Background/Objectives: The aim of the project is a longitudinal assessment of body image and mental health in scoliosis females pre-, postoperatively and in a follow-up, and implementation (one group-CBT scoliosis sample, CBTSS) or not (second group-control scoliosis sample, CSS) of CBT interventions. A healthy female sample (HFS) was also selected for comparative purposes. Methods. 36 in total AIS patients participated in the 1st and 2nd study phases, whereas 23 were eligible in the follow-up. Regarding HFS, 18 participants were included in the study. The CBT intervention took place pre- and postoperatively, during the patients' stay in hospital. Participants completed the Spinal Appearance Questionnaire (SAQ), Body Esteem Scale (BES) and Strengths and Difficulties Questionnaire-25 (SDQ-25). Body image was also assessed using a virtual reality-based application “Avatar Scoliosis 3D”. Results: The difference between the desired and objective, actual body shape is significant preoperatively both in the CBTSS and CSS at p

COVID-19 has substantially influenced healthcare systems, requiring early prognosis for innovative therapies and optimal results, especially in individuals with comorbidities. Healthcare practitioners have used AI systems for investigating, anticipating, and predicting diseases, through means including medication development, clinical trial analysis, and pandemic forecasting. This study proposes the use of AI to predict disease severity in terms of hospital mortality among COVID-19 patients. Methodology: A cross-sectional study was conducted the approval from the Research Ethics Committee of King Abdulaziz University (KAU), Saudi Arabia. The study used sequential sampling approaches to include 50 Real-Time Polymerase Chain Reaction (RT-PCR) positive COVID-19 patients from KAU's coronavirus isolation wards. A pre-designed form was used to collect each patient's demographic information, including age and gender, signs and symptoms, illness severity (mild, moderate, severe), and laboratory findings. Furthermore, the length of the hospital stay and the result, whether the patient recovered or died, were reported. Results: The study involved 50 patients with varying degrees of disease severity, most of whom suffered from fever, fatigue, cough, sore throat, and diarrhoea. Laboratory analysis of COVID-19 patients showed increased white blood cell and platelet counts, with C-reactive protein levels above normal. Elevated LDH levels indicated possible tissue damage, while ferritin levels were elevated. Other enzymes were in the normal range, but bilirubin levels were slightly elevated. Overall, the patient's lab results indicated inflammation and possible blood clot formation. The study evaluated the predictive accuracy for outcomes and mortality of COVID-19 patients based on factors such as CRP, LDH, Ferritin, ALP, Bilirubin, D-dimers, and hospital stay (p-value ≤0.05). The predictive accuracy mortality of patients with COVID-19 using AI showed Hospital stay, D-Dimers ALP, Bilirubin, LDH, CRP, and Ferritin significantly affected hospital mortality. (p ≤ 0.0001). Conclusion: Artificial Intelligence is crucial for identifying early coronavirus infections and monitoring patient conditions. It improves treatment consistency and decision-making via the development of algorithms. AI can track the crisis at various scales, facilitate research, and aid in developing treatment regimens, prevention strategies, and drugs and vaccines. It also aids in monitoring health and facilitating research on the virus.

The escalating global demand for clean water has propelled research into sustainable and cost-effective purification methods. Activated carbon (AC) derived from biowaste materials presents an environmentally friendly and economically viable solution for water treatment. This review article provides an extensive overview of the synthesis techniques, characterization methods, and applications of biowaste activated carbon (BAC) for water purification. It discusses the diverse sources of biowaste, such as agricultural residues, food waste, and biomass, and explores various activation methods including physical, chemical, and biological processes. Furthermore, the article examines the adsorption mechanisms, performance factors, regeneration strategies, and emerging trends in BAC synthesis and application. Insights from this review can guide future research endeavors and facilitate the development of sustainable water purification technologies.

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

Preserving and passing on folk traditions and gastronomic culture to the next generations was an important task of the older age group in every historical era. The most important objective of this study is to reveal people's attitudes regarding to the values of gastronomy and culture in a West Hungarian county. The combined presence of the Szigetköz Nature Park and the World Heritage sites (Fertő-Hanság National Park, Pannonhalma Abbey) in the offer requires re-sponsible, environmentally, socially and economically sustainable tourism planning. In the framework of a quantitative research (questionnaire survey), the tourists’ knowledge of gas-tronomy values and also their knowledge regarding to the architectural, cultural and natural attractions will be analysed. Four hypotheses were formulated in the study. The data collec-tion took place between September 1. 2023 and October 30. 2023 (N=666). The sample is not representative, the respondents were selected arbitrarily and randomly. The most important novelty of the study is that in contrast to previous studies, in this study, tourists' visits to different destinations were measured, while previous studies focused on tourists' interests.

We develop a primality test for Mersenne numbers and investigate the primality of the sequence of Catalan-Mersenne numbers. We use induction as a proof to show that the 5th Catalan-Mersenne number is a prime number, thus demonstrating the infinitude of Mersenne primes.

This study explores innovative strategies to enhance hands-on learning experiences in a Database Management Systems (DBMS) course while addressing challenges related to software installation complexities and financial barriers. The investigation focuses on an online course format catering to students majoring in information systems, healthcare administration, business administration, and marketing. Traditional software installation hurdles, especially for complex systems like Microsoft Access and MySQL, can impede students' engagement and access. To overcome these challenges, the study proposes leveraging cloud-based solutions and clientless remote desktop gateways like Apache Guacamole. Results indicate that these approaches effectively eliminate software installation obstacles, ensuring seamless access to essential tools for all students. The study underscores the importance of innovative technological solutions in promoting inclusive and impactful learning environments in higher education.

The rapid and accurate detection of viruses and the discovery of single nucleotide polymorphisms (SNPs) are crucial for disease management and understanding viral evolution. In this study, a pipeline for virus detection, validation, and SNP discovery from next-generation sequencing (NGS) data is presented. By integrating state-of-the-art bioinformatics tools with artificial intelligence, the pipeline processes raw sequencing data to identify viral sequences with high accuracy and sensitivity. Before aligning the reads to the reference genomes, quality control measures and adapter trimming are performed to ensure the integrity of the data. Unmapped reads are subjected to de novo assembly to reveal novel viral sequences and genetic elements. The effectiveness of the pipeline is demonstrated by the identification of virus sequences, illustrating its potential for the detection of known and emerging pathogens. SNP discovery is performed using a custom Python script that compares the entire population of sequenced viral reads to a reference genome. This approach provides a comprehensive overview of viral genetic diversity and identifies dominant variants and a spectrum of genetic variations. The robustness of the pipeline is confirmed by the recovery of complete viral sequences, which improves our understanding of viral genomics. This study highlights the synergy between traditional bioinformatics techniques and modern approaches, providing a robust tool for analyzing viral genomes and contributing to the broader field of viral genomics.

Stroke constitutes a significant public health concern due to its impact on mortality and morbidity. This study investigates the utility of machine learning algorithms in predicting stroke and identifying key risk factors using data from the Suita study, comprising 7,389 participants and 53 variables. Initially, unsupervised K-prototype clustering categorized participants into risk clusters, while five supervised models including Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Light Gradient Boosted Machine (Light-GBM) were employed to predict stroke outcomes. Stroke incidence disparities among identified risk clusters using the unsupervised K-prototype clustering method are substantial, according to the findings. Supervised learning, particularly RF was a preferable option because of the higher levels of performance metrics. The Shapley Additive Explanations (SHAP) method identified age, systolic blood pressure, hypertension, estimated glomerular filtration rate, metabolic syndrome, and blood glucose level as key predictors of stroke, aligning with findings from the unsupervised clustering approach in high-risk groups. Additionally, previously unidentified risk factors such as elbow joint thickness, fructosamine, hemoglobin, and calcium level demonstrate potential for stroke prediction. In conclusion, machine learning facilitated accurate stroke risk predictions and highlighted potential biomarkers, offering a data-driven framework for risk assessment and biomarker discovery.

A contemporary technique for calculating seismic risk is earthquake nowcasting (EN), which analyzes the progression of the earthquake (EQ) cycle in fault systems. 'Natural time' is a novel idea of time that serves as the foundation for EN assessment. The earthquake potential score (EPS), which has been discovered to have useful uses regionally and worldwide, is a unique tool EN uses to predict seismic risk. For the estimation of the EPS for the occurrences with the highest magnitude among these applications, we have since 2021 concentrated on Greece territory, applying sophisticated Artificial Intelligence (AI) algorithms, both wise (semi)supervised and unsupervised models, along with a customized dynamic sliding window technique that performs as a stochastic filter able to fine-tune the geo seismic occurrences. Long short-term memory (LSTM) neural networks, random forests, and clustering (geospatial) models are three machine learning techniques that are particularly good at finding patterns in vast databases and may be used to enhance earthquake prediction performance. In this study, we attempt to forecast whether practical Machine-learning and AI/Game-theoretic-based approaches can help predict big earthquakes and the normal future seismic cycle for 6-12 months. Specifically, we focus on answering two questions for a given region: (1) Is there a chance that a significant earthquake—say, one with a magnitude of M ≥ 6.0 will happen in the upcoming year? (2) What is the largest earthquake magnitude predicted in the upcoming year, and with which exact geographic coordinates (GCS)? Our results are quite promising and project a high precision accuracy score (≥ 98%) for seismic nowcasting in terms of four predictive parameters: the approximate (a) latitude, (b) longitude, (c) focal depth, and (d) magnitude of the phenomena.

Electric vehicles (EVs) play a significant role in reducing carbon emissions. In the US, EVs are mostly owned by multi-vehicle households, and their usage is primarily studied in the context of vehicle miles traveled. This study takes a unique approach by analyzing EV usage through the lens of vehicle choice (between EVs and internal combustion engine vehicles) within multi-vehicle households. A two-step machine-learning framework (clustering and decision trees) is proposed. The framework determines the preferred trip category for EV use and captures the effects of household attributes, driver attributes, built-environment factors, and gas prices on EV use in multi-vehicle households. Results indicate that discretionary trips (accumulated local effect = 0.037) are mostly preferred for EV use. EV preference is more pronounced among households with fewer workers (<2) and lower income levels. These findings are valuable for policymakers and auto manufacturers in targeting specific market segments and promoting EV adoption.

Origin, mechanics and properties of the Solar System are analysed in the framework of the Complete Relativity theory (by the same author). According to Complete Relativity, everything is relative. Any apparent absolutism (notably invariance to scale of dimensional constants, absolute elementariness, invariance to time) is an illusion stemming from limits imposed by [or on] polarized observers that will inevitably lead to misinterpretation of phenomena (another illusion) occurring on non-directly observable scales or even on observable but distant scales in space or time. If everything is relative, reference frames will exist where particles are planets and where planets are living beings. Earth is, therefore, analysed here in more detail, both as a particle and, as a living evolving being (of, hypothesized, extremely introverted intelligence). The analysis confirms the postulates and hypotheses of the theory (ie. existence of discrete vertical energy levels) with a significant degree of confidence. During the analysis, some new hypotheses have emerged. These are discussed and confirmed with various degrees of confidence. To increase confidence or refute some hypotheses, experimental verification is necessary. Main conclusions that stem from my research and are further confirmed in this paper are: universes are, indeed, completely relative; Solar System is a scaled (inflated, in some interpretations) Carbon isotope with a nucleus in a condensed (bosonic) state and components in various vertically excited states; life is common everywhere, albeit extroverted complex forms are present on planetary surfaces only during planetary neurogenesis; anthropogenic climate change is only a part (trigger from one perspective) of bigger global changes; major extinction events on a surface of a planet are relative extinctions, a regular part of transformation and transfer of life in the process of planetary neurogenesis.

Pulmonary hypertension (PH) is a serious condition linked to immune-system dysfunction. Myositis-specific/associated antibodies (MSA/MAA) play a role in idiopathic inflammatory myopathy (IIM) and interstitial lung disease (ILD), but their significance in PH remains unclear. We believe the presence of these antibodies, may be underestimated. This study analyzed adult PH patients without pre-existing IIM for MSA/MAA prevalence using a line-blot assay. We compared PH patients with and without ILD signs to a cohort clinically suspected of IIM/ILD (n=558). Our PH cohort (n=121) showed a significantly higher prevalence of overall weak positive MSA/MAAs and positive overlap syndrome-associated MAAs than the suspected IIM/ILD group (p

Previous research has already examined the relationship between Future Anxiety, a construct recently introduced in Italy, and mental health in young adults, although possible mediating variables in this relationship have so far never been investigated. The present study attempts to fill this gap by exploring the incidence of Future Anxiety on psychological distress in a group of 302 young Italian adults (18 - 30 years; M = 21.9; SD = 2.6), presenting and evaluating the simultaneous mediating effect of Intolerance of Uncertainty and Non-Pathological Worry.Findings highlighted how Future Anxiety had a positive and significant direct effect on Stress and Depression, but not on Anxiety. In the three serial mediation models proposed, Intolerance of Uncertainty and Non-Pathological Worry mediated the relationship between Future Anxiety and mental health outcomes. The results also confirmed the hypothesized serial mediation effect by highlighting how young adults with greater Future Anxiety experienced more Intolerance of Uncertainty, which positively affected Non-Pathological Worry levels and, in turn, exacerbated psychological distress. Finally, results indicated that female participants experienced more Stress, Anxiety, and Depression in relation to Future Anxiety compared to males. Starting from the review of main references on this subject, the results discussed provide new insights for understanding youth psychological distress. Finally, practical implications for the design of supportive interventions for this study’s target group are proposed.

