Foundational and state-of-the-art anomaly detection methods through power system state estimation are reviewed. The traditional components for bad data detection such as chi-square testing, residual-based methods, and hypothesis testing are discussed to explain the motivations for recent anomaly detection methods given the increasing complexity of power grids, energy management systems, and cyber-threats. In particular, state estimation anomaly detection based on data-driven quickest change detection and artificial intelligence are discussed and directions for research are suggested with particular emphasis on considerations of the future smart grid.

In the early decades of the 19th century, the deaf population in the eastern US and Canada was distributed across a vast area. After the 1817 founding of the American School for the Deaf (ASD) in Hartford, CT and the subsequent establishment of schools for the deaf in New York City (NYSD), Philadelphia, and many other US states, hundreds of deaf students called these schools home for several years. After leaving school, the early American Deaf community faced a challenge: How would the community maintain its social and linguistic ties across a vast geographical area once community members had dispersed to their hometowns? In this paper we analyze the attendance registries of two large gatherings of deaf individuals in Hartford in the years 1850 and 1854. These were among the largest and earliest known gatherings of deaf adults. The demographic data included in these registries open a window onto the evolving American Deaf community of the mid-19th century. Our analyses of the attendees’ school affiliations, ages, and marital status show that the signing community that had taken root among students at schools in Hartford and New York persisted among the adult graduates of those schools in towns across the northeastern US. We compare the places of residence of ASD and NYSD alumni in 1850 and 1854 to their hometowns when they first enrolled at school. Our comparisons suggest the mid-19th-century signing community had become more urban; it was centered to a greater extent in populous cities such as New York, Boston, and Hartford than had been true when the attendees had enrolled in school. We consider how the geography of deafness in the 19th century might inform our understanding of the sources of regional variation in ASL. We also consider how early cross-regional interactions may have inhibited such regional variation.

Accurate calculation of non-covalent interaction energies in nucleotides is crucial for understanding the driving forces governing nucleic acid structures and functions, as well as developing advanced molecular mechanics forcefields or machine learning potentials tailored to nucleic acids. Here, we dissect the nucleotides’ structure into three main constituents: nucleobases (A, G, C, T, and U), sugar moieties (ribose and deoxyribose), and phosphate group. The interactions among these fragments and between fragment and water were analyzed. Different quantum mechanical methods were compared for their accuracy in captuing the interaction energy. The non-covalent interaction energy was decomposed into electrostatics, exchange-repulsion, dispersion, and induction using two ab-initio methods: Symmetry-Adapted Perturbation Theory (SAPT) and Absolutely Localized Molecular Orbitals (ALMO). These caculations provide the benchmark for different QM methods while providing valuable understanding of the roles of various interamolecular forces in hydrogen bonding and aromatic stacking.

We suppose that a Cooper pair (CP) will experience a damping force exerted by the condensed matter. A Langevin equation of a CP in two dimensional condensed matter is established. Following a method similar to Nelson's stochastic mechanics, generalized Schr\"{o}dinger equation of a CP in condensed matter is derived. If the CPs move with a constant velocity, then the corresponding direct current (DC) electrical conductivity can be calculated. Therefore, a Drude like formula of resistivity of CPs is derived. We suppose that the damping coefficient of CPs in two dimensional cuprate superconductors is a linear function of temperature. Then the resistivity and scattering rate of CPs turn out to be also linear-in-temperature. The origin of linear-in-temperature resistivity and Planckian dissipation in cuprate superconductors may be the linear temperature dependence of the damping coefficient of CPs.

Herein is introduced a simple scalar field model derived from classical based kinetic energy, gravitational potential energy, and Special Relativity’s rest mass energy. By applying a classical orbit over the scalar field, relativistic effects are predicted. The scalar field is then applied to a classical model of the Hydrogen atom resulting in a relativistic effect equal to the binding energy of the Hydrogen atom. In addition, the model derives the fine structure constant due to the gravitational effect. The relativistic effects are then discretized in increments equal to the model’s gravitational induced constant. The discretization produces the Hydrogen atom spectral emissions and an angular moment equal to Planck’s reduced constant. The model is not presented as a replacement for current theory, rather it is for inspection and illustration of how a simplistic model may offer a fundamental bridge between the more complex, time proven theories of General Relativity and Quantum Mechanics.

Wide bandgap (WBG) power semiconductor devices are increasingly replacing silicon IGBTs in high-power and high-voltage power electronics applications. However, there is a significant gap in the literature regarding efficient testing methodologies for high-power and high-voltage converters under constrained laboratory resources. This paper addresses this gap by presenting comprehensive, hardware-focused testing methodologies for high-power and high-voltage WBG power semiconductor based converters, preceding the control evaluation phase. The proposed methods enable thorough evaluation and evaluation of converter hardware, including device switching characteristics, driving circuit functionality, thermal management performance, insulation integrity, and sustained operation at full power. We utilize the double pulse test (DPT) to characterize switching performance in a two-level phase leg configuration, extract circuit parasitics, and validate magnetic components. The DPT is further applied to optimize gate driving circuits, validate overcurrent protection mechanisms, and measure device on-resistance. Additionally, a multicycle test is introduced to rapidly assess steady-state converter performance and estimate efficiency. Recognizing the critical role of thermal management in high-power converters, our methodologies extend to the experimental extraction of key thermal parameters—such as junction-to-ambient thermal resistance and thermal capacitance—via a heat loss injection method. A correlation method between temperature sensor measurements and junction temperature is presented to enhance the accuracy of device temperature monitoring during tests. To ensure reliability and safety, dielectric withstand tests and partial discharge measurements are conducted at both component and converter levels under conventional 60 Hz sinusoidal and high-frequency PWM waveforms. Finally, we highlight the importance of testing converters under full voltage, current, and thermal conditions through power circulating tests with minimal power consumption, applicable to both non-isolated and isolated high-power converters. Practical examples are provided to demonstrate the effectiveness and applicability of these hardware testing methodologies.

Cutaneous Squamous Cell Carcinoma (cSCC) is an increasingly common malignancy of the skin and the leading cause of death from skin cancer in adults over the age of 85. Fibroblast Growth Factor Receptor 2 (FGFR2) has been identified as an important effector of signaling pathways that lead to the growth and development of cSCC. In recent years, there have been numerous studies evaluating the role FGFR2 plays in multiple cancers, its contribution to resistance to anti-cancer therapy, and new drugs that may be used to inhibit FGFR2. This review will provide an overview of our current understanding of FGFR2 and potential mechanisms in which we can target FGFR2 in cSCC. The goals of this review are the following: 1) to highlight our current knowledge on the role of FGFR2 in healthy skin and contrast this with its role in the development of cancer; 2) to further explain the specific molecular mechanisms that FGFR2 uses to promote tumorigenesis; 3) to describe how FGFR2 contributes to more invasive disease, 4) to describe its immunosuppressive effects in skin, and 5) to evaluate its effect on current anticancer therapy and discuss therapies on the horizon to target FGFR2 related malignancy.

The novelty of this study consists in: i) synthesis and characterization of electrode materials recycled from a spent car battery and doped with MnO2 and CuO by the analysis of X-ray diffraction (XRD), Infrared (IR) and Electron Paramagnetic Resonance (EPR) data and ii) the investigation of electrochemical properties of prepared materials in view of new applications as electrode materials for battery. Electron Paramagnetic Resonance (EPR) data indicate that the intensity of the resonance line corresponding to the Cu+2 ion was modified with the increase of the dopant content. The analysis of X-ray Absorption Spectroscopy (XAS) data indicates that by increasing the dopant content there is a process of ordering the oxygen atoms around the lead similar to the PbO2 theoretical model. The electrochemical performances of the recycled and manganese-copper-doped materials are optimized for applications as new anodic electrode for the car battery.

This qualitative research explores negotiation dynamics within procurement, focusing on strategies, challenges, and outcomes in contemporary business environments. Negotiation in procurement plays a crucial role in shaping organizational strategies, supplier relationships, and operational efficiencies. In a globalized economy characterized by rapid technological advancements and market uncertainties, effective negotiation practices are essential for organizations seeking competitive advantage and sustainable growth. Through semi-structured interviews with procurement professionals, supply chain executives, and industry experts, this study examines the nuanced strategies employed in negotiation processes. Thematic analysis of the data reveals key themes including negotiation strategies (e.g., preparation, flexibility), challenges (e.g., price volatility, regulatory constraints), and outcomes (e.g., cost savings, innovation incentives). Relationship management emerges as pivotal, highlighting the importance of trust, transparency, and mutual respect in fostering collaborative supplier partnerships. The study also explores contextual factors (e.g., organizational culture, industry dynamics) and emotional dimensions (e.g., emotional intelligence, interpersonal dynamics) that influence negotiation effectiveness.

Supplier collaboration and partnership in procurement are essential elements for enhancing organizational efficiency, innovation, and resilience in today's globalized markets. This qualitative study investigates the dynamics of effective supplier relationships, focusing on trust, communication, innovation, quality, cost savings, and resilience as critical factors. Data were gathered through semi-structured interviews, case studies, and document analysis across diverse industries, highlighting insights from procurement professionals and supplier representatives. Key findings underscore the foundational role of trust and communication in fostering successful collaborations. Establishing transparent, ongoing communication channels facilitates mutual understanding, reduces conflicts, and enhances overall satisfaction. Collaborative innovation emerged as pivotal, enabling organizations to pool resources and expertise for product development and process improvement. Quality and reliability were identified as significant outcomes of close partnerships, particularly in industries with stringent standards such as aerospace and healthcare. Furthermore, the study reveals substantial cost savings and efficiency gains through collaborative efforts in process optimization and waste reduction. Effective risk management practices within these partnerships enhance supply chain resilience, enabling organizations to anticipate and mitigate disruptions proactively. Despite these benefits, challenges such as cultural differences, technological integration, and regulatory compliance require strategic mitigation strategies. In conclusion, organizations can optimize supplier collaborations by prioritizing trust-building, fostering a culture of innovation, and investing in robust relationship management practices. This approach not only enhances operational performance but also positions organizations to navigate market uncertainties and achieve sustainable growth in a competitive landscape.

Implementing ethical procurement standards is increasingly recognized as pivotal for organizations aiming to align their practices with principles of social responsibility and sustainability. This qualitative research explores the experiences, challenges, strategies, and impacts associated with ethical procurement across diverse sectors. Motivations for adopting ethical procurement include enhancing corporate reputation, meeting stakeholder expectations, and complying with regulatory frameworks. However, organizations face significant challenges such as balancing ethical considerations with cost-efficiency pressures, navigating complex regulatory landscapes, and ensuring transparency across global supply chains. Strategies for overcoming these challenges emphasize effective supplier relationship management, leveraging technological innovations for transparency, and investing in supplier capacity-building. The study reveals that ethical procurement practices contribute to organizational resilience by improving risk management, enhancing stakeholder engagement, and fostering innovation in procurement processes. Moreover, ethical procurement supports sustainable development goals by promoting environmental sustainability, supporting social equity through fair labor practices, and contributing to economic development. Future research directions include exploring the impact of emerging technologies on ethical procurement, promoting global collaboration for unified standards, and evaluating the long-term sustainability of ethical procurement initiatives.

This qualitative study explores the challenges and successes in supplier development from the perspectives of procurement managers across diverse industries. Through in-depth interviews, key themes emerged, highlighting the critical role of communication, trust, performance measurement, capacity building, risk management, innovation, regulatory compliance, and technology integration in supplier relationship management. Procurement managers emphasized the importance of clear, continuous communication and trust-building activities to align objectives and foster collaborative partnerships. Performance measurement was crucial for evaluating and improving supplier performance, supported by capacity-building initiatives to enhance supplier capabilities. Risk management strategies focused on identifying and mitigating risks, while compliance efforts aimed to ensure adherence to industry standards. Innovation and technological integration were pivotal for driving efficiency and competitiveness, enabling faster time-to-market and improved product quality. Cultural sensitivity and relationship strengthening emerged as essential for navigating diverse cultural contexts and enhancing partnership effectiveness. Overall, the findings underscored positive outcomes including enhanced quality, cost efficiencies, and increased resilience within supply chains. This research contributes valuable insights into effective supplier management practices, emphasizing the strategic importance of supplier development initiatives for sustainable growth and competitive advantage in today's dynamic business environment.

n this article a first attempt at formalizing a new approach to the grand unified theory is introduced. This theory named NUVO is based primarily on considering two aspects of inertia. The first aspect is how a mass couples to space, introducing definitions to distinguish massive particles from massless particles. The second aspect is space’s availability to couple to massive particles. In essence these are the two contributions of inertia; mass and space. Postulates, clarifications, and a mathematical structure are introduced. Part 1 covers the physics of the very large (cos- mic), laying ground work for part two which applies the structure to the very small (quantum). The cosmic application of the theory will show a strong correlation to empirical data and correspondence to General Rela- tivity, including; time dilation, length contraction, and orbital advances. Departing from the canonical findings of General Relativity by predicting a quantization of physical units under the effect of acceleration and or gravity.

