Smoking is a pervasive global health concern associated with a myriad of diseases, but its impact on cellular aging, particularly in relation to telomeres, is increasingly recognized. Telomeres, protective caps at the ends of chromosomes, play a crucial role in maintaining genomic integrity. This review critically examines the existing evidence on the association between smoking and telomere atrophy, exploring the molecular mechanisms involved and the implications for accelerated aging and heightened disease risk. The comprehensive analysis encompasses both cross-sectional and longitudinal studies, elucidating potential gender and age disparities. Insights into the molecular pathways linking smoking to telomere shortening are discussed, along with the broader implications for public health. The review concludes by outlining potential interventions and suggesting future research directions in this critical area.

The only cases where exact distributions of estimates are known is for samples from exponential families, and then only for special functions of the parameters. So statistical inference was traditionally based on the asymptotic normality of estimates. To improve on this we need the {\it Edgeworth expansion} for the distribution of the standardized estimate. This is an expansion in $n^{-1/2}$ about the normal distribution, where $n$ is typically the sample size. The 1st few terms of this expansion were originally given for the special case of a sample mean. In earlier work we derived it for {\it any } standard estimate, hugely expanding its application. We call an estimate $\hat{w}$ of an unknown vector $w\in R^p$, a {\it standard estimate}, if $E\ \hat{w}\rightarrow w$ as $n\rightarrow \infty$, and for $r\geq 1$ the $r$th order cumulants of $\hat{w}$ have magnitude $n^{1-r}$ and can be expanded in $n^{-1}.$ Here we give another huge extension. We give the expansion of the distribution of {\it any smooth function} of $\hat{w}$, say $t(\hat{w})\in R^q,$ giving its distribution to $n^{-5/2}$. We do this by showing that $t(\hat{w})$, is a standard estimate of $t(w)$. This provides far more accurate approximations for the distribution of $t(\hat{w})$ than its asymptotic normality. %NOT USED: The building blocks of the Edgeworth expansions are the {\it cumulant coefficients } of the estimate. These cumulant coefficients are also needed for bias reduction, Bayes estimates and confidence regions. We give {\it chain rules} for the cumulant coefficients of $t(\hat{w})$ in terms of those of $\hat{w}$ and the derivatives of $t(w)$, up to those needed for 5th order Edgeworth expansions for $t(\hat{w})$ and its {\it tilted expansion}, useful for the tail of the distribution.

Simple Summary: The distribution of typical bacterial redox enzymes such as pyruvate-ferredoxin oxidoreductase (PFOR) in protozoa remains interestingly puzzling. Previous studies have demonstrated diverse cellular localizations of PFOR in some amitochondriate anaerobic protozoa. PFOR is of particular pharmacological importance because it catalyzes the reductive bio-activation of nitro-based prodrugs to cytotoxic radical metabolites. Metronidazole was developed primarily as an antiprotozoal agent against infections caused by Trichomonas vaginalis. However, its antimicrobial spectrum was subsequently expanded to cover anaerobic bacterial infections. It has been shown that mutations in the genes encoding PFOR result in inherent resistance of PFOR-possessing anaerobic protozoa and bacteria to nitro-based prodrugs. Deciphering the evolutionary history of PFOR is crucial in deepening our understanding of the evolution of anaerobic pathogens and unfold new approaches for drug discovery and targeting in pathogen chemotherapy. Abstract: The present frontrunners in the chemotherapy of infections caused by protozoa are nitro-based prodrugs that are selectively activated by PFOR-mediated redox reactions. This study seeks to analyze the distribution of PFOR in selected protozoa and bacteria by applying comparative bioinformatics approaches to test the hypothesis that PFOR was most likely acquired through horizontal gene transfer (HGT) from bacteria. Furthermore, to identify other genes that were putatively acquired using proteome-wide and gene expression analyses. A plausible explanation for the patchy occurrence of PFOR in protozoa is based on the hypothesis that bacteria are potential sources of genes that enhance optimal adaptation of protozoa in hostile environments. The exclusively expressed proteins obtained from Entamoeba histolytica and the putative gene donor, Desulfovibrio vulgaris, showed an over-expression of eleven genes involved in intermediary metabolism. If these results can be reproduced in other PFOR-possessing protozoa, it would provide a more validated evidence to support the horizontal transfer of pfor from bacteria.

This paper provides a new discovery that adds to the contemporary theory of modelling of non-stationary queues, by capturing analytically the behavior of the root parameter, for the G1/M/1 PSFFA model of non-stationary Ek/M/1 queue. Additionally, it has been also revealed that the resulting root parameter reduces to the PSFFA model of non-stationary queue. Potential applications of PSFFA to Computer engineering are provided. Some challenging open problems are addressed combined with closing remarks and future research directions.

Green economy has emerged as a significant pillar of sustainable development in the current global context, and the unpredictability of economic policy has progressively garnered the interest of businesses and government officials as one of the obstacles they must confront. This paper examines how uncertainty in the green economy impacts the green economy's efficacy. The research concentrates on how changes in a particular region can result in geospatial diffusion (spatial spillover), which is a form of spatial spillover wherein the uncertainty of the green economy can impact its efficacy. This paper examines the policy formulation and current state of the green economy across various regions, as well as the diffusion of economic policy uncertainty across geographical areas and the subsequent impact on the green economy's status quo. There is a negative correlation between economic policy uncertainty and green economy efficacy, according to research. There is a spatial spillover effect between economic policy uncertainty and the efficacy of the green economy. Regional variations exist in the impact of economic policy uncertainty on the efficacy of the green economy. The findings indicate that the implementation of AI has a more substantial beneficial effect on carbon emissions. An increase in carbon dioxide emissions poses a growing challenge for the industrial sector in its pursuit of carbon neutrality.

Using the h-index to assess individual researchers is not only unethical and unfair but also inaccurate and misleading. This index fails to offer a reliable measure of a researcher's impact based on their citation scores. Beyond statistical and conceptual considerations, authorship practices, especially in the case of multi-authored publications, give rise to significant problems that often go unnoticed. While some modifications of the h-index have been proposed to mitigate these weaknesses, the fundamental deficiencies persist. Most of these flaws have been effectively addressed by the c-score, a composite citation index. The c-score excludes self-citations, normalizes the number of citations by considering the number of authors in each paper, and takes into account first, single, and last authorship. This approach provides a more realistic measure of the impact of each individual researcher based on raw citations.

Foodborne illnesses can be infectious and dangerous and most of them are caused by bacteria. Some types of common food-related bacteria exist widely in nature and pose a serious threat to both humans and animals, and can cause poisoning, diseases, disabilities and even death. Rapid, reliable and cost-effective methods for bacteria detection are of paramount importance in food-safety and environmental monitoring. Polymerase chain reaction (PCR), lateral flow immunochromatographic assay (LFIA) and electrochemical methods have been widely used in food-safety and environmental monitoring. In this paper, the recent developments (2013-2023) covering PCR, LFIA and electrochemical methods for various bacteria detection (Salmonella, Listeria, Campylobacter, Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli)) considering different foods types, analytical performances and the reported limit of detection (LOD) are discussed. It is found that the bacteria type and food sample type contribute significantly to the analytical per-formance and LOD. Detection by LFIA has higher average LOD (24 CFU/ml) than detection by electrochemical methods (12 CFU/ml) and PCR (6 CFU/ml). Salmonella and E. coli in the Pseudomonadota domain usually have low LODs. LODs are usually lower for detection in fish and eggs. LFIA with gold and iron nanoparticles are prominent in the majority of articles of 26 CFU/ml and 12 CFU/ml respectively. Electrochemical methods reveal that the average LOD is highest for cyclic voltammetry (CV) of 18 CFU/ml), followed by electrochemical impedance spectroscopy (EIS) of 12 CFU/ml and differential pulse voltammetry (DPV) of 8 CFU/ml. Finally, the review discusses the challenges and future perspectives (including the role of nanomaterials/advanced materials) to improve the analytical performance for bacterial detection.

Conventional text style transfer (TST) methodologies primarily utilize style classifiers to segregate the content and stylistic elements of text for effective style transformation. Despite the pivotal role of these classifiers, their influence on TST techniques remains largely unexplored. This study embarks on a detailed exploration of the limitations inherent in style classifiers within current TST frameworks. We reveal that these classifiers often inadequately comprehend sentence syntax, leading to diminished performance in TST models. In response, we introduce the Syntax-Enhanced Style Transfer (SEST) model, a groundbreaking approach incorporating a syntax-sensitive style classifier. This classifier ensures that the extracted style representations robustly encapsulate syntax nuances, enhancing TST effectiveness. Rigorous evaluations across diverse TST benchmarks demonstrate that SEST significantly surpasses contemporary models in performance. Additionally, our case studies highlight SEST's proficiency in producing syntactically coherent sentences that aptly retain original content.

Background: During esophagogastroduodenoscopy performed with colonoscopy, gastric and duodenal erythema, erosions, and ulcerations are often observed. This investigation was designed to review the prevalence of gastroduodenal lesions in patients who underwent wireless capsule endoscopy using standard bowel cleansing preparations, but no endoscopy or sedation. Methods: A retrospective analysis was conducted on patients referred for capsule endoscopy. Records and capsule reports were reviewed for patient demographics, preparation prescribed, procedural indications, and gastroduodenal findings. Preparations studied included polyethylene glycol lavage (PEG), PEG plus bisacodyl (PEG+bis), bisacodyl (bis), oral sulfate solution (OSS) and no prep. Results: Among the 1236 records, 498 (40.3%) were men and 738 (59.7%) were women. The mean age was 57 years +/- 17.8 years SD. The percentage of patients with lesions after any bowel preparation was 52.7% for gastric lesions and 23.6% for duodenal lesions. The percentage of patients with gastroduodenal lesions was 58.3% with prep, compared to 38.2% without prep. These findings were statistically significant with RR 1.53 [1.19-1.94] (p-value=0.00004). This difference was more pronounced in the OSS group RR 1.65 [1.29-2.1] and bisacodyl groups RR 1.64 [1.25-2.15] compared to the PEG group RR 0.95 [0.7-1.3]. Conclusion: This study showed that patients undergoing wireless capsule endoscopy who received bowel preparations had a significant increase in gastric and duodenal lesions. Of the preparations studied, OSS was associated with the greater number of gastroduodenal lesions, while PEG was the least associated with lesions with an occurrence similar to the non-prep group. The clinical significance of these lesions remains undetermined.

Cloud computing has become a widespread technology due to ICT advancements. It allows businesses to move and take advantage of the pay-as-you-go price model. Enterprises pay for what they use and don't have to buy, setup, or maintain resources. However, outsourcing core resources such as storage, servers, operating systems, and software applications from a third party needs careful decisions to take advantage of cloud facilities. Choice of appropriate service provider, deployment and service model must be aligned with business needs and goals. In this paper, we will present cloud computing benefits, cloud deployment methods, services, state-of-the-art migration methods, tools and techniques and will conclude with the role of SDN in cloud computing.

Abstract: New paradigms have emerged in mapping since the 20th century due to theoretical and practical advances in computer technology, communications, and cartography. For the design of the Expert-Topographic Map Service in Mexico, we adopted a theoretical framework of Cybercartography and expanded to incorporate expert systems and eventually other artificial intelligence resources. Using a transdisciplinary approach, our efforts could focus on the interconnection between knowledge and geotechnology to offer solutions to societal complex problems. This paper explores the theoretical pillars supporting the design of an Expert-Topographic Map Service, including cybercartography, knowledge-based systems and surface mathematical modeling. For the first time, cybercartography is applied in the realm of topographic mapping. As shown, a map conceived solely as an information system has been transformed, in the digital era, into a container of knowledge through the abstract representation of features like relief via the Triangular Irregular Network Model. Thereby, we can bridge from digital topographic maps to other knowledge-based models such as expert systems. The societal demand and empirical context for this research demonstrate that topographic maps and services are still at the core of cartographic initiatives in the 21st century.

Gold nanoparticles (NPs) are among the most commonly employed metal NPs in biological applications, with their distinctive physicochemical features. Their extraordinary optical properties, stemming from the strong localized surface plasmon resonance (LSPR), contribute to the devel-opment of novel approaches in the areas of bioimaging, biosensing, and cancer research, especially for photothermal and photodynamic therapy. The ease of functionalization with various lig-ands provides a novel approach to the precise delivery of these molecules to targeted areas. Gold NPs ability to transfer heat and electricity positions them as valuable materials for advancing thermal management and electronic systems. Moreover, their inherent characteristics, such as in-ertness, give rise to the synthesis of novel antibacterial and antioxidant agents as they provide a biocompatible and low-toxic approach. Chemical and physical synthesis methods are utilized to produce gold NPs. The pursuit of more ecologically sustainable and economically viable large-scale technologies, such as environmentally benign biological processes referred to as green/biological synthesis, has garnered increasing interest among global researchers. Green synthesis methods are favorable among other synthesis techniques as they minimize the necessity for hazardous chemicals in the reduction process due to their simplicity, cost-effectiveness, energy efficiency, and biocompatibility. This article discusses the importance of gold NPs, their optical and conductivity properties, antibacterial, antioxidant, and anticancer properties, synthesis methods, contemporary uses, and biosafety, emphasizing the need to understand toxicology principles and green commercialization strategies.

