The plantar plate (PP) tear of the second metatarsophalangeal joint (MTPJ) is the most common reason for forefoot pain in clinical practice. PP is the main stabilizing structure of the joint and, together with collateral ligaments, is the key to maintaining the stability of MTPJ. Many surgical procedures have been described to repair PP tears. Currently, there is still controversy regarding which is the surgical superior option (direct versus indirect PP repair techniques). Transfer of the flexor digitorum longus tendon to the dorsum of the proximal phalanx is one of the surgical techniques described to treat PP tears associated with MTPJ instability. We present two cases that developed instability of the second MTPJ secondary to chronic PP tear with symptoms resolved after transfer of the flexor digitorum longus (FDL). Currently, the literature review shows that the procedure seems to be the most consistent surgical option in chronic cases of PP tears.

Artificial Intelligence (AI) faces several mathematical challenges, such as optimization, generalization, interpretability of models, and phase transitions. These problems significantly limit the application of AI in critical areas such as medicine, autonomous systems, and finance. This paper examines the main mathematical problems of AI and proposes solutions based on the use of the universality of the Riemann zeta function.

Alzheimer’s disease (AD) is a neurodegenerative disease that is characterized as a progressive decline in cognitive functions that primarily affects older adults. Alzheimer’s is pathophysiologically characterized by the accumulation of amyloid-beta (Aβ) plaques, neuroinflammation, accumulation of tau proteins in neurofibrillary tangles (NFTs), and tissue loss. These three main characteristics are hallmarks of neurodegeneration. Statins are a class of medications that lower the cholesterol levels in the blood, and their anti-inflammatory effects have gained attention for their potential impact on influencing AD progression. This literature review explores the relationship between the use of statins and AD, examining the effect of statins on cholesterol metabolism, neuroinflammation, apolipoprotein E (ApoE), and Aβ production. This literature review was conducted using PubMed and Google Scholar to summarize the association between statins and AD. The neurodegenerative properties of Alzheimer’s disease have been imaged and documented in both rodent models and humans. Experiments using transgenic mice and knock-in mice have shown that specific human genes enhance neurodegeneration, and the overactivation of glial cells in the brain causes hallmark neuroinflammation. These rodents all subsequently suffered from neurodegeneration and AD symptoms. Humans showed promise of possible AD biomarkers in the blood and brain through the presence of excess isoprostanes and oxysterols, respectively, providing hope for future research into early detection/treatment. There has been evidence that statins exhibit neuroprotective pleiotropic effects in rodent models, showcasing reductions in cellular adhesion molecules (the main molecule in inflammation), oxidative stress, and inflammatory peptides. ApoE is a cholesterol transport protein in the brain and is critical to forming an effective synapse. Statin use has effectively altered the ApoE4 allele and reduced the Aβ production in the brain. However, the mechanism for which statins slow the progression of neurodegeneration in AD is still unclear and warrants further research before it can be officially called a treatment.

Biobutanol is becoming more relevant as a promising alternative biofuel, primarily due to its advantageous characteristics. These include a higher energy content and density compared to traditional biofuels, as well as its ability to mix effectively with gasoline, further enhancing its viability as a potential replacement. A viable strategy for attaining carbon neutrality, reducing reliance on fossil fuels, and utilizing sustainable and renewable resources is the use of biomass to produce biobutanol. Lignocellulosic materials have gained widespread recognition as highly suitable feedstocks for the synthesis of butanol, together with various value-added byproducts. The successful generation of biobutanol hinges on three crucial factors: effective feedstock pretreatment, the choice of fermentation techniques, and the subsequent enhancement of the produced butanol. While biobutanol holds promise as an alternative biofuel, it is important to acknowledge certain drawbacks associated with its production and utilization. One significant limitation is the relatively high cost of production compared to other biofuels, additionally, the current reliance on lignocellulosic feedstocks necessitates significant advancements in pretreatment and bioconversion technologies to enhance overall process efficiency. Furthermore, the limited availability of biobutanol-compatible infrastructure, such as distribution and storage systems, poses a barrier to its widespread adoption. Addressing these drawbacks is crucial for maximizing the potential benefits of biobutanol as a sustainable fuel source. This document presents an extensive review encompassing the historical development of biobutanol production and explores emerging trends in the field.

The study provides a comprehensive and detailed analysis of the existing key policies and considerations in Taiwan's Other Effective Area-Based Conservation Measures (OECMs), with the objective of providing useful evidence-based insights for formulating new effective environmental-friendly policies and promoting the existing policies. The study adopts a mixed research methodology that entails the combination of qualitative and quantitative research methodological frameworks. The primary source of the quantitative data for the study is the World Database on Protected Areas (WDPA) which provides variable data on OECMs and a component of databases of the Protected Planet Initiative (PPI) which is the joint product of UNEP and IUCN, managed by UNEP-WCMC and the IUCN working with governments, communities and collaborating partners. The qualitative methodological framework for the research adopted a technical systematic review approach based on the three-step framework for systematic reviews that involved planning, conducting and reporting the review. The review was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The sources that were included in the review included scientific research materials that focused on the policies related to OECMs. Taiwan has a total of 92 individual areas that are designated as national protected areas (PAs) and OECMs and formally recognized by the World Database on Protected Areas (WDPA). Out of the 92 designated areas, only seven are managed by the Construction and Planning Agency while the remaining 85 areas are managed by the Forestry Bureau. In terms of designation, 37 areas are designated as major wildlife habitats, 21 areas are designated as nature reserves, 20 areas are designated as wildlife refuges, eight areas are designated as national parks and six areas are designated as forest reserves. The primary themes that were identified were associated with marine spatial planning, environmental impact assessment (EIA) and marine scientific research and included biodiversity, protected area consideration, geographically defined areas, coastal resources and marine ecosystems. Other Effective Area-Based Conservation Measures (OECMs) have not been widely implemented yet, but most countries, including Taiwan, are increasingly aligning their existing policies with the strategies outlined in the OECMs policies to achieve large area-based conservation targets and reduce biodiversity loss.

This systematic review critically examines the adoption and integration of Human Resource Information Systems (HRIS) and Artificial Intelligence (AI) in small and medium-sized enterprises (SMEs), with a focus on enhancing workforce productivity and strategic decision-making. Using the PRISMA framework, 100 research articles from reputable sources such as Google Scholar, Scopus, and Web of Science were analyzed. The analysis reveals that HRIS adoption can improve employee productivity by 29%, decision-making by 20%, and operational efficiency by 26%, highlighting its transformative impact on SMEs. The review identifies major challenges, including high implementation costs, limited IT resources, and integration difficulties with AI and machine learning technologies. Despite these barriers, integrating AI into HRIS presents significant opportunities for SMEs, fostering innovation in talent management, compliance automation, and data-driven decision-making, thus creating a competitive edge in rapidly evolving markets. Actionable insights for practitioners emphasize the need for cost-effective, scalable HRIS solutions tailored to the unique operational needs of SMEs, while researchers are urged to further explore AI-driven HRIS advancements to address current gaps in workforce engagement and performance management. This review offers a comprehensive roadmap for future HRIS innovations and underscores the strategic importance of digital transformation in human resources for sustained SME competitiveness.

Biliary tract cancers (BTCs) are aggressive in nature, often presenting asymptomatically until they are diagnosed at an advanced stage. Surgical resection or liver transplantation are potential curative options. However, a large proportion of patients present with incurable locally advanced or metastatic disease and most of these patients are only eligible for palliative chemotherapy or best supportive care. More recently, targeted therapies have proven beneficial in a molecularly selected subgroup of patients with cholangiocarcinoma who have progressed on previous lines of systemic treatment. However, only a minority of patients with BTCs whose tumours harbour specific molecular alterations can access these therapies. Antibody drug conjugates (ADCs) are novel anti-cancer therapies designed to minimise challenges of systemic drug distribution and are currently being investigated in multiple types of malignancies, after failure of standard therapeutic options. This review outlines the mechanism of action of ADCs and the current research in this field in various cancer types, including BTCs.

Introduction: The advancement of nursing science and practice necessitates the documentation of information, which is increasingly being recorded in electronic mediums due to the progress of information technology. Various countries around the world have implemented electronic nursing records (ENRs) or are in a process of implementing it. This study aims to ascertain the significance of electronic nursing records and consolidate their primary benefits for nursing. Methods: The study utilized an established scoping review methodology (Arksey and O‘Malley protocol; JBI method; PRISMA 2020). Results: Out of 6970 initial articles extracted from 4 databases, 36 were included in the study. Several essential elements for structuring, introducing, and emphasizing the importance of ENRs have been recognized, including the availability of standardized terminology, enhancement of nursing care quality, advancement of research activity, integration with electronic systems, optimization of healthcare, and conditions for ENR integration. Conclusion: Electronic nursing records are indispensable and beneficial for enhancing care quality, improving patient safety, and affirming the autonomy of the nursing profession.

Ferroptosis is a recently identified iron-dependent programmed cell death with lipid peroxides accumulation and condensation and compaction of the mitochondria. Recent study indicated that ferroptosis played a pivotal role in ischemic cardiac injury with the mechanisms remained largely unknown. This study demonstrated that iron overload occurred in the ischemia/reperfusion (I/R) cardiac tissues, which initiated myocardial ferroptosis. The expression levels of mitochondrial inner membrane protein MPV17 were reduced when ferroptosis occurred in cardiomyocytes treated with high levels of iron or in the ischemic cardiac tissues. Overexpression of MPV17 delivered via adenovirus significantly reduced ferroptosis in both cardiomyocytes subject to high levels of iron and cardiac I/R tissues. Mitochondrial glutathione (mtGSH), crucial for reactive oxygen species (ROS) scavenging and mitochondrial homeostasis maintenance, was depleted during myocardial ferroptosis caused by iron overload. The mechanistic study showed that MPV17 could increase mtGSH levels through maintaining the protein homeostasis of SLC25A10, which was a mitochondrial inner-membrane glutathione transporter. The absence of MPV17 during iron overload resulted in the ubiquitination-dependent degradation of SLC25A10, leading to impaired mitochondrial glutathione import. Moreover, we found that MPV17 was the targeted gene of Nrf2, which played a pivotal role in preventing lipid peroxides accumulation and ferroptosis. The decreased expression levels of Nrf2 led to the inactivation of MPV17 during iron overload-induced myocardial ferroptosis. In summary, this study demonstrated the critical role of MPV17 in protecting cardiomyocytes from ferroptosis and elucidated the Nrf2-MPV17-SLC25A10/mtGSH signaling pathway in the regulation of myocardial ferroptosis.

Objectives: The aim of this study was to evaluate the levels of physical literacy (PA) in primary school children in Santiago, Chile, and to explore the relationship between PA and body mass index (BMI). In addition, gender and age differences were analyzed in relation to PA levels in a context where childhood obesity remains a public health challenge. Methods: 439 students in grades 5-8 were assessed using the Canadian Assessment of Physical Literacy - 2 (CAPL-2) questionnaire. Demographic variables (sex, age, and BMI) were correlated with levels of motivation to engage in physical activity and physical activity knowledge. Chi-square were applied with acceptable significance p<0.050 and good p<0.010. Results: The results revealed a significant correlation between motivation for physical activity and gender, with boys showing higher levels of motivation than girls. In addition, an inverse relationship was observed between BMI and motivation, suggesting that more motivated children tend to have a healthier BMI. Knowledge about physical activity increased with age, but did not have a significant influence on BMI. Conclusions: The findings highlight the need to design gender-specific interventions to promote PA and physical activity adherence, with motivation being a key factor in promoting a healthy lifestyle. Public health policies should address these factors to improve pediatric health in Chile.

The rapid increase in unstructured data across various fields has made multi-document comprehension and summarization a critical task. Traditional approaches often fail to capture relevant context, maintain logical consistency, and extract essential information from lengthy documents. This paper explores the use of Long-context Large Language Models (LLMs) for multi-document summarization, demonstrating their exceptional capacity to grasp extensive connections, provide cohesive summaries, and adapt to various industry domains and integration with enterprise applications/systems. The paper discusses the workflow of multi-document summarization for effectively deploying long-context LLMs, supported by case studies in legal applications, enterprise functions such as HR, finance, and sourcing, as well as in the medical and news domains. These case studies show notable enhancements in both efficiency and accuracy. Technical obstacles, such as dataset diversity, model scalability, and ethical considerations like bias mitigation and factual accuracy, are carefully analyzed. Prospective research avenues are suggested to augment the functionalities and applications of long-context LLMs, establishing them as pivotal tools for transforming information processing across diverse sectors and enterprise applications.

