Taiwan’s auditors have suffered from processing excessive audit data, including drawing audit evidence. This study advances sampling techniques by integrating machine learning with sampling. This machine learning integration helps avoid sampling bias, keep randomness and variability, and target the risker samples. We first apply a Naive Bayes classifier to classify data into some classes. Next, a user-based, item-based, or hybrid approach is employed to draw audit evidence. The representativeness index is the primary metric for measuring the representativeness of audit evidence. The user-based approach denotes the selection of samples between two percentiles in a class as audit evidence. It may be equivalent to a combination of monetary and variable sampling methods. The item-based approach represents the choice of risky samples as audit evidence. It may be identical to a combination of non-statistical and monetary sampling methods. Auditors can hybridize those user-based and item-based approaches to balance representativeness and riskiness in selecting audit evidence. Three experiments show that sampling using machine learning integration has the benefits of drawing unbiased samples, handling complex patterns, correlations, and unstructured data, and improving efficiency in sampling big data. However, the limitations are the classification accuracy output by machine learning algorithms and the range of prior probabilities.

Abstract Background: Temporomandibular disorders (TMD) are a range of clinical problems related to the temporomandibular joint (TMJ), chewing muscles, and surrounding facial structures. Functional magnetic resonance studies suggest that these disorders affect over 5% of the population. The relationship between dental occlusion and TMD has been a topic of debate in dentistry; some researchers suggest using lateral cephalograms and cephalometric data to identify which morphological profiles and types of malocclusion are most likely to cause TMD. The aim of this study is to identify the morphological profiles and associated skeletal malocclusions that have the greatest influence on the development of TMD. This will be accomplished through the analysis of cephalometric data obtained from cephalograms and condylar section images of patients from the Orthognathodontics Department of Chieti, who underwent low-dose cbct during their initial visit. Matherial and methods: This study, conducted at the Orthognathodontics Department of Gabriele D’Annunzio University in Chieti, examined a group of 67 patients (both males and females) presenting with signs of temporomandibular joint disorders (TMD). The inclusion criteria for the study were first-time TMD diagnosis, age 18 and above, and accessible medical records, wide field of view cone beam low dosage, and photographs. Patients with a history of tumor, trauma, surgical interventions in the jaw and facial area, fractures, and other craniofacial anomalies were excluded from the study. The aim of the study is to further understand the morphological profiles and associated skeletal malocclusions that contribute to TMD. Results: male patients: sagittal profile: 56% exhibited a skeletal Class II profile due to mandibular retrognathia. Vertical Profile: 73% were brachyfacial with a hypodivergent pattern. Dental Relationships: Increased overjet and a tendency towards deep bite were observed. 23% exhibited deep bite, 20% were normodivergent, and 8% were dolichofacial. The soft tissue profile tended towards flatness. Condyle Position: in Class II hypodivergent males, the condyle was non-concentric and positioned more posteriorly. In mesiodivergent males, the condyle was concentric, while in hyperdivergent males, it was slightly anterior. Female Patients: Sagittal Profile: 79% had a skeletal Class II profile with mandibular retrognathia. Vertical Profile: 47% were hypodivergent with reduced anterior facial height (105°). Dental Relationships: 17% exhibited deep bite, and 48% of those with a Class II profile had increased overjet. 43% were mesofacial, and 10% were dolichofacial. Condyle Position: In Class II hypodivergent and normodivergent females, the condyle was non-concentric and positioned more posteriorly. In hyperdivergent females, the condyle was positioned more anteriorly and higher in the fossa. Conclusion: The study highlighted significant differences in cephalometric parameters and condyle positions between male and female patients with TMD. A posteriorly positioned condyle was associated with a flattened condylar head, particularly in Class II hypodivergent profiles. These findings underscore the importance of individualized diagnostic and treatment approaches based on detailed cephalometric and condylar assessments. Further research is needed to explore the implications of these variations for TMD management and outcomes.

The objective of this study was to detail the monomer composition of resin-based dental materials sold in the market in 2023 and to evaluate the proportion of BPA derivatives in relation with their applications. A search on manufacturers’ websites was performed to reference resin-based dental materials currently on the market. Their monomer composition was determined from material safety data sheets and completed with a search on PubMed database. Among the 543 material compositions exploitable, 382 (70.3%) contained BPA derivatives. Among them, 56.2% contained BisGMA, 28% BisEMA, the most frequently reported. A total of 59 monomers of which 6 BPA-derivatives were found. 309 materials (56.9%) contained UDMA and 292 (53.8%) TEGDMA. Less than one third of materials identified contained no BPA derivatives. These proportions vary a lot depending on their applications with materials dedicated to dental care of young populations containing the highest proportions of BPA-derivatives monomers. The long-term effects on human health of the different monomers identified including BPA-derivatives monomers is a source of concern. For children and pregnant or lactating women arises the question to take a precautionary principle and avoid the use of resin-based dental materials likely to release BPA by opting for alternative materials.

Motivated by the PEACOC project on metal recovery from solid wastes, an innovative magnetic density separation (MDS) process has been developed for granular material sorting. It has intrinsic advantages over the existing industrialized MDS by eliminating fluid turbulence and particle jamming problems. The new MDS applies an inclined planar magnet and a horizontal basin containing a static magnetic fluid as the separation medium. A particle sliding phenomenon is identified as a feature of the process which could help the separation. The MDS successfully sorted shredded PCBAs to concentrate valuable metals and sorted shredded wires to reduce metallic contaminants in the plastic fractions. A pilot scale facility is introduced to show the design to achieve continuous production and to reduce the consumption of ferrofluid.

To address the response of small RNAs (sRNAs) biogenesis to drought stress, we identified sRNAs biogenesis genes, including 11 encoding argonauts (AGO), 8 encoding dicer-like proteins (DCL), and 9 encoding RNA-dependent RNA polymerases (RDR) in the peach genome. Notably, the largest numbers of sRNAs biogenesis genes are located to chromosome 1. The PAZ, PIWI, and MID domains were identified in PpAGOs, while the ribonuclease IIIa and IIIb domains were characterized in PpDCLs. The RDRP domain was recognized in PpRDRs. Orthologous similarity and collinearity analyses between Arabidopsis and peach revealed 5, 1, and 2 collinear blocks in AGOs, DCLs, and RDRs, respectively. Moreover, 41, 40, and 42 cis-acting elements were located in the promoters of PpAGOs, PpDCLs, and PpRDRs, respectively, with the majority related to drought stress response. Analysis of RNA sequencing (RNA-seq) data revealed that sRNAs biogenesis genes were involved in drought stress response in different tissues. Furthermore, the expression of candidate genes was verified in two peach cultivars, Beijing 2-7 (BJ2-7) and Sinai (SN), which are drought tolerance and sensitive, respectively. Interestingly, the expression of PpAGO2b, PpDCL2b, PpDCL4, and PpRDR4 genes was induced in ‘BJ2-7’ but inhibited in ‘SN’ under drought stress. Overall, this study provides insight into the roles of sRNA biogenesis genes in response to drought stress in peach.

Glioblastoma (GB) is the most aggressive and prevalent glioma within the Central Nervous System. GB exhibit a dismal 5-year survival rate (~6%) due to unfavorable prognosis and lack of viable treatment options. Therefore, novel therapies with plant-derived compounds emerge as very promising. This study aims to investigate the antitumor activity of 7α-acetoxy-6β-hydroxyroyleanone (Roy) in GB cell lines. Roy was isolated from Plectranthus hadiensis Schweinf. and its antitumor mechanism was assessed in a panel of five GB cell lines to mimic tumor heterogeneity. Metabolic activity was evaluated by Alamar Blue® assay, while cell death, cell cycle regulation, mitochondrial membrane potential, and activated caspase-3 were evaluated by flow cytometry. mRNA levels of target genes were measured by qPCR and protein expression was assessed by Western blotting. Cell uptake and impact on mitochondrial morphology were evaluated by confocal microscopy. Roy induced G2/M cell cycle arrest, mitochondrial fragmentation, and apoptosis by inhibiting the expression of anti-apoptotic proteins and increasing activated caspase-3 levels with concentration 6-9 fold lower than those of temozolomide, the first-line treatment. Roy demonstrated a robust antitumor activity against GB cells, without affecting non tumoral cells (microglia and astrocytes), being a promising natural lead compound for the development of novel chemotherapeutic approaches.

We present a case report of a 26-years-old female suffering from Coffin Siris Syndrome, who underwent orthodontic treatment and surgery to solve her malocclusion and improve her aes-thetics and functional occlusion. Methods: The presurgical phase involved multibracket self-ligating attachments, Damon prescription. The patient underwent maxillofacial surgery to correct the severe skeletal malocclusion and relocate the bone bases in the right relationship. The post-surgical orthodontic treatment was performed to complete the alignment. Results: The pa-tient improved her aesthetics and functional abilities. Conclusions: Syndromic patients can un-dergo orthodontictreatment if comorbidities and collaboration allow it. Support and collaboration of families and psychotherapists must be considered, but clinical cases of syndromic patients can be faced and solved. Obviously, each syndromic patient is considered unique, and the risk-benefit ratio must be correctly assessed for each one.

A new two-step method for developing a nanocomposite of polypropylene (PP) decorated with photocatalytically active TiO2 nanoparticles (nTiO2) is proposed. This method involves low-temperature plasma functionalization of polypropylene followed by ultrasound-assisted anchoring of nTiO2. The nanoparticles, polymeric substrate, and resultant nanocomposite were thoroughly characterized using nanoparticle tracking analysis (NTA), microscopic observations (SEM, TEM, EDX), spectroscopic investigations (XPS, FTIR), thermogravimetric analysis (TG/DTA), and water contact angle (WCA) measurements. The photocatalytic activity of the nanocomposites was evaluated through the degradation of methyl orange. The individual TiO2 nanoparticles ranged from 2-6 nm in size. Oxygen plasma treatment of PP generated surface functional groups (mainly -OH and -C=O), transforming the surface from hydrophobic to hydrophilic, which facilitated efficient deposition of nTiO2. Optimized plasma treatment and sonochemical deposition parameters resulted in an active photocatalytic nTiO2/PP system, degrading 80% of methyl orange under UVA irradiation in 200 minutes. The proposed approach is considered versatile for the functionalization of polymeric materials with photoactive nanoparticles and, in a broader perspective, can be utilized for the fabrication of self-cleaning surfaces.

Nanocellulose (CNC) seems to be a promising surfactant, which, together with expandable graphite (EG), forms the essence of an effective natural-based fire retardant wood coating. In our research, the most suitable composition of the mixture was tested concerning good solubility, dispersion, and consistency. Favorable results were achieved with the formulation composed of a 4% CNC alkaline solution with 80 wt.% of selected EG. Subsequently, six different EG were used to prepare these wood fire retardant coatings. The effectiveness of treatments was verified using a test with a radiant heat source, where the test samples' relative weight loss, relative burning rate, and surface temperature during 600 sec were evaluated. All prepared formulations can be characterized as more or less equally effective. However, the best results were obtained with EG of GG 200 – 100 N, where the mass loss of the sample was 8.10 ± 1.24%. Very good results were also achieved by graphite 25 E + 180 HPH (8.70 ± 0.89%), which is similar to the previous one, even according to the microscopic assessment of the coating as well as the expanded layer. Graphite type 25 K + 180 (8.86 ± 0.65 %) shows the expanded layer's best cohesion, coating uniformity, and ease of application. The results of this work confirmed that the CNC coating itself has significant retardation effects.

The literature study delves into novel therapeutic strategies in transplantation medicine, highlighting unique approaches that could revolutionize current practices. It emphasizes novel patterns that have the potential to transform the current landscape. Commencing with a thorough examination of the historical environment, it traces crucial advances and changes in transplantation. The focus is on traditional techniques, emphasizing their limitations and challenges. An extensive examination of contemporary transplantation therapies offers valuable insights into the most recent progress in organ, cellular, and tissue transplantation. This analysis examines the immunological obstacles and outlines the current advancements and constraints. The exploration further navigates into novel models and concepts such as immunomodulation, developments in organ preservation techniques, gene editing, biomaterials, scaffold-based solutions, and the integration of precision medicine, artificial intelligence, and machine learning applications. Each section analyzes the potential for change and current progress in various areas, backed by relevant scientific sources up to 2023. The subsequent sections delve into innovative cellular therapies, biotechnological progress, current clinical trials, and case studies demonstrating effective applications. This examination delves into the ethical and regulatory considerations of innovative therapeutic procedures, emphasizing ethical implications, regulatory frameworks, and the importance of balancing innovation with patient welfare. The literature review concludes by offering a forward-looking perspective, emphasizing potential progress, anticipated challenges, and advocating for collaboration and interdisciplinary approaches to overcome limitations in the field of transplantation medicine.

Antiviral peptides (AVPs) represent a promising strategy for addressing the global challenge of viral infections and their growing resistance to traditional drugs. Lab-based AVP discovery methods are resource-intensive, highlighting the need for efficient computational alternatives. In this study, we developed five non-trained but supervised Multi-Query Similarity Search Models (MQSSMs) integrated into the StarPep toolbox. Rigorous testing and validation across diverse AVP datasets confirmed the models' robustness and reliability. The top-performing model, M13+, demonstrated impressive results with an accuracy of 0.969 and a Matthew’s correlation coeffi-cient of 0.71. To assess their competitiveness, the top five models were benchmarked against 14 publicly available machine learning and deep learning AVP predictors. The MQSSMs outper-formed these predictors, highlighting their efficiency in terms of resource demand and public ac-cessibility. Another significant achievement of this study is the creation of the most comprehensive dataset of antiviral sequences to date.