Polo-Like Kinase-1 (PLK1) is a key regulator of the G2/M cell cycle and has been linked to treatment resistance in prostate cancer (PCa). This study aimed to explore the correlation between PLK1 expression, determined through RNA-seq analysis, and clinical outcomes in PCa patients. We analyzed tumor samples from 452 patients diagnosed with prostate adenocarcinoma between 2014 and 2020, sourced from nine institutions affiliated with the Oncology Research Information Exchange Network (ORIEN). PLK1 expression levels were determined using RNA-seq data and stratified into high (≥75th percentile) vs. low (<75th percentile) expression. Univariate and multivariate Cox proportional hazard models compared overall survival between patients with low vs. high PLK1 expression, adjusting for age, race, PSA, and stage. Of the 452 tumors, 241 (53.3%) had high PLK1 and 211 (46.7%) had low PLK1 expression. Median follow-up was 2.74 years for low PLK1 and 2.71 years for high PLK1. No significant difference in overall survival was observed between low and high PLK1 groups in univariate (p=0.86; HR 1.09) or multivariate (p=1.0; HR 0.99) analyses. This study found no association between RNA-seq-based PLK1 expression and prognosis in PCa. PLK1 expression is not a prognostic marker for prostate cancer.

Cisplatin (CDDP) remains a key drug for patients with advanced bladder cancer (BC), despite the emergence of new therapeutic agents. Identifying factors contributing to treatment resistance to CDDP is crucial. The acidity of the tumor microenvironment has been reported to be associated with treatment resistance and poor prognosis across various cancer types. Our objective was to investigate the effects of an acidic environment on BC cells and elucidate the mechanisms behind CDDP resistance. Our findings show that BC cells cultured in acidic conditions developed resistance to cisplatin as acidity increased. Notably, CDDP administered to BC cells in a pH 6.0 environment required twice the concentration compared to pH 7.5 to achieve equivalent toxicity. Using chloroquine and navitoclax, we identified the involvement of Bcl-2 and LC3B pathways in the acquisition of CDDP resistance under acidic conditions. Western blot analysis revealed that the activation of Bcl-2 and XIAP expression appears to inhibit both apoptotic and autophagic cell death. These results suggest that alleviating the acidity of the tumor microenvironment in clinical settings might enhance BC sensitivity to CDDP.

Reliable prediction of building-level energy demand is crucial for the building managers to optimize and regulate energy consumption. Conventional prediction models omit the uncertainties associated with demand over time; hence, they are mostly inaccurate and unreliable. In this study, a Bayesian neural network (BNN)-based probabilistic prediction model is proposed to tackle this challenge. By quantifying the uncertainty, BNNs provide probabilistic predictions that capture the variations in the energy demand. The proposed model is trained and evaluated on a subset of the building operations dataset of Lawrence Berkeley National Laboratory (LBNL), Berkeley, California, which includes diverse attributes related to climate and key building performance indicators. We have performed thorough hyperparameter tuning and used fixed-horizon validation to evaluate trained models on various test data to assess generalization ability. To validate the results, quantile random forest (QRF) was used as a benchmark. The study compared BNN with LSTM, showing that BNN outperformed LSTM in uncertainty quantification.

Parkinson's disease (PD) is the second most common neurodegenerative disorder, entailing several motor-related symptoms that contribute to a reduced quality of life in affected subjects. Recent advances in wearable technologies and computing resources have shown great potential for the assessment of PD-related symptoms. However, the potential applications (e.g., early diagnosis, prognosis and monitoring) and key features of digital biomarkers for motor symptoms of PD (DB-MS-PD) have not been comprehensively studied. This study aims to provide a state-of-the-art review of current digital biomarker definitions for PD, focusing on the use of wearable devices. This review systematically examines research articles from 2012 to 2024, focusing on key features and recent technologies in PD research. A total of 22 studies were included and thoroughly analyzed. Results indicate that DB-MS-PD can accurately distinguish patients with PD (PwPD) from healthy controls (HC), assess disease severity or treatment response, and detect motor symptoms. Large sample sizes, proper validation, non-invasive devices, and ecological monitoring make DB-MS-PD promising for improving PD management. Challenges include sample and method heterogeneity and lack of public datasets. Future studies can leverage evidence of the current literature to provide more effective and ready-to-use digital tools for monitoring PD.

Multifunctional coatings based on Sn-Ni materials with and without titanium oxide nanoparticles (TiO2NPs) incorporation were prepared using the electrochemical deposition technique at 70°C. TiO2NPs were dispersed in the electrolyte bath, and their influence on both surface texture, crystalline phase, and properties was investigated. Various techniques such as X-ray phase analysis (XRD), scanning electron microscopy (SEM), and energy dispersive X-ray microanalysis (EDX) were used to characterize the prepared coatings. The anti-corrosion effectiveness of the coatings was assessed using potentiodynamic polarization curves and electrochemical impedance spectroscopy in an artificial sweat medium, while the bactericidal activity of the composite coatings (the ability to induce cell death) was evaluated in accordance with ISO 27447:2009 test. The influence of the TiO2NPs on the composition, structure and properties of the deposited coatings was established. Particular attention was paid to the relationship between the anticorrosive and bactericidal properties of the coatings and their structure and composition. The synergistic effect of the various properties was investigated and discussed.

This paper explores the application of machine learning (ML) in predicting functional recovery in patients with ischemic stroke. As technology advances, ML shows significant potential in the field of stroke medicine, especially in the areas of big data analytics and personalized medicine. Studies have shown that ML algorithms can improve the accuracy of stroke image analysis, subtype classification, risk assessment, treatment guidance, and prognosis prediction. However, the widespread use of ML still faces challenges such as data standardization, model validation, privacy, and bias. This paper reviews the current application status of ML in the field of stroke, discusses the challenges faced, and looks forward to the future development direction, aiming to promote the practical application of ML technology in the diagnosis and treatment of stroke to improve the prognosis and quality of life of patients.

Graph query languages such as Cypher are widely adopted to match and retrieve data in a graph representation, due to their ability of retrieving and transforming information. Despite the most natural way to match and transform information is through rewriting rules, those are scarcely or partially adopted in graph query languages. Their inability of doing so has a major impact on the subsequent way the information is structured, as it might then appear more natural to provide major constraint over the data representation so to consequently constraint the way the information should be represented. On the other hand, recent works are starting to move towards an opposite direction, as the provision of a truly general semistructured model (GSM) allows to both represent all the available data formats (Network-Based, Relational, and Semistructured) as well as support an holistic query language expressing all major queries in such languages. In this paper, we show that the usage of GSM enables the definition of a general rewriting mechanism which can be expressed in current graph query languages only at the cost of adhering the query to the specificity of the underlying data representation. We formalise the proposed query language in terms graph rewriting mechanisms described as a set of production rules $L\to R$ while providing restriction to the characterization of L, while extending it to support structural graph nesting operations, useful to aggregate similar information around an entry-point of interest. We discuss how GSM, by fully supporting index-based data representation, allows for a better physical model implementation leveraging the benefits of columnar database storages. Preliminary benchmarks shows the scalability of this proposed implementation in comparison with state-of-the-art implementations.

Papillomaviruses (PVs) are oncogenic and infect the skin and mucosa of various host species. Considering the recent advances in research on PVs using rolling circle amplification (RCA) followed by high-throughput sequencing (HTS), in this study, we aimed to investigate the bovine papillomavirus (BPV) types associated with proliferative lesions in the upper alimentary tract of an affected bull and characterize the viral strains through complete genome sequencing using this strategy. We analyzed the PV strains associated with two hyperplastic esophageal lesions through PCR using degenerate primer pairs and RCA, followed by HTS. HTS of the libraries generated using RCA products provided the whole genome sequence of BPV4 present in squamous papilloma, whereas, the complete genome sequence of BPV2 and subgenomic fragments of BPV4 were identified in carcinoma in situ (CIS). We, for the first time, have sequenced BPV2 identified from the CIS of the bovine upper alimentary canal. Additionally, RCA followed by HTS allowed characterization of the mixed infection by BPV2 and BPV4 in this lesion. These data reveal that BPV4 is not the only BPV type present in CIS of the esophageal mucous membrane; moreover, a mixed infection caused by BPV2 and BPV4 at the tested anatomical site was demonstrated.

This study contributes to the Sybil nodes detecting algorithm in Online Social Networks (OSNs). As major communication platforms, online social networks get significantly guarded from malicious activity. A thorough literature review identified various detection and prevention Sybil attack algorithms. Additional exploration of distinct reputation systems and their practical application led to the study’s discovery of machine learning algorithms, i.e., the KNN, Support Vector Machines, and Random Forest algorithms. The study details the data cleansing process for the employed dataset in its process for optimizing the computational demands required to train machine learning algorithms, achieved through dataset partitioning. Such a process led to explaining and analysis of conducting experiments and comparing their results. Such experiments demonstrate the algorithm’s ability to detect Sybil nodes in OSNs (100% accuracy in SVM, 99.6% in Random Forest, and 97% in KNN algorithms); thus concluding by proposing future research opportunities.

Using polymethylmethacrylate (PMMA) bone cement is widespread in orthopedic surgeries for implant fixation and as a carrier for antibiotic delivery to prevent and treat infections. This review comprehensively evaluates in vitro studies investigating the antibiotic elution profiles and mechanical properties of PMMA bone cement. We explore the kinetics of antibiotic release, factors influencing elution efficiency, and the impact of various antibiotics on the mechanical properties of PMMA composites. At the same time, we examine how the inclusion of antibiotics affects the mechanical integrity of PMMA, including parameters such as compressive strength, tensile strength, and fatigue resistance. Through a detailed analysis of these studies, this review aims to provide insights into optimizing PMMA bone cement formulations for enhanced therapeutic efficacy and structural performance.

Lymphadenopathy is a common manifestation of both reactive and malignant diseases, and fine needle aspiration (FNA) is an effective and inexpensive screening method. It can prevent unnecessary invasive surgery and excisional biopsy, especially in benign cases. Unfortunately, the lack of universally accepted terminology for reporting results has hindered its widespread support. The Sydney system proposal for lymph node cytopathology categorization and reporting introduced five diagnostic categories to address the lack of universally accepted terminology for reporting results in lymphadenopathy. Our study analyzed 188 lymph node FNC samples from King Abdulaziz University Hospital, Saudi Arabia, examining clinical follow-up data, pathology records, patient information, and final diagnosis from January 2019 to December 2022. Most specimens were from axillary LNs, with 99.5% tissue correlation. The Sydney System Category classification identified 56.9% of cases as malignant, while 26.1% were benign. The final surgical specimen diagnosis revealed a higher percentage of malignant diagnoses, with the highest ROM in malignant/Category V. In conclusion, our study demonstrates that LN-FNAC offers high diagnostic accuracy for LN aspirates, with the Sydney approach potentially aiding risk stratification and achieving consistency in cytologic diagnosis, but further multi-centric research is needed.

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

In the knowledge era, intellectual capital has been considered a key factor in creating value within organisations. This study examines the relationships and interactions between the components of intellectual capital and the profitability of Panamanian banking, and financial institutions listed on the Latin American Stock Exchange (LATINEX) from 2014 to 2020. Utilising the Valued-Added Intellectual Coefficient (VAIC)™ model, which evaluates the intellectual capital of organisations based on information from financial statements, the study constructs a regression model to examine the relationship between the Return on Equity (ROE) and the components of the VAIC™. The findings confirm the study’s hypothesis, demonstrating that the Structural Capital Efficiency (SCE) and company size (SIZE) variables explain 57% of the variance in ROE for the analysed institutions. The results suggest that the Intellectual Capital (IC) of financial sector institutions listed on LATINEX is significantly influenced by the SCE coefficient, which shows a negative relationship, suggesting that investment in structural capital does not enhance profitability. On the other hand, larger institutions exhibited higher profitability during the study period.

The paper explores using generative artificial intelligence (AI) in financial market data management and forecasting. By integrating multiple data sources and feature extraction techniques, such as fundamental analysis, technical indicators, global economic data, and sentiment analysis, generative AI constructs a comprehensive deep learning framework that significantly enhances financial data management efficiency and market forecasts' accuracy. Specifically, technologies like generative adversarial networks (Gans) and variational autoencoders (VAE) demonstrate substantial data augmentation and model optimisation potential. The application value of the model in real-time market prediction and trading strategy optimization is further amplified through reinforcement learning methods.

In the past twenty years, the IT industry has moved away from using physical servers for workload management to workloads consolidated via virtualization and, in the next iteration, further consolidated into containers. In the next step, container workloads based on Docker and Podman as underlying container technologies were orchestrated/automated via Kubernetes or OpenShift. On the other hand, high-performance computing (HPC) environments have been lagging in that process, as there’s still much work to figure out how to apply containerization platforms for HPC in real-life scenarios. Kubernetes and OpenShift have many advantages – generally speaking, container technologies use quite a bit less overhead from the computing perspective while providing many benefits in flexibility, modularity, and maintenance. Therefore, they are ideal for tasks requiring a lot of computing power. There are also some tradeoffs regarding the complexity of these two platforms - they’re just not that user-friendly when used by people without years of experience managing them. In this paper, we propose a different architecture based on seamless hardware integration and user-friendly, dynamic workload placement based on real-time performance analysis and prediction coupled with Machine Learning-based scheduling.

Intermittent fasting (IF) has been indicated as a valuable alternative to the classical caloric restriction dietary regimen for lowering body weight and preventing obesity-related complications such as metabolic syndrome and type II diabetes. However, is it effective? In this review article, we analyzed over 50 clinical studies in which IF, conducted by alternate day fasting (ADF) or time-restricted feeding (TRF), was compared with the caloric restriction approach. We evaluated the different roles of IF in treating and preventing human disorders such as metabolic syndrome, type II diabetes, and some types of cancer, as well as the usefulness of IF in reducing body weight and cardiovascular risk factors such as hypertension. Furthermore, we explored the cellular pathway targeted by IF to exert their beneficial effects by activating effector proteins that modulate cell functions and resistance to oxidative stress. In contrast, we investigated the concerns for human health related to the adoption of IF dietary regimen, highlighting the profound debate on weight loss regimens. We have examined and compared several clinical trials to formulate an updated conception regarding IF and its therapeutic potential.