This qualitative research investigates sustainable procurement practices, focusing on the integration of environmental and social criteria in supplier evaluation processes. The study explores how organizations, ranging from large multinational corporations to smaller enterprises, navigate sustainability challenges and opportunities within their procurement strategies. Data were gathered through semi-structured interviews with procurement professionals and sustainability managers across diverse industries. Themes identified include varying organizational commitments to sustainability, from structured policies and resource allocation in larger firms to reactive approaches constrained by resource limitations in smaller entities. Effective supplier relationship management emerged as crucial, facilitating collaborative partnerships aimed at improving environmental and social performance across supply chains. Motivations for sustainable procurement practices encompass regulatory compliance and responding to consumer demands for eco-friendly products, shaping procurement decisions to enhance market competitiveness and stakeholder satisfaction. Environmental and social criteria integration in supplier evaluations highlighted strategies such as lifecycle assessments and sustainable sourcing practices, aimed at minimizing environmental footprints and promoting ethical labor practices. Benefits included cost savings and enhanced brand reputation, tempered by challenges such as higher procurement costs and supplier resistance. Leadership commitment and organizational culture were identified as critical enablers of sustainable procurement, influencing strategic alignment and fostering a culture of sustainability within organizations. The study underscores the transformative potential of sustainable procurement in achieving organizational resilience and contributing to global sustainability goals.

Agile procurement has emerged as a transformative strategy for organizations striving to maintain competitiveness in a rapidly evolving marketplace. This qualitative research investigates the implementation, benefits, challenges, and outcomes of agile procurement practices in supply chain management. Through semi-structured interviews and case studies across diverse industries, this study explores how agile procurement enhances organizational adaptability and responsiveness. Key findings reveal that agile procurement enables organizations to swiftly adjust strategies in response to market fluctuations and customer demands, fostering increased customer satisfaction and loyalty. The integration of advanced technologies, including AI and blockchain, facilitates real-time data analysis, optimizing procurement processes and enhancing supply chain efficiency. Organizational culture emerges as a critical factor in successful agile procurement, with leadership support and a collaborative environment driving cultural change towards agility and innovation. Despite its benefits, challenges such as resistance to change and the need for significant technology investments are identified, requiring careful change management and strategic alignment. Case studies illustrate the versatility of agile procurement across sectors, showcasing its role in enhancing operational efficiencies, innovation capabilities, and overall supply chain performance. In conclusion, agile procurement offers organizations a strategic framework to navigate complexities and uncertainties effectively, capitalizing on market opportunities while mitigating risks. Embracing agile principles fosters a resilient organizational culture capable of adapting to dynamic market conditions. Future research should focus on further refining agile procurement strategies to address emerging challenges and sustain competitive advantage in the global marketplace.

Apoptosis, the programmed and intentional death of senescent, damaged, or otherwise superfluous cells, is the natural end-point for most cells within multicellular organisms. Apoptotic cells are not inherently damaging, but if left unattended they can lyse through secondary necrosis. The resulting release of intracellular contents drives inflammation in the surrounding tissue and can lead to autoimmunity. These negative consequences of secondary necrosis are avoided by efferocytosis—the phagocytic clearance of apoptotic cells. Efferocytosis is a product of both apoptotic cell and efferocyte mechanisms, which cooperate to ensure the rapid and complete removal of apoptotic cells. Herein, the processes used by apoptotic cells to ensure their timely removal, and the receptors, signaling, and cellular processes used by efferocytes to identify, remove, and process the apoptotic cells, are reviewed.

From 1964 to the early 1970s, Orson Anderson led a research program at the Lamont Geological Observatory in the newly-emerging field of “mineral physics”. In collaboration with colleagues Edward Schreiber and Naohiro Soga, Orson exploited the techniques of physical acoustics to study the behavior of the sound velocities of minerals at elevated pressures and temperatures. This research program also included semi-empirical studies of relationships between the bulk modulus and the molar volume of solids and the use of lattice dynamics to calculate the elastic moduli of cubic structures as a function of pressure to predict instabilities, as well as theoretical investigations of the Lagrangian vs. Eulerian formulations of finite strain equations of state.

The Flack Parameter is now almost universally reported for all chiral materials characterized by X-ray crystallography. It’s elegantly simplicity was an inspired development by Flack, and although the original algorithm for its computation has been strengthened by other workers, it remains an essential outcome for any crystallographic structure determination. As with any one-parameter metric, it needs to be interpreted in the context of its standard uncertainty.

Multiple myeloma (MM) is a common type of cancer that unfortunately leads to a significant number of deaths each year. The majority of the reported MM cases are detected in the advanced stages, posing significant challenges for treatment. Additionally, all MM patients eventually develop resistance or experience relapse, therefore advances in treatment are needed. However, developing new anti-cancer drugs, especially for MM, requires significant financial investment and a lengthy development process. The study of drug repurposing involves exploring the potential of existing drugs for new therapeutic uses. This can significantly reduce both time and costs, which is typically a major concern for MM patients. The utilization of pre-existing non-cancer drugs for various myeloma treatments presents a highly efficient and cost-effective strategy, considering their prior preclinical and clinical development. The drugs have shown promising potential in targeting key pathways associated with MM progression and resistance. Thalidomide exemplifies the success that can be achieved through this strategy. This review delves into the current trends, the challenges faced by conventional therapies for MM, and the importance of repurposing drugs for MM. This review highlights a noncomprehensive list of conventional therapies that have potentially significant anti-myeloma properties and anti-neoplastic effects. Additionally, we offer valuable insights into the resources that can help streamline and accelerate drug repurposing efforts in the field of MM.

The ability to simulate realistically the electronic structure of superconducting materials is important to understand and predict various properties emerging in both the superconducting topological and spintronics realms. We introduce a tight-binding implementation of the Bogoliubov-de Gennes method, parameterized from density functional theory, which we utilize to explore the bulk and thin films of Nb, known to host a significant superconducting gap. The latter is useful for various applications such as the exploration of trivial and topological in-gap states. Here, we focus on the simulations aspects of superconductivity and study the impact of temperature, Cooper-pair coupling and dimensionality on the size of the superconducting order parameter.

This qualitative study explores the pivotal role of trust in supplier relationships from the perspectives of procurement professionals. Through in-depth interviews with diverse industry stakeholders, the research examines the multifaceted nature of trust, its antecedents, dynamics, challenges, and strategic implications within modern supply chain management. Trust is conceptualized as a cornerstone that fosters collaborative exchanges, mitigates risks, and enhances organizational resilience in a competitive global marketplace. Findings highlight key factors influencing trust formation, including effective communication, ethical conduct, relationship history, transparency, and cultural alignment. Challenges such as perceived opportunism, communication breakdowns, and regulatory compliance issues are identified as barriers requiring proactive management strategies. Strategies for building and maintaining trust emphasize proactive engagement, transparent decision-making, performance evaluation, mutual benefit alignment, and effective conflict management. The study further explores the impact of trust on procurement decisions, supplier performance, innovation capabilities, cost efficiencies, and long-term sustainability. Practically, the research underscores the importance of integrating trust-building initiatives into supplier relationship management strategies to optimize operational efficiencies, foster innovation, and achieve sustainable growth. By aligning procurement practices with supplier capabilities and market dynamics, organizations can navigate complexities, seize opportunities, and enhance strategic partnerships that drive mutual value creation. Future research directions include exploring emerging trends such as digitalization, sustainability, and ethical considerations in trust-based supply chain interactions.

This qualitative study investigates the influence of organizational culture on procurement practices across multiple industries, aiming to enrich understanding of how cultural dynamics shape decision-making, supplier relationships, and strategic outcomes within procurement departments. Through semi-structured interviews with procurement professionals, organizational leaders, and industry experts, data were gathered to explore the impact of leadership styles, ethical frameworks, industry dynamics, and external influences on procurement strategies. Findings reveal that transformational leadership fosters innovation, strategic alignment, and long-term partnerships in procurement, whereas transactional and autocratic styles may prioritize cost efficiency over broader strategic goals. Ethical cultures within organizations significantly influence supplier selection criteria and procurement decisions, highlighting the importance of integrating ethical standards consistently to mitigate risks and enhance organizational reputation. Industry-specific dynamics necessitate adaptive procurement strategies tailored to technological advancements, regulatory requirements, and market conditions. Effective supplier relationship management practices, emphasizing trust, transparency, and mutual value creation, enhance procurement effectiveness and resilience. Organizational structures, including centralized, decentralized, and hybrid models, play crucial roles in optimizing procurement operations. Learning cultures promoting continuous improvement and knowledge sharing foster innovation and resilience in procurement practices. External factors such as market volatility, regulatory changes, and geopolitical risks underscore the need for adaptive procurement strategies and robust risk management practices. This study contributes to theoretical insights and practical implications for aligning organizational culture with strategic procurement objectives to optimize effectiveness, mitigate risks, and drive sustainable value creation across supply chains.

Supplier diversity initiatives in procurement have emerged as strategic imperatives for organizations aiming to enhance competitiveness and foster socio-economic equity. This research investigates the impact of supplier diversity initiatives across various industries, analyzing implementation strategies, challenges, and outcomes through a mixed-methods approach. Qualitative data, including interviews with procurement professionals and case studies of exemplary organizations, reveal diverse approaches to implementing supplier diversity—from formalized programs with dedicated resources to ad hoc initiatives driven by regulatory compliance or social responsibility goals. Challenges identified include the identification and qualification of diverse suppliers, scalability issues, and internal resistance within procurement teams. Quantitative analysis of survey data highlights positive impacts on organizational performance metrics, such as procurement spend allocation towards diverse suppliers, supplier-driven innovation, and enhanced supply chain resilience. Best practices in successful supplier diversity programs underscore strategic alignment with overall procurement strategies, effective supplier relationship management, and strong leadership commitment. Socio-economic impacts encompass economic inclusion, community engagement, and skills development among diverse supplier networks, contributing to local economic growth and broader social benefits. Despite these benefits, challenges remain in measuring qualitative outcomes and overcoming systemic barriers to implementation. Cultivating an inclusive organizational culture and leveraging leadership support are crucial for sustaining supplier diversity efforts. Continued collaboration and innovation in supplier diversity practices are recommended to maximize benefits and drive meaningful socio-economic impact globally.

This qualitative study explores supplier selection criteria from the perspectives of procurement professionals across diverse industries. Supplier selection is crucial for organizational efficiency and performance, influenced by factors beyond traditional cost considerations. The research aims to uncover nuanced criteria such as quality assurance, supplier reliability, innovation capability, sustainability practices, strategic alignment, relational dynamics, and risk management strategies. These criteria reflect a shift towards holistic evaluation frameworks that integrate economic, social, and environmental dimensions in procurement decision-making. Methodologically, the study employed semi-structured interviews with 30 procurement professionals, ensuring depth and diversity in perspectives. Thematic analysis was used to identify recurring themes and patterns, illuminating the complexities and strategic importance of supplier selection processes. Findings highlight the strategic role of suppliers in driving innovation, enhancing supply chain resilience, and supporting organizational goals. Moreover, the study underscores the significance of sustainable sourcing practices, ethical considerations, and effective supplier relationships in fostering long-term partnerships and mitigating operational risks. Practical implications suggest that organizations should adopt integrated approaches to supplier selection, leveraging data-driven insights and technological advancements to optimize decision-making. By prioritizing strategic alignment, fostering collaborative partnerships, and implementing robust risk management strategies, organizations can navigate uncertainties, capitalize on market opportunities, and sustain competitive advantage.

This qualitative study explores the intricate impact of cultural differences on global procurement practices within multinational supply chains. Cultural dimensions profoundly influence communication dynamics, negotiation strategies, decision-making processes, and supplier relationship management in diverse global contexts. Effective cross-cultural communication is crucial for fostering trust and clarity across different cultural norms, while negotiation strategies vary based on cultural preferences for collaboration or competition. Decision-making processes are shaped by cultural attitudes towards risk tolerance, time orientation, and decision authority, influencing procurement agility and resilience. Strategic implications of cultural diversity include opportunities for innovation and localized adaptation in procurement practices, tempered by challenges such as adaptation costs and regulatory compliance. Emotional intelligence (EI) emerges as pivotal in navigating cultural complexities, enhancing stakeholder engagement, conflict resolution, and collaborative partnerships critical for sustainable procurement practices in multicultural settings. Economic factors, including stability, currency fluctuations, and market volatility, impact procurement strategies and supply chain resilience, necessitating proactive risk management and adaptive approaches. Barriers to growth in global procurement, such as regulatory complexities and geopolitical risks, require strategic planning, stakeholder collaboration, and infrastructural investments for operational continuity. By understanding and addressing cultural influences, multinational corporations can enhance cross-cultural competence, strategic decision-making, and capitalize on global market opportunities. This study contributes insights and recommendations to enhance procurement effectiveness and competitiveness in an interconnected global economy, supporting ongoing efforts to optimize global procurement practices.