This study optimizes the placement and farm layout of Vertical Axis Wind Turbines (VAWTs) using a neural fuzzy network, an advanced machine learning system, and meta-heuristic algorithms. The methodology introduces a novel approach to enhance turbine efficiency and overall farm performance. The objective is to determine the optimal configuration of vertical axis wind turbines using a neural-fuzzy system and meta-heuristic optimizers. Turbine efficiency and power generation rates are assessed through three-dimensional numerical simulations based on the Reynolds-averaged Navier-Stokes equations. This innovative design, featuring straight blades with bevel-angle vortex generators, represents a significant advancement over traditional straight-blade VAWTs. Comparative analyses demonstrate that the oblique configuration exhibits higher average output moment and power. A novel concept integrates the strengths of Darrieus VAWTs, enhancing efficiency through vortex generator integration. Simulation results are validated with empirical data, confirming the superior aerodynamic efficiency and increased power generation of the oblique configuration. Inspired by the optimal group movements of birds, this study recommends adopting the oblique arrangement for improved wind turbine performance.

This paper introduces an innovative energy circuit that challenges conventional understandings of energy conservation, marking a significant departure from traditional frameworks. Seeking to enhance energy generation within existing paradigms, this innovation holds promise for addressing pressing global issues such as the energy crisis and environmental sustainability, while also stimulating scientific inquiry. In contrast to prevalent misconceptions rooted in philosophical and scientific constraints, this study refutes the notion of generating energy from nothing and questions the viability of perpetual motion machines as conceptual models. Instead, it proposes a novel circuit design derived from an unconventional electrical short circuit, which is shown to disrupt the established principles of energy conservation. This circuit offers a transformative approach with diverse applications, including self-recharging capabilities for electric vehicles, bolstering microgrid infrastructure, and facilitating the integration of renewable energy sources. Transcending conventional scientific boundaries, this paper prompts philosophical reflections on the evolving nature of scientific exploration. Ultimately, the energy circuit represents a pivotal step towards mitigating the global energy crisis by reducing reliance on finite resources and fostering sustainability. The paper concludes by illustrating the circuit's potential to revolutionize energy systems and contribute to a more resilient and sustainable future.

olten salt reactors (MSRs) utilize salts as coolant or as the fuel and coolant together with fissile isotopes dissolved in the salt. It is necessary to therefore understand the behavior of the salts to effectively design, operate, and regulate such reactors, and thus there is a need for thermodynamic models for the salt systems. Molten salts, however, are difficult to represent as they exhibit short range order that is dependent on both composition and temperature. A widely useful approach is the modified quasichemical model in the quadruplet approximation that provides for consideration of first and second nearest neighbor coordination and interactions. Its use in the CALPHAD ap-proach to system modeling requires fitting parameters using standard thermodynamic data such as phase equilibria, heat capacity, and others. Shortcoming of the model is its inability to directly vary coordination numbers with composition or temperature. Another issue is the difficulty in fitting model parameters using regression methods without already having very good initial values. The proposed paper will discuss these issues and note some practical methods for the effective genera-tion of useful models.

Kamchatka berries (Lonicera caerulea L.) are known for their high content of phenolic compounds or vitamins, which is reflected in their antibacterial, detoxifying and anti-inflammatory properties. They are used in the production of jams, juices, wines and as natural dye. A bioferment was prepared from the pomace of the Kamchatka berry varieties Aurora and Indigo Gem and the strains Saccharomyces cerevisiae and Lacticaseibacillus paracasei, which was used to prepare a cosmetic preparation with a concentration of 5% in accordance with the guidelines of the COSMOS certification body. Conducted physico-chemical and organoleptic analyses and bioactive profile characterisation (UHPLC-DAD and UHPLC-ESI-MS/MS). The results showed that the presence of caffeic acid 4.47 ± 0.07 mg/100g was detected after fermentation of Kamchatka berry pomace. Vitamin C content increased by 141% after fermentation of Kamchatka berry pomace. The results of stability tests showed that in the process of physicochemical analysis of cosmetic preparation with bioferment of Kamchatka berry pomace the pH should oscillate in the range of 4.38-4.76 ± 0.01. Stability tests showed that the cosmetic should be protected from high temperatures and UV radiation and proved that the product is stable under changing conditions, resulting in lower transport and storage costs.

Machine Learning (ML) has brought about a transformative era in reactor operations, reshaping monitoring, control, and optimization strategies. This survey comprehensively explores the diverse spectrum of ML applications in industrial reactors. From real-time sensor analysis ensuring reactor functionality to adaptive control algorithms ensuring stability, ML's impact is profound and multifaceted. The benefits of ML are equally evident in optimization, encompassing performance trend prediction, proactive maintenance, and fine-tuning of operations for enhanced efficiency. This review identifies dominant ML techniques, operations stages receptive to ML integration, core data sources, and critical input-output parameters. Aimed at both academics and practitioners, this exploration enriches reactor technologies, unlocking their full potential through insights driven by ML.

The age-related loss of muscle mass and strength is referred to as “sarcopenia”. The combined effect of sarcopenia and osteoporosis is a devastating threat to the old adult, accounting for reduced mobility, risk for falls and subsequent fractures. In previous studies, we observed a high degree of inter-individual variability of paraspinal muscle fatty infiltration, one most relevant index of muscle wasting. This aspect solicited us to develop a computerized method to quantitatively characterize muscle fatty infiltration in aging and diseases. Magnetic resonance images of paraspinal muscles from 58 women of different age (age range 23-85 years) and physio-pathological status (healthy young, pre-menopause, post-menopause, and os-teoporosis), were used to set up the method. It is based on fractal analysis of lean muscle area (contractile muscle) to estimate muscle fatty infiltration. In particular, lacunarity was computed by parameter β from our hyperbola model function, used to fit the GBA (gliding box algorithm) curvilinear plot. Succolarity was estimated by parameter µ, for the four main directions, through an algorithm implemented on purpose. Results show that fractal lacunarity, by quantifying muscle fatty infiltration, can discriminate be-tween osteoporosis and healthy aging while succolarity can separate the other three groups showing similar lacunarity. Therefore, fractal features of contractile muscle, by measuring fatty infiltration, can represent good indices of sarcopenia in aging and disease.

This scientific paper explores the increasingly widespread use of collaborative robots in the industrial environment, highlighting them as a solution to challenges related to the high costs of human labour and the associated management difficulties. The authors focus on the process of defining requirements for the implementation of collaborative robots, providing strategies based on mathematical management models. This approach translates into significant benefits for companies, such as cost reduction, quality improvement, and increased operational efficiency. Additionally, the paper proposes an innovative mathematical model for assessing total costs, budgeting, profitability, and electric power consumption associated with the operation of collaborative robots. This model allows for a comparison between the costs involved in using human labour and those associated with collaborative robots, providing critical information for technological investment decisions. The efficiency of this mathematical model is demonstrated through a practical application, where collaborative robots were integrated into a production environment, and costs and efficiency were evaluated compared to the use of human labour. This scientific paper provides a systematic and efficient approach to implementing collaborative robots in industrial processes, benefiting from strategies based on mathematical management models and an original mathematical model for evaluating performance and associated costs.

Dendritic cell (DC) cancer vaccines are a promising therapeutic approach, leveraging the immune system to fight tumors. These vaccines utilize DCs' ability to present tumor-associated antigens to T cells, triggering a robust immune response. DC vaccine development has progressed through three generations. The first generation involved priming DCs with tumor-associated antigens or messenger RNA outside the body, showing limited clinical success. The second generation improved efficacy by using cytokine mixtures and specialized DC subsets to enhance immunogenicity. The third generation uses blood-derived DCs to elicit a stronger immune response. Clinical trials indicate that cancer vaccines have lower toxicity than traditional cytotoxic treatments. However, achieving significant clinical responses with DC immunotherapy remains challenging. Combining DC vaccines with immune checkpoint inhibitors (ICIs) such as anti-cytotoxic T-lymphocyte Antigen 4 and anti-programmed Death-1 antibodies has shown promise by enhancing T cell responses and improving clinical outcomes. These combinations can transform non-inflamed tumors into inflamed ones, boosting ICIs' efficacy. Current research is exploring new checkpoint targets like LAG-3, TIM-3, and TIGIT, considering their potential with DC vaccines. Additionally, engineering T cells with chimeric antigen receptors or T cell receptors could further augment the anti-tumor response. This comprehensive strategy aims to enhance cancer immunotherapy, focusing on increased efficacy and improved patient survival rates.

Activated Corrosion Products (ACPs) formation and deposition pose a critical safety issue for nuclear fusion reactors. The working fluid transports the ACPs towards regions accessible to worker personnel. Predicting ACPs formation deposition and transport is fundamental for source term identification, reduction of radiation exposure assessment, maintenance plan definition, design optimization, and waste management. The code OSCAR-Fusion has been developed by the CEA (France) to evaluate the ACPs generation and transport in closed water-cooled loops for fusion application. This work aims at assessing the impact of water chemistry on the transport, precipitation, and deposition of corrosion products for the EU-DEMO divertor Plasma Facing Unit Primary Heat Transfer System. Sensitivity analyses and uncertainty quantification are needed due to the multi-physics phenomena involved in ACPs formation and transport. The OSCAR-Fusion/RAVEN code coupling developed by the Sapienza University of Rome and ENEA has been used. This work presents the perturbation results of different parameters chosen for a closed water-cooled loop considering a continuous scenario of 1888 days. The aim of this work is to assess the variation of build-up of ACPs, perturbing the alkalizing agent concentration into the coolant and the corrosion and release rates of different materials.

Despite being stored at 113 K and atmospheric pressure, LNG cold potential is not exploited to reduce green ships’ energy needs. An innovative system based on three Organic Ranking Cycles integrated into the regasification equipment is proposed to produce additional power and recover cooling energy from condensers. A first-law analysis identified ethylene and ethane as suitable working fluids for the first and the second ORC making available freshwater and ice. Propane, ammonia and propylene could be arbitrarily employed in the third ORC for air-conditioning. An environmental analysis that combines exergy efficiency, ecological indices and hazard aspects for marine environment and ship’s passengers, indicated propylene as safer and more environmentally friendly. The exergy analysis confirms more than 20% of the LNG potential can be recovered from every cycle to produce a net clean power of 76 kW, whereas 270 kW can be saved by recovering condensers' cooling power to satisfy some ship needs. Assuming the sailing mode, a limitation of 162 kg in LNG consumptions was determined, avoiding the emission of 1584 kg of CO2 per day. Marine thermal pollution is reduced by 3.5 times by recovering the working fluids' condensation heat for the LNG pre-heating.

Innovation is a crucial issue in healthcare services since it can affect job-related variables such as productivity, satisfaction and burnout. The aim of our study was to examine the impact of innovation support on quiet quitting, innovative behavior and innovation outputs among nurses. We conducted a cross-sectional study in Greece during April 2024. We employed a convenience sample of nurses. We used the following instruments: (a) the Innovation Support Inventory (ISI) to measure innovation support, (b) the Quiet Quitting Scale (QQS) to measure quiet quitting, (c) the Innovative Behavior Inventory (IBI) to measure innovative behavior, and (d) the Innovation Outputs (IO) scale to measure innovation outputs. Our multivariable analysis identified a negative relationship between innovation support and quiet quitting. Moreover, we found that managerial support and cultural support improved several aspects of innovative behavior, such as idea generation, idea search, idea communication, implementation starting activities, involving others, and overcoming obstacles. Additionally, managerial support improved innovation outputs. Our findings suggested the positive impact of innovation support on quiet quitting, innovative behavior and innovation outputs among nurses. Organizations and nurses’ managers should establish an innovative working environment to improve nurses’ passion, motives and productivity.

This study offers a concise summary of the research that has been done on alternative methods of HRM. A survey of 47 articles on the topic of creative human resource management uncovered three primary schools of thinking. At its core, innovation in HRM entails nothing more than that. One such topic worthy of investigation is the way human resource management approaches new situations. Third, research on inventiveness in the business world has given rise to the concept of "innovative HRM." Each of these three approaches, as well as the theoretical underpinnings of each, will be covered in this article. The note wraps up with a discussion of the significance of the findings for next research as well as clinical practice.

Faced with increasing climate challenges, this pioneering study introduces groundbreaking approaches to ensure the resilience of potato crops in east-central Poland. Our research aimed to develop an innovative, cost-effective system tailored to the diverse local conditions of this region. Conducted between 2018 and 2020, the study analyzed integrated and organic production systems across different soil types and potato varieties. The experiment was conducted using a randomized block design with three replications in two locations. Integrated practices, enhanced by mineral fertilization and chemical protection, notably delayed the onset of late blight by 16 days and extended the critical infection period by 17% compared to their organic counterparts. Remarkably, the integrated systems resulted in a 49% increase in total production and a 52% increase in commercial yields, demonstrating their effectiveness in enhancing crop resilience. Different potato varieties exhibit varied responses to cultivation systems, influencing both yield and disease resistance. Further investigation into these varietal responses can help optimize cultivation practices, leading to improved efficiency and sustainability in potato farming. Location and soil conditions have a significant impact on potato yield and the spread of potato blight. Further research into specific soil properties and the adaptation of varieties to local conditions can contribute to increased productivity and stability in potato production. This study not only paves the way towards sustainable agriculture but also highlights the crucial role of soil diversity in shaping resilient farming practices.

