Metabolites present in the hemolymph of honey bees play a crucial role in modulating the metamorphic process within the species. However, the precise alterations in metabolite composition, along with the associated variances and regulatory pathways implicated during the larvae-to-pupae metamorphosis of honey bees, remain incompletely elucidated. In this investigation, we gathered hemolymph samples from honey bee larvae at three distinct physiological stages-feeding, prepupal, and pupae and subjected them to metabolite analysis utilizing the liquid chromatography-mass spectrometry (LC-MS) technique. Employing principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA), we identified significant differential metabolites and conducted a metabolic pathway analysis on those differentially up-regulated during the prepupal and pupae stages. Notably, metabolites up-regulated in the hemolymph of prepupal stage larvae primarily governed glucose metabolism and fat digestion and absorption, while those in pupae stage larvae were involved in regulating chitin and lipopolysaccharide precursor formation, as well as the biosynthesis of phenylalanine, tyrosine, and tryptophan. These findings bear significant implications for advancing our comprehension of the metamorphic processes in honey bees.

Abrasive Water Jet Machining (AWJM) is a non-conventional machining process that, unlike other methods, is deemed superior because of its applicability, versatility, and no heat-affected zones in the target material. The main objective of this paper was to develop a cheap, practical model for a low-pressure water jet cutting machine and provide some empirical test data for cutting delicate materials. Proper design calculations were performed and are included for both the water jet machine and the two-axis numerical control. Finite Element Analysis results validate the structural integrity of beams and columns in AWJM. Computational Fluid Dynamic analysis of the nozzle shows good agreement with the theoretical calculations regarding the pressure and velocity of the water-abrasive mixture exiting the nozzle. Modal analysis in ANSYS was done to mitigate potential failure due to resonance induced by vibrations. Limited testing on various thicknesses of polystyrene foam ranging from 1-5 mm thickness and rubber sheet of 1 mm thickness showed that even low pressure of 25-30 bar was sufficient to produce a kerf without any burr. However, extensive testing to report optimized parameters like nozzle transverse speed, standoff distance, abrasive flow rate, etc for working at low-pressure ranges is still a consideration for future investigation.

Postprandial glucose levels between 4 and 7.9 hours (PPG4–7.9h) correlate with mortality from various diseases including hypertension, diabetes, cardiovascular disease, and cancer. This study aimed to assess if predicted PPG4–7.9h could diagnose diabetes. Two groups of participants were involved: Group 1 (4420 participants) had actual PPG4–7.9h, while Group 2 (8422 participants) lacked this measure but had all the diabetes diagnostic measures. Group 1 underwent multiple linear regression to predict PPG4–7.9h using 30 predictors, achieving accuracy within 11.1 mg/dL in 80% of the participants. Group 2 had PPG4–7.9h predicted using this model. Receiver operating characteristic curve analysis showed that predicted PPG4–7.9h could diagnose diabetes with an accuracy of 87.3% in Group 2, with a sensitivity of 75.1% and specificity of 84.1% at the optimal cutoff of 102.5 mg/dL. Simulation on 10,000 random samples from Group 2 revealed that 175 participants may be needed to investigate PPG4–7.9h as a diabetes diagnostic marker with a power of at least 80%. In conclusion, predicted PPG4–7.9h appears to be a promising diagnostic indicator for diabetes. Future studies seeking to ascertain its definitive diagnostic value might require a minimum sample size of 175 participants.

Turbulent dissipation is a central issue in the star and galaxy formation process. Its fundamental property of space-time intermittency, well characterised in incompressible laboratory experiments, remains elusive in cosmic turbulence. Progress requires the combination of state-of-the-art modelling, numerical simulations and observations. The power of such a combination is illustrated here where the statistical method intended to locate extrema of velocity shears in a turbulent field is applied to numerical simulations of compressible magneto-hydrodynamical (MHD) turbulence dedicated to dissipation scales and to a nearby turbulent diffuse molecular cloud. We demonstrate that short-spacing increments of observables can detect strongly dissipative structures. In our simulations, we compute structure functions of various synthetic observables and show that they verify Extended Self-Similarity. This allows to compute their intermittency exponents and we show how they could help constraining some properties of the underlying three-dimensional turbulence. In observations of a turbulent cloud close to the Sun in our Galaxy, a remarkable coherent structure of velocity shear extremum is disclosed . At the location of the largest velocity shear, this coherent structure is found to foster 10 × more carbon monoxide molecules than standard diffuse molecular gas, an enrichment supported by models of non-equilibrium warm chemistry triggered by turbulent dissipation. The power of the combination between modelling and observations is also illustrated by observations of the CH+ cation that provide unique quantitative informations on the kinetic energy trail in the massive, multi-phase and turbulent circum-galactic medium of a galaxy group at redshift z = 2.8.

In this paper is presented the design and syntheis of a dynamic output feedback neural network controller for a non-holonomic mobile robot. First the dynamic model of a non-holonomic mobile robot is presented, in which these constraints are considered for the mathematical derivation of a feasable representation for this kind of robot. Then two control strategies are provided based on kinematic control for this kind of robot. The first control strategy is based on driftless control, this means, that considering that the velocity vector of the mobile robot is orthogonal to its restriction a dynamic output feedback and neural network controller is designed in order that the control action would be zero only when the velocity of the mobile robot is zero. The Lyapunov stability theorem is implemented in order to find a suitable control law. Then another control strategy is designed for trajectory tracking purposes, which similar to the driftless controller, a kinematic control scheme is provided but suitable to implement in more sophisticated hardware. In both control strategy a dynamic control law is provided along with a feedforward neural network controller, so in this way, by the Lyapunov theory the stability and convergence to the origin of the mobile robot position coordinates is ensured. Finally, two numerical experiment are presented in order to validate the theoretical results synthetized in this research study. Discussions and conclusions are provided in order to analyze the results found in this research study.

Non-vertebrate species represent about ~95% of known metazoan (animal) diversity. They remain to this day relatively unexplored genetically, but understanding their genome structure and function is pivotal for expanding our current knowledge of evolution, ecology and biodiversity. Following the continuous improvements and decreasing costs of sequencing technologies, many genome assembly tools have been released, leading to a significant amount of genome projects being completed in recent years. In this review, we examine the current state of genome projects of non-vertebrate animal species. We present an overview of available sequencing technologies, assembly approaches, as well as pre and post-processing steps, genome assembly evaluation methods, and their application to non-vertebrate animal genomes.

The quality and shelf-life of NCS (Non-centrifugal sugar) mainly depend on the moisture content present in it. NCS formed by the current practice of open sun drying contains moisture substantially greater than the acceptable level of 3%. This paper presents the work taken up to design a tunnel dryer to attain require moisture content in granular NCS for various load conditions. Initially, an experimental investigation had been carried out on a laboratory scale dryer to achieve required moisture content (< 3%) for various load conditions. This experimental data was used for validating two drying models and found that one of the models is best suitable for designing an industrial-scale dryer. For various load conditions on each tray and dryer exit temperature, nine different cases were arrived at. The number of trucks, trays, drying time and energy requirements were computed using the suitable theoretical model. Tunnel dryer with a length of 18 m, a height of 1.2 m, a width of 1 m, number of trucks of 18 and 24 number of trays on each truck was found to be the suitable dryer to dry 1 tone of NCS based on the minimum energy requirement of 176.49 MJ, and a minimum drying time of 68 minutes.

Untranslated regions (UTRs) of flaviviruses contain a large number of RNA structural elements involved in mediating the viral life cycle, including cyclisation, replication, and encapsidation. Here we report on a comparative genomics approach to characterize evolutionarily conserved RNAs in the 3'UTR of tick-borne, insect-specific and no-known-vector flaviviruses in silico. Our data support the wide distribution of previously experimentally characterized exoribonuclease resistant RNAs xrRNAs within tick-borne and no-known-vector flaviviruses and provide evidence for the existence of a cascade of duplicated RNA structures within insect-specific flaviviruses. On a broader scale, our findings indicate that viral 3'UTRs represent a flexible scaffold for evolution to come up with novel xrRNAs

The aim of the study was to identify factors associated with non-adherence to tuberculosis (TB) preventive treatment among contacts with latent TB infection of new cases of pulmonary TB cases reported in Catalonia in 2019-2021. All contacts aged 18 years or older with a latent TB infection who received a TB preventive treatment were included in the study. The Chi square test and the odds ratios (OR) were used to assess the association between non-adherence to TB preventive treatment and the study variables, considering a p < 0.05 as statistically significant. Multiple logistic regression analysis was used to detect the in-dependent factors associated with TB preventive treatment non-adherence, considering a p < 0.05 as statistically significant. The percentage of non-adherence to TB preventive treatment found in this study was 23.7%. A multivariable logistic regression analysis determined that the following factors were significantly associated with TB preventive treatment non-adherence among adult contacts: “exposure at school or workplace” (aOR = 3.34), “exposure to an index case without laboratory confirmation of TB” (aOR = 2.07), “immigrant contact” (aOR = 1.81), “male gender” (aOR = 1.75) and “exposure duration <6 hours per week or sporadic exposure” (aOR = 1.60). By contrast, the factor “short-term TB preventive treatment regimen” (aOR = 0.38) was significantly associated with a lower treatment non-adherence. Adherence to TB preventive treatment should be improved among adult contacts of TB pulmonary cases with latent TB infection by recommending short-term treatment regimens and by developing health education activities, with a greater focus on contacts with factors associated with treatment non-adherence.

Non-alcoholic beer (NAB) or low alcoholic beer (LAB) are taking over the market with a growing sale. Sus-tainable recycling and valorization of exhausted brewer’s spent grains (BSG) coming from craft beer is a relevant issue in brewing process. In this work, recycled BSG and BSG+GJ (supplemented with 10% grape juice) were used as wort-substrate to inoculate already selected non-conventional yeasts to produce NABLAB craft beer. Results showed that wort composed by only recycled BSG produced appreciate NAB beers (ethanol from 0.12% to 0.54 % v/v) while the addition of 10% of grape juice made LAB beers (ethanol from 0.82 to 1.66 % v/v). As expected, volatile compounds production was highest with the addition of grape juice. Lachancea thermotolerans confirmed the lactic acid production and, as Saccharomyces cerevisiae, is characterized by (in both worts) ethyl butyrate and isoamyl acetate, while Torulaspora delbrueckii produced relevant amounts of exanol, phenylethyl acetate and β-phenyl ethanol (wort added with grape juice). Wickeramhomyces anomalus and Pichia kluyvery showed consistent volatile production but only in wort with grape juice addition where a fermentation activity was exhibited. The overall results indicated that reused BSGs, non-conventional yeasts and grape juice is a suitable strategy for specialty NABLAB beer.

With increased vulnerabilities and vast technology landscapes, it is extremely critical to build systems which are highly resistant to cyber-attacks, to break into systems to exploit. It is almost impossible to build 100% secure authentication & authorization mechanisms merely through standard password / PIN (With all combinations of special characters, numbers & upper/lower case alphabets and by using any of the Graphical password mechanisms). The immense computing capacity and several hacking methods used, make almost every authentication method susceptible to cyber-attacks in one or the other way. Only proven / known system which is not vulnerable in spite of highly sophisticated computing power is, human brain. In this paper, we present a new method of authentication using a combination of computer’s computing ability in combination with human intelligence. In fact this human intelligence is personalized making the overall security method more secure. Text based passwords are easy to be cracked ^[6]. There is an increased need for an alternate and more complex authentication and authorization methods. Some of the Methods ^{[7] [8]} in the category of Graphical passwords could be susceptible, when Shoulder surfing/cameras/spy devices are used.

Previous studies demonstrate the critical importance of non-coding RNAs interfacing with chromatin-modifying machinery resulting in promoter-enhancer-based gene regulation and raise the possibility that many other enhancer-like RNAs may operate via similar mechanisms. Critically, more than 80% of the disease-linked variations identified in genome-wide studies are located in the non-coding regions of genomes, especially non-coding RNA, suggesting non-coding RNAs are relevant to disease. Thus, a critical path forward for understanding non-coding RNAs' role, especially long non-coding RNAs, is to understand the genomic regions' transcriptional regulation, especially non-coding regions. Here, we developed a user-friendly R package called SomaGene for studying and identifying enhancer-like non-coding RNAs with enriched somatic mutations in the cancer genome. SomaGene accepts different genomic variants (whole genome/exome somatic point mutations, structural variations, copy number variations) to identify those RNAs that significantly mutated in diseases (e.g., cancer). It then uses multiple publicly available genomics and epigenetics datasets including ENCODE epigenomics annotations, FANTOM5 tissue-specific expression profiles, disease-associated genome-wide association SNPs, and tissue-specific eQTL pairs to identify those RNAs with potentially enhancer function. SomaGene, as a powerful R package, can provide the opportunity to cancer scientists to study the roles of non-coding RNAs in different cancer genomes.

In this article, the usual factorials and binomial coefficients have been generalized and extended to the negative integers. Basing on this generalization and extension, a new kind of polynomials has been proposed, which led directly to the non-classical hypergeometric orthogonal polynomials and the non-classical second-order hypergeometric linear DEs. The resulting polynomials can be used in non-relativistic and relativistic QM, particularly, in the case of the Schrödinger equation, and Dirac equations for an electron in a Coulomb potential field.