Throughout the evolution of machine learning, the size of models has steadily increased as researchers strive for higher accuracy by adding more layers. This escalation in model complexity necessitates enhanced hardware capabilities. Today, state-of-the-art machine learning models have become so large that effectively training them requires substantial hardware resources, which may be readily available to large companies but not to students or independent researchers. To make the research on machine learning models more accessible, this study introduces a size reduction technique that leverages stages in Pyramid Training and Similarity Comparison. Our results demonstrate that pyramid training can reduce model complexity while maintaining accuracy of conventional full-sized models, offering a scalable and resource-efficient solution for researchers and practitioners in hardware-constrained environments.

Over the last decade, the prevalence of health issues has increased by approximately 29.1%, putting a substantial strain on healthcare services. This has accelerated the integration of machine learning in healthcare, particularly following the COVID-19 pandemic. The utilization of machine learning in healthcare has grown significantly, however many present approaches are unsuitable for real-world implementation due to high memory footprints and lack of interpretability. We introduce DeClEx, a pipeline designed to address these issues. DeClEx ensures that data mirrors real-world settings by incorporating gaussian noise and blur and employing autoencoders to learn intermediate feature representations. Subsequently, our convolutional neural network, paired with spatial attention, provides comparable accuracy to state of the art pre-trained models while achieving threefold improvement in training speed. Furthermore, we provide interpretable results using explainable AI techniques. We integrate denoising and deblurring, classification and explainability in a single pipeline called DeClEx.

This study examines the synergistic interaction between the immunomodulatory functions of lactic acid bacteria postbiotics and the anti-inflammatory properties of Smilax China L. extract through a combined fermentation process. Using atopic dermatitis (AD) as a model, characterized by an immune imbalance that leads to skin inflammation, we developed a fermented product, MB-2006, and compared its effects to those of heat-killed probiotics, Lactobacillus acidophilus (LAC) and Lac-tobacillus rhamnosus (LRH). Our experiments focused on elucidating the mechanism of action of MB-2006 in AD-like HaCaT keratinocyte cells, particularly its impact on the NF-kB pathway, a pivotal regulator of inflammation. MB-2006 proved more effective in reducing inflammation markers such as IL-4 and thymic stromal lymphopoietin (TSLP), and in inhibiting NF-kB activation, compared to LAC and LRH. Significantly, MB-2006 also reduced the expression of thymus- and activation-regulated chemokine (TARC), highlighting a synergistic effect that enhances its thera-peutic potential. These results suggest that the combined fermentation of Smilax china L. extract with lactic acid bacteria enhanced both the anti-inflammatory and immunomodulatory effects, pre-senting a promising integrative approach to treating conditions like AD. Further studies are needed to validate these results in clinical settings and fully explore the potential of this synergistic fer-mentation process.

This study aims to analyze various types of pellet fuels used as energy sources in Bulgaria, focusing on their energy characteristics and the consumer preferences. Both standard and specialized methods such as thermogravimetry (TG) and differential scanning calorimetry (DSC) are used for the analyses. The results from TG and DSC indicate that during the drying of the samples, moisture is evaporated from their surface, along with the release of volatile substances. The processes during the analysis are accompanied by energy absorption, with the main stage being combustion, where the primary amount of heat is generated. Standard analysis methods show that wood pellets usually contain about 7.31% moisture, 0.72% ash and have a calorific value of 18.33 kJ/kg, while sunflower pellets contain about 7.62% moisture, 2.42% ash and have a calorific value of 19.63 kJ/kg. Mixed pellets contain about 7.07% moisture, up to 0.69% ash and have a calorific value of 18.05 kJ/kg. A specialized marketing research was conducted to investigate consumer attitudes and preferences toward purchasing different types of solid biomass fuels on Bulgarian market. This study provides information on the quality of pellets as fuel by offering a detailed analysis of their fuel properties and ensuring their effective utilization as an energy source.

To regulate the growth of battery-based electric vehicles (BEVs) in Indonesia and mitigate their impact on the power grid's supply-demand balance, the government can adjust BEV regulations and offer subsidies. The Jawa-Madura-Bali (Jamali) electrical system, being the largest in Indonesia [1], faces the challenge of accommodating the increasing number of vehicles [2]. Subsequent to analyzing Jamali's electricity supply using data from the National Electricity Company (RUPTL) [3], simulations are constructed to model the grid's demand side. Input variables such as Jamali's population, internal combustion engine (ICE) and electric vehicle populations, initial charging time (ICT), slow- and fast-charging ratios, and BEV charge load curves are simulated. Scenario variables like supply capacity growth speed, vehicle population growth speed, subsidy impact on EV attractiveness, ICT, and fast-charging ratio are subsequently simulated for 2024-2029. Four key simulation outcomes are identified: the best-case scenario (Scenario 1776), achieves the highest EV growth with minimal grid disruption, resulting in a 45.38% EV percentage in 2029 and requiring an annual allocation of 492 billion rupiah to match supply with demand. The worst outcome scenario leads to a 23.12% EV percentage, necessitating 47.566 billion rupiah for EV subsidies in 2029. Additionally, the most and least probable scenarios based on literature research are evaluated. This simulation and its results provide insights into EV growth's impact on the grid's balance in one presidential term from 2024 to 2029 [4], aiding the government in planning regulations and subsidies effectively. Improving the simulation's accuracy depends on refining input variables over time.

Cisplatin is an election chemotherapeutic agent for many cancer treatments. Its cytotoxicity against neoplastic cells is mirrored by that taking place in healthy cells and tissues, resulting in serious adverse events. A very frequent one is ototoxicity, causing hearing loss which may permanently affect quality of life after successful oncologic treatments. Exacerbated oxidative stress is a main cytotoxic mechanism of cisplatin, including ototoxicity. Previous reports have shown antioxidant protection against cisplatin ototoxicity, but there is a lack of comparative studies on the otoprotectant activity and mechanism of antioxidant formulations. In this paper we report that a combination of vitamins A, C, E and Mg++ (ACEMg), previously shown to protect against noise-induced hearing loss, reverses auditory threshold shifts, promotes outer hair cell survival, and attenuates oxidative stress in the cochlea after cisplatin treatment, thus protecting against extreme cisplatin ototoxicity in the rat. The addition of 500 mg N-acetylcysteine (NAC), which administered individually also shows significant attenuation of cisplatin ototoxicity, to the ACEMg formulation, results in degradation of ACEMg otoprotection. Mg++ administered alone, as MgSO4, also prevents cisplatin ototoxicity, but in combination with 500 mg NAC, otoprotection also is greatly degraded. Increasing the dose of NAC to 1000 mg, also results in dramatic loss of otoprotection activity compared with 500 mg NAC. These findings support that single antioxidants or antioxidant combinations, particularly ACEMg in this experimental series, have significant otoprotection efficacy against cisplatin ototoxicity. However, an excess of combined antioxidants and/or elevated doses, above a yet to be defined “antioxidation threshold”, results in unrecoverable redox imbalance with loss of otoprotectant activity.

Abstract: Effectiveness of a Single Fixed Dose 3 mg Rasburicase for Prevention and Management of Hyperuricemia of Tumor Lysis Syndrome in adult Cancer Patients Background: Tumor lysis syndrome (TLS) is a potentially life-threatening complication associated with certain types of cancer. Rasburicase is an essential medicine required to prevent and treat the hyperuricemia associated with TLS. Due to a shortage of rasburicase during the COVID-19 pandemic, a fixed dose strategy of 3 mg rasburicase had been used in many adult cancer patients in our center. Objective: The objective of this study was to assess the effectiveness of a 3 mg fixed dose of rasburicase in preventing and managing hyperuricemia associated with TLS in adult cancer patients. Methods: We conducted a retrospective, observational cohort study between March 2020 and November 2022. The study included adult patients who received a fixed dose of 3 mg rasburicase. The primary outcome measure was the reduction in serum UA levels of

The review emphasizes the importance of the petroleum refining industry in Iraq, highlighting the environmental obstacles it presents. The industry's significant role in the country's economy necessitates a crucial evaluation and improvement of the environmental impact of oil refining in Iraq. The study scrutinizes the progression of crude oil refining techniques, from basic distillation to advanced technologies like vacuum distillation, thermal cracking, and catalytic cracking, all of which are associated with environmental damage. The refining processes produce hazardous gases such as carbon dioxide, carbon monoxide, sulfur oxides, and nitrogen oxides. Refineries also consume substantial amounts of water and discharge effluent, causing environmental issues. It highlights that significant solid waste is produced throughout the refining process, contributing to the environmental difficulties caused by the petroleum industry in Iraq. The paper proposes several approaches to enhancing the environmental performance of Iraq's petroleum refining processes through a comprehensive environmental impact assessment, focusing on identifying problematic areas, measuring environmental damage, and proposing solutions. It provides insights into the types of waste generated in Iraqi refineries, such as polluted hydrocarbon liquids, and highlights the environmental impact of leaks and spills from oil and byproducts, affecting groundwater and soil quality. The paper suggests reusing consumable auxiliary agents and mineral elements in other industrial fields to minimize waste generation, as well as employing advanced technologies like artificial intelligence and machine learning for efficient refining processes and reduced effluents. By offering suggestions to policymakers, industry stakeholders, and environmental regulators in Iraq, the study aims to inform sustainable practices and environmental management strategies within the petroleum refining sector, contributing to improved environmental outcomes and sustainable development in the industry.

Viral contamination in the aquaculture industry is a significant challenge that requires further research. Emerging evidence suggests that long noncoding RNAs (lncRNAs) play a role in regulating various biological processes, including immunity. However, most studies have focused on model organisms, and little is known about non-coding RNAs in the immune response to viral hemorrhagic septicemia (VHS) in rainbow trout. In this study, we investigated the listing of non-coding RNAs (ncRNAs) in rainbow trout challenged with VHS virus. We explored their potential role in defense-like responses based on transcriptomic analysis of the virus-treated and control groups. As a result of this research, 4207 lncRNAs were identified, of which 182 lncRNAs were differentially expressed between treated and untreated samples. Among 7753 lncRNA transcripts, 1920 were novel intergenic (class code “u”), and 3748 transcripts were potentially novel isoform of lncRNAs. Gene ontology analysis revealed biological pathways associated with the stress response and immune signaling. Pairs of genes such as TP63-MSTRG.62, IL10-MSTRG.9783, IL10-MSTRG.9784, TK1-MSTRG.22826, and MSTRG.17881-GLI1 showed cis interactions, while DOCK10-MSTRG.30015, MSTRG.36357-LOC101268921, and MSTRG.34190-ENPP2 showed trans interactions. In this study, the role of lncRNAs in regulating the expression of the target genes was clearly identified. This finding is consistent with the regulatory processes of immune system responses mediated by cytokines, as well as the regulation of oxygen levels in response to viral infection. The information presented here highlights the various regulatory mechanisms of lncRNAs in the expression of immune system genes in fish treated with VHS virus.

To address the problems of insufficient semantic fusion between text and questions and the lack of consideration of global semantic information encountered in machine reading comprehension models, we proposed a machine reading comprehension model called BERT_hybrid based on BERT and hybrid attention mechanism. In this model, BERT is utilized to separately map the text and questions into the feature space. Through the integration of Bi-LSTM, attention mechanism, and self-attention mechanism, the proposed model achieves comprehensive semantic fusion between text and questions. The probabilities distribution of answers is computed using Softmax. Experimental results on the public dataset DuReader demonstrate that the proposed model achieves improvements in BLEU-4 and ROUGE-L scores compared to existing models. Furthermore, to validate the effectiveness of the proposed model design, we analyze the factors influencing the model’s performance.

Estrogen receptor-positive (ER+) breast cancer is common among postmenopausal women and is frequently treated with Letrozole. Letrozole inhibits aromatase from synthesizing estrogen from androgens. Decreased estrogen slows the growth of tumors and can be an effective treatment. Letrozole resistance is increasingly being observed, which poses a unique problem for patients. We reanalyzed transcriptomic data comparing individuals who responded to Letrozole therapy (responders) to those who were resistant to treatment (non-responders). We identified SOX11 and S100A9 as two genes that significantly differed between these patients; with “PLK1 signaling events” being the most significant signaling pathway. We also identified PRDX4 and E2F8 as the top transcriptional biomarkers for ER+ treatment resistance. Many of the other significant gene products play a known role in ER+ breast cancer or other types of cancer, which partially validate our results. Several of the gene products we identified do not have a characterized role in ER+ breast cancer. Our analysis identified a set of genes that warrant further research to elucidate the molecular mechanism of Letrozole resistance in this patient population, as well as novel high-performing biomarkers. We anticipate that these findings could contribute to improved therapeutic outcomes in human patients.

