Semi-autonomous vehicles (AVs) enable drivers to engage in non-driving tasks but require them to be ready to take control during critical situations. This "out-of-the-loop" problem demands a quick transition to active information processing, raising safety concerns and anxiety. Multimodal signals in AVs aim to deliver take-over requests and facilitate driver-vehicle cooperation. However, the effectiveness of auditory, visual, or combined signals in improving situational awareness and reaction time for safe maneuvering remains unclear. This study investigates how signal modalities affect driver’s behavior using virtual reality (VR). We measured drivers’ reaction times from signal onset to take-over response and gaze dwell time for situational awareness across twelve critical events. Furthermore, we assessed self-reported anxiety and trust levels using the Autonomous Vehicle Acceptance Model questionnaire. Results showed visual signals significantly reduced reaction times, whereas auditory signals did not. Additionally, any warning signal, together with seeing driving hazards, increased successful maneuvering. Analysis of gaze dwell time on driving hazards revealed that audio and visual signals improved situational awareness. Lastly, warning signals reduced anxiety and increased trust. These results highlight the distinct effectiveness of signal modalities in improving driver reaction times, situational awareness, and perceived safety, mitigating the “out-of-the-loop” problem and fostering human-vehicle cooperation.

African swine fever (ASF) continues to spread in Africa, Europe, Asia, and the island of Hispaniola increasing the need to develop more streamlined and highly efficient surveillance and diagnostic capabilities. One way to achieve this is by further optimization of already established standard operating procedures to remove bottlenecks for high-throughput screening. Real-time polymerase chain reaction (RT-PCR) is the most sensitive and specific assay available for the early detection of ASF, but it requires high quality nucleic acid extracted from the samples. Whole blood from live pigs and spleen tissue from dead pigs are the preferred samples for ASF RT-PCR. Whole blood can be used as is in nucleic acid extraction, but spleen tissues require an additional homogenization step. In this study, we compared the homogenates and swabs prepared from 52 spleen samples collected from pigs experimentally inoculated with highly and moderately virulent ASF virus strains. The results show that not only are the spleen swabs more sensitive when executed with a low-cell-count nucleic acid extraction procedure followed by RT-PCR assays, they also increase the ability to isolate ASFV from positive spleen samples. Swabbing is a convenient, simpler, and less time-consuming alternative to tissue homogenization. Hence, we recommend spleen swabs over tissue homogenates for high-throughput detection of ASFV by real-time PCR.

Background: Monitoring the mobility of players during wheelchair sports is essential to support coaches in their understanding of the activity and in their training programming. However, the amount of information available from the monitoring tools, combined with a general approach to processing and a poor presentation of the data to the coaches, is not effective and remains unused. Thus, this study aimed to propose a simple and efficient algorithm for identifying locomotor tasks (static, forward/backward propulsion, pivot/tight/wide rotation) during wheelchair movements based on wheelchair kinematic data. Methods: A total of 36 wheelchair tennis and badminton players participated, completing at least one of three proposed tests: the star test, the figure-of-eight test, and the forward-backward test. Locomotor tasks were identified using a five steps procedure including data reduction, symbolic approximation and pattern logical search. Results: Using this method, 99% of locomotor tasks were properly identified for the star test, 95% for the figure-of-eight test and 100% for the forward-backward test. Conclusion: This method appears to be a valuable tool for a simple and clear identification and representation of locomotor tasks over extended periods of time. Future research should aim at applying this method to multiple wheelchair court sports matches or daily life declination.

This article investigates and studies the current situation of implementing the credit system in ordinary high schools in Zhejiang Province, and puts forward relevant suggestions. Firstly, analyze the background and objectives of implementing the credit system in ordinary high schools in Zhejiang Province. Then, through a questionnaire survey method, a sample survey was conducted on the current status of the implementation of the credit system in ordinary high schools in Zhejiang Province. The results showed that there are some problems in the management of the credit system in schools, such as unreasonable credit course settings, inaccurate recording and statistics of credits, etc. Further analysis reveals that students and parents have biases and utilitarian motives in their understanding and evaluation of the credit system.

This study explores the inelastic doubly differential transverse momentum spectra of the primary charged particles, (π + + π − ), (K + + K − ) and (pp̄) as a function of underlying event √ (UE) at s = 13 T eV . The particle production is measured on the basis of different angular regions like toward, transverse and away, elucidated with respect to the direction of leading particle of an event. To study the thermal freeze-out parameters, the non extensive Tsallis distribution function is used, to extract the temperature Tef f , and chemical potential µ, which provides a basis to explain the QCD matter. The Tsallis distribution function clearly describes transverse momentum spectra in pseudorapidity region of |η| < 0.8. The best fit corresponds to minimum χ2 /ndf value for the transverse momentum distribution. It is observed that effective temperature Tef f changes from away to towards and forward region.

Digitalization plays a crucial role in improving the performance of chemical companies. In this context, different modeling, simulation, and optimization techniques like MILP, discrete-event simulation (DES), and data-driven (DD) models are being used. Due to their heterogeneity, these techniques must be executed individually, and holistic optimization is a manual and time-consuming process. We propose Benders decomposition to combine these techniques into one rigorous optimization procedure. The main idea is that heterogeneous models can simultaneously be optimized as Benders subproblems. We illustrate this concept with the distributed permutation flow shop scheduling problem (DPFSP) and assume that a MILP, DES, and DD model exist for three flow shops. Our approach can compute bounds and report gap information on the optimal makespan for five medium-sized literature instances. The approach is promising because it enables the optimization of heterogeneous models and makes it possible to build optimization capabilities on an existing model and tool landscape in chemical companies.

(1) Background: We aim to construct a machine learning (ML) algorithm to predict the risk of distant metastasis (DM) of T1 and T2gallbladder cancer (GBC); (2) Demographic and clinical pathological data of T1 and T2 GBC patients were extracted from the National Institutes of Health (NIH)’s Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015 to develop seven ML algorithm models. Models were evaluated based on accuracy, precision, recall rate, F1- score, and area under the receiver operating characteristic curve (AUC); (3) Results:A total of 4371 patients were included in the study, of whom 764 (17.4%) developed DM. Multivariate logistic regression showed that age, histology, tumor size, T and N stages were independent factors in GBC with DM. A novel nomogram was established to predict distant metastasis in early T stage GBC patients. Evaluation indicators of the best model Random Forest (RF) were as follows: accuracy (0.828), recall rate (0.862), precision (0.811), F1- score (0.836), and AUC value (0.913); (4) Con-clusions: The RF model constructed in this study could accurately predict distant metastasis in GBC patients, which may provide clinicians with more personalized clinical decision-making recom-mendations.

Background and objectives: Due to resistance and lack of treatment options, hospital-acquired Acinetobacter baumannii (A. baumannii) infections are associated with high mortality. The aim of this study was to identify the characteristics and outcomes of patients with infections caused by multidrug resistant A. baumannii in a tertiary-care teaching hospital and to determine the risk factors for in-hospital mortality. Materials and methods: A retrospective cohort study including 196 patients with A. baumannii strains isolated from different clinical specimens in the Hospital of the Lithuanian University of Health Sciences in 2016, 2017 and 2020, 2021 was conducted. Data on patients’ characteristics, comorbid diseases, treatment, length of hospital and ICU stay, outcome were collected. To determine risk factors for in-hospital mortality, logistic regression analysis was performed. Results: There were 60 (30.6%) women 136 (69.4%) men with a mean age of 61.7 ± 16.6 years (range, 52–74). More than three-fourths (76.5%, n = 150) of the patients had at least one comorbid disease. The highest number of A. baumannii strains were isolated from patients hospitalized in ICUs (43.4%, n = 85). A. baumannii strains producing three types of β-lactamases were more frequently isolated from women than men (77.8 % vs. 22.2%, p = 0.006). Infections caused by A. baumannii strains producing two types of β-lactamases were significantly more often treated with combination therapy than infections caused by strains producing one type of β-lactamase (78.9% vs. 60.0%, p = 0.019). Patients with A. baumannii strains producing two different types of β-lactamases (AmpC plus KPC, AmpC plus ESBL, or ESBL plus KPC) stayed significantly shorter at the ICU compared to patients with A. baumannii strains not producing β-lactamases (median of 9, IQR 2–18, vs. median of 26, IQR 7–38, p = 0.022). Death occurred in 58.7% (n = 115) of patients. Logistic regression analysis showed that combination therapy, length of hospital stay of < 10 days after A. baumannii infection, age of > 58 years, and absence of co-infection were independent predictors of in-hospital mortality. Conclusions: Patients with infection caused by A. baumannii strains producing two different types of β-lactamases were more frequently treated with combination therapy. Mortality of patients with multidrug resistant A. baumannii infection was high, and it was associated with patient’s age, length of hospital stay after the diagnosis of A. baumannii infection, absence of co-infection, and combination treatment.

In our recent publications pertaining to 4G model of final unification and based on strong and electroweak interactions, we have developed a completely new formula for estimating nuclear binding energy. With reference to currently believed Semi Empirical Mass Formula (SEMF), we call our formula as ‘Strong and Electroweak Mass Formula’ (SEWMF). Our formula constitutes 4 simple terms and only one energy coefficient of magnitude 10.1 MeV. First term is a volume term, second term seems to be a representation of free nucleons associated with electroweak interaction, third term is a radial term and fourth one is an asymmetry term about the mean stable mass number. Considering this kind of approach, nuclear structure can be understood in terms of strong and weak interactions and cold nuclear fusion like complicated concepts can be understood in a theoretical approach positively. In this paper, by considering the accountability of we are making an attempt to improve the applicability and effectiveness of SEWMF. Number 0.00125 being a workable electroweak coefficient for Z=6 to 132 and A=2Z to 3.5Z, number of free nucleons assumed to be associated with electroweak interaction can be expressed as Improved asymmetry term can be expressed as, where represents the light house like stable mass number. With reference to old version, our improved binding energy formula can be expressed as, We are working on its possible modification for mass numbers less than the stable mass numbers. Following this approach, it is possible to show that nuclear binding energy scheme is associated with strong and weak interactions and is practically independent of Coulombic repulsions. Proceeding further, currently believed cold nuclear fusion assumed be associated with hydrated metals can be understood and can be confirmed with strong and weak interactions independent of coulombic repulsions. We are very confident to say that our approach will certainly motivate modern science community in this new direction.

Increasing population size and income growth are causing and increasing demand for food and protein of animal origin. Insects are an interesting alternative to conventional animal source proteins as they can convert by-products from the agricultural industry to biomass for commercial feed for livestock and potentially as a food source for human consumption. Microorganisms have been found to affect insects and can be accumulated via horizontal and vertical transmission. This study aimed to identify if the removal of egg- and substrate-associated microorganisms impact larval performance through the following parameters: development of biomass, final biomass, and the survival rate of house fly (Musca domestica) larvae. Four treatments were tested on substrate consisting of 10.81% alfalfa (Medicago sativa), 21.62% wheat bran (Triticum aestivum), and 67.57% water: (A) disinfected eggs and non-autoclaved substrate, (B) non-disinfected eggs and autoclaved substrate, (C) disinfected eggs and autoclaved substrate, and (D) a control without any removal of microbiota. The results showed a significant decrease in final biomass for the treatments with only disinfected eggs, only autoclaved substrate and both when comparing to the control, and a significant decrease in survival rate for B and D. Moreover, the development of biomass showed a significant difference between days within all treatments. Together this suggest that microorganisms of housefly eggs and the growth substrate plays an important role for growth, which is critical in commercial insect production. Further studies must be performed to examine these parameters in more commercially relevant substrates.

This paper presents a demonstration of a linearly-polarized transmit-arrays antenna with high-efficiency and wideband operating in X-band. The topology of the unit cell consists of two identical patch antennas loaded by C-loop slot and interconnected by a metalized via through a ground plane sandwiched between two identical substrates [18]. A waveguide measurement system WGMS has been used for single cell characterization (reflection/transmission coefficients). Good results have been demonstrated in terms of matching performances; the reflection coefficient S11 is under 10-dB in the 9.4-10.4 GHz band (i.e. 10.1% around 9.9 GHz) and with only 0.35 dB-insertion loss at 10 GHz. The transmit-arrays prototype permitted to achieve 22.4 dBi of directivity and 20.1 dBi of gain. The aperture and radiation efficiencies are about 28.2% and 58.3%, respectively. With a focal ratio (F/D) of 1/2 the spill-over loss is less than 2 dB. Beam-scanning up to ± 35° has been achieved with the same phase quantization (passive) and less than 3 dB of gain losses.

Acute myeloid leukemias are characterized by genetic alterations that lead to a complete or partial block at various stages of myeloid differentiation, leading to continual proliferation of myeloid progenitor cells. These alterations can include a well-documented chromosomal translocation that leads to the synthesis of the PML-retinoic acid receptor fusion protein that leads to a block in differentiation and the ability to induce differentiation with all-trans retinoic acid and other small molecules. In essence, in large part, the disease is due to stem cell-like cells that are blocked in their ability to undergo terminal differentiation to more mature, non-proliferative cell types. We discovered a long non-coding RNA (lncRNA), lncRNAp53int1, encoded from the first intron of the p53 tumor suppressor gene. Interestingly, lncRNAp53int1 appears to play an important regulatory role in maintaining the undifferentiated and proliferative state in a manner independent from p53 gene expression. lncRNAp53int1 is expressed at high levels in proliferating, undifferentiated promyelocytes and its levels fall significantly during their terminal differentiation to non-proliferating granulocytes or macrophages. Furthermore, forced overexpression of lncRNAp53int1 blocks terminal differentiation. The observation that the expression of this lncRNA is repressed during terminal differentiation of human leukemic cells and its expression blocks differentiation of leukemic myeloid progenitor cells, is likely to have clinical implications with regards to differentiation therapy for myeloid leukemia. Ongoing research aims to identify the molecular partners that it associates with and the signaling pathways that this lncRNA participates in with the long-term goal of identifying molecules that inhibit lncRNAp53int1 activity and serve as potential therapeutic drugs. The goal of this mini-review is to disseminate these novel and interesting findings to readers and to describe where we think this research is headed and the impact it can have on myeloid leukemias.

Urban ultra-low altitude airspace (ULAA) presents unique challenges for unmanned aerial vehicle (UAV) path planning due to high building density and regulatory constraints. This study analyzes and improves classical path planning algorithms for UAVs in ULAA. Experiments were conducted using A*, RRT, RRT*, and artificial potential field (APF) methods in a simulated environment based on building data from Chengdu City, China. Results show that traditional algorithms struggle in dense obstacle environments, particularly APF due to local minima issues. Enhancements were proposed: a density-aware heuristic for A*, random perturbation for APF, and a hybrid optimization strategy for RRT*. These modifications improved computation time, path length, and obstacle avoidance. The study provides insights into the limitations of classical algorithms and suggests enhancements for more effective UAV path planning in urban environments.