The prevalence of diabetes mellitus (DM) continues to rise globally, posing significant health challenges and burdens. This metabolic disorder, characterized by elevated blood glucose levels, contributes to various complications including cardiovascular diseases, kidney failure, and stroke. While conventional diabetic drugs exist, they often come with adverse side effects, necessitating the exploration of safer and more cost-effective alternatives, particularly from natural sources like medicinal plants. This study investigates the potential of Neocarya macrophylla (Nm) Ethyl acetate leaf fraction in managing DM. Utilizing a high-fat diet/streptozotocin-induced diabetic rat model, the study explores several key aspects including effective dose determination, biological activity, impact on body mass index (BMI), and complete blood count. Statistical analysis was conducted using GraphPad Prism version 9.1. The determination of the minimum effective dose reveals that 120mg/kg of Ethyl acetate fraction of Nm reduced the blood glucose by 28.9% after 4 hours. In addition, ethyl acetate fraction (120 mg/kg) possessed the most hypoglycemic activity compared to the other fractions of Nm. The Ethyl acetate fraction of Nm at 120mg/kg significantly reduced fasting blood glucose levels compared to the diabetic control(p=0.001) and slightly decreased BMI. Furthermore, the fraction demonstrated significant improvement in the parameters of some of the blood count indices such as red blood cells (p<0.001), total white cells (p<0.01) and platelet (p<0.001) compared to the diabetic control. These findings underscore the potential of Nm as a holistic therapeutic option for managing DM and its haematological complications. In conclusion, this study sheds light on the hypoglycemic potential of Nm Ethyl acetate leaf fraction, offering valuable insights into its effectiveness, safety, and broader physiological impacts. Further research into the mechanisms underlying its therapeutic effects is warranted to fully harness its therapeutic potential in diabetes management.

The high dependence on light crude oil as the main source of energy in automobiles., industrial processes, source of raw material for various industrial synthesis have made the heavy crude more available in the world and open for research work on its potentials as a source of energy for the increasing population of the world in areas like energy source for powering big marine engines, energy source in heavy industrial machines e.t.c. Though the relatively unfavourable characteristics of heavy fuel oil such as; high viscosity, high probability of precipitating is a reasonable challenge to the possible utilization of heavy fuel as a source of energy in the areas highlighted above. These issues of heavy fuel oil are largely due to the presence of Asphaltene in it which is a large complex hydrocarbon in heavy fuel oil. Understanding the combustion potential of asphaltene is therefore an interesting and challenging problem that has attracted increasing attention from both academia and industry. This research work is aimed at carrying combustion studies on the Forcados (Ni-geria) heavy fuel fraction asphaltene HFFA extracted from Forcados crude Oil and examining its combustion characteristics with the view to examine it for future sweet heavy fuel generation for it source got low sulphur content, to ascertain the volatile composition, moisture and ash content. The HFFA extracted to determine physical characteristics of the HFFA extracted for fuel properties potentialities and this study was carried out to evaluate the chemical constituents of forcadous asphaltene lead-ing to the generaration of HFFA using GCMS. The Forcados asphaltene showed some good fuel properties when subjected to ce-tane number, API gravity, flash point and cloud point parameter test. Probing further with AAS for trace metal presence showed some high concentration on Chromium (Cr), Nickel (Ni), Iron (Fe), Lead (Pb), Cadmium (Cd), Copper (Cu), Manganese (Mn) and Zinc (Zn) indicating the potential for residual and soot formation after combus-tion. But still being a sweet asphaltene from Nigerian sweet crude source will be de-void of corrosive effect on machineries and heavy fuel engine if used to power it as in the case of high sulphur content in Venezuelan crude oil and some other world. The GCMS showed the decomposition of heavy crude asphaltene peaks and sig-naling the presence of heavy fuel fraction in the composition of the asphaltene while the FTIR and the UV-VIS identified the various functional groups in the compounds and the identification of signals that cannot be seen in the normal spectrum respec-tively.

The increased prevalence of obesity worldwide has been implicated for the alarming rise of the incidence of gestational diabetes and preeclampsia as well, both considered as threatening conditions for both mother and fetus. We studied gene polymorphisms of the proinflammatory cytokine Interleukin 6 (IL-6) and the gene expression levels of VEGF and VEGF-receptor all known to be involved in pregnancy complications aiming to identify possible predisposing risk factors in pregnancies with obesity. G allele of IL-6 was found to correspond with an increased risk for gestational diabetes and preeclampsia occurrence. Furthermore, in obese pregnant mothers with either gestational diabetes or pre-existing type 2 diabetes and to those developed preeclampsia it was confirmed that gene expression levels of VEGF were reduced while they were increased for VEGF receptor. We conclude that the genetic profile of the obese pregnant woman shares a common background with that of a pre-existing type 2 diabetes mellitus and therefore predisposes to complications in pregnancy.

Based on our recent thermodynamic formulation of the Friedmann equation, we demon- strate how the age of the universe must be approximately 14.6 billion years. This is about 800 million years older than predicted by the Λ-CDM model and therefore greatly alleviates the early galaxy formation problem.

Since the 1970s, the usefulness of nailfold capillaroscopy (NFC) in the diagnosis of rheumatological disorders such as systemic sclerosis has been well known, and further studies also showed that NFC can detect non-rheumatic diseases such as diabetes, glaucoma, dermatitis, Alzheimer disease, and so on. In the past decade, the morphological changes in the nailfold capillary have been also reported in the unhealthy lifestyle habits such as smoking, inappropriate diets, sleep shortage, and even psychological stress which presents slow blood flow. Therefore, study in the relationships between the morphology of nailfold capillaries and lifestyle habits has high potential to understand the unhealthy state, or even predict the pre-disease condition. So, simple, inexpensive, and non-invasive methods such as NFC are constantly needed for routine health checkups. Thus, we undertook a systematic search in PubMed database, and summarized the studies reporting the assessment of morphological NFC in order to undertake a comprehensive review on the usefulness of NFC not only in clinical diagnosis, but also in unhealthy dietary lifestyle improvements. Here in this review paper, we finally summarized the dietary and lifestyle health promotion strategy judging from NFC- and the other relating-measurement from the viewpoint of healthy microvascular blood flow and endothelial function.

The design of a mixed-mode proportional-integral-derivative (PID) controller circuit using current-feedback operational amplifiers (CFOAs) as active components is proposed. With the same circuit topology, the proposed configuration of three CFOAs, four resistors, and two capacitors is capable of performing the PID controller in all four operation modes: namely voltage mode, trans-admittance mode, current mode, and trans-impedance mode. Numerous mathematical analyses are conducted to determine the controller performance under ideal and non-ideal conditions. Additionally, the mixed-mode second-order lowpass filter is suggested, and also used to examine the workability of the proposed mixed-mode PID controller in a feedback control structure. The proposed PID controller is implemented with the commercially available IC-type CFOA AD844, and the simulation results are presented to illustrate the functionality of the controller and its closed-loop control system.

Cervical cancer is one of the ailments that endangers the health of women all over the world and causes infertility. Fortunately, this disease can be avoided. Both the results and participation rates of the current preventative strategy remain poor. Hence, preventative or early detection methods remain challenging and open. In gynecology and computer science fields, few studies on identifying cervical cancer are based on behavior risk factor and machine learning. Moreover, various social and behavioral aspects might often make it more difficult to detect cervical cancer especially in low‑ and middle‑income countries (LMICs). Accordingly, focus on predicting the presence of cervical cancer through behavioral risk factors is the basic structure of this research. We proposed an approach to classify cervical cancer from a social-behavioral perspective using logistic regression to predict cervical cancer. We got significantly improved outcomes than the existing methods. Moreover, we used feature engineering to formulate less dimensionality as a pre-processing step and optimized parameters to be prepared for classification phase. The results proved that using the logistic regression with regularization type L1 had a promising performance. The accuracy of Logistic Regression (LR) L1 was 97.2%. Such results support the proposed work as a reliable classification predictive tool.

Objective: Mechanical bowel preparation is essential for the visualisation of the colon during colonoscopy, and previous studies have identified changes in gut microbiota composition after bowel preparation and colonoscopy. Considering the gut microbiota is increasingly implicated in mood, we aimed to explore the potential impact of this intervention on mood and the microbiota-gut-brain axis. Methods: We conducted a pre-post intervention study, with timepoints of one week before and one month after bowel preparation and colonoscopy, in community-dwelling adults referred for colonoscopy. Our primary outcome was change in average Hospital Anxiety and Depression Scale depression sub-scores using generalised estimating equations. We also examined changes in average anxiety, stress, and quality of life scores, and faecal microbiota composition and potential function using 16S rRNA sequencing. We further explored associations between changes in depressive symptoms and the gut microbiota and conducted post-hoc analyses to explore potential effect modifiers. Key Results: 59 participants were included in the analyses. Depressive symptoms decreased one-month post-procedure compared to baseline (adjusted β=−0.64; 95%CI: −1.18, −0.11). Irritable bowel syndrome (IBS) appeared to moderate this relationship (1.78; 0.292, 3.26); depressive symptoms increased in those with, and decreased in those without, IBS. Changes in gut microbiome composition included reduced alpha diversity, modest effects on beta-diversity, and increases in genera associated with potential health benefits, one-month post-procedure compared to baseline. Increases in the CLR-transformed abundance of Ruminococcaceae UCG-009 were associated with improvements in depressive symptoms. Conclusions: There is preliminary evidence of a potential mental health effect of bowel preparation and colonoscopy, which may be associated with changes to the gut microbiota. There may also be a differential mental health impact of this procedure for those with and without IBS. Considering the limitations of our study, further research is required to confirm these findings and their clinical relevance.

The Sei Dareh Bridge is a cable-stayed bridge located in West Sumatra Province, Indonesia. The bridge, which crosses the Batanghari River, has a main span of 123 meters long and 9 meters wide. Traffic load is transmitted through 24 prestressed cables to a 42.4-meter-high pylon made of concrete. The bridge deck and traffic loads are directly supported by steel box girders as main beams that are reinforced laterally with cross beams IWF 800.300.16.24 and stringers IWF 350.350.12.19. This paper discusses static and dynamic testing on the bridge which aims to assess its feasibility before it is opened to the public. Based on the test, it was concluded that a static load of 73% could not be achieved because the deflection that occurred was beyond the allowable deflection. This is exacerbated by a loud clanging sound on the ST2-X1 prestressed cable when loading to 240 tons or 58% of the targeted load. In addition, this bridge is included in the "lazy bridge" category because it takes 24 hours to return to an undeformed condition after loading. As a recommendation for this bridge, it is necessary to carry out a structural health monitoring system (SHMS) regularly on bridge slabs and cables.

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

For the first time, this study identified seven potential ligands with high binding energies through the docking approach against the Crystal Structure of human Melanoma-associated antigen B1 (MAGEB1). The ligands—Imatinib, Bafatinib, Diosmin, Ginkgetin, Bilobetin, Amentoflavone, and Hypericin—showing strong binding energies around -10 kcal/mol, indicate a potentially robust interaction with the target protein. Moreover, the additional step of predicting toxicity properties using the pKCSM server provides valuable insights into the safety profiles of these ligands. From these results, the parameters for Diosmin: —Max. tolerated dose (human),- Oral Rat Acute Toxicity (LD50), and - Oral Rat Chronic Toxicity (LOAEL)—suggest a favorable safety profile, making it a potential candidate for further consideration against Melanoma. Moving forward, it's advisable to conduct further experimental validations, including in vitro and in vivo studies, to confirm the efficacy and safety of Diosmin and other potential ligands. Consideration of pharmacokinetics, metabolism, and specific mechanisms of action will contribute to a comprehensive understanding of these compounds' potential as therapeutic agents.

The evolutionary theory of aging, particularly antagonistic pleiotropy (AP), provides an account of the ultimate origins of aging. What remains unclear is the nature of the proximate mechanisms by which AP gives rise to diseases of aging, like cardiovascular disease and Alzheimer’s disease. Damage-centric theories focusing on loss of genetic and cellular function have been proposed, as well as programmatic theories focusing on unwanted gene and cellular function. The latter include the hyperfunction and developmental theory that view aging as the futile continuation, or run-on, of growth and developmental programmes into later life. Yet neither type of theory has performed well in explaining late-life disease aetiology, particularly with respect to disease onset, presentation and progression. What is proposed here in this review is a new programmatic theory of aging. We argue that the emergence of many specific diseases may involve quasi-programmes that are not the result of run-on, but rather are triggered by other factors in late life. Such triggers may be non-programmatic (e.g. infection, mechanical injury) or programmatic. Moreover, the consequent pre-pathological and pathological changes may in some cases trigger further changes, leading to futile and destructive cascades of quasi-programmes and pathology. The origins of triggered quasi-programmes can be traced to biological constraint i.e. the inability of organisms to optimise all functions at once. And, to some extent, the new theory presented here revises the understanding of AP. That is, because any gene can be triggered in an erroneous manner, every gene is potentially an AP gene that risks pathology, though level of risk varies according to constraint. To help validate the theory, we test it against several complex diseases of aging. The new model in this review attempts to provide a blueprint understanding that, to a certain extent, closes the gap in the causal chain of events between evolutionary causes of aging and the aetiology of age-related diseases. It also helps to explain why certain disorders mimic accelerated aging and how interventions, such as the suppression of IIS and mTOR retard many aspects of aging; notably, though, unlike prior programmatic theories, the new theory is not mTOR-centric. Finally, it provides new perspectives on possible treatment of aging.

