while maintaining these in situ conditions and also replicating those high-temperature and high-pressure conditions in the laboratory. In an effort to facilitate more HT-HHP cultivation, we present two HT-HHP batch culture incubation systems for cultivating deep-sea vent and subsurface (hyper)thermophilic microorganisms. One HT-HHP system can be used for batch cultivation up to 110 MPa and 121°C, and requires sample decompression during subsampling. The second HT-HHP system can be used to culture microorganisms up to 100 MPa and 160°C with variable-volume, pressure-retaining vessels that negate whole-sample decompression during subsampling. Here, we describe how to build cost effective heating systems for these two types of high-pressure vessels, as well as the protocols for HT-HHP microbial batch cultivation in both systems. Additionally, we demonstrate HHP transfer between the variable-volume vessels, which has utility in sampling and enrichment without decompression, laboratory isolation experiments, as well as HHP filtration.

Intensive application of synthetic pesticides was the routine practice of commercial agriculture during the Green Revolution to boost agricultural productivity to meet global food demand. Alongside this, the application of chemical pesticides caused adverse effects on the environment and its ecoreceptors including human health. Negative externalities arising from conventional farming instigated the call for sustainable development during the sixties to promote and balance the nexus between socially acceptable economic growth and environmental protection. Consequently, a blueprint of 17 Sustainable Development Goals (SDGs) and 169 targets including ecological stewardship and food security was drafted. Eight out of the 17 SDGs are directly linked to sustainable agriculture based on the direct impact of agriculture, judicious use of critical resources and conservation and the Principles of green chemistry. As a green chemical agent, biopesticides have been shown to have the potentials to substitute chemical pesticides with equal agricultural productivity. The adoption of bio-based pesticides via integrated pest management (IPM) has proven to be the most effective option to influence most dimensions of sustainable agriculture. Therefore, biopesticide-driven IPM if utilized with requisite education, skills and research would boost sustainable agriculture. This chapter reviews the prospects, importance, and limitations of biopesticides to sustainable agriculture and how sustainable agriculture is connected to sustainable development, Green Chemistry, and integrated pest management.

The planning of bicycle infrastructure across our cities remains is a complex task involving many key stakeholders including the community, who traditionally have had limited involvement in the planning process. This research develops an interactive bicycle prioritisation index tool which includes participatory spatial and textual citizen feedback. The research involves three components. Firstly, a survey of current cyclists in Sydney, their current level of participation, priorities in investment in cycling, and preferred locations for cycling infrastructure. Secondly, it documents the development of an interactive digital bicycle planning tool which is informed through citizen feedback. Thirdly, it evaluates the approach in conversation with potential end-users, including government, planning practitioners, and advocacy group members. The research proposes the combination of multiple passive and active data traces with end-user evaluation to legitimise the citizen co-design of bicycle investment prioritisation initiatives. A case study approach has been taken, focusing on the city of Sydney, Australia. The bicycle planning support system can be used by cities when engaging in cycle prioritisation initiatives, particularly with a focus on integrating citizen feedback and navigating new and complex data landscapes introduced through recent, passively collected big data sets.

Global stress is widespread in todays post-pandemic world of political and economic uncertainty. Vibroacoustic technology is a vibrotactile intervention with multiple uses, and its impact on stress lacks interpretation. This research assessed if the vibroacoustic technology of a Vibroacoustic Sound Massage (VSM) can reduce psychological, physiological and cognitive stress. The Perceived Stress Scale (PSS-10), and electrocardiogram (ECG) and electroencephalogram (EEG) biosignals were used to quantify results. Participants were divided into Low Stress and High Stress groups. ECG results show VSM increased parasympathetic activity for all participants, with the Low Stress group more effected. EEG results indicate increased concentration (TBR), reduced arousal and increased relaxation (BAR), and non-significant effects on participant well-being (FAA), though variability in this metric was homogenised after VSM. Together, these results validate VSM as an effective support tool for stress management and further research is required.

Within this paper, electro-mechanical long-term tests on a thrust bearing are presented. The effects of an additional electrical load on the bearing raceways and the used lubricant are investigated. Chemical and rheological investigations are presented which show the changes in the lubricant. These investigations are compared with the electrical loads and the occurring raceway damage. In addition, a comparison is made with mechanical reference tests. This procedure makes it possible to classify the changes that occur due to the electrical load and to distinguish the effects from each other. The background to these investigations is the increased occurrence of parasitic currents in electric motors, which can lead to damage to machine elements. The phenomena that occur here are new challenges in the development of drive trains.

Rainfall, or more generally the precipitation process (flux), is a clear example of chaotic variables resulting from a highly nonlinear dynamical system, the atmosphere, represented by a set of physical equations such as the Navier-Stokes equations, energy balances and hydrological cycle among others. As a generalization of the Euclidean (ordinary) measurements, chaotic solutions of these equations are characterized by fractal dimensions, which are non-integer values that represent the complexity of variables like the precipitation. However, observed precipitation is measured as an aggregate variable over time, thus physical analysis of the observed fluxes is very limited. Therefore, this review aims to go through the different approaches used in the identification and analysis of the complexity of the observed precipitation, taking advantage of its geometry footprint. To address the review, it ranges from classical perspectives of fractal-based techniques to new perspectives at temporal and spatial scales as well as for classification of climatic features, including monofractal dimension, multifractal approaches, Hurst exponent, Shannon entropy and time scaling in intensity-duration-frequency curves.

Most recent university campuses follow the North American model, built on city limits or countryside, with large separate buildings in open green spaces. Studies suggest that prevalence and severity of mental health issues among university students are increasing over the past decade in most countries. University services were created to face this growing problem, however individual based interventions have limited effects on mental health and well-being of a large population. Our aim was to verify if and how the natural environment in Campuses is focused on programs to cope with the issue of mental health and well-being among students. Systematic review of literature was undertaken with search in Scopus and LILACS with the keywords “green areas” AND “well-being” AND “Campus”, following PRISMA guidelines. As a result, 32 articles were selected. Research on the topic is recent, mostly in the USA, Bulgaria, and China. Most studies used objective information on campuses’ greenness and/or university students’ perception. Mental health was usually measured by validated scores. Findings of all the studies indicated positive association between campus greenery and well-being of students. We conclude that there is a large potential for use of university campuses in programs and sites for students´ restoration and stress relief.

Pearl millet (Pennisetum glaucum L.) is the second most important cereal grown in Eritrea after sorghum (Sorghum bicolor L.) grown under low input systems by small scale farmers. The crop utilizes soil moisture efficiently and has ability to tolerate soil toxicity and extreme temperatures than other cereals. It is a sustenance and food security crop important for its nutritive and cultural value and provides dietary energy and nutrition. However, despite the positive attributes and qualities of pearl millets for the present and future agriculture, production has been low. We attribute this to inadequate rainfall distribution, poor crop management by poorly resourced farmers, unavailability and high prices of farm inputs such as fertilizer and pesticides and low adoption of improved varieties by the farmers. This review outlines the constraints, interventions the government/ farmers have and can implement and the prospects of actions that can improve pearl millet production. As much as there have been efforts by the government and stakeholders to address these challenges and improve productivity of pearl millet, more needs to be done to meet the increasing demand of the increasing populations. This will enable farmers to intensify and diversify their agricultural systems and improve food security situation in the country. Unless a combined effort in soil fertility improvement, policies to promote use of modern varieties and conservation of and promotion of this crop biodiversity, the potential of this crop as famine and poverty alleviation among the rural poor will not be realized.