Artificial intelligence (AI) driven language models have seen a rapid rise in development, deployment, and adoption over the last few years. This surge has sparked many discussions about their societal and political impact, including political bias. Bias is a crucial topic in the context of large models due to its far-reaching consequences on technology, politics, and society. It significantly influences public perception, decision-making, political discourse, and AI policy governance and ethics. This study investigates political bias through a comparative analysis of four prominent AI models: ChatGPT-4, Perplexity, Google Gemini, and Claude.Through a comprehensive analysis by systematically and categorically evaluating their responses to politically and ideologically charged tests and prompts, utilizing the Pew Research Center’s Political Typology Quiz, the Political Compass assessment, and ISideWith political party quiz, this study identifies significant ideological leanings and the nature of political bias within these models. The findings revealed that ChatGPT-4 and Claude exhibit a liberal bias, Perplexity is more conservative, while Google Gemini adopts more centrist stances. The presence of such biases underscores the critical need for transparency in AI development and the incorporation of diverse training datasets, regular audits, and user education to mitigate these biases. This analysis also advocates for more robust practices and comprehensive frameworks to assess and reduce political bias in AI, ensuring these technologies contribute positively to society and support informed, balanced, and inclusive public discourse, which will point towards neutrality.The results of this study add to the ongoing discourse about the ethical implications and development of AI models, highlighting the critical need to build trust and integrity in AI models. Additionally, future research directions have been outlined to explore and address the complex issue of bias in AI.

This study explores advanced feature engineering and semantic enrichment methods to enhance text classification, focusing on detecting figurative language in tweets. The novel features introduced, Syno\_Lower\_Mean and Syn\_Mean, measure the use of uncommon synonyms and the mean frequency of synonyms, capturing semantic richness crucial for detecting figurative expressions. Using resources like SenticNet and Framester, we enrich our feature set with sentiment and frame semantic information. Our approach includes extensive data preprocessing, sophisticated feature selection, and implementing various classification models, such as SVM, KNN, Logistic Regression, Decision Trees, Random Forest, BERT, and LSTM networks. We rigorously evaluate each model's performance to assess the effectiveness of our features and enrichment methods. Putting emphasis on model explainability, we use decision tree analysis, feature importance analysis, and the TREPAN algorithm to approximate SVM decisions. Although we focus on figurative language detection, our methods have broader implications for various NLP text classification tasks. Our findings demonstrate significant improvements in classification accuracy and interpretability through innovative feature design and dataset enrichment.

Background: Accidental caustic burns of the esophagus in children represent a significant global health challenge, often necessitating esophageal reconstruction. The aim of this study is to compare the efficacy and morbidity related to esophagus replacement with colonic and gastric tube transplants in a pediatric population followed for caustic stenosis. Method: This retrospective study was conducted at a tertiary pediatric surgery unit for children treated from January 1989 to December 2022. We compared colonic and gastric tube esophageal replacement. Short-term (within 30 days) and mid-term outcomes and complications were reviewed. Statistical evaluation was considered using a Chi-square test for categorical data analysis. Results: A total of 124 children with caustic esophageal burns were included. Among them, 23 (18.5%) had a gastric tube transplant for esophagus replacement and 101 (81.5%) a colonic transplant. During surgical intervention, we found a significantly higher risk of complications when using a colonic transplant (34%, p < 0.001). There was no significant statistical difference in postoperative short-term and mid-term complications between the two techniques. Twenty-six (26%) of the children required a reoperation, with a higher risk in the gastric tube transplant group (p < 0.001). Endoscopic dilatation after surgery was also performed on a higher number of children who had received a gastric tube transplant (p = 0.005). Overall, 97.6% recovered full normal oral feeding. Conclusions: We found that colonic and gastric tube replacement are both good options for pediatric esophageal replacement after a caustic injury and show effectiveness over time. Gastric tube transplants carried a slightly higher risk of reoperations and a higher number of dilatations post-surgery. However, our groups are not really comparable due to the much higher number of colonic transplants. Both surgical options have to be considered during surgery and the choice depends on the anatomy of the patient. Our future research will focus on assessing long-term quality of life and potential risk of neoplastic complications.

Oral drug absorption is the primary route for drug administration. However, this process hinges on multiple factors, including the drug’s physicochemical properties, formulation characteristics, and gastrointestinal physiology. Given its intricacy and the exorbitant costs associated with experimentation, the trial-and-error method proves prohibitively expensive. Theoretical models have emerged as a cost-effective alternative by assimilating data from diverse experiments and theoretical considerations. These models fall into three categories: data-driven models, encompassing classical pharmacokinetics, quantitative-structure models (QSAR), and machine/deep learning. Mechanism-based models include quasi-equilibrium, steady-state, and physiologically based pharmacokinetics, alongside first principles such as molecular dynamics and continuum models. This review provides an overview of recent modeling endeavors across these categories, evaluating their respective advantages and limitations. Additionally, a primer on partial differential equations and their numerical solutions is included in the supplementary materials, recognizing their utility in modeling physiological systems despite their mathematical complexity limiting their widespread application in this field.

Vitronectin is a glycoprotein, present in plasma and extracellular matrix, implicated in cell migration. The high amount of vitronectin found in neuroblastoma biopsies was associated with poor prognosis. However, there are almost no studies of vitronectin levels in neuroblastoma cell culture media nor in plasma of neuroblastoma patients. Vitronectin concentration in culture media of four neuroblastoma cell lines grown in monolayer and in 3D-models, and in plasma of 114 neuroblastoma patients, was quantified using ELISA. Three of the neuroblastoma cell lines secreted vitronectin to culture media when cultured in monolayer and 3D-models. Vitronectin release was higher by neuroblastoma cells cultured in 3D-models than in monolayer, and was still great when cells grown in 3D-scaffolds with cross-linked vitronectin. Vitronectin secretion occurred independently of cell numbers in cultures. Its concentration in plasma of neuroblastoma patients ranged between 52.4 and 870µg/mL (median, 218µg/mL). A ROC curve was used to establish a cutoff of 361µg/mL, above which patients over 18-months-old had worse prognosis (p=0.0018). Vitronectin could be considered a new plasma prognostic biomarker in neuroblastoma, and warrants confirmation in collaborative studies. Drugs inhibiting vitronectin interaction with cells and/or extracellular matrix could represent a significant improvement in survival for neuroblastoma patients.

The article presents the results of the technical-economical study regarding the optimization of the FDM parameters (Lh – the height of the layer deposited in one pass and Id – the filling percentage) for the manufacture of PETG and ASA parts. To carry out the technical-economical study, we used the fundamental principle of value analysis, which consists in maximizing the ratio between Vi/Cp, where Vi - represents the mechanical characteristic, and Cp - represents the production cost. The results of the study show that for the tensile specimens made of PETG, the parameter that significantly influences the results of the Vi/Cp ratios is Lh, and in the case of the compression specimens made of PETG, the parameter that significantly influences the results of the Vi/Cp ratios is Id. In the case of specimens manufactured by FDM from ASA, the parameter that decisively influences the results of the Vi/Cp ratios of the tensile and compression specimens is Id – the filling percentage. By performing optimization of the process parameters with multiple responses, we identified the optimal parameters for FDM manufacturing of parts from PETG and ASA: Lh = 0.20 mm and Id = 100%.

Present experimental study assesses the mechanical properties of glass/carbon/glass hybrid composite laminates after exposure to moisture and elevated temperatures for extended periods. The top and bottom layers of the hybrid laminates are glass fiber reinforced and the middle layer is carbon fiber reinforced with the matrix specified as a polymer material. The hybrid laminates were manufactured using the resin transfer molding method and their compressive and tensile properties were determined using a tensile testing machine. The material parameters such as the storage modulus, the loss modulus, and the damping factors of the laminates were identified using dynamic mechanical analysis as a function of the temperature and the vibration frequency. The experimental results on compressive and tensile properties revealed slight variations when the hybrid laminates were kept at low temperatures for extended periods. This might occur due to the increasing molecular cross-linking of the polymer network. As the temperature increased, compressive, tensile, storage modules, loss modulus, and damping factors decreased. This might occur due to the increasing mobility of the binder material. Particularly, the highest stiffness parameters were obtained on -80°C/GCG (Glass/Carbon/Glass) laminates due to the presence of beta transition on the glassy region. The relationships between the glass transitions and the targeted frequencies were characterized. The values of the glass transition shift towards higher temperatures as the frequency increases. This might occur due to a reduction in the gaps between the crosslinking of the epoxy network when the frequency increases. The accuracy of the storage modulus results was compared with the empirical models. The model based on the Arrhenius law provided the closest correlation. Meanwhile, another model was observed that was not accurate enough to predict when gamma and beta relaxations occur under a glassy state.

The metabolites secreted by probiotics or released after their lysis are called postbiotics. They provide physiological benefits to the host, preventing the colonisation of pathogens by improving the intestinal environment for beneficial commensal bacteria, which reduces the incidence of digestive disorders and improve the immune system. The aim of this work was to evaluate the addition of postbiotics to dairy cow rations during the transition period on nutrient digestibility, composition, and milk yield. The effects of two postbiotics were evaluated in twelve Friesian cows from 30 days before calving to two months of lactation. The animals were randomly allocated to the treatments control (CT) and supplemented with postbiotics (PC and PR). Feeding was ad libitum with 60/40 of forage/concentrate ratio. Daily feed intake and milk production were recorded individually throughout the study. Two digestibility balances were performed, one before parturition and one after parturition. Colostrum was sampled at first milking and milk was sampled weekly. Data were analysed using a mixed mode in R software. The results suggest that postbiotic supplementation in late gestation and early lactation increase the voluntary intake of dry matter, especially in the PR treatment, with higher apparent total tract digestibility of dry matter, organic matter and neutral detergent fiber. Both treatments including postbiotics induced an increase in colostral immunoglobulin concentration. Milk production of cows receiving the PC treatment was the highest, with high fat and protein yields and a higher persistence of the production curve throughout the lactation.

Oral mucositis (OM) is one of the common adverse events associated with cancer treatment that decreases quality of life and affects treatment outcome. However, the medications used to manage OM are generally only palliative, and our knowledge of the syndrome is limited. The etiology of the syndrome is thought to be complex and multifactorial. We investigated the trends and characteristics of OM and estimated molecular initiating events (MIEs) associated with the development of the syndrome using FDA Adverse Event Reporting System. The study of trends and characteristics suggested that OM is significantly more likely to occur in females and nonelderly patients and is likely to be induced by protein kinase inhibitors such as afatinib and everolimus. Next, we used Toxicity Predictor, an in-house quantitative structure–activity relationship system, to estimate OM-associated MIEs. The results revealed that agonist activity of human pregnane X receptor, thyroid-stimulating hormone-releasing hormone receptor, and androgen receptor may be associated with OM development. Our study findings are expected to help avoid the risk of OM induction during the drug discovery process and clinical use of antineoplastic agents.

Between 2019 and 2023, sixteen universities increased their research output by more than fifteen times the global average, alongside significant changes in authorship dynamics (e.g., decreased first authorship, increased numbers of hyperprolific authors, increased numbers of multiaffiliations, and increased numbers of authors per publication). Using bibliometric methods, this study detected patterns suggesting a reliance on unconventional authorship practices, such as gift, honorary, and sold authorship, to inflate publication metrics. This study underscores the need for reforms by universities, policymakers, funding agencies, ranking agencies, accreditation bodies, scholarly publishers, and researchers to maintain academic integrity and ensure the reliability of global ranking systems.

This study introduces a novel method that combines Generative Adversarial Networks (GANs) with conformal prediction to revolutionize the domain of stock ticker forecasting. Our approach enhances prediction accuracy and offers dependable prediction intervals to gauge uncertainty, surpassing current GAN-based techniques in unpredictable market scenarios. We made a validation using AAPL stock data, showing the ability of our model to generate accurate forecasts and reliable assessments of prediction uncertainty. The prediction intervals generated provide investors and risk managers with a powerful tool to make informed decisions. Our approach represents a notable advancement in financial prediction as it improves the clarity and reliability of forecasts. By incorporating conformal prediction into the GAN framework, the reliability of forecasts is improved, providing a thorough evaluation of uncertainty that is crucial for successful risk management. This framework has the potential to transform the field of predictive analytics in finance. It shows a solution that balances accuracy and uncertainty quantification. The results clearly show the effectiveness of this method, paving the way for its potential application in a wide range of financial prediction scenarios.

Methylene blue has been electropolymerized on the surface of a stainless steel 316. The addition of sodium oxalate and working at a pH near 11 has allowed to obtain steel electrodes coated with electroactive polymer. This polymer shows electrochromic properties similar to those of the monomer, but also appears electroactivity at more positive potentials which is associated to the active centers in the bridges between monomeric units. The study by means of digital video electrochemistry has allowed on the one hand, to quantify the color changes on the entire surface of the stainless steel simultaneously and by means of the mean color intensities to separate the contribution to the overall polymer response of the active centers of the phenothiazine ring and of the inter-monomer bonds. A reduction mechanism for the polymer compatible with the pH variation of the observed electrochemical behavior is proposed.

This study builds on our previous Systematic Literature Review (SLR) that assessed the applications and performance of zk-SNARK, zk-STARK, and Bulletproof Non-Interactive Zero-Knowledge Proof (NIZKP) protocols. To address identified research gaps, we designed and implemented a benchmark comparing these three protocols using a dynamic MiMC hash application. We evaluated performance across four general-purpose programming libraries and two programming languages. Our results show that zk-SNARK produced the smallest proofs, while zk-STARK generated the largest. In terms of proof generation and verification times, zk-STARK was the fastest, and Bulletproof the slowest. Interestingly, zk-SNARK proofs verified marginally faster than zk-STARK, contrary to other findings. These insights enhance our understanding of the functionality, security, and performance of NIZKP protocols, providing valuable guidance for selecting the most suitable protocol for specific applications.

Allopolyploidy in plants involves the merging of two or more distinct parental genomes into a single nucleus, a significant evolutionary process in the plant kingdom. Transcriptomic analysis provides valuable insights into the fate of duplicated genes, evolutionary novelties, and environmental adaptations exhibited by allopolyploid plants. However, transcriptome profiling is challenging due to genomic redundancy, which is further complicated by the presence of multiple chromosomes sets and the variations among homoeologs and allelic genes. Prior to transcriptome analysis, sub-genome phasing and homoeology inference are essential for obtaining a comprehensive view of gene expression. This review aims to clarify the terminology in this field, identify the most challenging aspects of transcriptome analysis, explain their inherent difficulties, and suggest reliable analytic strategies. Furthermore, bulk RNA-seq is highlighted as a primary method for studying allopolyploid expression, with an emphasis on the critical steps of read mapping and normalization in differential gene expression analysis.