Dirac's Large Number Hypothesis (LNH), proposed in 1937, has captivated the scientific community with its exploration of profound correlations between cosmic and atomic scales. This hypothesis delves into the intricate interplay between the infinitesimally small and the vastly large, offering potential insights into the fundamental nature of the universe. As we continue to uncover the mysteries of the cosmos, the LNH oscillates on the precipice of scientific acceptance—neither fully validated nor entirely dismissed. In this review paper, we embark on a comprehensive journey through Dirac's LNH, shedding light on its theoretical underpinnings, its implications for universe models, and its resonance with the Anthropic Principle. We delve into the possibilities of variable gravitational constants and continuous mass creation, inviting further exploration into the intricacies of our cosmic symphony. By embracing the ongoing quest for understanding, we endeavor to unravel the profound harmonies that connect the infinitesimal with the infinite, contributing to the symphony of knowledge in theoretical physics and cosmology.

This study aimed to find alternative feeds or supplementary feeds that can perform similarly to the existing commercial feeds thereby reducing farmer expense and cutting down their cost of production and increasing their profitability. The formulations for the study included four grow-out treatments mainly: control (commercial feed), taro+control (powdered Colocasia esculenta+commercial fish feed), bloodmeal (formulated fish feed based on bloodmeal), banana stem+control (chopped banana stem+commercial fish feed). A total of 12,000 fingerlings initially weighing 16 g (TL=10 cm) individually were assigned randomly to the four treatments (3000 in each cage measuring 6 x 6 m). The result of the study showed no significant differences between feed treatments from 6^th week onwards, whether with weight [MS=0.130, df=3, F=1.14, P=0.333] or total length of the treatments [MS=0.008, df=3, F=0.40, P=0.75]. The FCR ratio showed bloodmeal (1.60) as lowest, followed by the control (1.65), and taro+commercial (1.71) and then banana stem+commercial (2.18). In terms of weight gain, fish from the bloodmeal treatment gained the highest (236.97 g), followed by control (223.33 g), then taro (217.67 g) and banana stem (196.99 g). As a result, we find that any of the tested treatments can serve as an alternative feed to using purely commercial fish feeds. Cost-benefit analysis showed that a better gross profit margin of 42% and cost-benefit ratio of 1.37 was observed in taro+commercial feed diet.

Water stable proteins may offer a new field of applications in smart materials for buildings and infrastructures where hydraulic reactions are involved. In this study, cement mortars modified through water-soluble silk fibroin (SF) are proposed. Water-soluble SF obtained by redissolving SF films in phosphate buffer solution (PBS) showed the formation of a gel with β-sheet features of silk II. Electrical measurements on SF indicate that calcium ions are primarily involved in the conductivity mechanism. By exploiting the water solubility properties of silk II and Ca2+ ion transport phenomena and its trapping effect over water molecules, SF provides piezoresistive and piezocapacitive properties to cement mortars, thus enabling self-sensing of mechanical strain which is quite attractive in structural health monitoring applications. SF/cement-based composite introduces the capacitive gauge factor that surpasses the traditional resistive gauge factor reported in the literature by threefold. Cyclic voltammetry measurements demonstrated SF cement mortars possess memcapacitive behavior for positive potentials around +5 V, attributed to an interfacial charge build-up modulated by the SF concentration and the working electrode. Electrical square-biphasic excitation combined with cyclic compressive loads revealed memristive behavior during the unloading stages. These findings along with the availability and the sustainability of SF pave the way for the design of novel multifunctional materials, particularly for applications in masonry and concrete structures.

Autonomous Underwater Vehicles (AUVs) are highly efficient tools for underwater exploration, capable of carrying various payloads to perform specific missions as needed. To ensure the success of these missions and the spatiotemporal accuracy of sampled data, integrated navigation systems and appropriate filtering algorithms are essential. These systems process and merge motion data to provide accurate positioning information. The most commonly used algorithms in integrated navigation systems are Kalman filter and its nonlinear derivatives. Of these, the ensemble Kalman filter (EnKF) is particularly notable for its ability to handle nonlinear systems by incorporating Monte Carlo methods. This study proposes an enhanced adaptive EnKF algorithm to improve the smoothness and accuracy of the filtering process. Instead of the conventional Gaussian distribution, this algorithm employs a Laplace distribution to construct the system state vector and observation vector ensembles, enhancing stability against non-Gaussian noise. Additionally, the algorithm dynamically adjusts the number of vector members in the ensemble using adaptive mechanism by specifying thresholds during filtering, to adapt the requirements of real-world observational settings. Using measured data from field trials, including DVL, GPS, and electronic compass data, we examine the effects of various parameter settings on the algorithm's performance. Optimal parameter settings are identified to fine-tune and verify the filtering algorithm as well as its adaptive capability. The results demonstrate that the enhanced adaptive EnKF algorithm exhibits superior filtering performance in terms of both accuracy and smoothness compared to the conventional EnKF and EKF algorithms. This indicates the significant advantages of our proposed algorithm for AUV navigation.

Breathing in fine particulate matter with diameters less than 2.5 µm (PM_2.5) has greatly increased an individual’s risk of cardiovascular and respiratory diseases. As climate change progresses, extreme weather events, including wildfires, are expected to rise, exacerbating air pollution. The 2023 Canadian wildfires highlighted the growing threat of PM_2.5 as smoke spread across U.S. cities like New York, Philadelphia, and Washington D.C. This research investigates the application of data augmentation techniques to improve the accuracy of PM_2.5 concentration forecasts in these urban environments. Models trained on imbalanced datasets often struggle to capture extreme pollution events, underestimating high PM_2.5 levels due to the model’s focus on more frequent, low-value samples. To address this, we implemented cluster-based undersampling and trained transformer models using various cutoff thresholds (12.1 µg/m³ and 35.5 µg/m³) and partial sampling ratios (10/90, 20/80, 30/70, 40/60, 50/50). Our results demonstrate that the 35.5 µg/m³ threshold, coupled with a 20/80 partial sampling ratio, provides the best performance regarding RMSE and R², particularly in capturing high PM2.5 events. Overall, models trained on augmented data significantly outperformed those trained on original data, highlighting the importance of resampling techniques in improving air quality forecasting accuracy, especially for high-pollution scenarios. These insights significantly contribute to a better understanding of PM_2.5 pollution with the hopes of more informed public health and environmental policies.

Living systems are capable on the one hand, of eliciting a coordinated response to changing environment (aka adaptation) and on the other hand, they are capable of reproducing themselves. Notably, adaptation to environmental change requires the monitoring of the surroundings, while reproduction requires monitoring oneself. These two tasks appear separate and making use of different sources of information. Yet both the process of adaptation as well as that of reproduction are inextricably coupled to alterations of genomic DNA expression, while a cell behaves as an indivisible unity in which apparently independent processes and mechanisms are both integrated and coordinated. We argue that at the most basic level, this integration is enabled by the unique property of the DNA to act as a double coding device harboring two logically distinct types of information. We review biological systems of different complexity and infer that inter-conversion of these two distinct types of DNA information represents a fundamental self-referential device underlying both systemic integration and coordinated adaptive response.

Background: Previous studies have highlighted that copper supplementation at 200% of the recommended daily dietary allowance modified vascular contraction and relaxation through increased reactive oxygen species (ROS) and prostaglandin formation, which modified the antioxidant status of middle-aged Wistar rats. Methods: In this study, young (1 month old) male Wistar rats (n/group = 10) received a diet supplemented with 6.45 mg copper/kg (100% of daily recommendation—Group A) for 8 weeks. The experimental group received 12.9 mg copper/kg of diet (200% of the daily recommendation—Group B). Results: Experimental supplementation with 200% copper modified the copper concentration in the blood (1.21-fold, p = 0.04), liver (1.15-fold, p = 0.032), and kidneys (1.23-fold, p = 0.045), potentiated the ROS formation in the aortic rings, and enhanced the sensitivity of the aortic rings to the vasodilator acetylcholine. We observed an increased participation of nitric oxide (NO) derived from inducible NO synthase (iNOS) in vascular contraction and a decreased net effect of vasodilator prostanoids derived from cyclooxygenase-2 in vascular relaxation. In rat kidneys, the concentrations of potassium (1.08-fold, p = 0.001) and iron (1.13-fold, p = 0.046) were higher, while, calcium (0.88-fold, p = 0.001) and chromium (0.77-fold, p = 0.005) concentrations were lower. In the rat liver, magnesium (1.06-fold, p = 0.012) was higher. No differences were observed in the concentrations of sodium, zinc, manganese, selenium, cobalt, molybdenum, and vanadium. The antioxidant activity of water- and lipid-soluble compounds; total antioxidant status in the blood; and superoxide dismutase, catalase, and malondialdehyde levels in the heart did not change. Conclusions: In young rats, prolonged supplementation with 200% copper had a lesser effect than anticipated on oxidative stress and vascular reactivity. Detailed data on the status of trace elements and their interactions in patients of different age groups are strongly required for effective nutritional and therapeutic intervention.

The Notch signaling pathway plays a major role in embryological development and in the ongoing life processes of many animals. Its role is to provide cell-to-cell communication in which a Sender cell, bearing membrane -embedded ligands, instructs a Receiver cell, bearing membrane- embedded receptors, to adopt one of two available fates. Elucidating the evolution of this pathway is the topic of this paper, which uses an orthologs approach to build a firm base for such a study. Using BLAST searches, orthologs were identified for all of the 49 listed components of the Notch signaling pathway. The time course of the integration of these proteins as animal evolution proceeded was elucidated. Insofar as cell –to-cell communication is only of relevance in multicellular animals, it is not surprising that the Notch system reached a fully-working configuration only with the evolutionary appearance of the Metazoa, the first multicellular animals The roles of the Notch system’s 49 components in contemporary descendants of the ortholog-contributing ancestors were ascertained from a survey of the literature. A single protein, the protein tyrosine kinase (PTK) of the protozoan Ministeria vibrans was identified as a possible pre-Metazoan ancestor of the DLL, JAG, and NOTCH proteins. A scenario for the evolution of the Notch signaling pathway is presented and described as the co-option of its components, clade by clade, in a repurposing of genes already present in the ancestral unicellular organisms.

The interaction between gut-residing microorganisms plays a critical role in the pathogenesis of Crohn’s disease (CD), where microbiome dysregulation can alter immune responses leading to unresolved local inflammation. The aim of this study is to analyze the immunomodulatory properties of our recently developed probiotic+amylase blend in the SAMP1/YitFc (SAMP) mouse model of CD-like ileitis. Four groups of SAMP mice were gavaged for 56 days with: 1) probiotic strains + amylase (concentration: 0.25 mg/100 uL PBS); 2) only probiotics; 3) only amylase; PBS (vehicle-treated controls). Ilea were collected for GeoMx Digital Spatial Profiler (DSP) analysis and histological evaluation. Histology assessment for inflammation indicated a significantly reduced level of ileitis in mice administered probiotics+amylase blend. DSP analysis showed decreased abundance of neutrophils and increased abundance of dendritic cells, innate lymphoid cells and macrophages, with a significant enrichment of five intracellular pathways related to apoptosis, in probiotics+amylase treated mice. Increased apoptosis occurrence was confirmed by TUNEL assay. Our data demonstrate a beneficial role of the probiotic and amylase blend, highlighting an increased apoptosis of innate immunity-associated cell subsets, thus promoting the resolution of inflammation. Hence, we suggest that our recently developed probiotic blend may be a therapeutic tool to manage CD and therefore could be a candidate compound to be tested in clinical trials.

A comprehensive study (monitoring, thermodynamic modeling) of natural and anthropogenically polluted waters of the Lovozero Massif has been carried out. A thermodynamic study of the weathering of the Lovozero Massif within the “water-rock-atmosphere” system at a temperature of 5°C showed that the elements contained in the rocks of the studied massif influence the formation of the chemical composition of natural waters. It has been established that an increase in the degree of “water-rock” interaction leads to an increase in the concentrations of F, Cl, SО42-, HCO3- in the solution. This affects the mobility of lanthanum, cerium and other elements due to the formation of complex compounds with them. The relatively high content of fluorine, phosphorus, HCO3- (weak and medium acids) in the solution promotes the dissolution of silicates while Si, Al, P are released into the solution. Monitoring of water from a flooded mine in which there is an increase in the degree of interaction of water with rock showed higher pH values for the concentrations of Na, HCO3-, F-, P, Al, Si, V, U, La, Ce. The conclusions are relevant in the context of groundwater extraction for drinking water supply purposes. The obtained information is useful to evaluated the health of the population of the region under study.

As Aotearoa-New Zealand faces increasing cyber threats, this paper comprehensively analyses the nation’s current cybersecurity landscape, revealing novel opportunities and challenges. Through an interdisciplinary approach, the study integrates social, cultural, and technological dimensions—providing a fresh perspective that has been underexplored in previous research. A key focus is integrating cultural values, particularly those of the indigenous Māori, into cybersecurity practices. This not only strengthens the effectiveness and trustworthiness of security measures but also fosters a more inclusive and resilient digital environment, demonstrating our deep respect for the unique contributions of Māori culture. Additionally, this paper introduces critical insights into the country's cybersecurity talent gap, with a special focus on the challenges of developing and retaining cybersecurity expertise in remote regions. Our study also uncovers underexplored opportunities for cross-sector collaboration between private enterprises, government agencies, and indigenous communities, promoting an inclusive and resilient approach to cybersecurity. By positioning Aotearoa-New Zealand as a potential leader in regional cybersecurity innovation, we provide forward-looking recommendations that leverage its distinctive cultural and technological strengths. This research contributes fresh insights to the global discourse on cybersecurity, offering practical strategies tailored to the specific needs of smaller nations.