The next-generation communication systems demand integration of sensing, communication, and power transfer (PT) capabilities, requiring high spectral efficiency, energy efficiency, and low cost, while also necessitating robustness in high-speed scenarios. Integrated sensing and communication systems (ISACS) exhibit the ability to simultaneously perform communication and sensing tasks using a single RF signal, while simultaneous wireless information and power transfer (SWIPT) systems can handle simultaneous information and energy transmission, and orthogonal time frequency space (OTFS) signals are adept at handling high Doppler scenarios. Combining the advantages of these three technologies, a novel cyclic prefix (CP) OTFS based integrated simultaneous wireless sensing, communication, and power transfer system (ISWSCPTS) framework is proposed in this work. Within the ISWSCPTS, the CP-OTFS matched filter (MF) based target detection and parameters estimation (MF-TDaPE) algorithm is proposed to endow the system with sensing capabilities. To enhance the system’s sensing capability, a waveform design algorithm based on CP-OTFS ambiguity function shaping (AFS) is proposed, which is solved by iteratively method. Furthermore, to maximize the system’s sensing performance under communication and PT Quality of Service (QoS) constraints, a semidefinite relaxation (SDR) beamforming design (SDR-BD) algorithm is proposed, solved using through SDR technique. Simulation results demonstrate that the ISWSCPTS exhibits stronger parameter estimation performance in high-speed scenarios compared to orthogonal frequency division multiplexing (OFDM), waveform designed by CP-OTFS AFS demonstrates superior interference resilience, and beamforming designed by SDR-BD strikes a balance in the overall performance of the ISWSCPTS.

Introduction: Type 1 diabetes mellitus is a chronic disease of autoimmune etiology that is highly prevalent in childhood. In the last decade, the possibility of using the Bacillus Calmette-Guérin vaccine for the treatment of this disease has been studied thanks to its immunomodulatory action . Objectives: The objective of this work is to carry out a systematic review of the available scientific evidence on the relationship between the tuberculosis vaccine and the treatment of diabetes in childhood. Secondarily, the aim is to study the incidence of Type 1 Diabetes Mellitus in a cohort of children from the Basque Country according to whether or not they have received the vaccine. Methods: An exhaustive bibliographic search has been carried out on the evidence available to date. For the epidemiological study in Euskadi, a comparison of accumulated incidences between vaccinated and unvaccinated population groups was made. Results: According to the literature analyzed, There is more and more evidence about the possible use of the tuberculosis vaccine in Type 1 Diabetes Mellitus. The results of our study were not conclusive, but we believe that it is necessary to continue with long-term studies to eliminate biases. Conclusions: The Bacillus Calmette-Guérin vaccine could be used for the treatment of autoimmune, allergic, infectious or oncological processes, although more studies are still necessary in this regard.

Dielectric barrier discharge (DBD) plasma has several applications in different fields. One of these fundamental applications is medical usages, where various methods are employed to improve the plasma treatment process. The combination of different gases is one of the important strategies to improve the performance of plasma in treatment. In this paper, the optimized plasma parameters for one-dimensional radiofrequency discharge produced at low pressures in a helium gas combination is studied. In this research, the optimal combination of H₂O and He is identified to attain the highest amount of reactive oxygen species (ROS). Considered mixture are 5,10,15 and 20 precent of H₂O for one dimensional helium gas discharge. The results show that the parameters of the output plasma are highly dependent on the composition of the input gases. It is found that the greatest concentrations of H+, He+, Hes (excited helium), and OH/ densities are observed when the H₂O percentage is 10%. Moreover, the density distributions of various species and the temperatures of electrons are numerically calculated during the electrical discharge process. These findings provide useful knowledge on how to optimize plasma parameters for biomedical applications, which may lead to improved treatment results in several therapeutic areas.

This manuscript offers a concise overview of paper microfluidics, emphasizing its sustainable sensing applications in healthcare, environmental monitoring, and food safety. Researchers have developed innovative sensing platforms for detecting pathogens, pollutants, and contaminants by leveraging the paper’s unique properties, such as biodegradability and affordability. These portable, low-cost sensors facilitate rapid diagnostics and on-site analysis, making them invaluable tools for resource-limited settings. The review discusses fabrication techniques, principles, and applications of paper microfluidics, showcasing its potential to address pressing challenges and enhance human health and environmental sustainability.

This paper investigates calendar anomalies, volatility patterns, and the best forecasting model for predicting volatility in the cryptocurrency market, focusing on ten prominent cryptocurrencies: Binance USD, Bitcoin, Binance Coin, Cardano, Dogecoin, Ethereum, Solana, Tether, USD Coin, and Ripple. Spanning from January 2016 to December 2023, the study utilizes sophisticated statistical models such as GARCH (p,q), EGARCH (p,q), and GJR-GARCH (p,q) to analyze precise changes in market dynamics and the impact of day-of-week fluctuations on cryptocurrency returns. Empirical evidence reveals significant findings regarding the persistence of volatility, positive and negative news effects on volatility, and day-of-week effects on cryptocurrency returns. Post-COVID-19, Sunday emerges as the least volatile day for cryptocurrencies, while Thursdays and Tuesdays exhibit greater volatility. Binance, Ethereum, Dogecoin, and Tether show anomalies where returns on Tuesday and Thursday significantly differed from those on other days of the week. Many other currencies, like the USD coin, Cardano, and Ripple, show anomalies only in the pre-COVID-19 period. The findings highlight the best forecast model for volatility for each top cryptocurrency, offering practical implications for investors, traders, regulators, and policymakers. These insights emphasize the importance of understanding and addressing calendar anomalies in the cryptocurrency market for informed decision-making, trading strategies, regulatory frameworks, and market stability.

This study investigates the petroleum potential of the Middle Jurassic Khatatba Formation (Fm) in the Matruh Basin, northwestern Egypt. This formation shows in situ dual source and reservoir characteristics, where alternations of fine and coarse clastics were deposited during semi-arid and semi-humid conditions due to climate changes and Tethyan sea level fluctuations. The organic-rich shales and argillaceous siltstones are fair to very good/excellent (TOCm wt%: 0.91–3.07) source rocks. They are rich in late mature to early postmature mostly gas-prone organic facies C, which sourced the juxtaposing intraformational coarse clastics of the Lower Safa Member with gas and condensates. The source rocks show poor to fair gas generation potential (S2: 0.38–1.96, mg HC/g rock). The middle part of the Lower Safa Member shows excellent organic richness (TOCm wt%: 5.39 and 22.90) of early postmature gas-prone carbonaceous material and coal deposits. These coaly shale layers exhibit fair to excellent wet gas and condensate generation potential (S2: 4.51–27.43, mg HC/g rock). Maturation of the source rocks was related to the Late Jurassic–Early Cretaceous Tethyan rifting. The onset of oil generation occurred in the Early Cretaceous (~ 116 Ma ago), while the onset of gas generation occurred in the Oligocene (~ 24 Ma ago). Shales of the Lower Cretaceous Alam El Bueib Fm are primary sealing rocks, while carbonates and shales of the Khatatba Fm are secondary sealing rocks. Trap types are structural, formed during the Late Jurassic and Early Cretaceous rifting of the Matruh Basin. Sandstones of the Upper Safa Member show upward increases in kaolinite and exhibit low-quality tight sandstone reservoirs. The Lower Safa Member sandstones show better gas reservoir quality with lower shale volumes. Operationally, the Lower Safa sandstone reservoirs in the Imhotep W-1X well are not suitable for gas production because they are ductile and show a high decline in production and pressure. Overall, the petroleum system of the Khatatba Fm shows mainly fair hydrocarbon potential in the study area.

This study examines HIV/AIDS-associated knowledge and attitudes towards treating disadvantaged communities among predoctoral dental students in U.S. dental schools who had not yet commenced their Community-Based Dental Education (CBDE) training. It also compares the difference in knowledge and attitudes between students with reported community engagement with PLWHA, and those without. Our study comprised 89 predoctoral dental students within their D1-D3 years of dental school who had not yet initiated their Community-Based Dental Education (referred to as pre-CBDE dental students). Responses were collected via an online survey. Participants were 68% females, 94% heterosexual, of mean age (years): 25.9 ± 3.5 SD. The majority (62%) were in their first (D1) and second (D2) years of dental education. Of the thirty knowledge questions, only five received a minimum of 90% correct responses. Similarly, we found no statistical differences in most of the knowledge/attitude sections, between those with and without prior PLWHA exposure. Encouragingly, 90% of our participants reported prior experience working with disadvantaged communities. Early community engagement fosters a sense of professional responsibility towards administering dental care to disadvantaged communities and we propose that it must be encouraged among aspiring dental school students.

Magnetic quantum oscillations (MQO) are traditionally applied to investigate the electronic structure of metals. In layered quasi-two-dimensional (Q2D) materials the MQO have several qualitative features giving additional useful information, provided their theoretical description is developed. Within the framework of the Kubo formula and the self-consistent Born approximation, we reconsider the phase of beats in the amplitude of Shubnikov oscillations of interlayer conductivity in Q2D metals. We show that the phase shift of beats of the Shubnikov (conductivity) oscillations relative to the de Haas - van Alphen (magnetization) oscillations is larger than expected previously and, under certain conditions, can reach the value of π/2, as observed experimentally. We explain the phase inversion of MQO during the 3D - 2D crossover and predict the decrease of relative MQO amplitude of interlayer magnetoresistance in a strong magnetic field, larger than the beat frequency.

We propose novel spectrometer designs that aim to enhance the measured spectral range 1 of ions on a finite-sized detector. In contrast to the traditional devices that use uniform magnetic 2 field, in which the deflection of particles increases inversely proportional to their momentum, in a 3 gradient magnetic field, the deflection of particles will be decreased due to the reduction of the 4 magnetic field along their propagation. Low energy ions are particularly impacted, as they are 5 deflected less and are more likely to reach the detector compared to being driven out of it while 6 using a uniform magnetic field. By the means of a gradient magnetic field, the nonlinear dispersion 7 of ions in a homogeneous magnetic field can approach a nearly linear dispersion. Nonetheless, 8 the dispersion of low energy ions in a homogeneous magnetic field remains unnecessarily high. 9 In this article, we explore linear, quadratic, and higher-order field profiles in comparison to the 10 homogeneous field case. We discuss the employed methodology and present simulation results of 11 the spectrometer with an extended ion spectral range, focusing on the minimum detectable energy 12 (energy dynamic range) and energy resolution

Alternative splicing is an essential regulatory mechanism for gene expression in mammalian cells contributing to protein, cellular, and species diversity. Isoform switching, the process where cells alter the expression of various splice forms (isoforms) of a gene, plays a critical role in cellular function and adaptation. Our study provides a comprehensive analysis of splice forms prevailing across ten of the most studied human cell lines using public RNAseq data. We analyzed the occurrence of splice forms and found substantial justification for revising the canonical sequences for 56 genes, suggesting that these alternative splice forms should be recognized as canonical. Additionally, distinct profiles of splice form prevalence across these cell lines offer new insights into their specific biological roles. Our findings reinforce and expand upon previous insights into the link between isoform expression and oncological processes. Notably, we identified three genes exhibiting statistically significant changes between cancerous and normal tissues. Moreover, a comparative analysis of prevailing isoforms across diverse cell lines with prior research unveiled 140 common splice variants associated with cancer, highlighting their importance for prognostication and understanding oncogenesis. We revealed unique patterns and variations in isoform switching of these lines that provide new insights into the importance of selecting specific ones for research.

Background: This study aimed to investigate the impact of the COVID-19 pandemic on breast reconstruction trends in the United States, focusing on implant-based and autologous techniques, as well as the timing of reconstruction (immediate vs. delayed). Methods: A retrospective analysis of data from the American Society of Plastic Surgeons' National Plastic Surgery Statistics from 2015 to 2022 was conducted. Annual trends in breast reconstruction procedures were analyzed, comparing the pre-pandemic (2015-2019) and pandemic (2020-2022) periods. Results: The total number of breast reconstructions increased from 106,338 in 2015 to 151,641 in 2022. The proportion of implant-based reconstructions decreased from 81.41% pre-pandemic to 76.51% during the pandemic (p < 0.001), with a notable rise in direct-to-implant procedures from 10.37% to 19.12% (p < 0.001). Autologous reconstructions increased from 18.59% to 23.49% (p < 0.001). Among autologous techniques, DIEP flaps remained the most popular. Immediate reconstruction rates increased from 72.61% pre-pandemic to 75.57% during the pandemic, while delayed recon-struction rates decreased from 27.39% to 24.43% (p < 0.001). Conclusions: The COVID-19 pandemic has significantly influenced breast reconstruction trends in the United States, with a shift towards autologous techniques, particularly DIEP flaps, and an in-crease in immediate reconstructions. These changes may reflect adaptations in surgical practice and decision-making processes in response to the unique challenges posed by the pandemic. Further research is needed to assess the long-term outcomes and patient satisfaction associated with these trends.