This qualitative research explores the integration of sustainability into procurement practices through the perspectives of supply chain practitioners. The study examines key challenges, strategies, and perceived benefits associated with sustainable procurement across diverse industries. Data were collected via semi-structured interviews with purposively sampled participants renowned for their expertise in procurement and sustainability. Thematic analysis revealed that while regulatory compliance, supplier engagement, and cost considerations pose significant challenges, strategies such as collaborative partnerships, embedding sustainability criteria into procurement contracts, and leveraging technology are pivotal in promoting sustainable procurement. Participants highlighted benefits including enhanced brand reputation, improved operational efficiencies, and strengthened stakeholder trust. Leadership commitment and organizational culture emerged as critical drivers of successful sustainable procurement initiatives, influencing employee engagement and organizational resilience. Looking forward, emerging trends such as circular economy principles and the integration of sustainability into corporate strategies are identified as transformative for future procurement practices. The study underscores the strategic importance of sustainability in enhancing organizational resilience, mitigating risks, and creating long-term economic, environmental, and social value. By addressing challenges, leveraging effective strategies, and embracing emerging trends, organizations can position themselves as leaders in sustainable procurement, contributing positively to global sustainability goals and gaining competitive advantage.

This qualitative study explores the multifaceted strategies organizations employ to build resilient supply chains through effective procurement risk management. Conducted over a six-month period in 2024, the research involved semi-structured interviews with 25 industry professionals from sectors including manufacturing, retail, healthcare, and technology, alongside document analysis and case studies. The study identifies four key themes: risk identification and assessment, supplier relationship management, digitalization in risk management, and strategic resilience practices. The findings reveal that organizations face diverse risks, including supplier, supply market, and external environmental risks, necessitating comprehensive risk assessment methodologies. Supplier relationship management emerges as a critical factor in mitigating risks, with practices such as regular audits, collaborative risk management, long-term partnerships, and supplier diversification being crucial. The adoption of digital technologies like predictive analytics, blockchain, advanced analytics, and artificial intelligence enhances risk management capabilities, providing data-driven insights and fostering transparency. Strategic resilience practices, including inventory buffering, flexible sourcing, redundancy, and scenario planning, are essential for maintaining supply chain continuity amidst disruptions. The study underscores the importance of an integrated and proactive approach to procurement risk management that leverages robust assessment, strong supplier relationships, digital tools, and strategic planning. These findings contribute to a deeper understanding of how organizations can effectively manage procurement risks and build resilient supply chains in a dynamic global environment. The insights offer valuable guidance for procurement professionals and organizational leaders in developing resilient and adaptable supply chain strategies to navigate the complexities of today's market.

Strategic procurement practices within global supply chains are crucial for organizations aiming to navigate complex challenges and achieve sustainable competitive advantage. This qualitative research explores how procurement has evolved from a cost-centric function to a strategic enabler of broader organizational objectives, including risk management, sustainability, and innovation. Through semi-structured interviews with procurement managers and supply chain executives across diverse industries, the study investigates key themes such as supplier relationship management, technological integration, and the impact of sustainability considerations on procurement decision-making. Findings indicate that effective procurement strategies, such as strategic sourcing and collaborative supplier partnerships, are pivotal in enhancing supply chain resilience and operational efficiency. Technological advancements, particularly artificial intelligence and big data analytics, are transforming procurement operations by optimizing processes and enhancing decision-making capabilities. However, the study identifies significant challenges, including regulatory complexities, geopolitical uncertainties, and internal resistance to change, which require adaptive approaches to procurement management. Sustainability emerges as a critical driver, with organizations adopting ethical sourcing practices, reducing carbon footprints, and promoting supplier diversity to meet environmental and social responsibility goals. Leadership qualities such as visionary thinking and emotional intelligence are essential for navigating these challenges and driving innovation within procurement practices. Overall, this research contributes to a deeper understanding of strategic procurement's role in organizational strategy and offers practical insights for enhancing procurement effectiveness and resilience in a competitive global market landscape.

This qualitative research explores the role of digital transformation in procurement through insights gathered from interviews with industry leaders. Digital technologies such as Robotic Process Automation (RPA), Big Data Analytics, Artificial Intelligence (AI), and Blockchain are examined for their impact on operational efficiency, strategic procurement management, supplier relationships, and sustainability practices. Findings reveal that these technologies streamline processes, enhance decision-making capabilities, and improve transparency, thereby enabling organizations to achieve greater agility and competitive advantage. Strategic factors including leadership commitment, strategic investments, and digital skills development emerge as crucial for navigating challenges such as organizational resistance, data security, and integration complexities. The study underscores the transformative potential of digital transformation in procurement, emphasizing its role in driving innovation, fostering sustainability, and aligning procurement practices with broader organizational goals. Looking forward, the research suggests that organizations must continue to innovate and adapt to technological advancements to maintain resilience and leadership in a digital economy. By integrating digital strategies effectively, organizations can enhance operational efficiencies, strengthen supplier relationships, and promote ethical business practices, ultimately positioning themselves for sustained success.

This study investigates how organizations adapt their procurement practices in response to supply chain disruptions, aiming to enhance resilience and ensure operational continuity. Through qualitative research involving interviews with procurement professionals and industry experts, the study identifies key adaptive strategies employed by organizations, including supplier diversification, enhanced inventory management, digital transformation, supplier collaboration, and contingency planning. These strategies are explored in depth, highlighting their implementation challenges and the outcomes achieved. Despite facing obstacles such as financial constraints, technological barriers, and supplier resistance, organizations have demonstrated a proactive approach in leveraging these strategies to mitigate risks and improve supply chain resilience. The findings reveal that adaptive procurement strategies have led to significant outcomes, including strengthened supplier relationships, increased operational efficiency, better risk management, and competitive advantage. These outcomes underscore the strategic importance of agility, technological integration, collaborative partnerships, and effective leadership in responding to disruptions and maintaining competitiveness. The study also discusses implications for practice and policy, emphasizing the need for continued investment in technology, collaboration, and resilience-building initiatives across supply chains. Overall, this research contributes to the understanding of how organizations can adapt and innovate in the face of dynamic supply chain challenges, providing insights that can guide future research and inform strategic decision-making in procurement and supply chain management.

This study investigates the adoption of emerging technologies in procurement within supply chain management, focusing on the transformative potential of artificial intelligence (AI) and blockchain. Through a qualitative approach, involving semi-structured interviews with procurement professionals and technology experts, the study explores how these technologies enhance operational efficiency, optimize inventory management, and improve supply chain transparency and trust. AI-driven predictive analytics were found to significantly enhance demand forecasting, inventory optimization, and supplier performance evaluation, fostering data-driven decision-making and proactive risk management. Blockchain technology ensures secure and transparent transactions, facilitating compliance with ethical sourcing standards and reducing risks associated with counterfeit goods. Despite these benefits, organizations face substantial challenges in adopting these technologies, including data security concerns, integration complexities with existing IT infrastructure, and skills shortages in AI and blockchain expertise. Leadership commitment and organizational readiness are identified as crucial enablers for overcoming these barriers and driving successful technology adoption. The study also highlights the strategic importance of supplier relationship management, emphasizing how emerging technologies enhance real-time collaboration, performance insights, and contractual transparency. By addressing these challenges and leveraging technological innovations strategically, organizations can achieve sustainable growth, resilience, and competitive advantage in an increasingly digital and interconnected global economy. The findings contribute to advancing knowledge on procurement innovation and offer valuable insights for organizations seeking to navigate the complexities of technology-driven procurement practices. Future research directions may explore the long-term impact of technology adoption on supply chain dynamics, sustainability initiatives, and organizational performance.

B lymphocyte development has two DNA recombination processes: V(D)J recombination of the immunoglobulin (Igh) gene variable region and class switching of the Igh constant regions from IgM to IgG, IgA, or IgE. V(D)J recombination is required for successful maturation of B cells from pro-B to pre-B to immature-B and then to mature B cells in the bone marrow. CSR occurs outside of the bone marrow when mature B cells migrate to peripheral lymphoid organs, such as spleen and lymph nodes. Both V(D)J recombination and CSR depend on an “open chromatin” state that makes DNA accessible to specific enzymes, recombination activating gene (RAG), and activation-induced cytidine deaminase (AID). Acetyltransferases GCN5 and PCAF possess redundant functions acetylating histone H3 lysine 9 (H3K9). Here, we generated a mouse model that lacks both GCN5 and PCAF in B cells. We found that double-deficient mice possess low levels of mature B cells in the bone marrow and peripheral organs, an accumulation of pro-B cells in bone marrow, and reduced CSR levels. We conclude that both GCN5 and PCAF are required for B cell development in vivo.

In the last two decades, the discovery of various pathways involved in renal cell carcinoma (RCC) have led to the development of biologically-driven targeted therapies. Hypoxia inducible factors (HIFs), angiogenic growth factors, von Hippel-Lindau (VHL) gene mutations and oncogenic miRNAs play essential roles in the pathogenesis and drug resistance of clear cell renal cell carcinoma. These insights have led to the development of VEGF inhibitors, mTOR inhibitors and immunotherapeutic agents which have significantly improved outcomes of patients with advanced RCC. HIF inhibitors will be a valuable asset in the growing therapeutic armamentarium of RCC. Various histone deacetylase (HDAC)inhibitors, including selenium and agents such as PT2385 and PT2977, are being explored in various clinical trials as potential HIF inhibitors to ameliorate the outcomes of RCC patients. In this article, we will review the current treatment options and highlight the potential role of selenium in the modulation of drug resistance biomarkers expressed in ccRCC tumors.

A novel electrophoretic technique to improve the sensing capabilities of charged particles in solution is presented. The proposed technique may improve the ability of metasurfaces to sense charged particles in solution by forcing them to preferentially sediment within metasurface regions of greatest sensitivity. Such a technique may be useful in various sensing applications, such as in biological, polymer, or environmental sciences, where low concentration particles in solution are of interest. The electrophoretic technique was simulated and experimentally tested using latex nanoparticles in solution. The results suggest that, using this technique, one may theoretically increase the particle density within the metasurface regions of greatest sensitivity by nearly 1900% in comparison to random sedimentation due to evaporation. Such an increase in particle density within the regions of greatest sensitivity may facilitate more precise material property measurements and enhance identification and detection capabilities of metasurfaces to low concentration particles in solution. It was experimentally verified that the electrophoretic technique enabled the preferential gathering of latex nanoparticles within the most sensitive metasurface regions, resulting in 900% - 1700% enhancements in metasurface sensing capabilities.

In recent years, a range of problems under the broad umbrella of computer vision based analysis of ancient coins have been attracting an increasing amount of attention. Notwithstanding this research effort, the results achieved by the state of the art in published literature remain poor and far from sufficiently well performing for any practical purpose. In the present paper we present a series of contributions which we believe will benefit the interested community. We explain that the approach of visual matching of coins, universally adopted in existing published papers on the topic, is not of practical interest because the number of ancient coin types exceeds by far the number of those types which have been imaged, be it in digital form (e.g., online) or otherwise (traditional film, in print, etc.). Rather, we argue that the focus should be on understanding the semantic content of coins. Hence, we describe a novel approach—to first extract semantic concepts from real-world multimodal input and associate them with their corresponding coin images, and then to train a convolutional neural network to learn the appearance of these concepts. On a real-world data set, we demonstrate highly promising results, correctly identifying a range of visual elements on unseen coins with up to 84% accuracy.

All living cells maintain a charge distribution across their cell membrane (membrane potential) by carefully controlled ion fluxes. These bioelectric signals regulate cell behavior (such as migration, proliferation, differentiation) as well as higher-level tissue and organ patterning. Thus, voltage gradients represent an important parameter for diagnostics as well as a promising target for therapeutic interventions in birth defects, injury, and cancer. However, despite much progress in cell and molecular biology, little is known about bioelectric states in human stem cells. Here, we present simple methods to simultaneously track ion dynamics, membrane voltage, cell morphology, and cell activity (pH and ROS), using fluorescent reporter dyes in living human neurons derived from induced neural stem cells (hiNSC). We developed and tested functional protocols for manipulating ion fluxes, membrane potential, and cell activity, and tracking neural responses to wounding and re-innervation in vitro. Finally, using morphology sensor, we tested and quantified the ability of physiological actuators (neurotransmitters and pH) to manipulate nerve wound re-innervation. These methods are not specific to a particular cell type and should be broadly applicable to the study of bioelectrical controls across a wide range of combinations of models and endpoints.

The ocean’s mixed layer depth (MLD) plays an important role in understanding climate dynamics, especially during extreme weather occurrences like hurricanes. This study investigates the effects of Hurricane Katrina (2005) on the MLD in the Gulf of Mexico, using the Delft3D modeling system. By integrating hydrodynamics and wave dynamics modules, we simulate the ocean’s response to extreme weather, focusing on temperature, salinity and MLD variations. Our analysis reveals significant cooling and mixing induced by Katrina, resulting in spatial and temporal fluctuations in temperature (~± 4°C) and salinity (~± 2.5 ppt). The MLD is estimated using a simple threshold method, revealing a substantial deepening to ~120 m on August 29th-30th during Hurricane Katrina in the middle of northern Gulf of Mexico, compared to an average MLD of ~20-40 m during pre-storm conditions. It took about 18-days to recover to ~84% of the pre-storm level after Katrina. Compared to the stand-alone FLOW model, the coupled FLOW+WAVE model yields a deeper MLD of ~5%. The MLD recovery and wave effect on the MLD provide insights from various scientific, environmental and operational perspectives, offering a valuable basis for ocean management, planning and applications, particularly during extreme weather events.