Abstract: Currently, antibodies are major therapeutic modalities in biopharmaceutical research and development. Because of required high dose for certain clinical applications, antibodies are formulated at high protein concentration for convenience of administration, shipping and storage. We will describe the inter-molecular interactions that can occur in such a crowded environment of high protein concentration. Two types of repulsive interactions, i.e., electrostatic and excluded volume effects, and three types of attractive interactions, i.e., hydrophobic, electrostatic and cross-linking, need to be considered in such a crowded environments. We then show consequences of such inter-molecular interactions, leading to high viscosity, opalescence and phase separation of antibody solutions. Co-solvents are used to control the stability, structure and molecular interactions and thereby to alleviate these solution problems. Among various co-solvents, arginine has been extensively used to suppress protein-protein interactions at high protein concentration. Arginine weakly but extensively interacts with aromatic/hydrophobic groups as well as charged groups on proteins, leading to effective suppression of viscosity, opalescence and phase separation of antibody solution.

This study looked into how financial knowledge and entrepreneurial proficiency affected the performance of small, sustainable businesses. In parallel, we looked at how business resilience mediated the relationship between entrepreneurial proficiency and financial knowledge and long-term company success. Using an offline questionnaire, we employed a quantitative approach to gather data from 275 Indian small company owners. PLS-SEM was used to analyse the data that had been gathered. The findings show that resilience and entrepreneurial ability are very positively impacted by financial knowledge. The business resilience and sustainable performance of Indian SMEs are significantly enhanced by entrepreneurial competencies. Moreover, it was shown that business resilience moderated the influence of financial knowledge and proficiency on sustainable performance among Indian SMEs, while concurrently having a significant impact on sustainable performance. In keeping with India Vision of Viksit Bharat@2047: Crystal Gazing Through MSME Sector, which places a strong emphasis on entrepreneurship and the growth of a financially independent entrepreneurial community, this study helps to open up business options for regional business owners who oversee small businesses. According to the most recent figures (2021–2022) from the Ministry of Statistics & Programme Implementation, MSMEs make up a startling 29.15% of India’s GDP. This indicates their critical significance in the development of the country as it equates to a sizeable portion of the economic pie. In addition to adding to the corpus of knowledge, this research can help policymakers develop relevant plans to motivate SMEs that have been most negatively impacted by the COVID-19 pandemic to operate sustainably. There are also several other ramifications for financial institutions and business owners.

Salt marshes are highly dynamic and biologically diverse ecosystems that serve as natural habitats for numerous salt-tolerant plants (halophytes). We investigated the bacterial communities associated with the roots and leaves of plants growing in the coastal salt marshes of the Daphne Bay area in Alabama, United States. We compared external (epiphytic) and internal (endophytic) communities of both leaf and root plant organs. Using 16S rDNA amplicon sequencing methods, we identified 10 bacterial phyla and 59 different amplicon sequence variants (ASVs) at the genus level. Bacterial strains belonging to the phyla Proteobacteria, Bacteroidetes, and Firmicutes were highly abundant in both leaf and root samples. At the genus level, sequences of the genus Pseudomonas were common across all four sample types, with the highest abundance found in the leaf endophytic community. Additionally, Pantoea was found to be dominant in leaf tissue compared to roots. Our study revealed that plant habitat (internal vs. external for leaves and roots) was a determinant of the bacterial community structure. Co-occurrence network analyses enabled us to discern the intricate characteristics of bacterial taxa. Our network analysis revealed varied levels of ASV complexity in the epiphytic networks of roots and leaves compared to the endophytic networks. Overall, this study advances our understanding of the intricate composition of the bacterial microbiota in habitats (epiphytic and endophytic) and organs (leaf and root) of coastal salt marsh plants and suggests that plants might recruit habitat- and organ-specific bacteria to enhance their tolerance to salt stress.

In the context of modern healthcare, the concept of patient-centered care (PCC) has emerged as a crucial aspect, prompting the need for innovative frameworks to empower patients and enhance healthcare outcomes. This paper introduces the Patient-Oriented Medical Ontology Conceptual Framework (POMOCF), a powerful framework aimed at giving patients control over their personal and healthcare information. It prioritizes patient independence by allowing for direct control of electronic health records (EHRs) and facilitates the gathering of information through document upload or scanning. In the POMOCF front-end framework, we propose to maintain scalability, along with robust authorization, authentication, and secure data protocols, all of which are detailed within the framework. This approach enhances data accuracy and security, improving data management efficiency. As part of our ongoing development, we are planning to implement an innovative inference system that will automatically analyze and extract relevant details from the uploaded authorized document, provide real-time updates, and maintain data accuracy. This approach further strengthens data accuracy and prevents unauthorized modifications, thereby making the data management process more efficient. POMOCF leverages medical ontology principles to ensure standardized clinical concepts and improved semantic interoperability. Our integration plans involve integrating genotypic data for personalized medicine initiatives and strengthening the front-end infrastructure. By linking front-end interfaces with advanced technological solutions, we aim to provide effective healthcare delivery, promoting personalized care and enhancing patient outcomes.

Protein glycation impacts enzymatic activity, disrupts metabolic processes, and is associated with chronic degenerative diseases. The human glycolytic enzyme triosephosphate isomerase (HsTIM, TPI1, or HsTPI) is associated with various disorders, such as enzymopathies originating from mutations. It also possesses moonlighting functions and is now recognized as a cancer marker. Previous reports of HsTPI mutants have demonstrated a significant increase of methyl-glyoxal (MGO) due to trioses accumulation. We compared how catalytic activity exerts differen-tial kinetic and structural stability effects due to mutations by tracking fluorescent argpyrimi-dine adduct (ARGp) through interaction with Arginine-MGO. Circular dichroism and fluores-cence spectroscopy were explored in HsTPI-WT and mutants HsTPI-C217K “Like-WT”, HsTPI-N16D accumulated in cancer, and HsTPI-E104D human deficiency mutant, by cysteines accessibility and time loss of activity and unfolding propensity in mutant enzymes with aggre-gates refractory to proteolysis in the C217K. Our study sheds new light on the increased suscep-tibility of mutants to generate MGO adducts due to TPI isomerization of MGO precursor sub-strates. Nevertheless, mutations enhance a negative feedback cycle, in which accumulated MGO access promotes accelerated loss of activity that leads to unfolding and aggregation. The cumu-lative and accelerated increase in MGO adducts, which probably are responsible for the patho-logical state in this TPI variant, are partially reversed by adding MGO-scavenger molecules.

This paper presents a new optimization algorithm to control the voltage of power system generators by the simultaneous tuning of the parameters of Automatic Voltage Regulator (AVR) and Power System Stabilizer (PSS) using a new technique called Particle Swarm Optimization with Periodic Oscillating Exponential Decay (PSO - POED). The proposed algorithm was applied to both the Single-Machine Infinite-Bus (SMIB) Power System and the 9-Bus Multi-Machine Power System. The results of the simulation show that the proposed method is efficient and guarantees an improvement in the dynamic stability and convergence rate of the simulations.

Bicuspid Aortic valve Stenosis (BCAS) with an incidence of 3% of the world's population constitutes the most frequent Congenital Heart Disease whereas all other subtypes collectively constitute 1% of all life births. Most and the extreme severity spectrum of valvular Aortic Stenosis (VAS) in adulthood are cases of congenital bicuspid aortic valve. It seems that the congenital occurrence of the bicuspid aortic valve is a major prerequisite of the pathological calcifications and fibrosis seen in adults. Those progressive changes can't be explained by sole hemodynamic destructive forces but other factors inherent to the bicuspid valve tissue are also contributing. Therapeutic options of (VAS) are relatively stagnant and have been limited to invasive and surgical options. Prudent observation of the risk factors of some CHDs including BCAS was the epigenetic effect of planetary electromagnetic field on the delicate process of endothelial mesenchymal transformation (EndoMT). The incidence of BCAS is progressively increasing as we depart north from the equator to the north pole. A deeper understanding of the cellular and molecular mechanisms underlying EndoMT in congenital as well as acquired heart diseases is expected to open a new era in reversing heart disease in the human species. The potential to manipulate EndoMT and its signaling pathways or to reverse it with external electromagnetic power is an exciting therapeutic option for a wide array of congenital and acquired heart diseases including bicuspid aortic stenosis (BCAS) in the human species.

Fiscal control and monitoring of public management are issues of great importance and relevance, as they focus on preventing and mitigating corruption, thus benefiting governments in their management and performance, and thus citizens. Given the large amount of data involved in the management and functioning of a government, it is pertinent to apply data analysis methods to contribute to fiscal control. This paper aims to investigate data management for this purpose, starting with a bibliometric study to demonstrate the relevance and pertinence of the current study. It examines existing data collection techniques that may facilitate such control, data storage considering its nature and the possibilities that contribute to this end, and data processing through techniques that allow obtaining adequate information for further analysis and decision making. The necessary architecture and interoperability between systems is also discussed, as the existence of large amounts and types of data in governments makes it crucial to promote these practices for accurate and truthful analysis. Finally, data visualization is addressed since this topic is highly relevant as it allows for the identification of anomalies, where proper visualization promotes appropriate analysis and thus informed decision making. This work is useful for modern audit and fiscal control entities, since data capture, storage, processing, interoperability, and visualization are crucial elements that collectively enhance the ability to supervise public expenditure effectively, ensuring that public funds are managed with the highest standards of transparency, accountability, and efficiency.

Automatic emotion recognition using portable sensors is gaining attention due to its potential use in real-life scenarios. Existing studies have not explored Galvanic Skin Response and Photoplethysmography sensors exclusively for emotion recognition using nonlinear features with machine learning (ML) classifiers such as Random Forest, Support Vector Machine, Gradient Boosting Machine, K-Nearest Neighbor, and Decision Tree. In this study, we proposed a genuine window sensitivity analysis on a continuous annotation dataset to determine the window duration and percentage of overlap that optimize the classification performance using ML algorithms and nonlinear features, namely Lyapunov Exponent, Approximate Entropy, and Poincaré’s indices. We found an optimum window duration of 11 seconds and 16 seconds for valence and arousal, respectively, with 50% overlap, and achieved an accuracy of 0.76 in both dimensions. In addition, we proposed a Strong Labeling Scheme that kept only the extreme values of the labels, which raised the accuracy score to 0.92. Under certain conditions mentioned, traditional ML models offer a good compromise between performance and low computational cost. Our results suggest that well-known ML algorithms can still contribute to the field of emotion recognition, provided that window duration, overlap percentage, and nonlinear features are carefully selected.

The current study explores the impact of celebrity endorsements and social media platforms on promoting sustainable consumer behavior in Nigerian tourism industry. The study employs Mentionlytics software to analyze online documents and examine how political celebrities and social media platforms (Twitter and Facebook) influence consumer behavior and decision-making processes within the tourism industry. The findings in phase 1 suggest that celebrity endorsements and social media platforms have a positive impact on sustainable consumer behavior. The results in phase 2 suggest that political celebrities engage followers on Facebook based on the 70% share. However, no engagement was found on Twitter based on the zero percent (0%) share, suggesting that Facebook enables political celebrities to promote sustainable tourism. The study contributes to the literature on sustainability and celebrity endorsements, offering insights for destination marketers and policymakers in the Nigerian tourism industry.

The SI unit of length, the Metre, is presently defined by taking the fixed numerical value of the fundamental constant `c', the invariant speed of light in vacuum. This definition has the same physical basis as the previous definition, as the length of the path travelled by light in vacuum during a time interval of 1/299 792 458 of a second. With the atomic standard second defined in terms of the ground state hyperfine transition in Caesium-133, this definition is supposed to provide a universally reproducible standard of length. However, this relies on Einstein's singular postulate that the relative velocity of light in vacuum is an invariant constant that is independent of any inertial motion of the reference laboratory. I argue that the basis of the definition of the standard metre should be changed to the specific form, "the length of the path equal to the two-way propagation of light in vacuum during a time interval of 1/299 792 458 of a second", to be compatible and consistent with the fact that it is only the two-way relative velocity that is consistent with being an invariant. The null result in the Michelson-Morley two-way experiment, and in all such experiments to date, is consistent with a Galilean one-way propagation of light (relative velocity $c'=c\pm v$) as well as an invariant relative velocity of light. All practical methods and protocols related to the implementation of length standard involve also a two-way propagation, not conforming to the present definition. Besides, this redefinition is absolutely necessary because the relative velocity of light in one-way propagation is indeed Galilean, and not an invariant, as proved here in multiple ways including a direct experiment.

TThe locality condition of probabilities underpinning the derivation of Bell inequalities can be violated classically. The wave function collapse of an entangled state of single photons results in the factorization of quantum probabilities. It is possible to differentiate, locally, between ensemble probabilities of single detections with and without wave function collapse for the alleged quantum nonlocality. The theoretical concept of photonic quantum nonlocality cannot be implemented physically because of the quantum Rayleigh scattering of single photons. A distinction needs to be made between the correlation of individual, single measurements of pure states and the correlation of the measurement ensemble of the mixed states. The correlation operator of Pauli vector operators delivers the same probabilities of correlated detections of photons for both independent and multi-photon states as for ‘entangled’ states of photons. As single-photon sources are not needed, the design and implementation of quantum computing operations and other devices will be significantly streamlined. © 2024 The Author

The current study evaluated the effect of powder fractions based on particle size on the chemical composition of macronutrients such as proteins and sugars, on phytochemical properties (total content of polyphenolic compounds, vitamin C and antioxidant activity), on preservation capaci-ty (water activity), reconstitutability properties (water absorption capacity and water solubility index) and physicochemical properties (particle size distribution and moisture content) of black-thorn berries (Prunus spinosa) powders. The fruits were separated from the plant material and seeds, dried and then ground using a FRITSCH PULVERISETTE 19 universal mill for hard mate-rials. Eight fractions were obtained after sieving on seven sieves with different mesh sizes, such as: 1 mm, 0.8 mm, 0.630 mm, 0.450 mm, 0.315 mm, 0.200 mm, 0.125 mm. The grinding/sieving pro-cedure was effective in separating Prunus spinosa powder into sufficiently different size classes. The maximal moisture content and water activity were 5.61% and 0.250 respectively, show the good preservation from a microbiological point of view and ensure prevention the oxidation of bi-ologically active compounds of blackthorn berries powders. For samples with reduced particle sizes, reconstitutability was greatly improved. Total phenolic content, protein content, carbohy-drates and antioxidant activity showed significant improvements for some particle size classes compared to the unsieved sample. Vitamin C presented a semnificative content for the fraction with particle large sizes, precisely because they did not undergo intense degradation processes. Therefore, the technique of grinding and successive sieving proved effective in enhancing the physicochemical and functional characteristics of powdered blackthorn berries, particularly for smaller particles.