Chymotrypsin from the digestive organs of bigfin reef squid, a major commercial squid species in Thailand, was purified to 41.27-fold with 5.74% yield by a sequential purification process including ammonium sulfate precipitation, size exclusion and ion exchange chromatography. According to SDS-PAGE, the molecular weight of purified chymotrypsin was 43 kDa. Native-PAGE analysis revealed a single band for this purified enzyme. Optimum pH and temperature for chymotrypsin activity of the purified enzyme were pH of 7.0 with a temperatures of 55°C. The purified chymotrypsin remained stable throughout a wide range of pH levels (6–11) and at relatively high temperature (50°C). It was significantly inhibited by PMSF and TPCK. The values of the kinetic constants Km and Kcat were found to be 1.33 mM and 31.46 s‒1, respectively. The purified chymotrypsin has the N-terminal amino acid IVGGQEATPGEWPWQAALQV. This study provided new information about the biochemical properties of pure chymotrypsin from bigfin reef squid, which is useful in the future investigation, aquaculture and application of bigfin reef squid.

In this study, we demonstrate a high luminous efficacy of 118 lm/W and high reliability through 450°C thermal aging of white LEDs (WLEDs) utilizing four-inch YAG: Ce3+ phosphor-in-glass (PiG) plates designed for vehicle headlights. The sintering process of mixing glass and phosphor typically generates pores, which can scatter light and reduce the luminous efficacy of the fabricated PiG. In this study, we produced four-inch PiG plates under four different fabrication conditions to evaluate their luminous efficacy. Our results revealed that the PiG plate with a thin thickness of 0.08 mm exhibited a 16.83% increase in luminous efficacy compared to the 0.15 mm plate, attributed to reduced light interaction with the pores. Unlike silicone-based phosphor WLEDs, which offer high performance but lower reliability due to the silicone resin's low transition temperature (150°C), our novel thin PiG plate achieves high performance and reliability. This advancement suggests that the proposed thin PiG plate could replace traditional silicone-based phosphors, enabling the development of high-quality WLEDs for vehicle headlights in automotive applications.

The conversion of methane into chemicals is of interest to achieve a decarbonized future. Fuel cells are electrochemical devices commonly used to obtain electrical energy, but can be utilized either for chemicals production or both energy and chemicals cogeneration. In this work, the partial oxidation of methane in fuel cells for electricity generation and valuable chemicals production at the same time is reviewed. For this purpose, different types of methane-fed fuel cells, both low temperature fuel cells, such as PEMFCs and AAEMFCs, and high temperature fuel cells, such as SOFCs, have been used. Also if few works have been devoted to this topic, the promising results drive the development of fuel cells using methane as the source for the cogeneration of power and valuable chemicals.

Evaluation of drug permeability using cell monolayers is an important in vitro assay in the process of drug development, to identify compounds with favourable pharmacokinetics that may proceed to in vivo studies. When allowed to differentiate on permeable filters for at least 21 days, monolayers of Caco-2 cells develop morphological and functional properties similar to those of the intestinal epithelium. Permeability through Caco-2 monolayers is thus particularly relevant to assess drug absorption after oral administration. The major drawback of this assay is its very low throughput, with the cell monolayers being used in a single permeability assay. We have previously proposed a protocol to allow the re-use of the Caco-2 monolayer on additional permeability assays during the stable period and shown that cell monolayer integrity is maintained. In this work we evaluate the effect of re-use on the permeability of several reference compounds that permeate through passive pathways and show that the cell monolayers can be re-used twice in additional permeability assays. Preliminary results were also obtained regarding active transport pathways, and a new methodology is proposed to quantify the contribution from passive and active transport. This is a major step towards the full validation of the re-use methodology proposed, which at least triplicates the throughput of this important in vitro assay.

Traditional concrete pavements have poor water permeability, while the strength of pervious concrete pavements is low. To solve these problems, this study designed Innovative recycled aggregate pervious concrete (I-RAPC) with controllable water permeability and high strength by using response surface methodology, and investigated the effects of different pore parameters (number, diameter, material, distribution form, etc.) on the performance of I-RAPC. And the strength discount factor method was proposed to construct the theoretical calculation model of compressive strength and pipe pore parameters, and the calculation model of water permeability coefficient was established at the same time. The results show that the fewer the number of holes and the smaller the pipe diameter of I-RAPC, the higher its compressive strength and the smaller the water permeability coefficient. The theoretical model of compressive strength can accurately evaluate the discounting effect of the pore parameters on the compressive strength of I-RAPC, and the maximum relative error is only 7.52%, and the maximum relative error of the calculation model of water permeability coefficient is only 4.42%. I-RAPC has the advantages of high strength and permeability with controllable performance, which overcomes the problems of random distribution of pore space, uncertainty of water permeability, and strength of ordinary pervious concrete.

The exponential growth and widespread adoption of Internet of Things (IoT) devices have introduced many vulnerabilities. Attackers frequently exploit these flaws, necessitating advanced technological approaches to protect against emerging cyber threats. This study introduces a novel approach utilizing hardware honeypots as an additional defensive layer against hardware vulnerabilities, particularly hardware trojans (HTs). HTs pose significant risks to the security of modern integrated circuits (ICs), potentially causing operational failures, denial of service, or data leakage through intentional modifications. The proposed system was implemented on a Raspberry Pi and tested on an emulated HT circuit using a Field-Programmable Gate Array (FPGA). This approach leverages hardware honeypots to detect and mitigate HTs in IoT devices. The results demonstrate that the system effectively detects and mitigates HTs without imposing additional complexity on the IoT devices. The trojan-agnostic solution offers full customization to meet specific security needs, providing a flexible and robust layer of security. The findings provide valuable insights into enhancing the security of IoT devices against hardware-based cyber threats, thereby contributing to the overall resilience of IoT networks. This innovative approach offers a promising solution to address the growing security challenges in IoT environments.

Background: The two-stage technique combining the Endoscopic Retrograde CholangioPancreatography (ERCP) with common bile duct (CBD) clearance carried out before the laparoscopic cholecystectomy represents the most common approach for CBD stones. Over time, different techniques have been proposed to manage cholecysto- choledocholithiasis (CCL) advantageously in one stage. Among these, the laparoendoscopic rendez-vous (LERV) addresses the CCL issue with a laparoscopic cholecystectomy with insertion of a guide wire performed at initial stage of the procedure, followed by the clearance of the bile duct carried out by the endoscopists. The goal of this study was to evaluate the efficacy and safeness of LERV procedure recording results and complications, also making a comparison between our results and current literature. Methods: We reviewed our experience of all consecutive patients with cholecysto-choledocholithiasis managed with LERV between January 2018 and December 2023. LERV success rate, operative time, length of hospital stay, stone recurrence, incidence of endoscopic and surgical complications were analysed. Results: A total of 120 patients underwent LERV in our facilities. We reported a 97% LERV success rate, 1.6% conversion-to-open rate, a median intraoperative time of 122 (range 95-220) min. The median hospital stay was 4 (range 2-38) days. An overall morbidity of 15% was reported (18/120): 15 Clavien-Dindo type 1/2, 2 type 3a and one type 3b. In two cases a re-operation during the hospital stay was necessary. At a median follow-up of 14 months (3-59) five patients experienced stone recurrence requiring redo-ERCP in two cases. Conclusion: LERV offers the significant advantage of a single stage procedure and hospitalisation along with a lower risk of post-ERCP pancreatitis, failed CBD cannulation and complications. Our experience confirms safety and effectiveness of the technique for CCL management.

This study presented a novel and sustainable method for producing chitin nanocrystals (PA-ChNCs) using phosphoric acid hydrolysis. The produced PA-ChNCs were used as stabilizers for Pickering emulsions and their physicochemical properties as well as stabilization mechanisms were systematically investigated. The PA-ChNCs exhibited small particle sizes and high surface areas, enabling an effective adsorption at the oil/water interface, which prevented coalescence in Pickering emulsions. The particle size and surface charge PA-ChNCs were strongly pH-dependent, which were critical factors for stabilizing Pickering emulsions. The study showed that emulsions with higher O:W ratios (50%) exhibited larger droplets but greater viscosity, forming a stable gel-like matrix that was more stable than emulsions with other O:W ratios after storage for 30 days. Emulsions with higher PA-ChNCs concentrations (2.0 wt%) and higher pH values (pH 10) showed small droplets and high viscosity, leading to stable emulsions. This research contributes to the development of sustainable and effective emulsifiers for use in the food industry, making utilization of seafood waste in an eco-friendly manner possible. Overall, this study highlights the potential of using newly developed PA-ChNCs as stabilizers for Pickering emulsions in food products.

Fiber-reinforced mycelium (FRM) composites offer an innovative and sustainable approach to construction materials for architectural structures. Mycelium, the root structure of fungi, can be combined with various natural fibers (NF) to create a strong and lightweight material with environmental benefits. Incorporating NF like hemp, jute, or bamboo into the mycelium matrix enhances mechanical properties. This combination results in a composite that boasts enhanced strength, flexibility, and durability. Natural FRM composites offer sustainability through the utilization of agricultural waste, reducing the carbon footprint compared to conventional construction materials. Additionally, the lightweight yet strong nature of the resulting material makes it versatile for various construction applications, while its inherent insulation properties contribute to improved energy efficiency in buildings. Developing and adopting natural FRM composites showcase a promising step towards sustainable and eco-friendly construction materials. Ongoing research and collaboration between scientists, engineers, and the construction industry will likely lead to further improvements and expanded applications. This article provides a comprehensive analysis of the current research and applications of natural FRM composite for innovative and sustainable construction materials. Additionally, the paper reviews the mechanical properties and potential impacts of these natural FRM composites in the context of sustainable architectural construction practices. Recently, the relevance of mycelium-based materials has extended beyond their original fields of microbiology and mycology to architecture.

Esters are versatile compounds with a wide range of applications in various industries due to their unique properties and pleasant aromas. Conventionally, the manufacture of these compounds has relied on the chemical route. Nevertheless, this technique employs high temperatures and inorganic catalysts, resulting in undesired additional steps to purify the final product by removing solvent residues, which decreases environmental sustainability and energy efficiency. In accordance with the principles of “Green Chemistry” and the search for more environmentally friendly methods, a new alternative, the enzymatic route, has been introduced. This technique uses low temperatures and does not require the use of solvents, resulting in more environmentally friendly final products. In spite of the large number of studies published on the biocatalytic synthesis of esters, little attention has been paid to the reactors used for it. Therefore, it is convenient to gather the scattered information regarding the type of reactor employed in these synthesis reactions, considering the industrial field in which the process is carried out. The comparison between the performance of the different reactor configurations will allow us to draw the appropriate conclusions regarding their suitability for each specific industrial application.

Anastomotic insufficiencies are severe complications of abdominal surgery, often leading to pro-longed hospitalization, serious tissue inflammation, even sepsis and the need for recurrent sur-gery. Current non-surgical treatments such as self-expanding metal stents (SEMS) and endoscopic vacuum therapy (EVT) have limitations, including stent migration or perforation. This review evaluates the effectiveness of the VacStent GITM, a novel medical device combining SEMS and negative-pressure wound therapy in treating gastrointestinal leaks. Data were gathered from four prospective studies and compared with existing treatments. Studies on the VacStent GITM applica-tion demonstrate technical success and competitive closure rates in upper gastrointestinal leaks, with minimal complications reported. Comparative analyses with SEMS and EVT reveal prom-ising and most importantly equally good outcomes while maintaining the possibility for sus-tained enteral nutrition and reducing stent migration risk. The VacStent GITM presents a promis-ing alternative to current non-surgical treatments. Ongoing research aims to validate its efficacy in lower gastrointestinal leaks and establish its role in leak management comprehensively. Fur-ther investigation is necessary to confirm these findings and optimize treatment protocols. Future usages of the VacStent GITM in colonic anastomotic insufficiencies promise an effective approach and might be able to lower the rates of necessary implementations of a stoma.

From grape cultivation to ripening and harvest timing to processing, each step can be a critical point when it comes to wine quality and phenolic composition. In this study, the influence of winemaking technology on resveratrol and quercetin content, as well as other polyphenolic compounds, was investigated. Resveratrol is a non-flavonoid polyphenolic stilbene synthesized by grape skin when damaged by infectious diseases or ionizing radiation. Quercetin is a phenol found in grape skins and stems and is produced to protect grapes from UV light damage. Trans-resveratrol and quercetin are known to act as antioxidants, reduce the risk of atherosclerosis and type 2 diabetes, inhibit the growth of cancer cells, and prevent the release of allergic and inflammatory molecules. However, the question was whether red wine could be enriched with these phenols using an innovative winemaking technology. The innovative idea was to completely replace the cold maceration process with maceration with the addition of wild yeast (Torulaspora delbrueckii, Td). Maceration with the addition of wild yeast (Td) offers the following advantages over traditional cold maceration: (1) higher concentrations of trans-resveratrol (>35-40%) and quercetin (>35-40%) in the final wine, (2) the new wine has a higher potential for human health, (3) the wine has a better aroma and stability due to the higher mannoprotein content, and (4) the better energy efficiency in the production process. The study of stability during storage and aging also included derivatives of benzoic acid and hydroxycinnamic acid, piceid, catechin, naringenin, rutin, kaempherol, hesperetin, and anthocyanins. The study found that younger wines had higher phenolic content, while storage of the wine resulted in a decrease in total phenolic content, especially monomeric stilbenes and quercetin.