Sorting nexins (SNXs) are a highly conserved membrane-associated protein family that plays a role in regulating protein homeostasis. This family of proteins is unified by their characteristic phox (PX) phosphoinositides binding domain. Along with binding to membranes, this family of SNXs also comprises a diverse array of protein-protein interaction motifs that are required for cellular sorting and protein trafficking. SNXs play a role in maintaining the integrity of the proteome which is essential for regulating multiple fundamental processes such as cell cycle progression, transcription, metabolism, and stress response. To tightly regulate these processes proteins must be expressed and degraded in the correct location and at the correct time. The cell employs several proteolysis mechanisms to ensure that proteins are selectively degraded at the appropriate spatiotemporal conditions. SNXs play a role in ubiquitin-mediated protein homeostasis at multiple levels including cargo localization, recycling, degradation, and function. In this review, we will discuss the role of SNXs in three different protein homeostasis systems: endocytosis lysosomal, the ubiquitin-proteasomal, and the autophagy-lysosomal system. The highly conserved nature of this protein family by beginning with the early research on SNXs and protein trafficking in yeast and lead into their important roles in mammalian systems. Underlying the importance of SNXs in protein homeostasis, genetic defects in SNXs have been linked with a variety of human diseases such as cancer, cardiovascular disease, neurogenerative disease, and viral infections.

The Greenland Ice Sheet is now the largest land ice contributor to global sea level rise, largely driven by increased surface meltwater runoff from the ablation zone, i.e. areas of the ice sheet where annual mass losses exceed gains. This small but critically important area of the ice sheet has expanded in size by ~50% since the early 1960s, and satellite remote sensing is a powerful tool for monitoring the physical processes that influence its surface mass balance. This review synthesizes key remote sensing methods and scientific findings from satellite remote sensing of the Greenland Ice Sheet ablation zone, covering progress in 1) radar altimetry, 2) laser (lidar) altimetry, 3) gravimetry, 4) multispectral optical imagery and, 5) microwave and thermal imagery. Physical characteristics and quantities examined include surface elevation change, gravimetric mass balance, reflectance, albedo, and mapping of surface melt extent and glaciological facies and zones. The review concludes that future progress will benefit most from methods that combine multi-sensor, multi-wavelength, and cross-platform datasets designed to discriminate the widely varying surface processes in the ablation zone. Specific examples include fusing laser altimetry, radar altimetry, and optical stereophotogrammetry to enhance spatial measurement density, cross-validate surface elevation change, and diagnose radar elevation bias; fusing optical imagery, radar imagery, and microwave scatterometry to discriminate between snow, liquid water, refrozen meltwater, and bare ice near the equilibrium line altitude; combining optical reflectance with laser altimetry to map supraglacial lake, stream, and crevasse bathymetry; and monitoring the inland migration of snowlines, surface melt extent, and supraglacial hydrologic features.

Fibromyalgia (FM) is a chronic central sensitivity syndrome characterized by augmented pain processing at diffuse body sites and presents as a multimorbid clinical condition. Long COVID (LC) is a heterogenous clinical syndrome that affects 10-20% of individuals following COVID-19 infection. FM and LC shares similarities with regards to the pain and other clinical symptoms experienced, thereby posing a challenge for accurate diagnosis. This research explores the feasibility of using surface enhanced Raman spectroscopy (SERS) combined with soft independent modelling of class analogies (SIMCA) to develop classification models differentiating LC and FM. Venous blood samples were collected using two supports, dried bloodspot cards (DBS, n= 48 FM and n= 46 LC) and volumetric absorptive micro sampling tips (VAMS, n= 39 FM and n= 39 LC). A semi-permeable membrane (10 kDa) was used to extract low molecular fraction (LMF) from the blood samples, and Raman spectra was acquired using SERS with gold nanoparticles (AuNPs). Soft Independent Modelling of Class Analogy (SIMCA) models developed with spectral data of blood samples collected in VAMS tips showed superior performance with a validation performance of 100% accuracy, sensitivity, and specificity achieving an excellent classification accuracy of 0.86 area under the curve (AUC). Amide groups, aromatic and acidic amino acids were responsible for the discrimination patterns among FM and LC syndromes, emphasizing the findings from our previous studies. Overall, our results demonstrate the ability of AuNPs SERS to identify unique metabolites that can be potentially used as spectral biomarkers to differentiate FM and LC.

Previous reviews by the authors [1, 2] indicate the continuing development and improvement of thermal protective systems through the introduction of polymer nanocomposites into polymer matrix composites. These materials perform as thermal protective systems for a variety of aerospace applications, such as thermal protection systems (TPS), solid rocket motors (SRM) nozzles, internal insulation of SRM, leading edges of hypersonic vehicles, and missile launch structures. A summary of the most recent, global technical research is presented. Polymeric resin systems continue to emphasize phenolic resins and other materials. New high-temperature organic resins based on phthalonitrile (PN), and polysiloxane are described and extend the increased temperature range of resin matrix systems.

Our search of existing cancer databases aimed to assess the current landscape and identify key needs. We analyzed 71 databases, focusing on genomics, proteomics, lipidomics, and glycomics. We found a lack of cancer-related lipidomic and glycomic databases, indicating a need for further development in these areas. Proteomic databases dedicated to cancer research were also limited. To assess overall progress, we included human non-cancer databases in proteomics, lip-idomics, and glycomics for comparison. This provided insights into advancements in these fields over the past eight years. We also analyzed other types of cancer databases, such as clinical trial databases and web servers. Evaluating user-friendliness, we used the FAIRness principle to assess findability, accessibility, interoperability, and reusability. This ensured databases were easily accessible and usable. Our search summary highlights significant growth in cancer databases while identifying gaps and needs. These insights are valuable for researchers, clinicians, and database developers, guiding efforts to enhance accessibility, integration, and usability. Addressing these needs will support advancements in cancer research and benefit the wider cancer community.

A comprehensive design framework is proposed for optimizing sparse MIMO (multiple-input, multiple-output) arrays to enhance multi-target detection. The framework emphasizes efficient utilization of antenna resources, including strategies for minimizing inter-element mutual coupling and exploring alternative grid-based sparse array (GSA) configurations by efficiently separating interacting elements. Alternative strategies are explored to enhance angular beamforming metrics, including beamwidth (BW), peak-to-sidelobe ratio (PSLR), and grating lobe limited field of view. Additionally, a set of performance metrics is introduced to evaluate virtual aperture effectiveness and beamwidth loss factors. The study employs the desirability function and explores optimization strategies for the partial sharing of antenna elements in multi-mode radar applications. A novel machine learning initialization approach is introduced for rapid convergence. Observations include the potential for peak-to-sidelobe ratio (PSLR) reduction in dense arrays and insights into GSA feasibility and performance compared to uniform arrays. The study validates the efficacy of the proposed framework through simulated and measured results. The study underscores the importance of effective sparse array processing in multi-target scenarios and highlights the advantages of the proposed design framework, offering clarity on sparse array efficiency and applicability in processing hardware providing clarity on its advantages over uniform and nonuniform arrays.

A novel technique using a W-band metasurface for the purpose of transmissive fine powder layer sensing is presented. The proposed technique may allow for the detection, identification, and characterization of inhomogeneous ultrafine powder layers which are effectively hundreds of times thinner than the incident wavelengths used to sense them. Such a technique may be useful during personnel screening processes (i.e., at an airport) and in industrial manufacturing environments where early detection and quantization of harmful airborne particulates can be a matter of security or safety. To our knowledge, the requisite science involved in such a novel W-band metasurface sensing technique has not been fully explored.

In this study, we explored the application of deep learning techniques for credit card fraud detection, aiming to improve the performance and reliability of anomaly detection methods in financial transactions. We first utilized the Isolation Forest algorithm, achieving a detection accuracy of 26% for the top 1000 transactions. Subsequently, we experimented with the Autoencoder algorithm, an unsupervised deep neural network model, which enhanced the detection accuracy to 33.6% in the best case despite some fluctuations. The results demonstrate deep learning models' strong feature extraction capability and adaptability, highlighting their potential to surpass traditional methods. However, the high imbalance in the dataset, with only 0.17% of transactions being fraudulent, poses a significant challenge. This study underscores the necessity for further experimentation and optimization of network structures and hyperparameters to achieve more stable and efficient fraud detection. The findings provide valuable insights and reference points for future research in financial fraud detection using deep learning methodologies.

The elevated or depressed transition temperatures observed in cuprate and pnictide superconductors and other exotic superconductors pose a challenge in the context of explaining them through the traditional Bardeen-Cooper-Schrieffer (BCS) models of superconductivity. A significant obstacle in understanding this phenomenon can be addressed by considering an alternative electron distribution. Our investigation has identified an anyonic distribution, where the occupancy of a site created by removing a hole is filled by an electron. In heavy fermion superconductors (HFSs) block spins must be included in the distribution. The interplay, that is, resonance between superconducting electrons within the conventional BCS framework and independent charge density waves (CDWs) might contribute to driving the high-transition-temperature superconductors (HTSCs).

Emerging data support associations between depletion of the healthy gut microbiome and aging-related physiological decline and disease. In humans, fecal microbiota transplantation (FMT) has been used successfully to restore gut microbiome structure and function to treat C. difficile infections, but application to healthy aging has been scarcely investigated. The marmoset is an excellent model for evaluating microbiome-mediated changes with age and interventional treatments due to their relatively shorter lifespan and many social, behavioral, and physiological functions that mimic human aging. This review 1) provides an overview of the rationale for FMT to support healthy aging using the marmoset as a translational geroscience model, 2) summarizes prior use of FMT in marmosets, 3) outlines a protocol for studying FMT in aging marmosets, and 4) describes knowledge gaps and future research needs in this field.

Let a,b,c be positive integers such that a²+b²=c², 2|b,gcd(a,b)=1. In 1956, Jesmanowicz conjectured that for any positive integer w, the only solution of (aw)^x+(bw)^y=(cw)^z in positive integers is (x, y, z) = (2, 2, 2). In this paper, based on Gaussian integer ring, we show that Je$\acute{s}$manowicz' conjecture is true for any positive integer

Despite the increase of seminary training, Black clergywomen continuously undergo subjugation, degradation, and humiliation in ministry leadership due to gender and race bias (Leslie, 2013) by clergymen. This article reports the findings of a qualitative study that examined the experiences of Black clergywomen regarding obstacles in ministry leadership and how these clergywomen ascribed meaning to their experiences. The two primary research questions were, “What are the experiences of Black clergywomen regarding obstacles in ministry leadership?” and “How do Black clergywomen attribute meaning to their experiences regarding obstacles in ministry leadership?” The results of the study indicated that bias of gender and inequality exists among clergymen; however, the Black clergywomen learned to embrace the experiences and learned from them. The conclusion of this article includes a discussion regarding practical implications of the education of clergy; and the re-evaluation of the perception of Black clergywomen and their experiences. The purpose of this qualitative study was to explore the experiences of Black clergywomen pertaining to challenges in clergy leadership and to explore how Black clergywomen attributed meaning to their experiences regarding challenges in ministry leadership.

Many cancers utilize L-glutamine as a major energy source. This “L-glutamine addiction” involves a well-characterized pathway whereby L-glutamine is hydrolyzed by a glutaminase (GLS) to L-glutamate, which is then converted to α-ketoglutarate, the carbons of which enter the tricarboxylic acid (TCA) cycle. However, mammalian tissues/cancers possess a rarely mentioned alternative pathway (the glutaminase II pathway): L-Glutamine is transaminated to α-ketoglutaramate (KGM), followed by ω-amidase (ωA)-catalyzed hydrolysis of KGM to α-ketoglutarate. Uncertainty may prevail over the name glutaminase II which may be confused with the enzyme named glutaminase 2 (GLS2). Thus, we recently suggested a new name for the glutaminase II pathway, namely the glutamine transaminase-ω-amidase (GTωA) pathway. Herein, we 1) evaluate three recent articles that mention L-glutamine addiction, but not the GTωA pathway, 2) summarize the metabolic importance of the GTωA pathway, including its role in closing the methionine salvage pathway, and 3) as a source of anaplerotic α-ketoglutarate. An advantage of the GTωA pathway [i.e., L-glutamine + α-keto acid + H2O α-ketoglutarate + L-amino acid + +NH4] is that it is irreversible and that there is no net change in redox status, permitting α-ketoglutarate production during hypoxia. Finally, we discuss possible clinical benefits of GTωA pathway inhibitors.

Escherichia coli phage Eco_BIFF was isolated from several laboratory stocks of E. coli K-12 MG1655 derivatives. The source of the contamination is unknown. Eco_BIFF is a lytic phage that shows effective growth inhibition of E. coli K-12. Here, we announce the complete genome sequence of Eco_BIFF, and major findings from its genome annotation.

The pig is an important source of meat production and provides a valuable model for certain human diseases. MicroRNA (miRNA), which is non-coding RNA and regulates gene expression at the posttranscriptional level, plays a critical role in various biological processes. Studies on identification and function of mature miRNAs in multiple pig tissues are increasing, yet the literature is limited. Therefore, we reviewed current research to determine the miRNAs expressed in specific pig tissues that are involved in carcass values (including muscle and adipocytes), reproduction (including pituitary, testis, and ovary), and development of some solid organs (e.g., brain, lung, kidney, and liver). We also discuss the possible regulating mechanisms of miRNA. Finally, as pig organs are suitable candidates for xenotransplantation, biomarkers of their miRNA in xenotransplantation were evaluated.