This study investigates the fixed-time consensus-based attitude control problem for large telescope on-orbit construction subject to discrete-time communication, unknown tiny disturbance torque, model uncertainty, and actuator saturation under an undirected communication graph. Motivated by the need to save wireless communication resources, the communication scheme was designed to exploit interference, which can save communication resources in proportion to the number of modular unit mirrors. Then, a fixed-time observer with discrete-time communication was proposed, which also handles the unknown channel attenuation problem when exploiting information interference. Moreover, based on the backstepping procedure and the suitably defined adaptive compensation law, the fixed-time attitude consensus control law was proposed to handle unknown tiny disturbance torque, model uncertainty, and actuator saturation. Finally, comparative simulation results were provided to verify the effectiveness of the fixed-time observer and proposed fixed-time control law.

Brake wear particles, as the major component of non-exhaust particulate matter, are known to have different emissions, depending on the type of brake assembly and the specifications of the vehicle. In this study, brake wear and wear particle mass emissions were measured under realistic vehicle driving and full friction braking conditions using current commercial genuine brake assemblies. Although there were no significant differences in either PM₁₀ or PM_2.5 emissions between the different cooling air flow rates, brake wear decreased and ultrafine particle (PM_0.12) emissions increased with increasing cooling air flow rate. Particle mass measurements were collected on filter media, allowing chemical composition analysis to identify the source of brake wear particle mass emissions. The iron concentration in the brake wear particles indicated that the main contribution was derived from disc wear. Using a systematic approach that measured brake wear and wear particle emissions, this study was able to characterize correlations with elemental compositions in brake friction materials, adding to our understanding of the mechanical phenomena of brake wear and wear particle emissions.

This work presents a Fault-Tolerant Model Predictive Control (FTMPC) algorithm applied to a simulation model for sewer networks. The control system will aim to prevent contaminated water from escaping the network, especially during periods of heavy rainfall, that can cause combined sewer overflows (CSO), while maintaining the flow of water towards the wastewater treatment plant (WWTP) as close as possible to its nominal value. The main purpose of the work is to preserve the operation of the predictive controller as much as possible, in accordance with its operational objectives, when there may be anomalies affecting the elements of the control system, mainly sensors and actuators. Comparing the results obtained considering various types of faults, with situations of normal controlled operation and with the behavior of the sewer network when no control is applied, will allow some conclusions to be drawn at the end.

Several series of new polymers were synthesized: binary copolyesters of vanillic (VA) and hydroxybiphenylcarboxylic (HBCA) acids, as well as ternary copolyesters additionally containing hydroxybenzoic acid (HBA) and obtained via three different ways (in solution, in melt and in solid state). The high values of logarithmic intrinsic viscosities and insolubility of several samples proved its high molecular weights. It has been shown that the use of vanillic acid leads to the production of copolyesters with a relatively high glass transition temperature (about 130°C). Thermogravimetric analysis revealed onset of weight loss temperatures of ternary copolyesters occurred at 330-350 °C, the temperature of 5% mass loss is in the range of 390-410 °C. Two-stage thermal destruction is observed for all aromatic copolyester of vanillic acid: decomposition begins with VA units at 420-480 °C, and then decomposition of more heat-resistant units demonstrated above 520 °C. The copolyesters are thermotropic and exhibit a typical nematic type of liquid crystalline order. Mechanical characteristics of copolyesters are close to those for semi-aromatic copolyesters, but are much lower than typical values for fully aromatic thermotropic polymers. Thus, vanillic acid is a mesogenic monomer suitable for the synthesis of thermotropic fully aromatic and semi-aromatic copolyester, but resulting processing temperature must not exceed 280°C.

The theories of Evolution and Big Bang have brought a major impact upon the scientific and societal perception upon the origins, abilities and roles of mankind on Earth. It is conclusively evident that Mother Nature and the physical realm is autonomous and all phenomena in the world occur without an imposition against the “free will” of such events and patterns. Nevertheless, this extent of freedom does not imply that life on Earth represents an accident and has no purpose. By careful analysis of ancient religious texts, it can be suggested even otherwise, that it is especially free will that is offered as a gift from outside of the physical dimensions of existence, with the purpose of a continuous edification and improvement of the overall life conditions and of the human perception. It may be that the multi-generational focus on improvement and progress have been misattributed as a long-term evolution of species, that humans came from animal ancestors and that there is a blurred line associating humans with animals. Furthermore, it may be that scientists based their suggestions that no outside Creator would have brought the Earth into existence on physical perspectives, when the extra-dimensional process of Creation implies that all elements of the physical existence undergo a process of Creation from the outside, where time, space and physical matter do not exist, in spite of such elements possibly reflecting unseen elements of the meta-physical world. Finally, there is the following example that deserves attention within the scientific community; just because all living cells - human, animal and plant - contain DNA chromosomes, ribosomes, mitochondria and a plasma membrane, it does not indicate that humans are animals, just as this does not indicate that plants are animals. In Science, there is a golden statement, that correlation does not imply causation. This example is in complete agreement with the verses of the Book of Genesis in the Holy Scriptures regarding the origins of life; namely, that animals could have been created by an Author of all life on Earth so that man would experience companionship. Another major accordance with the teachings of the Holy Scriptures is the fact that life emerged from the water, and not from the soil, although the soil constituted the second principal means of the commencement and extension of life. Namely, after life first emerged in the seas and the oceans from bacteria, a few bacteria were passed from the marine water into the nearby soil on islands and surrounding land through the circulatory air above the sea level. Afterward, the first life forms emerged from the soil, via the transferred bacteria. Eastern Orthodox Christianity regards water as the principal environment of both physical and spiritual birth. Overall, an improved scientific perception of the timeline of life on Earth may be reached via an approach that combines molecular biology with quantum physics, given that the three layers of Science - Biology, Chemistry and Physics - together with their foundational layer of Mathematics, are in fact situated in a relationship of complete harmony.

The purpose of this qualitative study was to describe parent perceptions of the home exercise pro-gram (HEP) for their infant with congenital muscular torticollis (CMT), and how these perceptions evolved over a physical therapy (PT) plan of care. Twelve participants were recruited from a pediatric PT clinic, and nine completed interviews at three time points. Qualitative description and an iterative approach for thematic analysis of 27 interviews yielded three themes that corresponded to the research questions. The participants’ responses were categorized into three main themes: 1) parents’ perceptions of three key exercises within the HEP; 2) internal and external sources of stress; and 3) sources of empowerment and disempowerment. Regarding the HEP, parents articulated common sentiments for three frequently prescribed exercises for the management of CMT: 1) Tummy time was the fast favorite, 2) ipsilateral cervical rotation was perceived as stressful, and 3) contralateral cervical lateral flexion felt uncomfortable. Additionally, participants disclosed internal and external sources of stress (guilt, uncertainty, and the demands of returning to work) and sources of disempowerment (inconsistent messaging from providers, feeling overwhelmed) and empowerment (being able to see the bigger picture and clear communication and education about the diagnosis) with respect to managing their infant’s CMT. These themes provide insight into the evolution of parent perceptions over a PT plan of care for CMT. Participants’ insights suggest a need for consistent messaging regarding the diagnosis and evidence-based management of CMT, addressing parent stress, and modifying how exercises are taught. This study contributes updated research on parents’ experience with physical therapy and the HEP for their infant’s CMT.

As the educational landscape evolves, understanding and fostering student adaptability has become increasingly critical. This study presents a comparative analysis of (XAI) techniques to interpret machine learning models aimed at classifying student adaptability levels. Leveraging a robust dataset, we employed several machine learning algorithms with a particular focus on Random Forest, which demonstrated a 91% accuracy. Our study utilizes (SHAP), (LIME), Anchors, (ALE), and counterfactual explanations to reveal the specific contributions of various features impacting adaptability predictions. Consistently, 'Class Duration' and 'Financial Condition' emerge as key factors, while the study also underscores the subtle effects of 'Institution Type' and 'Load-shedding'. This multi-faceted interpretability approach bridges the gap between machine learning performance and educational relevance, presenting a model that not only predicts but also explains the dynamic factors influencing student adaptability. The synthesized insights advocate for educational policies accommodating socioeconomic factors, instructional time, and infrastructure stability to enhance student adaptability. The implications extend to informed and personalized educational interventions, fostering an adaptable learning environment. This methodical research contributes to responsible AI application in education, promoting predictive and interpretable models for equitable and effective educational strategies.

Rural areas are not only faced with the problems of rural depopulation but also with the problem of water supply and water quality which is a basic necessity of life. In light of this, this paper assesses the rural water supply situation and the bacteriological quality of different water sources in the Obokun Local Government Area of Osun State, Nigeria. The safety of the water sources for human consumption and possible occurrence of the water borne diseases in the study area were determined. The study employed descriptive and analytical methods of data analysis to achieve the objectives of the inquiry. Findings showed that the study area suffered from inadequate water supply and poor locations of the sources of water: The study also revealed that the microbiological quality of the water sources used was unsafe, poor and not acceptable for human consumption. In addition, many man- days-hours were wasted in search of water. It is therefore recommended that the government should make the rural water supply and the maintenance of water quality a priority in its policy formulation.

We propose that quarks and gluon flux tubes emerge from networks of standing vacuum waves. Each unbound nucleon, in its ground state, may be electromagnetically modeled as massless quantized charge on two pairs of orbiting arcs. Each charge arc is associated with a superposition of radially-oriented vacuum fundamental harmonics. These quantum superpositions of radial waves are coupled to nucleon mass-energy. The charge arcs orbit on the two surfaces of a spindle torus with polar charge-exclusion zones. These ground-state models of unbound nucleons may be interpreted as pairs of virtual Möbius bands. The optimal triangular Möbius band may explain proton uniqueness. These unbound proton and neutron models are shown to be precisely connected via a parameter dependent on neutron mass and the sum of the up and down bare quark masses. Due to this precise connection, and the relatively high experimental precision of proton magnetic moment, neutron magnetic moment is calculated about two orders of magnitude more precisely than the most accurate experiments to date. This quantum network-based approach to modeling unbound low-energy nucleons calculates several other measurable parameters.

The understanding of spatiotemporal variations in reference evapotranspiration (ETo) and its long-term trends is of paramount importance for water cycle studies, modeling, and water resource management, especially in the context of climate change. Therefore, the primary aim of this study is to critically evaluate the performance of various CMIP5 global climate models in simulating the Penman-Monteith reference evapotranspiration and its associated climate variables (maximum and minimum air temperature, incident solar radiation, relative humidity, and wind speed). This evaluation is based on data from nine climate models and 33 automatic meteorological stations (EMA) in the state of Mato Grosso, spanning the period 2007-2020. The statistical metrics used for evaluation include Bias, root mean square error, and Pearson and Spearman correlation coefficients. The projections of the most accurate model were then used to analyze the spatial and temporal changes and trends in ETo under the RCP 2.6, 4.5, and RCP 8.5 scenarios from 2007 to 2100. The HadGEM2-ES model projections indicate static averages similar to current conditions until the end of the century in the RCP 2.6 scenario. However, in the RCP 4.5 and 8.5 scenarios, there is a continuous increase in ETo, with the most significant increase occurring during the dry period (May to September). The areas of the Amazon biome in the north of Mato Grosso exhibit the largest increases in ETo when comparing the observed (2007-2020) and projected (2020-2100) averages. The trend analysis reveals significant changes in ETo and its variables across the state of Mato Grosso in the RCP 4.5 and 8.5 scenarios. In the RCP 2.6 scenario, significant trends in ETo are observed only in the northern Amazon areas. Despite not being observed in all AWSs, the trend analysis of the observed data demonstrates more intense changes in ETo and the existence of the evapotranspiration paradox with an increase in the Cerrado areas and reductions in the Pantanal and southern Amazon areas.

Due to the rapid growth of the Internet of Things (IoT), securing communications between a huge number of devices has become very difficult. Access controls and authentication secure the connection between IoT devices and protect sensitive data from unauthorized users or malicious attackers. In this paper, we provide a comprehensive review to emphasize the critical role of authentication and access control in securing IoT environments. This paper explores different types of access controls, like Attribute-Based Access Control and Role-Based Access Control. Furthermore, it demonstrates different authentication techniques, like passwords and biometrics. Based on the previous mechanisms, we discuss different IoT security challenges regarding authentication and access control mechanisms and highlight future directions. In addition, this paper investigates the integration between access control and authentication to safeguard IoT communications.