The adoption of social media metrics by small and medium-sized enterprises (SMEs) has become a critical tool for engaging customers and enhancing strategic outcomes. However, many SMEs face challenges in effectively tracking and evaluating social media investments, making it difficult to assess the effectiveness of their strategies. This systematic review identifies and analyses key social media activities and performance metrics that contribute to SME strategic success. Through an extensive review of literature from Google Scholar, Web of Science, and Scopus, we selected 138 studies published between 2014 and 2024. The analysis reveals that engagement metrics (e.g., likes, shares), brand awareness (e.g., mentions), and conversion metrics (e.g., click-through rates) significantly influence organizational performance and long-term success. SMEs leveraging detailed engagement metrics reported a 25% increase in customer retention, while brand awareness metrics led to a 30% improvement in customer acquisition. The review highlights areas requiring further research, including a need for sector-specific metric analysis and a deeper understanding of emerging social media platforms. These results offer practical insights for SMEs to enhance their strategic use of social media and adapt to rapidly changing market dynamics.

Small and Medium-scale Enterprises (SMEs) need a platform that actively enables collaboration with Research institutions and consultants since SMEs lack the financial resources to conduct independent research. Such a platform will require a verifiable manipulation-free system for enabling, executing, and recording collaboration activities and tracking reputations among the organizations and individuals that use the platform. Blockchain provides an opportunity to build such a collaborative platform by enabling the verifiable recording of outcomes from collaborations, aggregating the resulting reputation of the collaborating parties, and offering tokenised incentives for rewarding positive contributions to the platform. Cryptocurrencies from which blockchain-based tokens are highly unstable, thereby, reducing business organisations’ interest in blockchain applications. Hence, there is a need to design a self-sustaining valuable token model that incentivises user behaviours that positively contribute to the platform. This paper explores the application of game theory in analyzing token-based economic interactions between the various groups of users in a blockchain-based collaboration platform to design and simulate a token distribution system that provides a fair reward mechanism for the users while also providing a dynamic pricing model for the utility value provided by the platform tokens. Furthermore, the paper analyzed potential risks on the token model design and propose mitigation strategies.

The management of user data in the cloud is easily poised to become a giant issue for any business, with so much digital information floating around these days that open it up as an easy target when companies aren’t vigilant. In this paper, a novel cloud-based service is proposed that employs various advanced NLP and encryption methods with the use of blockchain. These techniques are combined to provide a solid solution to secure fundamental data such as credit card numbers, passports or any government identity cards etc. Using a hybrid NLP model, integrating Transformer Models and Named Entity Recognition (NER), to automatically catagorzing data as critical vs non-critical. Only the most important data is encrypted by a user’s cryptographic wallet before being divided into multiple chunks and stored on an exclusive cloud cluster; metadata then takes turns managing securely through blockchain to provide traceable means of retaining integrity. Smart contracts provide strict access control measures and change the cryptographic nonce if need be to prevent illegal entrance into a specific zone, thus create security. This all-inclusive strategy maintains well-known high security standards for protecting the confidentiality, availability and integrity of your sensitive data on a global scale—delivering you simple yet scalable secure world-class cloud-based data management. A proposed framework developed to fulfil the security requirements for current cloud services, which is a beneficial contribution in context of data protection and cloud Security.

Adverse medical events not only harm patients and families, but also cause significant negative impact on healthcare providers, with potential to compromise future professional functioning. These “second victims” may need organizational support and rehabilitation to return to functionality. We analyzed the validity of an adapted tool, the Second Victim Experience and Support Tool (SVEST), to a population in Israel, H-SVEST. The H-SVEST was completed by 172 nurse participants working in a variety of patient care settings. The H-SVEST was assessed for content validity, internal consistency, and construct validity with confirmatory factor analysis (CFA). The CFA run on the initial model with 10 factors and 36 items did not meet criteria for goodness of fit. After removing five items based on their low factor loadings and the correlation, The model fit significantly improved with acceptable CFI, TLI, RMSEA, and SRMR; χ2(389) =626.939, p<.001; χ2/df=1.61; TLI=0.901; CFI=0.917; RMSEA [90% CI]=0.060 [0.051, 0.068]; SRMR=0.064. The final version included 31 items and 10 factors with Cronbach α values ranging from 0.66 to 0.94. The H-SVEST demonstrates robust psychometric properties and valuable insights into the second victim experience in the Israeli context. Comparative analysis with other versions highlights potential cultural influences and areas for further investigation. Implementing this tool and developing evidence-based interventions based on its results can significantly improve well-being and resilience of healthcare providers in Israel and other countries with diverse cultural populations. This study was not registered.

Objectives: This study investigated the efficacy and safety of performing phacoemulsification using the eight-chop technique with iris hooks in patients with small pupils. Methods: The iris hooks and control groups each included 65 eyes. Cataract surgeries were performed using the eight-chop technique. The operative time, phaco time, aspiration time, cumulative dissipated energy, and volume of fluid used were measured. Best-corrected visual acuity, corneal endothelial cell density (CECD), and intraocular pressure (IOP) were measured preoperatively and postoperatively. Results: In total, 130 eyes of 107 patients (mean age, 75.9 ± 7.1 years; 58 men, 72 women) with cataracts were evaluated. The mean operative time, phaco time, aspiration time, cumulative dissipated energy, and volume of fluid used were 10.6 min, 20.7 s, 101.1 s, 7.8, and 38.0 mL, respectively, in the iris hooks group and 4.6 min, 16.2 s, 72.1 s, 7.0, and 28.9 mL, respectively, in the control group. The decrease in CECD at 19 weeks postoperatively was 2.1% and 1.2% for the iris hooks and control groups, respectively. In both groups, IOP decreased significantly (all p &lt; .01) at 7 and 19 weeks postoperatively. No intraoperative complications were observed in either group. Conclusions: The eight-chop technique using iris hooks resulted in a small postoperative reduction in CECD and excellent values for intraoperative outcome measures. In addition, those cataract surgeries were very short, efficient, and safe, without complications. The eight-chop technique using iris hooks could provide an ideal solution for patients with small pupils.

Quinoa (Chenopodium quinoa, Amaranthaceae) is a pseudocereal native to the Andes of South America that contains high protein content and adequate nutrient levels. Peru possesses an abundant morphological diversity of quinoas and is among the top producers and exporters worldwide of this precious crop. However, knowledge about the genetic and population components of quinoa from the Peruvian Andes is still limited. We here used 13 microsatellite markers to determine the genetic diversity and population structure of 105 landraces of quinoa cultivated in 11 provinces of Ayacucho, the southern Peruvian Andes. A total of 285 bands were manually scored, generating a 105 x 285 presence/absence data set. Principal coordinate analysis, and similar to a dendrogram using UPGMA clustering algorithm, showed that quinoa from Ayacucho is grouped into three clusters without a clear geographic component. Estimation of the genetic diversity indices was conducted considering the three populations (C1: south 1, C2: south 2, C3: north) determined by STRUCTURE analysis, showing mean expected heterozygosity was 0.08. The highest population divergence (FST) was exhibited for C2 and C3 (0.03), whereas the lowest for C1 and C3 (0.02). Analysis of molecular variance revealed the greatest variation within populations (80.07%) and indicated that variability between populations is 19.93%. Microsatellite markers were effective; however, more studies of the genetic components of quinoa from other Peruvian Andean localities are still needed. We expect this work helps pave the way towards the development of modern breeding programs of quinoa in Peru with accurate strategies of conservation of this nutritious crop.

This work utilizes the particle swarm optimization (PSO) for the optimal sizing of a solar – wind – battery hybrid renewable energy system (HRES) for a rural community in Rivers State, Nigeria (Okorobo-Ile Town). The objective is to minimize the total economic cost (TEC), the total annual system cost (TAC) and the levelized cost of energy (LCOE). A two – step approach is used. The algorithm first determines the optimal number of solar panels and wind turbines. Based on the results obtained in the first step, the optimal number of batteries and inverters is computed. The overall results obtained is then compared with results from the NGSA-II and hybrid GA – PSO optimization algorithm. An energy management system monitors the energy balance and ensures the load management is adequate using the battery state of charge as a control strategy. Results obtained showed that the optimal configuration consist of solar panels (154), wind turbine (3), inverter (136) and batteries (29). This results in a minimized TEC, TAC and LCOE of 476, 731USD, 301, 947USD and 0.011USD/kWh respectively. The optimal configuration when simulated under various climatic scenarios was able to meet the energy needs of the community irrespective of ambient condition.

Neurofibroma is a type of benign tumor that affects the peripheral nerves. It can be classified into three subtypes: localized, diffuse, and plexiform, with localized being the most prevalent. Although uncommon, neurofibromas can appear as diffuse tumors that impact the skin and underlying tissues of the head, neck, and body in young individuals and children. Diffuse neurofibromas are characterized by thickened, indurated, and ill-defined skin lesions that often invade underlying tissues. We present a unique case of a 45-year-old Caucasian woman who developed debilitating headaches caused by a gradually enlarging diffuse neurofibroma on her scalp and a comprehensive review of diffuse neurofibroma and its differential diagnosis. Although diffuse neurofibromas are less common in middle-aged individuals, they should still be considered a possible diagnosis in infiltrative and indurated skin lesions. Identifying its characteristic histopathological findings to diagnose diffuse neurofibroma accurately is crucial since its clinical presentations can vary.

Individualized nursing care allows a systematic assessment and intervention, considers the patient's preferences, values, and context, and contributes to a positive care trajectory. However, its operationalization has proven to be challenging. This research aims to determine which items of nursing care individualization are most integrated into nurses' clinical practice, and those that are less included. A cross-sectional study was conducted on 122 eligible and registered nurses at a Hospital Center, in Ophthalmology (operating room and inpatient ward), Cardiology Service, Internal Medicine, and Medical Emergency Unit, in Portugal. The Indi-vidualized Care Scale nursing version (ICS-Nurse) was used for the assessment, including three sub-dimensions: clinical situation, personal life situation, and decisional control over care-related decisions. Analyses were performed using Cronbach's Alpha and Principal Component Analysis to confirm the relationships between the variables, suggested by the literature and previous studies. In the results, no statistically significant differences were identified between the sociodemographic profile and the sub-dimensions of individualization. Nurses overall have a good perception of the importance of individualized care (4.06 ± 0.46 ICS-A-NURSE), but face difficulties in its implementation during the last shift worked (3.97 ± 0.49 ICS-B-NURSE). The sub-dimensions more integrated into the care environment were clinical situations and decisional control, and the less integrated were the personal lives of patients. This study identifies key aspects of the individualization of nursing care in acute and perioperative settings, as its omission represents a failure to address the multidimensional health needs of patients, families, and caregivers. We suggest the development of training programs that promote a holistic approach, as well as future studies that consider patient outcomes related to the individualization of nursing care.

Objective: Scaphoid fractures, particularly occult and non-displaced fractures, are difficult to detect using traditional X-ray methods due to their subtle appearance and variability in bone density. The study proposes a two-stage CNN approach to detect and classify scaphoid fractures using anterior-posterior (AP) and lateral (LA) X-ray views for more accurate diagnosis. Methods: The study emphasizes the use of multi-view X-ray images (AP and LA views) to improve fracture detection and classification. The multi-view fusion module helps integrate information from both views to enhance detection accuracy, particularly for occult fractures that may not be visible in a single view. The proposed method includes two stages that are stage 1: Detect the scaphoid bone using Faster R-CNN and Feature Pyramid Network (FPN) for region proposal and small object detection. The detection accuracy for scaphoid localization is 100% with Intersection over Union (IoU) scores of 0.8662 for AP views and 0.8478 for LA views. And stage 2: Perform fracture classification using a ResNet backbone and FPN combined with a multi-view fusion module to combine features from both AP and LA views. This stage achieves a classification accuracy of 89.94%, recall of 87.33%, and precision of 90.36%. Results: The proposed model performs well in both scaphoid bone detection and fracture classification. The multi-view fusion approach significantly improves recall and accuracy in detecting fractures compared to single-view approaches. In scaphoid detection, both AP and LA views achieved 100% detection accuracy. In fracture detection, using multi-view fusion, the accuracy for AP views reached 87.16%, and for LA views, it reached 83.83%. Conclusion: The multi-view fusion model effectively improves the detection of scaphoid fractures, particularly in cases of occult and non-displaced fractures. The model provides a reliable, automated approach to assist clinicians in detecting and diagnosing scaphoid fractures more efficiently.