With its sights set on sustainable development, transport policy finds itself confronted with the challenge of convincing people to abandon the current path of growth and instead use small, slower vehicles with a reduced range in the future. The problem with this goal is that people's mental structures are shaped by the car ensconced in their heads. Thinking in other terms hardly seems possible; moreover, many of the products classified as vehicles, but smaller in scale than the "car" and that already exist, remain unknown, nor can they be tried out - they are quite literally nowhere to be seen. In light of this situation, the German Federal Environmental Foundation has commissioned a feasibility study to explore the establishment of a World of Experience (Erlebniswelt) of sustainable urban mobility - the EcoMobileum®. Here, the aim is to open up the horizons of a new culture of mobility in order to get people excited about the transformation of mobility.

The assessment of caprock integrity for underground storage of CO2 and/or enhanced oil recovery (EOR) systems is a multiscale endeavor. Caprock sealing behavior depends on coupled processes that operate over a broad range of length and time scales including nanoscale heterogeneity in capillary and wettability properties to depositional heterogeneity that is basin wide. Larger-scale sedimentary architecture, fractures, and faults can govern properties of potential “seal-bypass” systems that may be difficult to assess. We present a multiscale investigation of geologic sealing integrity of the caprock system that overlies the Morrow B sandstone reservoir, Farnsworth Unit, Texas, USA. The Morrow B sandstone is the target geologic unit for an on-going combined CO2 storage–EOR project by the Southwest Regional Partnership on Carbon Sequestration (SWP). Methods and/or data encompass small-to-large scales, including: petrography using electron and optical microscopy; mercury porosimetry; core examinations of sedimentary architecture and fractures; well logs; a suite of geomechanical testing; and a noble gas profile through sealing lithologies into the reservoir, as preserved from fresh core. The combined data set allows a comprehensive examination of sealing quality by scale, by primary features that control sealing behavior, and an assessment of sealing behavior over geologic time.

Extensive phytochemical and chromatographic analysis of different root fractions of Jatropha pelargoniifolia Courb. (Euphorbiaceae) resulted in the isolation and identification of 22 distinct secondary metabolite compounds. Two new compounds, 6-hydroxy-8-methoxycoumarin-7-O-β-D-glycopyranoside and (3-(2-(methylamino) ethyl)-1H-indol-2-yl) methanol, were isolated and identified for the first time from a natural source. In addition, other known compounds, such as hovetricoside C and N-methyltryptamine were isolated from Euphorbiaceae, and hordenine, N-methyltyramine, their salts, cynaroside and linarin were identified in Jatropha spp. for the first time. Some isolated metabolites, such as β-sitosterol, β-sitosterol glucoside, curcusons D and C, naringenin, apigenin, cleomiscosins B and A, spruceanol, propacin, jatrophadiketone, and uracil were previously identified in various Jatropha species. The structures of the isolated compounds were determined using different spectroscopic techniques. The anti-inflammatory, antinociceptive, antipyretic, and antioxidant activities were evaluated for some adequately available isolated compounds. Compounds showed significant antinociceptive activity compared with the standard analgesic drug indomethacin. The edema size was significantly reduced (p< 0.05–0.001) in the animals treated with low doses (5 and 10 mg/kg) of the isolated compounds compared with those treated with a high dose (100 mg/kg) of standard anti-inflammatory drug (phenylbutazone). Furthermore, all tested compounds showed a significant (p< 0.05–0.001) reduction in the rectal temperature of hyper-thermic mice.

We present a compact optical head design for wide-range and low noise displacement sensing using deep frequency modulation interferometry. The on-axis beam topology is realised in a quasi-monolithic component and relies on cube beamsplitters and beam transmission through perpendicular surfaces to keep angular alignment constant when operating in air or vacuum, which leads to the generation of ghost beams that can limit the phase readout linearity. We investigate the coupling of these beams into the non-linear phase readout scheme of DFMI and demonstrate adjustments of the phase estimation algorithm to reduce this effect. This is done through a combination of balanced detection and the inherent orthogonality of beat signals with different relative time-delays in deep frequency modulation interferometry that is a unique feature not available for heterodyne, quadrature or homodyne interferometry.

This qualitative research explores the transformative impact of technological innovations on retail marketing effectiveness. Through thematic analysis of interviews with industry professionals, the study identifies key themes including enhanced customer engagement, personalized marketing strategies driven by AI and machine learning, data-driven decision-making leveraging big data and analytics, the rise of e-commerce platforms, integration of mobile technologies, adoption of augmented reality (AR) and virtual reality (VR), development of omnichannel strategies, and implementation of loyalty programs. These themes illustrate how technology has reshaped retail marketing by enabling real-time customer interactions, personalized shopping experiences, and targeted marketing campaigns that enhance customer satisfaction and loyalty. The findings highlight the critical role of digital platforms like social media in fostering community engagement and brand loyalty. AI and machine learning facilitate personalized marketing efforts, tailoring product recommendations and enhancing customer experiences. Data-driven strategies optimize marketing ROI by providing insights into consumer behavior and market trends. E-commerce platforms expand market reach and streamline transactions, while mobile technologies and AR/VR innovations create immersive shopping experiences that captivate consumers. Omnichannel strategies integrate physical and digital channels, delivering seamless brand experiences and enhancing customer retention through CRM systems and loyalty programs. Looking ahead, retailers must navigate challenges such as rapid technological change, the need for continuous adaptation, and concerns about data privacy. By embracing technological advancements strategically and maintaining ethical standards, retailers can sustain competitive advantage, meet evolving consumer expectations, and drive growth in the digital era.

In the literature on occupational stress and recovery from work several facets of thinking about work in off-job time have been conceptualized. However, research on the focal concepts is currently rather disintegrated. In this study we take a closer look at the five most established concepts, namely (1) psychological detachment, (2) affective rumination, (3) problem-solving pondering, (4) positive work reflection, and (5) negative work reflection. More specifically, we scrutinized (1) whether the five facets of work-related rumination are empirically distinct, (2) whether they yield differential associations with different facets of employee well-being (burnout, work engagement, thriving, satisfaction with life, and flourishing), and (3) to what extent the five facets can be distinguished from and relate to conceptually similar constructs, such as irritation, worry, and neuroticism. We applied structural equation modeling techniques to cross-sectional survey data from 474 employees. Our results provide evidence that (1) the five facets of work-related rumination are highly related, yet empirically distinct, (2) that each facet contributes uniquely to explain variance in certain aspects of employee well-being, and (3) that they are distinct from related concepts, albeit there is a high overlap between (lower levels of) psychological detachment and cognitive irritation. Our study contributes to clarify the structure of work-related rumination and extends the nomological network around different types of thinking about work in off-job time and employee well-being.

Ketogenic diet (KD) is getting in the focus as auxiliary cancer therapy, since it provides sufficient energy supply for healthy cells, while impairing energy production in tumor cells underlying the Warburg effect. Thereby, it can assist in inhibiting tumor growth and simultaneously counteract cachexia, which is frequently observed in cancer patients under chemotherapy. In order to provide molecular evidence for the proposed synergistic inhibition of tumor growth, we applied untargeted quantitative metabolome analysis on a breast cancer xenograft mouse model. Healthy mice and such bearing breast cancer xenografts and receiving chemotherapy were compared after treatment with control diet and KD. Metabolomic profiling was performed on plasma samples, applying high-performance liquid chromatography coupled to tandem mass spectrometry. Statistical analysis revealed metabolic fingerprints comprising numerous significantly regulated features in the group of mice bearing breast cancer. This fingerprint disappeared after treatment with KD, resulting in recovery to the metabolic status observed in healthy mice receiving control diet. Moreover, amino acid metabolism as well as fatty acid transport were found to be affected by both, the tumor and the applied KD. Our results provide clear evidence of a significant molecular effect of KD in the context of tumor growth inhibition.