This study explored factors influencing the adoption of blockchain technology in US educational settings using the UTAUT2 model. Results from 160 IT officers via an online survey and PLS-SEM analysis showed that performance expectancy and social influence significantly predict behavioral intentions towards blockchain adoption, impacting actual utilization. While some factors like effort expectancy, facilitating conditions, hedonic motivation, price value, and habit did not show significant relationships, this research underscores UTAUT2's relevance in blockchain acceptance in education. Future studies should address limitations and explore diverse stakeholder perspectives for strategic implementation approaches.

The study of ecosystems, both natural and artificial, has historically been mediated by population dynamics theories. In this framework, quantifying population numbers and related variables (associated with metabolism or biological-environmental interactions) plays a central role in measuring and predicting system-level properties. As we move towards advanced technological engineering of cells and organisms, the possibility of bioengineering ecosystems (from the gut microbiome to wildlands) opens several questions that will require quantitative models to find answers. Here, we present a comprehensive survey of quantitative modelling approaches for managing three kinds of synthetic ecosystems, sharing the presence of engineered strains. These include test tube examples of ecosystems hosting a relatively low number of interacting species, mesoscale closed ecosystems (or ecospheres), and macro-scale, engineered ecosystems. The potential outcomes of synthetic ecosystem designs and their limits will be relevant to different disciplines, including biomedical engineering, astrobiology, space exploration and fighting climate change impacts on endangered ecosystems. We propose a space of possible ecosystems that captures this broad range of scenarios and a tentative road map for open problems and further exploration.

It is desirable to upgrade previous evolutionary theories, which have remained incomplete and controversial for decades. Here we employ the concept of carbon-based entities (CBEs), which include methane, amino acids, proteins, organisms, and other entities containing relatively many carbon atoms. We deduce the driving force, mechanisms, steps, modes, tempos of CBE evolution, through integration of biology, physics, and chemistry using logics for complex issues. We hence establish the Carbon-Based Evolutionary Theory (CBET). The CBET suggests that evolution is the increase in hierarchy, diversity, fitness of CBEs under natural selection and driven by thermodynamics due to the chemical effect of the thermodynamic features of the Earth on CBEs. It provides better explanations for life origin, macroevolution events, natural selection, sympatric speciation, and evolution tempos than previous evolutionary theories. It reveals the evolutionary basis of multiple important social notions, including diversity, collaboration, altruism, obeying rules, and proper increase in freedom. It refutes some wrong notions in thermodynamics, including negative entropy (negentropy) and that biological order is equal to thermodynamic order, which have misled many people. The CBET is supported by its deduction and application. It could be a rare bridge linking laws of thermodynamics, evolution of life, and development of human society, and could have great significance in various sciences.

A hemostatic sponge prototype was successfully synthesized from fish gelatin as an alternative to mammalian gelatin, which was mixed with alginate in certain combinations and double cross-linking of calcium ions and gamma irradiation at a dose of 20 kGy to improve the characteristics and effectiveness of its function as a local hemostatic agent. There was an improvement in the physicochemical and mechanical properties, porosity index, absorption capacity, biodegradation properties, biocompatibility, and hemocompatibility of the FGAS prototypes compared with the pure fish gelatin sponge. Hemostatic activity tests showed that the means of clotting time, prothrombin time, and activated partial thromboplastin time were shorter in the FGAS prototype than in the negative control, and there was no significant difference compared with the commercial gelatin sponge. The hemostatic mechanism of the FGAS prototype combined a passive mechanism as a concentrator factor and an active mechanism through the release of calcium ions as a coagulation factor in the coagulation cascade process.

Archaeometry can help archaeologists in multiple instances, one of the common archaeometric goals are the provenance analyses. Volcanic stones appear frequently in archaeological sites as materials used to build grinding tools like millstones and mortars or as building materials. Petrographic characterization is commonly applied to identify their main mineralogical components. However, provenance of volcanic stones is usually undertaken by comparison with geochemical data from reference outcrops using common descriptive statistical tools such as biplots of chemical elements, and unsupervised multivariate data analysis like principal component analysis (PCA). Recently, the use of supervised classification methods has shown a superior performance in assigning provenance to archaeological samples. However, these methods require the use of reference databases for every possibly provenance class to be able to train the used classification algorithms. The existence of comprehensive collections of published geochemical analyses of igneous rocks enables the use of the supervised approach for provenance determination of volcanic stones. In this paper, the provenance of volcanic grinding tools from two archaeological sites (Iulia Libica, Spain and Sidi Zahruni, Tunisia) is attempted using data from the GEOROC Database through unsupervised and supervised approaches.

Quantum computing is tipped to lead the future of global technological progress. However, the obstacles related to quantum software development are an actual challenge to overcome. In this scenario, this work presents an implementation of the quantum search algorithm in Atos Quantum Assembly Language (AQASM) using the quantum software stack my Quantum Learning Machine (myQLM). We present the creation of a virtual quantum processor whose configurable architecture allows the analysis of induced quantum noise effects on the quantum algorithms. The codes are available throughout the manuscript so that readers can replicate them and apply the methods discussed in this article to solve their own quantum computing projects. The presented results are consistent with theoretical predictions and demonstrate that AQASM and myQLM are powerful tools for building, implementing, and simulating quantum hardware.

The movement of liquid droplets on the energy gradient surface has attracted extensive attention. Inspired by biological features in nature, such as the periodic spindle-shaped nodes in spider silks and conical-like barbs of cacti, the structure-property-function relationship of multifunctional gradient surfaces. In this study, a series of specific patterns are fabricated by 3D printing technology, followed by modification via the atmospheric pressure plasma treatment and liquid phase chemical deposition, resulting in enhancing the ability of water droplets of 5μL to travel 18.47mm on a horizontal plane and 22.75mm against gravity up to 20° tilting angle. Additionally, analysis techniques have been employed including contact angle analyzer, ESCA and laser confocal microscope to evaluate the sample performance. This work could further be applied to many applications related to microfluidic devices, drug delivery and water/fog collection.

The construction sector of the Kingdom of Saudi Arabia (KSA), valued at USD 152 billion and employing 2.54 million people by 2023, is crucial to its economy. However, it faces challenges such as delays, disputes, and cost overruns. This study aims to address these issues by implementing Building Information Modeling (BIM) in the KSA, based on an extensive literature review highlighting the role and significance of BIM in mitigating construction claims. BIM improves collaboration, communication, and data integration among stakeholders. Hence, this study proposes a comprehensive BIM package framework comprising Revit Architecture, Microsoft Project, and Cost-X to reduce claims effectively. Validated through a KSA claims case study with a USD 1,870,000 claims value and 360-day delay, the BIM package significantly reduced the claims value to USD 188,000 and saved 275 days. Interview sessions were conducted to validate the effectiveness of the BIM package; 95% favored the use of BIM, 86% supported NEC4 contract adoption alongside BIM, 100% acknowledged BIM's potential in reducing design errors, 95% were confident in the case study's accuracy, and 82% were satisfied with data accuracy. This study confirms that BIM is an effective approach for minimizing construction claims in the KSA.

Age-related diseases place an intense and growing stress on healthcare systems. Numerous theories of ageing exist. Yet prediction, prevention and treatment limitations of age-related disease persist because we lack a complete aetiological understanding of their origins. Here we propose a new theory that aims to provide a blueprint-type understanding of ageing and disease aetiology, working across multiple scientific disciplines. Supported by specific examples, we demonstrate that the primary driver of much of age-related diseases is the futile triggering of specific molecular pathways in a pathological manner, which we term patho-pathways. Patho-pathways induce pathological cell, tissue and system changes in the form of hyperactivity (undesirable increased and new biological activities that are typical of age related disease). As part of patho-pathways, all wild-type (normal) genes have the potential to contribute to age-related diseases (though specific risk varies and can be formularised). In a domino-style effect, one patho-pathway typically triggers others, resulting in complex, but traceable, cascades. Utility, in terms of changing clinical and scientific practice, is derived from mapping these cascades to create Blueprint Maps that allow identification of biomarkers and therapeutic targets far upstream in the causal chain of events. Finally, our theory provides testable hypotheses concerning predictions of links between otherwise seemingly disparate diseases as well as new interventions into ageing.

(1) Background: Since microplastics in the aquatic environment are difficult to prevent and can cause adverse physiological and biochemical reactions to various organisms, we aimed to analyze the effectiveness of an eco-friendly removal method using aquatic plants with high ornamental value and excellent water purification ability. (2) Methods: Iris pseudacorus and Lythrum anceps were planted in tap water contaminated with microplastics to analyze the removal rate and root adsorption of microplastics. (3) Results: The amount of microplastics in the planting boxes of Iris pseudacorus and Lythrum anceps was significantly reduced, and the adsorption of microplastics on the roots was confirmed. (4) Conclusions: It was found that the removal of microplastics in water by aquatic plants is effective and that microplastic pollution does not significantly affect plant growth. However, the removal of microplastics by adsorption on plant roots may be affected by various environmental factors, so it is necessary to consider various limitations.

The Internet's core network, crucial for key services, lacks a clear definition, hindering Internet development and security research. This study analyzes important Autonomous Systems (ASes) and proposes a rule-filtering, top-down method to infer the Internet's core network. It identifies two core memberships: Tier-1 ASes and Regional Tier-1 ASes. Despite a gap, Regional Tier-1 ASes show potential to join the core. Our proposed core structure, unlike traditional methods that randomly select TOP-K nodes, offers improved rationality and interpretability. Historical data analysis reveals the Internet's core structure as a tightly interconnected network of large provider ASes. Despite some changes, this structure shows remarkable stability and growing influence, potentially encouraging other ASes to establish direct connections with the core ASes, accelerating the trend towards a flattened Internet structure. Furthermore, the core structure may be evolving from a majority to a more minority-centric structure.

Carotenoids are common and diverse organic compounds with various functional roles in ani-mals. Except for certain aphids, mites, and gall midges, all animals acquire necessary carotenoids only through their diet. The House fly (Musca domestica) is a cosmopolitan pest insect that populates diverse habitats. Its larvae feed on organic substrates that may vary in carotenoid composition according to their specific content. We hypothesized that the carotenoid composition in the adult House fly’s body would reflect its composition in the larval feed. We reared house fly larvae on substrates that differed in carotenoid composition and characterized the carotenoid composition of the emerging adults. Our results indicate that the carotenoid composition of adult House flies is related to the carotenoid composition in its natal substrate, but does not directly reflect it. We suggest that these findings may be developed to identify sources of House fly in-festations. We also recommend that care should be taken when considering the rearing substrates of House fly larvae used for animal feed.

Water quality assessment stands as a fundamental step in water resource management. In addition to substances and organisms present in the water, land use and land cover are two factors affecting also water quality. This study analyzed the correlation and influence between water quality and land use and land cover in the Miranda River Basin (MRB) and the natural wetlands in the Pantanal Biome. Using a watershed-wide approach, results suggested that water quality management policies can be considered in terms of sub-basins (smaller planning units). The Water Quality Index (WQI) was considered GOOD or EXCELLENT throughout the MRB. It was observed that the natural wetlands have the capacity to contribute to improve WQI, with reductions in thermotolerant coliforms and turbidity; however, high values were found for thermotolerant coliforms, a temporal increasing trend of biochemical oxygen demand (BOD), and a reduction in dissolved oxygen and total phosphorus. Conversely, it was found in these flooded areas a trend of decrease in dissolved oxygen and an increase in BOD concentrations. Natural wetlands play important hydrological and ecological roles in water quality, storing, removing, and cycling nutrients. They are highly relevant areas for defining watershed management and conservation strategies, environmental protection, and providing ecosystem services.

Chronic exposure to the nephrotoxic metal pollutant, cadmium (Cd), has been associated with hypertension, but the mechanism by which it raises blood pressure is not understood. We hypothesize that exposure to Cd reduces the glomerular filtration rate (GFR), which in turn, causes a rise in blood pressure. Data were collected from 447 Thai subjects with a mean age of 51.1 years, of which 48.8% had hypertension, 15.4% had diabetes and 6.9% had an estimated GFR (eGFR) below 60 mL/min/1.73 m2 (low eGFR). The mean blood and urinary Cd concentrations were 2.75 and 4.23 µg/L, respectively. The prevalence odds ratio (POR) for hypertension rose twofold in those with blood Cd levels of 0.61-1.69 µg/L or urinary Cd excretion levels ≥ 0.98 µg/g creatinine. In the hypertensive group, the eGFR was inversely associated with age (β =−0.517), the Cd excretion rate (β = −0.177), and diabetes (β = −0.175). Mean eGFR in the normotensive group was 7.5 mL/min/1.73 m2 higher than the hypertensive with a similar Cd body burden. Mean systolic blood pressure (SBP) in those with low or medium eGFR plus heavy Cd body burden was 9.5 mmHg higher than those with the same Cd body burden and a normal eGFR. By mediation analysis, a 22.7% increase in SBP and a 5% increase in diastolic blood pressure (DBP) were attributable to the effect of Cd on GFR. Thus, a rise of blood pressure appears to be a consequence of GFR loss due to Cd-induced kidney damage. This finding is consistent with a well-known role of the kidney in long-term blood pressure regulation.