Integrating ecosystem services (ESs) to delineate ecological functional zones (EFZs) is a fundamental work in terrestrial spatial planning and ecosystem management. However, existing studies have largely overlooked the refinement of EFZs at local scales, which hinders targeted and multi-scale ecosystem management. This study introduced a "two-step refinement zoning method" to address this gap, first using the self-organizing feature mapping method to delineate EFZs based on ESs at a township scale, and then applying hotspot overlay analysis to identify hotspots of dominant ESs within EFZs at a village scale. By overlaying the outcomes of these two steps, EFZs can be further graded by designating villages with hotspots of dominant ESs as level I and those without as level II. The proposed method was applied in Wuhan City, dividing it into five types of EFZs with different ESs combinations and land use compositions. Furthermore, 5.23% of villages were identified as Level I of EFZs, serving as advantageous areas of dominant ESs in the study area. On this basis, diversified management strategies and conservation priorities were proposed. This study provides a theoretical and methodological reference for terrestrial spatial planning and sustainable ecosystem management.

Cured-in-place pipe (CIPP) lining is a widely adopted method for pipeline renewal, offering advantages such as rapid installation and cost-effectiveness. However, concerns regarding the environmental impacts of volatile organic compound (VOC) emissions during the installation process have raised issues regarding the CIPP method. The literature review conducted in this paper indicated the need for stringent monitoring and management practices to mitigate adverse effects, emphasizing the importance of safe installation protocols. This paper presents the initial results of a case study focusing on VOC emissions, specifically investigating non-styrene polyester resins and water curing. To capture emissions from CIPP activities, the methodology involved air sampling using various equipment, including photoionization detectors (PID), summa canisters, passive worker sampler sorbent tubes, and method 13 cartridges. The preliminary findings indicate that non-styrene polyester resins do not exceed the exposure limits set out by the OSHA and USEPA. The future phases of this project will explore different resins and curing methods.

The olive tree (Olea europaea L.) is an evergreen tree that occupies 19% of the woody crop area and is cultivated in 67 countries on five continents. The largest olive production is concentrated in the Mediterranean basin, where the olive tree has had an enormous economic, cultural and environmental impact since the 7th century BC. In the Mediterranean region, salinity stands out as one of the main abiotic stress factors significantly affecting agricultural production. Moreover, climate change is expected to lead to increased salinisation in this region, threatening olive productivity. Salt stress causes combined damage by osmotic stress and ionic toxicity, restricting olive growth and interfering with multiple metabolic processes. A large variability in salinity tolerance among olive cultivars has been described. This paper aims to synthesize information from the published literature on olive adaptations to salt stress and its importance in salinity tolerance. The morphological, physiological, biochemical, and molecular mechanisms of olive tolerance to salt stress are reviewed.

This study investigates the transformative impact of ChatGPT, a cutting-edge AI language model developed by OpenAI, on the financial sector. We explore ChatGPT's applications in financial analysis, focusing on its ability to perform tasks traditionally handled by human analysts. By creating a set of multi-step and advanced reasoning financial tasks, and establishing several task-specific evaluation metrics, our experimental results demonstrate that ChatGPT-4o can effectively perform both basic and some complex financial analysis tasks comparable to those executed by humans. However, our empirical evaluation reveals limitations in its performance on complex tasks that require comprehensive understanding and critical thinking. The study highlights the necessity for meticulous task formulation and robust evaluation to achieve consistent functionality. While ChatGPT enhances efficiency in financial analysis, its integration with human expertise remains crucial for effective decision-making. This study contributes to the understanding of AI's role in finance and provides insights into its potential and constraints, guiding future integration of AI technologies in financial practices.

Using assembly theory, we investigate the assembly pathways of binary strings of length N formed by joining bits present in the assembly pool and the strings that entered the pool as a result of previous joining operations. We show that the string assembly index is bounded from below by the shortest addition chain for N, and we conjecture about the form of the upper bound. We define the degree of causation for the minimum assembly index and show that for certain N it features regularities that can be used to determine a shortest addition chain. We show that a string with the smallest assembly index for N can be assembled by a binary program of length equal to this index if the length of this string is expressible as a product of Fibonacci numbers. We conjecture that there is no binary program that has a length shorter than the length of the string having the largest assembly index for N that could assemble this string. The results confirm that four Planck areas provide a minimum information capacity that corresponds to a minimum thermodynamic (Bekenstein-Hawking) entropy. Knowing that the problem of determining the assembly index is at least NP-complete, we conjecture that this problem is NP-complete, while the problem of creating the string so that it would have a predetermined largest assembly index is NP-hard. The proof of this conjecture would imply P ≠ NP, since every computable problem and every computable solution can be encoded as a finite binary string.

Danyore Valley area is a new prospect of copper-gold mineralization in the Gilgit-Baltistan province, Kohistan terrane, northern Pakistan. The mineralization is Cu-Au vein-type, localized within quartz veins and controlled by a fracture system mainly trending NW and NE. The host units belong to the Ladakh-Kohistan arc terrane, which covers northern Pakistan and north-western India and mainly comprises Precambrian basement units, Paleozoic to Cenozoic magmatic rocks, and sedimentary strata. The mineralized wall rocks consist of Mesozoic gabbro and diorite, which have undergone an intensive hydrothermal alteration. The study area, Danyore Valley, has yet to be explored. The geological background and mineralization type in literature are scarce. Moreover, the tectonic setting, petrogenesis, age, and magmatic evolution of the gabbro-diorite hosting unit still need to be better understood. Furthermore, the sources of metals and mineralized fluids and the types of mineralization and alteration are also unexplored. This research's contribution presents the field investigation, microscopic observations, whole rock geochemistry (major, trace, and REE), mineral analysis (EPMA), in situ LA–ICP–MS zircon U–Pb age dating, and zircon trace elements data for Danyore Valley Cu-Au prospect of Kohistan Batholith. The current research work's objectives are to (a) constrain the emplacement ages of the Danyore Valley host rocks, (b) determine the petrogenesis and tectonic environment of the gabbro-diorite wall rocks, and (c) identify the mineralization style and alteration patterns of Cu-Au occurrences. The U-Pb isotopic data of studied zircons from Danyore Valley diorite specimens yielded concordia ages from 111.60 ± 0.90 Ma to 112.18 ± 0.74 Ma. Correspondingly, the gabbro rock sample displayed a concordia age of 110.21 ± 0.99 Ma, indicating the crystallization time of the host bodies is mainly the early cretaceous period (∼110 Ma). The findings of this study reveal that the calc-alkaline affinity and arc-like geochemical characteristics of the gabbro and diorite rocks have been characterized by a significant enrichment in large-ion lithophile elements and an apparent depletion in high-field strength elements. The parent magma probably originated from a partial melting process of mantle depletion, and geochemical traits are characteristic of magmas associated with subduction zones. The Danyore Valley area of Kohistan terrane is defined by the existence of several mineralized quartz veins, which are mainly sulfide assemblages. The sulfide ore is mainly comprised of chalcopyrite, pyrite, and bornite, with a smaller amount of covellite and sphalerite and significant traces of gold, which are distributed mainly in sulfides. Copper and gold mineralization of Danyore Valley is associated with phyllic, propylitic, and carbonatization alteration assemblages. Metal-rich quartz veins exhibit a spatial correlation with diorite and gabbro rocks. The discovery of several surface Cu-Au vein-type mineralized areas accompanying outcrops of copper supergene enrichment at the Danyore Valley prospect is significant evidence (predictor patterns) of porphyry-style deposits in the Gilgit district, Kohistan terrane, northern Pakistan. This work also advocates the importance of the Danyore Valley prospect and Kohistan Batholith region for further detailed geological studies.

Corrugated board is a composite material characterized by strong orthotropy in both the elastic and plastic phases. Additionally, due to its layered structure, which consists of alternately arranged flat and wavy layers of paper, its mechanics becomes complicated. Therefore, a precisely selected set of laboratory tests is needed to correctly identify all the necessary material parameters of cardboard. The work attempts to define a full set of laboratory tests in order to determine material parameters describing the linear-elastic, orthotropic behavior of cardboard and the basic parameters defining popular plasticity criteria, such as the asymmetric orthotropic Hoffman criterion. For this purpose, sensitivity analysis and numerical models of several selected basic laboratory tests were used. Since the aim of the work is to choose appropriate laboratory tests necessary to correctly determine the material parameters of corrugated board (not its individual layers), the numerical models do not contain detailed cardboard geometry, but only its homogenized representation in the form of the flat shell models. All numerical models are based on the nonlinear finite element method and constitutive modelling in the form of UMAT subroutines implemented in the ABAQUS software. Based on the analyses, appropriate measurements and laboratory tests were indicated that are most sensitive to the material parameters sought.

Sorghum grain processing can improve the nutritional content by promoting dietary properties that contribute to food security and economic development. The quality, nutritional content, and processing properties of sorghum bicolor grain can greatly affected by the inbred line races and variance in pericarp colour.The current study assessed the influence of the Husking Fraction Time Units (HFTU) process, which employed set time units per second (S), on the variation in the nutritional profile of fifty-one inbred line sorghum varieties based on distinct pericarp colours. When the assessment of the nutritional profile was involved: dry matter, total protein besides, namely mineral (P, K, S, Ca, Mg, Na, Fe, Zn, and Mn). The variety groups showed a significance value of (P < 0.05), indicating the study hypothesis's truth.The results demonstrated substantial impacts implied by the Husking Fraction Time Unit (HFTU) technique. This occurrence was noted when the dry matter percentage was increased in the husked products, specifically the endosperm (grits) and bran. The protein percentage redistributed by 19.2% compared to the whole grain and bran content. In comparison, the ratio of N/S was 14:1 in the S. bicolor and 12:1 in the kafirin in the bran part. Moreover, a strong correlation was observed among the examined minerals of S.bicolor and kafirin, such as the correlation between Ca: P, K: Na, and Fe: Zn attributed 80 (S) time unit, with correlation coefficients of R = 0.784 and R = 0.586, R= 517, R= 0.884, R= 0.745, and R = 0.893, respectively. At the same time, the 80 (S) time unit showed a significant effect on the colour property profile.The study results could benefit breeders and nutrition specialists in developing genotypes and processing sorghum grains, promoting research, and aiding several industrial sectors owing to the grain's adaptability and nutritional properties.

Cadmium Sulfide nanoparticle (CdS-LA hybrid nanoparticles) was synthesized here by a green approach using the precursor cadmium acetate and sodium sulphide along with the extract of a plant Lathyrus aphaca L. containing the phytochemicals which were responsible for surface modification of nanoparticles. The nanoparticle was used to evaluate their inhibition potential against species of bacteria and fungi. The nanoparticles were characterized by XRD which demonstrates the hexagonal crystal structure. SEM confirms the homogenous surface appearance of the CdS-LA hybrid crystalline structure. EDX analysis confirms surface modification of nanoparticles by phytochemicals. FTIR confirmed the Cd-S linkage laterally with the related functional groups and the presence of metabolites on the surface of nanoparticles. The UV-visible spectroscopy confirmed the peak at the characteristic wavelength range but a slight shift occurred in the peak of the CdS nanoparticles due to the presence of the phytochemicals. This study particularly provides an environment-friendly strategy to synthesize the CdS nanoparticles capped by Lathyrus Aphaca L. extract that are biologically active due to the mediation of the plant extract. CdS-LA hybrid nanoparticles have shown inhibition potential against various species of bacteria and fungi and realize the biological importance of the green synthesis of nanoparticles especially mediated with the plant extract.

Precision farming is transforming how antibiotics get used on farms. It fights the overuse that creates superbugs and harms nature. Farmers now have high-tech tools to use antibiotics ultra-precisely. Drones, AI, and advanced watering equipment help them pinpoint only sick plants and animals needing treatment. This shields crops while avoiding environmental damage. More careful antibiotic use makes livestock healthier and boosts harvests too. And it prevents resistant germs, where antibiotics stop working altogether. The approach helps farms in multiple ways, using fewer resources for even better results. There are some growing pains, like high costs for small farms. And questions around data privacy also cause concern. But overcoming these hurdles could help precision farming spread far and wide. This technology promises safer, greener, and more productive agriculture. Targeted use of antibiotics protects both crops and people from drug-proof germs. And nature benefits when less medicine spreads into soil and water. The future looks bright for farming with precision.

Prospecting for a future breeding site is an essential component of informed dispersal. It allows individuals to reduce the uncertainty of their environment by gathering personal and social information about the local quality of alternative breeding areas, and to make informed emigration and settlement decisions. Although this process has been studied in territorial and social animal species for decades, it is still not well-understood and spatial patterns of prospecting movements are hard to generalize over taxa or even species due to substantial intra and inter-specific variability. Using 124 empirical studies which have explicitly described prospecting in a context of breeding habitat selection in birds, mammals, fish and invertebrates, I review why, how, when and which individuals prospect depending on their life history traits and sociality. From this synthesis, I identify persisting knowledge gaps which explain why prospecting is still understudied and sometimes overlooked. I finally propose key objectives and research directions, to shed light on prospecting movements and their consequences on informed dispersal strategies, individual fitness and population dynamics, both empirically and theoretically. A better understanding of the mechanisms underlying prospecting, their causes and their consequences will fully reveal how prospecting could constitute a powerful adaptive response to environmental changes for many social and territorial species which will help them persist on the long-term. It will also significantly enhance our ability to predict species responses to environmental changes and thus, inform more effective management plans for threatened species

Artifact metrics is a technology for authenticating artifacts based on their unique characteristics. The artifact-metric system offers "clone resistance," i.e., it makes it highly improbable to create another object exhibiting the same measured values as a genuine artifact. However, determined adversaries may still attempt to create imitations or clones with close physical characteristics to those of registered products, even if they cannot perfectly replicate the genuine product. Such clones serve to deceive users into believing they are genuine rather than counterfeits. Thus, in this study, we consider a scenario in which we measure raster-scanning-generated clones via a non-raster scanning method. Further, we employ image processing techniques to generate image data representing the clones and theoretically assess the filtering effects on these images. Our findings reveal that applying filters to specific frequency components in the spatial frequency domain can effectively highlight differences between raster-scanning-created clones and the corresponding genuine artifacts. Thus, we demonstrate directional emphasis filtering in artifact metrics as an effective approach for rejecting raster-scanning-created clones.