Bacillus cereus is a gram-positive bacterium widespread in the environment, especially in soil and dust. It produces two types of toxins causing vomiting and diarrhea. Nowadays, food borne outbreaks due to Bacillus cereus group bacteria (especially Bacillus cereus sensu stricto) are increased, as reported by European Food Safety Authority, representing a very huge problem in agri-food chain. In this work, we analyzed 118 strains belonging to Bacillus cereus group, isolated from several food sources (fruit and vegetables, dairy products, bakery products) concerning their susceptibility to antibiotics currently most used to treat infections. Many strains showing an intermediate susceptibility to clindamycin, erythromycin, and tetracycline were detected, suggesting an evolving acquisition of resistance against these antibiotics. Moreover, one strain showed intermediate resistance to meropenem, another antibiotic currently used to treat infections caused by Bacillus cereus. Beside the antimicrobial characterization, all strains were studied comparing their antimicrobic phenotype with the presence/absence of antimicrobial genes in their genome. The analysis showed a not complete correlation between genes carried by the strains and their phenotype, demonstrating that the antibiotic resistance is due not only to genetic factors, but also to other factors such as the inappropriate use of antibiotics that can determine an acquired resistance for bacteria.

The common house mosquito (Culex pipiens) is a native vector for West Nile virus (WNV). Invasive species like the tiger mosquito (Aedes albopictus) and Asian bush mosquito (Aedes japonicus) are rapidly spreading through Europe, posing a major threat as vectors for dengue, chikungunya (CHIKV), and Japanese Encephalitis virus (JEV). These mosquitoes share a similar ecological niche as larvae, but the carry-over effects of aquatic larval interactions to terrestrial adult stage remain largely unknown and their medical relevance requires further investigation. This study examines the context-dependency of larval interactions among Aedes albopictus, Aedes japonicus and Culex pipiens. The survival, development time, growth, and energetic storage were measured in different European populations within density-response experiments (intraspecific) and replacement experiments (interspecific) at 20°C and 26°C. Overall, Ae. japonicus was the weakest competitor, while competition between Ae. albopictus and Cx. pipiens varied with temperature. Culex pipiens was infected with WNV, Ae. albopictus with CHIKV and Ae. japonicus with JEV. While no JEV infection was observed, mosquitoes experiencing interspecific interactions during their larval stages exhibited higher infection rates and viral RNA titers for CHIKV and WNV. This increased susceptibility for viral infection after larval competition suggests a higher risk of arbovirus transmission in co-occurring populations.

Background/Objectives: Postoperative intraocular lens (IOL) is a risk associated with IOL scleral fixation. However, the cause of IOL tilt during IOL suturing remains unclear. Therefore, this study aimed to evaluate the surgical outcomes of a modified IOL suturing technique and investigate the factors contributing to postoperative IOL tilt and decentration. Methods: We included 25 eyes of 22 patients who underwent IOL suturing between April 2018 and February 2020. A modified IOL suturing technique that decreased the need for intraocular suture manipulation was used. Factors contributing to IOL tilt and decentration were investigated using an intraoperative optical coherence tomography (iOCT) system. Results: The mean postoperative best-corrected visual acuity improved from 0.15 ± 0.45 to -0.02 ± 0.19 (p = 0.02). The mean IOL tilt angle at the last visit after surgery was 1.84 ± 1.28 degrees. The study revealed that the distance of the scleral puncture site from the corneal limbus had a stronger effect on IOL tilt; while, the suture position of the haptics had a greater effect on IOL decentration. Conclusions: The modified IOL suturing technique, which avoids intraocular suture handling, had favorable surgical outcomes with improved postoperative visual acuity and controlled IOL tilt and decentration. Accurate surgical techniques and careful measurement of distances during surgery are crucial for preventing postoperative IOL tilt and decentration.

Background. The minimum wage has become a standard measure in economic and social policies of countries all over the world and it directly or indirectly affects between 20% and 30% of the labour force. The primary objective of this measure is to guarantee that workers receive a minimum wage that allows them to lead a decent life, thereby reducing inequality and poverty. However, studies on the minimum wage have not focused on assessing the effects on these dimensions, but on employment, anticipating a negative effect (in line with the traditional theory of perfect competition), which they have been unable to substantiate. Objectives and Methods. The objective of this study is to address this research gap by analysing the effects of minimum wage increases on income inequality and poverty. To this end, firstly, a systematic review of the empirical analyses was conducted using the PRISMA methodology, with a view to ensuring that all empirical evidence was available. Secondly, the Spanish case was examined. As the significant increase in minimum wage in Spain in 2019 (21,3% in real terms) presents an invaluable opportunity to utilise this event as a natural experiment to generate new evidence, a difference-in-differences approach was employed to assess the impact of this phenomenon. Results. In relation to the first objective, a number of non-exhaustive and outdated literature reviews have been identified, which have been subjected to a critical review. In addition, a total of 31 articles that empirically analysed this relationship in recent years (2020-2024) have been included. The available evidence indicates a clear inverse relationship between the minimum wage and inequalities and poverty. Regarding the Spanish case, there has been a dearth of scientific studies on this subject, particularly in the context of the significant increase observed in 2019, which makes this article of particular relevance. The results are statistically significant, demonstrating an increase of approximately 18% in annual gross income among low-income households, relative to the control group. Furthermore, there is evidence of a spillover effect and a lighthouse effect towards income groups closer to the treatment group. This suggests that the minimum wage increase has a positive impact on the income of workers earning just above the new minimum and even below it. This result is consistent with the existing literature, which shows that minimum wage increases have a positive effect on the income of workers earning slightly above or below the new minimum. Scientific contribution. In doing so, two new basic scientific contributions were made: a systematic, exhaustive, and up-to-date literature review (up to June 2024), as there is, to our knowledge, no recent systematic review of this relationship (minimum wage vs. inequality). Then, the introduction of new scientific evidence demonstrating that a significant increase in the minimum wage can significantly improve the income of low-wage earners without the adverse effects that would otherwise disrupt this positive effect, thereby reducing income inequality and poverty. As a limitation of the study, it would be desirable to delve deeper into other aspects not analysed here, such as the effects on productivity and consumption. Furthermore, it has not been possible to analyse the medium and long-term effects, due to data limitations. Nevertheless, there is evidence that inequality and poverty are on a downward path.

Carbon dioxides capture chemical looping combustion (CLC) technology uses metal oxides as oxygen transporters (TO). (1) These oxygen transporters, OXMN009 and OXMN009P, are used in a cyclic process that prevents the formation of nitrogen oxides by keeping air and fuel separate. (2) Thermogravimetric balance (TGA) experiments were conducted to evaluate the kinetic behavior of these copper-modified oxygen transporters. (3) It was found that OXMN009P has improved reactivity and oxygen transfer properties due to copper impregnation. The kinetic parameters obtained in the TGA indicate that the reaction is non-thermal and requires less energy to initiate. (4) The results show that OXMN009P has reactivity comparable to other manganese-based materials reported in the literature and can be an effective option for carbon dioxide capture.

Viral hepatitis is currently acknowledged as a significant public health issue that necessitates a prompt and immediate response. Hepatitis is a significant worldwide health problem that causes the death of approximately 1.5 million individuals annually. The objective of this study was to ascertain the occurrence rate of hepatitis A, E, B, and C infections in the Hajjah governorate of Yemen from 2020 to 2023.A retrospective study was conducted in the Hajjah Governorate of Yemen for four years, 2020– 2023. About 41162 cases were collected from the clinical records of epidemiological surveillance in the Public Health Office of the Hajjah Governorate. All cases were diagnosed in different laboratories based on direct observation of viral hepatitis in the blood sample. The required data were obtained by using the designed questionnaire. The findings of the present investigation were summarized as follows: The current findings indicate that the prevalence rate of Hepatitis A and E was 761 (1.85%), while the prevalence rate of Hepatitis B and C was 971 (2.36%) among the participants of the study. The current findings indicate that the incidence of Hepatitis A and E was greater in 2022 (2.3%), while Hepatitis B and C had a higher rate in 2020 (2.9%). The study revealed a higher prevalence of hepatitis A and E among individuals originating from Al Miftah district 116, with a rate of 7.5%. Furthermore, the prevalence of hepatitis B and C in Hajjah city was significantly higher, reaching 579 cases (22.9%). The month with the highest incidence of hepatitis A and E viruses was September, with a rate of 85 cases (2.6%), while the lowest incidence was observed in April, with a rate of 1.3%. The prevalence of hepatitis B and C viruses was highest in October 1997, with a rate of 2.8%, followed by November 1997 with the same rate. The lowest observed incidence of 1.6% was recorded in April. In Autumn, a significant prevalence of hepatitis A and B viruses, as well as hepatitis B and C viruses, was identified at rates of 2.2% and 2.6%, respectively.The study findings indicate that the occurrence of HAV, HEV, HBV, and HCV in the study area is consistent with global trends. Although the study found a low prevalence of hepatitis viruses, these types of viruses will continue to pose a significant risk to public health. Based on this study, it is imperative for authorities to actively enhance public awareness in order to enable prompt planning and essential arrangements for an effective response to outbreaks or epidemics. This will ultimately lead to a reduction in illness, death, and economic burden.

Brand communication and supply chain management are critical components of value co-creation in B2B markets, yet their interplay and implications remain underexplored in current literature. This qualitative study investigates how these elements synergistically contribute to mutual value creation among businesses. Through semi-structured interviews with senior executives and managers from diverse industries, key insights were gleaned regarding the strategic alignment of brand communication strategies with supply chain practices. Findings underscore the importance of authenticity, transparency, and consistency in brand messaging to build credibility and foster stakeholder trust. Supply chain management emerged as pivotal in supporting effective brand communication, facilitated by advancements in AI, blockchain, IoT, and cloud computing, enhancing operational efficiency and responsiveness across global networks. Entrepreneurship and emotional intelligence were identified as crucial drivers of innovation and collaboration within B2B contexts, augmenting organizational agility and resilience. Furthermore, the integration of sustainable practices within supply chain operations was found to enhance brand reputation and mitigate risks associated with environmental and ethical considerations. The study highlights actionable insights for practitioners, emphasizing the strategic integration of brand communication and SCM capabilities to navigate complexities, capitalize on emerging opportunities, and foster sustainable growth. This research contributes to a deeper understanding of the multifaceted dynamics shaping B2B interactions and provides a foundation for future research endeavors. By aligning brand communication strategies with SCM practices and leveraging technological advancements, businesses can enhance competitive advantage, cultivate enduring relationships with stakeholders, and achieve sustainable success in a dynamic global marketplace.

Manufacturing firms need to streamline their initiatives in line with 17 sustainable development goals (SDGs) 2030 as a means for improving performance. This research adapts SDG’s goals 8 decent job and economic growth’ as a measure of performance, in examine the effect of corporate sustainability strategies on performance of manufacturing firms. Census sampling technique was used in cross sectional survey of 900 multi-industry managers from one hundred and fifty (150) manufacturing firms in Kano, Nigeria. A five Likert scale, well-structured questionnaire was used in collecting data, analysed by Structural Equation Modelling SEM PLS Package. The study shows positive and significant effect of eco-efficiency, and positive and insignificant effect of both legitimation and risk mitigation strategies on performance respectively. The study concluded that the positive and significant effects of eco efficiency initiatives could be due to benefits derived from total quality management system, energy monitoring, and process safety management reflected in sustainability oriented visionary leadership of the managers. The positive and insignificant effects of legitimation initiatives could be as a result of huge spending on sustainability reporting, and corruption. The positive and insignificant effect of risk mitigation could be due to pro-activeness of the firms’ managers in tackling risk through sustainability oriented visionary leadership. The study recommended firms should adopt conservative eco-efficiency initiatives for improving performance and stop adopting extroverted legitimation and introverted risk mitigation strategies as both have no significant effect on performance. Future researchers should use longitudinal research design using financial metrics adopting the same independent variables in other economic sectors.

This paper shows the usage of a numerical analysis model which enables the calculation of the life of a railway wheels used for low-floor freight wagons as a function of its primary operating factors, which allows carrying out sensitivity analyses. Low-floor wagons are being increasingly used for combined transport applications and many types of bogies have been proposed in order to constitute the wagons. Due to the uniqueness of this type of wagons, the bogie configurations in terms of wheelbase and axle load have hardly been analyzed so far. The numerical analysis model used addresses the primary challenges that arise in the vehicle – track interaction and establish the relations among them. The main aspects of this model have been described in the paper, which has been later used to calculate the life of an ordinary-diameter wheel for several wheelbase and axle load values. This study has been replicated with reduced-diameter wheels, which are commonly used for low-floor wagons. In this way, it is possible to know the evolution of the life depending on the wheelbase and the axle load. The root causes underlying the observed behaviors can be explained by the entire understanding of the rolling phenomenon provided by the full analytical work.

ERI and SSZ-13 were subjected to post-synthetic treatments (depending on the zeolite topology) to create micro-/mesoporous materials. The results of NH3-SCR-DeNOx show that the applied treatments improved the catalytic activity of the Cu-containing ERI-based materials; however, the NO conversion does not vary for the different materials treated with NaOH or NaOH/HNO3. For the micro-/mesoporous Cu-containing SSZ-13, a lower NO conversion in NH3-SCR-DeNOx is observed. Thus, our findings challenge the current paradigm of enhanced activity of micro-/mesoporous catalysts in NH3-SCR-DeNOx. The modification of the supports results in the presence of different amounts and kinds of copper species (especially isolated Cu2+ and aggregated Cu species) in the case of ERI- and SSZ-13-based samples. The present copper species further differentiate the formation of reactive reaction intermediates. Our studies approved that besides the -2,2-peroxo dicopper(II) complexes (verified by in situ DR UV-Vis spectroscopy), also copper nitrates (evidenced by in situ FT-IR spectroscopy) act as reactive intermediates in these catalytic systems.