The increase in population and the challenges caused by it are always among the concerns of decision-makers and policymakers in large countries. One of the most serious concerns is in the field of energy consumption. Optimizing energy use is one of the most effective ways to manage limited resources and energy. Energy consumption in residential houses constitutes a significant percentage of the total energy consumption worldwide; therefore, current research focusing on mathematical models aims to provide a predictive multi-objective linear mathematical model for residential house consumption. For this purpose, the consumption of water, electricity, and gas for 80 residential houses, including 10 household appliances and equipment on a weekly basis, has been considered. The results showed that the mixed-integer multi-objective predictor model is able to optimize household consumption plans compared to the actual state of household energy consumption. Since the goals of household satisfaction and energy consumption costs in the model conflict with each other, the influence coefficient was calculated to demonstrate the simultaneous achievement of these goals. The optimal value achievable with the default model for the model's purposes is 69%.

The Internet of Medical Things (IoMT) represents a specialized domain within the Internet of Things, focusing on medical devices that require regulatory approval to ensure patient safety. Trusted composition of IoMT systems aims to ensure high assurance of the entire composed system, despite potential variability in the assurance levels of individual components. Achieving this trustworthiness in IoMT systems, especially when using less-assured, commercial, off-the-shelf networks like Ethernet and WiFi, presents a significant challenge. To address this challenge, this paper advocates a systematic approach that leverages the Architecture Analysis & Design Language (AADL) along with Behavior Language for Embedded Systems with Software (BLESS) specification and behavior. This approach aims to provide high assurance on critical components through formal verification, while using less-assured components in a manner that maintains overall system determinism and reliability. A clinical case study involving an automated opioid infusion monitoring IoMT system is presented to illustrate the application of the proposed approach. Through this case study, the effectiveness of the systemic approach in achieving trusted composition of heterogeneous medical devices over less-assured networks is demonstrated.

Dengue infection is caused by the Dengue virus (DENV) and is transmitted to humans by infected female Aedes aegypti and Aedes albopictus mosquitoes. There are nearly 100 million new dengue cases yearly in more than 120 countries with a five-fold increase in incidence over the past four decades. While many patients experience a mild illness, a subset suffer from severe disease which can be fatal. Dysregulated immune responses are central to the pathogenesis of dengue, and haematologic manifestations are a prominent feature of severe disease. While thrombocytopaenia and coagulopathy are major causes of bleeding in severe dengue, leucocyte abnormities are emerging as important markers of prognosis. In this review, we provide our perspective on the clinical aspects and pathophysiology of haematologic manifestations in dengue. We also discuss the key gaps in our current practice and areas to be addressed by future research.

Understanding and improving seismic resilience in regions prone to earthquakes is crucial for mitigating the effects of natural disasters. This study zeroes in on Montenegro, a region frequently affected by seismic activity, with the goals of critically evaluating current resilience levels, pinpointing key preparedness gaps, and assessing the efficacy of existing response strategies. Employing qualitative methods, the research involved semi-structured interviews with residents from Montenegro's most vulnerable areas, including Nikšić, Podgorica, Bar, Kotor, Cetinje, Budva, Herceg Novi, and Berane. These participants, selected for their firsthand experiences with significant earthquake impacts, contributed to a deeper understanding through discussions that aligned with a broad conceptual framework, exploring everything from the nuances of citi-zen resilience to local government responses and personal preparedness. The study aimed to gather in-depth views on community resilience during earthquakes, evaluate citizens' knowledge and preparedness for such disasters, and examine local governance strategies for enhancing seismic resilience. It revealed varying resilience levels across communities, with some displaying well-structured strategies while others showed notable deficiencies. The findings underscore the urgent need for community-specific preparedness programs and improvements in both structural and educational frameworks to enhance resilience. This research highlights the necessity of a comprehensive approach that includes detailed risk assessments, tailored preparedness training, and stronger public awareness efforts. Additionally, it emphasizes strengthening local governments' capabilities to enact and sustain effective response measures to ensure ongoing community resilience against future seismic challenges.

The decarbonization of the electricity grid as one among the actions to reduce fossil fuel emissions, and thus their impact on global warming in the future, will be achieved mainly via the integration and widespread diffusion of renewable power sources. This is going to be supported also by the shift from the paradigm production-transmission-distribution, where electricity production oversees large-size power plants, to renewable-based distributed/diffused production, where electricity is generated very close or even by the same (group of) user(s) (or prosumers in the latter case). The number of mid-/small-size installations based on renewable energy technologies will therefore increase substantially, and the related renewable generation will be dominant against that from large-size power plants. Unfortunately, this will reduce the reliability of the grid very likely, unless appropriate countermeasures are taken/implemented, hopefully at the same time the paradigm shift is being achieved. To this aim, it is important to identify the anomalies and main fault causes that might determine in renewable-based power systems. This paper surveys the current state-of-the-art on anomalies and faults affecting wind-PV-storage hybrid power systems, i.e., the main renewable technology ensemble that will establish the future grid, and highlights possible research directions that may help to fill the literature gaps.

This study describes a novel method for grading pathological sections of gliomas. Our own integrated hyperspectral imaging system was employed to characterize 270 bands of cancerous tissue samples from microarray slides of gliomas. These samples were then classified according to the guidelines developed by the World Health Organization, which define the subtypes and grades of diffuse gliomas. We explored a hyperspectral feature extraction model called SMLME-Resnet using microscopic hyperspectral images of brain gliomas of different malignancy grades. The model combines the channel attention mechanism and multi-scale image features to automatically learn the pathological organization of gliomas and obtain hierarchical feature representations, effectively removing the interference of redundant information. It also completes multi-modal, multi-scale spatial and spectral feature extraction to improve the automatic classification of glioma subtypes. The proposed classification method demonstrated high average classification accuracy (>97.3\%) and Kappa coefficient (0.954), indicating its effectiveness in improving the automatic classification of hyperspectral gliomas. The method is readily applicable in a wide range of clinical settings, offering valuable assistance in alleviating the workload of clinical pathologists. Furthermore, the study contributes to the development of more personalized and refined treatment plans, as well as subsequent follow-up and adjustment of treatment, by providing physicians with insights into the underlying pathological organization of gliomas.

Reviewed are recent efforts leading to chemo-enzymatic syntheses of strongly fluorescent ribosides of nucleobase analogs, potentially applicable in analytical biochemistry and cell biology. Described are syntheses and properties of fluorescent purine, 8-azapurine and etheno-purine ribosides, obtained using various types of the purine nucleoside phosphorylase (PNP) as catalysts of ribosylation, and -ribose-1-phosphate (r1P) as a second substrate. In several instances, the ribosylation sites were different than the canonical purine N9. Some of the obtained ribosides show fluorescence yields close to 100%. Their main applications are assays of PNP, nucleoside hydrolases, and other enzyme activities both in vitro and, possibly, within the living cells, using fluorescence microscopy.

For most people, using social media to research products has become common. Despite previous research, there is a gap in understanding reviewers' product-related comments and how they lead to purchase intentions. In terms of contributions, this study analyses people's dependence on social media for product information in purchase intention while considering the moderating impact of risk and trust on the link between purchase intention and social media. The data were collected quantitatively using surveys. The sample consisted of 384 students. The study hypotheses were tested using the PROCESS macro after exploratory factor analysis and correlation analysis were conducted. Among those surveyed, it was confirmed that most people sought product-related comments on social media when seeking information about a product they might be interested in purchasing. It was also observed that the risk factor reduced the impact of other variables in the model presented in this study. In conclusion, this investigation is more reliable, and its outcomes benefit scholars, supervisors, merchants, and webmasters, for instance, in establishing a study for future research efforts and providing practical guidance that could boost promotional efforts and marketing activities, especially in this era of artificial intelligence.

Raman spectroscopy (RS) turns out to be a promising tool for cancer di- agnosis. In particular, in the last years several studies have demonstrated how the diagnostic performances of Raman Spectroscopy can be significantly improved by employing Machine Learning (ML) algorithms for the interpre- tation of Raman-based data. In line with these findings, in this paper, we demonstrated how RS coupled with ML allowed to accurately distinguish the three grades of Chondrosarcoma and to distinguish Chondrosarcoma and a benign counterpart called Enchondroma. We obtained such results by ana- lyzing a dataset composed of a relatively small number of Raman spectra, collected in a previous study. Such spectra were acquired from micromet- ric tissue sections with a Confocal Raman Microscope. In particular, we tested the classification performances of a Support Vector Machine and a Random Forest Classifier, as representative of Machine Learning, and two versions of the Multi-Layer Perceptron, as representative of Deep Learning (DL). These models showed excellent classification performances, especially those belonging to DL, with accuracy reaching 99.7%. This outcome makes the aforementioned models a promising route for future improvements of di- agnostic devices focused on detecting bone cancerous tissues. In addition, we highlighted how the ML models studied resulted in slightly worse classifi- cation performances in comparison to DL. Alongside the diagnostic purpose, the aforementioned approach allowed to identify characteristic molecules, i. e. amino acids, nucleic acids and bioapatites, relevant for the obtainment of the final diagnostic response, through the analysis of the so-called Per- mutation Feature Importance. Permutation Feature Importance could hence represent a promising parameter for the understanding of the biochemical processes on the basis of the tumor progression. In turn, the spectral bands highlighted by Permutation Feature Importance could represent precious in- dicators in the attempt to restrict the spectral acquisition to specific Raman bands. This last objective could help to reduce the amount of experimental data needed to obtain an accurate final grading outcome, with consequent reduction of the computational cost.

Energy metabolism regulates the proliferation of stem cells by regulating energy production and the production of substrates through biosynthetic pathways. It is an important target for cell regulation and stem cell applications, and is crucial for determining the pluripotency and cell fate of stem cells. In this context, this article focuses on reviewing the latest research progress on the association between glucose metabolism, amino acid metabolism, fatty acid metabolism, and mitophagy with stem cell function, elucidating how key energy metabolism pathways affect stem cell function by regulating signal transduction and epigenetic modifications. In this review, we discuss the key factors affecting energy metabolism and their association with stem cell function. The integration of energy metabolism and stem cell fate regulation will open up a new path for future regenerative medicine practices.

We hypothesis that large earthquakes generate Horndeski-like Gravitational Wave (GW). We find that such a Horndeski-like GW propagates with the speed of sound. The sound waves generated by an earthquake make a local and temporal change to the Earth’s diagravitational medium; therefore, they modify the GW speed in a standard, Alternative-Theory-of-Gravity (ATG) sense. The quantum of the Horndeski-like GW is a massless scalar quasiparticle and cannot exist outside of the propagation region of the P-field. The Horndeski-like GW may be detectable by future GW detectors with a sensitivity of 10−15 Hz^−1/2 in the region of 0.1–1 Hz.

Bosentan, an endothelin-receptor antagonist (ERA), has potential anti-atherosclerotic properties. We investigated the complementary effects of bosentan and atorvastatin on the progression and composition of the atherosclerotic lesions in diabetic mice. Forty-eight male apoE-/- mice were fed high-fat diet (HFD) for 14 weeks. At week 8, diabetes was induced with streptozotocin and mice were randomized into 4 groups: 1) Control/COG: no intervention. 2) ΒΟG: bosentan 100 mg/kg/day per os. 3) ATG: atorvastatin 20mg/kg/day per os). 4) BO+ATG: Combined administration of bosentan and atorvastatin. The intra-plaque contents of collagen, elastin, monocyte chemoattractant protein-1 (MCP-1), tumor necrosis factor-a (TNF-a), matrix-metalloproteinases (MMP-2,-3,-9), and TIMP-1 concentrations were determined. The percentage of lumen stenosis significantly decreased across all treated groups: BOG: 19.5±2.2%, ATG: 12.8±4.8%, BO+ATG: 9.1±2.7% compared to controls (24.6±4.8%, p&lt;0.001). Both atorvastatin and bosentan significantly increased collagen content and fibrous cap thickness versus COG (p&lt;0.01). All intervention groups reduced the relative intra-plaque concentrations of MCP-1, MMP-3,-9, and increased TIMP-1 compared to COG (p&lt;0.001). Importantly, bosentan showed modest but additive to atorvastatin effects on the latter parameters compared COG (p&lt;0.05). Bosentan treatment in diabetic, atherosclerotic apoE-/- mice delayed the atherosclerosis progression and enhanced plaques’ stability, showing modest but complementary effects with atorvastatin, which are promising in atherosclerotic cardiovascular diseases.