With the increasing prominence of renewable energy sources providing flexibility to the power grid, there is a growing recognition of the need to expand virtual Energy Storage Systems (ESS) to replace traditional ESS, which faces challenges in terms of supply and scalability. Grid-connected microgrids can supply power stably and are being built, so they can be used as virtual ESS to provide flexibility to the power system. This study proposes an approach to determine the optimal Power Conversion System (PCS) and battery capacity for a Virtual Energy Storage System(VEES) based on a grid-connected microgrid incorporating Photovoltaic (PV) and ESS. In this paper, it is assumed that microgrids can provide flexibility to the grid by participating in the energy trading market, there are corresponding profits and penalties for order. Numerical examples are performed to demonstrate the effectiveness of the proposed method.

Abstract: Intra-abdominal abscesses (IAA) may commonly arise following complicated gastrointestinal tract infections and, on occasion, from infections within the urinary system. Many of these IAA are initiated as a consequence of post-surgical complications. These abscesses have a substantial risk of morbidity and mortality. As a result, it is crucial to diagnose and treat them promptly to minimise these adverse outcomes. Therefore, radiological modalities play a vital role in diagnosing, localising, and detecting associated complications of IAA, as sometimes other investigations could be less reliable and non-specific. Radiological modalities are pivotal in achieving an accurate diagnosis, localising the abscesses, and identifying associated complications. This is especially important since alternative investigative methods may be misleading in certain situations. Radiological techniques such as ultrasound scans (USS), contrast-enhanced computed tomography (CECT), and even magnetic resonance imaging (MRI) are immensely helpful in diagnosing these conditions. These imaging tools guide clinicians in determining the most appropriate patient management strategies. In this article, we compile a case series involving tubo-ovarian abscess, appendicular abscess, diverticular abscess and infected walled-off pancreatic necrosis, paying particular attention to radiological features in the diagnosis. Furthermore, we reviewed the existing literature to delineate characteristic radiological features related to the cases we discussed.

Moving object detection plays a crucial role in various applications, particularly in traffic surveillance and collision warning systems. However, the high cost of training and slow detection pose significant challenges to the practicality and real-time performance of existing methods. These challenges hinder the practicality and real-time performance of existing methods. The need for a reliable and efficient moving object detection system prompts the search for cost-effective strategies. Enhancing detection speed without sacrificing accuracy is crucial for real-time applications. Overcoming these challenges is essential to advance the field of moving object detection and improve its applicability in various domains. This paper presents a comprehensive review of the literature on moving object detection, proposes novel strategies to overcome the challenges of high training costs and slow detection. The study emphasizes the importance of reliable speed monitoring systems and advancements in control systems to enhance driver assistance on urban highways. Each frame in the dataset undergoes YOLOv6 processing to detect and classify objects, generating bounding box predictions and class probabilities. Optical flow, specifically the Lucas-Kanade method, is then utilized to compute motion vectors between consecutive frames. These motion vectors facilitate object tracking across frames, enabling refined bounding box positions and improving overall object tracking accuracy. The results demonstrate the effectiveness of the proposed technique in reducing training costs, improving detection speed, and maintaining a high level of accuracy when compared to existing methods. The paper concludes by summarizing the findings and highlighting the potential of the proposed strategy for precise and reliable moving object recognition in real-world traffic scenarios

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

Anomaly Detection in real time data is accepted as a vital research area. Clustering has effectively been tried for this purpose. As the datasets are real time, the time of generating of the data is also important. In this article, we introduce a mixture of partitioning and agglomerative hierarchical approach to detect anomalies from such datasets. It is a two-phase method which follows partitioning approach first and then agglomerative hierarchical approach. The dataset can have mixed attributes. In phase-1, a unified metric defined on mixed attributes is used. The same is also used for merging of similar clusters in phase-2. Also, we have kept the track of time attribute of each data instance which produces the clusters with their lifetimes in phase-1. Then in phase-2, we merge the similar clusters. While merging, the similar clusters, the lifetimes of the corresponding clusters with overlapping cores are to be superimposed producing fuzzy time intervals. This way, each cluster will have an associated fuzzy lifetime. The data instances either belonging sparse clusters or not belonging to any of the clusters can be treated as anomalies. The efficacy of the algorithms can be established using both complexity analysis as well as experimental studies.

The synthesis of tetra- and pentanorlabdane compounds with rearranged cycle B based on commercially available (+)-sclareolide is reported. Desired compounds were prepared from intermediate ketones via Baeyer-Villiger oxidation. The structures of synthesized compounds were confirmed by spectral IR, 1D (1H, 13C and 15N, DEPT) and 2D (H-COSY, H,C-HSQC, H,C-HMBC, H,N-HMBC, NOESY) NMR analyses, mass-spectrometry and single crystal X-rays diffraction. Two of the four obtained compounds showed high antifungal and antimicrobial activity, comparable and exceeding that of standards Caspofungin and Kanamycin. DFT calculations revealed the stability of compounds in gas, DCM, water and methanol. Molecular docking to four targets (1KZN, 1U1Z, 3QLS, 2Q85) showed good agreement with the results of in vitro evaluation and confirmed the biological activity of compounds 3 and 4, with binding affinities comparable and for some targets exceeding that of Caspofungin and Kanamycin.

Opioid analgesics have been used for more than 5,000 years and remain the principal pain medications prescribed today. Although morphine is considered the gold standard for pain relief, this µ-opioid receptor (MOP)-selective agonist provides only moderate relief for many chronic pain conditions and promotes several unwanted effects that can adversely affect patient quality-of-life, prevent adherence to treatment or generate addiction. In addition to the lack of progress in the development of better analgesics, there have been no significant breakthroughs to date that have addressed side effects mentioned above. Fortunately, a better understanding of opioid pharmacology has restored hope for the development of better and safer pain medications. In this review, we describe how clinically approved opioids were initially characterized as biased ligands and what impact this approach could have on clinical practice. We also looked at the preclinical and clinical development of MOP biased agonists, with an emphasis on the oliceridine story, as the first specifically designed biased painkiller. Moreover, we explore the discrepancies between ligands with low intrinsic efficacy and those with biased properties. Finally, we examine the rationale behind biased ligand development during the opioid crisis era.

This article study was developed based on the relationship between access to justice and the instrumentality of the legal process, aiming to assess the effectiveness of the constitutional principle enshrined in Article 5, item XXXV: “the law shall not exclude any injury or threat to a right from the consideration of the Judiciary” (BRAZIL, 2008, p.27). To achieve this goal, the concept of justice was examined, as well as the definition and evolution of access to justice within legal science. In light of these concepts, it became possible to establish a connection between access to justice and the instrumentality of the legal process. This analysis reveals that the State has not yet achieved sufficient efficiency in providing support to its less favored citizens in facilitating access to justice.

Sunflower (Helianthus annuus L.) is an important oilseed crop cultivated extensively across the globe. High salinity adversely impacts plant growth and physiological processes. In this study, the data of the phenotypes and various indices were collected to clarify the physiological mechanisms underlying sunflower's salt tolerance with the seedlings of two salt-tolerant (182265 and 182283) and two salt-sensitive (182093 and 186096) genotypes, which were exposed to 350 mM NaCl for 4 days. The findings revealed that, during the seedling stage, salt-tolerant sunflowers accumulated less Na+ and more K+, resulting in a higher K+/Na+ ratio that mitigated ionic toxicity throughout the plants, compared to the salt-sensitive resources. Furthermore, the salt-tolerant germplasms also exerted salt tolerance through the following several pathways: they maintained robust osmotic regulation by accumulating higher levels of proline, soluble sugars, and other osmolytes; they neutralized reactive oxygen species (ROS) by elevating the activity of antioxidant enzymes; and they sustained optimal growth by boosting photosynthesis. Taken together, this study provided a more comprehensive assessment of the sunflower's physiological salt tolerance, offering valuable insights for further exploration of the molecular mechanisms of salt tolerance and accelerating the breeding process for sunflower varieties with improved salt resilience.

Introduction: Lumbar radiculopathy, frequently triggered by disc herniation, affects around one in 50 young adults (30-55 ages), leading to significant impacts on quality of life. When conservative treatments fail to alleviate symptoms, surgical intervention such as discectomy is often pursued. Technological advancements have led to various minimally invasive techniques, promising improved outcomes. Our aim was to compare clinical outcomes of different techniques. Methods: We conducted a systematic search in PubMed using "lumbar disc hernia" and the meta-analysis filter. Inclusion criteria comprised meta-analyses focusing on lumbar disc herniation treatments, published in English. A rigorous selection process adhering to PRISMA guidelines ensured high-quality evidence extraction. Results: From 28,171 initial records, 31 meta-analyses involving 87,852 patients were included. Heterogeneity across the literature presented challenges, notably in study populations, surgical techniques, and research designs. Among the techniques evaluated, full-endoscopic lumbar discectomy (FELD) emerged as superior in various perioperative parameters, including Visual Analog Scale (VAS) scores, Oswestry Disability Index (ODI), operation time, and complications. Conversely, automated percutaneous discectomy (AUTD) consistently exhibited poorer outcomes, suggesting limited effectiveness compared to other techniques. Conclusion: Despite advancements, the heterogeneity observed in the literature underscores the need for standardized approaches in minimally invasive spinal surgery research. FELD stands out as a preferred technique, offering favorable outcomes across multiple parameters. Conversely, techniques like AUTD raise concerns regarding efficacy. Future research should aim for uniformity in methodologies to facilitate accurate comparisons and guide clinical decision-making.

This study presents a novel approach to automatic generation of cultural and context-specific science assessments for K-12 education using generative AI (GenAI). We first developed a GenAI Culturally Responsive Science Assessment (GenAI-CRSciA) framework that establishes the relationship between CRSciA and GenAI, by incorporating key cultural tenets such as indigenous language, Indigenous knowledge, ethnicity/race, and religion. The CRSciA framework along with dynamic prompt strategies were used to develop the CRSciA-Generator model within the OpenAI platform. The CRSciA-Generator allows users to automatically generate assessments tailored to students’ cultural and contextual needs. In a pilot comparison test between the CRSciA-Generator and the base GPT 4o (with standard prompt), the models were tasked with generating CRSciAs that aligned with the Next Generation Science Standard on predator and prey relationship for students from Ghana, the USA, and China. The results showed that the CRSciA-Generator output assessments incorporated more tailored culturally and context assessment items for each specific group with examples, such as traditional stories of lions and antelopes in Ghana, Native American views on wolves in the USA, and Taoist or Buddhist teachings on the Amur tiger in China than the standard prompt out within the base GPT 4o. However, due to the background information provided, the CRSciA-Generator overgeneralized its output focusing on broad national contexts, treating entire countries as culturally homogenous and neglecting the subcultures. Therefore, we recommend that teachers provide detailed background information about their students when using the CRSciA-Generator. Additionally, we believe the pilot test did not fully validate the model’s efficacy, and future studies involving human experts’ review are recommended to evaluate the cultural and contextual validity of the generated assessments. We also suggest empirical studies in diverse contexts to further test and validate the model’s overall effectiveness.

Efforts to achieve carbon neutrality, which aims to reduce the net carbon emissions to zero by decreasing carbon emissions from human activities and increasing carbon absorption, are actively underway. Additionally, the search for clean energy alternatives to fossil fuels has become a global research trend. This paper presents research on metal-air batteries, focusing on the development of energy supply technologies that do not generate carbon emissions during power generation and require less space for power generation compared to existing renewable energy sources. The proposed Mg-Air Battery (MAB) in this study uses magnesium as the metal anode and theoretically offers a maximum open-circuit voltage of 3.1V and a high energy density of 6.8kWh/kg. While previous research has primarily focused on designing small-capacity cells and maximizing the performance of metal anodes, this study differentiates itself by designing a large-capacity MAB cell and optimizing its electrical performance. For the large-capacity cell design, the weight, shape, and size of the anode were designed based on MAB performance factors, and research was conducted on manufacturing methods to optimize the performance of the air cathode. Furthermore, to enhance usability and extend the lifespan of the MAB cell, it was designed to allow electrolyte circulation, and the electrolyte circulation performance was verified through simulations of fluid flow within the cell. Based on the study of the power performance of the newly designed large-capacity MAB cell, the feasibility of con-structing a kW-class system using multiple Mg-Air battery cell stacks was confirmed.

The paper provides analysis that the generation of the gyroscopic torque described by the vector multiplication is one-way inertial phenomenon. Respectively, vector multiplication is one-way equation from the type: If B times C is equal A, A is not equal B times C. Presumably, it affects the Conservation Laws.

We evaluated the inhibitory effects of our developed Chol-PEG2000 micelles and Chol-PEG500 vesicles on amyloid-β (Aβ) aggregation, a key factor in Alzheimer's disease. ThT assay proved that Chol-PEG2000 delayed Aβ fibril elongation by 17 hours and Chol-PEG500 by 40 hours at 10-times molar ratio against Aβ40 peptide. At 50-times molar ratio, both Chol-PEG2000 and Chol-PEG500 significantly inhibited Aβ aggregation, as shown by minimal fluorescence intensity increase over 48 hours.