Numerical models widely used for hydrocarbon phase behavior and compositional flow simulations are based on assumption of thermodynamic equilibrium. However, it is not uncommon for oil and gas-condensate reservoirs to exhibit essentially non-equilibrium phase behavior, e.g., in the processes of secondary recovery after pressure depletion below saturation pressure, or during gas injection, or for condensate evaporation at low pressures. In many cases the ability to match field data with equilibrium model depends on simulation scale. The only method to account for non-equilibrium phase behavior adopted by the majority of flow simulators is the option of limited rate of gas dissolution (condensate evaporation) in black oil models. For compositional simulations no practical yet thermodynamically consistent method has been presented so far except for some upscaling techniques in gas injection problems. Previously reported academic non-equilibrium formulations have a common drawback of doubling the number of flow equations and unknowns compared to the equilibrium formulation. In the paper a unified thermodynamically-consistent formulation for compositional flow simulations with non-equilibrium phase behavior model is presented. Same formulation and a special scale-up technique can be used for upscaling of an equilibrium or non-equilibrium model to a coarse-scale non-equilibrium model. A number of test cases for real oil and gas-condensate mixtures are given. Model implementation specifics in a flow simulator are discussed and illustrated with test simulations. A non-equilibrium constant volume depletion algorithm is presented to simulate condensate recovery at low pressures in gas-condensate reservoirs. Results of satisfactory model matching to field data are reported and discussed.

Background/Objectives: Systematic quality review of ultrasound exams is recommended to assure accurate diagnosis. Our primary objectives were to develop a quantitative method for quality review of estimated fetal weight (EFW) and to assess accuracy of EFW for an entire practice and for individual personnel. A secondary objective was to evaluate accuracy of fetal sex determination. Methods: This is a retrospective cohort study. Eligible ultrasound exams included singleton pregnancies with live birth and known birth weight (BW). A published method was used to predict BW from EFW for exams with ultrasound-to-delivery intervals up to 12 weeks. Mean error and median absolute error (AE) were compared between different personnel. Image audits were performed for exams with AE&gt;30% and exams with reported fetal sex different than newborn sex. Results: We analyzed 1,938 exams from 890 patients. In the last exam before birth, median AE was 5.9% and predicted BW was within ±20% of actual BW in 97.2% of patients. AE was &gt;30% in 28 exams (1.4%); image audit found correct caliper placement in all 28. Only 2 patients (0.2%) had AE&gt;30% on the last exam before birth. One sonographer systematically over-measured head and abdominal circumferences, leading to EFWs that were overestimated. Reported fetal sex differed from newborn sex in 7 exams (0.4%), 5 patients (0.6%). Images in 4 of these patients were annotated with correct fetal sex but a clerical error was made in the report. In 1 patient, the unclear image was labeled “probably female” but the newborn was male. Conclusions: Accuracy of EFW in this practice was similar to literature reports. Quantitative analysis identified a sonographer with outlier measurements. Time-consuming image audits could be focused on a small number of exams with large errors. We suggest some enhancements to ultrasound reporting software that may help to reduce clerical errors. We provide tools to help other practices perform similar quality reviews.

Welding spot defect detection using deep learning methods provides an effective way of body-in-white quality monitoring. Based on the existing Faster R-CNN model, this paper proposed an improved faster R-CNN model for resistance welding spot surface defect inspection to improve inspection efficiency and accuracy. The model contains the following improvements. Firstly, the improved algorithm uses anchor box with higher confidence output by the RPN network to locate welding spots. When a defect is detected and the detection system is in a suspended state, the Fast R-CNN network is used to confirm the defect category and details. Secondly, a new pruning model is proposed to replace the entire backbone neural network, which unnecessary convolutional layers and connection layers are deleted, and some parameters of each hidden layer are further reduced. On the premise of ensuring detection accuracy, the parameter quantity is extremely reduced, and the speed is improved. Experiments show that the model proposed in this paper took about 15ms for one single image test, and both the detection accuracy and recall rate reached over 90% according to the test on our dataset. This deep learning model meets the requirements of welding spot defect detection.

In recent years, digital transformation has become a pivotal factor for Small and Medium-sized Enterprises (SMEs), empowering them to adopt emerging technologies for competitive advantage. This systematic literature review examines 60 research papers published between 2014 and 2024, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework to explore the impact of digital technologies such as artificial intelligence, cloud computing, blockchain, and the Internet of Things (IoT) on SME performance. The review focuses on key drivers and barriers, including operational efficiency, customer engagement, and market expansion. Methodologies employed in the analyzed studies include quantitative approaches (60%), such as surveys and structural equation modelling, qualitative methods (25%), including interviews and case studies, and mixed methods approaches (15%) that combine both. A geographic distribution analysis highlights contributions from various countries, revealing regional research gaps. The results show that digital technologies have significantly improved SME operations, but challenges like limited resources and strategic focus persist. Additionally, the dominance of quantitative methods indicates a potential bias, suggesting the need for more diverse methodological approaches to fully understand the transformative potential of digital technologies for SMEs.

Hyperspectral small target detection (HSTD) is a promising pixel-level detection task. However, due to the low contrast and imbalance number between the target and background spatially and high dimensions spectrally, it is a challenging one. To address these issues, this work proposes a representation learning-based graph and generative network for hyperspectral small target detection. The model builds a fusion network through frequency representation for HSTD, where the novel architecture incorporates irregular topological data and the spatial-spectral feature to improve its representation ability. Firstly, a graph convolutional network (GCN) module better models the non-local topological relationship between samples to represent the hyperspectral scene’s underlying data structure. The mini-batch-training pattern of the GCN decreases the high computational cost of building an adjacency matrix for high-dimensional data sets. In parallel, the generative model enhances the differentiation reconstruction and the deep feature representation ability with respect to the target spectral signature. Finally, a fusion module compensates for the extracted different types of HS features and integrates their complementary merits for hyperspectral data interpretation while increasing detection and background suppression capabilities. Experiments on different hyperspectral data sets demonstrate the advantages of the proposed architecture.

Current trends in systemic risk literature provide new insights into multi-hazard risks that interact and compound with built environments, creating more significant impacts on socio-economic and human systems. Recurrent natural hazards and extreme weather events are more likely to compound and cascade into more impactful events, especially in vulnerable societies. In small-island communities (SICS), including large archipelagos and Small Island Developing States (SIDS), the long-term impact of multi-, compounding-, and cascading-hazards (MCC hazards) can result in persistent vulnerability and residual risks. This is due to delayed responses, limited resources, poverty, fewer evacuation options, and inadequate markets and infrastructure. Using Ternate, a densely populated small volcanic island in North Maluku, Indonesia, as a case study, this paper assesses the impacts of seven types of natural hazards: flash floods, landslides, extreme weather, extreme waves and abrasion, earthquakes, tsunamis, and volcanic eruptions. The research focuses on the multi-hazard impact on population, land use, and infrastructure exposures in 60 villages in Ternate. The findings highlight population density, land use, and infrastructure exposure to multi-hazard risks, providing valuable information on potential losses in future hazard events.

The impact of propeller effects and power contribution on the aerodynamics of small aircraft is indispensable. The aerodynamic analysis of wings in flight varies from rigid wing analysis due to wing deflection caused by transferred aerodynamic loads. This paper investigates the intertwined influence of propeller effects and elasticity on the aerodynamics of small propeller-driven aircraft. Through a detailed methodology, a twin-engine propeller-driven aircraft is analyzed as a case study, providing insights into the proposed approach. Two critical analyses are presented: an examination of propeller effects in rigid aircraft and the incorporation of elastic wing properties. The former establishes a foundational understanding of aerodynamic behaviour, while the latter explores the impact of wing elasticity on performance. Validation is achieved through comparative analysis with wind tunnel test results from a similar rigid structure aircraft. Utilizing NASTRAN software, aerodynamic analysis of the elastic aircraft is conducted, complemented by semi-empirical insights. The results highlight the importance of these factors across different angles of attack. Furthermore, deviations from the rigid aircraft configuration emphasize the considerable influence of static aeroelasticity analysis, notably increasing longitudinal characteristics by approximately 20%, while showing a lower impact of 5% in lateral-directional characteristics. This study contributes to enhanced design and operational considerations for small propeller-driven aircraft, with implications for future research and innovation, particularly for the purpose of efficient concepts in advanced air mobility.

Pinus squamata is one of the most threatened conifer endemic to northeastern Yunnan Province, China, and it is prioritized as one of the Plant Species with Extremely Small Populations (PSESP) for urgent protection in China. However, we lack a comprehensive consideration of the protection effect and the endangered mechanism, especially based on the underground growth status of endangered plants. The integrated study of soil properties and rhizosphere bacteria can assist conservation to understand therequired conditions for the protection and survival of rare and endangered species. In our study, bacterial communities in wild, ex-situ, and reintroduced P. squamata rhizosphere were compared using Illumina sequencing of the V3-V4 region of the 16S rRNA genes. We determined the soil physicochemical properties, analyzed the relationships between the bacterial communities and soil physicochemical factors, and predicted the potential bacterial ecological functions. The reintroduced site Qiaojia (RQ) had the highest richness and diversity. Samples were scattered (R = 0.93, P = 0.001), indicating significant difference between the different conservation sites. Soil total potassium (TK) and available nitrogen (AN) were the main factors driving bacterial community (0.01 &lt; P ≤ 0.05). The low abundance of Plant growth-promoting rhizobacteria (PGPR) may be a biotic factor contributing to the endangerment of P. squamata. This study provides a foundation to assess the effect of conservation based on bacterial diversity and plant growth-promoting rhizobacteria (PGPR) to guide future research into the conservation of P. squamata.

The study of angular correlations of heavy-flavor particles in hadronic collisions can provide crucial insight into the heavy-quark production, showering and hadronization processes. The comparison with model predictions allows us to discriminate among different approaches for heavy-quark production and hadronization, as well as different treatments of the underlying event employed by the models to reproduce correlation observables. In ultra-relativistic heavy-ion collisions, where a deconfined state of matter, the quark-gluon plasma (QGP), is created, heavy-flavor correlations can shed light on the modification of the heavy-quark fragmentation due to interaction of charm and beauty quarks with the QGP constituents, as well as characterize their energy loss processes while traversing the medium. Insight into possible emergence of collective-like mechanisms in smaller systems, resembling those observed in heavy-ion collisions, can also be obtained by performing correlation studies in high-multiplicity proton-proton and proton-nucleus collisions. In this review, the most recent and relevant measurements of heavy-flavor correlations performed in all collision systems at the LHC and RHIC will be presented, and the new understandings that they provide will be discussed.

The detection and analysis of small molecules, typically defined as molecules under 1000 Da, is of growing interest ranging from the development of small molecule drugs and inhibitors to the sensing of toxins and biomarkers. However, due to challenges such as their small size and low mass, many biosensing technologies struggle to have the sensitivity and selectivity for the detection of small molecules. Notably, their small size limits the usage of labeled techniques that can change the properties of small molecule analytes. Furthermore, the capability of real-time detection is highly desired for small molecule biosensors’ application in diagnostics or screening. This review highlights recent advances in label-free real-time biosensing technologies utilizing different types of transducers to meet the growing demand for small molecule detection.

The article presents a technology for producing nitrogen-containing nanoporous biocarbon with high degree of elemental composition homogeneity, confirmed by electron spectroscopy. The research explores the relationship among the electronic characteristics of supramolecular nanoporous carbon, its porous structure, and the capacitance at its interface with the electrolyte. The obtained biocarbon is characterized by micro and mesopores, as evidenced by the results of studies by the method of nitrogen adsorption/desorption. The specific area of the available porous surface was found to be 1247 m2/g. Comparing this result with the data of small-angle X-ray scattering, we conclude that micropores are open while mesopores remain closed. This material was found to have a saturation magnetization σs of 1.4 A∙m2∙kg-1 and a coercive force Hc of 10 kA/m. The impedance studies of electrochemical cells of supercapacitors made of the experimental biocarbon were carried out. Equivalent electrical circuits of the studied electrochemical processes were constructed and characterized.

For equivalent modeling of mixed wind farms (WFs), existing clustering indicators cannot consider the complex coupling characteristics between different types of wind turbines (WTs). This paper proposes a refined equivalent modeling method for mixed WFs based on artificial intelligence technology. Firstly, the electromechanical transient performance of mixed WFs is analyzed. The WT type, wind speed and direction, and voltage dip are considered the main factors affecting the external dynamic response of mixed WFs. Secondly, the equivalent node model is established, including the selection of independent and dependent variables. Then, the multiple artificial neural networks (ANNs) are trained one by one based on sample data, to explore the nonlinear relationship between the dependent variables and the independent variables. Finally, the electromechanical transient simulations of the power systems with a mixed WF is carried out by using the MATLAB platform. Simulation results show that the proposed model can reflect the external characteristics of the mixed WF in different wind scenarios and voltage dips.