Introduction: The aim of this study is to compare the histopathological findings in the resected tracheal ring of tracheotomized critically ill patients with or without severe SARS-CoV-2 infection. Material and Methods: Prospective case-control study. Data collection period was between May 2020-2022. 80 tracheostomies on patients with long intubation were performed and the resected tracheal ring was examined by standard microscopy. 40 consecutive tracheotomies in COVID-19 patients and 40 in patients without COVID-19 disease were carried out. Results: The mean age was 68.18 years in the COVID group and 56.1 years in the NO COVID group. The male/female ratio was 32/8 versus 29/11 respectively. No relevant histological alterations were found in 82.5% of samples. Chronic subepithelial inflammation was found in 13.8% of cases. Two cases presented vasculitis (2,5%) and one case thrombotic microangiopathy (1,2%), all cases in the COVID group. We found no statistically significant dependence between relevant histologic findings versus no alterations (X2=0.779) no significant indices for measuring association (Rho= 0.1316) and no significant risk indices (RR = 1.8, OR=2.032, PAR= 44%). Conclusion: There is no evidence of increased risk of histopathological findings of the resected tracheal ring in patients with long intubation and COVID-19 disease.

The dietary supplement industry is a growing market with a variety of suppliers, producers, and distributors in terms of size and quality. Because of the little amount of regulation placed on the dietary supplement industry compared to the pharmaceutical industry in the United States, there is less pressure on supplement companies ensure that their labels accurately reflect the actual product’s content. There are few studies on the quality of fish oil sold in the U.S., particularly about quantitation of ω-3 fatty acids, specifically eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). The aim of this study was to compare the amount of ω-3 fatty acids found in fish oil capsules and liquids bought from local stores to their label claim. Of the 16 fish oil products tested, 6 were ± 20% outside of the label claim for EPA and 10 of 15 were ± 20% outside of the label claim for DHA. One product did not have a label claim for DHA. The large variance in the amount of omega-3s from the product label could mislead consumers to ingesting significantly more or less than expected.

Plastic surgery is a diverse speciality, relevant to non-plastic doctors, as plastic surgeons frequently collaborate with other specialities and its’ basic principles are transferable across multiple specialities. Foundation year (FY) doctors are the most junior doctors in the workforce and may need to apply plastic surgery knowledge and principles during their clinical duties. Despite this, formal plastic surgery education for junior doctors is limited, resulting in an educational gap. This study gains insight into the perceived confidence, knowledge gaps, skills, educational activities and needs related to plastic surgery. This qualitative study uses phenomenology through semi-structured individual interviews with 8 FY doctors. Data was analysed using reflexive thematic analysis. This study revealed that plastic surgery features diversely in the work life of FYs, who often manage patients with a lack of knowledge and confidence, influencing patient care and FY wellbeing. FYs primarily acquire knowledge and confidence through experiential learning and individual initiative. A need for curriculum improvements was expressed. FYs are an essential part of the workforce who exhibited educational gaps and a lack of confidence in plastic surgery knowledge. We suggest improved integration of plastic surgery into the FY curriculum for improved FY knowledge and patient care.

Diuretic resistance is a servomechanism involving superoxide that results from the use of escalating doses of diuretics in the treatment of heart failure. Without intervention this may lead to increased heart failure mortality. Recent heart failure studies involving the use of SGLT2 inhibitors and GLP-1 agonists have shown reductions in the need for loop diuretics along with reductions in hospitalizations for heart failure and cardiovascular mortality. Multiple mechanisms have been proposed to explain the benefits of both these drug classes but this paper is the first to explain and propose superoxide induced diuretic resistance as a therapeutic target for the treatment of heart failure.

This paper investigates the secular decline in real interest rates and the potential influence of central bank monetary policy on long-term government bond yields, focusing particularly on the US Federal Reserve (Fed). While various demand-side and supply-side explanations, such as ageing populations, lack of investment opportunities, and reduced productivity growth, have been proposed for this decline. A recent study highlighted the significant role of 3-day time windows around Federal Open Market Committee (FOMC) meetings in capturing yield changes in 10-year Treasuries. To explore if similar patterns exist in other advanced economies, this study constructs 3-day monetary policy decision windows around the 10-year government bond yields for selected countries, using both domestic central bank decision dates and those of the Fed. The findings suggest that, despite heterogeneity among advanced economies and factors like unconventional monetary policy tools and exchange rate interventions, there is substantial evidence supporting a stronger influence of the Fed's decisions on global bond yields compared to national monetary policies. By employing a simple Ordinary Least Squared (OLS) method to analyze the covariance between bond yields and policy decisions, this study establishes a connection between the literature on the global financial cycle and secular stagnation. The results imply that the Fed's influence extends beyond US borders, potentially contributing to a global monetary policy dynamic.

The escalating antibiotic crisis in Nigeria presents a critical challenge, violating fundamental human rights and ethical obligations. Skyrocketing antibiotic costs severely restrict access to essential medications, particularly for vulnerable populations. This crisis not only exacerbates health disparities but also fuels the emergence of antibiotic resistance, posing grave public health risks. Rooted in regulatory gaps, lack of transparency in drug pricing, and inadequate healthcare infrastructure, the crisis demands a comprehensive, collaborative response. Policy interventions targeting antibiotic affordability, regulatory reforms, and healthcare infrastructure investments are imperative. Upholding ethical standards and accountability mechanisms is essential to ensuring equitable access to antibiotics and safeguarding public health in Nigeria.

With the urgent need of precise positioning faced by internet of things (IoT) applications, the universality and cost of indoor positioning devices become key factors. Since the 5G network has been widely deployed, new opportunity is brought by tightly fusing the traditional low-cost sensors, i.e., the magnetometer. In this study, using 5G channel state information (CSI) and geomagnetic data, a multi-input convolutional neural network (CNN) localization system was proposed. First, to generate a data tensor that is easy for CNN processing, the raw data was reconstructed individually. Then, to comprehensively incorporate the features of 5G CSI and geomagnetic strength data, the ReLU function was chosen as the activation function of the convolutional layer. After that, a multi-input CNN was trained using the incorporated geomagnetic strength and CSI amplitude in the off-line side, and the trained CNN was recorded as a location fingerprint, which can be used for the user position prediction. Finally, in the online side and using a multi-input CNN, the 2-D coordinates are estimated and tested indoors in a typical conference room scenario. The results showed that longer sampling time of fingerprint data result in better uniqueness of the reference point, while the data collection time of locating points does not need to be long. Taking the positioning efficiency and accuracy into consideration, a sampling time of 3s at the reference point and 0.2s at the locating point are recommended. The positioning accuracy using the proposed method was 1.41 m, with an improvement of 22.9% compared with the 5G positioning, and an improvement of 18.0% compared with the 5G and geomagnetic fusing positioning using single CNN.

This study focuses on enhancing the prediction of flow characteristics in gas pipelines under hydrate-forming conditions using a validated CFD model. Four-Quadrants approach was introduced to analyse the relationship between gas and water flowrates, and to provide further insights into hydrate formation, agglomeration, deposition, and pipeline plugging. The analysis considered subcooling temperatures, water volume fractions, and gas velocities, to assess the risk of hydrate plugging in subsea gas pipelines. Results indicate that higher subcooling temperatures significantly increase the risk of hydrate formation and plugging, especially at lower gas velocities. At subcooling temperatures above 7.1 K, hydrate agglomeration and deposition become more pronounced, leading to a greater risk of plugging. Similarly, water volume fractions above 0.06 were found to increase the likelihood of hydrate blockages. However, higher gas velocities were shown to reduce this risk by promoting the sloughing of hydrates and preventing deposition. The findings align with existing literature and offer practical insights for flow assurance in gas pipeline operations.

The global landscape of health and disease has undergone significant transformations over the past several decades. While infectious diseases once dominated the morbidity and mortality statistics, non-communicable diseases (NCDs) have emerged as the leading cause of death and disability worldwide. This shift has profound implications for public health systems, healthcare delivery, and global health policies. This introduction aims to explore the main tendencies of disease burden, morbidity, and mortality in the world, with a special emphasis on NCDs and the Implications of Emerging AI Technologies. By examining the current trends and underlying factors, we can better understand the challenges and opportunities for improving global health outcomes.

We investigated the potential of Mucuna pruriens and Canavalia ensiformis as phytoremediation candidates for Tebuthiuron (TBT)-contaminated soils. Crotalaria juncea was the bioindicator specie for tebuthiuron and Lactuca sativa used in ecotoxicological bioassays, both analyses aim to verify the herbicide presence in soil samples as TBT is persistent with environmental and health risks due to its tendency to bioaccumulate. We conducted a 140-day greenhouse experiment associated with bioaugmentation by microbial inoculants - solid or liquid. Both C. ensiformis (CE) and M. pruriens (MP) exhibited distinct growth patterns, with MP demonstrating a faster growth rate than CE, evident from its higher growth apex (α = 84.52) and specific growth rate (k = 0.113). While soil samples with microbial inoculants demonstrated significant biomass increase with tebuthiuron absence, the introduction this herbicide notably hindered phytomass production, particularly in MP + TBT treatments. Liquid inoculant notably contributed to biomass accumulation in MP, whereas microbial bioaugmentation did not substantially enhance phytomass in CE under tebuthiuron presence. Furthermore, C. juncea exhibited initially slow development in the reference treatment but displayed accelerated growth and greater height with liquid inoculant compared to solid inoculant. Despite the presence of tebuthiuron, C. juncea in soil with TBT alone reached a maximum height exceeding 100 cm. However, tebuthiuron significantly reduced biomass accumulation in C. juncea, indicating its high sensitivity to this herbicide. Liquid inoculant facilitated the highest dry biomass accumulation in C. juncea, yet the introduction of tebuthiuron led to a considerable reduction in biomass, underscoring the plant's susceptibility to it. While bioaugmentation showed potential in mitigating herbicide phytotoxicity, its efficacy varied among tested inoculants. In bioassays with L. sativa, bioaugmentation with liquid inoculant resulted in a higher final germination index (GI) compared to solid inoculant and the reference treatment. Conversely, soil samples containing only tebuthiuron demonstrated a higher final GI and growth velocity compared to the reference treatment, implying the natural attenuation of toxicity over time. Additionally, previous cultivation of Mucuna pruriens positively influenced the development of test-organism, resulting in a higher GI and growth rate compared to the reference treatment. These findings provide valuable insights for various stakeholders, including the scientific community, industries, and bioengineers. They offer a strong incentive to develop advanced bioremediation strategies to address persistent pesticide contamination, especially in intensive agroecosystems like sugarcane-producing fields. Implementing our biological solution holds the potential to usher in a cleaner and safer era in agriculture, thereby protecting both society and the environment.

The resurgence of mpox, particularly in regions where the virus was previously non-endemic, has reignited interest in the cross-protective potential of smallpox antibodies. Given the genetic similarity between the mpox virus and variola virus (the causative agent of smallpox), antibodies generated against smallpox may offer a degree of protection against mpox. This study investigates the presence of smallpox and mpox antibodies in human immunoglobulin preparations containing IgG against both mpox virus and vaccinia virus using ELISA techniques. The implications of these findings for post-exposure prophylaxis (PEP) are discussed in light of the recent mpox outbreaks in Africa, as reported by the World Health Organization (WHO). Current data suggest that smallpox vaccination, even decades after eradication, may confer substantial protection against mpox, thereby serving as a critical tool in managing emerging outbreaks. Further the presence of mpox antibodies in immunoglobulin preparations was also significant. These findings strongly suggest the potential use of intravenous immunoglobulins preparation as possible therapeutic strategy. Particularly it also underscores the need for further research into the development of targeted post-exposure prophylaxis strategies that leverage the cross-reactivity of orthopoxvirus antibodies.