Novel strategies in coastal protection are needed to cope with climate change-induced sea level rise. They aim at the sustainable development of coastal areas in light of an intensification and land use changes. A promising approach is the design of nature-based solutions (NbS), complementing the safety levels of technical infrastructures. However, NbS lack a widespread and large-scale implementation. To address this deficit, co-design concepts are needed that combine experiences from science and practice. This work presents and discusses the approach of a coast-specific real-world laboratory (RwL) addressing the inclusive design of ecosystem-based coastal protection. Strategies of RwLs are applied for the first time in a coastal context along the North Sea coastline in Germany. We found the concept of RwLs suitable for coastal transdisciplinary research, although adaptions in the spatial reference level or flexibility in location and time of experimentation are necessary. A profound actor analysis is indispensable to specify participatory processes and interaction levels. A criteria-based cooperative selection of RwL sites helps to reveal and solve conflicting interests to achieve trust between science and practice. Addressing site-specific characteristics and practitioners’ needs, our coastal RwL provides a mutual learning space to develop and test NbS to complement technical coastal protection.

Recycled wastewater is considered as a sustainable source of irrigation water. Despite commendable safety records, viral contamination of agricultural products has occurred the past causing disease outbreaks. This review examines the apprehension that the novel coronavirus (SARS-CoV-2) may also spread through recycled wastewater irrigation (RWI) industry. The novel SARS-CoV-2 is now perceived as an enteric pathogen, and has been found to remain stable in the wastewater for days. Mounting evidences also suggest that viral particles shed by infected individuals through sewage, and greywater is much higher (up to 10 Log₁₀) than the amount typically removed (6-7 Log₁₀) through the recycled water disinfection processes. Such gap indicated an increased risk of infection through fecal-oral transmission route. This study also identified greywater irrigation schemes posing a higher risk of transmission of SARS-CoV-2. It was recommended that countries putting greywater in the ‘low risk’ category may rewrite the safety guidelines in post COVID-19 times. This review also suggest that the choice of irrigation method could be critical in protecting the farmers, and the consumers from possible infections during the pandemic. In this regard, irrigation methods (i.e. sprinkler) that generate airborne droplet (leading to aerosols) may be operated with caution when public spaces are in the vicinity. The study also indicated that the developing countries should regulate surface irrigation practice that pump water from polluted rivers during the pandemic.

Disorder of S-adenosylhomocysteine hydrolase (AHCY) activity leads to the potentially lethal rare disease AHCY deficiency, first described in 2004 by Baric and co-workers [1]. In order to shed new light on molecular aspects of the disease, in particular changes at transcriptome level, we enabled knock-down of AHCY expression in model systems such as the colon cancer cell line SW480 to simulate the environment occurring in AHCY deficiency patients. Further, we per-formed deep sequencing of mRNA, followed by differential expression and molecular pathway analysis. Fifteen differentially expressed networks were identified, and interestingly, we found a predicted effect of AHCY down-regulation on the expression of the Lymphoidphoid enhanc-er-binding factor 1 (LEF1) gene, indicating changes in the TCF4/LEF1 complex. LEF1, a member of the T-cell Factor (TCF)/LEF1 family of high-mobility group transcription factors, is a down-stream mediator of the Wnt/β-catenin signaling pathway [2]. LEF1 is essential in stem cell maintenance, and especially in its role in epithelial-mesenchymal transition (EMT). Western blot analysis of LEF1 protein expression confirmed our transcriptomic data predictions and revealed significantly increased LEF1 protein in AHCY- deficient cells, providing a novel link between AHCY and cancer cell phenotype.

Today massive amounts of sequenced metagenomic and -transcriptomic data from different ecological niches and environmental locations are available. Scientific progress depends critically on methods that allow extracting useful information from the various types of sequence data. Here, we will first discuss types of information contained in the various flavours of biological sequence data, and how this information can be interpreted to increase our scientific knowledge and understanding. We argue that a mechanistic understanding is required to consistently interpret experimental observations, and that this understanding is greatly facilitated by the generation and analysis of dynamic mathematical models. We conclude that, in order to construct mathematical models and to test mechanistic hypotheses, time-series data is of critical importance. We review diverse techniques to analyse time-series data and discuss various approaches by which time-series of biological sequence data was successfully used to derive and test mechanistic hypotheses. Analysing the bottlenecks of current strategies in the extraction of knowledge and understanding from data, we conclude that combined experimental and theoretical efforts should be implemented as early as possible during the planning phase of individual experiments and scientific research projects.

Although work events can be regarded as pivotal elements of organizational life, only a few studies have examined how positive and negative events relate to and combine to affect work engagement over time. Theory suggests that to better understand how current events affect work engagement (WE), we have to account for recent events that have preceded these current events. We present competing theoretical views on how recent and current work events may affect employees (e.g., getting used to a high frequency of negative events or becoming more sensitive to negative events). Although the occurrence of events implies discrete changes in the experience of work, prior research has not considered whether work events actually accumulate to sustained mid-term changes in WE. To address these gaps in the literature, we conducted a week-level longitudinal study across a period of 15 consecutive weeks among 135 employees, which yielded 849 weekly observations. While positive events were associated with higher levels of WE within the same week, negative events were not. Our results support neither satiation nor sensitization processes. However, high frequencies of negative events in the preceding week amplified the beneficial effects of positive events on WE in the current week. Growth curve analyses show that the benefits of positive events accumulate to sustain high levels of WE. WE dissipates in the absence of continuous experience of positive events. Our study adds a temporal component and informs research that has taken a feature-oriented perspective on the dynamic interplay of job demands and resources.

Wash’Em is a process that supports humanitarians in assessing and designing rapid but context-specific hygiene programmes in crises or outbreaks. The process consists of training implementers, using tools to learn from populations, and entering findings into a software which generates contextualised activities. A process evaluation of Wash’Em use was conducted in a drought-affected area in Midland province, Zimbabwe. Data was collected during the programme design and following implementation, using a mix of qualitative methods. Findings were classified against the intended stages of Wash’Em, and the evaluation domains were defined by the UKRI Medical Research Council. The Wash’Em process was not fully implemented as intended. An abridged training was utilised, some of the tools for learning from populations were omitted, many of the recommended activities were not implemented, the delivery modalities were different from intended, the budget available was minimal, and the number of people exposed to activities were fewer than hoped. Despite these ‘on the ground’ challenges and adaptations, the Wash’Em process was considered feasible by implementers and was seen to be less top-down than most programme design approaches. The populations exposed to the intervention found the activities engaging, understood the content, and reportedly took action to improve handwashing behaviour.