BACKGROUND: diabetic foot ulcers (DFU) represent the main cause of major amputations and hospitalizations in diabetic patients. Aim of this study was to assess safety and cost-efficacy of intramuscular injection of peripheral blood mononuclear cells (PBMNCs), in diabetic patients with no-option chronic limb-threatening ischemia (CLTI) and small artery disease (SAD). METHODS: a retrospective study was carried out on a series of types 2 diabetic patients with DFU grade Texas 3 and no-option CLTI and SAD. All patients had undergone at least a previous revascularization and were allocated in a surgery waiting-list for major amputation. The principal endpoint evaluated at 90 days was a composite of TcPO2 values at the first toe ≥30 mmHg and/or TcPO2 increase of at least 50% from baseline and/or ulcer healing. Secondary endpoint were individual components of the primary endpoint, any serious and non-serious adverse events, direct costs at one year. RESULTS: the composite endpoint was achieved in 9 patients (60.0 %); one patient (6.7%) healed within 90 days and 26.7% and 46.7% showed TcPO2 ≥30 mmHg and a TcPO2 increase of at least 50% at 90 days, respectively. At 1-year, three (20.0%) patients underwent a major amputation (all diagnosed SAD grade III). One patient died after seven months, and seven patients (46.7%) healed. The overall median and mean cost per patient were 8,238±7,798€ and 4,426[3,798;8,262]€, respectively. CONCLUSIONS: the use of PBMNCs implants in no-option CLTI diabetic patients with SAD seems to be of help in reducing the risk of major amputation.

Cytochrome P450 monooxygenases (P450s) are promising versatile oxidative biocatalysts. However, the practical use of P450s in vitro is limited by their dependence on the co-enzyme NAD(P)H and the complex electron transport system. Using H2O2 simplifies the catalytic cycle of P450s; however, most P450s are inactive in the presence of H2O2. By mimicking the molecular structure and catalytic mechanism of natural peroxygenases and peroxidases, an artificial P450 peroxygenase system has been designed with the assistance of a dual-functional small molecule (DFSM). DFSMs, such as N-(ω-imidazolyl fatty acyl)-l-amino acids, use an acyl amino acid as an anchoring group to bind the enzyme, and the imidazolyl group at the other end functions as a general acid-base catalyst in the activation of H2O2. In combination with protein engineering, the DFSM-facilitated P450 peroxygenase system has been used in various oxidation reactions of non-native substrates, such as alkene epoxidation, thioanisole sulfoxidation, and alkanes and aromatic hydroxylation, which showed unique activities, and regio- and enantioselectivities when compared with native P450s. Moreover, the DFSM-facilitated P450 peroxygenase system can switch to the peroxidase mode by mechanism-guided protein engineering. In this short review, the design, mechanism, evolution, application, and perspective of these novel non-natural P450 peroxygenases for the oxidation of non-native substrates are discussed.

In the leading/trailing edge’s adaptive machining of the near-net-shaped blade, a small portion of the theoretical part is retained for securing aerodynamic performance by manual work. However, this procedure is time-consuming and depends on the human experience. In this paper, we defined retained theoretical leading/trailing edge as the reconstruction area. To accelerate the reconstruction process, an anchor-free neural network model based on Transformer was proposed, named LETR (Leading/trailing Edge Transformer). LETR extracts image features from an aspect of mixed frequency and channel domain. We also integrated LETR with the newest meta-Acon activation function. We tested our model on the self-made dataset LDEG2021 on a single GPU and got an mAP of 91.9\%, which surpassed our baseline model, Deformable DETR by 1.1\%. Furthermore, we modified LETR’s convolution layer and named the new model after GLETR (Ghost Leading/trailing Edge Transformer) as a lightweight model for real-time detection. It is proved that GLETR has fewer weight parameters and converges faster than LETR with an acceptable decrease in mAP (0.1\%) by test results.

Matrix metalloproteinases (MMPs) have been demonstrated to have both detrimental and protective functions in inflammatory diseases. Several MMP inhibitors, with the exception of Periostat®, have failed in Phase III clinical trials. As an alternative strategy, recent efforts have been focussed on the development of more selective inhibitors or targeting other domains than their active sites (e.g., exosites, ectosites) through specific small molecule inhibitors or monoclonal antibodies. Here, we present some examples that aim to better understand the mechanisms of conformational changes/allosteric control of MMPs functions. In addition to MMP inhibitors, we discuss unbiased global approaches such as proteomics and N-terminomics to identify new MMP substrates and achieve a better understanding of the roles of these proteases in diseases.

As early as February 2020, many countries have started imposing measures to curb the spread of Covid-19. Despite the right intention, it is a challenging moment for the people, especially the rural population living in the coastal areas. The document presents the preliminary findings on the impacts of Covid-19 on the small scale fisheries in Tun Mustapha Park, Sabah, Malaysia.

Over the last three decades, special economic zones (SEZs) have given new impetus to the ever-growing export-oriented industrialization in developing countries. Where various economies have benefited from SEZs, many zones have ended up becoming enclaves with trifling advantage. The SEZs in Pakistan have experienced the same fate and failed to contribute to exports, employment and creating linkages with the domestic economy. Recently under China Pakistan Economic Corridor (CPEC), SEZs are proposed to be set up in Pakistan; with a hope to fuel the stuttering economy. However, it is pertinent to first understand the local context and device policies considering stakeholders' perspectives. This study aims to identify the factors for the successful implementation of SEZs derived from the regional context of Pakistan. In-depth interviews are conducted from most relevant stakeholders, who have been involved in the development of SEZs. The results pointed towards the removal of political influence over zones and government taking the lead role in deciding the types of industry to be invited in these zones. Each zone should have a clear vision of development based on its regional advantage. The zone promotions should be based on competitiveness rather than fiscal incentives. Joint ventures and PPP to be encouraged inside the zones for sustainable operations.

Social customer relationship management (SCRM) is a new philosophy influencing the relationship between customer and organization, where the customer gets opportunity to control relationship through social media. The paper aims on (a) identification of current level of SCRM and also on (b) influence of basic organizational characteristics on SCRM level. The data were gathered through the questionnaire distributed in 362 organization headquartered in the Czech Republic. The questionnaire comprised 54 questions focusing on the significance of marketing and CRM practices, establishing a relationship with the customer, online communities, the use of social media in marketing, and acquiring and managing information. The majority of questions were scalable and used typical five-level Likert scale. Results showed that larger firms more often set up their own online communities and manage them strategically, moreover they are able to manage information better. Contrariwise, small sized organizations use social networks as a way to establish communication with the customer more than large sized entities. Use of social media for marketing purposes is significantly higher in organizations oriented on consumer markets than on business markets.

During recent years UAVs have been increasingly used in agriculture and forestry research and application. Nevertheless, most of this work has been devoted to improving accuracy and explanatory power, often at the cost of usability and affordability. We tested a low-cost UAV and a simple workflow to apply four different greenness indices to the monitoring of pine (Pinus sylvestris and P. nigra) after-fire regeneration in a Mediterranean forest. We selected two sites and masured all pines within a pre-selected plot. Winter flights were carried out at each of the sites, at two flight altitudes (50 and 100 m). Automatically normalizing images entered an SfM based photogrammetric software for restitution and the obtained point cloud and orthomosaic processed to get a canopy height model and four different greenness indices. Sum of pine DBH was regressed on summary statistics of greenness indices and canopy height model. ExGI and GCC indices outperformed VARI and GRVI in estimating pine DBH, while canopy height model slightly improved the models. Flight altitude did not severely affect model performance. Our results show that low cost UAVs may improve forest monitoring after disturbance, even in those habitats and situations were resource limitation is an issue.

Taking four of the United Nations Development Goals as reference, this overview describes the need to see from a systemic perspective, the food certifications programs along the food chain in Mexico as today food certifications are voluntary. Using secondary data, the main objectives were: a) there is a fall short in food safety policies and those federal agencies responsible for food safety, to guarantee safe food along the whole domestic food chain, especially in that for low income players; b) the amount of the Mexican Federal Budget Expenses devoted to safety food issues is really low, considering the health, well- being, and food security consequences; and c) due the structural heterogeneity of the Mexican food market, there is a lack of coordination in food regulations along all agents of the food supply chain, bringing to alternate informal markets that put at risk peoples´ health, increasing poverty and inequalities. According to this exercise, only 0.7- 8.7% of producers, 12.5% of supermarkets as well as 42.8% of restaurants would have some type of certifications. Public policies must attend this issue in order to improve food safety and security for the whole population, reducing inequalities, poverty and ensuring them a healthy live.

Purpose: To compare the efficacy and safety of graft-free short tunnel small flap (STSF) technique with that of scleral patch graft (SPG) in Ahmed glaucoma valve (AGV) implantation. Design: Randomized clinical trial. Participants: Eighty-eyes of eighty patients with medically uncontrolled glaucoma including 41 in STSF and 39 eyes in SPG. Methods: Patients were enrolled and assigned randomly to STSF or SPG. Main Outcome Measures: tube exposure, Intraocular pressure (IOP), number of glaucoma medications, best corrected visual acuity (BCVA), surgical complications, and success rate ( defined as intraocular pressure (IOP) >5 mmHg, ≤21 mmHg, and IOP reduction ≥20% from baseline at two consecutive visits after three months, no reoperation for glaucoma). Results: only one case in SPG developed tube exposure at 1-year follow-up. The cumulative probability of success during the first year of follow-up was 70% in the STSF and 65% in SPG (P = 0.36). IOP decreased significantly from 29.6 ± 8.6 mmHg at baseline to 16.4 ± 3.6 mmHg at the final follow-up in STSF (p = 0.001). The corresponding numbers for SPG were 30.9 ± 11.2 and 15.8 ± 4.7, respectively (p = 0.001). The final IOP was comparable between both groups (p = 0.65). Mean ± standard deviation of the number of glaucoma medications was 1.8 ± 0.9 in STSF and 1.6 ± 0.9 in SPG at final follow-up (P = 0.32). Postoperative complications developed in 8 patients (19%) in STSF and 9 patients (23%) in SPG (P = 0.81). Conclusions: STSF and SPG techniques had comparable complication rate at one-year follow-up. Both techniques were comparable in terms of success rate, postoperative IOP, and glaucoma medications.

With the inclusion of snakebite envenoming on the World Health Organisation’s list of Neglected Tropical Diseases, an incentive has been established to promote research and development effort in novel snakebite antivenom therapies. Different technological approaches are being pursued by different research groups, including the use of small molecule inhibitors against enzymatic toxins, as well as peptide and oligonucleotide-based aptamers and antibody-based biotherapeutics against both enzymatic and non-enzymatic toxins. In this article, the most recent advances in these fields are presented, and the advantages, disadvantages, and feasibility of using different toxin-neutralizing molecules are reviewed. Particular focus within small molecules is directed towards the inhibitors, varespladib, batimastat, and marimastat, while in the field of antibody-based therapies, novel recombinant polyclonal plantivenom technology is discussed.

Globally, there is increasing prevalence of non- communicable chronic diseases (NCCD) like obesity, metabolic syndrome, type2 diabetes mellitus (T2DM), hypertension, allergic asthma and neuro-developmental/psychiatric problems making NCCD a leading cause of disability, morbidity and mortality . Some of these NCCD are presenting at a younger age especially in the socio-economically disadvantaged communities of affluent countries, and in low and middle -income countries undergoing industrialization and socioeconomic transition.to more economic prosperity. NCCD are often attributed to unhealthy personal lifestyles, but there may be more at play. Through a case report-based discussion, I will illustrate how environmental exposures during the critical window of life, including in utero and early infancy, can significantly influence health as an adult . I will discuss how establishment of a rich and diverse symbiotic gut microbiota in the first three years of life promotes health while a loss of diversity and abundance of beneficial symbiotic gut microbes can predispose to aforementioned NCCD , and the best practices to establish a symbiotic gut.

The continuous casting nozzle which guides and protects the flow of liquid steel undergoes a progressive reduction in its internal diameter following the accumulation on the internal wall of non-metallic inclusions. This narrowing of the channel is due to a mechanical attachment (non-metallic inclusions) and this, because of the turbulent regime of the flow of the liquid steel. This phenomenon is very often associated with the casting of low carbon steels deoxidized exclusively with aluminium. Clogging generally leads to a slowing down of the casting speed and, in severe cases, to the total stoppage of the installation and consequently to the appearance in the slab of the defect called "resumption of casting or belt". The aim of this work is to determine the nature of the deposit and the blocking mechanism of the pouring nozzles. For that, a chemical analysis as well as tests concerning the adhesion of the deposit were carried out on samples taken from damaged pouring nozzles. We found that it was at a load of 187.5 kgf that the rupture of the sample took place, during the interfacial indentation tests, which represents a very high level of adhesion. On the other hand, chemical analysis by X-ray fluorescence of the deposits revealed a fairly high level of alumina (Al₂O₃ = 90%) which undoubtedly comes from inclusions resulting from the deoxidation of the metal. It can therefore be said that the clogging phenomenon is produced by a continuous attachment of non-metallic inclusions to the rough walls of the nozzle.