Synthetic Aperture Radar (SAR) ship target detection has been extensively researched. However, most methods use the same dataset division for both training and validation. In practical applications, it is often necessary to quickly adapt to new loads, new modes, and new data to detect targets effectively. This presents a cross-domain detection problem that requires further study. This paper proposes a method for detecting SAR ships in complex backgrounds using fusion tensor and cross-domain adversarial learning. The method is designed to address the cross-domain detection problem of SAR ships with large differences between the training and test sets. Specifically, it can be used for the cross-domain detection task from the fully-polarised medium-resolution ship dataset (source domain) to the high-resolution single-polarised dataset (target domain). This method proposes a Channel Fusion Module (CFM) based on the YOLOV5s model. The CFM utilises the correlation between polarised channel images during training to enrich the feature information of single-polarised images extracted by the model during inference. The article proposes a module called Cross-Domain Adversarial Learning Module (CALM) to reduce overfitting and achieve adaptation between domains. Additionally, the paper introduces the Anti-Interference Head (AIH) which decouples the detection head to reduce the conflict of classification and localization problems. This improves the anti-interference and generalization ability in complex backgrounds. This paper conducts cross-domain experiments using the constructed medium-resolution SAR full polarization dataset (SFPD) as the source domain and the high-resolution single-polarised ship detection dataset (HRSID) as the target domain. Compared to the best-performing YOLOV8s model among typical mainstream models, this model improves Precision by 4.9%, Recall by 3.3%, AP by 2.4%, and F1 by 3.9%. This verifies the effectiveness of the method and provides a useful reference for improving cross-domain learning and model generalization capability in the field of target detection.

Background: The receptor activator of the nuclear factor-kB (RANK)/RANK ligand (RANKL)/osteoprotegerin (OPG) pathway is a determining pathway in the balance between bone formation and resorption; disruptions in this complex can affect bone metabolism. Methods: This study analyzed the changes in RANKL, OPG and 25(OH)D levels, the RANKL/OPG ratio, and other bone turnover markers (BTM) from diagnosis to complete remission in children with acute lym-phoblastic leukemia (ALL). This is a prospective observational cohort study. This study was carried out in the Instituto Mexicano del Seguro Social in Mexico City. Thirty-three patients (4-17 years) with newly diagnosed B-cell ALL were included. The patients were treated with the HP09 chemotherapy protocol. Children who had previously been treated with corticosteroids were excluded. A pe-ripheral blood sample at diagnosis and remission was collected to determine the 25(OH)D and BTM concentrations. Results: Increased RANKL (p=0.001) and osteocalcin (p

This paper considers how prehistoric rock art can illuminate the environmental conditions of a vast but poorly known region in the distant past and in the process shed light on issues of environment, faunal survival, and cultural change. The rock art being considered here is located in the Baga Oigor valley of Bayan Ölgiy aimag, northwestern Mongolia; together with the petroglyphic complexes of Tsagaan Gol and Aral Tolgoi, it is part of the largest, most ancient, and best–preserved body of rock art in this mountainous region dividing North and Central Asia. The Baga Oigor complex itself includes materials dating from the late Paleolithic (12,000 yrs BP) through the Turkic Period (mid-first millennium CE). Within the thousands of compositions included in the complex, one of the least noticed images is that of the moose (Alces alces). Yet as much as any other animal representation within the petroglyphs of Baga Oigor, this image reveals the radical transformation of the environment of the Altai Mountains over several thousand years and its cultural implications. The examination of Alces alces and of its pictorial contexts sheds light on a world inhabited by ancient hunters and herders and sharpens our understanding of the dynamics of cultural change.

The spread of multidrug-resistant mycobacterium strains requires the development of new approaches to combat diseases caused by these pathogens. For that, photodynamic inactivation (PDI) is a promising approach. In this study, a tricarbocyanine (TCC) is used for the first time as a near-infrared (740 nm) activatable PDI photosensitizer to kill mycobacteria with deeper light penetration. For better targeting, a novel tricarbocyanine dye functionalized with two trehalose units (TCC2Tre) is developed. The photodynamic effect of the conjugate against mycobacteria, including Mycobacterium tuberculosis, is evaluated. Under irradiation, TCC2Tre causes more effective killing of mycobacteria compared to the photosensitizer without trehalose conjugation, with 99.99% dead vegetative cells of M. tuberculosis and M. smegmatis. In addition, effective photoinactivation of dormant forms of M. smegmatis is observed after incubation with TCC2Tre. Mycobacteria treated with TCC2Tre are more sensitive to 740 nm light than the Gram-positive Micrococcus luteus and the Gram-negative Escherichia coli. For the first time, this study demonstrates the possibility of in vitro PDI of mycobacteria including the fast-growing M. smegmatis and the slow-growing M. tuberculosis using near-infrared activatable photosensitizers. These findings are useful for the development of new efficient alternatives to antibiotic therapy.

The nuclear reactor measurement system is a crucial component of the nuclear measurement system in a nuclear power plant. Its primary function is to measure the power distribution within the reactor core using detectors, calibrate, and provide data on core fuel consumption. Therefore, the study of the detectors' reliability is crucial for ensuring the safe operation of the nuclear power system. The article describes the operational mechanism of the gas ionization chamber detector utilized in the intermediate-range detector of the off-board nuclear measurement system. It also analyzes the movement of particles between the plates during the ionization process of the nuclear reaction taking place in the detector. The functional relationship between the current in the recombination region and the ionization region involved in the actual working condition, and the change with the increase of voltage between the plates, is deduced. A mathematical model is established for the number of pulses generated between the plates and the magnitude of the voltage between the plates. Subsequently, the change in the offset of the voltage corresponding to the inflection point of the ping curve and the change rule of the slope of the ping curve are investigated. Combined with the analysis of experimental data, the results show that the initial particle energy of Ar+, the primary sensitive particle on the detector surface, follows a normal distribution and is influenced by the energy loss associated with the initial velocity and the voltage between the plates. The trends of the inflection points and slopes of the ping curves can be utilized to evaluate the performance and operational status of the detector. Combined with the results of the experimental data analysis, the fit is good, and the inflection point currents in the normal state decrease by about 1.5% annually. The intelligent diagnostic system, based on the method studied in this paper, has been successfully implemented in the RPN digital retrofit and upgrade project at Qinshan No. 2 Plant.

Abstract: Imaging of low (LGG) to high (HGG) grade gliomas is conventionally performed with MRI, which is the non-invasive gold-standard imaging modality to derive data. Gliomas (Grade 1,2,3,4) are lethal and demonstate poor outcomes despite novel therapies. Integrins compose of heterodimeric parasympathetic nervous system; the aVb3 (RGD i.e. Galacto-Arginine-Glycine-Aspartic acid) have been displayed as a potential biomarker that can be imaged via PET in order to trace the angiogenetic pathway. Gliomas are common primary central nervous system (CNS) tumours which are often pose a diagnostic challenge, even to stage and manage because of their heterogeneity in molecular aberrations. Several core mutational core hallmarks of gliomas are inducing/accessing vasculature, tumour promoting inflamation, polymorphic microbes and avoiding/resisting cell death; these ultimately lead to poor prognosis. In 2007, the classification of diffuse gliomas was based on the histopathology and subtype e.g. Pilocytic astrocytoma and low cell proliferation, in 2016, the classification of diffuse gliomas was based on the IDH status, 1p/19q codeletion, subtype and grade; then in 2021, the IDH status (wild-type or mutant), molecular profile, subtype and grade were added in order to improve the classification of diffuse gliomas. Imaging (MRI) techniques progress stalled despite the imperfections in MRI e.g distinguishing RN (radionecrosis) and PsP (Pseudoprogression) hence the exploration of PET probes that detect important hallmarks of gliomas e.g. techniques such as [68Ga]68Ga-RGD positron emission tomography (PET) to be utilised to assess vasculature. This case report aimed to determine the potential clinical utility of molecular imaging with 68Ga-RGD PET used in complementary to traditional MRI techniques.

Early disease detection is crucial for maximizingcrop yields and minimizing financial losses in agriculture. Inorder to categorise leaf diseases in pepper, tomato, and potato plants, this study suggests a revolutionary CNN design. The algorithm collects disease-specific features from input photos by using data augmentation techniques to artificially enlarge the training dataset. ReLU-activated convolutional layers gradually capture features at different levels, from low to high, while max pooling layers minimise spatial dimensionality. After thecharacteristics are extracted, a fully-connected layers with a softmax activation function classify them into illness groups. A well chosen dataset containing labelled healthy and sick leaves is used to train and validate the model. Generalizability to untesteddata is ensured via performance evaluation on an independent testing set. The field of deep learning for agricultural applications benefits from this research. This strategy has the ability to rev- olutionise agricultural practices by enabling automated disease identification. This might result in early interventions, better crop health, and eventually sustainable agricultural production.

The increasing concern regarding climate change continues to motivate research in the Arctic. Within the delicate cycle of the cryosphere, leads are an important kinematic feature that regulate heat balances in the Arctic. Therefore, it is necessary to quantify the genesis of leads over time to identify when and where changes are occurring. The use of a principal component analysis (PCA) is one such tool that is used to identify the characteristics of seasonal ice variability. The PCA not only identifies “normal” or “dominant” conditions or features, but also extract anomalous spatial features from an archive of long-term sequence of images.

One characteristic of mammalian species is their capacity to produce and secrete milk from their mammary glands to feed and provide vital nutrients for the growth of their offspring. Even though mammary glands provide the same function in different species, their development, shape, and structure can vary according to their reproductive and ecological adaptations. Reproduction studies are important for cetacean conservation because they provide essential information to assess the dynamics of populations and species, particularly in relation to the management of animals under human care. A vast majority of literature on the female cetacean reproductive anatomy and physiology has focused on the ovaries, which can be used to infer life history characteristics, or genital diseases and anomalies. However, literature regarding the morphology, physiology, and developmental pattern of their mammary glands is scarce, with few anatomical and histological descriptions in species such as baleen whales; and more recently it has been assessed with the use of ultrasound in finless porpoises (Neophocaena asiaeorientalis). The aim of this review is to describe the current diagnostic tools applied in human and veterinary medicine to assess the mammary glands and how marine mammal medicine could benefit from these tools to evaluate the mammary glands in free-ranging and captive cetaceans. With the use of imaging techniques such as B-mode ultrasound, non-invasive studies could be performed to assess the mammary tissues, as what has been done to characterize the morphology of other organs in cetaceans, such as the reproductive tract of Indo-Pacific bottlenose dolphins under human care. By understanding and revising the current diagnostic tools to assess the mammary gland of humans and domestic animals, such as ultrasonography, it might be possible to determine which techniques could be applied by marine mammal veterinarians to enhance the evaluation of the cetacean mammary gland morphology and physiology.

Soil tillage intensity influences the distribution of nutrients, and soil’s physical and me-chanical properties, as well as gas flows. The impact of reduced tillage on these indices in spring barley cultivation is still insufficient and requires more analysis on a global scale. This study was carried out at Vytautas Magnus University, Agriculture Academy (Lithu-ania) in 2022–2023. The aim of the investigation was to determine the effect of the tillage systems on the soil temperature, moisture content, CO2 respiration and concentration in spring barley cultivation limited by the semi-humid subarctic climate. Based on a long-term tillage experiment, five tillage systems were tested: deep and shallow mold-board ploughing, deep cultivation-chiselling, shallow cultivation-chiselling, and no-tillage. Shallow ploughing technology was found to be better at conserving soil moisture and maintaining a higher temperature. Deep cultivation had a lower moisture content and lower soil temperature. Shallow cultivation fields in most cases increased CO2 emissions and CO2 concentration. The results show that in direct sowing fields, most cases had a positive effect on crop density. Direct sowing fields resulted in significantly lower grain yields of spring barley in the years studied.

This study examines the potential of UiO-66 and g-C3N4-based composite catalysts for environmental purification and pesticide degradation. By integrating zirconium-based metal-organic framework UiO-66 with graphitic carbon nitride (g-C3N4), a composite with a Z-type heterojunction structure is created, enhancing photocatalytic pesticide degradation and phosphorus recovery. The optimal composite, UiO-66/g-C3N4(UG6:4), shows high efficiency in degrading organophosphorus pesticides like DDVP under visible light. This catalyst's high surface area and porous nature efficiently adsorb and break down persistent soil pollutants, including DDT and DDVP. Featuring robust stability and effective photocatalytic activity, the UiO-66/g-C3N4 composite holds promise for soil remediation and dealing with organic pollutants. Future research will aim to further refine this material’s structure and properties, ensuring its practical application in environmental cleanup.

This study examines if enterprises’ digital transformation enhances their sustainable development capabilities and reduces carbon emissions, thus enhancing carbon neutrality performance and implementing the "dual-carbon" strategy. It specifically explores the impact of Chinese firms’ digital transformation on carbon neutrality performance in 30 provinces and municipalities in China from 2011 to 2021. Based on the Difference-in-Difference method and spatial econometric modeling, this study finds a U-shaped relationship between enterprise digital transformation and carbon performance, with spatial spillover effects. It also finds that converting environmental charges into taxes can significantly improve carbon performance. In terms of the mechanism of action, digital transformation affects carbon performance by influencing energy use efficiency and adjusting the level of industrial structure advancement and rationalization. In terms of heterogeneity, this U-shaped relationship exists only in the eastern and central regions, and the significance is more substantial in the east; in addition, the impact of enterprise digital transformation on carbon performance is more evident in regions with higher R&D intensity and higher economic development levels. These findings imply that the government should further encourage and guide enterprise digital transformation, monitor the effects of environmental protection policies and select and implement carbon emission reduction strategies according to local conditions to improve carbon performance.

African swine fever virus (ASFV) is a large enveloped DNA virus that causes a highly pathogenic hemorrhagic disease in both domestic pigs and wild boars. The ASFV genome contains a double-stranded DNA encoding more than 150 proteins. The ASFV possesses only one protease pS273R, which is important for virion assembly and host immune evasion. Therefore, the specific monoclonal antibody (mAb) against pS273R is useful for ASFV research. Here, we generated two specific anti-pS273R mAbs named as 2F3 and 3C2, both of which were successfully applied for ELISA, Western blotting and Immunofluorescence assays. Further, we showed that both 2F3 and 3C2 mAbs recognize a new epitope of N terminal 1-25 amino acids of pS273R protein, which is highly conserved across different ASFV strains including all genotypes I and II strains. Based on the recognized epitope, an indirect ELISA was established and was effective in detecting antibody during ASFV infection. To conclude, the specific pS273R mAbs and corresponding epitope identified will strongly promote ASFV serological diagnosis and vaccine research.