While referral-level medicine is important in the veterinary curriculum, students also need a solid base knowledge of clinically relevant routine surgery and diagnostic skills. Veterinary hospitals must maintain a steady caseload that provides wellness cases and commonly encountered conditions. Shelter Medicine programs can create the opportunities to meet these challenges. Students can gain quantifiable surgical experience in spay/neuter with measured growth in surgical efficiency and competency while providing needed community service for animal shelters. Students can directly interact with shelter animals by performing examinations, diagnostic testing, and development of treatment protocols and recommendations for commonly encountered problems. Furthermore, students can obtain a working knowledge of biosecurity on a population level to minimize risk of infectious diseases spreading to healthy populations.

The vast majority of autonomous driving systems are limited to applications on roads with clear lane markings and are implemented using commercial grade sensing systems coupled with specialized graphic accelerator hardware. This research reviews an alternative approach for autonomously steering vehicles that eliminates the dependency on road markings and specialized hardware. A combination of machine vision, machine learning and artificial intelligence based on popular pre-trained Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) was used to drive a vehicle along roads lacking lane markings (unmarked roads). The team developed and tested this approach on the ACTor (Autonomous Camus TranspORt) vehicle - an autonomous vehicle development and research platform coupled with a low-cost webcam based sensing system and minimal computational resources. The proposed solution was evaluated on real-world roads and varying environmental conditions. It was found that this solution may be used to successfully navigate unmarked roads autonomously with acceptable road following behavior.

Entropy generation, formulated by combining the first and second laws of thermodynamics with an appropriate thermodynamic potential, emerges as the difference between a phenomenological entropy function and a reversible entropy function. The phenomenological entropy function is evaluated over an irreversible path through thermodynamic state space via real time measurements of thermodynamic states. The reversible entropy function is calculated along an ideal reversible path through the same state space. Entropy generation models for various classes of systems—thermal, externally loaded, internally reactive, open and closed––are developed via selection of suitable thermodynamic potentials. Here we simplify thermodynamic principles to specify convenient and consistently accurate system governing equations and characterization models. The formulations introduce a new and universal Phenomenological Entropy Generation (PEG) theorem. The systems and methods presented––and demonstrated on grease degradation, battery charging and discharging, metal fatigue and pump flow––can be used for design, analysis, and support of diagnostic monitoring and optimization.

With the digital transformation of the logistics industry, smart logistics algorithms have become a core technology to improve efficiency and reduce costs. This paper reviews the development history of traditional logistics technology and discusses the key role of technologies such as the Internet of Things, big data analysis, artificial intelligence, and automation in logistics technology innovation. It focuses on the application of intelligent logistics algorithms in path optimization, intelligent scheduling, data mining and prediction, and intelligent warehousing. To solve the problem of inconsistency between training and testing objectives, this paper proposes DRL4Route, a deep reinforcement learning-based path optimization framework, and designs the DRL4Route-GAE model. Validated through extensive offline experiments and online deployments, the model significantly outperforms existing optimal benchmark methods on real datasets, improving the location deviation squared metrics and the top-three location prediction accuracy metrics. These research results provide important support to further promote the intelligent development of the logistics industry.

Accurate fire severity mapping is essential for understanding the impacts of wildfires on vegetation dynamics in arid savannas. The frequent wildfires in these biomes often cause topkill, where vegetation experiences above-ground combustion, but the below-ground root structures survive, allowing for subsequent regrowth post-burn. Investigating post-fire regrowth is crucial for maintaining ecological balance, elucidating fire regimes, and enhancing the knowledge base of land managers regarding vegetation response. This study examined the relationship between bush fire severity and post-burn coppicing/regeneration events of woody vegetation in the Kalahari Desert of Botswana. Utilizing UAV-derived RGB imagery combined with a Random Forest (RF) classification algorithm, we aimed to enhance the precision of burn severity mapping at a fine spatial resolution. Our research focused on a 1 km2 plot within the Modisa Wildlife Reserve, extensively burnt by the Kgalagadi Transfrontier Fire of 2021. The UAV imagery, captured at various intervals post-burn, provided detailed orthomosaics and canopy height models, facilitating precise land cover classification and burn severity assessment. The RF model achieved an overall accuracy of 79.5% and effectively identified key burn severity indicators, including green vegetation, charred grass, and ash deposits. Our analysis revealed a >50% probability of woody vegetation regrowth in high severity burn areas six months post-burn, highlighting the resilience of these ecosystems. This study demonstrates the efficacy of low-cost UAV photogrammetry for fine scale burn severity assessment and provides valuable insights into post-fire vegetation recovery, thereby aiding land management and conservation efforts in savannas.

Button batteries pose a significant threat to young children and are found in many household items and children’s toys. Along with product manufacturers and retailers, parents and caregivers have a role in button battery ingestion prevention through vigilance regarding items containing button batteries in the home, and knowledge of button battery ingestion symptoms. There is limited information available about parent and caregiver perspectives towards button battery safety. Identifying the areas where increased education is required is important for informing safety campaigns and delivering targeted education. This study aimed to examine parent and caregiver elemental perspectives on button battery safety. One hundred and seventy-four parents and caregivers of children aged 0 to 5 completed a cross-sectional online survey. Distribution occurred via social media. The survey contained multiple-choice questions pertaining to button battery perspectives, and one open-ended question. Respondents recognized the dangers of button battery ingestion, yet only 37% reported being familiar with button battery ingestion symptoms. While 68% knew of household items containing button batteries, only 21% were aware of product recall information sources. Approximately 64% understood immediate post-ingestion steps and 17% found current safety labels unsatisfactory. In an open-ended question, parents and caregivers provided comments about button battery safety that revealed five broad themes; supervision and education; safe storage of button batteries in the home; ensuring children cannot access button batteries; disposing of button batteries safely; and avoiding purchasing items containing button batteries. This study provides a foundation for ongoing investigation of parent and caregiver perspectives on button battery home safety.

We present a discussion and analysis regarding the benefits and limitations of open and non-anonymized peer review based on literature results and responses to a survey on the reviewing process of alt.chi, a more or less open-review track within the CHI conference, the predominant conference in the field of human-computer interaction (HCI). This track currently is the only implementation of an open-peer-review process in the field of HCI while, with the recent increase in interest in open science practices, open review is now being considered and used in other fields. We collected 30 responses from alt.chi authors and reviewers and found that, while the benefits are quite clear and the system is generally well liked by alt.chi participants, they are reluctant to see it used in other venues. This concurs with a number of recent studies that suggest a divergence between support for a more open review process and its practical implementation. The data and scripts are available on https://osf.io/vuw7h/, and the figures and follow-up work on http://tiny.cc/OpenReviews.

Hepatitis B Virus (HBV) infection carries a significant health burden worldwide. It is a leading cause of acute and chronic liver disease resulting in cirrhosis and hepatocellular carcinoma (HCC). This virus affects millions globally, and despite several medical advancements, research, and efforts to develop curative treatment, the persistence of HBV in infected individuals by cccDNA and integration pose formidable challenges. This review aims to provide a broad-based overview of HBV persistence, integration and the implications for chronic infection and tumorigenesis. By considering these points, we bring forth insights into the advancement of therapies that aim to disrupt the chronicity of HBV infection and improve clinical outcomes.

Transplant oncology is a relatively new field in which transplantation is used to treat patients who would otherwise be unresectable. New anticancer treatment paradigms using tumor and transplant immunology and cancer immunogenomics are emerging. In turn, liver transplantation (LT) has become a potential therapy for certain patients with colorectal cancer (CRC) with liver metastasis, hepatocellular (HCC), cholangiocarcinoma (CCA), and metastatic neuroendocrine tumor (NET) to the liver. Although there are established criteria for LT in HCC, the evidence regarding LT as a treatment modality for certain gastrointestinal malignancies is still debated. The aim of this review is to highlight updates in the role of LT for certain malignancies, including HCC, metastatic CRC, hilar CCA, and neuroendocrine tumor (NET), as well as contextualize LT use and discuss controversies in transplant oncology.

Fertility preservation technologies have existed for decades, and the field is rapidly advancing; limited data exist regarding the use of these technologies by transgender patients. Many options are available for transgender patients who wish to preserve fertility before transitioning. These options include the cryopreservation of gametes, ovarian tissue, or embryos. Currently, ejaculated, or testicular sperm, immature oocytes, and ovarian tissue can be preserved for later use, but no such use option exists for immature testicular tissue. Many financial, sociological, and legal barriers and a lack of awareness among physicians and patients also hindered the utilization of these fertility preservation services. While options are abundant, usage rates are relatively low. The initial data regarding the successful use of preserved tissues appears promising, with birth rates not dissimilar to non-transgender patients. Further investigations into this area are needed. In addition, counseling regarding fertility preservation options should become a significant part of the provider-patient conversation before transitioning therapies.; fertility; transgender; reproductive technology.

Knowledge regarding egg morphology can aid the selection of postharvest fumigants for insect control. Accordingly, scanning electron microscopy (SEM) was used to examine eggs of spotted lanternfly (SLF), Lycorma delicatula (White) (Hemiptera: Pentatomidae), a pest recently invasive to the mid-Atlantic region of the United States. As the overwintering life stage of SLF, eggs are deposited on a variety of refugia, including many forestry products that can be distributed geographically via travel, commerce, and/or trade. For fumigation to control SLF, and potentially translate into a viable strategy for limiting the spread of SLF by subject pathways, the fumigant must permeate the chorion to react with biomolecules and/or disrupt cellular processes. SLF chorion was characterized by a porous network of aeropyles localized around the operculum, in cranial and caudal relation to the developing nymph, as well as an interstice between the operculum edge and the opercular rim. The confirmation of chorionic ultrastructure that allows for ready gas exchange warrants further investigation of fumigation efficacy, even for those “non-reactive” fumigants, such as phosphine and hydrogen cyanide, which must overcome the suppression of cellular processes coincident with overwintering.

On February 28, 2023, the Facebook page of the United Nations Children's Fund (UNICEF) South Africa, announced the beginning of the HPV vaccination campaign for 2023. The aim of this study was to examine the attitudes of Facebook users, who commented on the UNICEF South Africa post, towards HPV vaccination to inform the development and implementation of interventions that can increase HPV vaccine acceptance and uptake. Several comments were questions regarding the eligible criteria for vaccination, side effects, consent form, and vaccination strategies. Many Facebook users were hesitant towards HPV vaccination due to various reasons including concerns around side effects, religious beliefs, vaccine stock outs, and their distrust in the institutions or systems involved in vaccination programmes. Few users accepted HPV vaccination because they believed that it was very important thing to do, beneficial for the children’s health, and they have vaccinated they children before. Our findings of the current study contribute to the promotion of acceptance and uptake of HPV vaccination by developing and implementing interventions tailored to address identified barriers that are associated with hesitant to HPV vaccination.

This review article seeks to provide relevant information about the applicability of cell-based assays in assessing cytotoxicity of phytochemicals in light of several traditional methods available. Phenolic compounds and other phytochemicals are significant resources for drug discovery and development, thus underlining the enormous potentials of plant-derived natural products for the prevention and management of oxidative stress associated with cancer and other diseases. These effects have been linked to the content of phytochemicals such as phenolic compounds and their antioxidant properties. The abundance and complexity of these bio-constituents highlight the need for well-defined methods for the in vitro characterization and quantification of extracts and/or preparations that can translate to in vivo effects. Cell culture systems provide a useful model for basic research and a wide range of clinical in vitro studies and physiological processes as well as assessing the toxicity and therapeutic potential of compounds including plant extracts with potential medicinal benefits. Their use in cancer research provide a useful insight into possible therapeutic properties of phytochemicals at the cellular level. This approach has been instrumental in the initial stages of developing chemotherapeutic agents where human cancer cell lines are used as experimental models. These models have continued to contribute to elucidating specific requirements for certain biochemical events associated with proliferation, metabolism, loss of cell viability/apoptosis. Cell culture systems remain a promising tool in natural product development.

The objective of this study is to preliminarily evaluate a new CT-biopsy guidance device, an origami needle guide. The device is created by laser cutting the structure from a sheet of cardboard, 3D printing two radiocontrast agent grids on to the surface and folding the structure into a rectangular prism with a viewing window. An abdominal imaging phantom was used to evaluate the device through CT imaging and the targeting of lesions for needle insertion. The lesion targeting trials resulted in a mean targeting error of 1.88 mm with a standard deviation of 0.73 mm. The device attaches to the patient and is rigid enough to adequately support standard biopsy needles, reducing the effect of gravity and the risk of laceration by the needles, making it potentially advantageous for biopsy of superficial lesions and lesions approached from a horizontal orientation. The device supports insertion of multiple needles at once, making it particularly suitable for composite ablation using multiple needles. Another advantage of the device is that it can guide off-axial needle insertion. The low-cost and disposability of the device make it well-suited for the minimally invasive image guided therapy environment.