Deuterium is a non-radioactive isotope of hydrogen, containing a neutron as well as a proton, which makes it twice as heavy as hydrogen. Deuterium is a natural element found at 156 parts per million in seawater. Human metabolism employs clever strategies to minimize the amount of deuterium in mitochondrial water, because it causes a stutter in ATPase pumps, introducing excess reactive oxygen species and inefficiencies in ATP production. Gut microbes produce hydrogen gas that is 80% depleted in deuterium (deupleted), and this gas is recycled into organic matter that supplies deupleted nutrients to the host, such as acetate, butyrate, formate, methionine, and choline. Mitochondrial dysfunction is associated with many chronic diseases, most notably, cancer. Dehydrogenases are flavoproteins that typically have a high deuterium kinetic isotope effect, and they supply deupleted protons to NAD⁺ to produce NADH, which supplies protons to the ATPase pumps. Here, we examine the unique metabolic policies of cancer cells in a new light, and we propose that a tumor may arise as a strategy to help repair the mitochondria of tumor-resident immune cells overburdened with deuterium. While lactate accumulation in the tumor microenvironment promotes tumor growth, it also provides a valuable deuterium depleted nutrient to the tumor-resident immune cells. We provide strong evidence that deuterium depleted water (DDW) is a promising treatment for cancer.

In aerospace, robotics, network engineering and mechanical engineering, there exist complex and urgent challenges that can be abstracted into mathematical optimization problems. Therefore, exploring solutions to these optimization problems is a crucial task. Metaheuristic algorithms have been applied across various fields.The Snake Optimization Algorithm (SO) is an innovative metaheuristic method recognized for its efficient solving capabilities.However, this algorithm encounters challenges such as diminished search efficiency in the later stages and a propensity to become ensnared in local optima. To mitigate these issues, this paper introduces an enhanced Snake Optimization Algorithm (ISO). ISO integrates the RIME Algorithm(RIME)and introduces two effective enhancement strategies to improve its capability to evade local optima.To assess the effectiveness of ISO,the population distribution state was first measured using three algorithms, including Star Discrepancy, and the exploration and exploitation performance was analyzed using the CEC2017 test functions. Subsequently, utilized 23 benchmark functions for testing.The evaluation outcomes indicate that ISO exhibits outstanding performance in terms of convergence velocity and robustness.Additionally, it was applied to engineering fields including UAV path planning,Robot path planning, Wireless sensor network node deployment and Pressure vessel design.In comparison to the SO algorithm, the ISO algorithm demonstrates superior stability, converges earlier, and improves its ability to solve for optimal .These findings highlight the significant potential of the ISO algorithm in diverse test functions and a wide range of interdisciplinary problems.

In order to study the effect of explosion load on the flexural performance of RC beams, two RC beams of the same size were carried out explosion test and bearing capacity test successively. Piezoelectric intelligent aggregate was embedded in the beams in advance to monitor the damage state of the beams, which realized the whole process of damage monitoring of the concrete inside the structure from explosion damage to compression damage.Based on wavelet packet analysis and residual bearing capacity damage evaluation criteria, the beam damage was quantitatively evaluated, and the bending bearing capacity of RC beam after explosion damage was compared and analyzed.The results show that the change of concrete strain gauge signal, the phenomenon of crack development and the increase of internal crack development index indicate that the RC beam is damaged by explosion load.After explosion damage, the damage index of the beam increases and the residual bending capacity decreases, which proves that the piezoelectric intelligent aggregate sensor can effectively monitor the bending capacity change of the component after explosion damage.

Objective: The effect of long-term performance of one-bottle or two-bottle bonding agents on the shear bond strength to lithium disilicate ceramics (LDS) were to investigate, and the long-term performance of the bond strength of two-bottle bonding agent (Tokuyama Universal Bond II) was investigated under conditions without hydrofluoric acid solution (abbreviated as HF)-pretreatment of LDS. Methods: Nine resin cements (both self-adhesive and adhesive types) were used. It was investigated 1) the adhesion strength of various resin cements to LDS from the presence or absence of HF-treatment, 2) to determine the effect of the deterioration in three times [after one-day storage (abbreviated as Base), and after 5,000 &amp; 20,000 thermocycles (abbreviated as TC 5k and TC 20k)] of one- and two-component bonding agents. And the difference in degradation between one- and two-component bonding gents consist of the silane coupling agent was performed by chemical analysis (High Performance Liquid Chromatography). Results: The trends of resin cements were statistically not very different for each cement 3 times with HF-conditions. Also ESTECEM II and Super-Bond Universal showed the significant greatest values in two conditions (TC 5k and TC 20k) without HF-condition. In TC 20k, ESTECEM II &amp; Super-Bond Universal showed significantly better results than others when treated with the recommended bonding agents without HF-condition. In TC 20k, there was not much statistically significant difference if pretreated with Tokuyama Universal Bond II without HF-condition. Significance: When using LDS, it was found that long-term durability could be maintained by pretreating with Tokuyama Universal Bond II without pretreating with various hazardous HFs.

Weathering and erosion transport minerals and organics toward the sea or lake bottoms over geologic time. The finest solids are deposited in lower, less turbulent areas, such as lake bottoms and continental shelves. They sometimes stack up to thicknesses of kilometers, and begin compacting. These sediment sections are called shales, and as initially deposited in water, shales can have porosities up to 50-80{\%} water, As they are buried, many alteration products from oil to slate are produced due to overburden and temperature increasess, making them important to study. A preceeding paper \cite{1} showed that pressure solution is the primary mechanism for porosity reduction, with possible mechanical compaction at shallow depths. Without naming the mineral(s) involved, it postulated that the greater the product of the water and pore interfaces, the faster the reaction would proceed. This term is $ \varphi^{4m/3}(1-\varphi)^{4n/3}$ , where $\varphi$ is porosity and m and n are numbers close to unity. The large exponents, {\em 4/3}, recognize that the reaction occurs at the molecular scale at which the surfaces are rough. A second term, $\exp^{(-E/RT)}$ , indicates that the reaction is impeded by a quantum energy barrier, E, with diminished impeding power as increased available thermal energy, represented by the absolute temperature, T, becomes available at greater depths in the Earth. These two factors combine to allow porosity $\varphi$ to reduce with time, or equivalently for the fraction of solids, $(1-\varphi)$, to increase with time,$\left. \frac{\partial(ln(1-\varphi) ) }{\partial t } \right |_{\sigma} = (\varphi )^{4m/3}( 1-\varphi )^{4n/3}Ae^{-E/(RT)}$. { \em Here it is shown that this equation can cover quantitatively any actual deposition rates which may have been experienced by the six sections studied, the actual deposition rates being unknown for these cases. Hence a time-depth depositional history for any new shale section, known in detail, would allow determination of the parameters m, n, E and a lumped proportionality constant A. This was accomplished by showing that, for a wide range of depositional rates, r, the range of E for any of the studied sections is small compared to laboratory measurements of quartz solution\cite{2}, 24+-15kJ/mol. Results were obtained over this range of r's using the previously determined m and n, and porosity and temperature profiles. The presently existing porosity profiles necessarily incorporate any overpressure or underpressure conditions that may have existed in the past or currently, as the net difference between overburden and pore pressure is a primary driving force for pressure solution. $SiO_2$ usually comprises 20-50{\%} of shales. In conclusion, pressure solution of quartz can account for vertical compaction of shales quantitatively in the studied examples. Separately, a quasi-eqivalent method for discussing reduced porosities in Macron 2 versus Macron 1 as increased vertical stress, rather than additional horizontal stress, is illustrated. Experiments are suggested to clarify the pressure solution mechanism. The role of horizontal forces is discussed. From a global point of view, shale compaction by pressure solution is a quantified step in the cycling of continental rocks, beginning with rifting.

This comprehensive review explores the multifaceted landscape of supercapacitors, highlighting their pivotal role in meeting the global demand for efficient energy storage solutions. Supercapacitors, with their high power density, rapid charge-discharge cycles, and extended cycle life, offer a compelling alternative to conventional batteries and capacitors. The review delves into the fundamental mechanisms of energy storage in supercapacitors, categorizing them into Electrochemical Double-Layer Capacitors (EDLCs), pseudocapacitors, and hybrid capacitors. It discusses significant advancements in supercapacitor technology, including nanostructured materials, flexible and wearable supercapacitors, solid-state supercapacitors, and hybrid supercapacitors, highlighting their potential applications across industries such as transportation, renewable energy, consumer electronics, and industrial power management. Through continued research and development, supercapacitors are poised to play a pivotal role in driving the transition towards a greener and more efficient future.

.Various synthetic nematicides are currently used effectively in the control of plant parasitic nematodes. However, these nematicides have adverse effects on humans and the environment. Neem oil is eco-friendly alternatives to synthetic nematicides. The effectiveness of repeated neem oil application in suppressing the root-knot nematodes infestation in figs seedlings was therefore examined in this study, both in its natural form (10 ml/L) and in its nano-emulsion form (5 and 7 ml/L). The recorded reduction parameters of M. incognita were J2/250g soil, galls and egg masses / 5g roots of infected fig seedlings were measured at that time, and the effects of these natural additives were compared with the Fosthiazate (Krenkel 75%EC). The impact of such soil amendments on some typical plant parameters, the total microbial count of soil, and the overall enzymatic activity of the fig rhizosphere were also included. Obtained results revealed that the soil population density of root knot nematode suppressed by 80.3% , reduction of nematode egg masses (60.4%) due to the application of nano-emulsion of neem oil (at 7ml/L). Present work recommend the use of nano-emulsion of neem oil as one of the effective and eco-friendly means to reduce the root- knot nematode on fig .

Perceived peer support is a critical factor in the academic adjustment of higher vocational college students. While previous studies have explored this relationship, few studies have delved into the underlying mechanisms. This study surveyed 9782 students from 35 higher vocational colleges in 13 provinces and cities in China to explore the relationship and mechanisms between perceived peer support and academic adjustment. Drawing on Conservation of Resources theory and Social Support Resource theory, the findings revealed that perceived peer support not only directly predicted the academic adjustment of higher vocational college students, but also indirectly through the independent mediating effect of academic hope and professional identity, as well as the chain-mediating effect of academic hope to professional identity. Additionally, students from vocational high schools showed a more significant increase in academic hope due to perceived peer support compared to those from general high schools, highlighting the moderating effect of educational background. The study provided a new theoretical perspective for understanding the complex mechanisms of academic adjustment in students and offers valuable guidance for educational practice, emphasizing the importance of fostering perceived peer support, academic hope, and professional identity in higher vocational education.

This study investigates the impacts of climate change policies on businesses across various sectors, aiming to understand how these regulations affect operational, financial, and strategic aspects of business management. Utilizing a mixed-methods approach, data was collected from 500 businesses through surveys and interviews, encompassing a wide range of industries, sizes, and geographic locations. The findings reveal a complex landscape where 30% of businesses report positive impacts, primarily in the renewable energy and technology sectors, citing increased demand for green products and improvements in energy efficiency. Conversely, 45% of businesses, especially from manufacturing and agriculture, experience negative impacts, including increased operational costs and regulatory compliance challenges. Notwithstanding, a significant majority of businesses are committed to enhancing their sustainability practices, viewing climate change policies as an opportunity for innovation and long-term growth. The study highlights the nuanced effects of climate change policies, emphasizing the need for sector-specific support measures to alleviate financial and operational burdens on negatively impacted businesses. Moreover, it points to a broader shift towards sustainability within the business community, suggesting that climate policies, despite their varied impacts, are driving significant changes in business strategies towards environmental stewardship.

Understanding the genotype x environment (GE) interaction for traget trait is valuable for growers, agronomists, breeders and the seed industry. The objective of this study was to see and explore the genotype x environment interaction for grain yield of wheat to better guide genotype selection and breeding. The genotype main effect and GE interaction effect (GGE) biplots resolved the following three genotypes: 85 (ETW17-377), 82 (ETW17-374) and 13 (ETW17-281) for being the best yielding and stable. The Kulumsa site planted on 4^th of July 2017 (environment 7=E7) and the DebreZeit site on 20^th of July 2017 (E3) were the most effective environments in distinguishing the test genotypes and are thus suitable environments for future evaluation and selection with specific adaptation. Melkasa site planted on 4^th July (E9) was a representative environment where genotypes can be evaluated for wide adpaptation. The genetic covariate biplot indicated that thousand kernel weight (TKW) and plant height (PH) had significant positive associations with grain yield implying the possible concurrent indirect selection of both traits for exploiting GE interaction for grain yield of wheat.

The future index prices are viewed as a critical issue for any trader and investor. For this craving, various models have shown up in the literature. The Geometric Brownian motion (GBM) is one of the popular models. This work examines four types of GBM as per the presence of memory or kind of volatility. These models include classical GBM with memoryless and constant volatility assumptions, SVGBM with memoryless and stochastic volatility assumption, GFBM with memory and constant volatility assumption, and SVGFBM with memory and stochastic volatility assumption. These models are utilized in an empirical study to forecast the future index price of Energy Sector in the Saudi Stock Exchange Market. The assessment was led by utilizing two error standards, mean square error (MSE) and mean absolute percentage error (MAPE). The outcomes showed that the SVGFBM occupies the highest level of accuracy according to smallest values of MSE and MAPE. While the accuracy of GBM come in the tail of the list models under study. These results have affirmed the positive affection of combining memory and stochastic volatility assumption into the GBM model, which agreed findings of numerous earlier works. Furthermore, the findings showed the GFBM models are more accurate than GBM models regardless of the type of volatility. While, under the same type of memory, the models with stochastic volatility assumption are more accurate than the corresponding models of constant volatility assumption. In general, all models considered in this work uncovered high accuracy through the value of MAPE ≤ 10%. This indicates of the ability of applying these models in a real financial environment. Through this empirical study, we can say that the Energy Sector in Saudi Arabia is predictable and stable and afterward we urge financial investors and stockholder to trade and invest in this sector.