Empowering women and promoting gender equality is crucial for accelerating sustainable development in fragile countries, including the Democratic Republic of Congo (DRC). However, there is scarce existing knowledge or understanding of the factors determining women’s empowerment in these contexts. We aimed to assess women's empowerment and determine its associated factors in Kinshasa, DRC. We analyzed data from the 2021 Performance Monitoring Assessment (PMA) survey. A sample of 1,365 women of childbearing age was retained for this study. Twenty empowerment items related to household decision-making, contraception use, and husband/partner influence were considered. We calculated the average women’s empowerment index (aWEI), identified the women empowerment variables using principal component analysis (PCA), and determined the associated factors for the first three principal components through the performance of multivariate binary logistic regression. In Kinshasa, the overall aWEI was estimated at 0.65. It was low for household decision-making (0.34) and high for husband/partner influence domains (0.93), respectively. Three principal components were identified and named, including the absence of threats, control of sexuality, and participation in decision-making. The factors associated with these components were having internet access, being in free union with a partner, being aged 40-49 years, and residing in a non-slum area. Increasing access to information would enable women in Kinshasa to make strategic decisions about their lives, benefiting themselves and others.

Before the green revolution, crude plant materials and plant-extracts were used for crop protection. However, their use was swiftly replaced by synthetic pesticides after World War II due to increased demand for more effective pesticides in intensified farming systems. The 20th century saw a steady increase in the use of synthetic pesticides until the mid-21st century when the world started to realize the negative impact of synthetic pesticides. The increased environmental awareness and the need for safe human food led to increased research and development of biopesticides as crop protection options in modern agriculture. This paper brings into perspective the global history of the application and use of botanical biopesticides in crop production. It also highlights the research progress, product development and registration challenges, and opportunities for business and adoption at the farm level in Kenya.

The glycoprotein hormones luteinizing hormone, follicle-stimulating hormone, thyroid-stimulating hormone and chorionic gonadotropin consist of a common alpha-subunit and a hormone-specific beta-subunit. The alpha-subunit is expressed in thyrotrophs, gonadotrophs, and placental cells, and its expression is regulated by extracellular signal molecules. Here, we assessed the regulation of the gene encoding the alpha-subunit in placental JEG-3 cells, using a chromatin-embedded reporter gene under the control of the glycoprotein hormone alpha-subunit promoter. The results show that stimulation of the cells with forskolin, an activator of adenylate cyclase, induced transcription of a reporter gene controlled by the alpha-subunit promoter. Similarly, expression of a nuclear-targeted catalytic subunit of cAMP-dependent protein kinase increased reporter gene transcription. Expression experiments involving constitutively active mutants of MKK6 and MEKK-1 showed that the alpha-subunit promoter is responsive to activation of p38 protein kinase but only slightly responsive to activation of c-Jun N-terminal protein kinase. Finally, we show that stimulation of a Galphaq-coupled designer receptor triggers transcription of a reporter gene controlled by the glycoprotein hormone alpha-subunit promoter, mediated by the transcription factor CREB. Deletion mutagenesis highlights the importance of a tandem cAMP response element within the alpha-subunit promoter that acts as a point of convergence for different signaling pathways.

The growing awareness of the biological effects of artificial light on humans has stimulated ample research. It is now widely accepted that asynchrony between artificialand natural light-dark cycles can elicit severe detrimental health effects. New research has been devoted to lighting solutions that dynamically change their color to mimic spectral changes of daylight and to account for human needs. However, in some situations, the visual properties of light must be preserved: For example professional TV video editors and shift workers who must work under standardized lighting conditions to do color correction in post-production. We have investigated the possibility to tune circadian effects using white lights that are spectrally different but nonetheless have similar color coordinates thus appear as a similar white tone. Our simulation results indicate that it is possible to modulate circadian light effects by combining LEDs for neutral white (4000 K), a widely used white tone for indoor lighting in europe. The results also show that the solutions combining single-color LEDs do however not meet the quality criteria from the visual point of view because their color rendering ability decays to unacceptable low levels. Combining narrowband LEDs with a broadband white LED improves the color rendering quality and we show how far circadian light effects can be tuned according to common theoretical models. The aim is to reflect daylight situations with artificial lighting, thus having a high melatonin suppression in the morning and low melatonin suppression in the evening. As a consequence our aim is to show what maximum and minimum circadian effect is possible with the same set of LEDs.

Originating in the 1970s, Magnetic Compression Anastomosis (MCA) has lately been revisited with a focus on minimal invasive surgery (MIS). The aim of this report is to reappraise our earlier experience with MCA with the intention of facilitating future MCA advancement. A retrospective review was conducted regarding preclinical experiments and clinical trials at a single institution from 1980 through 1995. The reviewed information was compiled and appraised to generate proposals for future MCA use. The experimental studies, including 250 MCA cases in gastrointestinal and urinary tract animal models, demonstrated the technical versatility of MCA as well as the superior biomechanical characteristics in comparison to hand-sewn anastomoses. Clinical trials encompassed 87 MCA procedures in 86 children, 2 to 10 years of age, involving the following techniques: non-operative esophageal recanalization (n=15), non-operative ileostomy undiversion (n=46), Swenson pull-through (n=10), non-operative urethral recanalization (n=5), and extravesical ureterocystoneostomy (n=11). Clinical MCA was found to be successful in over 87% of cases. MCA limitations concerning anastomotic failure and scarring were thought to be mostly due to inadequate magnetic compression. Based on our historic experience, we propose further research on the technical aspects of MCA, along with the biologic aspects of anastomotic tissue remodeling. Magnets should be designed and manufactured for a wide spectrum of pediatric surgical indications, particularly in combination with novel MIS techniques.

Postural deficits such as hyperlordosis (hollow back) or hyperkyphosis (hunchback) are relevant health issues. Diagnoses depend on the experience of the examiner and are therefore often subjective and prone to errors. Machine learning (ML) methods in combination with explainable ar-tificial intelligence (XAI) tools have proven useful for providing an objective, data-based orien-tation. However, only a few works have considered posture parameters, leaving the potential of more human-friendly XAI interpretations still untouched. Therefore, the present work proposes an objective, data-driven ML system for medical decision support that enables especially human-friendly interpretations using counterfactual explanations (CFs). Posture data for 1151 subjects were recorded by means of stereophotogrammetry. An expert-based classification of the subjects regarding the presence of hyperlordosis or hyperkyphosis was initially performed. Using a Gaussian progress classifier, the models were trained and interpreted using CFs. Label errors were flagged and re-evaluated using confident learning. Very good classification performances for both hyperlordosis and hyperkyphosis were found, whereby the re-evaluation and correction of the test labels led to a significant improvement (MPRAUC = 0.97). A statistical evaluation showed that the CFs seemed to be plausible in general. In the context of personalized medicine, the present study’s approach could be of importance for reducing diagnostic errors and thereby improving the individual adaptation of therapeutic measures. Likewise, it could be a basis for the development of apps for preventive posture assessment.

Identifying macroeconomic events that are responsible for dramatic changes of economy is of particular relevance to understand the overall economic dynamics. We introduce an open-source available efficient Python implementation of a Bayesian multi-trend change point analysis which solves significant memory and computing time limitations to extract crisis information from a correlation metric. Therefore, we focus on the recently investigated S&P500 mean market correlation in a period of roughly 20 years that includes the dot-com bubble, the global financial crisis and the Euro crisis. The analysis is performed two-fold: first, in retrospect on the whole dataset and second, in an on-line adaptive manner in pre-crisis segments. The on-line sensitivity horizon is roughly determined to be 80 up to 100 trading days after a crisis onset. A detailed comparison to global economic events supports the interpretation of the mean market correlation as an informative macroeconomic measure by a rather good agreement of change point distributions and major crisis events. Furthermore, the results hint to the importance of the U.S. housing bubble as trigger of the global financial crisis, provide new evidence for the general reasoning of locally (meta)stable economic states and could work as a comparative impact rating of specific economic events.