Background: Commensal Neisseria species are part of the oropharyngeal microbiome and important for health, but also serve as a reservoir for antimicrobial resistance. Little is known about the prevalence of these species in the general population, how this varies by age and how antimicrobial susceptibility varies between species. Methods: We assessed the prevalence and antimicrobial susceptibility of commensal Neisseria species in the parents (n=38) and children (n=50) of 35 families in Belgium.Results: Various commensal Neisseria (n=5) could be isolated from the participants. Most abundant were N. subflava and N. mucosa. N. subflava was detected in 77 of 88 (87.5%) individuals and N. mucosa in 64 of 88 (72.7%). N. mucosa was more prevalent in children (41/50 [82%]) than parents (23/38 [60.5%]; P<0.05), while N. bacilliformis was more prevalent in parents (7/36 [19.4%]) than children (2/50 [4%]; P<0.05). N. bacilliformis showed high ceftriaxone minimum inhibitory concentrations (MICs; median MIC 0.5mg/L; IQR 0.38-0.75) and these high MICs explained the higher ceftriaxone MICs of all Neisseria isolates from the parents than the children. The median azithromycin MIC of all Neisseria isolates per individual was positively correlated with the median family MIC (rho=0.24; P=0.033). The same association was found for the analysis limited to N. subflava (rho=0.36; P=0.004) and N. mucosa (rho=0.30; P=0.027). Interpretation: The most abundant commensal Neisseria species found in this population were N. subflava and N. mucosa, of which the prevalence of N. mucosa varied by age. The prevalence of N. bacilliformis also varied by age and showed concerningly high ceftriaxone MICs which warrant further investigation. We found evidence of clustering of azithromycin, but not ceftriaxone, MIC by family.

Surface water plays a crucial role in climate change, human production, and life, making accurate monitoring and observation of surface water particularly important. However, due to the significant diversity and complexity of water distribution in surface space, accurate mapping of surface water faces considerable challenges. When extracting water bodies from medium-resolution satellite remote sensing images, CNN methods may suffer from limitations in receptive fields and insufficient context modeling capabilities, leading to the loss of water body boundary details and poor fusion of multiscale features. Currently, there is relatively little research on this issue; therefore, it is necessary to explore new combinations of deep learning networks to address these challenges. The purpose of this study is to address the above issues. We propose a new combination of deep learning networks that fully utilize multiscale information to enhance water features. Specifically, we first combine deformable convolutions with the Swin Transformer to increase effective receptive fields while better integrating global semantic information. This combination can capture features of water bodies at different scales, improve the accuracy and integrity of water extraction, and provide reliable technical support for detailed water body extraction. We tested the newly constructed model using Sentinel-2 satellite images. Our model achieved results of over 90%, with an average accuracy of 97.89%, average precision of 94.98%, average recall of 90.05%, and an average F1 score of 92.33%. In addition, our model achieved an accuracy of 98.03% in mountainous areas. Our experiments and results validate the potential of combining the Swin Transformer and deformable convolutions in detailed water body extraction.

The emergence of acquired resistance to EGFR-TKIs is almost inevitable even after a remarkable clinical response. Secondary mutations such as T790M and C797S are responsible for the resistance to 1st/2nd generation (1/2G) TKIs and 3G TKIs, respectively. To overcome both the T790M and C797S mutations, novel 4G EGFR-TKIs are now under early clinical development. In this study, we evaluated the efficacy of a 4G EGFR-TKI in the treatment of lung cancer with EGFR mutation as well as explored resistance mechanisms to a 4G TKI. First, we compared the efficacies of seven TKIs including a 4G TKI, BI4020, against Ba/F3 cell models that simulate resistant tumors after frontline osimertinib treatment failure because of a secondary mutation. We also established acquired re-sistant cells to BI4020 by chronic drug exposure. Ba/F3 cells with an osimertinib-resistant secondary mutation were refractory to all 3G TKIs tested (alflutinib, lazertinib, rezivertinib, almonertinib, and befotertinib). BI4020 inhibited the growth of C797S-positive cells; however it was not effective against L718Q-positive cells. Erlotinib was active against all Ba/F3 cells tested. In the analysis of resistance mechanisms of BI4020 resistant (BIR) cells, none harbored secondary EGFR mutations. HCC827BIR cells had MET gene amplification and were sensitive to a combination of capmatinib (MET-TKI) and BI4020. HCC4006BIR and H1975BIR cells exhibited epithelial to mesenchymal transition. This study suggests that erlotinib may be more suitable than 4G TKIs to overcome sec-ondary mutations after front-line osimertinib. We found that off-target mechanisms that cause re-sistance to earlier generation TKIs will also cause resistance to 4G TKIs.

[Introduction]: In the contemporary international financial environment, marked by intricate complexities and increasing uncertainties, the impact of exchange rate fluctuations on national economies has become increasingly significant. In this context, this study uses the Chinese economy as a case study to delve deeply into the interaction effects between macroprudential and monetary policies, analyzing how these policies jointly address economic instability. The aim is to offer new perspectives and strategies for stabilizing the global economic and financial landscape. [Methods]: This paper constructs an open-economy Dynamic Stochastic General Equilibrium (DSGE) model specifically tailored for China, incorporating Bayesian estimation and numerical simulation techniques. The study meticulously examines how macroprudential and monetary policies can be coordinated to achieve economic stability in response to exchange rate shocks. [Results]: The research finds that (1) targeted coordination of macroprudential and monetary policies towards asset prices and price levels can maintain stability under exchange rate shocks; (2) the effective implementation of such coordinated policies not only mitigates the fluctuations in asset prices due to exchange rate shocks but also enhances the level of societal welfare; (3) in terms of choosing an exchange rate regime, a managed floating rate system can prevent policy overlaps and conflicts that might occur in a floating rate system during the coordination of macroprudential and monetary policies, thus offering comparative advantages. [Discussion]: The findings underscore the importance of policy integration in a dynamic and complex global economic environment. They provide policy recommendations for China and other emerging market countries on how to effectively maintain economic stability through the synergistic interplay of macroprudential and monetary policies amid fluctuations in exchange rates and asset prices.

Although the neurofilament light chain (NfL) is used as a biomarker for neurodegenerative decline, its use in surgery- and anaesthesia-induced acute cognitive dysfunction remains controversial. We aimed to synthesise the evidence to explore the potential of NfL as an established biomarker for perioperative neurocognitive disorders (PND). We systematically searched the PubMed, EMBASE, MEDLINE, Cochrane Library electronic databases, and Cochrane Central Registry of Clinical Trials. Our results show that CSF NfL levels positively correlated with blood NfL levels (r = 0.63; 95% confidence interval [CI], 0.42-0.77). The pooled standardised mean difference (SMD) showed a significantly higher preoperative CSF NfL levels (SMD = 0.27; 95% CI, 0.07-0.47) and both pre- and postoperative blood NfL levels (SMD = 0.53, 95% CI, 0.40-0.66 and SMD = 0.58, 95% CI, 0.43-0.73) in the postoperative delirium (POD) group. Postoperative blood NfL levels were significantly elevated in both POD group (SMD = 0.49; 95% CI, 0.34-0.64) and no-POD group (SMD = 0.67; 95% CI, 0.53-0.81). Our meta-analysis indicates that NfL may serve as a potential biomarker for POD, and elevated preoperative blood NfL levels could be a risk factor for POD. Further studies are needed to confirm the association of CSF/blood NfL levels with other PND types.

Cancer is one of the most dreaded illnesses of the 20th century, cancer is continuing to spread and is becoming more common in the 21 st century.As of right now, breast cancer seems to be the most common cancer worldwide and the leading cause of cancer-related fatalities.In present study we used different network pharmacology tools for identification of target that involved in breast cancer that network pharmacology tool used target identification and validation process in drug discovery.In present study we used UniprotKB as text mining tool for identification of breast cancer gene in that we got the 2,658 gene in that we take the 165 in study the we done the GO and KEGG enrichment analysis in that we take pathways related to the breast cancer further we used STRING for determination protein-protein interaction in that we got the interaction between NDUFA1 with NDUFA3 and EREG,MYO1B with ACTN4 and XRCC3 with XRCC2.The interaction network was drawn and the network was analyzed by Cytoscape.

Retinitis pigmentosa (RP) is a heterogeneous inherited retinal disorder. Mutations in KIZ cause autosomal recessive (AR) RP. We aimed to characterize the genotype, expression pattern, and phenotype in a large cohort of KIZ cases. Sanger and whole exome sequencing were used to identify KIZ variants. Medical records were reviewed and analyzed. Thirty one patients with biallelic KIZ mutations were identified: 28 homozygous for c.226C>T (p.R76*), 2 compound heterozygous for p.R76* and c.3G>A (p.M1?), and one homozygous for c.247C>T (p.R83*). c.226C>T is a founder mutation among patients of Jewish descent. Clinical parameters were less severe in KIZ compared to DHDDS and FAM161A cases. RT-PCR analysis in fibroblast cells revealed the presence of four different transcripts in both WT and mutant samples with a lower percentage of the WT transcript in patients. Sequence analysis identified an exonic sequence enhancer (ESE) that includes the c.226 position which is affected by the mutation. KIZ mutations are an uncommon cause of IRD worldwide, but are not rare among Ashkenazi Jews. Our data indicate that p.R76* affect an ESE which in turn results in pronounced skipping of exon 3. Therefore, RNA-based therapies might show low efficacy since the mutant transcripts is spliced.

Background: In physiotherapy, a classic muscle-bone concept is used to translate basic and clinical anatomy. By defining the anatomical structures from superficial to deeper layers which frame the ArthroMyoFascial complex, our aim is to offer clinicians a comprehensive concept of fasciae within the muscle-bone concept. Method: Narrative review and ultrasound observation. Results: Based on literature and ultrasound skeletonization, the ArthroMyoFascial complex has been defined. This model clarifies fascial continuity at the joint level, describing anatomical structures from skin to deeper layers, including superficial fascia, deep fascia, myofascia including skeletal muscle fibers, and arthrofascia all connected via connective tissue linkages. This model enhances understanding of the muscle-bone concept within the larger ArthroMyoFascial complex. Conclusion: The ArthroMyofascial complex consists of multiple layers from superficial to deeper anatomical structures, namely the skin, superficial fascia, deep fascia, myofascia including muscle fibers, and arthrofascia, all linked within a connective tissue matrix. This model indicates that it is a force-transmitting system from the skin to the bone. This information is crucial for manual thera-pists, including physiotherapists, osteopaths, chiropractors, and massage therapists, as they all work with fasciae within the musculoskeletal domain. Understanding fascia within the mus-cle-bone concept enhances clinical practice, aiding in therapeutic testing, treatment, reporting, and multidisciplinary communication, which is vital for musculoskeletal and orthopedic rehabilitation.

Background and Objectives: To assess femoral shaft bowing (FSB) in the coronal and sagittal planes and introduce the clinical implications of total knee arthroplasty (TKA) by analyzing a three-dimensional (3D) model with virtual implantation of the femoral component. Materials and Methods: Sixty-eight patients (average age: 69.1 years) underwent 3D model reconstruction, incorporating medullary canals, by importing computed tomography (CT) data into Mimics® software. A mechanical axis (MA) line was drawn from the midportion of the femoral head to the center of the intercondylar notch; proximal/distal straight centerlines (length, 60 mm; diameter, 1 mm) were placed in the center of the medulla canal. Acute angles between the two centerlines were measured as lateral and anterior bowing. The acute angle by distal centerline and MA line was measured as distal coronal and sagittal alignment in both anteroposterior (AP) and lateral views. The diameter of curve (DOC) of the medulla along the posterior border was measured. Results: The mean lateral bowing on the AP view was 3.71°, and the mean anterior bowing on the lateral view was 11.82°. The average DOC of the medullary canal was 1501.68 mm. The distal coronal alignment of all femurs was an average of 6.40°, and the distal sagittal alignment was 2.66°. Overall, 22 femurs had coronal bowing, 42 had sagittal bowing, and 15 had both. Conclusion: In Asians, FSB is present in coronal, sagittal, or both directions. Increased anterolateral FSB may lead to cortical abutment in the sagittal plane despite limited space in the coronal plane. During TKA, distal coronal alignment can guide distal femoral valgus cut angle, whereas distal sagittal alignment helps anticipate femoral component positioning, avoiding anterior notching. Osteotomy along the anterior cortical bone to prevent notching may result in outliers due to differences between distal sagittal alignment and distal anterior cortical axis.

This study utilizes data from the fourth National Health Survey conducted in 2019. in the Republic of Serbia, aiming to contribute to a deeper understanding of the factors influencing the mobility of the elderly population. It examines the sociodemographic and psychosocial factors associated with functional limitations in older adults. By analyzing variables such as age, gender, marital status, education, income, social support, and mental health, the study seeks to explain their impact on the prevalence of walking limitations.Questionnaires were employed as a research instrument in line with the methodology of the European Health Survey (EHIS). The analysis is based on a sample of 3,705 participants aged 65 and above. Statistical significance between variables was assessed using the Chi-square test. Post-hoc comparisons were performed using pairwise z-tests. Univariate logistic regression was employed to identify predictors of walking difficulties. Additionally, multivariable logistic regression was conducted to further explore predictors while adjusting for potential confounding variables, with odds ratios and corresponding 95% confidence intervals estimated.Women exhibit significantly higher prevalence of walking difficulties compared to men (p < 0.001). There is a significant variation in the prevalence of walking difficulties among different age groups. Individuals aged 75-84 show the highest prevalence in all categories of walking difficulties, with particular significance in the categories of "no difficulty," "some difficulty," and "unable to walk at all" (p < 0.001). Higher levels of education generally correlate with lower prevalence of walking difficulties. Married or partnered individuals have 0.522 times lower odds of reporting difficulties in walking compared to singles (p < 0.05). Individuals with lower wealth index (1-Least affluent) have significantly higher prevalence of walking difficulties.This knowledge can inform targeted interventions to enhance mobility and improve the overall well-being of older individuals.

Numerous study reports on chitosan hydrogels in different forms such as films, porous structures, nanoparticles, and microspheres for biomedical applications, however, this study concentrates on their modifications with different crosslinking agents and observing their effects on drug loading and releasing capacities. Linear chitosan along with crosslinked by two major cross-linkers, i.e., genipin and disulfide have been used to formulate three different hydrogel systems. The cross-linking process is heavily impacted by the temperature and the pH conditions. Three different drugs, i.e., thymoquinone, gefitinib, and erlotinib are loaded in phosphate buffer solutions and infused with three different hydrogel systems, thus, a total of nine combinations are studied and analyzed for drug loading and releasing capabilities with Ultraviolet–visible (UV-Vis) spectroscopy. This study finds thymoquinone shows the lowest loading efficacy compared to two other drugs in all three systems. Gefitinib shows stable loading and releasing regardless of crosslinking systems and genipin crosslinked system shows stable loading and releasing with all three drug molecules. These experimental results agree well with the findings of our previously published results conducted with molecular dynamics simulations.

Solifenacin (SFC) is a potent muscarinic antagonist that effectively reduces bladder muscle contraction, thereby alleviating symptoms such as frequency of micturition and urgency. Oxidation of SFC leads to the formation of impurities like Impurity K. Effective analysis and control of this impurity is crucial for ensuring compliance with regulatory standards and safeguarding patient health. To address these challenges, we propose a novel one-step synthesis of Impurity K from SFC. Impurity K was synthesized using cerium ammonium (IV) nitrate (CAN) in water/acetonitrile as the solvent. Additionally, we describe a new HPLC-MS method for the detection of Impurity K in solifenacin succinate tablets.