Respiratory infections with RSV account for an important part of hospital admissions for acute respiratory infections. Nirsevimab has been developed to reduce the hospital burden RSV (respiratory syncytial virus) infections: Compared with the product previously used, it has a stronger binding capacity to RSV F protein and a high affinity for FcRn (neonatal receptor for the Fc fragment of IgG), which extends its lifespan. Nirsevimab has been shown to be highly effective in reducing hospitalization rates for RSV infections but a large or unknown number of treated subjects have been excluded in clinical and post-marketing studies. However, analysis of these studies cannot exclude that in rare cases, nirsevimab facilitates and worsens RSV infection (or other respiratory infections). This could be attributable to ADE (antibody-dependent-enhancement) which has been observed with RSV F-protein antibodies in inactivated vaccine trials. This risk has been incompletely assessed in preclinical and clinical trials (incomplete exploration of nirsevimab effector functions and pharmacokinetics). ADE by disruption of the immune system (not studied and due to FcRn binding) could explain there is no reduction in all-cause hospital admissions in treated age groups. Given the high price of nirsevimab, the cost-effectiveness of mass immunization campaigns may therefore be debated from an economic as well as a scientific point of view.

This paper introduces the self-supervised pretext task of rare visual token enhancement: given an image, the model is trained to push the rarest visual tokens far from all the others. This pretext task slightly-but-consistently improves baseline performances for both registration and few-shot change detection on OSCD, LEVIR-CD and S2looking.

Social responsibility is imperative for its important function in the growth of societies and organizations. However, the research on corporate social responsibility (OSR) has predominantly focused on the actions of organizations. Not much has been discussed regarding the employee's behaviours in promoting the development of social responsibility within organizations. CI is known for its significant role in the organization's various outcomes, Although a conceptualization and some empirical support have been provided for its relationship with the behaviour of employees, However, the effect of CI on employee socially responsible behaviours has not yet been investigated. In this article, following OC and OI theories, we improve the research model which can describe mechanisms underpinning through which CI, OI and POS support actions for employees' social responsibility. Data was collected from members of service professionals in Saudi Arabia and examined using Structural Equation Modeling- Partial Least Squares. The findings indicated that CI actions and activities develop the skills that motivate employees to support social responsibility inside and outside the organization. Moreover, our research paper explained the mechanism under which CI activities reshape employees' socially responsible manners. The current study is among the first to look at how to modify the socially responsible behaviour of employees across organizations, which can be a starting point for transforming those employees into a sustainable society.

The study compares three machine learning and deep learning models—Support Vector Regression (SVR), Recurrent Neural Networks (RNN), and Long Short-Term Memory (LSTM)—for predicting market prices using the NGX All-Share Index dataset. The models were evaluated using multiple error metrics, including Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE), and R-squared. RNN and LSTM were tested with both 30 and 60-day windows, with performance compared to SVR. LSTM delivered better R-squared values, with a 60-day LSTM achieving the best accuracy (R-squared = 0.993) when using a combination of endogenous market data and technical indicators. SVR showed reliable results in certain scenarios but struggled in fold 2 with sudden spike that shows high probability of not capturing the entire underlying NGX pattern in the dataset correctly as witnessed with the high validation loss during the period. Additionally, RNN faced the vanishing gradient problem that limits its long-term performance. Despite challenges, LSTM's ability to handle temporal dependencies, especially with the inclusion of On-Balance Volume, led to significant improvements in prediction accuracy. The use of the Optuna optimization framework further enhanced model training and hyperparameter tuning, contributing to the performance of the LSTM model.

Background: Chronic diseases are major causes of morbidity, disability, and death worldwide. In many cases, they are potentially preventable and treatable. Glaucoma is one of the leading causes of morbidity and blindness, the early recognition of which can help reduce the adverse outcomes of the disease. Health illiteracy among these patients and the absence of self-management of these diseases are barriers to effective management worldwide. Therefore, the present study aimed to calculate the level of health literacy and activity level of patients’ activation in self-management and to explore the link between them among patients with glaucoma in outpatient clinics. Material and methods: Convenience sampling of patients with glaucoma attending the outpatient ophthalmology clinics of a university hospital in Heraklion-Greece was performed. Convenience sampling was used to recruit 312 participants. Data were collected between November 2023 and May 2024. The Patient Activation Measure-13 (PAM-13) questionnaire, in its Greek version, was used to evaluate patients’ activation level in self-management, whereas the Greek version of the European Health Literacy Survey Questionnaire 16 (HLS-EU-16) was used to assess health literacy. Results: Participants were classified as level 1(disengaged & overwhelmed) level in self-management (= 40.7, SD: ±29.9) and a sufficient health literacy level (= 10.7, SD ±3.7). However, there was no statistically significant relationship between health literacy levels and patient activation in self-management (p=0.602). Conclusions: Glaucoma patients experience challenges with health literacy and self-management activation, though there is no significant relationship between these two parameters. Multifaceted interventions seem essential for enhancing patients’ activation. Further research involving larger sample sizes, multi-center studies, and interventional design is needed.

In physics we construct idealized mathematical models in order to explain various phenomena which we observe or create in our laboratories. In this article, I recall how sophisticated mathematical models evolved from the concept of a number created thousands years ago and I discuss some challenges and open questions in quantum foundations and in the standard model. We liberated nuclear energy, landed on the Moon and built ‘quantum computers’. Encouraged by these successes many believe, that when we reconcile the general relativity with the quantum theory then we will have the correct theory of everything. Perhaps, we should be much more humble. Our perceptions of reality are biased by our senses and by our brain bending them to meet our priors and expectations. Our abstract mathematical models describe only in an approximate way different layers of physical reality. To describe the motion of a meteorite we can use a concept of a material point but the point-like approximation breaks completely, when the meteorite hits the Earth. Similarly, thermodynamic, chemical, molecular, atomic, nuclear, elementary particle layers of physical reality are described using specific abstract mathematical models and approximations. In my opinion, the theory of everything does not exist.

An oceanographic cruise from southern Adriatic to the northern Ionian basins, during 2013 spring period, allowed us to describe spatial abundance and distribution of decapod crustacean larval assemblages with a multidisciplinary approach. Seventeen locations on the Apulian and Albanian shelves and offshore waters, including the Strait of Otranto, were sampled by BIONESS electronic multinet. In May 2013 a swarm of zoeae (11 Brachyura taxa, mostly at first instar, with Xantho granulicarpus at 87%) was recorded in the neuston of the Italian side. Decapod larvae were concentrated in the first 20-30 m surface layer, strongly linked to the thermocline and generally above the DCM, suggesting that they are involved in surface water circulation. The migratory behavior of decapod larvae in coastal stations is quite regular between 20 and 60 m depth and daily time independent. In offshore stations, migration is compatible with the day-night cycle, where a minimum WMD value is evident at about 20m at night. The availability of four satellite-tracked surface drifters in the same area and period of the larvae presence, represented a possibility to discuss the geographic dispersal of larvae linked to the surface circulation in successive days. Only one drifter crossed the south Adriatic passing from the Italian to the Balkan neritic area, employing about 40 days. The actual genetic homogeneity of many Brachyura coastal species populations on the opposite sides of the Adriatic Sea, suggests the existence of a genetic connection which should not rely exclusively upon larvae circulation and needs to be fueled by additional strategies of biological communication.

Background: Lung cancer remains the leading cause of cancer-related mortality globally, predo-minantly affecting older individuals. Despite the increasing use of immune checkpoint inhibitors (ICIs) like nivolumab in non-small cell lung cancer (NSCLC), the efficacy and safety in elderly pa-tients, particularly those aged 65 and above, remain underexplored due to their underrepresenta-tion in clinical trials. Methods: This retrospective study analyzed data from 60 elderly patients (≥65 years) with metastatic NSCLC who received nivolumab as second-line or later therapy between January 2020 and May 2023. Results: The median age was 67 years, with a predominance of males (78%). Nivolumab was administered for a median of 8 cycles, with 33.3% of patients recei-ving 15 or more cycles. The median OS was 23 months, and the 1-, 3-, and 5-year survival rates were 93.3%, 54.1%, and 18.6%, respectively. Multivariate analysis identified adenocarcinoma histology, fewer than 15 cycles of nivolumab, and non-response to prior therapies as independent predictors of poor OS. Nivolumab treatment was generally well-tolerated, with 45% of patients experiencing at least grade 1 toxicity. Conclusion: Nivolumab is effective and well-tolerated in elderly patients with metastatic NSCLC, providing survival benefits comparable to those observed in younger populations. The number of treatment cycles and initial response to therapy are key determinants of survival, underscoring the importance of continued treatment in this age group.

Glioblastoma (GBM) is an incurable primary brain cancer characterized by increased reactive oxygen species (ROS) production. The redox-sensitive tumor suppressor gene TP53, wildtype (wt) for 70% of patients, regulates redox homeostasis. Glioblastoma stem cells (GSCs) increase thioredoxin (Trx) and glutathione (GSH) antioxidant systems as survival redox-adaptive mechanisms to maintain ROS below the cytotoxic threshold. Auranofin, an FDA-approved anti-rheumatoid drug, inhibits thioredoxin reductase 1 (TrxR1). L-buthionine sulfoximine (L-BSO) and the natural product piperlongumine (PPL) inhibit the GSH system. We evaluated the cytotoxic effects of Auranofin alone and in combination with L-BSO or PPL in GBM cell lines and GSCs with known TP53 status. The Cancer Genome Atlas/GBM analysis revealed a significant positive correlation between wtp53 and TrxR1 expression in GBM. Auranofin induced ROS-dependent cytotoxicity within a micromolar range in GSCs. Auranofin decreased TrxR1 expression, AKT(Ser-473) phosphorylation, increased p53, p21 and PARP-1 apoptotic cleavage in wtp53-GSCs, while mutant-p53 was decreased in a mutant-p53 GSC line. p53-knockdown in a wtp53-GSC line decreased TrxR1 expression and significantly increased sensitivity to auranofin, suggesting the role of wtp53 as a negative redox-sensitive mechanism in response to auranofin in GSCs. Auranofin and L-BSO combination synergistically increased ROS, decreased IC50s and induced long-term cytotoxicity irrespective of p53 in GBM cell lines and GSCs. Intriguingly, Auranofin increased expression of glutathione S-transferase pi-1 (GSTP-1), a target of PPL. Combination of auranofin with PPL synergistically decreased IC50s to a nanomolar range in GSCs, supporting the potential to repurpose auranofin and PPL in GBM.

Cowpea (Vigna unguiculata (L.) Walp.) is an important legume cultivated mainly in regions with limited water availability across the African and American continents. Its productivity is significantly affected by environmental stresses. Thaumatin-like proteins (TLPs), which belong to the PR-5 (Pathogenesis-Related 5) protein family, are known to be responsive to both biotic and abiotic stresses. However, their role remains controversial, with some TLPs associated with plant defense (particularly against fungal infections) and others associated with drought response. In this study, we evaluated the structural diversity and gene expression of TLPs in cowpea (VuTLPs) under different stress conditions, including biotic [mechanical injury followed by inoculation with Cowpea Aphid-borne Mosaic Virus (CABMV) or Cowpea Severe Mosaic Virus (CPSMV)] and abiotic (root dehydration). Genomic anchoring of VuTLPs revealed 34 loci encoding these proteins. Neighbor-joining analysis clustered the VuTLPs into three distinct groups. We identified 15 segmental duplication and six tandem duplication gene pairs, with the majority of VuTLP genes found to be under purifying selection. Promoter analysis associated VuTLPs with bHLH, Dof-type, and MYB-related transcription factors, supporting their diverse roles. Diversity in VuTLP function was also observed in their expression profiles under various stress conditions. Gene expression data showed that most VuTLPs are recruited within the first minutes after stress imposition, except in the root dehydration assay, where most transcripts were induced 150 minutes post-stress, a finding also validated by qPCR. Moreover, the data suggest that VuTLPs exhibit functional specialization depending on the stress condition, highlighting their diverse roles and biotechnological potential.