China is a large agricultural country, and the crop economy has an important place in the national economy. The identification of crop diseases and pests, as well as the non-destructive classification of crops, has always been a challenge in agricultural development, hindering the rapid growth of the agricultural economy. Hyperspectral imaging technology combines imaging and spectral techniques, using hyperspectral cameras to acquire raw image data of crops. After correcting and preprocessing the raw image data to obtain the required spectral features, it becomes possible to achieve rapid non-destructive detection of crop diseases and pests, as well as non-destructive classification and identification of agricultural products. This paper first provides an overview of the current applications of hyperspectral imaging tech-nology in crops both domestically and internationally. It then summarizes the methods of hyper-spectral data acquisition and application scenarios. Subsequently, it organizes the processing of hyperspectral data for crop disease and pest detection and classification, deriving relevant pre-processing and analysis methods for hyperspectral data. Finally, it conducts a detailed analysis of classic cases using hyperspectral imaging technology for detecting crop diseases and pests and non-destructive classification, while also analyzing and summarizing the future development trends of hyperspectral imaging technology in agricultural production. The non-destructive rapid detection and classification technology of hyperspectral imaging can effectively select qualified crops and classify crops of different qualities, ensuring the quality of ag-ricultural products. In conclusion, hyperspectral imaging technology can effectively serve the ag-ricultural economy, making agricultural production more intelligent and holding significant im-portance for the development of agriculture in China.

(1) Background: a study was undertaken to determine the prevalence of chronic diseases and health conditions that affect oral health and oral health self-care among independent living older adults in rural areas of Victoria, Australia; (2) Methods: The study analysed data from the Crossroads-II project, with a total of 1407 participants aged 55 years and older. Participants self-completed questionnaires about health conditions, service use, and demographics. 572 attended a 2-hour health screening that included an assessment of prescribed medications; (3) Results: Most participants were female (55.3%), with a mean age of 69.1 (SD=9.2) years. Participants had a high prevalence of medical conditions, the most common were high blood pressure, arthritis, high lipids, hearing loss, and chronic pain. Almost all participants reported taking medications, with an average of 4.3 medications per person. Among those who attended the health screening, 78.1% were taking medications that could cause xerostomia (dry mouth); (4) Conclusions: This study provides initial information on the prevalence of medical conditions, medication usage, with potential impact on oral health of older adults living in rural Victoria. This information would be valuable for healthcare and dental workforce planning, policy development, and improving the overall well-being of this population.

This work aims to initiate a reflection on the awareness of environmental, social, and corporate governance issues, summarized in the acronym ESG (Environmental, Social, Governance), among Italian SMEs. The integration of ESG issues into business models has led to an expansion of the risk taxonomy affecting corporate management. In addition to traditional financial risks, new risks have emerged, primarily climate risk, environmental, and energy risks, which can significantly impact companies' ability to create economic value. This includes planning and designing virtuous initiatives focused on sustainability and the ability to build public-private partnerships with various stakeholders. After this theoretical framework aimed at highlighting the evolution of the concept of corporate sustainability following the introduction of ESG factors, a clustering of non-performing loans of Italian companies is proposed using a k-Means algorithm, comparing the results obtained through two different methods, namely the Elbow method and the Silhouette coefficient. Finally, using data on Italian regions between 2004 and 2023, an empirical analysis is conducted to provide an estimate of the relationship between non-performing loans and some variables related to ESG components.

Okra, a widely grown vegetable in many regions, often suffers from freshness loss during transportation, causing significant waste. Factors like variety, environment, maturity, and handling affect its quality. Current methods for checking okra tenderness are slow and prone to mistakes, so we need a better, non-damaging method. This study aims to use a device on a robot arm to assess okra freshness and tenderness. We tested 120 okra pods, storing some in a cold chamber for 24 hours (considered tender) and others at room temperature for two days before moving them to a cold environment for five more days (considered not tender). We used a force sensor on a robot arm to measure okra hardness without damaging it, then did tenderness tests. We found that certain sensor data, like the first slope (S1) and the difference between the maximum value and the first overshoot (Os), were good predictors of tenderness, with an accuracy rate of nearly 80%. We also validated this non-damaging method with weight loss, compression, and puncture tests, achieving a 95.5% accuracy rate in distinguishing between tender and non-tender okra pods.

Micronutrient deficiencies remain a public health burden among non-pregnant women in developing countries, including Nepal. Hence, this study examined micronutrient deficiencies among non-pregnant Nepalese women aged 15-49 using the 2016 Nepal National Micronutrient Status Survey (NNMSS). Data on 2143 non-pregnant women was extracted from the 2016 NNMSS. The study analysed ferritin, soluble transferrin receptor (sTfR), red blood cell (RBC) folate and zinc. Multivariable logistic analysis was carried out to assess factors associated with micronutrient deficiencies. Prevalence of ferritin, sTfR, folate, and zinc were 19%, 13%, 16% and 21%, respectively. Non-pregnant women from the Janajati region were significantly less prone to ferritin [adjusted odds ratio (AOR): 0.45; 95% confidence interval (CI): 0.25, 0.80], and those who had body mass index (BMI) of 25 kg/m2 or higher had significantly higher odds of ferritin [AOR: 2.69; 95% CI: 1.01, 7.17]. Non-pregnant women aged 35-49 years were significantly less predisposed to folate deficiency [AOR: 0.58; 95% CI: 0.40, 0.83], and the likelihood of zinc deficiency was significantly lower among non-pregnant women from richer households [AOR: 0.48; 95% CI: 0.31, 0.76]. The study provides further insight into screening high-risk subgroups and instituting public health interventions to address the prevailing micronutrient deficiencies among non-pregnant Nepalese women.

Within the polyurethanes market, only 0.1% are from renewable sources. With the continuing concern about climate change and greenhouse gases in the atmosphere, the substitution of monomers and processes derived from petrochemical sources is crucial for the development of biomaterials. Therefore, polyhydroxyurethanes have propose due to their synthesis route with the incorporation of monomers from renewable sources such as vegetable oils and the substitution of isocyanates known for their high toxicity, carcinogenicity and petrochemical origin, and the use of carbon dioxide. There are few reports on the use of soybean oil and the possible application of these materials in wound healing applications. Based on this, polyhydroxyurethanes were obtained from carbonated soybean oil and two diamines, one aliphatic: 1,4-butadiamine (putrescine), and one cycloaliphatic: 1,3-cyclohexanobis(methylamine), and they were physiochemically, mechanically, and thermally characterized. Four polyhydroxyurethanes were obtained, with stability to hydrolytic and oxidative media, thermal stability above 200 °C, tensile strength between 0.9-1.1 MPa, elongation at break between 81 and 222%. And water absorption up 102% and contact angle between 63,70 and 101,39. Achieving new formulations of biobased NIPHUs that represent a more sustainable process which allow to achieve the physicochemical, mechanical, and thermal properties required for the preparation of wound dressings.

As critical biocontrol agents, Trichoderma and Metarhizium have demonstrated vast potential in disease prevention and pest control respectively. Current applications, however, are predominantly confined to singular use or simplistic combinations of the two fungi. This study innovatively utilizes Metarhizium and Trichoderma as experimental subjects, employing non-targeted metabolomics to compare the differences in metabolites between co-culture and separate fermentation. The metabolite distinctions in co-culture are meticulously analyzed using sample correlation, least squares discriminant analysis, cluster analysis, and KEGG enrichment analysis. Metabolome sequencing analysis is then applied to compare the co-culture fermentation filtrate with Trichoderma atroviride and Metarhizium anisopliae. Differential metabolite analysis found that co-culture had significantly up-regulated or down-regulated metabolites compared to singular cultures.However,significant metabolite discrepancies are discovered in singular cultures, notably the up-regulated metabolites such as osthole and spirocyclic amine, which have documented antibacterial functions that may prove effective against Fusarium graminearum. Ultimately, the findings from this research contribute to the exploration of synergistic applications of biocontrol fungi and serve as a valuable reference for future development of bio-pesticides for disease and pest control.

This study aimed to investigate whether non-fasting plasma triglycerides were associated with diabetes mortality. It included 7,312 US adult participants. Diabetes mortality data were obtained via linkage to the National Death Index (NDI) records. Hazard ratios of non-fasting plasma triglycerides for diabetes mortality were assessed using Cox proportional hazards models, adjusting for age, gender, ethnicity, obesity, poverty-income ratio, education levels, physical activity, alcohol consumption, cigarette smoking status, survey period, hypercholesterolemia, hypertension, diabetes, and family history of diabetes. Among these participants, 1,180 had diabetes. A total of 420 diabetes-caused deaths were recorded during a mean follow-up of 16.8 years. A 1-natural-log-unit increase in non-fasting plasma triglycerides was associated with a 41% higher diabetes mortality risk (hazard ratio, 1.41; 95% confidence interval, 1.19-1.67). Participants with non-fasting plasma triglycerides in the highest quintile, versus those in the lowest quintile, had a 144% higher diabetes mortality risk (hazard ratio, 2.44; 95% confidence interval, 1.49-4.02). The positive association of non-fasting plasma triglycerides with diabetes mortality was independent of diabetes status at the baseline. In conclusion, this study demonstrated that non-fasting plasma triglycerides were positively associated with diabetes mortality, independent of diabetes status at the baseline. Non-fasting triglycerides may be a therapeutic target for diabetes-related complications.

Meat serves as a vital component of the human diet, offering a rich source of protein and essential trace elements. China stands as both a significant producer and consumer of meat on a global scale, leading the world in terms of total meat production and consumption. As the standard of living within the country continues to rise, there is a growing emphasis on the nutritional value and safety of meat consumption. The tenderness of meat is a critical factor influencing its overall quality. Traditionally, tenderness has been assessed through shear force testing, a method that is inherently destructive, inefficient, and results in considerable sample wastage. In light of these drawbacks, non-destructive testing techniques have emerged as a preferred alternative, promising greater accuracy, efficiency, and convenience without compromising the integrity of the samples. This paper delves into the application of five advanced non-destructive testing technologies in the realm of meat tenderness assessment. These include near-infrared spectroscopy, hyperspectral imaging, Raman spectroscopy, airflow optical fusion detection, and nuclear magnetic resonance detection. Each technology is scrutinized for its respective strengths and limitations, providing a comprehensive overview of their current utility and potential for future development. Moreover, the integration of these techniques with the latest advancements in artificial intelligence (AI) technology is explored. The fusion of AI with non-destructive testing offers a promising avenue for the development of more sophisticated, rapid, and intelligent systems for meat tenderness evaluation. This integration is anticipated to significantly enhance the efficiency and accuracy of quality assessment in the meat industry, ensuring a higher standard of safety and nutritional value for consumers. The paper concludes with a set of technical recommendations aimed at guiding the future direction of non-destructive, AI-enhanced meat tenderness detection, thereby contributing to the ongoing improvement of the meat industry in China and beyond.

Despite significant milestones in armed conflict research generally and climate security research specifically, methodologically tight explanation of naturally caused armed conflict still leaves much to be desired. In this article we unpack the black box of the climate-security nexus and advance causal modelling of armed conflict. To infer effects of natural causes on armed conflict outcomes, we apply recent advances in causal methods to conflict outcomes that have been non-experimentally observed across Iraqi municipalities. Retrieval of an entire empirical causal structure of climate-conflict pathways allows us to corroborate the existence of a cause-and-effect relationship between climatological, environmental, and demographic variables and armed conflict. We confirm that soil temperature, population density, and variability of latent energy cause an increase in fatalities, while rice production decreases fatalities. We discuss our findings, their limitations, and future research directions, and reflect on their relevance for policy interventions.

Background: Despite scientific advances, the management of procedural pain in neonates remains suboptimal. Applying adequate therapy to control pain during the neonatal period is a moral and ethical act. In recent decades, ample evidence has accumulated regarding the risks, associated with both untreated pain and the use of more aggressive analgesic therapy. Thus, the emphasis in neonatal clinical practice is on non-aggressive pain management techniques, including homeopathic agents. The efficacy and safety of homeopathic agents for reducing procedural pain in neonates is the subject of the present study. Materials and Methods: Healthy full-term newborn babies with an average age of 72-84 hours were included. They were divided into three study groups: group (A) – not anesthetised, /n= 67/, group (B) – anesthetised with Arnica D30 /n=40/ and group (C)- anesthetised with Sol.Glucose 25% /n=40/. The severity of the pain was assessed using the multimodal - Neonatal Infant Pain Scale (NIPS) and the unimodal - Neonatal Facial Coding System (NFCS) scale. Assessments were done 30s before, 30 seconds after, and 5 minutes after the painful stimulus caused by the heel prick. Heart rate, transcutaneous oxygen saturation, respiratory rate and blood pressure were examined at the same intervals. The results obtained were processed statistically by descriptive analysis and ANOVA at a significance level of p&lt; 0.05. Results: 5 minutes after heel prick both scales showed a statistically significant lower score in those given Arnica D30, compared to those who received Sol.Glucose 25%. When monitoring the physiological indicators, we found a significant increase in the heart rate 30 seconds after the procedure.5 minutes after the heel prick we recorded significantly respiratory rate and systolic blood pressure in all three groups compared to pre-procedural values. Conclusions: Arnica D30 has better analgesic effects compared to Sol.Glucose 25% for newborn babies after heel prick tests.