Background: This study assesses the effects of the ‘Radiant’ image enhancement technique on fetal nuchal translucency (NT) measurements during first trimester sonographic ex-ams. Methods: A retrospective analysis of 263 ultrasound images of first trimester midsagittal sections was conducted. NT measurements were obtained using a semi-automatic tool. Statistical methods were applied to compare NT measurements with and without ‘Radi-ant’ enhancement. An in-vitro setup with predefined line distances provided additional data. Results: Incremental increases in NT measurements were observed with varying levels of ‘Radiant’ application: An average increase of 0.19 mm with ‘Radiant min’, 0.24 mm with ‘Radiant mid’ and 0.30 mm with ‘Radiant max.’ The in-vitro results supported these findings, showing consistent effects on line thickness and measurement accuracy, with the smallest mean deviation occurring at the ‘Radiant mid’ setting. Conclusions: ‘Radiant’ image enhancement leads to significant increases in NT measure-ments. To avoid systematic biases in clinical assessments, it is advisable to disable ‘Radi-ant’ during NT measurement procedures. Further studies are necessary to corroborate these findings and to consider updates to the NT reference tables based on this technology.

Abstract: Peptide pools composed of short amino acid sequences have proven to be versatile tools in various research areas and clinical applications. They are powerful tools for epitope mapping, immunotherapy, and vaccine development. Their importance lies in their ability to map complex protein structures, enabling a comprehensive understanding of immune responses and facilitating the identification of potential therapeutic agents. The application of peptide pools also extends to the field of personalized medicine, offering tailored solutions for diseases such as cancer and infectious diseases. Peptide pools are complex mixtures of immunostimulatory antigens primarily intended for T-cell stimulation. They are commercially available in many different compositions and variants. However, unlike other reagents that consist of only one or a few compounds, peptide pools are highly complex products with limited stability. This makes their quality control a major challenge. Quantitative peptide analysis usually requires sophisticated methods, in most cases isotope-labeled standards and reference materials. None of these are routinely available for these products. Synthesis and purification of all labeled peptides might be required. Usually, this approach would be prohibitively laborious and expensive. Therefore, an approach is needed to provide a practical and feasible method for quality control of peptide pools. With insufficient quality control, the use of such products could lead to incorrect experimental results, which would worsen the well-known reproducibility crisis in the biomedical sciences. Here we propose the use of ultra-high performance liquid chromatography (UHPLC) with two detectors, a standard UV detector (at 214 nm) for quantitative analysis and a high-resolution mass spectrometer (HRMS) for identity confirmation. To be cost-efficient and fast, quantification and identification are performed in one chromatographic run. An optimized protocol is shown, and different peak integration methods are compared and discussed. This work was performed using a peptide pool known as CEF, which consists of 32 peptides derived from cytomegalovirus (CMV), Epstein-Barr virus (EBV) and influenza virus, ranging from 8 to 12 amino acids in length.

Fifteen transgenic shoot clones (TS A-TS O) regenerated from Hypericum perforatum hairy roots were evaluated for growth characteristics, phenylpropanoid, and naphthodianthrone production, as well as non-enzymatic and enzymatic antioxidant status. Transgenic shoots displayed higher biomass production and non-altered phenotype compared to control shoots. Phenylpropanoid production in TS was not related to phenylalanine ammonia lyase activity indicating that alternative enzymes could be involved in the regulation of phenylpropanoid/flavonoid biosynthesis. The positive correlation between phenylpropanoids (phenolic acids, flavonoids, flavan-3-ols, tannins) and non-enzymatic antioxidant assays suggested that these compounds are the main contributors to the redox state and radical scavenging properties of TS clones. More importantly, enhanced naphthodianthrone production (hypericin, pseudohypericin and protopseudohypericin) in TS was associated with the number of leaf dark glands. Concerning the enzymatic antioxidant status of TS, guaiacol peroxidase was shown as the main enzyme that turn down H2O2 levels, while the up-regulation of superoxide dismutase coincided with decreased O2•− production. The efficiency of antioxidant enzymes for O2•− and H2O2 neutralization declined the MDA level and consequently delayed lipid peroxidation in TS clones. Altogether, H. perforatum transgenic shoots could be proposed as a prospective biotechnological system for scale-up production of naphthodianthrones and phenylpropanoids with antioxidant properties.

Introduction Blunt carotid injuries (BCI) in pediatric trauma are quite rare. Due to the low number of cases, only a few reports and studies have been conducted on this topic. This review will discuss how frequent BCI/ BCVI on pediatric patients after blunt trauma is, what routine diagnostics look like, if a CT/ CTA scan on pediatric patients after blunt trauma is always necessary and if there are any negative health effects? Methods This literature review includes reviews, systematic reviews, case reports and original studies in english language between 1999 and 2020 that have dealt with pediatric blunt trauma and the diagnostics of BCI and BCVI. Furthermore, publications on the risk of radiation exposure on children were included in the study. For literature research, Medline (PubMed) and the Cochrane library were used. Results Pediatric BCI/ BCVI, shows an overall incidence between 0.03 – 0.5% of confirmed BCI/ BCVI cases due to pediatric blunt trauma. 1.1 – 3.5% of pediatric blunt trauma patients underwent CTA to detect BCI. Only 0.17 – 1.2% of all CTA scans shows a positive diagnosis for BCI. In children, the median volume CT dose index on a non-contrast head CT is 33 milligray, a computed tomography angiography needs at least 138 mGy. A cumulative doses of about 50 mGy almost triples the risk of leukemia, and doses of about 60 mGy triples the risk of brain cancer. Discussion Knowing that a BCI could have extensive neurologic consequences for children, it is necessary to evaluate routine pediatric diagnostics after blunt trauma. Computed tomography scans (CT) and computed tomography angiography (CTA) are mostly used in routine BCI diagnostics. However, since radiation exposure in children should be as low as reasonably achievable, it should be asked if other diagnostic methods could be used to identify risk groups. Trauma guidelines and clinical scores like the McGovern score are reflect established BCI screening options, as well as using duplex ultrasound.

This study investigates the transformative impact of technology adoption on retail marketing strategies, focusing on artificial intelligence (AI), big data analytics, augmented reality (AR), virtual reality (VR), mobile technology, and automated customer service solutions. Through qualitative research methods, including interviews and thematic analysis, insights were gathered from industry stakeholders across diverse retail sectors. The findings reveal that AI facilitates personalized marketing through data-driven insights, enhancing customer satisfaction and loyalty. Big data analytics enable retailers to forecast trends, optimize inventory, and tailor marketing strategies to consumer preferences effectively. AR and VR technologies enrich customer experiences by offering immersive and interactive shopping environments, bridging the gap between physical and digital retail spaces. Mobile technology supports omni-channel strategies, providing seamless integration and personalized interactions across platforms. The COVID-19 pandemic accelerated digital transformation in retail, emphasizing the resilience and adaptability of technology-driven strategies in navigating disruptions. AI-powered chatbots and virtual assistants streamline customer service operations, enhancing efficiency and customer satisfaction.

This study explores the transformative impact of e-commerce technologies on supply chain management within the retail sector. Through a thematic analysis of current literature and qualitative research findings, the study examines how technologies such as real-time monitoring, predictive analytics, AI, blockchain, and IoT are reshaping inventory management, procurement, logistics, and customer service. The research highlights significant improvements in operational efficiency, decision-making, and customer experience driven by these technologies. However, challenges such as system integration complexities, cybersecurity risks, and regulatory compliance issues are also identified. The study emphasizes the strategic adoption and integration of e-commerce technologies to enhance supply chain resilience, sustainability, and competitiveness. Insights from the analysis underscore the evolving role of technology in driving innovation and efficiency across supply chain functions, while also necessitating careful management of risks and complexities. Looking forward, the study discusses future trends including AI advancements, IoT connectivity, and blockchain applications, which are poised to further revolutionize supply chain dynamics. By addressing these trends and challenges strategically, retailers can leverage e-commerce technologies to optimize operations, mitigate risks, and meet evolving consumer demands in a digital-first marketplace.