The global textile sector, pivotal to economic development, significantly contributes to environmental degradation, prompting a shift towards sustainable raw material sources. Embracing circular economy principles, this industry is exploring the valorization of agricultural by-products. This study introduces an innovative approach to repurposing mango waste into valuable textile fibers, a byproduct of the fruit processing industry, predominantly generated during juice and jam production. The focus is on the lignocellulosic constituents of mango waste, specifically the peel, seed, and fibrous material, traditionally considered as refuse. Previous research has predominantly utilized mango peel in pectin extraction for food applications, whereas the potential of seed and fibrous content remains underexplored. This investigation endeavors to transform these fibrous by-products into high-value materials suitable for textile manufacturing. The process involved washing, drying, and comprehensive physicochemical characterization of mango fibers, emphasizing lignin quantification, revealing a composition of 12.2% lignin. An experimental design was employed to elucidate the impact of variables such as liquid-to-solid ratio, reaction duration, and sodium hydroxide concentration on lignin dissolution through alkaline hydrolysis. Optimal conditions—10% NaOH concentration, 30 mL/g liquid-to-solid ratio over six hours—achieved an 83% reduction in lignin content. The resulting fibers exhibited properties akin to conventional natural fibers, including a favorable aspect ratio indicative of their suitability for textile applications. A subsequent softening process using propylene glycol enhanced the fibers' spinability, producing a durable, textured fabric ideal for eco-conscious fashion applications, including bags, footwear, and accessories. This research demonstrates the feasibility of converting mango waste into a textile-worthy material and underscores the importance of waste revalorization in promoting sustainability within the circular economy framework.

Cotton is the most ubiquitous and profitable fiber with diverse industrial and domestic applications. Grown in over 100 countries, it has a global market value of about $40 billion and employs over 350 million people from fields to textile mills, contributing about 7% of total labor-force recruitment in developing economies. Cotton has an indeterminate growth habit and an extensive tap root system affected by soil physicochemical and environmental conditions. There is a consensus among experts that conventional cotton cultivation still has a long way to attain sustainability, which is essential if cotton will maintain its competitive edge over other natural and synthetic fibers like hemp, polyesters, and rayon. Despite several efforts already committed to growing cotton sustainably, sustainability has eluded cotton cultivation globally because of the intense farm inputs (freshwater, pesticides, and heavy-duty equipment) needs, especially in developing economies. Some of the technological advancements towards achieving the goal of sustainable cotton cultivation include the development of new varieties, improved irrigation and mulching and precision agriculture techniques, application of remote sensing and Unmanned Aerial Systems (UAS) combined with image processing, and the introduction of autonomous and multi-purpose robotic platforms for growing and harvesting cotton. This review attempts to evaluate the successes already achieved by stakeholders in moving cotton towards sustainable production and identify areas where efforts are still needed to reach sustainable production and improved profitability goals for cotton with projections for future research directions.

We changed the symmetry of the Weak Force from SU(2) to the quaternion group $Q_8$, and found that spin spacetime separates into two complementary spaces: a spin polarization spacetime of even parity states, and a spin coherence space, in the $S^3$ hypersphere, of odd parity coherent states. Under the quaternion group, spin is a boson of spin 1 in free flight and a fermion of spin $\frac{1}{2}$ when measured. It immediately follows that neutrinos are not needed to balance spin and conserve energy in beta decay. Additionally, we find the boson electrons emitted in beta decay are odd to parity, leading to parity conservation even though the observed beta distribution is asymmetrical.

Based on the theory that certain geological fault zones surpass the influence of other abiotic and biotic site factors for mound-building red wood ants (Formica rufa group), an area northwest of Tuttlingen with extremely high ant density was systematically surveyed, taking into account official geological maps. Indicators of active fault zones were recorded. These were additionally examined in a model area using a high-resolution digital terrain model (DTM 1-meter). The study area is located in the Swabian Jura at the western edge of the Albstadt shear zone, where recent seismic activity is documented by frequent earthquakes. The earthquakes are considered to be the cause of gas permeability in the strike-slip faults, around which the clustered nesting sites were mapped. More than 2900 nests of the Formica rufa group were mapped and their site conditions analysed in different geomorphological positions. In addition to recording forestry site conditions, a geological classification was carried out, as well as an analysis of soil gases/mofettes in areas with the highest nest densities. The correlation between forestry data and nest sites did not reveal a consistent pattern. In contrast, the relationships with gas-permeable strike-slip faults, though predominantly covered with Quaternary sediments, could be identified through CO₂- and CH₄-rich gas emissions, mofettes, and doline features. The interpretations were complicated due to different mapping ages and signatures of the geological maps. Fortunately, this issue could be analysed and evaluated in a sub-area with mappings from 1936/71 and 1995 regarding presumed or confirmed fault trajectories. New insights were gained regarding the relationships between Formica nest sites, gas-permeable faults, and groundwater levels on narrow mountain ridges with steep relief. Here, the lateral emission of CO₂ depends on the groundwater level and does not occur vertically directly above the fault. C- and H-isotope data of CO₂ and CH₄ do not show a consistent source. While methane is mainly derived from biological production by Archaea in the upper crust and in swamp areas, CO₂ mostly originates from the mantle. The results of the investigations revealed that a multitude of geological and ecological factors must be considered for the interpretation of the occurrences of Formica sites northwest of Tuttlingen. These factors confer a distinct originality to this region, contributing not only to an enhanced understanding of site conditions but also furnishing information regarding environmentally relevant gas emissions.

Several strategies promote phyllosphere colonization by soil-born Trichoderma plant-beneficial strains. One of these is foliar spraying with suspensions containing large amounts of chlamydospores – spores with a thick cell wall structure that makes them highly resistant to harsh environmental conditions. Trichoderma biomass was produced by cultivation on cornmeal medium and compared by microscopic and thermogravimetric analysis with the biomass produced in potato dextrose broth. Both analyses revealed higher chlamydospores content and thicker mycelium in the fungal biomass produced on cornmeal medium. The Trichoderma suspension rich in chlamydospores was sprayed on bitter gourd (Momordica charantia) leaves at two concentration levels, 106 and 108 ufc/ml. The effect of these treatments on plant physiological parameters, leaf photosynthetic pigments, polyphenol and flavonoid contents, antioxidant activity of leaves and fruits and yield was compared to the control (plants sprayed with water) and to the experimental treatment sprayed with 108 ufc propagules produced in potato dextrose broth. The effect of chlamydospore-rich suspensions on plant physiological parameters was more pronounced and long-lasting compared with the other treatments. The treatment with chlamydospore-rich suspension enhanced the accumulation of polyphenols and flavonoids in the leaves and fruits and increased the antioxidant activity. The application of the foliar treatment with Trichoderma suspensions did not modify the cytocompatibility of the extracts from fruits determined on L929 cells.

The study used ERA5 reanalysis SST dataset re-gridded to a common grid of 0.25° X 0.25° spatial resolution (latitude × longitude) for the historic (1940–2014) and projected (2015–2100). The SST simulation under the SSP5-8.5 scenarios was carried out with output from 8 General Circulation Models (GCMs). The bias-corrected dataset was developed using Empirical Quantile Mapping EQM for the historical (1940-2015) and the future (2030-2100) while the CMIP6 model simulation was evaluated against the ERA5 monthly rainfall observed data for monthly and annual sea surface temperatures (SST) over the Gulf of Guinea. ). The CMIP6 models simulation for SST projection from 2030-20100 based on SSPS 8.5 SST is projected to increase by 4.61o (31oC) in 2030 to 35oC in 20100 in the coastal GOG and 2.6oC in the Western GOG (Sahel). The correlation coefficient (r) was used to evaluate the performance of the CMIP6 models and the analysis showed ACCESS 0.1,CAMS CSM 0.2, CAN ESM 0.3, CMCC, 0.3 and MCM, 0.4 indicating that all models performed well in capturing the climatological pattern of the SST. The.CMIP6 bias corrected model simulations showed increased SST warming over the GOG will be higher in the Far period end than the Near-term climate. The study affirmed that the CMIP6 projections can be used for multiple assessments related to climate and hydrological impact studies and for the development of mitigation measures under a warming climate

Candida glabrata (Nakaseomyces glabratus), the second most prevalent Candida pathogen globally, has emerged as a major clinical threat due to its ability to develop high-level azole resistance. In this study, two new 5,6-dihydrotetrazolo[1,5-c]quinazoline derivatives (c11 and c12) were synthesized and characterized using IR, LC-MS, 1Н and 13C NMR spectra. Along with 13 previously reported analogues, these compounds underwent in vitro antifungal testing against clinical C. glabrata isolates using a serial dilution method (0.125-64 mg/L). Remarkably, compounds c5 and c1 exhibited potent antifungal activity, with minimum inhibitory concentrations of 0.37 μM and 0.47 μM, respectively – about 20-fold improvement over standard drugs like amphotericin B, caspofungin, and micafungin. A detailed structure-activity relationship analysis revealed crucial molecular features enhancing antifungal potency. Extensive molecular docking studies across 18 protein targets explored potential binding pockets and affinities of the lead compounds. A robust 3D-QSAR model, incorporating molecular descriptors Mor26m and Mor29e, displayed good predictive ability for antifungal activity. In silico predictions indicated an absence of herbicidal effect, negligible environmental toxicity (to honeybees, avian species, and aquatic organisms), and mild human toxicity concerns for these compounds. This comprehensive approach aims to develop novel and effective antifungal compounds against the clinically relevant pathogen C. glabrata.

The paper discusses the change of meaning and metonymium of Emo in Chinese cyber language here. Drawing on corpus-based analysis of emo posts published in the social media network Sina micro blog, we investigate how such aesthetics and sociocultural meanings attached to being “Emo”serves as a metonymy that enables diverse representations of affective states as well as situated emotion enactments. The findings suggest that the term “Emo”has been stretched as it is no longer confined to emotional events within or possibly just beyond emo, with a broader range of listings reflecting different emotions in various contexts. The metonymical nature of the use of “Emo”in Chinese reflects a broader cultural and social phenomenon occurring today in China -- particularly among some young net users. The research underscores the emotional expression pattern of Chinese netizens, which renders a good reference to comprehensively understand the evolution of language type in digital context.

Requirements elicitation from multiple human sources involves information validation and conflicts resolution to deal with uncertainty inherent in the process. Most requirements analysis methods focus on expressing the requirements and ignore the uncertainty inherent in the process of requirements elicitation. This paper build on the work presented by the author in [1,10], where a method for requirements elicitation from multiple sources was presented. This paper gives an overview of the method and presents detailed case studies. The cases studies were designed to illustrate different aspects of the Source Control Method and to determine its feasibility and its practical utility as a problem investigation and information validation technique.

Introduction: microRNA-181a (miR-181a) is a crucial post-transcriptional regulator of many mRNA transcripts and ncRNAs, influencing cell proliferation, cancer cell stemness, apoptosis, and immune responses. Its abnormal expression has been characterized in numerous cancers, making it a significant genomic vulnerability and biomarker in cancer research. Areas Covered: Here, we summarize miR-181a’s correlation with poor patient outcomes across numerous cancers, and the mechanisms governing miR-181a’s activity and processing. We comprehensively describe miR-181a’s involvement in multiple regulatory cancer signaling pathways, cellular processes, and the tumor microenvironment. We also discuss current therapeutic approaches to targeting miR-181a, highlighting their limitations and future potential. Expert Opinion: miR-181a is a clinically relevant pan-cancer biomarker with potential as a therapeutic target in cancer. Its regulatory control of tumorigenic signaling pathways and immune responses positions it as a promising candidate for more personalized treatments. The success of miR-181a as a target relies on the development of specific therapeutics platforms. Future research on miR-181a's role in the tumor microenvironment and the RNA binding proteins that regulate its stability will help uncover new techniques to targeting miR-181a. Further research into miR-181a serum levels in patients undergoing therapy will help to better stratify patients and enhance therapeutic success.

Dietary intake of Wistar rats of biofortified with 8-hydroxy-7-iodo-5-quinolinesulfonic acid (8-OH-7-I-5QSA) kale of both cultivars ‘Oldenbor F1’ and ‘Redbor F1’ for 8 weeks resulted in sig-nificantly higher iodine concentrations in the urine and kidneys of rats, which proves iodine bio-availability. Rats diets with 'Oldenbor F1' and 'Redbor F1' kale non- and -biofortified with 8-OH-7-I-5QSA had a significantly lower or a tendency for lower concentration of TSH, triglyc-eride, total and direct bilirubin, TBARs, uric acid, aspartate aminotransferase (AST) and alanine aminotransferase (ALT) concentrations in serum. Dietary intake of 'Oldenbor F1' and 'Redbor F1' kale biofortified with 8-OH-7-I-5QSA significantly increased the total antioxidant status (TAS). The study confirms that kale biofortified with iodine in organic form iodoquinoline 8-OH-7-I-5QSA is bioavailable and well absorbed by the Wistar rat and has a positive effect on selected biochemical parameters.

In the past thirty years, childhood obesity rates have risen significantly worldwide, affecting over 340 million children in affluent nations. This surge is intricately tied to metabolic disorders, notably insulin resistance, type 2 diabetes mellitus (T2DM), and the continually evolving spectrum of metabolic-associated (dysfunction) steatotic liver disease (MASLD). This review underscores the alarming escalation of childhood obesity and delves comprehensively into the evolving and dynamic changes of nomenclature surrounding diverse conditions of hepatic steatosis, from the initial recognition of non-alcoholic fatty liver disease (NAFLD) to the progressive evolution into MASLD. Moreover, it emphasizes the crucial role of pediatric endocrinologists in thoroughly and accurately investigating MASLD onset in children with T2DM where each condition influences and exacerbates the progression of the other. The review critically highlights the inadequacies of current screening strategies and diagnosis, stressing the need for a paradigm shift. A proposed solution involves the integration of hepatic magnetic resonance imaging assessment in the diagnostic arsenal for children showing insufficient glycaemic control and weight loss post-T2DM diagnosis, thereby complementing conventional liver enzyme testing. This holistic approach aims to significantly enhance diagnostic precision, fostering improved outcomes in this vulnerable high-risk pediatric population.