ABSTRACT The work is focused on determining the energy transfer from EV’s to grid for different operating conditions. The study has been simulated on a scaled model and later validated through experimental tests on batteries of 20 kWh, 40 kWh, 60 kWh and 80 kWh for EV’s energy rates from 130 Wh/km to 180 Wh/km. Tests have been developed to evaluate the energy transfer from driving distance between 0 and 50 km. Results have proved there is a linear dependence between energy transfer and energy rate. Experimental and simulated values have been correlated showing a 99.6% accuracy. The ratio of energy transfer to battery energy capacity depends not only on this latter parameter, but also on the energy rate of the electric vehicle. Experimental tests have shown a variation from a minimum transfer ratio of 54.1% for the highest electric vehicle energy rate and lowest battery energy capacity and power transfer to grid rate to a maximum of 88.6% for the highest power transfer to grid rate and battery energy capacity and lowest electric vehicle energy rate.

Patients with chronic kidney disease (CKD), particularly those with end-stage kidney disease (ESKD) undergoing dialysis or kidney transplantation, face ongoing challenges in relation to the risk of COVID-19. In addition to their underlying condition, factors such as immune-evasive variants, immunosuppressive therapies, and the need for dialysis contribute to poor COVID-19 outcomes in this population. Severe COVID-19 can lead to the deterioration of CKD/ESKD, resulting in acute kidney injury, septic shock, and respiratory failure. Moreover, patients with CKD/ESKD have shown impaired response to COVID-19 vaccination, with seroconversion failures associated with the burden of immunosuppressive treatments, further heightening their vulnerability to severe disease. Despite the current endemic, it is crucial to acknowledge the ongoing significance of COVID-19 as a serious threat to patients burdened with chronic diseases like CKD and ESRD. Understanding the impact of COVID-19 on these patients is essential, as they remain at risk of severe disease progression. This paper presents the results of a literature review to enhance our understanding of COVID-19-related risks in patients with CKD/ESKD. Expert insights and illustrative scenarios provide practical perspectives and highlight the importance of risk stratification based on clinical factors for guiding targeted measures and treatments to mitigate COVID-19 risks in these vulnerable patients.

This study provides a comprehensive analysis of global patent trends in battery recycling, focusing on secondary batteries and related technologies across Korea, China, and the United States. The data, collected from various patent databases, was quantitatively analyzed to identify technology trends and direct future development. The analysis reveals distinct emphases on technologies such as lithium-ion and waste battery recycling, highlighting notable differences in patent activities among key companies and countries. China's large number of patents in battery manufacturing processes contrasts with the USA's focus on electrochemical cell construction and storage systems, while Korea shows significant activity in waste battery technology. The study underscores the competitive landscape and innovation efforts in the battery recycling sector, providing insights into the technological focuses and priorities of each country. It also identifies key challenges, such as the need for consistent innovation and broader geographic coverage in Korea, enhancing patent influence and international presence in China, and ensuring high patent quality and fostering innovation in lagging sectors in the United States. Addressing these challenges through enhanced collaboration, increased R&D investments, and supportive policies is crucial for strengthening the global position and driving further innovation in the battery recycling sector.

A large share of the reinforced concrete (RC) building stock in Mediterranean countries faces a dual challenge of seismic vulnerability and energy inefficiency, calling for urgent renovation efforts. While energy upgrades have been the focus of previous renovation policies, recent research highlights the critical need for integrated retrofitting solutions that address both structural integrity and energy performance. Multi-criteria decision-making (MCDM) approaches are a promising tool for optimizing the combined choice of these integrated interventions, considering various decision variables (DVs) of economic, social, environmental, and technical nature. To understand the impact of climate and seismic hazard conditions on multi-criteria-based retrofitting assessment, a case-study RC school building is selected and assumed to be located in three distinct climate conditions, cold, mild, and warm, and three seismic hazard levels, low, medium and high. Moreover, given the complexity and challenges of quantifying seismic performance metrics for practitioners, an available simplified (practice-oriented) approach is compared herein with a more thorough research-based one for quantifying the seismic performance of RC buildings within the MCDM framework. Both approaches are applied to the case-study building, considering twelve possible combinations of energy and seismic interventions. The accuracy of the practice-oriented approach and its impact on the retrofitting rankings is evaluated, emphasizing the importance of accessible and efficient evaluation methods in facilitating informed decision-making for building renovation

The study assessed the risk perception, attitude, and management tools of 260 randomly selected farmers and processors in the rice value chain using data elicited via a structured questionnaire. Descriptive statistics, Equally Likely Certainty Equivalent (ELCE) technique, Binary logistic regression, and a 5-point Likert scale were employed in the data analyses. Descriptive statistics show that the respondents are young, active, and in their productive age with an intermediate education level. Majority of the farmers and processors were risk averse. Risk aversion was common among farmers and processors. Farmers' risk attitudes and perceptions of risk are significantly influenced by a number of factors, including age, access to extension services, farm size, marital status, household size, education, income, training, and experience. Majority of rice farmers consider price risk as the most important risk while majority of processors perceive production risk as the most important risk. Pests and diseases, price fluctuation, drought, and lack of input were the most important source of risk to farmers, while processors perceived price fluctuation, technology adoption, and poor storage facilities as the most important source of risk. Off-farm investment, spraying for pests and diseases, cash contribution, market information, and cooperative were the important risk mitigating management strategies employed by the farmers/processors. The study suggests improvements in the identified risk sources, which could influence the attitude and perception of the farmers and processors.

The interaction of matter when separated by a distance is a fundamental question, whether such interactions occur through instantaneous action at a distance or retarded interaction (principle of locality)? While the mainstream consensus favors the principle of locality, instantaneous action at a distance offers certain advantages. Previously, instantaneous action at a distance has been viewed as an appearance or representation from specific gauge choices of electromagnetic potentials (retarded). In this paper, we propose a novel approach that combines Weber’s electrodynamics with the concept of vacuum polarization to explore a new possible connection between the two viewpoints: instantaneous action at a distance and the locality principle. This new approach aligns with the observation of locality in signal/energy propagation while retaining the notion of instantaneous action at a distance.

Fatigue is a recognized concern in air traffic management, prompting international bodies like ICAO and EASA to advocate for Fatigue Risk Management Systems (FRMS). EU Regulation 2017/373, effective since January 2020, imposes specific requirements on air traffic service providers regarding controllers' fatigue, stress, and rostering systems, as part of safety management protocols. Despite active campaigns promoting fatigue awareness in air traffic control (ATC), there remains a need for standardized operational requirements. Eurocontrol recently published "Guidelines on fatigue management in ATC rostering systems" (April 23), aiming to facilitate the adoption of common fatigue operational standards. However, neither EU Regulation 2017/373 nor existing documentation specifies exact rostering criteria. Air Navigation Service Providers (ANSPs) typically derive these criteria from scientific literature, best practices, historical data, and legal and operational necessities. Yet, assessing and monitoring fatigue in operational settings can be complex and require long-term studies due to its multifaceted nature, spanning factors such as sleep quality, circadian rhythms, psychosocial influences, individual traits, and environmental conditions. The case studies reported in this paper represent an attempt to create an evidence-based protocol for fatigue risk monitoring in ATC operations, utilizing a non-invasive approach and collecting multidimensional data. The two case studies involved en-route and tower controllers from different ATC Centers, and the results underscore the importance of fatigue assessment in ATC and elucidates challenges in implementing fatigue monitoring within operational contexts.

Evaluation of biliary strictures remains a challenge due to the low sensitivity of standard diagnostic work up, but the introduction of direct single-operator cholangioscopy (DSOC) changed this paradigm. Aim of our study was to evaluate diagnostic performance of DSOC and DSOC-targeted biopsies, intraductal ultrasound (IDUS) and brush cytology in patients with indeterminate biliary stricture (IBS). We evaluated patients who underwent advanced diagnostic work up for IBS in our endoscopy unit from ‘01/2018 to ‘12/2022; all patients had at least one previous attempt to characterize the biliary stricture. Final diagnosis was based on surgical pathology and/or clinical and radiological follow-up of at least 12 months. A total of 57 patients with a mean age of 67.2 ± 10.0 years were included, with a mean follow up of 18.2 ± 18.1 months. IBS were mostly located in the distal common bile duct (45.6%) and final diagnosis was consistent with malignancy in 35 patients (61.4%). DSOC and IDUS showed a significantly higher accuracy (89.5% and 82.7% respectively) compared to standard cytology (61.5%, p <0.05). In our experience, DSOC visualization and IDUS both demonstrated an optimal diagnostic yield in the differentiation of IBS, with an acceptable safety profile both quantitatively and qualitatively.

The article examines the relationship between household food waste and GDP in various European regions, aiming to determine how economic prosperity influences household food waste levels. Using comparative analysis of secondary and tertiary data, we developed a synthetic indicator (IpFW), to assess the interaction between GDP per capita and household food waste per capita. Despite expectations, higher GDP did not consistently correlate with lower food waste, challenging assumptions about economic prosperity and environmental stewardship. The research underscores the complex interplay between economic factors and food waste management, revealing no significant correlation even at regional levels. It also highlights the potential of e-commerce in enhancing food waste reduction strategies. E-commerce platforms can optimize food supply chains and consumer behavior, contributing to more sustainable consumption patterns. The conclusions call for a reevaluation of policies and suggest that integrating e-commerce could bolster efforts to manage food waste more effectively, aligning with the Sustainable Development Goals.

In this study, a new nitrogen-enriched multiwall carbon nanotube is prepared and utilized to stabilize palladium species. After the characterization of this new composite, it was applied as a catalyst in the reduction of nitroarenes and hydrodesulfurization of dibenzothiophene. Using this newly established catalyst, a wide range of aromatic compounds were reduced to the corresponding amines under a very low amount of Pd (0.005 mol%) in short reaction times. Also, dibenzothiophene (a major pollutant in fuel oil) was very efficiently transformed using this catalyst. Its robustness was studied in the recycling process where, after 20 runs in the reduction of 4-nitrotoluene and 5 times in the desulfurization of dibenzothiophene, the activity of the catalyst remained intact. According to the E-factor calculations, the present Pd catalyst meets the standards of green chemistry.

The broad global distribution of freshwater clams belonging to the genus Corbicula is driven by multiple hermaphroditic lineages. These lineages, characterized by shared morphological traits and phenotypic plasticity, pose challenges to morphological identification. Genetic markers, such as the mitochondrial COI gene, play a crucial role in delineating these lineages and their ranges. Morphotypes represent observed phenotypic variations, while lineages are defined based on genetic markers. Here, we comprehensively review Corbicula's distribution in Argentina, dis-criminate extant lineages based on both morphological and genetic (COI) data, and describe variation in internal and external morphology using 15 Argentine populations. Haplotype net-works identified two mitochondrial lineages: A/R morphotype (FW5 haplotype) and C/S mor-photype (FW17 haplotype). Strikingly, despite having similar vectors, origins, and invasive stages, Corbicula lineages exhibit virtually segregated distributions. However, intermediate morphotypes and both mitochondrial haplotypes are found in sympatry in northeastern Argen-tina, suggesting the presence of hybrids due to maternal genome retention. These findings con-tribute to the clarification of the identity and distribution of Corbicula lineages in Argentina, where the genus has been found for over half a century. Similar studies are needed in other areas to better understand the invasion patterns of a successful and plastic group.

There is currently an exponential growth in the electric vehicle market, which will require an increase in the electrical grid capacity to meet the demand of charging. If, on the one hand, the introduction of energy generation from renewable sources can be used to meet that requirement, the intermittent nature of some of these sources poses challenges to the required real time equilibrium between generation and consumption. The impossibility of controlling generation from some of these sources leads to the attempt of controlling and manage the consumption of electricity, according with the levels of generation. In this context, the emergence of smart grids has introduced mechanisms that guarantee a balance between consumption and generation of electricity. One of these mechanisms is the smart charging of electric vehicles. Effective smart charging relies on communication between the supply equipment and the electric vehicle, en-abling the adjustment of the energy transfer according with the generation levels. Thus, there is a necessity for a standardised system that guarantees this communication. In this context, the ISO 15118 standard, allows high level communication mechanisms, much beyond the basic control solutions offered by the IEC 61851-1 specification. In this context, this paper presents the development of a charge emulation system, based on the ISO 15118 communication protocol and discusses its application for demand response purposes.

The dynamic evolution and variation of electrical loads is now a priority for optimum management and, above all, forecasting. Indeed, these dynamic load variations require computer tools able to implement optimal load forecasting models. Scientific research into automated models for forecasting electrical loads therefore represents a challenge for scientific researchers. Several research studies have therefore been carried out. These include machine learning approaches such as: LSTM (Long Short-Term Memory), Support Vector Machine (SVM) and others. This article proposes a comparison study between a hybrid model based on the wavelet transform coupled with the adaboost method, and LSTM, for forecasting electricity consumption loads. Python 3.10 was used for the studies. The first results obtained consisted in the study of electricity load forecasts over four (04) data sets of the year (January, April, August and December). These results are very satisfactory, showing a good correlation between the real results of the electrical load consumption data, and the results of the implemented model. The electrical load consumption data are collected from a renewable energy production source: photovoltaic solar energy. The model test results (R2) obtained range from 0.919 to 0.958. These results are representative of real data and reflect the model's performance. The second set of results concerns a comparative study between the methods used by Y. Xie et al (CNN, MLP, LSTM-AM and LSTM-AM-MLP), and our approach. The prediction results obtained between the approaches show a prediction gap ranging from 0.15 to 0.78 for RMSE and 0.83 for MAPE. These results show significant differences between the methods. The minimization of errors by our model, therefore, reflects the model's performance in terms of accuracy, which is necessary for the optimal management of consumer electricity load forecasts in order to ensure balance between supply and demand.