To understand microbial growth with mathematical models has a long tradition that dates back to the pioneering work of Jacques Monod in the 1940s. Growth laws are simple mathematical expressions that aim at describing growth rates of microbes as functions of external parameters, in particular nutrient concentrations. These laws are now widely applied to construct, e.g., dynamic ecosystem models. However, to explain the growth laws from underlying (first) principles is extremely challenging. In the second half of the 20th century, numerous experimental approaches aimed at precisely measuring heat production during microbial growth to determine the entropy balance in a growing cell and to quantify the exported entropy. This has led to the development of thermodynamic theories of microbial growth, which have generated fundamental understanding and identified principle limitations of the growth process. Whereas these approaches considered a growing microbe as a black box, modern theories heavily rely on genomic resources to describe and model genome-scale networks to explain microbial growth. Interestingly, however, thermodynamic constraints are often included in modern modelling approaches only in a rather superficial fashion, and it appears that recent modelling approaches and classical theories are disconnected fields. In order to stimulate a closer interaction between these fields, we here review various theoretical approaches that aim at describing microbial growth based on thermodynamic principles. We start with classical black-box models of cellular growth, and continue with genome-scale modelling approaches that include thermodynamics, before we place these models in the context of fundamental considerations based on non-equilibrium statistical mechanics. We conclude by identifying conceptual overlaps between the fields and suggest how the various types of theories and models can be integrated. We outline how concepts from one approach may help to inform or constrain another, and we demonstrate how genome-scale models can be used to infer classical black-box parameters, which are experimentally accessible in growth experiments. Such integration will allow understanding to what extent microbes can be viewed as thermodynamic machines, and how close they operate to theoretical optima.

The accurate prediction of molecular properties such as lipophilicity and aqueous solubility are of great importance and pose challenges in several stages of the drug discovery pipeline. Machine learning methods like graph-based neural networks (GNNs) have shown exceptionally good performance in predicting these properties. In this work, we introduce a novel GNN architecture, called directed edge graph isomorphism network (D-GIN). It is composed of two distinct sub-architectures (D-MPNN, GIN) and achieves an improvement in accuracy over its sub-architectures employing various learning, and featurization strategies. We argue that combining models with different key aspects help make graph neural networks deeper and simultaneously increase their predictive power. Furthermore, we address current limitations in assessment of deep-learning models, namely, comparison of single training run performance metrics, and offer a more robust solution.

Background: Repeated SARS-CoV-2 infections are plausible and related published data are scarce. We aimed to identify factors associated with the risk of recurrent (three episodes) laboratory-confirmed symptomatic SARS-CoV-2 infections. Methods: A retrospective cohort study was conducted and 1,700 healthcare workers were enrolled. We used risk ratios (RR) and 95% confidence intervals (CI) to evaluate factors associated with symptomatic SARS-CoV-2 infections. Results: We identified 14 participants with recurrent illness episodes. Therefore, the incidence rate was 8.5 per 10,000 person-months. In multiple model, vaccinated adults (vs. unvaccinated, RR = 1.05 [1.03 - 1.06]) and those with a severe first illness episode (vs mild disease, RR = 1.05 [1.01 - 1.10]) were at increased risk for repeated symptomatic SARS-CoV-2 reinfections. Increasing age showed a protective effect (per each additional year of age: RR = 0.98 [0.97 - 0.99]). Conclusions: Our results suggest that recurrent SARS-CoV-2 infections are rare events in adults and they seem to be determined, partially, by vaccination status and age.

Barley straw was used to reinforce PHB in a discontinuous semi-industrial process. Four different fibres were used as reinforcing material : sawdust (SW), defibred (DFBF), delignified (DBF) and bleached (BBF) fibres. Looking at the mechanical properties, onlythe elastic moduli (Et) revealed an improvement. Oppositely, the strengths at break, under both tensile and bending assays, tended to decrease, evidencing a poor affinity between both components. Thanks to the mechani-cal treatment applied on the fibre, DFBF appeared as the most promising filler with the mechani-cal properties of the composites closest to those of neat PHB. DFBF-based composites were then produced by means of a process intensification using a twin-screw extruder, and then moulded into flowerpots. Mechanical results showed almost the same properties between the discontinuous and intensification processes. The suitability of the material to be used on agriculture flowerpots was demonstrated by simulation. . PHB-DFBF composite material can be considered an alterna-tive to replace petrol-based products for applications in agriculture and horticulture.

Psychological readiness following Anterior Cruciate ligament Reconstruction (ACLR) correlates with different return to sport outcomes. However, the relationship between strength and power and psychological readiness remains unexplored. The aim of this study was to investigate the relationship between the Anterior Cruciate Ligament Return to Sport After Injury (ACL-RSI) scores and various hamstrings and quadriceps strength and power variables. Twelve participants (20.7±2.5 years old; 174.2±7.5 cm; 70.2±8.5 kg; 18.2±8.3% of body fat) who had an ACLR nine months or more before the study completed the ACL-RSI questionnaire and isokinetic strength testing of the hamstrings and quadriceps (60°.s-1 and 180°.s-1). Based on ACL-RSI scores, they were divided into “cases” and “controls”, deemed not psychologically ready and psychologically ready to return to previous sport performance (PILOS), respectively. The main findings are that quadriceps’ and hamstrings’ rate of torque development (RTD) and time since surgery were determinants of psychological readiness following ACLR. Furthermore, compared to controls cases showed significantly lower angle-specific quadriceps and hamstrings torque close to extension and lower RTD, but no difference in peak torque. These results suggest that physiotherapists should facilitate athletes’ RTS by focusing on the restoration of RTD and strength at angles close to full knee extension.

Understanding the molecular underpinnings of the evolution of complex (multi-part) systems is a fundamental topic in biology. One unanswered question is the extent to which similar or different genes and regulatory interactions underlie similar complex systems across species. Animal eyes and phototransduction (light detection) are outstanding systems to investigate this question because some of the genetics underlying these traits are well-characterized in model organisms. However, comparative studies using non-model organisms are also necessary to understand the diversity and evolution of these traits. Here, we compare the characteristics of photoreceptor cells, opsins, and phototransduction cascades in diverse taxa, with particular focus on cnidarians. In contrast to the common theme of deep homology, whereby similar traits develop mainly using homologous genes, comparisons of visual systems - especially in non-model organisms - are beginning to highlight a “deep diversity” of underlying components, illustrating how variation can underlie similar complex systems across taxa. Although using candidate genes from model organisms across diversity was a good starting point to understand the evolution of complex systems, unbiased genome-wide comparisons and subsequent functional validation will be necessary to uncover unique genes that comprise complex systems of non-model groups to better understand biodiversity and its evolution.