Background: Cardiovascular risk in prediabetic patients is substantial yet it is often underestimated in everyday clinical practice. Objectives: This study examines the future cardiovascular risk in prediabetic patients presenting with ST-segment elevation myocardial infarction (STEMI). Methods: We conducted a retrospective analysis of 725 STEMI patients at a tertiary center in Austria between 2018 and 2020, categorized into groups of non-diabetic, prediabetic, and diabetic patients. Baseline characteristics, cardiovascular risk factors, and long-term survival outcomes were compared using Kaplan-Meier survival analysis along with other statistical tests. Results: Of the 725 patients, 407 (56.1%) were non-diabetic, 184 (25.4%) prediabetic, and 134 (18.5%) diabetic. Prediabetic patients exhibited significant additional cardiovascular risk factors, such as arterial hypertension (67.4%) and dyslipidemia (78.3%), with prevalence rates between those of non-diabetic and diabetic patients. Kaplan-Meier analysis revealed that at three-year follow-up, prediabetic patients faced a survival disadvantage with a significant decrease in survival rates compared to non-diabetic patients (log-rank p = 0.016); their survival outcomes approached those of diabetic patients (p = 0.125). Conclusions: Our findings underscore the critical need for early identification and aggressive management of prediabetes in cardiovascular care of patients after acute STEMI. In current clinical practice, prediabetic patients are often underdiagnosed and undertreated, putting them at disproportionate risk. Integrating rigorous cardiovascular risk management strategies for prediabetic individuals, including lifestyle interventions and potentially pharmacological treatments, could prevent the progression to diabetes and mitigate associated cardiovascular risks. This paradigm shift in treating prediabetes as seriously as diabetes may significantly improve long-term survival outcomes for this vulnerable population.

Hydrogen has the potential to decarbonize the energy and industrial sector in the future, mainly if it is generated by water electrolysis. Proton Exchange Membrane water electrolysis (PEMWE) system is regarded as a propitious technology to produce green hydrogen from water using power supplied by renewable energy sources. It offers many benefits such as high performance, high proton conductibility, quick response, compact size, and low working temperature. Many conceptual and functional parameters influence the effectiveness of PEM, including temperature, pressure of anode and cathode regions, water content and wideness of layer, and cathode and anode exchange current density. In addition, the anodic half reaction (known as oxygen evolution reaction (OER)), and cathodic half reaction (known as the hydrogen evolution reaction (HER)) perform an important function in the development of PEMWE. The current paper aims at presenting these parameters and discussing their impacts on the performance of PEM. Also, the PEM efficiency is presented. The different methods used to enhance the scattering of OER electrocatalyst and minimizing catalyst loading to minimize the price of PEMWE are also highlighted. Moreover, the alternative of noble metals that could be used as electrocatalyst in HER and OER to minimize the cost of PEM are reviewed and presented.

One of the still debated topics regarding the olfactory function concerns the presence or absence of sex-related differences of individuals. In this study, we checked for a relationship between the olfactory function of females and males and their ability to perceive single molecules, and how this can influence the intensity with which the complex odor formed by a set of single molecules is perceived. First, females and males were classified as normosmic or hyposmic based on the TDI olfactory score obtained using the Sniffin' Sticks test. Subsequently, the headspace of roasted coffee beans as a complex olfactory stimulus was broken down into single molecules by means of a chromatographic column; these were simultaneously conveyed to a mass spectrometer (for their subsequent classification) and to the human nose which acts as a chemical sensor by means of an olfactometer port. The results obtained with this gas chromatography-olfactometry approach show both qualitative and quantitative differences between females and males, with females performing better than males. In addition, the odor intensity reported by females when sniffing pen #10 containing coffee aroma is significantly higher than that reported by males. In conclusion, these data highlight that the human ability to perceive both single compounds and complex odors is strongly conditioned, not only by olfactory function of individuals, but also by their sex.

Aim: This study aims to analyze the structure and impact of research collaborations in colonoscopy from 2000 to 2023 by examining co-authorship networks. The goal is to understand the evolution of these networks, identify key contributors, and assess how collaborative relationships influence the field. Method: I conducted a comprehensive network analysis of co-authorship patterns using data from the Web of Science (WoS) Core Collection database. The analysis included 41,213 articles related to colonoscopy published between 2000 and 2023. Using Python (Version 3.10.5) and PyCharm (Software Version 2022.1.3), we evaluated the networks through macro-level indicators (network density, clustering coefficient, number of components, average distance) and micro-level indicators (degree centrality, closeness centrality, betweenness centrality).Result: The analysis revealed a network with increasing but still fragmented collaboration over the years. The network density showed low proportions of realized connections relative to potential ones, with a high clustering coefficient indicating tight-knit groups when collaborations occurred. The number of components remained high, reflecting a fragmented structure. Prominent researchers such as Hassan, Cesare (Italy) and Dekker, Evelien (Netherlands) consistently emerged as central figures across different periods, demonstrating significant roles in facilitating connections between various research clusters.Conclusion: The study highlights a growing but fragmented collaborative landscape in colonoscopy research. Key researchers have played central roles in connecting different parts of the network, yet there remains substantial room for further integration. Strengthening collaborations across isolated groups could enhance the cohesiveness and impact of research in this field.

The objective of this research project was to evaluate the effects of the addition of inorganic fillers into PEBA at various loading levels on the processing, mechanical, thermal and physical properties of the polymer. The composites investigated in this study were Pebax® 6333 SA01 MED (PEBA100) with 10 wt.%, 20 wt.% and 30 wt.% Barium Sulphate (PEBA/BaSO4) and Bismuth Oxychloride (PEBA/BiOCl) respectively. Composites were prepared using twin screw extrusion and injection moulding. Post-processing, composite samples were analysed for their mechanical properties (via tensile, impact and flexural analysis), thermal properties (via differential scanning calorimetry), rheological performance (via melt flow index) and physical properties (via density analysis and ash content testing). The results of which reveal how filler type and concentration influence PEBA composites. The results of the study suggest that BiOCl filler enhances the aesthetic properties, increases the stiffness, while maintaining some level of flexibility with minimal adverse effects on the tensile and impact strength. When comparing BiOCl to BaSO4 filled composites, it was clear that depending on the application of the polymer composite, BiOCl may provide more desirable properties. The study highlights the importance of optimising filler concentration and processing conditions to achieve desired composite properties for specific medical applications.

Where mining activities cause disturbance in catchments, streams are often impacted by heavy loads of fine eroded material. Since geomorphological processes are very slow, it is expected that during rehabilitation typically hundreds of years are required for a mine landform to return back to stability. A sensitive approach to analyzing post-mining landform stability in tropical regions is to assess the quantity of fine suspended sediments (FSS = silt + clay (0.45 µm < diameter < 63 µm)) leaving the catchment where the mine resides and entering the receiving streams in response to storm events. Continuous stream discharge and FSS quantities upstream and downstream of the catchment where the mine resides were modeled using HEC-HMS (Hydrologic Engineering Centre-Hydrologic Modeling System). Once calibrated, the model was run for a thousand years to predict continuous stream discharge and FSS quantities for various predicted rainfall scenarios. Short-term erosion and deposition across the mine catchment were also evaluated using a cali-brated landform evolution model, CAESAR-Lisflood. This paper reviews watershed soil erosion measurements and modeling research. It compares the previous research to approach above that assesses mine landform erosion and stability in terms of fine-suspended sediments. This approach can be used to determine mine landform erosion dynamics, predict achieving stability equilib-rium, and as a post-mining rehabilitation assessment tool.

Shiga toxin-producing Escherichia coli (STEC) is a significant public health threat due to its ability to cause severe gastrointestinal diseases in humans, ranging from diarrhea to life-threatening conditions such as hemorrhagic colitis and hemolytic uremic syndrome (HUS). As the primary reservoir of STEC, cattle play a crucial role in its transmission through contaminated food and water, posing a considerable risk to human health. This comprehensive review explores host-pathogen interactions during STEC colonization of the bovine gut, focusing on the role of gut microbiota in modulating these interactions and influencing disease outcomes. We integrated findings from published transcriptomics, proteomics, and genomics studies to provide a thorough understanding of how STEC adheres to and colonizes the bovine gastrointestinal tract. The insights from this review offer potential avenues for the development of novel preventative and therapeutic strategies aimed at controlling STEC colonization in cattle threby reducing the risk of zoonotic transmission.

The increasing prevalence of multidrug-resistant pathogens (MDR), persistent biofilms, oxidative stress, and cancerous cell proliferation pose significant challenges in healthcare and environmental settings, highlighting the urgent need for innovative and sustainable therapeutic solutions. The exploration of nanotechnology, particularly the use of green-synthesized nanoparticles, offers a promising avenue to address these complex biological challenges due to their multifunctional properties and biocompatibility. Utilizing a green synthesis approach, Mauritia flexuosa Mf-AgONPs were synthesized and characterized exhibiting potent antibacterial effects against both non-resistant and MDR bacterial strains, with minimum inhibitory concentrations (MICs) ranging from 11.25 to 45 µg/mL. Mf-AgONPs also demonstrated significant antifungal efficacy, particularly against Candida glabrata, with a MIC of 5.63 µg/mL. Moreover, the nanoparticles showed strong biofilm inhibition capabilities and substantial antioxidant properties, underscoring their potential to combat oxidative stress. Additionally, Mf-AgONPs exhibited pronounced anti-tumor properties against various cancer cell lines, displaying low IC50 values across various cancer cell lines while maintaining minimal hemolytic activity at therapeutic concentrations. These findings suggest that Mf-AgONPs synthesized via an eco-friendly approach offer a promising alternative for biomedical applications, including antimicrobial, antifungal, antioxidant, and anticancer therapies, warranting further in vivo studies to fully exploit their therapeutic potential.

In conventional Federated Learning (FL), clients work together to train a model managed by a central server, intending to speed up the learning process. However, this approach imposes significant computational and communication burdens on clients, particularly with complex models. Additionally, while FL strives to protect client privacy, the server's access to local and global models raises security concerns. To address these challenges, Split Learning (SL) separates the model into parts handled by the client and the server, though it suffers from inefficiencies due to sequential client participation. To overcome these issues, SplitFed Learning (SFL) was proposed, which combines the parallelism of FL with the model-splitting strategy of SL, enabling simultaneous training by multiple clients. Our main contribution is the theoretical analysis of SFL, which, for the first time, includes non-i.i.d. datasets, non-convex loss functions, and both full and partial client participation. We provide convergence proofs for a state-of-the-art SFL algorithm based on conventional convergence analysis assumptions for FL. Our results prove that we can recover the linear convergence rate of conventional FL for the SFL algorithm with the distinction that increasing the number of local steps or clients may not speed up the convergence in SFL.

Microscale swimmers have to face the dominance of viscous forces over inertial forces, the so-called low Reynolds number (hereafter Re) regime. The undulatory motion of an elastic tail is one of the few possible mechanisms for the self-propulsion of microswimmers in the particular conditions of low Re. Instead of using a complex arrangement of multiple actuators along the body of the swimmer, this work studies the propulsion of a swimming microrobot that is able to generate a non-reciprocal motion by moving a passive elastic tail with non-uniform properties using only a single actuator located at its head. A simulation model is developed in MATLAB to evaluate the effect of different mass and elasticity distributions in the tail on the microrobot propulsion. The results are used to observe the undulating motion of the tail and to optimize the design of the robotic microswimmers in terms of efficiency.

Software is increasingly vital, with automated systems regulating critical functions. As development demands grow, manual code review becomes more challenging, often making testing more time-consuming than development. A promising approach to improving defect detection at the source code level is the use of artificial intelligence combined with natural language processing (NLP). Source code analysis, leveraging machine-readable instructions, is an effective method for enhancing defect detection and error prevention. This work explores source code analysis through NLP and machine learning, comparing classical and emerging error detection methods. To optimize classifier performance, metaheuristic optimizers are used, and a modified algorithm is introduced to meet the study’s specific needs. The proposed two-tier framework uses a convolutional neural network (CNN) in the first layer to handle large feature spaces, with AdaBoost and XGBoost classifiers in the second layer to improve error identification. Additional experiments using Term Frequency-Inverse Document Frequency (TF-IDF) encoding in the second layer demonstrate the framework’s versatility. Across five experiments with public datasets, the CNN achieved an accuracy of 0.768799. The second layer, using AdaBoost and XGBoost, further improved these results to 0.772166 and 0.771044, respectively. Applying NLP techniques yielded exceptional accuracies of 0.979781 and 0.983893 from the AdaBoost and XGBoost optimizers.