Large-span post-tensioned (PT) beams play a crucial role in maximizing the benefits of post-tensioning techniques. Bonded and unbonded systems are prevalent, with the latter being more widespread in the United States. While bonded systems are advantageous for creating long spans when multiple tendons are grouped in ducts, limited literature exists on their demolition. In a case study, this paper addresses the unique challenge of demolishing large-span bonded post-tensioned beams due to a building's functional change. Emphasizing insights for engineers, it explores the use of cutting and dismantling methods, considering the presence of prestressed cables. The demolition process is distinctive due to the presence of numerous pre-stressed cables along the beams, necessitating a specialized and cautious cutting approach. This is accomplished through the use of a drilling technique that selectively distresses the tendons, ensuring they are not all affected simultaneously. An intriguing observation discussed in this paper pertains to the occurrence of horizontal cracks accompanied by loud sounds following the drilling process, offering insights from the design perspective of PT systems. The paper details an innovative method for safely demolishing large-span bonded PT beams, using ground-penetrating radar and computer models to navigate structural complexities and ensure nearby structures' safety.

Low fertility is a critical social problem worldwide, and infertility has a prevalence of 15%. This cross-sectional study aimed to understand the factors affecting the usage and satisfaction of Korean medicine (KM) in subfertile women. An online survey was conducted from November 3 to November 8, 2021. The survey collected basic information, KM treatment experience, and satisfaction from women who experienced poor pregnancy. The t-test and chi-square test (χ2-test) were used to determine the overall characteristics of the subjects and factors affecting the utilization and satisfaction of KM treatment. Of the total of 29,465 people, 4,922 read the survey email, and 601 responded. After excluding 51 insincere respondents, 550 respondents were included in the final analysis. Of these, 43.1% had experience with conventional treatment, and 15.6% had received KM treatment. Integrative subfertility treatment was significantly more common (24.9%) than KM treatment alone (10.2%) (P=0.00). Women with no childbirth experience (P=0.01) and those with a master’s degree (P=0.01) were more willing to participate in the ‘KM Support Project for Subfertility’. Our findings suggest that subfertile patients prefer integrated medical treatment over KM alone. Further studies are needed to assess the status of integrative medicine treatment, satisfaction with each KM intervention, factors for low satisfaction, and patient requirements.

Non-impregnated small pore graphite (NSPG) with the compact microstructure for using in molten salt reactors (MSR) was prepared by the novel process, and the pore diameter of the obtained graphite was reduced to ~800 nm. The irradiation evaluation of the prepared graphite was carried out by 7 MeV Xe26+ ion irradiation and the microstructural changes of the graphite were investigated with IG-110 as a comparison. The graphitization degree of NSPG was higher than that of IG-110, though it was not subjected to an impregnation process. Under low-dose ion irradiation (

Dye-containing effluent generated in textile industries is polluting and complex wastewater. It should be managed adequately before the final destination. The up-flow anaerobic blanket (UASB) reactor application is an eco-friendly and cost-competitive treatment. The present study briefly reviews the UASB application for dye wastewater valorization. Bioenergy and clean water production potential during dye-containing wastewater treatment are emphasized to promote resource recovery in textile industries. Efficiencies of color and chemical oxygen demand of 50–97% and 60–90% are reported in bench-scale UASB studies. A biogas yield of 0.36–36.04 L d-1 in UASB, which treats dye-containing effluents, is documented. Bioenergy production and water reuse allow environmental and economic benefits. However, data on full-scale UASB treating dye wastewater are missing. Besides, studies on combined systems integrating membrane processes, such as ultrafiltration and nanofiltration, and pretreatment of wastewater and sludge for improvements in biogas production might realize the complete potential for resource recovery of UASB technology.

This work presents a nonlinear model predictive control scheme that challenges overcoming the obstacles holding back over decades to develop affordable autonomous control and monitoring systems applied in the large-scale industry. Among the numerous proposals in the literature, most do not consider the significant fluctuation of kinetic parameters in the reduced mathematical model ADM2, widely used for control and monitoring purposes. The prevalent cause, on a basis, is the lack of information caused by some dynamics and parameters that cannot be measured in real-time by reliable sensors. In addition, to make matters worse, those systems inherently act with nonlinear nature and have a high sensitiveness to uncontrollable inputs and perturbations. Therefore, to prevent these drawbacks, this work proposes a new methodology that reconstructs the lack of information from the non-measurable dynamics, concentration of bacterias, and the kinetic parameters related to reaction rates. Simulations results demonstrate the effectiveness of the methodology compared with traditional industrial control schemes.

Alzheimer's disease (AD) remains a significant challenge in the field of neurodegenerative disor-ders, even nearly a century after its discovery, due to the elusive nature of its causes. The develop-ment of drugs that target multiple aspects of the disease has emerged as a promising strategy to address the complexities of AD and related conditions. The immune system's role, particularly in AD, has gained considerable interest, with nanobodies representing a new frontier in biomedical research. Advances in targeting antibodies against amyloid-β (Aβ) and using messenger RNA for genetic translation have revolutionized the production of antibodies and drug development, open-ing new possibilities for treatment. Despite these advancements, conventional treatments for AD, such as Cognex, Exelon, Razadyne, and Aricept, often have limited long-term effectiveness, under-scoring the need for innovative solutions. This necessity has led to the incorporating of advanced technologies like artificial intelligence and machine learning into the drug discovery process for neurodegenerative diseases. These technologies help identify therapeutic targets and optimize lead compounds, offering a more effective approach to addressing the challenges of AD and similar conditions.

The satellite Earth observation (EO) sector is burgeoning with hundreds of commercial satellites being launched each year, delivering a rich source of data that could be exploited for societal benefit. Data streams from the growing constellation of commercial satellites are of variable quality, limiting the potential for their combined use in science applications that need long time-series data from multiple sources. The quality of calibration performed on optical sensors onboard many satellite systems is highly variable due to calibration methods, sensor design, mission objective, budget, or other operational constraints. A small number of currently operating well-characterised satellite systems with onboard calibration, such as Landsat-8/9, Sentinel-2, and planned future missions like the NASA Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder, the European Space Agency (ESA) Traceable Radiometry Underpinning Terrestrial and Helio Studies (TRUTHS), and LIBRA from China, are considered benchmarks for optical data quality due to their traceability to international measurement standards. This paper describes the concept of a space-based transfer calibration radiometer called the Satellite Cross-Calibration Radiometer (SCR) that would enable the calibration parameters from satellites such as Landsat-8/9, Sentinel-2, or other benchmark systems to be transferred to a range of commercial optical EO satellite systems while in orbit. A description of the key characteristics of the SCR to successfully operate in orbit and transfer calibration from Reference systems to Client systems is presented. A system like the SCR in orbit could complement SI-Traceable satellites (SITSats) to improve data quality and consistency and facilitate the interoperable use of data from multiple optical sensor systems for delivering higher returns on the global investment in EO.

Sensory integration is an essential function of human life, and its decline causes difficulties in the quality of life, especially in older adults. In this study, we proposed an arm-reaching task based on a virtual reality head-mounted display (VR-HMD) system to assess sensory integration in daily life, and examined whether reaching task performance was associated with age and resting-state functional connectivity (rsFC) between the brain regions of interest involved in sensory integration. We hypothesized that performance during a reaching task with multiple cognitive loadings would be affected by aging. The gap angle between the reaching hand and target positions was compared between older and middle-aged adults as a measure of sensory integration function. In addition, rsFC, which was significantly correlated with the gap angles of individual participants in the older adult group, was identified using resting-state functional magnetic resonance imaging data. The mean gap angle was significantly larger in the older adults than in the middle-aged group and was also significantly correlated with connections between the left primary motor area and the left inferior temporal gyrus, temporo-occipital part. Because the connectivity between the areas is known to be related to visuomotor integration, the results suggest the involvement of visuomotor integration in the decline of sensory integration function in old age and the validity of the gap angle during the proposed VR-HMD task as an index for the decline in function.

This study aims at highlighting and illustrating innovative actions for achieving and/or improving accurate medical coding within a DRG system. Already grouped DRG cases recorded in the first DRG implementation year in the region of Crete were examined. A sample of 130,000, from a total of 200,000, cases were analyzed and audited, through a process consisting of three stages: i) Digitalization, ii) Auditor training, and iii) Control & consultation. The results indicated that a significant proportion of DRG coding, with a length of stay exceeding one day, were reclassified into different DRG categories. This was not primarily due to errors in the selection of the principal diagnosis, but resulted from coding errors, including omission of secondary diagnoses coding, medical procedures that should have been included and utilization of less specific codes. The findings indicate that medical coding control, consulting services and the adoption of targeted actions can be instrumental for proper implementation of the DRG coding system, and for ensuring transparent allocation of resources within hospitals. Ultimately, this shortens the coding learning curve, from four years typically reported in the international literature, to a more efficient duration of two years, leading to rational and documented clinical and financial management of hospitals.

Purpose- This study seeks to investigate the collaboration between Digitalization and traditional manufacturing industry and investigate, how digitalized management brings new chances and challenges of management. Design/methodology/approach – The author designed a content analytical study researching the role of digitalization in traditional manufacturing industries. The article presents a selective but systematical review of recent digitalization trend and digital twin to be applied for innovative management in Industry 4.0 era. Findings– Digitalization is highly correlated with traditional manufactory in Industry 4.0 era. The study brings a new outlook on the next wave of Digitalization and review of associated challenges and opportunities for management and innovation in traditional manufacturing industries. Research limitations/implications – The research focuses on two branches of traditional industries only: machine tools building and metalworking industries. Future research needs to examine other traditional industries. The research is limited to 2 high related traditional manufacturing industries, machine tools and metalworking industry. Practical implications – The study and application of digitalization should be highly recommended and launched in traditional manufacturing industries. Universities, institutes and vocational schools should update, optimize their courses systems according to prediction of future industry. Originality/value – The paper enhances understanding about the collaboration between digitalization and traditional manufacturing industry. This paper analyzes an important issue the digitalization serves traditional industries. It is unique in its broad analysis of the related terms – Digitalization, Machines 4.0, Industry 4.0 and innovative management in Industry 4.0 era.

Recently, attention mechanisms have developed into an important tool for performance improvement of deep neural networks. In computer vision, attention mechanisms are generally divided into two main branches: spatial and channel attention. Both attention categories have their own advantages. The fusion of both attentions achieves higher performance, on the cost of the computational load. This paper introduces an innovative and lighter n-shifted sigmoid channel and spatial attention (CSA) module to reduce the computational cost and to improve the 3D scene relevant features selection. To validate the proposed attention module, 3D scene object detection in the deep Hough voting point sets is considered as the testing application. The proposed attention module with its piecewise n-shifted sigmoid activation function improves the network’s learning and generalization capacity which effectively predict bounding box parameters directly from 3D scenes and detect objects more accurately. This advantage is achieved by selectively attending to more relevant features of the input data. When used in the deep Hough voting point sets, the proposed attention module outperforms state-of-the-art 3D detection methods on the sizable SUNRGBD dataset. Experiments conducted showed an increase of 12.02 mean accuracy precision (mAP) when compared to the celebrated VoteNet (without attention). It also got 9.92 mAP higher compared to the MLVCNet, and 10.32 mAP higher than the Point Transformer. The proposed model not only decreases the sigmoid vanishing gradient problem but also brings out valuable features by fusing channel-wise and spatial information while improving accuracy results in 3D object detection.

Globalized in 1995 through the TRIPs Agreement, humanity’s dominant mechanism for encouraging innovations involves 20-year product patents, whose monopoly features enable innovators to reap large markups or licensing fees from early users. Exclusive reliance on this reward mechanism in the pharmaceutical sector is morally problematic for two main reasons. First, it imposes a great burden on poor people who cannot afford to buy patented treatments at monopoly prices and whose specific health problems are therefore neglected by pharmacological research. Second, it discourages pharmaceutical firms from fighting diseases at the population level with the aim of slashing their incidence. These problems can be much alleviated by establishing a supplementary alternative reward mechanism that would enable pharmaceutical innovators to exchange their monopoly privileges on a patented product for impact rewards based on the actual health gains achieved with this product. Such an international Health Impact Fund (HIF) would create powerful new incentives to develop remedies against diseases concentrated among the poor, rapidly to provide such remedies with ample care at very low prices, and to deploy them strategically to contain, suppress, and ideally to eradicate the target disease. By promoting innovations and their diffusion together, the HIF would greatly enlarge the benefits, and thereby also the cost-effectiveness, of the pharmaceutical sector, in favor of the world’s poor especially.