We discuss what we believe could be an improvement in future discussions of the ever-changing brain. We do so by distinguishing different types of brain variability and outlining methods suitable to analyse them. We argue that, when studying brain and behaviour data, classical methods such as regression analysis and more advanced approaches both aim to decompose the total variance into sensible variance components. In parallel, we argue that a distinction needs to be made between innate and acquired brain variability. For varying high-dimensional brain data, we present methods useful to extract their low-dimensional representations. Finally, to trace potential causes and predict plausible consequences of brain variability, we discuss how to combine statistical principles and neurobiological insights to make associative, explanatory, predictive, and causal enquires; but cautions are needed to raise association- or prediction-based neurobiological findings to causal claims.

Measuring the status and trends of biodiversity is critical for making informed decisions about the conservation, management or restoration of species, habitats and ecosystems. Defining the reference state against which status and change are measured is essential. Typically, reference states describe historical conditions, yet historical conditions are challenging to quantify, may be difficult to falsify, and may no longer be an attainable target in a contemporary ecosystem. We have constructed a conceptual framework to help inform thinking and discussion around the philosophical underpinnings of reference states and guide their application. We characterise currently recognised historical reference states and describe them as Pre-Human, Indigenous Cultural, Pre-Intensification and Hybrid-Historical. We extend the conceptual framework to include contemporary reference states as an alternative theoretical perspective. The contemporary reference state framework is a major conceptual shift that focuses on current ecological patterns and identifies areas with higher biodiversity values, regardless of the disturbance history. The specific context for which we design the contemporary conceptual frame is underpinned by an overarching goal—to maximise biodiversity conservation and restoration outcomes in existing ecosystems. The contemporary reference state framework can account for the inherent differences in the diversity of biodiversity values (e.g., species richness, habitat complexity) across spatial scales, communities and ecosystems. In contrast to historical reference states, contemporary references states are measurable and falsifiable. This ‘road map of reference states’ offers perspective needed to define and assess the status and trends in biodiversity and habitats. Our framework for contemporary reference states provides a tractable way for policy-makers and practitioners to navigate biodiversity assessments to maximise conservation and restoration outcomes in contemporary ecosystems. We illustrate how to define a contemporary reference state using an example from south-eastern Australia.

Knowledge of the interaction between inorganic and organic phosphates with soil minerals is vital for improving the soil P fertility. To achieve an in-depth understanding we combined adsorption experiments and hybrid ab initio molecular dynamics simulations to analyze the adsorption of common phosphates, i.e. orthophosphate (OP), glycerolphosphate (GP) and inositolhexaphosphate (IHP), onto the 100 surface plane of goethite. Experimental adsorption data per mol P-molecule basis fitted to the Freundlich model show the adsorption strength increases in the order GP &lt; OP &lt; IHP, and IHP adsorption being saturated faster followed by GP and OP. Modeling results show that OP and GP form stable monodentate (M) and binuclear bidentate (B) motifs with B being more stable than M, whereas IHP forms stable M and 3M motifs. Interfacial water plays an important role through hydrogen bonds and proton transfers with OP/GP/IHP and goethite. It also controls the binding motifs of phosphates with goethite. Combining both experimental and modeling results, we propose that the B motif dominates for OP, whereas GP forms M and IHP forms a combination of M and 3M motifs. The joint approach plausibly explains why IHP is the predominant organically bound P form in soil. This study could be considered as a preliminary step for further studies for understanding the mechanisms of how microbes and plants overcome the strong IHP–mineral binding to implement the phosphate groups into their metabolism.

Head and neck cancer is the sixth most frequent cancer type. Drug resistance and toxicity are common challenges of the existing therapies, making the development of reliable preclinical models essential for the study of the involved molecular mechanisms as well as for eventual intervention approaches that improve the clinical outcome. Preclinical models of head and neck squamous cell carcinoma have been traditionally based in cell lines and murine models. In this review, we will go over the most frequently used preclinical models, from immortalized-cell and primary tumour cultures in monolayer or 3D, to the currently available animal models. We will scrutinize their efficiency in mimicking the molecular and cellular complexity of head and neck squamous cell carcinoma. Finally, the challenges and opportunities of other envisaged putative approaches, as well as the potential of the preclinical models to further develop customized therapies will be discussed.

The ductile behavior of strain hardening cement-based composites (SHCC) under direct tensile load makes them promising solutions for applications where high energy dissipation is needed, such as earthquake, impact by a projectile, or blast. However, the superior tensile ductility of SHCC due to multiple cracking does not necessarily entail compressive and shear ductility. As an effort to characterize the behavior of SHCC under impact compressive and shear loading, relevant to the mentioned high-speed loading scenarios, the paper at hand studies the performance of a SHCC and its constituent cement-based matrices using the split-Hopkinson bar method. For compression experiments, cylindrical specimens with a length-to-diameter ratio (l/d) of 1.6 were used. The selected length of the sample led to similar failure modes under the quasi-static and impact loading conditions, which was necessary for a reliable comparison of the obtained compressive strengths. The impact experiments were performed in a split-Hopkinson pressure bar (SHPB) at a strain rate that reached 110 s-1 at the moment of failure. For shear experiments, a special adapter was developed for a split-Hopkinson tension bar (SHTB). The adapter enabled performing impact shear experiments on planar specimens using the tensile wave generated in the SHTB. Results showed a dynamic increase factor (DIF) of 2.3 and 2.0 for compressive and shear strength of SHCC, respectively. As compared to the non-reinforced constituent matrix, the absolute value of the compressive strength was lower for the SHCC. Contrarily, under shear loading, the SHCC yielded the higher shear strength than the non-reinforced matrix.

Background: The respiratory syncytial virus infection (RSV) spread has been unusually high during 2022 and increasing trends have been documented We aimed to assess the survival experience of children hospitalized due bronchiolitis by laboratory-confirmed RSV. Methods: A nationwide and retrospective cohort was conducted in Mexico and data from 436 children aged 5 years and younger, with symptoms onset from August 2021 to November 2022, were analyzed. Survivor functions and 95% confidence intervals (CI) were computed by using the Kaplan-Meier method. Results: The survival rates were high, particularly within the first three weeks of admission. The 3-day survival was 99.8% (CI 95% 98.4-99.9%) and went to 98.9% (CI 95% 96.5-99.7%), 97.5% (CI 95% 91.9-99.3%), 86.7% (95% CI 48.2-97.2%), and 69.4% (95% CI 24.2-91.0%) on days 7, 14, 21 and 28 of hospital stay, respectively. We documented 5 fatal outcomes, and the mortality rate was 2.1 per 1,000 person-days. Conclusions: We analyzed a large set of pediatric patients with bronchiolitis by RSV and the presented results contribute to achieving a better understanding of the in-hospital evolution of this disease.

This research delves into a detailed exploration of the thermal decomposition behavior of bio-based polymers, specifically Thermoplastic Starch (TPS) and Poly(lactic acid) (PLA). The study focuses on the impact of three different heating rates under a nitrogen atmosphere, providing comprehensive insights into the thermal stability of these eco-friendly polymers. In particular, the TPS kinetic model is examined, encompassing the decomposition of three distinct fractions. In contrast, PLA exhibits a simplified kinetic behavior requiring only a fraction described by a zero-order model. The kinetic study involves a systematic investigation into the individual contributions of key components within TPS, including starch, glycerin, and polyvinyl alcohol (PVA). This nuanced analysis contributes to a comprehensive understanding of the thermal degradation process of TPS and PLA, enabling the optimization of processing conditions and the prediction of material behavior across varying thermal environments. Furthermore, the incorporation of different starch sources and calcium carbonate additives in TPS enhances our understanding of the polymer's thermal stability, offering insights into potential applications in diverse industries.