In ocean engineering, accurate and efficient numerical simulations are crucial. Leveraging axisymmetry vastly enhances the efficiency of a simulation, reducing a three-dimensional scenario to a two-dimensional simulation. Exploiting axisymmetry enables a significant reduction in computational demand while maintaining simulation fidelity. In this paper, axisymmetry is leveraged to perform a large ensemble of simulations, in order to evaluate and maximise the accuracy and efficiency of a Computational Fluid Dynamics (CFD) simulation. In particular, the free decay motion and wave radiation from a heaving semi-submerged sphere are simulated, using the Reynolds Averaged Navier Stokes (RANS) solver, interFOAM, in the opensource finite volume CFD software OpenFOAM. Validated against highly accurate experimental data, extensive parametric studies are conducted, previously limited by computational constraints, which facilitate the refinement of simulation setups. More than 50 iterations of the same heaving sphere simulation are performed, informing efficient trade-offs between computational cost and accuracy across various simulation parameters and mesh configurations. Ultimately, by employing axisymmetry, this research contributes to the development of more accurate and efficient numerical modeling in ocean engineering.

Differential Evolution (DE) is an evolutionary algorithm that has become increasingly popular due to its effectiveness and efficiency. However, its adaptation for multi-objective optimization requires further investigation. To address this issue, a novel algorithm called ILSDEMO has been proposed, which incorporates indicator-based selection and local search into a self-adaptive DE. ILSDEMO employs an archive population to store non-dominated solutions, generating an initial population uniformly distributed over the feasible solution space using orthogonal design. Additionally, two variants of DE are used to expedite convergence, while q-Gaussian mutation is utilized to exploit better trial individuals. The k-nearest neighbor rule is used to eliminate crowded solutions, and indicator-based selection is employed to generate a new parent population without diversity preservation. The performance of ILSDEMO was investigated on the test instances from the ZDT series and DTLZ series in terms of the selected indicators. The results suggest that ILSDEMO accurately and evenly approximates the true Pareto front compared to NSGAII, IBEA, and DEMO.

Currently, there are several drugs used for the treatment of type 2 diabetes (T2D), however, all of them have adverse effects. Benzothiazoles have a broad spectrum of biological activities such as antidiabetic. This study aimed to evaluate in silico and in vivo two series of 2-aminobenzothiazole derivatives linked to isothioureas (3a-w) or guanidines (4a-z) for the treatment of T2D. The ADMET properties were determined in silico from which it was possible to select compounds 3a, 3b, 4a, 4b, 4c, 4r, 4s, 4x, and 4y and, with molecular docking, it was shown that 3b and 4y showed high affinity for PPAR gamma (ΔG = -7.8 and -8.4 kcal/mol, respectively). In vivo, the LD50 value was estimated in rat based on OECD Guideline 425, being > 1750 mg/kg for both compounds. The pharmaco-logical effect of 3b and 4y was evaluated in the T2D rat model, showing that after oral admin-istration in equimolar ratio to pioglitazone (15 mg/kg) for 4 weeks, both compounds were able to reduce blood glucose levels (< 200 mg/dL) and improve the lipid profile. Therefore, 3b and 4y could be used in the future as antidiabetic agents.

The material properties and structural characteristics of ballistic composites are crucial to their ballistic performance. Investigation for the influence of the material and structural parameters of UHMWPE body armor on anti-fragmentation penetration performance has been made by numerical simulation in this paper, with a numerical modeling simulating the penetration of a 1.1 g FSP into the target plate of UHMWPE body armor, by which the simulation results demonstrate that the failure process of the body armor target plate primarily involves shear damage, interlayer delamination, and tensile damage. Furthermore, the study evaluates the effects of elastic modulus, tensile strength, shear strength, number of layers, and interlayer strength on the ballistic limit velocity of UHMWPE body armor. The findings reveal that the ballistic limit velocity is most sensitive to changes in shear strength, with variation rates ranging from -18.02% to 10.81%, showing an approximate positive correlation, while the elastic modulus has the smallest impact on ballistic limit velocity, with variation rates ranging from -1.8% to 3.6%. Additionally, appropriate interlayer strength can improve the ballistic limit velocity of the body armor to a certain extent. This study provides theoretical methods and recommendations for optimizing anti-penetration performance of UHMWPE body armor.

This study investigates the integration of natural intelligence (NI) and artificial intelligence (AI) within traditional firms, proposing a multilayer network framework to enhance economic value. The research explores the central question: How can the integration of NI and AI, facilitated by copula nodes, drive economic value creation in digitized firms? Through empirical testing across multiple industries—namely manufacturing, retail, and finance—the study evaluates the cost-benefit improvements associated with AI adoption. The findings reveal substantial efficiency gains, improved decision-making, and notable cost reductions, validating the proposed model's predictions. The study emphasizes the critical role of copula nodes in optimizing interactions between NI and AI, ensuring that their integration yields maximum economic benefits. By providing a novel framework for quantifying AI's economic impact within digitized firms, this research fills a significant gap in the literature on multilayer networks and intelligent systems. The practical implications are profound, offering a strategic pathway for firms to enhance profitability and competitiveness in the digital age.

AI integration is becoming more important in today’s world and could potentially be very useful in the life sciences and biotechnology. This study evaluates the effectiveness of AI systems in teaching molecular cloning techniques to newcomers in molecular biology, focusing on a comparison between Gemini Advanced (powered by Gemini Ultra 1.0) and ChatGPT (GPT-4o). Molecular or DNA cloning is a lab technique for creating multiple copies of a specific DNA segment. It involves isolating the DNA fragment, inserting it into a vector, and introducing it into a host cell, typically bacteria, which then generates numerous copies of the DNA. This essential technique underpins genetic engineering, allowing for gene study, protein expression, and the creation of genetically modified organisms. The primary objective of this study was to assess whether individuals with limited laboratory experience could effectively acquire a specific molecular biology skill set solely through an AI system, rather than relying on the more traditional ‘learning by shadowing’ approach. Participants with limited lab experience completed these tasks using both Gemini and GPT-4o, and evaluated on quality of instructions, conciseness, scientific accuracy, and user satisfaction. Results indicated that both AI systems demonstrated strengths in delivering clear and comprehensive instructions, but in different ways. Gemini, although more interactive with images and diagrams lacked directness and had a harder time keeping past steps in its “memory”. On the other hand, GPT-4o was much more direct and concise in the steps listed and had more accurate results akin to what is performed in the lab. This study underscores the potential of AI-driven tools to simplify complex biotechnological procedures, making them accessible for learners at all levels.

Pigeon Newcastle disease, caused by pigeon paramyxovirus type 1 (PPMV-1), is a significant infectious disease in pigeons that can result in substantial mortality and poses a severe threat to the pigeon industry. Rapid and accurate onsite diagnosis of pigeon disease is crucial for timely diagnosis and the implementation of effective prevention and control measures. In this study, we established a rapid detection method for PPMV-1 based on recombinase-aided amplification (RAA) and CRISPR/Cas12a. The RAA primers target the conserved regions of the L gene for preamplification in clinical nucleic acid samples, followed by CRISPR/Cas12a detection of the target gene. Visualization could be achieved by combination with a lateral flow dipstick (LFD). This method demonstrated high specificity, showing no cross-reactivity with non-PPMV-1 samples. The sensitivity of the method assessed by fluorescence analysis reached 100 copy/µL, and when it was combined with an LFD, the sensitivity was 103 copies/µL. The constructed RAA-CRISPR/Cas12a-LFD visual detection method was applied to clinical sample testing and was found to enable rapid and accurate detection of swab samples and tissue specimens. Its sensitivity was consistent with the current gold standard, quantitative real-time PCR results. The RAA-CRISPR/Cas12a-LFD detection method we developed provides a novel approach for the rapid, simple, precise, and specific onsite diagnosis of pigeon Newcastle disease.

To verify the efficacy of placental extracts (Pla-Ext) and human mesenchymal stem-cell-derived exosomes (hMSC-Exo) against human skin aging, we investigated the human dermal fibroblast (HDF) response following hMSC-Exo and Pla-Ext treatment and whether they elicited resistance to damage when HDFs were subjected to several types of aging stresses. The effect of hMSC-Exo alone, the combined effect of Pla-Ext and hMSC-Exo, and the effect of hMSC-Exo (Pla/MSC-Exo) recovered from cultures with Pla-Ext added to hMSC were verified using collagen, elastin, and hyaluronic acid synthase mRNA levels for each effect. Cells were subjected to photoaging (UV radiation), glycation (glycation end product stimulation), and oxidation (H2O2 stimulation) as HDF stressors. Pla-Ext did not significantly affect normal skin fibroblasts considering intracellular parameters; however, a pro-proliferative effect was observed. Pla-Ext induced resistance to several stresses in skin fibroblasts (UV irradiation, glycation stimulation, H2O2 stimulation) and inhibited reactive oxygen species accumulation following H2O2 stimulation. Although the combined efficacy of hMSC-Exo and Pla-Ext was unclear, some changes resulted in senescence stress resistance due to preconditioned hMSC-Exo stimulated by Pla-Ext. This suggests that Pla-Ext supplementation may cause some changes in the surface molecules or hMSC-Exo content (e.g., microRNA).

The goal of this study is to create and carry out a self-healing cloud system by combining an event-driven automation framework depending on the if-this-then-that principle for managing incidents and recovery. A recovery engine with Artificial Intelligence (AI)-based decision-making approaches is presented—which chooses the best remedial actions from a pre-established catalogue in order to maximise system reliability and minimise downtime. The system is tested on an OpenStack-based video on demand service—where multiple issues are replicated in order to assess the efficaciousness of various recovery actions and workflows. The decision-making module of the recovery engine examines data from these experiments to determine the most effective remedial actions, taking into account their impact on the quality of service and other factors. The recovery engine is only meant to need human input when it comes to parameterizing and optimising decision models at particular points in time. In order to show how these AI-driven decision-making techniques can enhance mean time to repair and overall service quality in cloud environments—the study presents and assesses their results. This novel strategy represents a change towards cloud systems that are more sturdy autonomous, and able to effectively manage anomalies and recover from failure.

This brief report investigates the potential correlation between manual labor and opioid addiction, focusing on contributing factors such as chronic pain, regular exercise, healthcare access, and housing stability. Although manual labor is associated with higher rates of work-related injuries and chronic pain, the review finds no strong, direct correlation between manual labor and increased opioid addiction rates. The relationship is complex and influenced by a range of socio-economic factors. The findings highlight the need for further research, particularly longitudinal studies, to explore these dynamics in depth and develop targeted interventions for at-risk populations.

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

Trenchless technologies are utilized for installing new pipes or repairing and replacing old ones, categorized into construction and rehabilitation/replacement methods. With rapid urbanization, new pipe networks must be established in proportion to population growth. Additionally, due to issues like corrosion and aging, a significant portion of storm sewers, waste sewers, gas, and water pipes need annual replacement or rehabilitation. Traditional open-cut methods are no longer viable due to traffic disruption, safety concerns, environmental impacts, and high costs. Trenchless construction methods address these issues effectively. Construction trenchless methods include horizontal earth boring (no worker entry), pipe jacking, and utility tunneling (worker entry). Horizontal earth boring is further divided into horizontal auger boring, horizontal directional drilling, pipe ramming, microtunneling, pilot tube microtunneling, and compaction methods. The first part of the current study reviews and discusses the design criteria for horizontal auger boring, horizontal directional drilling, pipe jacking, pipe ramming, and microtunneling. Based on these unique project requirements, the optimal trenchless technology can be proposed. In the second part of the research, a hierarchical algorithm is proposed, based on literature concepts, to serve as a decision-making tool for selecting the optimal trenchless construction method. Sometimes, multiple methods may be proposed, with the best one chosen based on equipment availability, skilled teams, budget, and sustainability principles. Although trenchless renewal methods are not the focus of this study, their design criteria are provided in the appendices to offer a comprehensive collection of design requirements for all trenchless technologies.