As technology and multimedia production have advanced, there has been a significant rise in attacks on digital media, resulting in duplicated, fraudulent, and altered data and the infringement of copyright laws. This paper presents a robust and secure digital image watermarking technique that has been implemented in the spatial domain and exploits the erratic and chaotic behaviour of the powerful elementary cellular automata rule-30. The crucial characteristics of the watermarking system, i.e., imperceptibility, capacity, and robustness, have been perfectly balanced by the suggested blind watermarking technique. In this approach, prior to embedding, the grayscale watermark image is downsized to its two Most Significant Bits (MSBs). Then, the 2-MSBs watermark is encrypted using an ECA rule-30 so as to level up the security attribute of the system. Then, the host image is scrambled using ECA rule-30 to distribute the watermark pixels throughout the host image and thus achieve the highest robustness against geometrical attacks. Finally, the encrypted watermark data is embedded into the scrambled host image using the ECA rule-30-based embedding key. The proposed method performs better in terms of imperceptibility, capacity, and robustness when compared to several systems with similar competencies. The simulation's findings demonstrate strong imperceptibility as evaluated by the Peak Signal-to-Noise Ratio (PSNR), which has an average value of 58.3735 dB and a high payload. The experimental outcomes, observed across a diverse range of standardized attack scenarios, unequivocally establish the ascendancy of the proposed algorithm over competing methodologies in the realm of image watermarking.

The prospect of drinking water serving as a conduit for gut bacteria, artificially selected by disinfection strategies and lack of monitoring at the point of use, is concerning. Certain opportunistic pathogens, notably some nontuberculous mycobacteria (NTM), often exceed coliform bacteria levels in drinking water, posing safety risks. NTM and other microbiota resist chlorination and thrive in plumbing systems. When inhaled, opportunistic NTM can infect the lungs of immunocompromised or chronically ill patients, and the elderly, primarily postmenopausal women. When ingested with drinking water, NTM often survive stomach acidity, reach the intestines, migrate to other organs using immune cells as vehicles, potentially colonizing tumor tissue, including in breast cancer. The link between the microbiome and cancer is not new, yet the recognition of intratumoral microbiomes is a recent development. Breast cancer risk rises with age, and NTM infections emerged as a concern among breast cancer patients. In addition to studies hinting at a potential association between chronic NTM infections and lung cancer, NTM have also been detected in breast tumors at levels higher than normal adjacent tissue. Evaluating the risks of continued ingestion of contaminated drinking water is paramount, especially given the ability of various bacteria to migrate from the gut to breast tissue via entero-mammary pathways. This underscores a pressing need to revise water safety monitoring guidelines and delve into hormonal factors, which includes addressing the disproportionate impact of NTM infections and breast cancer on women and examining the potential health risks posed by the cryptic and unchecked microbiota from drinking water.

Environment, forage quality, management practices, pathogens and pesticides influence honeybee responses to stressors. This study proposes an innovative approach to assess colony health and performance using molecular diagnostic tools, by correlating hemolymph proteins with common measures of colony strength, prevalent honeybee pathogens (Varroa destructor and Nosema spp.) and essential elements (iron, zinc and copper). Colonies were selected from four apiaries in the province of Bologna (Italy), located in different environmental and foraging conditions. Haemolymph samples were taken from June to October 2019. The Varroa infestation of the colonies was estimated by assessing the natural fall of the mites, while the bees were tested for Nosema spp. spores using microscopic method. Proteins were separated using SDS-PAGE and colony performance was assessed by determining adult bees, total brood, and honey and pollen reserves. The biomarkers measured proved to be useful for monitoring changes in performance and trophic conditions during summer and early autumn. Significant correlations were found between haemolymph proteins and colony performance measures. A positive correlation between pollen reserves and vitellogenin and hexamerin 70a highlights the importance of these proteins for successful overwintering. In October, Varroa infestation was negatively correlated with total proteins, vitellogenin, apolipophorin II, transferrin, and hexamerin 70a, with negative implications for overwintering; furthermore, Varroa infestation was also negatively correlated with iron content, potentially affecting iron homeostasis.

Keywords: Artificial Intelligence in Implantology; AI in Dental Implantology; Machine Learning in Dental Implantology; Deep Learning in Implant Dentistry; Robotics in Dental Implantology; AI-Based Implant Planning.

Fingerprint recognition systems have achieved widespread integration into various technological devices, including cell phones, computers, door locks, and time attendance machines. Nevertheless, individuals with worn fingerprints encounter challenges when attempting to unlock original fingerprint systems, resulting in disruptions to their daily activities. This study explores two distinct methods for fingerprint backup: traditional fingerprint impression and 3D printing technologies. Unlocking tests were conducted on commonly available optical fingerprint lock-equipped cell phones to assess the efficacy of these methods, particularly in unlocking worn fingerprints. The research findings indicated that traditional fingerprint impression method exhibited high fidelity in reproducing fingerprint patterns, achieving an impressive unlocking success rate of 97.8% for imprinting unworn fingerprints. However, when dealing with worn fingerprints, traditional fingerprint impression technique showed a reduced unlocking success rate, progressively decreasing with increasing degrees of finger wear. In contrast, 3D printed backup fingerprints, with image processing and optimization of ridge height, mitigated the impact of fingerprint wear on unlocking capability, resulting in an unlocking success rate of 84.4% or higher. Thus, the utilization of 3D printing technology proves advantageous for individuals with severely worn or incomplete fingerprints, providing a viable solution for unforeseen circumstances.

A novel electrospun nanofiber was developed using polyamide-6 (PA) and ε-poly-L-lysine (PL). PA is a popular textile polymer having desirable mechanical and thermal properties, chemical stability, and biocompatibility. However, PA nanofibers are prone to bacterial growth and user discomfort. PL, a natural homopolyamide, is non-toxic, antimicrobial, and hydrophilic but lacks spinnability due to its low molecular weight. Given its similar backbone structure as PA, with an additional amino side chain, PL was integrated with PA to develop multifunctional nanofibers. This study explores a simple, scalable method to obtain PL nanofibers by utilizing the structurally similar PA as the base. The goal was to enhance the functionality of PA by addressing its drawbacks. The study demonstrates spinnability of varying concentrations of PL with base PA while exploring compositions with higher PL concentrations than previously reported. Electrospinning parameters were studied to optimize the nanofiber properties. The effects of PL addition on morphology, hydrophilicity, thermal stability, mechanical performance, and long-term antimicrobial activity of nanofibers were evaluated. The inclusion of PL in PA-based nanofibers resulted in super hydrophilicity, increased tensile strength, and efficient antimicrobial properties with long-term stability. These enhanced characteristics hold promise for the composite nanofiber’s application in medical and protective textiles.

Object of this work is the design and the simulation of a hybrid UAV with VTOL capabilities that has been designed for landing on naval moving platforms. The work is focused on the innovative propulsion layout adopted on the UAV. Authors discuss how adopted low level control strategies can exploit the innovative features of the proposed system assuring a good rejection of transversal wind disturbances. Particular attention is dedicated to low level modelling and control of the system emphasizing how choices regarding low level actuation and control should improve performances and robustness of the system.

Efficiency improvement is the new challenge in all fields of design. In this scenario the reduction of power losses is becoming more and more a main concern also in the design of power transmissions. Appropriate models to predict power losses are therefore from the earliest stages of the design phase. The aim of the project is to carry on lubrication simulations of several variants of a cylindrical-roller-bearing to understand the lubricant distribution and the related churning power losses. Several strategies to reduce the computational effort have been used. Among them the sectorial symmetry and three innovative meshing strategies (purely analytical with and without interfaces and analytical/subtractive) that have been implemented in the OpenFOAM® environment. The results of the different approaches were compared among them and with experimental observations showing good agreement and reasonable savings in terms of computational effort.

Among the many Lysosomal Storage Disorders (LSDs) that would benefit from the establish-ment of novel cell models, either patient-derived or genetically engineered, is Mucopolysaccha-ridosis type II (MPS II). In fact, even though a specific therapeutic approach does exist for this disorder (Enzyme Replacement Therapy, ERT, with recombinant human IDS) and haematopoiet-ic stem cell transplantation (HSCT) may also hold promise whenever the disorder is diagnosed soon enough, both approaches have their own drawbacks. Here we present our results on the establishment and characterization of two MPS II pa-tient-derived stem cell line(s) from deciduous baby teeth. To the best of our knowledge, this is the first time a stem cell population is isolated from LSD patient samples obtained from the oral cavity. Taking into account our results on the molecular and biochemical characterization of those cells and our first insights on their subcellular MPS phenotype, we consider these cells will be a valuable tool for both pathophysiological assessments and drugs screenings. Ultimately, we believe patient-derived dental pulp stem cells (DPSC) may represent a feasible alternative to induced pluripotent stem cells (iPSC) in many labs with standard cell culture con-ditions and limited (human and economic) resources.

The large-scale processing of Cassava (Manihot esculenta Crantz.) generates significant quantities of solid wastes annually. Cassava peels (CP) account for 5 wt.% - 30 wt.% of wastes from the processing of cassava tubers. The poor disposal and management of CP pose risks to human health, safety and the environment. Therefore, there is an urgent need to identify and examine low cost, socially acceptable and environmentally friendly strategies to mitigate the immediate and long terms disposal and management challenges. Lack of such measures results in the accumulation of CP wastes, which are currently buried, combusted, or dumped in open fields. Therefore, this paper reviewed the potential routes for the biochemical, thermochemical, and plasma valorisation of CP. The literature reviewed revealed that biochemical technologies such as anaerobic digestion (AD) and fermentation are the most widely utilised approaches currently adopted for CP valorisation. AD produces biogas (methane 50-72 vol. % and carbon dioxide 25-45 vol. %), whereas fermentation yields bioethanol. However, the numerous challenges such as substrate-induced inhibition, associated with the biochemical processes hamper microbial degradation, methane formation, and process efficiency. Furthermore, the processes generate secondary wastes or digestate/sludge, which requires additional processing before disposal. Therefore, innovative thermal, thermochemical, and plasma technologies were proposed to valorise CP into syngas, biofuels, bioenergy, biochemicals, and fertilizers, among others. However, the waste products of fermentation cannot be effectively utilised as bio-fertilizers, whereas bioethanol causes corrosion in engines. Overall, the biochemical, thermal, thermochemical and plasma technologies can effectively valorise CP for effective net energy generation.

In this paper, the effect of Bi₂O₃ doping on the mechanical properties of PbO ceramic pellets was studied. For this purpose, different ratios of Bi2O3/PbO (i.e., xBi2O3–(1-x)PbO, where x is 0, 1, 3, 5, 7 wt%) were fabricated and sintered at 570, 620, and 670°C. Mechanical properties including density, hardness, flexural strength, and sintering of PbO were studied for the aforementioned compositions. Phase compositions, microstructures, and worn surfaces of the composites were characterized by scanning electron microscopy and X-ray diffraction (XRD). The XRD analysis revealed that a solid solution formed in the composite ceramic. The best suited conditions of temperature and doping of Bi₂O₃ for optimal sintering are 620°C and 3 wt%, respectively. The hardness of the 3 wt% Bi2O3–97 wt% PbO ceramic was 717 MPa, which is about four times higher than the hardness of pure PbO; in addition, the strength of the composites was 43 MPa, which is two times higher than that of pure PbO. The integrity of the composites was verified using the lead–bismuth eutectic alloy flushing experiment. Results of this research paper are important for future studies of oxygen control in the lead–bismuth eutectic alloy of lead-cooled fast reactors.

Alzheimer’s disease (AD) is an age-associated neurodegenerative disorder. A wealth of evidence indicates that the amyloid β (Aβ) aggregates result from dyshomeostasis between Aβ production and clearance, which plays a pivotal role in the pathogenesis of AD. Consequently, therapies targeting Aβ reduction represent a promising strategy of AD intervention. Tetramethylpyrazine nitrone (TBN) is a novel tetramethylpyrazine derivative with the potential for the treatment of AD. Previously, we demonstrated that TBN markedly improved cognitive functions and reduced Aβ, APP, BACE 1 and hyperphosphorylated tau levels in 3 × Tg-AD mice. However, the mechanism by which TBN inhibits Aβ deposition still unclear. In this study, we employed the APP/PS1 mice treated with TBN (60 mg/kg, ig, bid) for six months and N2a/APP695swe cells treated with TBN (300 μM) to explore the mechanism of TBN on the Aβ reduction. Our results indicated that TBN significantly alleviated cognitive impairment and reduced Aβ depositions in APP/PS1 mice. Further investigation of the underlying mechanisms revealed that TBN decreased the expression of APP and BACE1, activated the AMPK/mTOR/ULK1 autophagy pathway and inhibited the PI3K/AKT/mTOR/ULK1 autophagy pathway, as well as decreased the phosphorylation levels of JNK and ERK in APP/PS1 mice. Moreover, TBN was found to significantly reduce the mRNA levels of APP and BACE1, as well as those of SP1, CTCF, TGF-β, and NF-κB, transcription factors involved in regulating gene expression. Additionally, TBN was observed to decrease the level of miR-346 and increase the levels of miR-147 and miR-106a in the N2a/APP695swe cells. These findings indicate that TBN may reduce Aβ levels likely via reducing APP expression by regulating APP gene transcriptional factors and miRNAs, reducing BACE1 expression, and promoting autophagy activities.

Technological advances in DBS hardware and software represent a significant growth area in functional neurosurgery. These advancements have the potential to significantly enhance treatment outcomes and expand the scope of neurological disorders that can be effectively addressed through DBS interventions. The introduction of directional DBS marks a new phase in neuromodulation, offering extended benefits for patients with Parkinson's disease, more efficient optimization of clinical outcomes, and targeted treatment of refractory symptoms through data-driven approaches. Implementing a multimodal programming strategy, incorporating novel current fractionation technology and image-guided tools for lead localization and brain sensing, further reduces reliance on traditional trial-and-error programming methods, paving the way for a more predictive application of this therapy. These advancements are expected to drive the development of sophisticated closed-loop stimulation systems capable of integrating continuous data streams for improved patient care.