Background: By using outcome prediction scores, it is possible to distinguish between good and poor performers with cochlear implants (CI) after CI implantation. The reasons for poor performance, despite good basic conditions, can be manifold. On the one hand, the postoperative fitting may be inadequate; on the other, neurophysiological disease processes may impair speech understanding with a CI. These disease processes are not yet fully understood. In acoustics, it is known that the auditory brainstem responses (ABR) and their latencies and amplitudes allow differential diagnosis based on reference values for normal-hearing individuals. The aim of this study was to provide reference values for electrically evoked brainstem responses (EABRs) in terms of rate-dependent latencies and amplitudes. Methods: 20 experienced adult CI recipients with a predicted and measured good postoperative word recognition score were recruited from the clinic’s patient pool. In the same stimulation mode and intensity we measured latencies and interpeak-latencies of EABRs and electrically evoked compound action potentials (ECAPs). With a defined supra-threshold stimulation intensity above the individual ECAP threshold, we applied stimulation at several rates between 11 and 91 stimuli per second. Results: We found rate dependences for EABR latency t3 and t5 in the order of 0.19 ms and 0.37 ms respectively, while ECAP was not affected by rate. Correspondingly, the interpeak intervalls’ rate dependences for t5-t1, t5-t3 and t3-t1 were of the order of 0.37 ms, 0.18 ms and 0.19 ms. Comparing the EABR amplitudes between the stimulation rates 11/s and 81/s, we found that at 81/s the amplitudes were significantly reduced down: to 73% for A3 and 81% for A5. These rate dependences of latency and amplitude in EABR have characteristics comparable to those of acoustic ABR. Conclusions: These data may serve to provide reference values for EABR and ECAP latencies, interpeak intervals and amplitudes with respect to stimulation rate. Altered response patterns of ECAPs and EABRs to normalised stimulation modes could be used in the future to describe and classify neuropathological processes in a better-differentiated way.

Literature on the use of nutritional supplements (NS) in tennis players is scarce. The objective of the present study was to evaluate NS consumption in a group of men's tennis players who participated in the 2016 Andalusian team championship. A total of 70 questionnaires from 7 different clubs were registered. The questionnaire was previously designed and evaluated through piloting in which the validity of the content, its application, its structure and its presentation were observed. The results showed that 100% of the sample group was in favor of NS consumption within the law, 88.6% claimed to have consumed them at some time and 61.4% presently consume them. The NS most consumed by study participants were sports drinks (69.35%), energy bars (29%), a vitamin complex (19.35%), protein (serum) (17.74%) and creatine (14.51%). A high percentage of NS consumers thought that they had obtained positive results from NS consumption. The percentages and the findings regarding NS consumption in the present study were similar to the contributions made by other studies which evaluated supplementation in athletes, although with some subtle differences.

We focus on macromolecules which are modelled as sequentially growing dual scale-free networks. The dual networks are built by replacing star-like units of the primal treelike scale-free networks through rings, which are then transformed in a small-world manner up to the complete graphs. In this respect, the parameter γ describing the degree distribution in the primal treelike scale-free networks regulates the size of the dual units. The transition towards the networks of complete graphs is controlled by the probability p of adding link between non-neighbouring nodes of the same initial ring. The relaxation dynamics of the polymer networks is studied in the framework of generalized Gaussian structures by using the full eigenvalue spectrum of the Laplacian matrix. The dynamical quantities on which we focus here are the averaged monomer displacement and the mechanical relaxation moduli. For several intermediate values of the parameter’s set (γ, p) we encounter for these dynamical properties regions of constant in-between slope.

COPD is a chronic inflammatory disease characterized by progressive airflow obstruction. Tobacco smoking is the main cause of COPD (COPD-TS), but chronic exposure to biomass smoke (COPD-BS), mainly wood smoke, is the second risk factor; both are considered to cause different phenotypes of COPD. COPD-BS is more eosinophilic than COPD-TS. The objective of the present study was to evaluate the serum level of interleukins involved in eosinophil maturation, recruitment, and survival, and their association with small airway obstruction, measuring cytokines by multiplex test (Bio-Plex) and evaluating the central airway resistance with impulse oscillometry (IOS), comparatively in patients with COPD due to biomass and smoking. The results showed that IL-1ra, IL-2, IL-4, IL-8, IL-9, IL-13, IL-17, and eotaxin were increased in COPD-BS related to COPD-TS. Resistance parameters showed that R5, X5, AX (area reactance), and R5-R20 were significantly higher in COPD-BS than in the COPD-TS group (p < 0.05). R20 was not different between the groups. These data suggest that the cytokines involved in the effect of eosinophils on airway inflammation in COPD-BS were increased compared with COPD-TS, which appears to be related to a predominance of peripheral airway obstruction in patients with COPD-BS more than in COPD-TS

Objectives: This study assessed the performance of a novel fluoride dentifrice containing micro- fibrillated cellulose (MFC) and 7% silica (Protegera™) versus common fluoride dentifrices. Methods: Removal of extrinsic stains was assessed using the pellicle cleaning ratio (PCR) method, and radioactive dentin abrasivity (RDA) was measured, to calculate a cleaning efficiency index (CEI). Fluoride efficacy was evaluated using widely used remineralization and fluoride uptake methods. Results: The MFC dentifrice removed stained pellicle significantly more effectively than the ADA reference material, Crest Cavity Protection™ and Sensodyne Pronamel™, and had equal performance to three known marketed stain-removing dentifrices (Arm & Hammer™ Advanced Whitening, Crest ProHealth™, and Colgate Optic White™). The MFC dentifrice vehicle had a low RDA (88), which was significantly less than Crest ProHealth (166) and Crest 3D-White™ (183). Based on PCR and RDA data, the CEI was 31% greater for the MFC product than for Crest ProHealth. In a 10-day pH cycling study, the fluoride efficacy of the MFC product was superior to a non-fluoridated control and was not significantly different from Sensodyne Pronamel and Crest Cavity Protection. The MFC dentifrice was superior for promoting fluoride uptake into incipient enamel lesions than the USP reference dentifrice. Conclusion: The low dentin abrasivity MFC dentifrice is highly effective in removing stained pellicle, and is an efficacious fluoride source when compared to other relevant commercially available fluoride dentifrices with high dentin abrasivity. Clinical Significance: Including micro-fibrillated cellulose into a fluoride dentifrice may enhance cleaning performance for the removal of external stain, while lowering abrasivity, and providing an effective fluoride source. This combination of benefits seems well suited to enamel protection and caries prevention.

Kratom (Mitragyna speciosa) is a Southeast Asian plant containing various alkaloids which induce pharmacological effects in humans. In Western countries, online vendors sell a variety of different kratom strains which are marketed to have distinct effect profiles. However, as of yet such marketing claims are unsubstantiated, and therefore the current study investigated whether differently colored kratom products can induce unique effects, as self-reported by users. 644 current kratom users were anonymously surveyed to compare the self-reported effects and motivations for using kratom products sold as red, green, and white strains. Most of the survey respondents were customers of the same kratom vendor, the products of which had been assessed for their alkaloid content by an independent laboratory. The survey respondents reported distinct subjective experiences for different kratom strains, in a manner congruent with common marketing descriptions. However, the product analyses revealed no significant cross-strain differences in alkaloid content, suggesting that the reported effect differences might be disproportionally influenced by marketing narratives and anecdotal reports. Future studies should engage a more diverse population and include kratom strains from various vendors. Controlled, blinded experiments could assess whether the reported effect differences stem from a placebo effect or from alternative factors, e.g. minor alkaloids and terpenes.