Understanding the strength of the associations between perceived risk and individuals’ behavioral intentions to protect their health is important for determining appropriate risk communication strategies in communities impacted by lead contamination. We conducted a survey within communities of northern Idaho, USA (n = 306) near a Superfund megasite with legacy mining contamination. We empirically test a theoretical model based on the Health Belief Model. Survey respondents had higher intentions to practice health protective behaviors when they perceived the risk of lead contamination as severe, recognized the benefits of health protective behaviors, and considered the risks of lead contamination. Women reported higher behavioral intentions than men, but age and mining affiliation did not have an association. Survey comments indicated that perceptions about the long-term environmental remediation in the region influenced risk perceptions. Understanding risk perceptions, behavioral intentions, and related factors can aid public health agencies in tailoring risk communication for increasing protective behaviors in mining-impacted communities internationally.

Heavy rains result in significant threats to human health and life. Floods and other natural disasters, which have a global impact annually, can be attributed to extended periods of intense precipitation. Accurate rainfall prediction is crucial in nations such as Bangladesh, where agriculture is the predominant field of occupation. The efficiency of machine learning methods is enhanced by the nonlinearity of rainfall, surpassing the effectiveness of other approaches. This study proposes the novel combination of rainfall occurrence prediction, rainfall amount prediction, and daily average temperature prediction. This research implements machine learning techniques and an ensemble-based classifier to predict rainfall occurrence, as well as machine learning regressor models and an ensemble-based regressor to predict the rainfall amount and daily average temperature, using the Bangladesh Weather Dataset. The ensemble classifier demonstrated an accuracy of 83.41% and a recall of 78.17%, exhibiting the best performance in predicting when it will rain, but its precision was the lowest, at 51.16%. The ensemble regression model outperformed the base models, including linear regression, random forest, and support vector regression in rainfall amount prediction, with the lowest mean absolute error of 0.36 and root mean squared error of 0.90. Additionally, this model provided the most precise daily average temperature prediction results with the lowest mean absolute error of 0.42 and root mean squared error of 0.54, highlighting its superiority over the other regression models in forecasting temperature. Ensemble approaches consistently exhibit superior task performance metrics.

We investigated 328 SARS-CoV-2 cases in Barwon South West Victoria, Australia, in the 2020 pre-vaccination period, comparing infections with symptoms to those that remained asymptomatic. De-identified self-reported data from three sequential questionnaires on case characteristics and symptom progression were examined. Multivariable logistic regression were used to model associations between demographic profile and symptoms. Asymptomatic cases were more than three times as likely to be from ethnic minority groups [OR 3.2, 95% CI 1.5 – 6.7, p<0.01], and approximately seven times more likely to be seniors (≥ 65 years) [OR 7.3, 95% CI 1.0 – 50.1] after adjusting for sex and occupation. The overrepresentation of ethnic minority groups among asymptomatic infections is suggestive of genetic haplotype variability by ethnic group, conferring greater cross protection from other coronaviruses in the early stages of the COVID-19 pandemic. This research should be repeated post-vaccination to reassess symptom expression according to ethnicity, and better comprehend case ascertainment impacts of cultural biases in testing and infection reporting, and the reliance on symptoms to trigger testing. These findings may in part reflect differences in testing patterns by ethnicity and true differences in disease expression, both important for appropriate transmission prevention strategies, and tailoring testing messaging towards ethnic minority communities.

Communication is a key method of expressing one's thoughts and opinions. Amongst many modalities, speech and writing are the most powerful and common forms of human communication. Analysing what and how people think has inherently been an interesting and progressive research domain. This includes bimodal sentiment analysis which is an emerging area in natural language processing (NLP) and has received a great deal of attention in recent years in a variety of areas including social opinion mining, health care, banking, and so on. At present, there are limited studies on bimodal conversational sentiment analysis as it proves to be a challenging area given the complex nature of the way humans express sentiment cues across various modalities. To address this gap, a comparison of the performance of multiple data modality models has been conducted on the MELD dataset, a widely-used dataset for benchmarking sentiment analysis within the research community. Our work then demonstrates the results of combining acoustic and linguistic representations. Lastly, our proposed neural network-based ensemble learning technique is employed over six transformer and deep learning-based models, achieving a State-Of-The-Art (SOTA) accuracy.

The recent growth of high-resolution spatial data, especially in developing urban environments, is enabling new approaches to civic activism, urban planning and the provision of services necessary for sustainable development. A special area of great potential and urgent need deals with urban expansion through informal settlements (slums). These neighborhoods are too often characterized by a lack of connections, both physical and socioeconomic, with detrimental effects to residents and their cities. Here, we show how a scalable computational approach based on the topological properties of digital maps can identify local infrastructural deficits and propose context-appropriate minimal solutions. We analyze 1 terabyte of OpenStreetMap (OSM) crowdsourced data to create worldwide indices of street block accessibility and local cadastral maps and propose infrastructure extensions with a focus on 120 Low and Middle Income Countries (LMIC) in the Global South. We illustrate how the lack of physical accessibility can be identified in detail, how the complexity and costs of solutions can be assessed and how detailed spatial proposals are generated. We discuss how these diagnostics and solutions provide a multiscalar set of new capabilities – from individual neighborhoods to global regions – that can coordinate local community knowledge with political agency, technical capability, and further research.

Background: Underreporting of Visceral Leishmaniasis (VL) in India remains a problem to public health controls. Effective and reliable surveillance systems are critical for monitoring disease outbreaks and public health control programs. However, in India, government surveillance systems are affected by levels of scarcity in resources and therefore, uncertainty surrounds the true incidence of asymptomatic and clinical cases, affecting morbidity and mortality rates. The State of Bihar alone contributes up to the 40\% of the worldwide VL cases. The inefficiency of surveillance systems occurs because of multiple reasons including delay in seeking health care, accessing non-authentic health care clinics, and existence of significant asymptomatic self healing infectious cases. This results in a failure of the system to adequately report true transmission rates and number of symptomatic cases that have sought medical advice (thus, high underreporting of cases). Objectives and Methods: There are several methods to estimate the extent of underreporting in the surveillance system. In this research, we use a mathematical dynamic model and two different types of data sets, namely, monthly incidence for 2003-2005 and yearly incidence from 2006-2012 from the Bihar's 21 most VL affected districts out of its 38 districts. The goals of the study are to estimate critical metrics to measure level of transmission and to evaluate the estimation process between the two data sets and 21 districts. In particularly, our focus is on (i) estimating infection transmission potential, underreporting level in incidence and proportion of self-healing cases, (ii) quantifying reproduction number of the$R_0$, and (iii) comparing underreporting incidence levels and proportion of self-healing cases between the two periods 2003-2005 and 2006-2012 and between 21 districts. Results: Our research suggests that the number of asymptomatic individuals in the population who eventually self-heal may have a significant effect on the dynamics of VL spread. The estimated mean self-healing proportion (out of all infected) is found to be $\sim 0.6$ with only 7 out of 21 affected districts having self-healing proportion less than $0.5$ for both data sets. The estimated mean underreporting level is at least $64$\% for the state of Bihar. The estimates of the basic reproduction numbers obtained are similar in magnitude for most of the districts, being in the range of (0.88, 2.79) and (0.98, 1.01) for 2003-2005 and 2006-2012, respectively. Conclusions: The estimates for the two types (monthly and yearly) of temporal data suggest that monthly data are better for estimation if less number of data points are available, however, in general, using such data set results in larger variances in parameters as compared to estimates obtained through aggregated yearly data. Estimated values of transmission related metrics are lower than those obtained from earlier analyses in the literature, and the implications of this for VL control are discussed. The spatial heterogeneity in these control metrics increases the risk of epidemics and makes the control strategies more complex.

Lagoons are becoming sporadically utilised albeit they are equipped with high potential for the outsourcing of environmental and industrial benefits. It leads to the endangered pollution of lagoon water aquatic system. The prime reason is the lack of knowledge among stakeholders and researchers regarding the influential parameters in establishing the lagoon water quality. The optimal quality for lagoon water is critical for the longevity of aquatic ecosystem. This study focuses on using bibliographic references to find the most influential factors determining the water quality in lagoons for deriving a comprehensive long-term water quality monitoring plan to ensure the sustainability of the lagoon water ecosystem. The lagoon water quality was classified in this study into biological, physical, and chemical parameters and studied for their importance upon enhancing the water quality. Experiments were conducted on selected parameters using the water samples from the selected Sri Lankan lagoons with available facilities to observe the water quality. The overall findings on physiochemical and biological characteristics using the experiments temperature, turbidity, pH, salinity, DO, BOD, COD, phosphates, nitrates, ammonia content and faecal coliforms in water specimens suggest that the selected Sri Lankan lagoons are heavily polluted due to their distinctive variations from the allowable threshold limits specified in the literature sources. To increase such increased risks associated with lagoon water systems, a long-term monitoring strategy is recommended to be incorporated at lagoon waters in order to assure their sustainability.

The first exposure to influenza is thought to impact subsequent immune responses later in life. The consequences of this can be seen during influenza epidemics and pandemics with differences in morbidity and mortality for different birth cohorts. There is a need for better understanding of how vaccine responses are affected by early exposures to influenza viruses. In this analysis of hemagglutination inhibition (HI) antibody responses in two cohorts of military personnel we noticed differences related to age, sex, prior vaccination, deployment and birth year. These data suggest that HI antibody production, in response to influenza vaccination, is affected by these factors. The magnitude of this antibody response is associated with, among other factors, the influenza strain that circulated following birth.

Supported wellbeing centres were set up in UK hospital trusts as an early intervention aimed at mitigating the psychological impact of COVID-19 on healthcare workers. These provided high quality rest spaces with peer-to-peer psychological support provided by National Health Service (NHS) staff volunteers called ‘wellbeing buddies’, trained in psychological first aid. The aim of the study was to explore the views of centre visitors and operational staff towards this COVID-19 workforce wellbeing provision. Qualitative semi-structured interviews were undertaken with twenty-four (20F, 4M) employees from an acute hospital trust in the UK. Interviews were digitally recorded and transcribed, data were handled and analysed using thematic analysis. Interviews generated 3 over-arching themes, and 13 sub-themes covering ‘exposure and job roles’, ‘emotional impacts of COVID-19 and ‘the wellbeing centres’. Supported wellbeing centres were viewed as critical for the wellbeing of hospital employees during the first surge of COVID-19 in the UK. Wellbeing initiatives require managerial advocacy and must be inclusive. Job-related barriers to work breaks and accessing staff wellbeing provisions should be addressed. High quality rest spaces and access to peer-to-peer support are seen to benefit individuals, teams, organisations and care quality. Training NHS staff in psychological first aid is a useful approach to supporting the wellbeing of the NHS workforce during and beyond the COVID-19 pandemic.

Several stochastic H∞ filters for estimating the attitude of a rigid body from line-of-sight measurements and rate gyro readings are developed. The measurements are corrupted by white noise with unknown variances. Our approach consists of estimating the quaternion while attenuating the transmission gain from the unknown variances and initial errors to the current estimation error. The time-varying H∞ gains are computed through differential and algebraic linear matrix inequalities whose parameters are independent of the state. The case of a gyro drift is addressed, too. Extensive Monte Carlo simulations show that the proposed stochastic H∞ quaternion filters perform well for a wide range of noise variances. The actual attenuation, which improves with the noise level and is worst in the noise-free case, is better than the guaranteed attenuation by one order of magnitude. The proposed stochastic H∞ filter produces smaller biases than a standard quaternion Kalman filter and similar standard deviations at large noise levels. An essential advantage of this H∞ filter is that the gains are independent of the quaternion, which makes it insensitive to modeling errors. This desired feature is illustrated by comparing its performances against those of unmatched Kalman filters. When provided with too high or too low noise variances the Kalman filter is outperformed by the $H_\infty$ filter, which essentially delivers identical error magnitudes.

Background: The work and life of a junior doctor has changed dramatically over the past 50 years. Descriptions of historic working conditions are usually anecdotal and tinted with nostalgia. But presented with the facts, do heath care professionals feel working conditions things have improved or declined in the last 50 years? Methods: An interview was conducted with a retired surgeon who, in 1970, worked as a house surgeon (Foundation Year 2, FY2 equivalent) at a regional burns service. This was compared with a review of available literature to assess objectively working conditions in that period. The information generated from this produced a poster summarizing the key differences over a 53-year timeframe. This information was presented to the current medical work force and a survey was conducted to determine their preference. Statistical analysis including binary logistic regression was performed. Results: The questionnaire was completed by 76 respondent healthcare workers of mixed grades and backgrounds. The majority of respondents (64%) would choose to work in today’s burns unit. The age of the respondent was the best predictor for preference of working conditions (p = 0.043). Conclusions: Multiple changes in the working conditions were identified. The majority of respondents consider today’s working conditions to be better than that of the past. However, more senior clinicians were more likely to prefer the conditions of 1970 to present day, suggesting a generational shift in opinion.