Malnutrition problems are related to diets that lack one or more essential elements, which it is extremely important to food enrichment to improve the content of compounds effective for health. The objective of this study is to evaluate the effect of the addition of Ca2+, K+ and Mg2+ on the induction of nutraceutical quality in grafted tomatoes grown in the NFT (Nutrient Film Technique) system. In the experiment, two factors were evaluated: plants with and without grafting and the foliar application of 10 ml L−1 Ca2+, 4 ml L−1 K+ and 10 ml L−1 Mg2+ cations separately for each case, in addition to the control. The treatments were evaluated using a completely randomized design, with 5 repetitions per treatment. The interactive effects between grafting and foliar application of Ca2+ induced a greater content lycopene, β-carotene and total flavonoids in fruits of tomato. The interactive effects between the graft and the Mg2+ foliar applications obtained the best results in the phenol content. As regards, capacity DPPH and ABTS, the graft decreased concentration, increasing the content of these through foliar applications of calcium. Regarding the enzymatic variables, graft factor increased activity catalase, glutathione peroxidase and phenylalanine ammonium lyase, obtained the best results graft interaction and foliar application of calcium and magnesium. The results obtained demonstrate the influence of the use of grafts and foliar applications of cal-cium and magnesium as tools that could improve the nutraceutical quality content of tomato crop

Metformin is an oral antidiabetic agent with antimicrobial properties, excreted in an active and unmetabolized form. Like some non-antibiotic drugs, subinhibitory concentrations of metformin may contribute to the expression of microbial resistance in wild-type strains. This work aimed to evaluate the biofilm formation of Pseudomonas aeruginosa TGC04 exposed to 100 and 200 µg/mL of metformin, varying the Chemical Oxygen Demand (COD) and flow regime. Biofilms were quantified after 2 and 24 hours, observing reductions and increases in biofilm growth around 13 and 64%, respectively. The greatest biofilm growth occurred in cells exposed to 200 µg/mL of metformin. Both the flow regime and COD concentration were important for the development of the biofilm, whose cells were mostly weakly to moderately adhered. The study provides evidence that in polluted aquatic systems with turbulent regimes, the inhibitory concentration of metformin promoted the least disturbances to the biofilm.

This publication delves into the intricate world of human communication, extending beyond the realm of spoken and written language to explore the profound influence of non-verbal communication. Focusing on body language—comprising gestures, facial expressions, postures, and movements—it reveals the pivotal role it plays in conveying emotions, intentions, and psychological states. The rapidly evolving fields of neuroscience and cognitive science are investigating the neural mechanisms and cognitive processes that underpin the interpretation and utilization of these non-verbal cues. Notably, the amygdala's involvement in processing emotional facial expressions has provided a neurological foundation for our emotional understanding in non-verbal communication. Concurrently, cognitive psychology sheds light on how perception, attention, and memory influence our interpretation of non-verbal cues and communication strategies.In our modern, technologically advancing society characterized by global interconnectivity and cultural diversity, the significance of non-verbal communication, especially in digital and virtual contexts, is paramount. The transformation of non-verbal expression into digital symbols like emoticons and emojis raises questions regarding its ability to maintain authenticity and emotional understanding. This publication endeavors to comprehensively explore the fundamental role of body language and non-verbal communication in contemporary society. By integrating insights from psychology, neuroscience, social sciences, and digital technologies, it aims to elucidate the underlying mechanisms guiding non-verbal communication. Additionally, it delves into the implications of non-verbal communication across diverse domains, including interpersonal communication, the workplace, politics, advertising, and the virtual world.The research presented herein strives to offer a thorough understanding of interpersonal dynamics, relationships, and social behavior, with the goal of promoting the development of more effective, conscious, and ethically guided communication strategies. Ultimately, this analysis aspires to inspire further interdisciplinary research and reflection, addressing emerging challenges and fully leveraging the potential of non-verbal communication in modern society. This, in turn, guides our path towards a communication landscape that is more inclusive, authentic, and empathetic.

Although adult spontaneous (non-diabetic) hypoglycaemia is rare, its recognition is important for the preventative or curative treatment of the underlying cause. Establishing Whipple’s triad; low blood glucose, neuroglycopaenia and resolution of neuroglycopaenia on increasing blood glucose levels to normal or above, is essential to verify hypoglycaemia. Awareness that hypoglycaemia may occur in severely ill patients is important for its prevention. Further investigation in such cases is unnecessary unless another cause of hypoglycaemia is suspected. Patients are often asymptomatic and normoglycaemic at review. History of medication, self-medication, access to hypoglycaemic drugs, alcohol and comorbidity may provide aetiological clues. The investigation involves obtaining blood samples during symptoms for laboratory glucose measurement or provoking fasting or postprandial hypoglycaemia as directed by symptoms. If confirmed, insulin, c-peptide, proinsulin, beta-hydroxybutyrate are analysed in hypoglycaemic samples. These will classify hypoglycaemia due to non-ketotic hyperinsulinaemia, non-ketotic hypoinsulinaemia and ketotic hypoinsulinaemia and direct investigations to identify the underlying cause. There are, however, many pitfalls, which may mislabel healthy individuals as “hypoglycaemic” or misdiagnose treatable or preventable causes of spontaneous hypoglycaemia. Clinical acumen and appropriate investigations will mostly identify hypoglycaemia and its cause.

This paper presents ConF, a novel deep learning model designed for accurate and efficient prediction of non-coding RNA families. NcRNAs are essential functional RNA molecules involved in various cellular processes, including replication, transcription, and gene expression. Identifying ncRNA families is crucial for comprehensive RNA research, as ncRNAs within the same family often exhibit similar functionalities. Traditional experimental methods for identifying ncRNA fam-ilies are time-consuming and labor-intensive. Computational approaches relying on annotated secondary structure data face limitations in handling complex structures like pseudoknots and have restricted applicability, resulting in suboptimal prediction performance. To overcome these chal-lenges, ConF integrates mainstream techniques such as residual networks with dilated convolutions and cross multi-head attention mechanisms. By employing a combination of dual-layer convolu-tional networks and BiLSTM, ConF effectively captures intricate features embedded within RNA sequences. This feature extraction process leads to significantly improved prediction accuracy compared to existing methods. Experimental evaluations conducted on a ten-fold publicly available dataset demonstrate the superiority of ConF in terms of accuracy, sensitivity, and other perfor-mance metrics. Overall, ConF represents a promising solution for accurate and efficient ncRNA family prediction, addressing the limitations of traditional experimental and computational methods.

Background: Chronic, non-cancer pain represents a serious public health and economic issue affecting approximately 20% of the global population. Chronic pain can affect many aspects of patient’s lives, including mental health, employment, and relationships. Current medical management is largely focussed on investigating and managing acute pain. Patients and clinicians are now increasingly aware of the potential benefits of combined treatments or complex interventions in alleviating chronic pain. These approaches include both physical interventions, such as exercise or yoga, as well as psychological support including cognitive behavioural therapy (CBT) and talking therapies. Methods: This study used network meta-analyses to explore the prevalence of complex interventions in pain management, and the effects of these interventions on quality of life, using outcome measures including intensity of chronic pain, assessment of functional disability and participant’s psychological state. Results: Psychological interventions were associated with improvements in pain intensity and depression. Exercise and manipulation technique-based treatments provided a statistically significant reduction in pain intensity. This effect was enhanced when exercise and CBT were combined. Mensendieck somatocognitive therapy (MSCT) plus standard gynaecological treatment (STGT) treatments appeared to have a better effect on chronic pain than multimodal exercise plus CBT treatment. Combined MSCT and STGT treatment, and multimodal exercise plus CBT treatments, reduced pain intensity, whilst MSCT+STGT treatments had a slightly better effect than exercise plus CBT treatment.Conclusions: Complex interventions have become more popular with patients as the risks associated with other interventions including surgery and pharmacological management have become better understood. These interventions can have a significant positive effect both on the physical and psychological health of patients. The analysis presented in this study suggests that further work is warranted in this area and that additional studies are required, both in more geographically diverse locations, and with larger cohorts.

Fermented food matrices, including beverages, can be defined as the result of the activity of complex microbial ecosystems where different microorganisms interact according to different biotic and abiotic factors. Certainly, in industrial production the technological processes aim to control the fermentation to place safe foods on the market. Therefore, if food safety is the essential prerogative, consumers are increasingly oriented towards a healthy and conscious diet driving the production and consequently the applied research towards natural processes. In this regard, the aim to guarantee safety, quality and diversify of products should be reached limiting or avoiding the addition of antimicrobials or synthetic additives using the biological approach. In this paper, following the recent re-evaluation of non-Saccharomyces yeasts (NSYs) has been re-viewed the bio-protectant and biocontrol activity with a particular focus on their antimicrobial power, probiotic features and promoting functional aspects. In this review, the authors would underline the contribution of NSYs in all food production chain and its role in the technological and fermentative features for their practical and useful use as biocontrol agent in food preparations.

The need to regulate the non-exhaust particulate emissions from vehicles has been discussed worldwide due to the toxicity to the human body as well as the atmosphere. In-depth studies have been conducted on precise analysis of the non-exhaust particulates, in particular, accurate measurement of tire-brake-road wear particles, and their proportion in the atmosphere. In this study, the influence of tire and road wear particles (TRWP) on particulate matter (PM) in the atmosphere was investigated through tire and PM samples. PM samples were collected from the atmosphere using a high-volume sampler equipped with a quartz filter. Additionally, polycyclic aromatic hydrocarbons (PAHs) and heavy metals in tire rubber were analyzed as markers by pyrolysis-gas chromatography/mass spectrometry (GC/MS), GC/MS, and inductively coupled plasma/mass spectrometry (ICP/MS). More vinylcyclohexene was detected than dipentene in the markers measured in the samples of tires equipped with vehicles driving on the road with the high-volume sampler installed, while more dipentene was detected in total suspended particles (TSP) samples. Among the PAHs measured in tire samples, pyrene exhibited the highest concentration. In TSP samples, benzo(b)fluoranthene showed the highest concentration. Among the heavy metals, zinc exhibited the highest concentration in all tire samples and calcium in TSP samples.

With the development of data science, more and more machine learning technologies have been designed to solve complicated and challenging real-world tasks containing a large volume of data. And many significant real-world datasets contain data in the form of networks or graphs. Graph Neural Networks is one of the powerful machine learning tools, which could provide a perfect solution to processing a large amount of non-Euclidean data. And because most bio information data in bioinformatics is in the non-Euclidean domain, Graph Neural Networks could then directly be applied to solve problems in bioinformatics. Much research has been done in the field of GNN, and there are also some surveys related to GNN and its applications. However, there has been little research focusing on GNN in bioinformatics, and we think in the future we could better utilize GNN in the field of biology, so we would like to write a literature review to help take a comprehensive look at GNN and their applications in the field of bioinformatics. In this paper, we would first introduce SOTA models in Graph Neural Networks, and second, introduce their applications in bio information. And then we would provide future directions of Graph Neural Networks in bioinformatics.

In this paper we use the additive thermodynamic formalism to obtain new bounds of the Hausdorff and box-counting dimension of certain non conformal hyperbolic repellers defined by piecewise smooth expanding maps on a $d$-dimensional smooth manifold $M$.

We suggest that the 14^th century scholar Nicholas of Autrecourt can be regarded as a precursor of the paraconsistent logics developed around 1950. We show how the Sorbonne licentiatus in theology provided in his few extant writings a refutation of both the principle of explosion and the law of non-contradiction, in accordance with the tenets of paraconsistent logics. This paves the way to the most advanced theories of truth in natural language and quantum dynamics.

We extend the standard solid-state quantum mechanical Hamiltonian containing only Coulomb interactions between the charged particles by inclusion of the (transverse) current-current diamagnetic interaction starting form the non-relativistic QED restricted to the states without photons and neglecting the retardation in the photon propagator. This derivation is supplemented with a derivation of an analogous result along the non-rigorous old classical Darwin-Landau-Lifshitz argumentation within the physical Coulomb gauge.

On-farm research was conducted at Gouripur sub-district under Mymensingh district of Bangladesh during the boro (mid November-June) season in 2013-14 and 2014-15 to evaluate the performance of non-puddled rice cultivation with and without crop residue retention. The rice var. BRRI dhan28 was transplanted by two tillage practices viz., puddled conventional tillage (CT) and non-puddled strip tillage (ST) and at two levels of mustard residues, i.e., no residue (R₀) and 50% residue (R₅₀). The experiment was designed in a randomized complete block design with four replications. There were no significant yield differences between tillage practices and residue levels in 2013-14. But in the following year, ST yielded 9% more grain compared to CT leading to 22% higher BCR. Retention of 50% residue increased yield by 3% compared to no-residue, which contributed to 10% higher benefit-cost ratio (BCR). The ST combined with 50% residue retention yielded the highest grain yield (5.81 t ha^-1) which contributed to produce the highest BCR (1.06).