Greenery-covered towers are a new generation of tall buildings characterized by substantial integration of vegetation. They aim to improve the quality of urban life by reducing air pollution, enhancing biodiversity, creating microclimates, and providing aesthetic and psychological benefits. This paper examines the innovative design approaches of greenery-covered towers, drawing on examples from different countries and contexts. It analyzes the technical, environmental, social, and economic aspects of these projects, as well as the challenges and opportunities they pose for the future of sustainable architecture. The paper concludes that greenery-covered towers should be further developed and refined to become a potential solution for addressing dense cities’ environmental and health issues.

This paper presents a new method for approximating the classical arcsine function. The proposed approximating methodology is simpler in its approach than other classical approaches and undeniably innovative. It is based on matrix representation besides the basic interpolation to approximate the inverse trigonometric function. It provides an efficient model which allows for reliable and precise calculations. The results are as per our knowledge unseen results in the previous literature.

The masonry building Heritage is appreciated for its aesthetic and historical value all around the world. The widespread presence of curved elements, such as arch, vault and dome express the relevant constructive abilities in the different historical epochs. These curved elements are characterized by architectural beauty, structural strength (especially against the gravity loads), thermal comfort and fire resistance. On the other hand, curved structures required scaffolding in order to be erected. The design, the construction and the dismantling of the scaffolds is typically time-consuming and expensive. In addition, the on-site working risk is related to time-interferences (e.g. in manpower working, at the same time, over and under scaffold). This technology dates back to the Era of the Roman Empire and it is currently still used, despite its limitations and disadvantages. In the present paper, an innovative technique (recently patented), aiming for the construction of a curved structural member without scaffolds, is proposed and illustrated. It consists in a Hinged Lifting Arch (HLA), using FRP (Fiber Reinforced Polymer) bonded strips. In details, a series of blocks are cut following an arch geometry and then aligned on the ground-floor in order to bond a composite on their top surface. Moreover, the impregnation of the polymeric adhesive is not allowed at the extremities of each block. The fiber sheet is applied continuously along the entire extrados. In this sense, hinges are introduced, in fact, the FRP-connected blocks are able to easily rotate, in the opposite direction, around the contact ends (i.e. hinge). Finally, the middle block is lifted-up and the arch takes the desiderated shape. In the first experimental demonstration, the natural calcareous stone was used, even if the proposed technique is totally material-independent. Moreover, an analytical model is proposed and discussed for designing the proper aspect ratio of the blocks in order to ensure the full mutual contact when the HLA is totally lifted up. The advantages of the proposed technique are related to the absence of scaffolds and improved seismic strength against horizontal loads thanks to the presence of the FRP, which limits the occurrence of hinges at the extrados.

A unique method for synthesizing a surface modifier for metallic hydrogen permeable mem-branes based on non-classic bimetallic pentagonally structured Pd-Pt nanoparticles has been de-veloped. It was found that nanoparticles had unique hollow structure. This significantly reduces the cost of their production due to economical use of metal. According to the results of electro-chemical studies, synthesized bimetallic Pd-Pt/Pd-Ag modifier showed excellent catalytic activi-ty (up to 60.72 mA cm–2), long-term stability and resistance to COads poisoning in alkaline oxida-tion reaction of methanol. The membrane with pentagonally structured Pd-Pt/Pd-Ag modifier showed the highest hydrogen permeation flux density up to 27.3 mmol s–1 m–2. Obtained hy-drogen flux density were 2 times higher than that for membranes with classic Pdblack/Pd-Ag modifier and an order of magnitude higher than that for unmodified membrane. Since the rate of transcrystalline hydrogen transfer through a membrane increased, while the speed of transfer through defects remained unchanged, a one and a half times rise in selectivity of the developed Pd-Pt/Pd-Ag membranes was recorded and it amounted to 3514. Achieved results are due to both the synergistic effect of the combination of Pd and Pt metals in the modifier composition and the large number of available catalytically active centers, which are present as a result of non-classic morphology with high-index facets. The specific faceting, defect structure and unusual properties provide great opportunities for the application of nanoparticles in the areas of membrane reac-tors, electrocatalysis, petrochemical and hydrogen industries.

Remote distributed generation control and demand response is nowadays a basic need, especially for the Distributed Network Operators (DNOs). The integration of Renewable Energy Sources (RES) with stochastic production characteristics into the grid in conjunction with the newly appeared stochastic demand consumers (i.e., electric vehicles) hardens the ef-forts of the DNOs to keep the grid’s operation within safe limits and prevent cascading black-outs while staying in compliance with the SAIDI and SAIFI indices during maintenance and re-pair operations. Taking also under consideration the aging of the existing grid infrastructure, making it year by year more prone to failure, it is yet of great significance for the DNOs to have access to real-time feedback from grid’s infrastructure, fast, with low-cost upgrade interventions, easily deployed on the field and with fast response potential, in order to be able to perform real-time grid management (RTGM). In this article, we describe the architecture, development and deployment of a hybrid real-time control system of distributed generation (DG) units, which has the potential to be applied easily to DNO’s substations, RES plants and consumers (i.e. electric vehicles’ charging stations), that combines a low-cost minimum intervention into the electricity grid and its components and eliminates all communication interoperability problems between the different vendors’ installed electrical equipment.

CO₂ geological storage in deep saline aquifers was recently developed at industrial scale mainly in sandstone formations. Experiences on CO₂ injections in carbonates aquifers for permanent trapping are quite limited, mostly from US projects such as AEP Mountaineer, Michigan and Williston Basin. The behavior of fractures in carbonates plays a key role in those reservoirs in which porous matrix permeability is very poor, which drives the CO₂ plume migration through the fracture network where hydromechanics and geochemical effects take place due to injection. Hontomín (Spain) is the actual on-shore injection pilot in Europe (EP Resolution of 14 January 2014), whose reservoir is comprised of fractured carbonates. Existing experiences from field scale tests conducted on site have supported to better understand the behavior of this type of reservoirs for CO₂ geological storage. Innovative CO₂ injection strategies are being carried out in ENOS Project (EU H2020 Programme, http://www.enos-project.eu). First results based on field tests conducted at Hontomín, and the advanced modelling developed so far will be analyzed and discussed in this article, as well as, the description of future works. The evolution of operating parameters such as flow rate, pressure and recovery term during the tests confirm the CO₂ migration through the fractures.

The production of butanol, acetone and ethanol by Clostridium acetobutylicum is a biphasic fer-mentation process. In the first phase the carbohydrate substrate is metabolized to acetic and bu-tyric acid, in the following second phase the product spectrum is shifted towards the economi-cally interesting solvents. Here we present a cascade of six continuous stirred tank reactors (CCSTR), which allows performing the time dependent metabolic phases of an ace-tone-butanol-ethanol (ABE) batch fermentation in a spatial domain. Experimental data of steady states under four operating conditions - with variations of the pH in the first bioreactor between 4.3 and 5.6 as well as the total dilution rate between 0.042 1/h and 0.092 1/h - were used to optimize and validate a corresponding mathematical model. Beyond a residence time distribution representation and substrate, biomass and product kinetics this model also includes the differen-tiation of cells between the metabolic states. Model simulations predict a final butanol product concentration of 8.2 g/L and a butanol productivity of 0.75 g/(L h) in the CCSTR operated at a pH in bioreactor 1 of 4.3 and D = 0.092 1/h, while 31 % of the cells are differentiated to the solventogenic state. Aiming at an enrichment of solvent-producing cells, a feedback loop was introduced into the cascade - sending cells from a later state of the process (bioreactor 4) back to an early stage of the process (bioreactor 2). In agreement with the experimental observations, the model accurately predicted an increase of butanol formation rate in bioreactor stages 2 and 3, resulting in an overall butanol productivity of 0.76 g/(L h) for the feedback loop cascade. The here presented CCSTR and the validated model will serve to investigate further ABE fermentation strategies for a controlled metabolic switch.

We herein provide an overview of the most recent multidisciplinary process advances that have occurred in the food industry as a result of changes in consumer lifestyle and expectations. The demand for fresher and more natural foods is driving the development of new technologies that may efficiently operate at room temperature. Moreover, the huge amount of material discarded by the agro-food production chain lays down a significant challenge for emerging technologies that can provide new opportunities by recovering valuable by-products and creating new applications. Aiming to design industrial processes, there is a need of pilot scale plants such as the “green technologies development platform” that was established by the authors. The platform is made up of a series of multifunctional laboratories that are equipped with non-conventional pilot reactors developed in direct collaboration with partner companies in order to bridge the enormous gap between academia and industry via the large-scale exploitation of relevant research achievements. Selected key, enabling technologies for process intensification make this scale-up feasible. We make use of two selected examples, the grape and olive production chains, to show how cavitational reactors, which are based on high-intensity ultrasound and rotational hydrodynamic units, can assist food processing and the sustainable recovery of waste to produce valuable nutraceuticals as well as colouring and food-beverage additives.

In the Global North, there is an increasing interest in pulses both for their beneficial effects in cropping systems and for human health. However, despite these advantages, the acreage dedi-cated to pulses has been declining and their diversity reduced, particularly in European temperate regions, due to several social and economic factors. This decline has stimulated a political debate in the EU on the development of plant proteins. By contrast, in the Global South, a large panel of minor pulses is still cropped in regional patterns of production and consumption. The aim of this paper is to investigate the for cultivation of potential minor pulses in European temperate regions as a complement to common pulses. Our assumption is that some of these crops could adapt to different pedo-climatic conditions, given their physiological adaptation capacity, and that these pulses might be of interest for the development of innovative local food chains in an EU policy context targeting protein autonomy. The research is based on a systematic review of 269 papers retrieved in the Scopus database (1974–2019), which allowed us to identify 41 pulses as candidate species with a protein content higher than 20% that are already consumed as food. For each spe-cies, the main agronomic (e.g. temperature or water requirements) and nutritional characteristics (e.g. proteins or antinutritional contents) were identified in their growing regions. Following their agronomic characteristics, the candidate crops were confronted with variability in the annual growing conditions for spring crops in European temperate areas to determine the earliest poten-tial sowing and latest harvest dates. Subsequently, the potential sum of temperatures was calcu-lated with the Agri4cast database to establish the potential climatic suitability. For the first time, 21 minor pulses were selected to be grown in these temperate areas and appear worthy of inves-tigation in terms of yield potential, nutritional characteristics or best management practices.

Campylobacter infection affects more than 200,000 people every year in Europe and in the last four years trend shows an increase of campylobacteriosis. Main vehicle for transmission of the bacterium is contaminated food like meat, milk, fruit and vegetables. In this study, the aim was to find characteristic VOCs of C. jejuni in order to detect its presence with an array of MOX gas sensors. Using a starting concentration of 10³ CFU/mL, VOCs were analyzed using GC-MS with SPME technique at the initial time (T0) and after 20 hours (T20). It has been found that Campylobacter sample at T20 is characterized by a higher number of alcohol compounds that the one at T0 and this is due to sugar fermentation. Sensors results showed the ability of the system to follow bacteria curve growth from T0 to T20 using PCA. In particular, this results in a decrease of ΔR/R₀ value over time. For this reason, MOX sensors are a promising technology for the development of a rapid and sensitive system for C. jejuni.

Internships can foster educational alliances between industry (business environment) and academic institutions, which can facilitate both flexibility and accelerated innovation. The purpose of this research is to search for the factors that determine HRD through the implementation of the Internship program among the students of Democritus University of Thrace and reveal the correlation between the factors. Also, this paper investigated the impact of the COVID-19 Eras on Human Resource Development (HRD) Factors and finally, investigated the correlation between the two variables "Recruitment in the specialization" and "Covid Eras". The sample of the research consisted of 1398 students of DUTh who implemented Internships during the academic years 2015-2016 to 2021-2022. A questionnaire with 60 variables was created for data collection. A random sampling method was applied to collect the sample. From the results of the survey, ten factors were extracted for human resource training that explained 75.512% of the total variance and for each one, Cronbach's Alpha reliability was tested, which was high. In detail, the factors revealed were Learning Outcomes, Efficacy, Emotional Commitment, Satisfaction, Participation, Empowerment, Role Ambiguity, Role Conflict, Supervisor and Collaboration. From the results of the study, it was evident that HR development - training is a multi-dimensional concept and is a necessary condition for the competitiveness of the firms. Training can help to improve the flexibility of the firm, but also to motivate the staff by implementing multidisciplinary training programs. In general, internship programs are valuable ways for students to acquire broad competences, where the practical knowledge gained supports and complements the theoretical studies acquired in educational institutions.

In general, during emergencies, healthcare is provided by tents and temporary structures that do not consider the environmental and social impact of the structure as a first term, in favor of swift response. The resultant construction intended as a temporary solution often persists long-term. This paper aims to analyze an alternative and innovative modular structure designed as a transitory solution in emergency and everyday life. In the first part of the paper, the conceptual framework, and the preliminary design for the new approach to basic non-conventional sanitary spaces are described, by investigating the benefits of a safe space as a generator space for care services and community. In the second part, the technological requirements of the system, its energy efficiency, and environmental impact are analyzed.