The acquisition of regional, 1 metre resolution LIDAR in the PNG Highlands combined with 3D modelling in MoveTM has revolutionized our understanding of the evolution of the Porgera gold mine and areas of new potential. The new 3D model demonstrates active pull-apart basins along a regional transfer during ongoing fold and thrust deformation. When overlain on regional aeromagnetic data, new potential is revealed. The Porgera gold mine is one of the richest in the world and lies in a wide valley at an elevation of 2800m surrounded by mountains up to 4000m high in the middle of the PNG Highlands. It lies along a major lineament, the Porgera Transfer Zone (PTZ), cutting across the orogen that is associated with a 50 km offset of the ophiolite belt. To the NW of the mine there is an extensive belt of low- to high-grade metasediments that formed in deep water during Jurassic rifting, but were metamorphosed during Eocene subduction to the north. Subduction ceased due to accretion of the Sepik Terrane which caused inversion and mild erosion of the Porgera area. The Late Oligocene onset of wrenching in the Mobile Belt to the north placed that area into extension, emplacing metamorphic core complexes, and led to regional subsidence in the Early Miocene. Collision of the margin with the Melanesian Arc in the Middle Miocene caused Late Miocene to Pliocene orogenesis creating the broad mountain belt that we see today, that is still active, as shown by the 2018 MW 7.5 earthquake. Regional mapping of the area using high resolution LIDAR in association with limited field mapping, analysis of gravity and magnetics data and drilling of 300-500m deep core-holes has allowed development of a detailed 3D structural model. The Porgera valley is constrained laterally by the Eastern Boundary and Western Boundary dextral strike-slip faults that lie along the PTZ cutting across the orogeny. However, whilst the position and nature of the faults is clear, due to bending, fracturing and offset of major synclines and anticlines, the faults do not crop-out as significant through-going features. Rather, the dextral offset of basement is soft-linked to the Tertiary limestones at surface due to intervening thick, ductile Cretaceous shales. Fold and thrust structures are ubiquitous in the Tertiary limestones, but the youngest structural features are large extensional faults, particularly around the Porgera valley. The intrusive underlying the Porgera ore-body was emplaced at 6.0+-0.3 Ma, the time of maximum compression during orogenesis. At this time the Eastern Boundary fault and Western Boundary fault were both active allowing a pull-apart basin to form locally along the PTZ at the south-eastern boundary of the Jurassic metasediments. This enabled emplacement of the intrusive. The gold-bearing fluids from the intrusive and metasediments were brought up through the Mesozoic muds to the contact with the Paleogene carbonates where the Porgera ore body was emplaced.

There is limited data on pregnancy outcomes in Pompe Disease (PD) resulting from deficiency of the lysosomal enzyme acid alpha-glucosidase. Late-onset PD is characterized by progressive proximal muscle weakness and decline of respiratory function secondary to the involvement of the respiratory muscles. In a cohort of twenty-five females, the effects of both PD on the course of pregnancy and the effects of pregnancy on PD were investigated. Reproductive history, course of pregnancy, use of Enzyme replacement therapy (ERT), PD symptoms, and outcomes of each pregnancy were obtained through a questionnaire. Among 20 subjects that reported one or more pregnancies, one subject conceived while on ERT and continued therapy through two normal pregnancies with worsening of weakness during pregnancy and improvement postpartum. While fertility was not affected, pregnancy may worsen symptoms, or cause initial symptoms to arise. Complications with pregnancy or birth were not higher, except for an increase in the rate of stillbirths (3.8% compared to the national average of 0.2-0.7%). Given small sample size and possible bias of respondents being only women who have been pregnant, further data may be needed to better analyze the effects of pregnancy on PD, and the effects of ERT on pregnancy outcomes.

Additive Manufacturing (AM) provides an opportunity to fundamentally redesign components previously limited by conventional manufacturing techniques. A new process for this workflow of design, manufacture by Powder Bed Fusion (PBF) and validation is presented, to which a case study of a crank for a high performance racing bicycle is applied. Topology optimisation generated conceptually ideal geometry from which a functional design was interpreted. Design for AM considerations were employed to reduce build time, material usage and post-processing labour. PBF was employed to manufacture the parts, and the build quality assessed using Computed Tomography (CT). Static and dynamic functional testing was performed and compared to a Finite Element Analysis (FEA). CT confirmed good build quality of tall, complex geometry with no significant geometrical deviation from CAD over 0.5 mm. Static testing proved performance close to current market leaders, although failure under fatigue occurred after just 2495 ± 125 cycles, the failure mechanism was consistent in both its form and location. These physical results were representative of those simulated, thus validating the FEA. This research demonstrates a complete workflow from design, manufacture, post-treatment and validation of a highly loaded PBF manufactured component, offering practitioners with a validated approach to the application of PBF.

The direct measurements of the magnetic flux density in steel blocks within Compact Muon Solenoid (CMS) magnet yoke are performed with 22 flux loops installed in selected regions of the yoke. The 10,000-ton CMS magnet flux return yoke encloses a 4 T superconducting solenoid with a 6-m-diameter by 12.5-m-length free bore and consists of five dodecagonal three-layered barrel wheels and four end-cap disks at each end. The yoke steel blocks, mostly up to 620 mm thick, serve as the absorber plates of the muon detection system. A TOSCA 3-D model of the CMS magnet has been developed to describe the magnetic field everywhere outside of the tracking volume which was measured with a field-mapping machine. In the present study, for the first time, the reliable reconstruction of the magnetic flux density in the steel blocks of the yoke is performed using the CMS magnet standard discharges from the operational magnet current of 18.164 kA. To provide this reconstruction, the voltages induced in the flux loops (with amplitudes of 20–250 mV) have been measured with six 16-bit DAQ modules and integrated offline over time. The results of the flux loop measurements during three magnet ramp downs are presented and discussed.

While some research supports utilizing plain radiography for measuring biomechanical alignment of the spine for prognosis and treatment, there are contrasting viewpoints regarding both the value and utilization of these procedures in conservative care. Evaluation of both conservative and non-conservative approaches to spinal care revealed vast differences in radiographic utilization and interpretation between orthopedic surgeons, primary care physicians, chiropractic physicians, and physical therapists, which may account for the different viewpoints and rationale in the literature. A research summary is provided regarding the various methods of spinal analysis utilized by these professions to help determine if there is any unique diagnostic or prognostic value associated with radiographic utilization that could assist in advancing conservative spinal assessment and treatment. Understanding any unique value provided through biomechanical assessment utilizing plain radiography of the spine established in the literature may help chiropractic physicians determine the appropriate use of radiographic procedures in clinical practice and how to coordinate efforts with other conservative and non-conservative professions to improve spinal healthcare.

Supported Wellbeing Centres have been set up in UK hospital trusts in effort to mitigate the psychological impact of COVID-19 on healthcare workers, although the extent to which these are utilised and the barriers and facilitators to access are not known. The aim of the study was to determine facility usage and gather insight into employee wellbeing and the views of employees towards this provision. The study included i) 17-week service use monitoring, ii) employee online survey with measures of wellbeing, job stressfulness, presenteeism, turnover intentions, job satisfaction, and work engagement as well as barriers and facilitators to accessing the Wellbeing Centres. Over 17 weeks, 14,934 facility visits were recorded across two sites (peak attendance in single week n= 2,605). Facilities were highly valued, but the service model was resource intensive with 134 wellbeing buddies supporting the centres in pairs. 819 hospital employees completed an online survey (88% female; 37.7% working in COVID-19 high risk areas; 52.4% frontline workers; 55.2% had accessed a wellbeing centre). There was moderate-to-high job stress (62.9%), low wellbeing (26.1%), presenteeism (68%) and intentions to leave (31.6%). Wellbeing was higher in those that accessed a wellbeing centre. Work engagement and job satisfaction were high. Healthcare organisations are urged to mobilise access to high-quality rest spaces and Psychological First Aid, but this should be localised and diversified. Strategies to address presenteeism and staff retention should be prioritised, and high dedication of healthcare workers should be recognised.

Vaccination attitudes among healthcare workers (HCWs) is a vital factor for measuring their level of vaccination uptake and intention to recommend vaccinations to their patients. To our knowledge, no study has been conducted in South Africa to assess hesitancy to influenza vaccines among HCWs. We used questionnaire adapted from Betsch and colleagues to conduct an online and face-to-face cross-sectional study among HCWs at the start of COVID-19 vaccine roll-out prior to the flu season. Main outcome was influenza vaccine hesitancy. We used multivariate logistic regression to assess predictors of influenza vaccine hesitancy. Of 401 participants, 64.5% were women, 49.2% nurses, and 12.5% physicians. A total of 54.9% were willing to accept vaccination, 20.4% were undecided, and 24.7% intended to refuse. Older participants above 17-25 years and physicians were likely to receive the vaccine. Key predictors of vaccine acceptance were confidence in the effectiveness, consideration of benefits and risks, and willingness to be vaccinated to protect others. Influenza vaccine hesitancy was highest in those who did not trust that influenza vaccines are safe. For future flu seasons, tailored education programs targeting younger HCWs and more information about the composition of flu vaccines would be vital to improve vaccine uptake.

Laparoscopic cholecystectomy (LC) is the gold standard of treatment for symptomatic gallstone disease. The aim of this study is to determine if postoperative opiate use is reduced with trans-versus abdominus plane (TAP) and rectus sheath (RS) regional anaesthetic blocks compared to port site local anaesthetic (LA) infiltration. A prospective, randomised cohort study was con-ducted of adult patients who underwent an emergency LC between 25 April 2022 and 25 May 2023. 40mls of 0.375% ropivacaine was infiltrated as either TAP and RS blocks or to port sites. Patient demographics, operative data and postoperative opioid use were collected from the med-ical record. 138 patients were enrolled in this study; 73 patients allocated to the LA to port sites cohort (52.9%) and 65 patients in the TAP and RS cohort (43.5%). The most common indication for surgery was acute cholecystitis. The average amount of opiate analgesia use was 115.2mg in the LA group compared to 61.2mg in the TAP and RS group (p

Background: Mounting evidence supports the role of the endocannabinoid system in neurophysiology, includ-ing blood-brain barrier (BBB) function. Recent work has demonstrated that activation of endocannabinoid re-ceptors can mitigate insults to the BBB during neurological disorders, like traumatic brain injury, cortical spreading depression and stroke. As alterations to the BBB are associated with worsening clinical outcomes in these conditions, studies herein sought to examine the impact of endocannabinoid depletion on BBB integrity. Methods: Barrier integrity was investigated in vitro via bEnd.3 cell monolayers to assess endocannabinoid syn-thesis, barrier function, calcium influx, junctional protein expression, and proteome-wide changes. Results: In-hibition of 2-AG synthesis using DAGLα inhibition and siRNA inhibition of DAGLα led to loss of barrier in-tegrity via altered expression of VE-cadherin, which could be partially rescued by exogenous application of 2-AG. Moreover, the deleterious effects of DAGLα inhibition on BBB integrity showed both calcium and PKC (protein kinase C)-dependency. Conclusions: These data indicate that disruption of 2-AG homeostasis in brain endothelial cells, in the absence of insult, is sufficient to disrupt BBB integrity thus supporting the role of the endocannabinoid system in neurovascular disorders.

The availability of new self-sensing cement-based strain sensors allows the development of dense sensor networks for Structural Health Monitoring (SHM) of reinforced concrete structures. These sensors are fabricated by doping cement-matrix materials with conductive fillers, such as Multi Walled Carbon Nanotubes (MWCNTs), and can be embedded into structural elements made of reinforced concrete prior to casting. The strain sensing principle is based on the multifunctional composites outputting a measurable change in their electrical properties when subjected to a deformation. Previous work by the authors was devoted to material fabrication, modeling and applications in SHM. In this paper, we investigate the behavior of several sensors fabricated with and without aggregates and with different MWCNTs content. The strain sensitivity of the sensors, in terms of fractional change in electrical resistivity for unit strain, as well as their linearity are investigated through experimental testing under both static and dynamically varying compressive loadings. Moreover, the responses of the sensors when subjected to destructive compressive tests are evaluated. Overall, the presented results contribute to improving the scientific knowledge on the behavior of smart concrete sensors and to furthering their understanding for SHM applications.

The static formation temperature (SFT) is required to determine the thermophysical properties and production parameters in geothermal and oil reservoirs. However, the SFT is not easy to be obtained by both experimental and physical methods. In this paper, a mathematical approach to predicting SFT based on a new model describing the relationship between bottom hole temperature (BHT) and shut-in time was proposed. The unknown coefficients of the model were derived from least squares fit by Particle Swarm Optimization (PSO) algorithm. Besides, the ability to predict SFT based on a few BHT data (such as first 3, 4, or 5 ones of a data set) was evaluated. The accuracy of the proposed method to predict SFT was testified with a deviation percentage less than ±4% and high values of regression coefficient R² (>0.98). The proposed method could be used as a practical tool to predict SFT in both geothermal and oil wells.