The General equilibrium theory tries to show how and why all free markets tend toward equilibrium in the long run. However, what is meant by equilibrium in this paper is more from a thermodynamical point of view. In order to understand the actual situation, it is necessary to study open systems which are complex. In physics, such a behavior in a complex system can be explain by using Non Equilibrium Thermodynamics. A system is able to self-organize and sustain itself away from equilibrium. Economic systems may fluctuate around a particular point. To sustain it far from the equilibrium state, it needs to degrade more energy and materials. In this study, the energy consumption patterns of Sri Lanka and USA are discussed. The pattern concerning Sri Lanka is close to the model proposed here, whereas the energy consumption pattern of USA is more complicated due to external factors.

The goal of this paper is to explore the relationship between the specific non-performing loan ratio (NPL ratio) and the corresponding impact on the bank’s profitability and lending behavior. It also seeks to investigate the macroeconomic impacts of economies with excessively high NPL ratios as well as the efficacy and impact of alleviation measures used by banks and governments around the world to help facilitate a decrease in high NPL ratios. The possible implications and effects of the COVID-19 pandemic on NPL ratios is also addressed in this paper. It is found that when excessively high NPL ratios go unaddressed, the economy tends to suffer. On the other hand, this study shows that when measures are taken to reduce or eliminate the high NPL ratios, economic performance improves, and the reduction has a clear positive impact on the economy.

A description of the motion in Non-Inertial Reference Frames by means of the inclusion of high time derivatives is studied. It is noted that incompleteness of the description of physical reality is a problem of any theory: both quantum mechanics and classical physics. The "stability principle" is put forward. We also provide macroscopic examples of Non-Inertial Mechanics and verify the use of high-order derivatives as non-local hidden variables based the equivalence principle when acceleration is equal to the gravitational field. Acceleration in this case is a function of the higher derivatives with respect to time. The definition of Dark Metrics for matter and energy is presented to replace the standard notions of Dark Matter and Dark Energy.

Night-time lights interact with human physiology through different pathways starting at the retinal layers of the eye, from the signals provided by the rods, the S-, L- and M-cones, and the intrinsically photosensitive retinal ganglion cells (ipRGC). These individual photic channels combine in complex ways to modulate important physiological processes, among them the daily entrainment of the neural master oscillator that regulates circadian rhythms. Evaluating the relative excitation of each type of photoreceptor generally requires full knowledge of the spectral power distribution of the incoming light, information that is not easily available in many practical applications. One such instance is wide area sensing of public outdoor lighting; present-day radiometers onboard Earth-orbiting platforms with sufficient nighttime sensitivity are generally panchromatic and lack the required spectral discrimination capacity. In this paper we show that RGB imagery acquired with off-the-shelf digital single-lens reflex cameras (DSLR) can be a useful tool to evaluate, with reasonable accuracy and high angular resolution, the photoreceptoral inputs associated with a wide range of lamp technologies. The method is based on linear regressions of these inputs against optimum combinations of the associated R, G, and B signals, built for a large set of artificial light sources by means of synthetic photometry. Given the widespread use of RGB imaging devices, this approach is expected to facilitate the monitoring of the physiological effects of light pollution, from ground and space alike, using standard imaging technology.

Facing with errors of a product after machining was a big title in this field. That will affect to product’s quality with unpredictable situation when products is in use for some particular application such as in medical facilities. Improving the precision of machine tools by exploring temperature on multiple points and measuring differential locations of the spindle is going to be executed in this study. A temperature measurement tool and a software running on Windows platform have been developed and combining with Non-bar system in order to support analyzing the temperature rising with the changes of length of the spindle to find the compensation solution based on eccentricity and length distortion. In this study, the whole tests have done on UX300 five – axis CNC machine tools for this investigation and the errors after applying compensation function have reduced 70% at least, with respect to the errors after machining without using compensation function.

We present a new method of estimating fitness of countries and complexity of products by exploiting a non-linear non-homogeneous map applied to the publicly available information on the goods exported by a country. The non homogeneous terms guarantee both convergence and stability. After a suitable rescaling of the relevant quantities, the non homogeneous terms are eventually set to zero so that this new method is parameter free. This new map reproduces the findings of the method proposed by Tacchella et al. [1], and allows for an approximate analytic solution in case of actual binarized matrices based on the Revealed Comparative Advantage (RCA) indicator. This solution is connected with a new quantity describing the neighborhood of nodes in bipartite graphs, representing in this work the relations between countries and exported products. Moreover, we define the new indicator of country net-efficiency quantifying how a country efficiently invests in capabilities able to generate innovative complex high quality products. Eventually, we demonstrate analytically the local convergence of the algorithm.

Anomalous waves and rogue events are closely associated with irregularities and unexpected events occurring at various levels of physics, such as in optics, in oceans and in the atmosphere. Mathematical modeling of rogue waves is a highly actual field of research, which has evolved over the last decades into a specialized part of mathematical physics. The applications of the mathematical models for rogue events is directly relevant to technology development for prediction of rogue ocean waves, and for signal processing in quantum units. In this survey, a comprehensive perspective of the most recent developments in methods for representing rogue waves is given, along with discussion of the devised and forms and solutions. The standard nonlinear Schrödinger equation, the Hirota equation, the MMT equation and further to other models are discussed, and their properties highlighted. This survey shows that the most recent advancement in modeling rogue waves give models which can be used to establish methods for prediction of rogue waves at open seas, which is important for the safety and activity of marine vessels and installations. The study further puts emphasis on the difference between the methods, and how the resulting models form a basis for representing rogue waves in various forms, solitary or with a wave-background. This review has also a pedagogic component directed towards students and interested non-experts, and forms a complete survey of the most conventional and emerging methods published until recently

Cardiovascular diseases (CVD) are the leading cause of morbidity and mortality worldwide, including in Croatia. Since most patients have multiple disorders and diseases caused largely by the same risk factors, and as it is essential to approach each patient as a person with all disorders, today we are talking about a new paradigm - cardio-renal-metabolic (CKM) syndrome and cardio-renal-metabolic health, which necessarily includes brain health. Elevated systolic blood pressure, LDL cholesterol, smoking, obesity, diabetes, impaired renal function or chronic kidney disease, which all stem from insufficient physical activity, unhealthy diet with excessive intake of table salt, and air pollution, are the leading causes of overall morbidity and mortality from CKM diseases, especially mortality from CVD. Experts from various fields key to CKM health have written this document with the aim of integrating it as part of the national plan for the prevention of chronic non-communicable diseases with a focus on CVD, which should become mandatory and be based on the existing guidelines of professional societies.

The purpose of this manuscript is to examine the extent to which Polish SMEs use digital marketing tools in the context of their impact on economic performance. The choice of the objective is due to the research gap related to the lack of studies on the impact of the use of digital marketing tools on economic performance by SME companies in Poland. In order to achieve the objective, a two-stage approach was used. The first stage identified the degree of use of digital marketing tools by Polish SMEs compared to EU countries based on secondary data. The second stage analyzed the impact of the use of selected digital marketing and sales communication tools on the economic performance of Polish SMEs. The analysis was based on primary data, which were the results of surveys conducted on a sample of 574 Polish SMEs in the industrial sector. The analysis used statistical methods such as difference significance tests (Mann-Whitney U test, ANOVA Kruskal-Wallis test and Dunn's post-hoc tests), Kendall's rank correlation coefficient and Multivariate Adaptive Regression Splines (MARSplines). The results obtained have theoretical and practical values. The theoretical implications are the enrichment of the marketing concept of customer value creation taking into account the digital customer, which is also the originality of the research. Practical implications refer to indicating to SME managers the need for, as well as ways of implementing and financing digital technologies within the framework of various EU programs for digital transformation of member states.

The effectiveness of simple weirs and the ability of rural farmers to construct durable weirs are still areas of concern in rural areas in Zambia. The objective of this study is to investigate the factors contributing to the varying levels of durability of the simple weir structures used for the diversion of river flows. This study was conducted in 5 districts where 33 SWs located in similar geographical zones were analyzed for their longevity. The research delved into catchment and climatic variables, and the social and psychological perception of simple weirs. The study conducted interviews with key informants who were familiar with the use of SWs in 5 districts in Muchinga provinces between 26 December 2023 and 15 January 2024 using semi-structured questions. The findings of this study indicated that simple weirs constructed on relatively square-shaped catchments and narrow-shaped catchment areas were less vulnerable to damage and easy to operate and maintain. The study also found that climatic factors such as storm rainfall events had little impact on the operation and maintenance of these weirs in Muchinga province, as most sites are in the rainfall shadow while farmers` views about the structures varied from site to site. Overly, planning is necessary for implementing small or large irrigation structures.

In the modern power grid, characterized by the increased penetration of power electronics and extensive utilization of renewable energy, inverters-based power plants play a pivotal role as the principal interface of renewable energy sources (RESs) and the grid. Considering the stability characteristics of grid-following (GFL) inverters when the grid is relatively weak, the application of grid-forming (GFM) controls becomes imperative to enhance the stability of the entire power plant. Thus, there is an urgent need for suitable and effective models to study the interaction and stability of the paralleled inverters employing GFL and GFM controls. Thus, the small-signal modeling with full-order state space model and eigenvalues analysis is presented in this paper. First, the small-signal state-space model of the individual GFL and GFM inverters is obtained considering the control loop, interaction, reference frame, transmissions, and time delays. Then, the models of the individual inverter are extended to the hybrid inverters to study the effects of the GFM inverters on the small- signal stability of the entire system. And, the impacts of the inertia and damping are analyzed by the eigenvalues of the state-transition matrix. Case comprising three parallel GFL inverters and two GFL inverters with one GFM inverter, respectively, are studied to examine the effectiveness and accuracy of the model. Finally, the stability margin obtained from the eigenvalue analysis of the entire system is verified by time-domain simulations.

Electrospun fiber scaffolds are widely used in small diameter vascular tissue engineering because they mimick organizational structure and biological function of natural extracellular matrix. However, there is still one problem of low patency rate in the long term. The main reasons are the mismatch of compliance and the easy formation of thrombus. Therefore, it is very important to promote the rapid endothelialization of small diameter tissue engineering blood vessels by regulating the topological structure and biological properties of electrospun fiber scaffolds. Firstly, crimped polylactic acid (PLA) fibers were prepared by heat treatment to mimick the crimped structure and nonlinear mechanical properties of the elastic membrane of blood vessel wall. It improved effectively the aspect ratio of human umbilical vein endothelial cells (HUVECs) and promoted lateral alignment and growth. Then, crimped PLA fibers with three levels of pore structure were prepared by thermal induced phase separation, vapor induced phase separation and laser ablation to enhance the degree of HUVECs infiltrarion and realize patterned cell growth. Crimped PLA fibers with three levels of pore structure promote rapid endothelialization of blood vessels, which is of great significance to achieve long term patency rate of small diameter tissue engineering blood vessels.

Energy transition is one of the greatest challenges facing humanity today. All micro, small, medium and large enterprises in operation will have to face it, and some can al-ready boast the first successes in this regard. This paper focuses on the involvement of these smallest players in energy transition. Micro and small entities are the largest part of the economy, having a great influence on its development. Looking at the wide scale of their activities, these entities are distinguished by a specific owner-manager relationship. This means that the final decision-making is influenced by business goals, but also by the manager's approach, their awareness of changes, and personal and other factors. Based on a structured and standardized survey questionnaire, the research was carried out using the Computer-Assisted Telephone Interviewing technique between April and May 2022 among owners of micro and small enterprises operating in Poland. The survey showed that active engagement of micro and small enterprises in energy efficiency initiatives is related to their market success and financial health.

Small-scale fisheries are significant sources of nutrition and livelihood globally. However, increasing anthropogenic activities in coastal areas of developing countries have threatened the sustainability of artisanal fisheries and species. Fisheries of Sardinella maderensis (Lowe, 1838), to which Nigeria contributes 9% of the global stock and is a significant livelihood source in the coastal communities of Ibeju-Lekki, Lagos, face sustainability threats. This research investigated the effects of anthropogenic activities on S. maderensis fishery in the coastal areas of Ibeju-Lekki, Lagos, Nigeria. The study adopted a mixed-method approach involving qualitative and quantitative research methods. These include species identification, water quality analysis, land use change analysis, field surveys, focus group discussions and interviews. Results show genetic analysis of the fish samples from six stations revealed that the species had a mean of 98% similarity to Sardinella maderensis in NCBI. Multiple linear regression indicates that anthropogenic variables explained approximately 4.62% of the variance in the fish catch (p &lt; .001, R2 = .05). Water samples showed heavy metal levels were above international limits, high total petroleum hydrocarbon (TPH) pollution in all stations (27.56 mg/L- 3985.40 mg/L). Physiochemical analysis of water samples indicated TDS higher than acceptable limits (Mean = 24971.1 mg/L) and inadequate chlorophyll-a level (Mean = 0.01 µg/L). Hence, urgent strategies are required to mitigate anthropogenic threats through inclusive coastal management policies supporting resilient artisanal fisheries and marine spatial planning.

The authors of the article analyze the existing methods and models of technological preparation of machine-building industries. The structure of a three-level simulation model with network-centric control, the structures of individual elements of the simulation model and the process of simulation modeling are described. The criteria for choosing a rational option for the processing technological route have been determined. During the research, a simulation program was implemented in C++. It allows you to select the optimal scenario for the operation of a production site based on two criteria: time and cost. The volume of implementation is about 2x103 lines of code. A diagram of the modeling algorithm for the implemented program, a description of the classes and their interactions are given in the article. The developed simulation model was tested at a machine-building enterprise using the example of the “Pusher” part, manufactured under single-unit production condi-tions. The technological equipment used for the manufacture of this part was formed in the form of input data of the simulation model. The results of simulation modeling for the selected part are described. For each variant of the technological processing route, the values of variable costs and the duration of the production cycle were determined.