In today's technologically advanced landscape, sensors feed critical data for accurate decision-making and actions. Ensuring the integrity and reliability of sensor data is paramount to system performance and security. This paper introduces an innovative approach utilizing discrete wavelet transforms (DWT) embedded within microcontrollers to scrutinize sensor data meticulously. Our methodology aims to detect and isolate malfunctions, misuse, or any anomalies before they permeate the system, potentially causing widespread disruption. By leveraging the power of wavelet-based analysis, we embed computational intelligence directly into the microcontrollers, enabling them to monitor and validate their outputs in real-time. This proactive anomaly detection framework is designed to distinguish between normal and aberrant sensor behaviors, thereby safeguarding the system from erroneous data propagation. Our approach significantly enhances the reliability of embedded systems, providing a robust defense against false data injection attacks and contributing to overall cybersecurity.

The fundamental divergence in foundation of modern physics lies in the incompatibility between quantum theory and relativity. This study created a relative continuum, found a mathematical tool for the cosmic continuum; proposed dark particle hypothesis, filled gap on minimum existence quantity particle; discovered new equivalence principle, bridged differences in foundation of physics; and established an ideal model, revealed deep essence of cosmic and material structure. In this model, any cosmic system is a continuum composed of existence continuum relative to the wavelength of bosons energy waves and its dimension continuum. This model provides new perspectives on the fundamental problems of physics and cosmology. Firstly, it elucidated the physical mechanism of bosons in fundamental interactions. Secondly, it reconstructed the understanding of the basic unit of the cosmic and material structure. Thirdly, it updated the inherent concepts about the existence form and existence dimension. Fourthly, it restored the causality truth of wave function collapse in quantum mechanics.

The refugee crisis has been one of the most challenging problems in the European in recent years, causing sudden and significant political turmoil in most of its member states. Notwithstanding the international treaties on refugee protection, a crucial issue is the reluctance of many local commu-nities to offer refugees access to the labour market and daily social activities. In addition to the dif-ficulties regarding social acceptance, there are also many other legal, social, ethical and political obstacles for refugees. This discussion is mainly limited to the realm of politics and ethics with very few references to the field of management, Corporate Social Responsibility (CSR) and corporate sustainability (CS) where the issues of marginalized people, minorities and vulnerable people are frequently addressed. To fill this gap, this article aims to discuss the role of CSR and CS in over-coming obstacles for refugees in their effort to integrate into the labor market. Through a narrative literature review and snowballing techniques, a theoretical framework is developed to outline the ways that CSR and CS can assist refugees in overcoming different types of obstacles in host coun-tries. Finally, in the discussion, ways in which CSR and CS literature could play a critical role in this discussion are highlighted and how the private sector could relieve the refugee crisis through CSR strategies.

The border between Niger and Libya, often described as an "ungoverned space," epitomizes the complex interplay of economic, political, and security challenges within the Sahel region. Authorities and international actors have made various efforts to establish control, but tribal structures predominantly manage governance in these areas. These structures lack formal institutions and rely heavily on external security interventions to combat terrorism and irregular migration. The increasing militarization of the region raises significant concerns about the long-term efficacy of these approaches in achieving sustainable security. This study argues that enduring stability in such contexts requires a nuanced balance of economic, political, and social factors. The research methodology includes a comprehensive literature review of security issues, governance, state fragility, and counter-terrorism, utilizing scientific journals, books, reports, and newspapers. The study investigated the dual nature of ungoverned spaces, examining their role in facilitating terrorism and organized crime while highlighting the critical need for governance to enhance citizen welfare and support state functions. Recent developments in Libya and the Sahel under-score the urgency of addressing security and developmental challenges. The study concludes by advocating for sustainable political and development initiatives over militarization, emphasizing the necessity of a new social contract to address the security challenges in the Sahel region effectively.

Polar auxin transport (PAT) and auxin efflux carriers are known components controlling leaf complexity and venation patterns in some model plant species. Evidence indicates that PAT generates auxin converge points (CPs) that in turn lead to local leaf formation and internally into major vein formation. However, the role of PAT in more diverse leaf arrangements and vein patterns is largely unknown. We used pharmacological inhibition of PAT in developing pinnate tomato, trifoliate clover, palmate lupin, and bipinnate carrot leaves and observed dosage-dependent reduction to simple leaves in these eudicots. Leaf venation patterns changed from craspedodromous (clover, carrot), semi-craspedodromous (tomato) and brochidodromous (lupin) to more parallel patterning with PAT inhibition. The visualization of auxin responses in transgenic tomato plants showed that discrete and separate CPs in control plants were replaced by diffuse convergence areas near the margin. These effects indicate that PAT plays a universal role in the formation of different leaf and vein patterns in eudicot species via a mechanism that depends on the generation as well as separation of auxin CPs. Computer simulations indicate that variations in PAT can alter the number of CPs, corresponding leaf lobe formation and position of major leaf veins along the leaf margin in support of experimental results.

Many natural and artificial liquid environments such as rivers, oceans, lakes, water storage tanks, aquariums, and urban water distribution systems, are difficult to access. As a result, technology is needed to enable autonomous liquid sampling to monitor water quality and ecosystems. The existing in-situ sample acquisition and handling systems for liquid environments are currently limited to a single use and are semi-autonomous, relying on an operator. Liquid sampling systems should be robust and light and withstand long-term operation in remote locations. The system components involved in liquid sampling should be sterilisable to ensure reusability. Here, we introduce a prototype of a liquid sampler that can be used in various liquid environments and may be valuable for the scientific characterisation of different natural, remote, and planetary settings. The Autonomous Planetary Liquid Sampler (APLS) is equipped with pre-programmed fully autonomous extraction, cleaning, and sterilisation functionalities. It can operate in temperatures between -10 ℃ and 60 ℃ and pressure of up to 0.24 MPa (~24 m depth below mean sea level on Earth). As part of the control experiment, we demonstrate its safe and robust autonomous opera-tion in a laboratory environment using a liquid media with Bacillus subtilis. A typical sampling procedure required 28 s to extract 250 mL of liquid, 5 s to fill the MilliQ water, 25 s for circulation within the system for cleaning and disposal, and 200 s to raise the system temperature from ~30 °C ambient laboratory temperature to 150 °C. The temperature is then maintained for another 3.2 hours to sterilise the critical parts, allowing a setup reset for a new experiment. In the future, the liquid sampler will be combined with various existing analytical instruments to characterise the liquid solution and enable the autonomous, systematic monitoring of liquid environments on Earth.

This article presents a rigorous approach to the Collatz Conjecture, focusing on fundamental properties of Collatz sequences. We establish key properties of the Collatz function and its inverse, including surjectivity and injectivity. The structure of Collatz sequences is analyzed in depth, proving important results such as the Bounded Subsequence Property and the uniqueness of cycles. Central theorems on the properties of Collatz sequences, including the boundedness of all sequences and the nature of the unique cycle, are presented and proved. These results culminate in a complete resolution of the Collatz Conjecture, demonstrating that all Collatz sequences eventually reach the cycle {1, 4, 2}. We provide a rigorous proof of the conjecture, while emphasizing the need for thorough peer review and verification by the mathematical community given the significance of this long-standing problem.

We study the nonlinear absorptive and dispersive optical properties of molecular systems immersed in a thermal reservoir interacting with a Four-wave Mixing (FWM) signal. Residual spin-orbit Hamiltonians are considered in order to take into account the internal structure of the molecule. As system parameters in the dissipation processes, transverse and longitudinal relaxation times are considered for stochastic solute-solvent interaction processes. The intramolecular coupling effects on the optical responses are studied using a molecule model consisting of two coupled harmonic curves of electronic energies with displaced minima in nuclear energies and positions. In this study, it was considered the complete frequency space is considered through the pump-probe detuning, not restricting the derivations to only maximums of population oscillations. This approach opens the possibility of studying the behavior of optical responses, which is very useful in experimental design. Our results indicate the sensitivity of the optical responses to parameters of the molecular structure as well as to those derived from the photonic process of FWM signal generation.

Measuring cell confluence in high-throughput screening of pharmaceutics, cell culture monitoring, cancer research, and industrial applications requires quantitative and standardizable measures to minimize subjective observations and increase throughput1-12 . Over the past half-century, non-invasive specialized programs have been created to quantitatively assess cell confluence, and some software tools exist to meet these needs1,4,5,6,7,8,9 . However, many of these tools are expensive, computationally-demanding, or inaccessible to non-experts1,6. With the assistance of generative artificial intelligence, we have developed the Confluence Analysis Program (CAP), a modern tool designed to be precise, interactive, and user-friendly. CAP is written entirely in Python and runs in any command-line interface (CLI), including Terminal (OS) and Command Prompt (Windows). In addition to fetching all necessary external libraries automatically and prompting drag-and-drop image retrieval, CAP features live visual comparison of cell mass identification to the original image assay. Our results demonstrate robust performance of CAP on fluorescent micrographs of varying confluences ranging from low to high. CAP is provided as a free resource, accessible in the Supplementary Materials.

Antimicrobial peptides (AMPs) are short, usually cationic peptides with an amphiphilic structure, which allows them to easily bind and interact with the cellular membranes of viruses, bacteria, fungi, and other pathogens. Bacterial AMPs, or bacteriocins, can be produced from Gram-negative and Gram-positive bacteria via ribosomal synthesis to eliminate competing organisms. Bacterial AMPs are vital in addressing the increasing antibiotic resistance of various pathogens, potentially serving as an alternative to ineffective antibiotics. Bacteriocins have a narrow spectrum of action, making them highly specific antibacterial compounds that target particular bacterial pathogens. This review covers the two main groups of bacteriocins produced by Gram-negative and Gram-positive bacteria, their modes of action, classification, sources of positive effects they can play on the human body, and their limitations and future perspectives as an alternative to antibiotics.

The present paper explored the possibility of discriminating between different malignant degrees of Chondrosarcoma (CS), a diffused bone tumor, and Enchondroma (EC), its benign version, through an approach based on the coupling between Confocal Raman Microscopy (CRM) and Machine Learning (ML) techniques. Recently, Raman Spectroscopy has proven to be a powerful tool for a complete grading of CS by distinguishing between grade 1, 2 and 3, and to distinguish CS from EC. In this paper, we tested some models, belonging either to ML or to the sub-type called Deep Learning (DL), showing excellent classification performances, especially the DL algorithms, with classification accuracy approaching to 100%, making the models promising for future implementations of Raman spectroscopy when applied to oncology diagnosis. In turn, we highlighted how some proper ML models result in worse classification performances but better resolution of specific chemical target compounds, possible candidate to become malignant markers, with relevant implication for a correct diagnosis.

Myocardial Infarction with Non-Obstructive Coronary Arteries (MINOCA) is a clinical entity characterized by the absence of significant coronary artery obstruction in epicardial arteries (&lt; 50%) on coronary angiography in the setting of acute myocardial infarction (AMI). This article aims to provide a narrative review of the pathophysiological mechanisms, diagnostic challenges, and prognosis associated with MINOCA focusing only on cases associated with myocardial ischemia but of non-atherosclerotic origin. Etiological factors, including thromboembolism, coronary artery spasm, spontaneous coronary artery dissection, coronary microvascular disease, and supply-demand mismatch are addressed. Imaging modalities such as echocardiography, advances in coronary angiography like intravascular ultrasound (IVUS) and optical coherence tomography (OCT), cardiac magnetic resonance (CMR), and coronary computed tomography angiography (CCTA) are also analyzed. MINOCA patients have a better short-term prognosis compared to those with obstructive coronary artery disease but face significant long-term risks, underscoring the need for precise diagnosis and management strategies. Elevated inflammatory markers and specific genetic predispositions are also associated with adverse outcomes in MINOCA. This review focused on MINOCA from the pathophysiological perspective on ischemic, non-atherosclerotic causes, the diverse underlying mechanisms, the challenges in achieving accurate diagnosis, the importance of a tailored therapeutic approach and the necessity for further investigation of clinical outcomes.