BA.2, a sublineage of Omicron BA.1, is now prominent in many parts of the world. Early reports indicate that BA.2 is more infectious than BA.1. To gain insight into BA.2 mutation profile and the resulting impact of mutations on interaction with receptor and/or monoclonal antibodies, we analyzed available se-quences, structures of Spike/receptor, and Spike/antibody complexes, and conducted molecular dynamics simulations. The results showed that BA.2 has 50 high-prevalent mutations compared to 48 in BA.1. Seventeen BA.1 mutations are not present in BA.2. Instead, BA.2 has 19 unique mutations and a signature Delta variant mutation (G142D). Intriguingly, the BA.2 has 28 signature mutations in Spike, compared to 30 in BA.1. This is due to two revertant mutations S446G and S496G in the receptor-binding domain (RBD), making BA.2 somewhat similar to Wuhan-Hu-1 (WT), which has G446 and G496. The molecular dynamics simulations showed that the RBD consisting of G446/G496 is more stable than S446/S496 containing RBD. Thus, our analyses suggest that BA.2 has evolved with novel mutations (i) to maintain receptor binding similar to WT, (ii) evade the antibody binding greater than BA.1, and (iii) acquire mutation of the Delta variant that may be associated with the high infectivity.

Fertility preservation technologies have existed for decades, and the field is rapidly advancing; limited data exist regarding the use of these technologies by transgender patients. Many options are available for transgender patients who wish to preserve fertility before transitioning. These options include the cryopreservation of gametes, ovarian tissue, or embryos. Currently, ejaculated, or testicular sperm, immature oocytes, and ovarian tissue can be preserved for later use, but no such use option exists for immature testicular tissue. Many financial, sociological, and legal barriers and a lack of awareness among physicians and patients also hindered the utilization of these fertility preservation services. While options are abundant, usage rates are relatively low. The initial data regarding the successful use of preserved tissues appears promising, with birth rates not dissimilar to non-transgender patients. Further investigations into this area are needed. In addition, counseling regarding fertility preservation options should become a significant part of the provider-patient conversation before transitioning therapies.; fertility; transgender; reproductive technology.

The accurate detection of clouds is an important first-step in the processing of remotely sensed satellite data analyses and subsequent cloud model predictions. While initial cloud retrieval technology began with the exploitation of one or two bands of satellite imagery, it has accelerated rapidly in recent years as sensor and retrieval technology have exploded, creating a new era in space exploration. Additionally, initial emphasis in satellite retrieval technology focused on cloud detection for cloud forecast models, more recently cloud screening in satellite acquired data is playing an increasingly critical role in the investigation of cloud free data for the retrieval of soil moisture, vegetation cover, ocean colour concentration and sea surface temperatures, as well as environmental monitoring of a host of products, e.g. atmospheric aerosol data, to study the Earth’s atmospheric and climatic systems. With about 60% of the Earth covered by clouds, on average, it is necessary to both accurately detect clouds in remote sensing data to screen cloud contaminate data in remote sensing analyses. In this paper, the evolution of cloud detection technology is highlighted with advancement in sensor hardware technology and possible AI algorithmic advances. Additionally, a discussion is presented on methods to obtain the cloud truth data needed to determine the accuracy of these cloud detection approaches.

Coastal environments are complex systems that are influenced by a combination of natural processes and human activities. Scientific interest in the effects of coastal erosion/accretion and climatic change-related processes greatly increased in recent decades due to the growing human development along coastal areas. This paper investigates the state and evolution of beach-dune systems for the 1977-2001 and 2001-2019 periods of the Mediterranean coast of Andalusia (Spain) using two different proxies: the dune toe line, which was used to track foredunes evolution, and the high-water line, which was used to assess shoreline evolution. Results showed a general erosional behavior of the studied beach-dune systems and identified cases where the main trend was altered through human interventions. In the 1977-2001 period, 54% of foredunes showed erosion, 24% accretion and 22% stability while and 34% of shorelines showed erosion, 40% accretion and 34% stability. In the 2001-2019 period, 42% of foredunes showed erosion, 28% accretion and 30% stability, and 40% of shorelines showed erosion, 34% accretion and 26% stability. Combining the evolution classes of each proxy (dune toe/shoreline) allows the behavior of both shoreline proxies to be assed together and provides insights additional to those derive from the use of a single proxy. In this regard, Erosion/Erosion (EE) was the most frequent behavior, with 25% and 27% in the first and second periods respectively, and Accretion/Accretion (AA), with 17% in both periods. Erosion of foredunes combined with stability or accretion of the shoreline (ES and EA) were the most common pairings in the first period, while stability of dunes combined with accretion of the shoreline (SA) and Stability/Stability (SS) dominated in the second period. The results obtained provide additional insights on the nature and drivers of coastal change that aid local coastal managers and administrations in understanding erosion processes. The method can be applied at other areas around the world where a similar data base is available.

Some cancer cells rely heavily on non-essential biomolecules for survival, growth, and proliferation. Enzyme based therapeutics can eliminate these biomolecules, thus specifically targeting neoplastic cells; however, enzyme therapeutics are susceptible to immune clearance, exhibit short half-lives, and require frequent administration. Encapsulation of therapeutic cargo within biocompatible and biodegradable poly(lactic-co-glycolic acid) nanoparticles (PLGA NPs) is a strategy for controlled release. Unfortunately, PLGA NPs exhibit burst release of cargo shortly after delivery or upon introduction to aqueous environments where they decompose via hydrolysis. Here we show the generation of hybrid silica-coated PLGA (SiLGA) NPs as viable drug delivery vehicles exhibiting sub-200 nm diameters, a metastable Zeta potential, and high loading efficiency and content. Compared to uncoated PLGA NPs, SiLGA NPs offer greater retention of enzymatic activity and slow the burst release of cargo. Thus, SiLGA encapsulation of therapeutic enzymes, such as asparaginase, could reduce frequency of administration, increase half-life, and improve efficacy for patients with a range of diseases.

In the current study, we assessed the effects of conventional and Ultra High Dose Rate (UHDR) irradiation on behavioral and cognitive performance one month following exposure and assessed whether these effects were associated with alterations in the number of immune cells in the hippocampus using flow cytometry. Conventional- and UHDR-irradiated mice showed impaired novel object recognition. During fear learning, conventional- and UHDR-irradiated mice moved less during the inter-stimulus-interval (ISI) and UHDR-irradiated mice also moved less during the baseline period (prior to the first tone). In irradiated mice, reduced activity levels were also seen in the home cage; conventional- and UHDR-irradiated mice moved less during the light period and UHDR-irradiated mice moved less during the dark period. Following behavioral and cognitive testing, infiltrating immune cells in the hippocampus were analyzed by flow cytometry. The percent Ly6G+ CD45+ cells in the hippocampus was lower in conventional- and UHDR-irradiated than sham-irradiated mice, suggesting that neutrophils might be particularly sensitive to radiation. The percent of Ly6G+ CD45+ cells in the hippocampus was positively correlated with the time spent exploring the novel object in the object recognition test, suggesting that the reduced percent Ly6G+ CD45+ cells in the hippocampus might mediate some of the detrimental radiation-induced cognitive effects.

Crypto-ransomware has emerged as one of the most significant cybersecurity threats in recent years. Ransomware attacks, particularly those involving the encryption of data and demanding payment in cryptocurrency, have caused severe disruptions across various critical industries, including healthcare, energy, and finance. The proliferation of these attacks is largely attributed to the anonymity provided by cryptocurrency transactions and the increasing sophistication of cybercriminal tactics. The impact of ransomware extends beyond immediate financial losses, often leading to prolonged operational downtime, reputational damage, and even risks to public safety. In this research paper, we explore the growing threat of crypto-ransomware by examining real-life case studies in key industries, analyzing the countermeasures taken, and proposing additional solutions to mitigate the risk. The goal is to raise awareness and provide actionable insights for organizations to better protect themselves against this pervasive threat.

Complex atypical endometrial hyperplasia (CAH) carries a high probability of cancer. Intraoperative evaluation of endometrial cancer in cases of CAH has not been reliable. The safety and sensitivity of sentinel lymph node (SLN) sampling has been validated. We aim to evaluate the efficacy and safety of SLN sampling in CAH managed by the da Vinci robotic platform. A total of 113 patients with a preoperative diagnosis of CAH were included in this retrospective cohort study. All underwent a robot assisted total laparoscopic hysterectomy and bilateral salpingo-oophorectomy with 69 patients undergoing SLN sampling. Statistical analysis calculated the probability of cancer, SLN map rate, and surgical complications. Predictors of cancer were evaluated. Forty-seven percent of the entire cohort were diagnosed with endometrial cancer. Median age was 63 years in the SLN cohort (N = 69) and 61 in the No SLN cohort (N = 44) (p= 0.363).  Median BMI was 34 Kg/m2 in the SLN cohort and 40 in the No SLN cohort (p= 0.004). Bilateral SLN map was 92.8% and unilateral SLN map rate was 7.2%. There were no grade 3-4 complications in the SLN cohort, and 4 grade 3-4 complications in the No SLN group (p=0.021). A preoperative diagnosis of CAH bordering on or cannot rule out cancer was the only predictor of cancer.

Drought monitoring and early detection have improved greatly in recent decades through the development and refinement of numerous indices and indicators. However, a lack of guidance, based on user experience, exists as to which drought monitoring tools are most appropriate in a given location. This review paper summarizes the results of targeted user engagement and the published literature to improve the understanding of drought across North America, and to enhance the utility of drought monitoring tools. Workshops and surveys were used to assess and make general conclusions about the perceived performance of drought indicators, indices and impacts information used for monitoring drought in the five main Köppen climate types (Tropical, Temperate, Continental, Polar Tundra, Dry) found across Canada, Mexico, and the United States. In Tropical, humid Temperate, and southerly Continental climates, droughts are perceived to be more short-term (less than 6 months) in duration rather than long-term (more than 6 months). In Polar Tundra climates, Dry climates, Temperate climates with dry warm seasons, and northerly Continental climates, droughts are perceived to be more long-term than short-term. In general, agricultural and hydrological droughts were considered to be the most important drought types. Drought impacts related to agriculture, water supply, ecosystem, and human health were rated to be of greatest importance. Users identified the most effective indices and indicators for monitoring drought across North America to be the U.S. Drought Monitor (USDM) and Standardized Precipitation Index (SPI) (or another measure of precipitation anomaly), followed by the Normalized Difference Vegetation Index (NDVI) (or another satellite-observed vegetation index), temperature anomalies, crop status, soil moisture, streamflow, reservoir storage, water use (demand), and reported drought impacts. Users also noted the importance of indices that measure evapotranspiration, evaporative demand, and snow water content. Drought indices and indicators were generally thought to perform equally well across seasons in Tropical and the colder Continental climates, but their performance was perceived to vary seasonally in Dry, Temperate, Polar Tundra, and the warmer Continental climates, with improved performance during warm and wet times of the year. The drought indices and indicators, in general, were not perceived to perform equally well across geographies. This review paper provides guidance on when (time of year) and where (climate zone) the more popular drought indices and indicators should be used. The paper concludes by noting the importance of understanding how drought, its impacts, and indicators are changing over time as the climate warms, and by recommending ways to strengthen the use of indices and indicators in drought decision-making.

As artificial intelligence (AI) makes significant headway in various arenas, the field of Speech-Language Pathology is at the precipice of experiencing a transformative shift towards automation. This study introduces QuickPic AAC, an AI-driven application designed to generate topic-specific displays from photographs in a "just-in-time" manner. Using QuickPic AAC, this study aimed to (a) determine which of two AI algorithms (NLG-AAC and GPT-3.5) results in greater specificity of vocabulary (i.e., percentage of vocabulary kept/deleted by clinician relative to vocabulary generated by QuickPic AAC; percentage of vocabulary modified); and to (b) evaluate perceived usability of QuickPic AAC among practicing speech-language pathologists. Results revealed that the GPT-3.5 algorithm consistently resulted in greater specificity of vocabulary and that speech-language pathologists expressed high user satisfaction for the QuickPic AAC application. These results support continued study of the implementation of QuickPic AAC in clinical practice and demonstrate the possibility of utilizing topic-specific displays as just-in-time supports.

Coccidioides spp are thermally dimorphic fungi found in geographically defined areas of the Western Hemisphere. The primary portal of entry is respiratory, with a symptomatic pneumonic disease as the most common presentation. Subsequent pulmonary complications as well as extrapulmonary metastatic infection may occur, either of which may be the presenting disease manifestation. Cavitary lung disease may be found incidentally or when investigating symptoms such as cough or hemoptysis. This study aims to explore the spectrum of coccidioidal cavities and the evaluation and management in a cohort of patients seen at Kern Medical over the last 12 years.

Collisions of low energy electrons with molecules are important for understanding many aspects of the environment and technologies. Understanding the processes that occur in these types of collisions can give insights into plasma etching processes, edge effects in fusion plasmas, radiation damage to biological tissues and more. A radical update of the previous expert system for computing observables relevant to these processes, Quantemol-N, is presented. The new Quantemol Electron Collision (QEC) expert system simplifyies the user experience, improving reliability and implements new features. The QEC GUI interfaces the Molpro quantum chemistry package for molecular target setups and to the sophisticated UKRmol+ codes to generate accurate and reliable cross-sections. These include elastic cross-sections, super elastic cross-sections between excited states, electron impact dissociation, scattering reaction rates, dissociative electron attachment, differential cross-sections, momentum transfer cross-sections, ionization cross sections and high energy electron scattering cross-sections. With this new interface we will be implementing dissociative recombination estimations, vibrational excitations for neutrals and ions, and effective core potentials in the near future.