Lipoprotein (a) is a highly atherogenic, lipid particle whose concentration is genetically determined, and represents an independent risk factor for cardiovascular disease. On the other hand, metabolic syndrome represents a cluster of interconnected cardiovascular risk factors (obesity, insulin resistance, arterial hypertension, dyslipidemia) that are a direct consequence of an unhealthy lifestyle. Some evidence suggests a connection between each component of metabolic syndrome and high levels of lipoprotein (a). Still, the exact mechanisms are not fully understood and may involve complex interactions between various metabolic pathways. High levels of lp(a) are associated with insulin resistance, a key feature of type 2 diabetes mellitus and obesity. Although there is no significant association between lp(a) and other lipid levels (LDL-C, HDL-C, triglycerides), studies have shown a strong synergistic effect of genetically elevated LDL-C and Lp (a) on the development of cardiovascular events. Also, there is supporting evidence that hypertensive patients with high levels of lp(a) have higher cardiovascular risk, there is no direct association between hypertension and lp (a). Treatment of metabolic syndrome is often long-term and challenging but very important to reduce the overall cardiovascular risk, especially in individuals with higher levels of Lp (a), in whom the risk of developing cardiovascular disease is much higher.

Nutrition therapy is the best solution to human chronic diseases, especially beer and barley which play an important role in human health and civilization. We demonstrated the actional mechanism of functional ingredients in beer and barley to combat chronic diseases, based on PubMed, google, CNKI, and ISI Web of Science databases from 1997 to 2024. Beer is rich in functional ingredients that is a complex of barley malt and hops; the health effect of beer against 26 chronic diseases is highly similar to that of barley, due to molecular mechanism of polyphenols (phenolic acids, flavonoids), melatonin, minerals, bitter acids, vitamins, and peptides. The ancient German Beer Purity Law provides much scientific basis today, especially indirectly supporting the human one cell disease theory. Low purine beer can be produced by enzymatic and biological degradation and adsorption of purines as well as dandelion addition. Functional beer with low purine and high active ingredients made from Beer Purity and barley malt as well as functional foods addition will be the key and important development direction, such as ginger beer and ginseng beer, especially coix-lily beer at the ancestors ca. 9000 years ago. This review paper not only reveals the actional mechanism of beer overcoming human chronic diseases, but also provides scientific basis for the development of functional beer for the prevention and treatment of human chronic diseases.

The yak (Poephagus grunniens) has evolved unique adaptations to survive the harsh environment of the Tibetan Plateau, while their gut microorganisms play a crucial role in maintaining the health of the animal. Gut microbes spread through the animal population not only by horizontal transmission but also vertically, which enhances microbial stability and inheritance between generations of the population. Homogenization of gut microbes in different animal species occurs in the same habitat enhancing interspecies coexistence. Using the yak as a model animal, this paper reviews the adaptive strategies under extreme environments and how the gut microbes of the yak circulate throughout the Tibetan Plateau system, which not only affects other plateau animals such as plateau pikas, but can also have a profound impact on the health of people. By examining the relationships between yaks and their gut microbes, this review provides new perspectives in understanding the adaptations of plateau animals and the stability of the ecosystem.

The intelligent elderly care model places new demands on the skills of aging caregivers. The identification and development of forward-thinking, high-potential nursing talent is essential for advancing the intelligent elderly care sector. Multi-benchmarking selection and competitive analysis is used to evaluate and identify nursing personnel in the rehabilitation treatment center of a hospital in Hefei City. Using proxy evaluation and democratic evaluation model, three types of benchmarks such as single item benchmark, individual benchmark and group benchmark were identified and selected, and the professional nursing team was constructed based on the evaluation results. Different from the traditional other-directed evaluation, multi-benchmarking selection and competitive analysis is self-directed evaluation, this method is more conducive to the identification of high-potential and digital nursing talents by intelligent elderly service organizations, and facilitates the formation of professional nursing teams with complementary strengths and cross-fertilization, so as to satisfy the diversified and multi-level needs of the elderly for intelligent elderly services.

In the plot under study, rice is grown under anaerobic conditions by means of flood irrigation that maintains a constant water depth during most of the crop cycle. Thus, water requirements reach a very high volume of about 12,000 m3/ha. At the outlet there is a drainage channel where there are no measuring devices. Its control will allow us to establish practices to reduce the high water consumption. We have designed a long-throated flume that can cover the entire range of flow rates to measure, between 0.02 and 0.05 m3/s in this case. Since the drainage channel has a trapezoidal cross section and is built on land, the throat of the flume will also be trapezoidal to ease the transition between the two sections and reduce head losses. A new procedure has been developed that allows to directly design the dimensions of the narrowed section, side slope and bottom width, by previ-ously choosing the modular limit, the sill height and the length of the throat more in accordance with the characteristics of the channel where the flume is to be installed. The analysis of the obtained results demonstrates the accuracy and feasibility of the presented procedure.

Passion fruit is a valued tropical fruit crop that faces environment-related growth strains. TCP genes are important for both growth modulation and stress prevention in plants. Herein, we systematically analyzed the TCP gene family in passion fruit, recognizing 30 members. Genes exhibiting closer phylogenetic relationships exhibited similar protein and gene structures. Gene members of the TCP family showed developmental stage or tissue-specific expression profiles during the passion fruit life cycle. Transcriptome data also demonstrated that many PeTCPs showed induced expression in response to hormonal treatments and cold, heat, and salt stress. Based on transcriptomics data, eight candidate genes were chosen for preferential gene expression confirmation under cold stress conditions. Additionally, four TCP genes exhibited in silico binding with cold stress-related miRNA319s. This study will aid in the establishment of novel germplasm, as well as the further investigation of the roles of PeTCPs and their cold stress resistance characteristics.

In this study, MBBR, utilizing kaldnes as a media to attach and grow microorganisms, was used to treat organics in a Compact Septage Treatment Plant (CSTP). Seeding and acclimatization processes were done initially to ensure the microorganisms were able to grow and adapt well within their environments. This research was done to determine the time required for those processes, the optimum conditions, and the growth mechanism of microorganisms during the acclimatization process. Both processes were run in a batch mode. Changes in colour and weight of kaldnes were analyzed for the seeding stage; while COD, MLVSS, pH &amp; temperature were observed for the acclimatization stage. Seeding and acclimatization were run for 6 and 16 days respectively. Acclimatization stage was halted when MLVSS, pH, temperature and COD reduction efficiency were stable. Three phases of microorganism growth were clearly observed in the end of the acclimatization stage, i.e., lag, constant increasing and declining rates. This indicated that microorganisms could adapt well with the MBBR system, and were ready to be utilized further to treat septage in the MBBR of the CSTP. Further research is required to investigate the efficacy of the MBBR with the acclimatized microorganisms in the CSTP.

Digital transformation provides new drivers for economic performance growth in enterprises, but can it further improve ESG performance and support sustainable development? Based on the perspective of resources and capabilities, this paper uses the relevant data of 1588 listed companies in strategic emerging industries from 2011 to 2021 to study the differential impact of digital transformation on enterprise ESG performance, and further tests the mediating role of absorptive capacity and the moderating role of regional digital level. The research results indicate that: firstly, digital transformation of enterprises can positively promote the improvement of ESG performance; Secondly, there are significant differences in the impact of digital transformation on the ESG performance of enterprises in terms of property rights and industry characteristics. The ESG performance of state-owned enterprises and high-end equipment manufacturing enterprises is more sensitive to digital transformation; Thirdly, absorptive capacity plays a mediating role between digital transformation and corporate ESG performance; Fourthly, the positive regulation of regional digital level promotes the ESG performance of enterprises through digital transformation. The research conclusion is based on a digital perspective, providing relevant insights for improving the ESG performance of strategic emerging industry enterprises and expanding their ESG development paths.

In this short communication, a concept has been presented to model geographical data to predict future temperature of Tabuk, region. Machine learning has been applied to the weather station data to develop a prediction model. The preliminary results are promising and encouraging and are envisaging to further this research towards the determination of unknown temperature rise in the region. This is important to mention here, that the problem has been formulated as a Regression problem, NOT as a classification problem. Hence, applying Convolutional neural networks is not possible, due to the non-existence of classes or converting the temperature values to classes does not make any sense. Hence, this is defined as a regression problem which achieved encouraging desirable results.

Phylogenomics has enriched our understanding that the Tree of Life can have network-like or reticulate structures among some taxa and genes. Non-vertical modes of evolution—such as hybridization/introgression and horizontal gene transfer—deviate from a strictly bifurcating tree model, causing non-treelike patterns. Here, we present a brief overview of a phylogenomic workflow for inferring organismal histories and compare methods for detecting reticulate evolution. We discuss how the timing of coalescent events can help disentangle introgression from incomplete lineage sorting and how horizontal gene transfer events can help determine the relative timing of speciation events. In doing so, we identify pitfalls of certain methods and discuss how to extend their utility across the Tree of Life. Workflows, methods, and future directions discussed herein underscore the need to embrace reticulate evolutionary patterns for understanding the timing and rates of evolutionary events, providing a clearer understanding of life’s history.

Providing user confidence in Mobile Government Services (MGS) is essential for the success of mobile government. This study aimed to test the moderating role of techno-skepticism in the impact of crisis management on mobile government. Some scholars have stated that government investment in mobile government services for public administration during the financial crisis is a critical issue for crisis management. In the constantly evolving and changing world, the rapid advancement of technology in modern societies has prompted an acceleration in investments in information and communication technologies. However, due to several inadequacies, citizens seem to respond negatively to the use of certain public technological services, leading them to develop a perspective of techno-skepticism. This issue has been cited in numerous scholarly studies as a critical subject for the effective implementation of technological innovations. The effectiveness of digital technology in the procurement of public services is highly dependent on the perceptions and behaviors of users. In this context, this study measured the attitudes of the participants and the connections between techno-skepticism, mobile government use, and crisis management among Northern Cyprus residents over 18 years old. The study employed a quantitative approach. A 5-point Likert scale was used to collect data by modifying the survey questions to fit the scope of the study. The study participants were selected using the random sampling method to acquire data from a total of 402 citizens. The study findings revealed that techno-skepticism mediates the impact of crisis management on mobile government. As a result, techno-skepticism is a critical and decisive factor in citizens’ mobile government use, affecting its utilization frequency. Techno-skepticism was also found to play a vital role in mobile government use. The current study represents a pioneering effort in testing the moderating role of techno-skepticism in the impact of crisis management on mobile government. It also provides various contributions to theory and practice, particularly in the fields of mobile government and the use of digital technologies.

Anxiety is a multifactorial pathology associated with oxidative stress and changes in different neurotransmitters in the central nervous system (CNS). Sarcomphalus joazeiro (Rhamnaceae) has a predicted effect on the CNS, being considered an alternative for pre-clinical investigations of anxiolytic drugs. The objective of this study is to evaluate the chemical composition, analyze the antioxidant capacity and the anxiolytic effect of the ethanolic extract of S. joazeiro leaves (EEFSJ) in zebrafish. The chemical profile was analyzed by liquid chromatography coupled to mass spectrometry (UPLC-PDA-ESI-QDA). Antioxidant action by DPPH• elimination and ABTS•⁺ capture assays. The 96 h acute toxicity and open field and light and dark tests, for sedative and anxiolytic evaluation, respectively, were applied in vivo, using zebrafish. It was possible to identify 11 compounds from the flavonoid and saponin class. EEFSJ exhibited a mean inhibitory concentration (IC50) of 185.2 ± 2.2 µg/mL and 74.17 ± 1.5 µg/mL against the DPPH• and ABTS•⁺ radicals, respectively. In vivo, EEFSJ demonstrated reduced locomotor activity and an anxiolytic effect similar to diazepam via GABAergic systems, without presenting toxicity within 96 h. These results suggest the safety of using EEFSJ for the development of clinical trials for the production of new anxiolytic drugs.

Permeability is a fundamental property of porous media, especially when studying resin transfer within a dense fibrous medium to manufacture composite materials. When the measurement of permeability tensor of composite reinforcements is difficult and time consuming, especially in thick, heterogeneous fibrous structures, a numerical approach based on the calculation of the tensor components on a 3D image of the material can be very advantageous. A new finite element based method proposed in this study allows solving very high-dimensional flow problems while limiting the biases associated with boundary conditions and the small size of the numerical samples addressed. The method is validated against academic test cases and against the results of a recent permeability benchmark exercise. The results emphasize that for heterogeneous and anisotropic microstructures, it is important to perform calculations on large samples using boundary conditions that do not suppress the transverse flows that occur when flow is forced out of the principal directions. Since these are not necessarily known in complex media, the permeability determination method must not introduce bias by generating non-physical flows.

The human voice has the potential to serve as a valuable biomarker for the early detection, diagnosis, and monitoring of pediatric conditions. This scoping review synthesizes the current knowledge on the application of Artificial Intelligence (AI) in analyzing pediatric voice as a biomarker for health. The included studies featured voice recordings from pediatric populations aged 0-17 years, utilized feature extraction methods, and analyzed pathological biomarkers using AI models. Data from 62 studies were extracted, encompassing study and participant characteristics, recording sources, feature extraction methods, and AI models. The review showed a global representation of pediatric voice studies, with a focus on developmental, respiratory, speech, and language conditions. The most frequently studied conditions were Autism Spectrum Disorder, intellectual disabilities, asphyxia, and asthma. Mel-Frequency Cepstral Coefficients were the most utilized feature extraction method, while Support Vector Machines were the predominant AI model. The analysis of pediatric voice using AI demonstrates promise as a non-invasive, cost-effective biomarker for a broad spectrum of pediatric conditions. However, further research and development are crucial to enhance the accuracy and applicability of these tools in clinical settings.