A recent study has suggested that the age profiles for deaths due to COVID-19 variants differs between variants and shows male/female specificity. This study demonstrates the age and sex dependency is common among human pathogens. The often-reported higher susceptibility to infections among the young and elderly is true in general but does not apply to individual pathogens. Even among different types of pneumonia there are subtle differences in the age profile. The gender ratio between pathogens likewise shows wide variation from as low as 10% female admissions for leptospirosis to around 90% for gonococcal admissions. The observed age/sex variation observed for mortality due to COVID-19 variants is an expression of a far wider phenomenon with implications to the age/sex response to vaccines. We propose that such differences are likely to be controlled by small noncoding RNAs which act as potent regulators of gene expression leading to altered cell morphology, metabolism, immune function, and response to vaccines.

The genetic diversity of coronavirus (CoV) is high, and its infection in animals has not yet been fully revealed. By RT-PCR detection of partial RNA dependent RNA polymerase (RdRp) gene of CoV, we screened a total of 502 small mammals belonging to 18 species in 12 genera and 4 orders collected in Dali and Nujiang Prefecture of Western Yunnan Province, China. The prevalence of β-CoV in Chevrieri's field mouse (Apodemus chevrieri) and Lancangjiang field mouse (A. ilex) were 3.54% (4/113) and 6.67% (6/90), respectively; the prevalence of α-CoV in White-footed Indochinese rat (Rattus nitidus) and long-tailed red-toothed shrew (Episoriculus leucops) was 75% (3/4) and 5.88% (1/17), respectively. The co-infection rates of β-CoV and α-CoV in Kachin red-backed vole (Eothenomys cachinus), Norway rat (R. norvegicus) were 2.22% (2/90), 3.85% (1/26) respectively. The identity of the partial RdRp genes obtained of 13 strains of β-CoV was 83.42%-99.23% at nucleotide level, and it is worth noting that the two strains from Kachin red-backed vole showed highly homology to BOV-36/IND/2015 from Indian bovine and DcCoV-HKU23 from one-humped camel (Camelus dromedarius) in Morocco, the nucleotide similarity between 97.86%-98.33%. Similarly, the identity of the 7 strains of α-CoV among the partial RdRp sequences was 94.00%-99.18% at nucleotide levels. The viral load in different tissues was measured by quantitative RT-PCR (qRT-PCR). The average CoV viral load in small mammalian intestinal tissue was 1.25×106copies/g, differently, the mean CoV viral load in liver, heart, lung, spleen and kidney tissue was from 1.29×103 to 4.02×103copies/g, which revealed that CoV has extensive tropism of intestinal tissue in small mammals (P &lt; 0.0001). This result revealed the genetic diversity, epidemiology, and infective tropism of α-CoV and β-CoV in small mammals from Dali and Nujiang, which deepens the comprehending of the retention and infection of coronavirus in natural hosts.

In the realm of modern drug discovery, the integration of chemoinformatics and quantitative structure-activity relationship (QSAR) modeling has emerged as a formidable alliance, enabling researchers to harness the vast potential of machine learning (ML) techniques for predictive molecular design and analysis. This review delves into the fundamental aspects of chemoinformatics, elucidating the intricate nature of chemical data and the crucial role of molecular descriptors in unveiling the underlying molecular properties. Molecular descriptors, including 2D fingerprints and topological indices, in conjunction with the structural-activity relationships (SARs), play a pivotal role in unlocking the pathway to small-molecule drug discovery. Technical intricacies of developing robust ML-QSAR models, including feature selection, model validation, and performance evaluation, are discussed herewith. Various ML algorithms, such as regression analysis and support vector machines, are showcased in the text for their ability to predict and comprehend the relationships between molecular structures and biological activities. This review serves as a comprehensive guide for researchers, providing an understanding of the synergy between chemoinformatics, QSAR, and ML. By embracing these cutting-edge technologies, predictive molecular analysis holds promise for expediting the discovery of novel therapeutic agents in the pharmaceutical sciences.

Compared to wide-field telescopes, small-field detection systems have higher spatial resolution, resulting in stronger detection capabilities and higher positioning accuracy. When detecting by small-field in synchronous orbit, both space debris and fixed stars are imaged as point targets, making it difficult to distinguish them. In addition, with the improvement of detection capabilities, the number of stars in the background rapidly increases, which puts higher requirements on recognition algorithms. Therefore, star detection is indispensable for identifying and locating space debris in complex backgrounds. To address these difficulties, this paper proposes a real-time star extraction method based on adaptive filtering and multi frame projection. We use bad point repair and background suppression algorithms to preprocess star image. Afterwards, we analyze and enhance the target signal-to-noise ratio(SNR). Then, we use multi frame projection to fuse information. Subsequently, adaptive filtering, adaptive morphology, and adaptive median filtering algorithms are proposed to detect trajectories. Finally, the projection is released to locate the target. Our recognition algorithm has been verified by real star images, and the images were captured using small-field telescope. The experimental results demonstrate the effectiveness of the algorithm proposed in this paper. We successfully extracted hip-27066 star, which has magnitudes about 12 and SNR about 1.5. Compared with existing methods, our algorithm has advantages in both recognition rate and false-alarm rate, and can be used as real time target recognition algorithm for space-based synchronous orbit detection payload.

The multivariate Gaussian random fields with matrix-based scaling laws are widely used for inference in statistics and many applied areas. In such contexts interests are often in symmetry and in the rates of change of spatial surfaces in any given direction. This article analyzes the almost sure sample function behavior for operator fractional Brownian motion, including multivariate fractional Brownian motion. We obtain the estimations of small ball probability and the strongly locally nondeterministic for operator fractional Brownian motion in any given direction. Applying these estimates we obtain Chung's laws of the iterated logarithm for spatial surfaces of operator fractional Brownian motion. Our results show that the precise rates of change of spatial surfaces are completely determined by the self-similarity exponent.

Growing interest surrounds the assessment of perivascular spaces (PVS) on magnetic resonance imaging (MRI) and their validation as a clinical biomarker of adverse brain health. Nonetheless, the limits of validity of current state-of-the-art segmentation methods are still unclear. Here, we propose an open-source three-dimensional computational framework comprising 3D digital reference objects and evaluate the performance of three PVS filtering methods under various spatiotemporal imaging considerations (including sampling, motion artefacts, and Rician noise). Specifically, we study the performance of the Frangi, Jerman and RORPO filters in enhancing PVS-like structures to facilitate segmentation. Our findings were three-fold. First, as long as voxels are isotropic, RORPO outperforms the other two filters, regardless of imaging quality. Unlike the Frangi and Jerman filters, RORPO’s performance does not deteriorate as PVS volume increases. Second, the performance of all “vesselness” filters is heavily influenced by imaging quality, with sampling and motion artefacts being the most damaging for these types of analyses. Third, none of the filters can distinguish PVS from other hyperintense structures (e.g. white matter hyperintensities, stroke lesions, or lacunes) effectively, the area under precision-recall curve dropped substantially (Frangi: from 94.21 [IQR 91.60, 96.16] to 43.76 [IQR 25.19, 63.38]; Jerman: from 94.51 [IQR 91.90, 95.37] to 58.00 [IQR 35.68, 64.87]; RORPO: from 98.72 [IQR 95.37, 98.96] to 71.87 [IQR 57.21, 76.63] without and with other hyperintense structures, respectively). The use of our computational model enables comparing segmentation methods and identifying their advantages and disadvantages, thereby providing means for testing and optimising pipelines for ongoing and future studies.

Potato is among one of the most important food crops, yet maintaining plant productivity in this drought-sensitive crop has become a challenge. Competition for scarce water resources and the continued effects of global warming exacerbate current constraints on crop production. While plants’ response to drought in above-ground tissues has been well documented, the regulatory cascades in developing tubers have been largely unexplored. Using the commercial Canadian cultivar ‘Vigor’, plants were subjected to a drought treatment under high-tunnels causing a 4 ℃ increase in canopy temperature when compared to the well-watered control. Tubers were sampled for RNAseq and metabolite analysis. Approximately 2600 genes and 3898 transcripts were differentially expressed by at least four-fold in drought-stressed potato tubers, with 75 % and 69 % being down-regulated respectively. A further 229 small RNAs were implicated in gene regulation during drought. The comparison of protein homologues between Solanum tuberosum L. and Arabidopsis thaliana L. indicates that downregulated genes are associated with phenylpropanoid, carotenoid, and patatin biosynthesis. This suggests that there may be nutritive implications to drought stress occurring during the potato tuber bulking phase in sensitive cultivars.

Cogging torque is a pulsating, parasitic and undesired torque ripple intrinsic of the design of a permanent magnet synchronous generator (PMSG), which should be minimized due to its adverse effects: vibration and noise. In addition, as aerodynamic power is low during start-up at low wind speeds in small wind energy systems, the cogging torque must be as low as possible to achieve a low cut-in speed. A novel mitigation technique using compound pre-slotting, based on a combination of magnetic and non-magnetic materials, is investigated. The finite element technique is used to calculate the cogging torque of a real PMSG design for a small wind turbine, with and without using compound pre-slotting. The results show that cogging torque can be reduced by a factor of 48% with this technique, while avoiding the main drawback of the conventional pre-slotting technique: the reduction of induced voltage due to leakage flux between stator teeth. Furthermore, through a combination of pre-slotting and other cogging torque optimization techniques, 84%, cogging torque can be eliminated for a given design.

The alignment of nanostructures in materials such as lyotropic liquid crystals (LLCs) templated materials has the potential to signicantly improve their performances. However, accurately characterising and quantifying the alignement of such fine structures remains very challenging. In situ small angle X-ray scattering (SAXS) and molecular dynamics were employed for the first time to understand the hexagonal LLC alignment process with magnetic nanoparticles under a magnetic field. The enhanced alignment has been illustrated from the distribution of azimuthal intensity in the samples exposed to magnetic field. Molecular dynamics simulations reveal the relationship between the imposed force of the magenetic nanoparticles under magnetic field and the force transferred to the LLC cylinders which leads to the LLC alignment. The combinational study with experimental measurement and computational simulation will enable the development and control of nanostructures in novel materials for various applications.

Currently, companies and SMEs (small and medium enterprises) are looking to be more competitive. In order to achieve this, they are adopting new business models and strategies that allow them to move towards sustainability. Strategies such as CSR (Corporate social responsibility) and supply chain management have become essential for ensuring a company’s permanence and financial consolidation. The literature has stated that the theories of Stakeholders and Sustainability are fundamental pillars for the development and sustained growth of business. The purpose of this article is to examine the effects of CSR and the SC (supply chain) on innovation, image and reputation, and in turn, their influences on profitability in SMEs. This research is based on a sample of 143 companies in the city of Guaymas Sonora, in Mexico. For the analysis and validation of the results, we used the SEM (Structural Equation Modeling) statistical technique based on the variance, through PLS (Partial Least Squares) (using SmartPLS version 3.2.6 Professional). The findings show that SMEs that develop social and sustainable practices increase their level of innovation, and improve their image, their reputation, and their financial profitability. This work contributes mainly to the development of Stakeholders and Sustainability.

The regulation of hepatic very-low-density lipoprotein (VLDL) secretion plays an important role in the pathogenesis of dyslipidemia and fatty liver diseases. VLDL is controlled by hepatic microsomal triglyceride transfer protein (MTTP). Mttp is regulated by carbohydrate response element binding protein (ChREBP) and small heterodimer partner (SHP). However, it is unclear whether both coordinately regulate Mttp expression and VLDL secretion. Here, adenoviral overexpression of ChREBP and SHP in rat primary hepatocytes induced and suppressed Mttp mRNA, respectively. However, Mttp induction by ChREBP was much more potent than suppression by SHP. Promoter assays of Mttp and the liver type pyruvate kinase gene revealed that SHP and ChREBP did not affect the transactivity of each other. Mttp mRNA and protein levels of Shp^/– mice were similar to those of wild-type; however, those of Chrebp^–/–Shp^–/– and Chrebp^–/– mice were much lower. Consistent with this, the VLDL particle number and VLDL secretion rates in Shp^–/–- mice were similar to wild-type, but were much lower in Chrebp^–/– and Chrebp^–/–Shp^–/–- mice. These findings suggested that ChREBP rather than SHP regulates VLDL secretion and that ChREBP and SHP do not affect the transactivities of each other.

The development of small scale hydroelectric power plants in Norway is determined by natural conditions, policies, attitudes and property rights. The owner of the river is the central decision maker. It is he who decides whether he will develop the power plant himself, Whether he wants to enter into a contract with an external investor and let him develop the power plant, whether he will sell his property rights or postpone the decisions. All available choices will involve risk. In order for him to make the best choice he must find the certainty equivalent to each of the choices and choose the one with the highest certainty equivalent. This is the first time the utility theory of John von Neumann and Oskar Morgenstern has been applied to decision makers in the hydro power industry in Norway.