This manuscript presents a novel approach to estimating the potential within Schrödinger equations, with a particular focus on applications to the Navier-Stokes problem in fluid dynamics. By establishing new theoretical estimates, we delve into the intricate dynamics of fluid flow, aiming to unveil previously obscured aspects of the Navier-Stokes equations. Through a rigorous mathematical framework, we explore how these new potential estimates can provide a fresh perspective on fluid mechanics, contributing to the ongoing quest to solve some of its most persistent challenges.

Massification in higher education has made the satisfaction of students’ needs a difficult conundrum among university lecturers. In contrast, the use of innovative design for collaborative learning enhances student engagement in the populous student’s context. Moreover, this paper aims to extensively explore innovative designs for fostering student engagement and collaborative learning among first-year students at the University of Venda. The study employed a qualitative research method with the purposive sampling technique. Subsequently, a group of 200 students was the population of this study. Participant Observation and narrative inquiry were used as data collection instruments. The students in their respective groups were assigned topics from the module content to use their talents to demonstrate their understanding of certain content in the module. The non-surprising findings of this paper elucidated that collaborative learning expedites students’ mastery of key concepts and subject content. The module lecturers introduced students to these innovative designs to ensure collaborative learning and effective student engagement. The key findings elucidated these aspects namely, role-playing exercises, group projects, peer-to-peer learning, use of talents, and peer feedback. The implication of this study is that students learn to work together, delegate responsibilities and communicate effectively to attain a common goal. Using these strategies, the lecturers promote collaboration among students and foster a more engaging and interactive learning experience. This paper further recommends efficient and effective techniques and strategies to foster student engagement and collaboration to track and monitor at-risk students timeously.

Environmental concerns, among other causes, are leading to meat replacement in the diet by healthy, nutritious and tasty foods. Alternative protein sources of plant origin can be an alternative to meat, but their low biological value proteins can be a problem. Novel foods, such as insect meals, can meet currently consumer demands. Therefore, this research has developed innovative prototypes of analogue burgers with animal and vegetable proteins. Concerned about health and allergies, a prototype incorporating soya to satisfy coeliacs was developed. An iterative and heuristic process was carried out to test the product development feasibility. The main raw materials used were insect flour (Tenebrio molitor), seitan and soya. In addition, oat and sodium alginate were used as binders. Shelf-life of the new product was evaluated by physicochemical (pH, aw, moisture, colour, acidity and peroxide index) and sensory analysis (quantitative analysis -QDA-). The production of the burger analogues was feasible. Product characterisation showed significant differences (p < 0.05) among samples for organoleptic properties, highlighting texture changes. Using a multivariate model, it was established “The best before date” at 7 days for all developed prototypes, conditioned by microbial growth. Finally, the spoilage model indicated an important contribution to bacterial growth with a notable modification in the pastiness and hardness of the burger analogues developed.

Aphasia is one of the most socially disabling post-stroke deficits. Although traditional therapies have been shown to induce adequate clinical improvement, aphasic symptoms often persist. Therefore, new rehabilitation techniques which act as a substitute or as an adjunct to traditional approaches are urgently needed. The present review provides an overview of the efficacy and safety of the most innovative approaches which have been proposed over the last twenty years. First, we examined the effectiveness of the pharmacological approach, principally used as an adjunct to language therapy, reporting the mechanism of action of each single drug for the recovery of aphasia. Results are conflicting but promising. Secondly, we discussed the application of Virtual Reality (VR) which has been proved to be useful since it potentiates the ecological validity of the language therapy by using virtual contexts which simulate real-life everyday contexts. Finally, we focused on the use of Transcranial Direct Current Stimulation (tDCS), both discussing its applications at the cortical level and highlighting a new perspective, which considers the possibility to extend the use of tDCS over the motor regions. Although the review revels an extraordinary variability among the different studies, substantial agreement has been reached on some general principles, such as the necessity to consider tDCS only as an adjunct to traditional language therapy.

Nutrients management is a mainspring in agricultural systems for sustained productivity, economy sustainability and environmental quality. Excessive and lesser nutrient application caused environmental pollution and reduced production, respectively impacting socio-economics of the entire ecosystems. Sustainable agricultural production thus demands supplementation of nutrients either through natural processes, application of animal by-products, and mineral fertilizers to crop fields. Technology application for treating useless agricultural wastes into useful source is a management strategy that prevents environment pollution. Crude animal manures triggered soil degradation, attenuation air and water quality, and resulted in higher concentrations of heavy metals. Primary nutrients, i.e., nitrogen, phosphorus and potassium are used globally and are non-renewable. Augmented upsurge in prices of inorganic fertilizers and required discharge restrictions on nutrient has stimulated the technological developments including biochar, composting, vermicomposting, composting with biochar, pyrolysis, forward osmosis, and electro-dialysis to recover nutrients. Therefore, outlining the research gaps considering the present and imminent potential of these technologies for adaptation of nutrient recycling is of great importance. Thus, it’s need of an hour to fix our environment and for that scientists are trying to introduce and renovate the technologies which have immense potential to mitigate the negative effects of technology adversities on our environment.

Natural spa springs are diffused all over the world and their use in pools is known since ancient times. This review underlines the cultural and social spa context focusing on hygiene issues, public health guidelines and emerging concerns regarding water management in wellness or recreational settings. The question of the "untouchability" of therapeutic natural waters and their incompatibility with traditional disinfection processes is addressed considering the demand for effective treatments that would respect the natural properties. Available strategies and innovative treatments are reviewed, highlighting potentials and limits for a sustainable management. Alternative approaches comprise nanotechnologies, photocatalysis systems, advanced filtration. State of the art and promising perspectives are reported considering the chemical-physical component and the biological natural complexity of the spa water microbiota.

In the face of geopolitical threats in Artsakh, the preservation of Armenia's epigraphic heritage has become a mission of both historical and cultural urgency. This project delves deep into Armenian inscriptions, employing advanced digital tools and strategies like the Oxygen text editor and EpiDoc guidelines to efficiently catalogue, analyze, and present these historical treasures. Amidst the adversities posed by Azerbaijan's stance towards Armenian heritage in Artsakh, the digital documentation and preservation of these inscriptions have become a beacon of cultural resilience. The XML-based database ensures consistent data, promoting scholarly research and broadening accessibility. Integrating the Grabar Armenian dictionary addressed linguistic challenges, enhancing data accuracy. This initiative goes beyond merely preserving stone and text; it is a testament to the stories, hopes, and enduring spirit of the Armenian people in the face of external threats. Through a harmonious blend of technology and traditional knowledge, the project stands as a vanguard in the fight to ensure that Armenia's rich epigraphic legacy and the narratives they enshrine remain undiminished for future generations.

Abstract: (1) Background: Sentinel lymph node biopsy assumes importance in the search for metastases, especially in patients with malignant breast disease. Our study approaches the new techniques to prevent complications such as possible postoperative seroma formation, pain or hypoesthesia of the axillary cord and medial arm surface, as well as motor deficits in a preventive manner to avoid disabling outcomes and presents initial data from its experience with the sentinel lymph node biopsy technique. (2) Methods: There are mainly two radioactive tracer detection techniques and a new technique using a radiotracer called Sentimag-magtrace. The positive lymph node is located and removed to perform histologic analysis. In our study, we evaluate 100 patients who underwent breast cancer surgery (3) Results: our experience allowed us to calculate the identification rate with the different methods of sentinel lymph nodes by radioactive tracer 88.9 % vs magnetic tracer technology (Sentimag) 89.5%. (4) Conclusions: Thus, this technique avoids radiation exposure for both patients and health care providers, as well as reducing costs and time.

The consideration toward Waste Cooking Oils (WCOs) is changing from hazardous waste to valuable raw material for industrial application. During the last five years some innovative processes based on the employment of recycled WCO have appeared in the literature. In the present review article, the most recent applications of recycled Waste Cooking Oil are reported and discussed. These include the production of bio-plasticizers, the application of chemicals derived from WCOs as energy vectors, and the use of WCOs as solvent for pollutant agents.

Even if silicon alkoxides (especially ethylsilicates) have long been used as consolidants of weathered stone monuments, their physical properties are not ideal. In this study, an innovative procedure for the consolidation of sedimentary rocks was developed that combines the use of organometallic and alkylamine catalysts with the addition of well-defined nanoparticles exhibiting a narrow size distribution centered at ca 10 nm. As a suitable test material, the Pietra di Lecce limestone was selected because of its color and problematic physico-chemical properties, such as rather low hardness. Using the developed procedure, the mechanical and surface properties of the limestone were improved without the unwanted over-consolidation of the surface layers of the stone, and any significant deterioration in the pore size distribution, water vapor permeability or the stone’s appearance. The developed modified ethylsilicates penetrated deeper into the pore structure of the stone than the unmodified ones and increased the hardness of the treated material. The formed xerogels within the stone pores did not crack. Importantly, they did not significantly alter the natural characteristics of the stone.

Cross-laminated timber (CLT) possesses both good shape stability and the possible two-way force transfer ability due to its crosswise lamination. However, the transverse layers in CLT are prone to rolling shear failure under an out-of-plane load. An innovative multi-layer composite laminated panel (CLP) was developed by combining structural composite lumber (SCL) and dimension lumber to overcome the rolling shear failure while maintaining high mechanical performance and aesthetic appearance of natural wood. The mechanical properties of 5-layer CLP consisted of laminated strand lumber (LSL) and dimension lumber with different layups were evaluated by both static and modal tests. The results showed that the shear resistance, bending stiffness and moment resistance of CLP were up to 143%, 43% and 87% higher than their counterparts of regular CLT, respectively. The failure modes observed in both shear and bending tests indicated that the use of LSL in transverse layers could eliminate the potential rolling shear failure in CLT. With the lamination properties from components tests as inputs, the validity of shear analogy method was assessed by test results. The mechanical properties can be well predicted by shear analogy method except for the bending moment resistance of CLP and CLT with either rolling failure in the cross layer or tension failure in the bottom layer.

Citizen science has emerged as a potent approach for environmental monitoring, leveraging the collective efforts of volunteers to gather data at unprecedented scales. Within the framework of the I-CHANGE project, MeteoTracker, a citizen science initiative, was employed to collect and analyze meteorological measurements. This paper presents the results of our analysis, demonstrating the effectiveness of citizen science in generating valuable environmental data. Through MeteoTracker, volunteers contributed to a comprehensive dataset, enabling insights into local weather patterns and trends. Our findings underscore the potential of citizen science to augment traditional monitoring efforts and inform decision-making processes in environmental research and management. The paper discusses the methodology employed, including data collection and statistical analysis techniques. Results highlight the reliability and accuracy of citizen-generated data, as well as the strengths of the MeteoTracker platform. The implications of our findings for environmental research, policy development, and public engagement are discussed, along with recommendations for enhancing the effectiveness of citizen science initiatives in environmental monitoring.

The production of concrete and the manufacturing process of cement results in a significant carbon footprint, contributing to a large portion of global emissions in structures such as buildings, bridges, roads, and tunnels. Although concrete is an ideal building material that is durable and long-lasting, it can be susceptible to micro-cracks. These micro-cracks in concrete can allow water and chlorine ions to penetrate the structure, leading to the degradation of concrete and corrosion of the reinforcement, posing an unacceptable level of structural risk. Self-healing concrete is not a new material in the construction industry but can be characterized by the capability of concrete to repair its cracks autogenously or autonomously. Recent advancements in concrete research and technology have given us a better understanding of concrete's healing properties. Self-healing concrete combines durability with sustainability while offsetting the high carbon output of concrete manufacturing and production and associated life-cycle costs. Technologies such as microbially-induced calcite (calcium carbonate) precipitation (MICP), shape memory polymers, encapsulation methods, hydration, and swelling agents can potentially reduce carbon emissions while enhancing resilience and longevity. This paper examines these technologies and their applications in the construction industry by comprehensively reviewing the literature and available case studies. The study concluded that there are promising advancements and innovations in concrete, particularly when improving upon the autogenous healing properties. The recommendations for future research include exploring more ways to bring the concrete industry and cement manufacturing toward net zero carbon emissions.

Sustainable bio-economy is considered to be one of the most promising routes towards the transition to a circular and climate-neutral economy. The valorization industry of bio-waste and agri-food by-products represents a key player in bioeconomy. In this article the design and the development of a web platform aiming at promoting synergies enabling the agricultural waste valorization is presented. The platform consists of: (i) the AgriPLaCE Waste Management Database which provides the users with an extended list of potential utilization measures for a variety of agricultural waste streams (ii) the AgriPLaCE Synergies Tool which aims to create synergies between different actors involved in the value chain from agricultural waste production to waste treatment and new valuable products’ exploitation. At the initial stage, the conceptual design of both tools took place by conducting an in-depth analysis for the user needs and services alongside the system architecture. Following, the AgriPLaCE platform development stage took place, with the implementation of all the necessary subsystems. The results showed that multiple potential collaborations can arise by the use of the AgriPLaCE platform, while users can also deepen on alternative and emerging treatment technologies and valuable products that can derive from a wide range of agricultural waste streams.