A one-dimensional model for fluid and solute transport in poroelastic materials (PEM) is studied. Although the model was recently derived and some exact solutions, in particular steady-state solutions and their applications, were studied, special cases occurring when some parameters vanish were not analysed earlier. Since the governing equations are nonintegrable in nonstationary case, the Lie symmetry method and modern tools for solving ODE systems are applied in order to construct time-dependent exact solutions. Depending on parameters arising in the governing equations, several special cases with new Lie symmetries are identified. Some of them have a highly nontrivial structure that cannot be predicted from a physical point of view or using Lie symmetries of other real-world models. Applying the symmetries obtained, multiparameter families of exact solutions are constructed, including those in terms of elementary and special functions (hypergeometric, Whittaker, Bessel and modified Bessel functions). A possible application of the solutions obtained is demonstrated and it is shown that some exact solutions can describe (at least qualitatively) the solute transport in PEM. The obtained exact solutions can also be used as test problems for estimating the accuracy of approximate analytical and numerical methods for solving relevant boundary value problems.

The integration of modern technologies like intramedullary fixators and advanced biometallic alloys has revolutionized traumatology and orthopedics. While these innovations have improved treatment, the exploration of new materials for implants persists. Tantalum and niobium, both non-toxic with similar properties, are preferred for titanium-based biomedical alloys due to their exceptional biocompatibility and corrosion resistance. Acting as stabilizers in titanium alloys, they form passive oxide layers resisting corrosion and remain compatible with biological systems. The novel Ti21Nb6Ta (TNT) alloy promises enhanced osteosynthesis outcomes. Our in vivo research on experimental animals evaluated the biocompatibility and osteoinduction of TNT compared to Ti-6Al-4V (BT-6) alloy (control group). The study comprised three experiments across different animal species, assessing acute toxicity, irritant effects, and long-term biocompatibility and osteoinduction through simulated osteosynthesis. Results indicated that aqueous extracts from both alloys were non-toxic and non-irritating. Furthermore, both demonstrated high biocompatibility and active osteoinduction potential after three months of implantation.

Wheat, a component of the staple diet globally, is a common food allergen in children. The symptoms of wheat allergy (WA) range from skin rash to shortness of breath, significantly impairing quality of life. Following initial clinical suspicion, individuals may undergo wheat allergen-specific skin prick test (SPT), blood test for serum immunoglobulin E (sIgE) levels or oral food challenge. Conventional management of WA lies in wheat avoidance, yet accidental consumption may be inevitable owing to the ubiquity of wheat in various food products. This article aims to provide an overview of the immunologic pathway of WA, followed by its novel diagnostic methods, namely alcohol-soluble SPT extracts, component-resolved diagnosis and basophil activation test (BAT). The mechanisms underlying wheat allergen-specific oral immunotherapy (OIT) as well as a summary of the efficacy, tolerability and safety of related clinical trials will then be discussed.

Objectives. To show the superiority of eccentric versus concentric strengthening in terms of improving quadriceps strength in knee osteoarthritis (OA). A randomized controlled study was conducted to perform 12 sessions of either eccentric or concentric isokinetic muscle strengthening over 6 weeks Methods. We recruited males and females, aged between 40 and 70 years, with predominantly unilateral femorotibial OA. Exclusion criteria were having a prosthesis, inflammatory arthritis or flare-up of OA, symptomatic patellofemoral OA, cardio-vascular or pulmonary disease that could be a contraindication to the study treatment, and any pathology that could cause muscle weakness. The primary endpoint was the between-group difference in change in maximum concentric isokinetic knee extension peak torque (PT) at 60°/s on the OA side at 6 weeks. Secondary endpoints were between-group difference in change in concentric hamstring PT at 60°/s; eccentric quadriceps and hamstring PT at 30°/s; 10 m and 200 m walking speeds; pain and functional status (WOMAC score) at 6 weeks and 6 months. Results. The sample consisted of 11 females and 27 males, with a mean age of 57.7 ±7.52 years and a body mass index (BMI) of 25.95 ±3.93 kg/m². Quadriceps strength increased more at 6 weeks in the concentric than the eccentric group with no statistical difference. There was a rate of 25% major adverse events in the eccentric group. Conclusion. Eccentric training resulted in a smaller improvement in quadriceps strength than concentric training and was associated with a high risk of muscle injury, particularly to the hamstring muscles.

Food waste is a common issue arising from grinding of food by experimental animals, leading to excessive food scraps falling into cages. In the wild, animals grind food by gnawing vegetation and seeds, potentially damaging the ecological environment. However, limited ecology studies have focused on food grinding behavior since the last century, with even fewer on rodent food grinding, particularly recently. Although food grinding function is partially understood, biological purposes remain under-investigated and driving factors unclear. This review aims to explain potential causes of animal food grinding, identify influencing factors, and discuss contexts and limitations. Specifically, we emphasize recent progress on gut microbiota significance for food grinding. Moreover, we show abnormal food grinding is determined by degree of excess normal behavior, emphasizing food grinding is not meaningless. Findings from this review promote comprehensive research on the myriad factors, multifaceted roles, and intricate evolution underlying food grinding behavior, benefiting laboratory animal husbandry and ecological environment protection, and identifying potential physiological benefits yet undiscovered.

In this paper, single and repetitive frequency UIS characteristics of 1200 V asymmetric (AT)and double trench silicon carbide (DT-SiC) metal–oxide-semiconductor field-effect transistors (MOSFETs) under different working conditions are investigated by experiment and simulation. For asymmetric trench SiC MOSFETs, the failure mode is all thermal runaway under working conditions. However, the failure mode of double trench SiC MOSFETs mostly is gate oxide rupture, which indicates an instable avalanche robustness under UIS stress. The variations of measured parameters are recorded to evaluate typical electrical features of device failure. Furthermore, TCAD simulation is used to reveal the electro-thermal stress inside the device during avalanche. Additionally, failed devices are decapsulated to verify the location of failure point from the perspective of the semiconductor die. Finally, a new type of stepped-oxide vertical power DT MOSFET with P-type shielding and current spread layers is proposed for improvement of gate dielectric reliability.

This study explores the enhancement of aqueous zinc-ion batteries (AZIBs) using ammonium-enhanced vanadium oxide cathodes. Density Functional Theory (DFT) calculations reveal that NH₄⁺ incorporation into V₆O₁₆ lattices significantly facilitates Zn²⁺ ion diffusion by reducing electrostatic interactions, acting as a structural lubricant. Subsequent experimental validation using (NH₄)₂V₆O₁₆ cathodes synthesized via a hydrothermal method corroborates the DFT findings, demonstrating remarkable electrochemical stability with a capacity retention of 90% after 2000 cycles at 5 A g⁻¹. These results underscore the potential of NH₄⁺ in improving the performance and longevity of AZIBs, providing a pathway for sustainable energy storage solutions.

Fine dust causes various disorders, including cardiovascular, neurological, renal, reproductive, motor, systemic, respiratory, and cancerous diseases. Therefore, it is necessary to study functional materials to prevent these problems. In this study we used various methods, including quantitative PCR, flow cytometry, ELISA, and Alizarin O staining, to study the beneficial effects of erucic acid against fine dust. Erucic acid and erucic acid-induced exosomes (EIE) strongly suppress the attenuation of osteocytic differentiation and inflammation induced by fine dust. Erucic acid effectively suppresses inflammation in fibroblasts exposed to fine dust. Notably, despite exposure to fine dust, EIE promoted osteocytic differentiation in adipose-derived stem cells (ASC) and osteogenesis in macrophages, in addition to phagocytosis. Dramatic upregulation of RunX2 and BMP7 by EIE indicates that it is a strong activator of osteocytic differentiation in ASC and protects them from the effects of fine dust. Moreover, EIE induces immune activity and acts as an osteogenic trigger for macrophages. Therefore, this study suggests the potential use of erucic acid and erucic acid-induced exosomes (EIE) as biomaterials to prevent environment-borne diseases.

To assess the usefulness of an attachable video laryngoscope (AVL) by attaching a camera and monitor to a conventional Macintosh laryngoscope (CML). Normal and tongue edema airway scenarios were simulated using a manikin. Twenty physicians performed tracheal intubations using CML, AVL, Pentax AWS® (AWS), and McGrath MAC® (MAC) in each scenario. Ten physicians with more than 10 cases of clinical experience with tracheal intubation using CML were included in the skilled group. Ten physicians with less than 10 cases of clinical experience with tracheal intubation using CML were included in the unskilled groups. The time required to intubate and the success rate were recorded. The degree of difficulty of use and glottic view assessment scored by participants. All 20 participants successfully completed the study. There was no difference in the success rate and time required for tracheal intubation in the normal airway scenarios. For the skilled group, in the tongue edema airway scenario, the AWS had the highest success rate (100%) followed by AVL (60%), MAC (60%), and CML (20%) (p = 0.001). The time required to intubate with the AWS was significantly shorter than with AVL (10.2 vs 22.3 s; p=0.002) or MAC (10.2 vs 23.7 s; p=0.001). There was no significant (p &gt; 0.05) difference between AVL and MAC. The degree of Difficulty of Use for AVL was significantly lower than that for CML (7.8 vs 2.8; p &lt; 0.001). There was no significant (p &gt; 0.05) difference between AVL and other video laryngoscopes. AVL had a higher rate of successful tracheal intubation than CML in the tongue edema scenario. AVL showed a similar success rate and time of tracheal intubation to the MAC. Therefore, AVL may be a possible alternative video laryngoscope device.

Blood cancers, including leukemia, lymphoma, and myeloma, pose significant diagnostic challenges due to their diverse and complex nature. Detecting these cancers early and accurately is crucial for timely intervention and improved patient outcomes. This review explores current and emerging detection methods for human blood cancers, focusing on their principles, advantages, limitations, and potential clinical applications.

Unmanned aerial vehicles (UAVs), commonly known as drones, present a cost-effective solution for the swift collection of data from vast and remote areas that are otherwise difficult to access. The Mediterranean Basin, known for being a hot spot for plant biodiversity, hosts several habitats and taxa of significant naturalistic value. However, many of these areas are often inaccessible to botanists, making exploration and research challenging. The aim of this paper is to involve the utilization of drone surveys and open-source software for botanical research. Our primary goal is to show the effectiveness of these tools in the field and demonstrate their practical application in Natura 2000 sites. The protected area chosen for this research is Rocca di Novara, situated in northeastern Sicily. Thanks to our drone investigations, we were able to capture images of the mountain’s side that is inaccessible to humans. This allowed us to observe the habitat of some species in detail. One of the most fascinating discoveries was the reappearance of Saxifraga callosa subsp. australis, which had not been confirmed in this area for over 140 years. Using drones for botanical research can boost field research, making monitoring easier and more cost-effective over time, especially in Natura 2000 sites.

In this pilot study, 84 subjects with a history of poor oral hygiene were enrolled in an interventional, randomized, prospective, open-label controlled trial. The aim was to provide preliminary clinical data on the products, the recruitment monthly rate, and patient satisfaction to estimate resources for the main study, as well as descriptive data on oral microbiota rebalancing. The population was divided into five groups: 20 participants received delicate mint toothpaste, 12 mint toothpaste, 20 mint mouthwash, and 20 delicate mint toothpaste and mint mouthwash using a specifically custom-designed toothbrush. The 12 subjects in the control group continued to use their oral care products without changing their normal routine. The study duration was 28 days.All subjects tolerated the products well, and there were no adverse events. Recruitment capability and procedures allowed a realistic estimation for the future main trial. The products did not cause any changes in tooth color. The participants who completed the treatment consisting of delicate mint toothpaste, mint mouthwash, and the specifically custom-designed toothbrush showed the gingival sensitivity best results (p≤0.000). The products induced a statistically significant decrease in plaque in all treated groups (p≤0.000) and an improvement of gingival sensitivity (delicate mint toothpaste, p≤0.005; mint toothpaste, p≤0.015; and mint mouthwash, p≤0.015). All the products were effective in stabilizing the oral microbiota.The tested products showed an optimal safety profile. They also stabilized the biodiversity of the oral microbiota, making it less susceptible to microbial fluctuations than the control group.

Design process can be divided into stages of analysis and synthesis. This paper presents the application of the object-oriented technique to the analysis as well as theoretical considerations concerning to design of gear size ranges. This analysis consists in decomposition of the designed artefact (a gear) according to the rule “from general to details view”. The basics of the object-oriented analysis were formulated. Furthermore, design phases and the objects related to theses phases were discussed. The following models have been considered: hierarchical model, entity-relationship model, data-flow model and object model. Analysis is additionally connected with interactions between particular design phases.