Pulmonary sarcoidosis is a multisystem granulomatous interstitial lung disease (ILD) with a variable presentation and prognosis. Early accurate detection of pulmonary sarcoidosis may prevent progression to pulmonary fibrosis, a serious and potentially life-threatening form of the disease. However, the lack of a gold-standard diagnostic test and specific radiographic findings pose challenges in diagnosing pulmonary sarcoidosis. Chest computed tomography (CT) imaging is commonly used but requires expert, chest-trained radiologists to differentiate pulmonary sarcoidosis from lung malignancies, infections, and other ILDs. In this work, we developed a multichannel, CT and radiomics-guided ensemble network (RadCT-CNNViT) with visual explainability for pulmonary sarcoidosis vs. lung cancer (LCa) classification using chest CT images. We leverage CT and hand-crafted radiomics features as input channels, and a 3D convolutional neural network (CNN) and vision transformer (ViT) ensemble network for feature extraction and fusion before a classification head. The 3D CNN sub-network captures localized spatial information of lesions, while the ViT sub-network captures long-range, global dependencies between features. Through multichannel input and feature fusion, our model achieved the highest performance with accuracy, sensitivity, specificity, and combined AUC of 0.93±0.04, 0.94±0.04, 0.93±0.08 and 0.97 respectively in a 5-fold cross-validation study with pulmonary sarcoidosis (n=126) and LCa (n=93) cases. The model offers promising potential for improving the diagnosis of pulmonary sarcoidosis. A detailed ablation study showing the impact of CNN+ViT compared to CNN or ViT alone, and CT+radiomics input, compared to CT or radiomics alone, is also presented in this work.

This study investigated a novel probiotic-enriched ice cream containing fermented white kidney bean homogenate to explore its potential health benefits. We assessed the viability of various probiotic strains during ice cream production and storage, focusing on their potential to reach the gut, and evaluated the overall antioxidant activity using DPPH, ABTS, FRAP, and TPC assays. The incorporation of fermented white bean homogenate significantly increased antioxidant capacity compared to the control group. Notably, strains like L. rhamnosus GG and L. plantarum 299v demonstrated the most pronounced effects on antioxidant activity, suggesting potential synergistic benefits between probiotics and bioactive compounds in fermented white beans. Although all probiotic strains experienced decreased viability during storage, certain strains, particularly L. plantarum 299v and L. casei DN-114001, showed promising survival rates even after 6 months. These results suggest the potential for developing probiotic ice cream containing viable bacteria capable of reaching the gut and contributing to a healthy gut microbiota. This could potentially improve digestion, reduce inflammation, and boost the immune system. Overall, this study highlights the potential of probiotic-enriched ice cream with fermented white kidney bean homogenate to combine the established benefits of probiotics for gut health with the enjoyment of consuming ice cream.

Myalgic Encephalomyelitis, also known as Chronic Fatigue Syndrome (ME/CFS) and Long COVID are characterized by debilitating post-exertional malaise and other core symptoms related to immune dysregulation resultant from post-viral infection, including mitochondrial dysfunction, chronic neuroinflammation and gut dysbiosis. The reported associations between altered microbiota composition and cardinal symptoms of ME/CFS and Long COVID, suggesting that use of microbial preparations, such as probiotics, by restoring the homeostasis of the brain-immune-gut axis may help in the management of symptoms in both conditions. Therefore, this review aims to investigate the implications of alerted gut microbiome and assess the evidence supporting use of microbial-based preparations, including probiotics, synbiotics, postbiotics alone and/or in combination with other nutraceuticals in the management of fatigue, inflammation, as well as neuropsychiatric and gastrointestinal symptoms among patients with ME/CFS and Long COVID.

Cement-free concrete has superior physical performance, such as strength and durability, compared to OPC concrete, however, it has the disadvantage of large shrinkage. Large shrinkage can cause cracks due to shrinkage stress in the long term. In this study, a shrinkage reducing agent (SRA) was used to reduce the shrinkage of cement-free mortar; its content was increased from 0.0 to 1.5 %. For an SRA content of 1.0 %, a calcium sulfoaluminate (CSA) expansive additive (EA) (2.5, 5.0, and 7.5%) was added. To calculate the shrinkage stress of cement-free mortar using the SRA and EA, the compressive strength, elastic modulus, and total and autogenous shrinkage were measured. The unit shrinkage stress of cement-free mortar was obtained by multiplying the elastic modulus by the length change and accumulated to obtain the shrinkage stress acting on the mortar according to the age. The shrinkage stress of cement-free mortar showed different tendencies as the age increased. At early ages, the shrinkage rate of the mortar occupied a large proportion of the shrinkage stress. In the long term, the shrinkage stress was significantly affected by the elastic modulus. As a result, SRA was found to be effective in reducing the shrinkage stress by decreasing both the elastic modulus and shrinkage. However, EA increased the shrinkage stress over the long term due to an increase in elastic modulus even though it compensated for early-ages shrinkage.

Melanin is extensively distributed in organisms and believed to be synthetized by tyrosinase (TYR), leading to aberrant coloring and skin conditions when over-produced. Loquat (Eriobotrya japonica (Thunb.) Lindl.) flowers contain large amounts of bioactive substances currently few studied on their suppressive capabilities to melanin synthesis. Its isolate product (LFP) was obtained by ethanol solution extraction and resin purification, of which the inhibitory mechanism on TYR activity was elaborated by enzyme kinetics and multi-spectroscopy determinations and the impact on related proteins’ expression in mouse melanoma B16 cells was analyzed with Western blotting. HPLC-MS analysis indicated that LFP was identified into 137 compounds, with 12 including flavonoids (quercetin, isorhamnoin, p-coumaric acid, etc.), cinnamic acid and its derivatives as well as benzene and its derivatives owning TYR inhibitory activities. LFP inhibited TYR activity in a concentration-dependent manner with its IC50 value being 2.8 mg/mL and an anti-competitive mechanism involved altering the enzyme's conformation. LFP reduced the expression of TYR, TRP1, and TRP2 in melanoma B16 cells, hence inhibiting the synthesis of melanin. Considered collectively, LFP would be a viable option for treating hyperpigmentation caused by tyrosinase, providing a theoretical basis for the value-added utilization of loquat flower resource in beauty and aging related functional products.

Mitochondrial encephalomyopathy, lactic acidosis, and stroke-like episodes (MELAS) syndrome is one of the most frequent maternally inherited mitochondrial disorders.MELAS syndrome is a multi-organ disease that presents with a wide range of symptoms, such as dementia, epilepsy, lactic acidemia, myopathy, hearing loss, stroke-like episodes, diabetes, short stature, and myopathy. MELAS primarily affects tissue with high energy demands such as the brain, muscles, and heart. With 65–76% of affected people presenting at or before the age of 20, childhood is the typical age of onset. Genetic testing, imaging tests such as magnetic resonance imaging (MRI) scans, and other techniques, tests of blood, urine, and cerebrospinal fluid in addition to muscle biopsy (if necessary) may be used to diagnose MELAS syndrome. Management of MELAS remains largely supportive, focusing on symptom alleviation and metabolic stabilization. The long-term prognosis of MELAS is variable, influenced by factors such as age of onset, severity of symptoms, and presence of comorbidities. While some patients experience a relatively stable course with intermittent exacerbations, others may exhibit progressive neurological deterioration and multiorgan involvement. Early recognition, prompt intervention, and close monitoring are essential for optimizing outcomes and mitigating complications.Presenting here a case report of an occurrence of MELAS in a 31-year old male patient with chief complaints of perspiration, uneasiness and weight loss with increase in appetite and past history of bilateral hearing loss and vision loss in left eye.

Exploring therapeutic options is crucial in the ongoing COVID-19 pandemic caused by SARS-CoV-2. Nirmatrelvir, a potent inhibitor targeting the SARS-CoV-2 Mpro, shows promise as an antiviral treatment. Additionally, Ivermectin, a broad-spectrum antiparasitic drug, has demonstrated effectiveness against the virus in laboratory settings. However, its clinical implications are still debated. Using computational methods such as molecular docking and 100 ns molecular dynamics simulations, we investigated how Nirmatrelvir and Ivermectin interact with SARS-CoV-2 Mpro(A). Calculations using density functional theory have been instrumental in elucidating the behavior of isolated molecules, primarily by analyzing the frontier molecular orbitals. Our analysis revealed distinct binding patterns: Nirmatrelvir formed strong interactions with amino acids like MET49, MET165, HIS41, HIS163, HIS164, PHE140, CYS145, GLU166, and ASN142, showing stable binding with a root mean square deviation (RMSD) of around 2.0 Å. On the other hand, Ivermectin interacted with THR237, THR239, LEU271, LEU272, and LEU287, displaying an RMSD of 1.87 Å, indicating enduring interactions. Both ligands stabilized Mpro(A), with Ivermectin showing stability and persistent interactions despite forming fewer hydrogen bonds. These findings offer detailed insights into how Nirmatrelvir and Ivermectin bind to the SARS-CoV-2 main protease, providing valuable information for potential therapeutic strategies against COVID-19.

The aim of this research work is to get a method for Galfenol electrodeposition thought which we can control the desired percentage of Ga versus Fe that has the maximum magnetostriction constant. Galfenol is electrodeposited on an optical fiber with an imbedded Fiber Bragg Grating (FBG) in its core. The final objective, that goes further of the scope of this research, is to get an optical magnetostrictive sensor. The device will sense magnetic field or current based on the combination of this magnetostrictive Galfenol, that will stress the optical fiber with the application of magnetic field or current and will change the reflected wavelength of the FBG as a consequence of the variation of the Bragg wavelength. We have developed a method of electrodeposition that allows controlling the density of current in the electrodeposition process in order to get the desired percentage of Ga and Fe in the alloy Ga X Fe 1-x. We have manufactured a set of samples with different parameters (as density of current and pH) and we have characterized these samples morphological, structural and magnetically. With this research we want to give to the scientific community the groundwork to design magnetostrictive optical sensors based on and FBG coated by giant magnetostrictive material. In this paper we have developed a method of covering the optical fiber controlling the composition of (Ga X Fe 1-X) in order to be able to get the maximum magnetostriction constant.

Starvation of photoreceptors induced by reduced dysregulated ocular blood flow is proposed as a common pathway for the pathogenesis of retinitis pigmentosa (RP). The current study evaluated the safety and efficacy of ophthalmic nerve stimulation (ONS) as an ocular blood flow neuromodulator, combined with ascorbic acid (AA) as a potent anti-oxidant in the treatment of RP. Additionally, the initial characteristics of rod responders were identified. Forty participants with simple, non-syndromic RP presented with a characteristic triad of RP (the bone spicule pigmentation, attenuation of retinal blood vessels, and waxy optic disc pallor), were en-rolled in a prospective open-label single-armed interventional study. The severity of the disease was clinically graded into six stages. Patients with an established diagnosis of RP; aged ≥ 4 years, with best corrected visual acuity (BCVA) ≥ 20/400 were included. All participants were daily treated with bilateral ONS sessions combined with intravenous administration of AA for two weeks. The primary efficiency endpoint was 6 months’ changes in scotopic vision as measured by a 10-item, 100-point, Low Luminance Questionnaire-10 (LLQ-10). The secondary efficiency points included best corrected visual acuity (BCVA) and contrast sensitivity. Rod responders were defined by ≥ 25 points increment of LLQ-10 score at 6 months after treatment. The results showed that ONS combined with AA treatment significantly improved low luminance vision, BCVA, and contrast sensitivity in patients with RP (p≤ 0.05). At 6-month visit, twenty-four (60%) patients were identified as rod responders and 16 (40%) patients were rod-non-responders. The mean change in LLQ-10 score was (46.35 ±16.81) in rod responders versus (4.9 ± 7.6) in non-responders (p < 0.0001). A clinically significant improvement of BCVA (≥0.2 logMAR) and contrast sensitivity (≥0.3 log unit) were demonstrated in 50% of the right eyes of rod responders. No serious adverse effects were reported and headache in 5 patients (12.5%) was the only en-countered side effect in this study. In conclusion, ocular neuromodulation is a safe therapeutic strategy for RP. It significantly improved night vision, BCVA, and contrast sensitivity. Determinants of rod responders include a shorter duration of night blindness, an earlier stage of the disease, and a relatively thicker ganglion cell layer at baseline. Additionally, two therapeutic scenarios were recognized; an early disease-modifying intervention that restores night vision and reverses the disease process and a late cone rescue intervention that improves/maintains central vision.

The implementation of sustainable practices, such as the use of renewable sources and efficient technologies, is crucial for reducing climate change. Energy efficiency is highly important on a global scale due to its relationship with climate change, aiming to minimize environmental impact. In Spain, renewable energy policies have increased self-sufficiency and reduced the use of fossil fuels. Optimizing energy consumption in residences, buildings, and industries is essential for improving efficiency. This was taken into consideration for conducting this study, focusing on the residential sector. The desire to understand the level of energy efficiency in Extremadura drove this project, which focuses on collecting and analyzing data on a set of homes located in the au-tonomous community of Extremadura, with the purpose of evaluating their energy efficiency. To achieve this, a computer tool will be employed to provide a detailed view of the different levels of energy efficiency present in the community. In addition to data collection and analysis, research will be conducted to identify areas for improvement. This will allow proposing a series of specific measures that users can implement to optimize energy efficiency in their homes, adapting them to the particular characteristics of each residence.

In 2011, commercial aviation contributed approximately 3.5% of global anthropogenic climate change through the emission of greenhouse gases during flight and operational non-CO2 climate effects. Over the last few years, numerous aviation-related organisations have set goals to reduce aviation’s climate impact. These goals, however, lack alignment, are poorly or ambiguously defined, or are internally inconsistent. This increases uncertainty about what aviation should work towards, how various stakeholders can contribute, and introduces problems with respect to accountability. In order to address this issue, this paper presents a comprehensive definition of a climate neutral air transport system as an “air transport system of which the climate effects of all its greenhouse gases and non-carbon dioxide effects throughout the entire life-cycle of each element of the system is balanced”. The proposed definition spans relevant system and encompasses all life cycle phases. To achieve a climate neutral air transport system by 2050, all life-cycle greenhouse gas emissions and non-CO2 climate effects remaining after in-sector reduction should be neutralised, as should all remaining non-CO2 climate forcing from emissions prior to 2050. Clarity on governance is furthermore needed, as the goal and associated targets proposed should be adopted globally.

Wearable sensors have become increasingly popular for assessing athletic performance, but the optimal methods for processing and analysing the data remain unclear. This study investigates the efficacy of discrete and continuous feature extraction methods, separately and in combination, for modelling countermovement jump performance using wearable sensor data. We demonstrate that continuous features, particularly those derived from Functional Principal Component Analysis, outperform discrete features in terms of model performance, robustness to variations in data distribution and volume, and consistency across different datasets. Our findings underscore the importance of methodological choices, such as signal type, alignment methods, and model selection, in developing accurate and generalisable predictive models. We also highlight the potential pitfalls of relying solely on domain knowledge for feature selection and the benefits of data-driven approaches. Furthermore, we discuss the implications of our findings for the broader field of sports biomechanics and provide practical recommendations for researchers and practitioners aiming to leverage wearable sensor data for athletic performance assessment. Our results contribute to the development of more reliable and widely applicable predictive models, facilitating the use of wearable technology for optimising training and enhancing athletic outcomes across various sports disciplines.