Nuclear fusion reactors are composed by several complex components whose behaviour may be not certain a priori. This uncertainty may have a significant importance in the evolution of fault transients in the machine, causing unexpected damages to its components. For this reason a suitable method for the uncertainty propagation during those transient is required. The Monte Carlo method would be the reference option, but it is, in most of the cases, not applicable due to the large amount of required simulations to be repeated. In this context the Polynomial Chaos Expansion has been considered as a valuable alternative. It allows to create a surrogate model of the original one in terms of orthogonal polynomials. Then, the uncertainty quantification is performed repeatedly calling this much simpler and faster model. Using the fast current discharge in the Divertor Tokamak Test Toroidal Field (DTT TF) coils as a reference scenario, this method has been applied: the uncertainty on the parameters of the Fast Discharge Unit (FDU) varistor disks is propagated to the simulated electrical and electro-magnetic relevant effects. Eventually two worst case scenarios have been analyzed from the thermal-hydraulic point of view with the 4C code, simulating a fast current discharge as a consequence of a coil quench. Eventually it has been demonstrated that the uncertainty on the inputs (varistor parameters) strongly propagates obtaining a wide range of possible scenarios in case of accidental transients. This result underlines the necessity to take into account and propagate all possible uncertainties in the design of a fusion reactor, according to the Best Estimate Plus Uncertainty approach.

There are currently around 78 Nuclear Power Plants (NPP) in the world based on Boiling Water Reactors (BWR). The current parameter to assess BWR instability issues is the linear Decay Ratio (DR). However, it is well known that BWRs are complex non-linear dynamical systems that may even exhibit chaotic dynamics that normally preclude the use of the DR when the BWR is working at a specific operating point during instability. In this work a novel methodology based on an adaptive Shannon Entropy estimator and on Noise Assisted Empirical Mode Decomposition variants is presented. This methodology was developed for real-time implementation of a stability monitor. This methodology was applied to a set of signals stemming from several NPPs reactors (Ringhals-Sweden, Forsmark-Sweden and Laguna Verde-Mexico) under commercial operating conditions, that experienced instabilities events, each one of a different nature

Efficient triaging and referral assessment are critical in ensuring prompt medical intervention in the Community Health Care (CHC) system. However, the existing triaging systems in many Community Health Services are an intensive, time-consuming process and often lack accuracy, particularly for various symptoms that might represent heart failure or other health-threatening conditions. There is a noticeable limit of research papers describing AI technologies for triaging patients. This paper proposes a novel quantitative data-driven approach using machine learning (ML) modelling to improve the community clinical triaging process. Furthermore, this study aims to employ the feature selection process and machine learning power to reduce the triaging process’s waiting time and increase accuracy in clinical decision-making. The model was trained on medical records of “Heart Failure” patients’ dataset, which included demographics, past medical history, vital signs, medications, and clinical symptoms. A comparative study was conducted using the list of machine learning algorithms where XGBoost demonstrated the best performance among other ML models. The triage levels of 2,35,982 patients achieved an accuracy of 99.94%, precision of 0.9986, recall of 0.9958, and f1-score of 0.9972 within 0.059 seconds. The proposed diagnostic model can be implemented for the CHC decision system and be developed further for other medical conditions.

This research delves into the integration of green roofs with Building Information Modeling (BIM), a pivotal advancement in sustainable urban construction. Aligning with the United Nations Sustainable Development Goals, particularly Goal 11, the study explores how this integration can address global challenges like climate change and resource depletion. Using the Dynamo Visual Programming Language within Autodesk Revit, the research develops a computational modeling approach for green roofs, focusing on their thermal and structural characteristics under varied environmental conditions. Key findings demonstrate the significant influence of substrate and drainage material combinations on green roofs’ thermal performance, highlighting the need for tailored designs based on climatic conditions. The study also emphasizes the importance of considering structural performance in both dry and saturated conditions for overall building integrity. The research identifies gaps in current practices, such as limited focus on specific green roof materials and reliance on certain software tools, suggesting the need for broader material selection and software adaptability. Future research directions include expanding material selections, exploring diverse environmental conditions, and integrating green roofs with various BIM software platforms. The study's implications extend to stakeholders in the construction industry, offering a framework for architects, urban planners, and policymakers to design and implement green roofs aligned with environmental goals. This work contributes to the field by proposing a novel approach to sustainable construction, integrating ecological design with digital technology, and setting a new benchmark in the integration of green roofs with BIM. By addressing these aspects, the research paves the way for future developments in sustainable urban construction, enhancing the efficiency, sustainability, and resilience of urban communities in line with global sustainability objectives.

The aim of this study is to introduce and evaluate a new approach by using 3D printed anthropomorphic breast phantoms in teaching X-ray mammography techniques Radiologic technologists. For this purpose, a physical anthropomorphic breast phantom is created, based on a computational breast version. The phantom is created by a stereolithography 3D printer. The practical exercises were conducted in three sessions with the participation of radiographers students first, second and third year of training, respectively. A survey was prepared to summarise the participants´ opinion about this new form of training in mammography technique. A total of 83 students were trained with the new approach. From these 52 responded to the survey questions. More than half of the students (71.2%) successfully handled the exercise with the physical breast phantom. The training provoked a substantial number of students to express the belief that incorporating modern methods based on digital technologies into their X-ray device training is essential. The instructor was well prepared and with the needed competence. The experience within this training convinces the future professionals to introduce the new technologies in their routine work, particularly for exercising the compression technique and breast positioning.

Research and development on innovative packaging materials have advanced significantly to safeguard packaged food against microbial contamination and oxidation. To combat demanding issues, active packaging has evolved as a viable method for minimizing oxidation/microbial growth in packaged goods, extending their shelf life, and ensuring the consumer's safety. Active food packaging includes O2, CO2 scavengers, moisture absorbers, U.V. barriers, and carriers of antioxidant and antimicrobial agents. Various antimicrobial agents are carried and/or incorporated into food packaging formulations. Consumers demand natural antimicrobials over chemical/synthetic ones, such as bacteriocins, bacteriophages, and essential oils. Bacteriophages (viruses) have emerged as a feasible option for decontaminating and eliminating infections from food sources. These viruses can target specific food-borne pathogens without impairing beneficial bacteria and, most critically, without causing disease in humans or animals. Fortifying bacteriophages into food packaging films will not only kill specific food microorganisms but has evolved as a new weapon to combat antimicrobial-resistant (AMR) issues. The present review summarises recent developments in active antimicrobial packaging focused particularly on bacteriophage-food packaging applications and advantages, drawbacks, and future trends for active food packaging.

This paper describes a novel methodology of data management in materials characterisation, which has as starting point the creation and usage of Data Management Plan (DMP) for scientific data in the field of materials science and engineering, followed by the development and exploitation of ontologies for the harnessing of data created through experimental techniques. The case study that is discussed here is nanoindentation, a widely used method for the determination and/or modelling of mechanical properties on a small scale.The same methodology can be applicable to a large number of techniques that produce big amount of raw data, while at the same time it can be invaluable tool for big data analysis and for the creation of an open innovation environment, where data can be accessed freely and efficiently.Aspects covered include the taxonomy and curation of data, the creation of ontology and classification about characterization techniques, the harnessing of data in open innovation environments via database construction along with the retrieval of information via algorithms. The issues of harmonization and standardization of such novel approaches are also critically discussed.Finally, the possible implications for nanomaterial design and the potential industrial impact of the new approach are described and a critical outlook is given.

We tested the use of mosquito traps as an alternative to insecticide spraying in Camargue (France) following the significant impacts observed on the non-target fauna through Bti persistence and trophic perturbations. In a village of 600 inhabitants, 16 Techno-Bam traps emitting CO₂ and using octenol lures were set from April to November 2016. Trap performance was estimated at 70% overall based on mosquito landing on human baits in areas with and without traps. Reduction of Ochlerotatus caspius and Oc. detritus, the two species targeted by Bti spraying, was respectively 74 and 98%. Traps were less efficient against Anopheles hyrcanus (46%), which was more attracted by lactic-acid than octenol lures based on previous tests. Nearly 300 000 mosquitoes from nine species were captured, with large variations among traps, emphasizing that trap performance is also influenced by surrounding factors. Environmental impact, based on the proportion of non-target insects captured, was mostly limited to small chironomids attracted by street lights. Breeding success of a house martin colony was not significantly affected by trap use, in contrast to Bti spraying. Our experiment confirms that deployment of mosquito traps can offer a cost-effective alternative to Bti spraying for protecting local populations from mosquito nuisance in sensitive natural areas.

Despite advances in our understanding of molecular aspects of oncogenesis, cancer remains a leading cause of death. The malignant behavior of a cancer cell is driven by the inappropriate activation of transcription factors. In particular, signal transducers and activators of transcription (STATs), which regulate many critical cellular processes such as proliferation, apoptosis, and differentiation, are frequently activated inappropriately in a wide spectrum of human cancers. Multiple signaling pathways converge on the STATs, highlighting their importance in the development and progression of oncogenic diseases. STAT3 and STAT5 are two members of the STAT protein family that are the most frequently activated in cancers and can drive cancer pathogenesis directly. The development of inhibitors targeting STAT3 and STAT5 has been the subject of intense investigations in the last decade, although effective treatment options remain limited. In this review, we investigate the specific roles of STAT3 and STAT5 in normal physiology and cancer biology, discuss the opportunities and challenges in pharmacologically targeting STAT proteins and their upstream activators, and offer insights into novel therapeutic strategies to identify STAT inhibitors as cancer therapeutics.

At INFN-LNS, and in collaboration with the ATOMKI laboratories, an innovative multi-diagnostic system with advanced analytical methods has been designed and implemented. This is based on several detectors and techniques (Optical Emission Spectroscopy, RF systems, Interfero-polarimetry, X-ray detectors) and here we focus on high resolution spatially-resolved X-ray spectroscopy, performed by means of a X-ray pin-hole camera setup operating in the 0.5−20 keV energy domain. The diagnostic system was installed at a 14 GHz Electron Cyclotron Resonance (ECR) ion source (ATOMKI, Debrecen), enabling high precision X-ray spectrally-resolved imaging of ECR plasmas heated by hundreds of Watts. The achieved spatial and energy resolution were 0.5 mm and 300 eV at 8 keV, respectively. We here present the innovative analysis algorithm that we properly developed for obtaining Single Photon-Counted (SPhC) images providing the local plasma emitted spectrum in a High-Dynamic-Range (HDR) mode, by distinguishing fluorescence lines of the materials of the plasma chamber (Ti, Ta) from plasma (Ar). This method allows a quantitative characterization of warm electrons population in the plasma (and its 2D distribution) which are the most important for ionization, and also to estimate local plasma density and spectral temperatures. The developed post-processing analysis is also able to remove the readout noise, that is often observable at very low exposure times (msec). The setup is now under update including fast shutters and trigger systems in order to allow simultaneously space and time-resolved plasma spectroscopy during transients, stable and turbulent regimes.

Habitual entrepreneurs became an important group of entrepreneurs who make a large contribution to the process of wealth creation. Previous studies have indicated that habitual entrepreneurship is a widespread phenomenon. It highlights the need to focus on the habitual entrepreneurs to understand the dynamic aspect of entrepreneurship. The aim of the article is to present the results of preliminary research on the relationships of entrepreneurial behavior of novice entrepreneurs and habitual entrepreneurs, in particular their motivation and impact on the entrepreneurial process. Research were conducted on a sample of 373 small innovative enterprises in the fourth quarter of 2017. The scale of habitual entrepreneurs in the examined sample is 32.44% and is comparable with research carried out in other countries. Survey results reveal that habitual entrepreneurs have greater tendency to create opportunities (introduction new products or services) than novice entrepreneurs. Habitual entrepreneurs also have higher development rate (increase of turnover) and larger share in the international market than novice entrepreneurs. The article also contains indications for further research into the phenomenon of multiple entrepreneurship.

The objective of the present contribution was to design and characterize resveratrol (RSV) and tocopherol (TOC) loaded 11S quinoa seed protein nanocomplexes. Firstly, molecular docking was performed to describe the probable binding sites between protein and ligands. Isothermal titration calorimetry allowed to obtain the thermodynamic parameters that described the molecular interactions between RSV or TOC with the protein. 11S globulin intrinsic fluorescence spectra showed a quenching effect exerted by RSV and TOC, demonstrating protein-bioactive compounds interactions. Stern-Volmer, Scatchard and Förster resonance energy transfer models application confirmed static quenching and allowed to obtain parameters that described the 11S-RSV or 11S-TOC complexation process. Secondly, protein aggregation induced by bioactive compounds interactions was confirmed by dynamic light scattering and atomic force microscopy with diameters <150 nm, detected by both techniques. Finally, it was found that antioxidant capacity of single 11S globulin did not decrease, meanwhile was additive for 11S-RSV. These nanocomplexes could constitute a real platform for the design of nutraceutical products.

This paper investigates the possible failure modes of the product development process in production companies that are active in the B2C markets with a focus on household products. Since these cases require short lead times and are difficult to differentiate, in many instances the end result will not be the desired one and could affect profitability for a season or for good. A model of these possibilities is created and an approach to plan contingencies for their solutioning is proposed in the article. The main guideline is to switch from failure probability determination to accepting failure as inevitable and using digital solutions to reinforce the development process in order to offset its impact. For this goal, an Industry 5.0 Abatement Factor (abbreviated IFAF) is introduced in the contingency planning approach, that factors in the evaluation the low cost of digital instruments and the proper mix of Technology, Humans and AI (abbreviated THAI). The new working procedure based on these concepts and their interlinkages is discussed based on specific examples.