Adopting an immune response and tissue-based nomenclature in food allergies brings the field closer to precision and personalized medicine. An updated classification of non-IgE-mediated food hypersensitivity highlights mechanisms through a complex pathophysiological perspective and endotype-driven framework. This approach aligns with the essential goals of discovering new diagnostic and therapeutic biomarkers, enhancing the understanding of clinical presentations, and refining immunotherapy and targeted treatments, such as monoclonal antibodies and small molecule drugs, to improve patient management and quality of life. Endotype-focused and molecular-based decision-making also endows translational and clinical research, fostering the ongoing scientific quest for more innovative solutions.

An isolated system always evolves according to unitary evolution and maintain coherence. However the system inevitably interacts with the environment, information about the relative phases between the quantum states leaks into the environment and becomes delocalized, known as environment-induced decoherence. Here we consider the gravitational decoherence of a quantum system near the event horizon of a Schwarzschild black hole. We show that the gravitational decoherence is non-Markovian, which is consistent with information conservation and the Pagecurve-like entanglement dynamics. Moreover, taking the point of view that information on the collapsed matter is stored as the quantum fluctuation of the horizon, the horizon can be regarded as an “uncertain” quantum object instead of random fluctuations of graviton noise. Now the Hawking radiation bath plays the role of the environment, leading to the decoherence of the horizon. Therefore, information about the location of the horizon, or equivalently information about the collapsed matter, is carried away by the Hawking radiation. The memory time of the non-Markovian process and the Page time are estimated.

The study addressed the following questions: How does continuous lighting (CL) im-pact plant physiology, photosynthetic and stress response? Does the impact of CL de-pend on the source of light and other environmental factors (natural vs artificial)? Do responses to CL differ for native and non-native plant species in the Subarctic and, if differences exist, what physiological reasons might they be associated with? Experi-ments were conducted with three native to Subarctic (Geranium sylvaticum L., Geum rivale L., Potentilla erecta (L.) Raeusch.) and three non-native plant species (Geranium himalayense Klotzsch, Geum coccineum Sibth. & Sm., Potentilla atrosanguinea Loddiges ex D. Don) introduced in Polar-Alpine Botanic Garden (KPABG, 67°38′N). Obtained re-sults have shown that plants lack specific mechanisms of tolerance to CL. Protective responses are non-specific and induced by developing photo-oxidative stress. In cli-mate chambers under constant environmental conditions artificial CL causes leaf inju-ries due to oxidative stress, the main cause of which is circadian asynchrony. In nature plants are not photodamaged during the polar day as endogenous rhythms are main-tained due to daily fluctuations of several environmental factors (light intensity, spec-tral distribution, temperature and air humidity). The obtained data show that among possible non-specific protective mechanisms, plants use flavonoids to neutralize excess ROS generated under CL. In local subarctic plants, their photoprotective role is signif-icantly higher than in non-native introduced plant species.

Introduction After the first use of infliximab in Crohn’s disease in 1995, the wide scale introduction of anti-tumour necrosis factor alfa (anti-TNF alfa) medications revolutionized the treatment of inflammatory bowel diseases (IBD’s). During the last two decades an increased number of molecules with multiple mechanisms of action were approved for the treatment of IBD with substantial increase of the costs of related to therapy. The increasing costs and access to therapy became a concern of payers and regulators but also for healthcare professionals. Biosimilars are biologic medical products that are highly structurally identical to their reference products and without any clinically meaningful differences in immunogenicity, safety or effectiveness. The introduction of biosimilars was seen as a way to provide a lower-cost alternative to the originator anti-TNF molecules and hence to increase treatment access and availability for patients. Material and methods This an observational, prospective study conducted in two IBD centers in Bucharest. The study included 53 patients, 27 male(M) and 26 female(F), diagnosed with UC or BC according to standard clinical,endoscopic, radiological, histological criteria that were non medically switched to a biosimilar. All patients completed at least the induction treatment with the originator adalimumab and they were clinically stable. After switch they received one of the market available biosimilars of Adalimumab(Hukyndra, Imraldi or Hyrimoz). For each patient, the following data were collected: age, sex, BC or UC diagnosis, previous and current therapy, clinical evolution, endoscopic scores as well as several biological markers. Aim The primary objective was the maintenance of clinical remission at twelve months after switching the original Adalimumab treatment to the biosimilar Adalimumab. The secondary objectives were to evaluate the presence of adverse effects and the treatment persistence at one year. Results In our population, there were 42 patients with Crohn's disease and 11 with ulcerative colitis who switched from the originator adalimumab to a biosimilar Adalimumab. The average age was 44,07 years old for patients with BC and 51,72 years old for patients with UC. No significant differences were found in terms of CF and CRP levels at 6 and 12 months after changing the originator biologic treatment to a biosimilar. Only one patient required changing the biological treatment, following the clinical and biological loss of response. The main adverse effect reported by patients was pain at the injection site. Of the 53 patients, only 2 patients reported pain at the injection site, but this was considered not significant because the patients had a BMI below 20 and they also reported the same symptom when administering the originator. One patient reported experiencing abdominal pain and rectal bleeding immediately after switch, but no recurrence was observed clinically and endoscopically. Conclusion: This observational study is the first carried out in Romania that shows that the after the non-medical switch, biosimilars of Adalimumab were as efficient as the originator Adalimumab in the clinical practice of patients with IBD. These results support that conclusion that the large-scale use of biosimilars does not significantly affect the effectiveness of the therapy and the safety of the patient.

Assessing the quality of corn seeds necessitates evaluating their content of water, fat, protein, and starch. This study integrates hyperspectral imaging technology with chemometric analysis techniques to achieve non-invasive and rapid detection of multiple key components in corn seeds. Hyperspectral images of the embryo surface of maize seeds were collected within the wavelength range of 1100~2498nm. Subsequently, image segmentation techniques were applied to extract the germ structure of the corn seeds as the region of interest. Seven spectral data preprocessing algorithms were employed, and the Detrending Transformation (DT) algorithm was identified as the optimal preprocessing method through comparative analysis using the Partial Least Squares Regression (PLSR) model. To reduce spectral redundancy and streamline the prediction model, three algorithms were employed for characteristic wavelength extraction: Successive Projections Algorithm (SPA), Competitive Adaptive Reweighted Sampling (CARS), and Uninformative Variable Elimination (UVE). Using both the original spectra and the extracted characteristic wavelengths, four content detection models were constructed: PLSR, Back Propagation Neural Network (BPNN), Radial Basis Function Neural Network (RBFNN), and Least Squares Support Vector Machine (LSSVM). The experimental results demonstrate that the DT-CARS-LSSVM model exhibits exceptional accuracy and stability in predicting these four key components, with determination coefficients of 0.9877, 0.9344, 0.9827, and 0.9592, respectively. This study not only provides a scientific basis for evaluating the quality of corn seeds but also opens up new avenues for the development of non-invasive detection technology in related fields.

This work presents the study of a reproducible acoustic emission method based on the launching of a metallic sphere and low-cost piezoelectric diaphragm. For this purpose, tests were first conducted on a carbon fiber-reinforced polymer structure, and then on an aluminum structure for comparative analysis. The Pencil Lead Break (PLB) tests were also conducted for comparisons with the proposed method. Different launching heights and elastic deformations of the structures were investigated. The results show higher repeatability for the sphere impact method, as the PLB is more affected by human inaccuracy, and it was also effective in damage detection.

In the last decade, the application of non-Saccharomyces yeasts in oenology as a natural tool to obtain wine diversification and higher quality has aroused great interest. In this work, three M. pulcherrima strains, isolated from vineyard, were characterized through the evaluation of their main technological properties, antimicrobial activity and specific enzymatic activities (β-glucosidase, β-lyase, polygalacturonase and protease). The M. pulcherrima strains did not produce any inhibition against S. cerevisiae, while they were able to exert an antimicrobial action against some unwanted bacteria and yeasts frequently present in grape must and potentially causing alteration of wines. After this preliminary screening, M. pulcherrima AS3C1 has been selected to be used in the winemaking of red grape Vitis vinifera cv. Aglianico on a pilot scale. The effect of sequential inoculation of M. pulcherrima AS3C1 with a commercial strain of Saccharomyces cerevisiae was verified using for comparison a single inoculum with S. cerevisiae and a spontaneous fermentation. Our results showed a higher concentration of anthocyanins and catechins in wines obtained by sequential inoculation of M. pulcherrima AS3C1 and S. cerevisiae. On the basis of the data obtained, M. pulcherrima AS3C1 possesses an enzymatic profile and some oenological properties that could contribute positively to the definition of the chemical composition of wines, suggesting its possible use for red winemaking processes.

The following article analyses the relationship between Non-Performing Loans and innovation systems at a global level. The analysed data were obtained from the World Bank and the Global Innovation Index for the period 2013-2022 for 149 countries. The analysis was conducted using clustering with the k-Means algorithm, optimized with the Silhouette coefficient and the Elbow method. Subsequently, econometric analysis was carried out using panel data with Random Ef-fects and Fixed Effects. The clustering results show that the optimal number of clusters is three. The econometric analysis highlights the positive relationship between Non-Performing Loans, the exports of cultural and creative services, and the Innovation Input Sub-Index. The results also show the negative relationship between Non-Performing Loans, the H-Index, and the exports and imports of ICT services.

Background: Approximately 10-20% of subjects vaccinated with HBsAg-based hepatitis B virus (HBV) vaccines are non-responders. BM32 is a recombinant grass pollen allergy vaccine containing the HBV-derived preS surface antigen as immunological carrier protein. PreS includes the binding site of HBV to its receptor on hepatocytes. We investigated if immunological non-responsiveness to HBV after repeated HBsAg-based vaccinations can be overcome by immunization with VVX001 (i.e., Alum-adsorbed BM325, a component of BM32). Methods: A subject failing to develop protective HBV-specific immunity after HBsAg-based vaccination received five monthly injections of 20 µg VVX001. PreS-specific antibody responses were measured by ELISA and micro-array technology. Serum reactivity to subviral particles of different HBV genotypes was determined by sandwich ELISA. PreS-specific T cell responses were monitored by CFSE staining and subsequent FACS analysis. HBV neutralization was assessed using cultured HBV-infected HepG2 cells. Results: Vaccination with VVX001 induced a strong and sustained preS-specific antibody response composed mainly of the IgG1 subclass. PreS-specific IgG antibodies were primarily directed to the N-terminal part of preS containing the NTCP attachment site. IgG reactivity to sub-viral particles as well as to the N-terminal preS-derived peptides was comparable for HBV genotypes A-H. A pronounced reactivity of CD3+CD4+ lymphocytes specific for preS after the complete injection course remaining up to one year after the last injection was found. Maximal HBV neutralization (98.4%) in vitro was achieved 1 month after the last injection which correlated with the maximal IgG reactivity to the N-terminal part of preS. Conclusion: Our data suggest that VVX001 may be used as a preventive vaccination against HBV even in non-responders to HBsAg-based HBV vaccines.

Federated learning is an effective approach for preserving data privacy and security, enabling machine learning to occur in a distributed environment and promoting its development. However, an urgent problem that needs to be addressed is how to encourage active client participation in federated learning. The Shapley Value, a classical concept in cooperative game theory, has been utilized for data valuation in machine learning services. Nevertheless, existing numerical evaluation schemes based on the Shapley Value are impractical as they necessitate additional model training, leading to increased communication overhead. Moreover, participants’ data may exhibit Non-IID characteristics, posing a significant challenge to evaluating participant contributions. Non-IID data weakens the marginal effects of participants, which in turn affects model accuracy and leads to underestimated contribution measurements. Current works often overlook the impact of heterogeneity on model aggregation. This paper presents a fair federated learning contribution measurement scheme that addresses the need for additional model computations. By introducing a noval aggregation weight, it enhances the accuracy of contribution measurement. Experiments on the MNIST dataset show that the proposed method can accurately compute the contributions of participants. Compared to existing baseline algorithms, the model accuracy is significantly improved, with a similar time cost.

Equine herpesvirus-1 (EHV-1) causes respiratory diseases, abortion, and encephalomyelitis in horses. EHV-1 immediate-early (IE) protein, essential for viral replication, is transactivated by the binding of a multiprotein complex including the open reading frame 12 (ORF12) and some host factors to the IE promoter region. Promoter-associated non-coding RNAs (pancRNAs), which are transcribed from bidirectional promoters, regulate the transcription of neighboring genes in mammals and pathogens. In this study, we identified a novel pancRNA transcribed from across the areas of the 5’-untranslated region and promoter of EHV-1 IE and named it IE pancRNA. IE pancRNA and mRNA were simultaneously expressed in EHV-1-infected RN33B-A68B2M cells. This pancRNA was also transcribed in RK13 and E. Derm cells, which are highly susceptible to EHV-1 infection. Furthermore, IE pancRNA upregulated IE gene expression in the presence of ORF12, and stable expression of IE pancRNA increased the number of EHV-1-infected RN33B-A68B2M cells. These results suggest that IE pancRNAs facilitate EHV-1 proliferation by promoting IE gene expression.