The term ovarian rejuvenation is used for treatments aiming to reactivate ovarian function in women suffering from premature ovarian insufficiency or women with poor ovarian response following ovarian stimulation treatments. Following Bologna criteria, patients with poor ovarian response (POR) are those patients with at least one previous stimulated cycle with POR, are of advanced maternal age, and have an abnormal ovarian reserve. Patients with at least 3 failed IVF cycles due to poor ovarian response (POR) and patients with POF with amenorrhea for at least 6 months, low estradiol, and high concentrations of LH and FSH were referred for ovarian PRP treatment. Out of 190 procedures, 15 were performed using the THL as there was an inaccurate visibility by vaginal ultrasound. Under direct visualization, PRP was injected in each ovary using a 19G needle. In the 53 patients referred for IVF, an embryo transfer was possible in 40% of the started cycles (n=21); the pregnancy rate per transfer was 52% with a live birth rate of 24%. The access to the pelvis by the THL enabled a direct visualization of both ovaries allowing a correct injection. Due to maternal age, patients should be informed of the elevated risks of 40% - 50% of biochemical pregnancies or miscarriages.

Background: Introduction of new technologies in the management of oral disease has revolutionized treatment approaches, offering less invasive options and improved patient outcomes. Among oral cavity diseases, sialolithiasis is the most common disorder of the salivary glands. It involves the formation of calculi or stones within the salivary ducts, primarily affecting the submandibular gland due to its tortuous duct and the alkaline nature of its saliva. In particular, Laser-assisted techniques have shown significant promise in enhancing the precision and safety in the management of sialolith removal. This article aims to present a case report and also explores the scientific evidence supporting these innovative methods, highlighting their benefits and limitations in clinical practice.; Methods: The research was conducted using PubMed and Scopus search engines with a combination of relevant keywords, including laser, laser-assisted, laser treatment in combination with sialolith, sialolith removal, and sialoadenectomy. Selected articles were carefully reviewed to identify studies reporting data on the effectiveness of laser-assisted sialolith removal; Results: The results of the literature review indicate a growing interest in the application of Diode Laser and CO2, with evidence suggesting improved clinical outcomes and reduced postoperative pain compared to traditional methods; Conclusions: Although lasers offer enhanced safety and reduced morbidity and bleeding, which ensures optimal visibility, their high cost and the need for specialized training are limitations. Further randomized clinical trials and longer follow-up studies are needed to better evaluate their use in sialolith removal.

Textile wastewater containing dyes pose significant environmental hazards. Advanced oxidative processes, especially the heterogeneous photo-Fenton process, are effective in degrading a wide range of contaminants due to high conversion rates and ease of catalyst recovery. This study evaluates the photocatalytic degradation of azo dyes Acid Red 18 (AR18), Acid Red 66 (AR66) and Orange 2 (OR2) using magnetite as a catalyst. The magnetic catalyst was synthesized via a hydrothermal process at 150°C. Experiments were conducted at room temperature, investigating the effect of catalyst dosage, pH, and initial concentrations of H2O2 and AR18 dye. Kinetic and thermodynamic studies were performed at 25, 40 and 60°C for the three azo dyes (AR18, AR66 and OR2) and the effect of the dye structures on the photocatalytic efficiency was investigated. At 25 °C for 0.33 mmol.L-1 of dyes at pH 3.0, using 1.4 g.L-1 of catalyst and 60 mg.L-1 of H2O2 under a UV radiation of 16.7 mW.cm-2 the catalyst showed a 62,3% degradation for AR18, 79.6% for AR66, and 83.8% for OR2 in 180 minutes of reaction. The oxidation of azo dyes under these conditions is spontaneous and endothermic. The pseudo-first order kinetic constants indicated a strong temperature dependence with an order of reactivity of the type: OR2 &gt; AR66 &gt; AR18, which is associated to the characteristics of molecular complexity (size, steric hindrance, aromatic conjugation), electrostatic repulsion and the nature of the acid-base interactions on the catalytic surface.

Based on an in-depth analysis of the factors influencing the compressive strength of ultra-high performance concrete (UHPC), this study examined the impact of both single factors and combined factors on UHPC performance using experimental data. The correlation analysis indicates that cement content, water content, steel fiber, and fly ash significantly affect the strength of UHPC, whereas silica fume, superplasticizers, and slag powder have a relatively smaller influence. This analysis provides a scientific basis for model development. Furthermore, the support vector regression (SVR) model was optimized using the arithmetic optimization algorithm (AOA). The superior performance and computational efficiency of the AOA-SVR model in predicting UHPC compressive strength were validated. Compared to SVR, support vector machine（SVM）, and other single models, the AOA-SVR model achieves the highest R2 value and the lowest error rates. The results demonstrate that the optimized AOA-SVR model possesses excellent generalization ability and can more accurately predict the compressive strength of UHPC.

Background: Sarcopenia is a progressive muscle disorder characterized by muscle wasting, decreased strength, and a substantially elevated risk of developing severe and potentially life-threatening health complications. For decades, muscle wasting has been recognized as a clinical symptom in various severe diseases and conditions. However, with increasing life expectancy and an aging population, sarcopenia has emerged as a prominent age-related condition in primary care, significantly contributing to disability and mortality rates. Aim and Objective: Our goal was to elucidate the clinical characteristics associated with sarcopenia prevalence in postmenopausal women with type 1 osteoporosis. Methodology: 370 postmenopausal osteoporosis patients who routinely visited the physiotherapy department at Ali Fatima Hospital were examined in this cross-sectional investigation. Mean age 64.59 ± 5.85 years, it was discovered that the patients' quality of life, postural stability, muscular strength, and balance were related to the existence of sarcopenia. Conclusion: In summary, among postmenopausal female patients with type 1 osteoporosis, the incidence of sarcopenia was relatively high (90.35%), affecting quality of life in 39.82% of patients, postural instability in 92.21% of patients, and balance in 39.92% of patients.

Statistics modules are included in most university degrees, independent of the degree area. They have an important role in preparing students for the real world. The overall goal of this paper is to identify the common statistical issues students face during the transition from secondary education to tertiary education. Drawing upon data from the University College Dublin (UCD) Math Support Center (MSC) and Universidad Rey Juan Carlos (URJC), our approach aims to optimize learning experiences while advancing sustainability objectives. In this paper, we conducted a categorization of statistical concepts taught in university (based on URJC). Using this categorization, UCD MSC tutor comments were categorized and validated, and subsequently descriptive analyses and text mining were used on the UCD MSC comments to achieve a deeper understanding of the statistical issues. Building on this study, we plan to develop a suite of evidence-based sustainable educational applications and games to support undergraduate students internationally in first-and second-year statistical modules. Our findings on students’ main statistical issues contribute to the cultivation of lasting statistical literacy among students. This research advances the sustainability agenda within statistical education.

In previous studies, drones have been used to carry out visual inspections of heritage elements. In order to complement the information obtained with the common drone, a new underwater drone model is proposed for the specific case of old bridges. The aim is to verify the applicability of underwater drones for the inspection of submerged elements of old heritage bridges, given the large number of bridge disasters and collapses linked to failures in their foundations. To this end, we carried out an underwater inspection of the visible submerged elements (submerged but not buried) of three old bridges crossing different rivers. The different locations and characteristics of these bridges allow us to draw some initial conclusions. The results of the operations carried out show that underwater drones are not only useful for this type of inspection, but that the work is much safer than with the means currently used (underwater divers). In addition, the use of drones makes it possible to study certain parameters that can anticipate subsequent foundation problems affecting the entire bridge, such as the settlement or rotation of piers or abutments.

The recent world events seem to play a significant influence in the acquisition and upgrowth of empathy and socio-emotional competencies (SEC). In this study we sought to assess how the perception of these events affects the level of socio-emotional competencies and interpersonal reactivity of Portuguese adolescents and analyze differences due to sex and relationship status on its dimensions. Participants were 230 adolescents of both sexes, living in Portugal, with ages between 16 and 18 years old, mostly female, with the secondary educational level, living in an urban area and not in a relationship. An online questionnaire was applied, with the Social and Emotional Competencies (SEC-Q) scale and the Interpersonal Reactivity Index (IRI). As results, it was found that adolescents have an above-average global interpersonal reactivity, with empathic concern and perspective taking presenting the higher values. Adolescents show a medium high average level of SEC, with the highest domains being self-awareness and social awareness and prosocial behavior. Girls showed significantly more interpersonal reactivity in empathic concern, personal distress and fantasy, and boys presented more self-awareness. As for the relationship status, adolescents not in a relationship manifest more personal distress, while those in a relationship present higher values in all dimensions of SEC. Although the perception of Portuguese adolescents does not seem to have been greatly affected by recent world events, these results can contribute to thinking about youth protection policies and designing more appropriate interventions to promote well-being in this crucial period of life, especially in times of instability.

The cyclamen mite, Phytonemus pallidus, is one of the important pests in strawberry cultivation in Canada. This insect pest hides on young strawberry leaves that have not yet opened, which limits their control. In addition, the fight against the latter involves the use of synthetic chemicals that are not without effect on the environment, human health and beneficial organisms. We hypothesized that vectorization by bees could reduce the number of applications, product runoff and provide targeted control of these pathogens. To do this, field trials were conducted to evaluate the effectiveness of bumblebees Bombus terrestris in propagating Beauveria bassiana to control this pest. Our results showed that bumblebees were able to disseminate the inoculum on strawberry plants. Also, all the products used (B. bassiana and neem oil) were effective on P. pallidus. It should be noted that high mortality has been noted on this pest thanks to the application of this entomopathogen by spraying. In addition, neither of the two products tested had a significant effect on lady beetles C. septempunctata. These results therefore suggest the use of bee vectoring and neem essential oils in the sustainable management of strawberry mites.

This paper is concerned about the novel exact solitons to the truncated M-fractional (1+1)-dimensional non-linear generalized Bretherton model with arbitrary constants . This model is used to explain the resonant nonlinear interaction between the waves in different phenomenon, including fluid dynamics, plasma physics, ocean waves, and many others. A series of exact solitons, including bright, dark, periodic, singular, singular-bright, singular-dark, and other solitons are obtained by applying the extended sinh-Gordon equation expansion (EShGEE), and the modified (G′/G2)-expansion tech- niques. A novel definition of Fractional derivative provides the solutions distinct from the present solutions. Mathematica software is used to obtain, and verify the solutions. The solutions are shown through 2-D, 3-D, and density plots. The stability process is performed to verify that the solutions are exact and accurate. The modulation instability is used to determine the steady-state stable results to the corresponding equation.

Background The aims of this study were to assess the peri-operative morbidity, mortality and long-term survival of octogenarians undergoing ATAAD repair, and to compare open and closed distal anastomosis techniques. Methods This was a single-centre retrospective study (2007-2021). Open versus closed distal anastomosis were compared. Uni and multi-variable logistic regression analyses were performed to identify independent predictors of in-hospital mortality. Kaplan-Meier and Cox proportional hazards methods were used to compare long-term survival. Results Fifty octogenarians patients were included (median age - 82 years, closed distal – 22, open distal - 28). Median CPB time was 187 minutes (open distal vs closed distal group; 219 minutes vs 115.5 minutes, p30 days or return to theatre; HR; 4.1, p=0.02) predicted adverse survival. Open distal anastomosis did no impact survival. Conclusions – ATAAD repair in selected octogenarians has favourable short and long-term survival. There is no significant difference between open versus closed distal anastomosis strategies.

There is paucity of data in the available medical literature regarding the parameters of volumetric perfusion of pancreas grafts. Materials and methods From February 5, 2016 to December 23, 2021, we performed perfusion computed tomography in 41 patients at different times after simultaneous pancreas and kidney transplantation. The study group consisted of 18 men (44%) and 23 women (56%) with a long history of type 1 diabetes complicated by terminal chronic renal failure. The results of perfusion computed tomography of the pancreas graft were studied, and the effects of post-transplantation timing and graft revascularization peculiarities on volumetric perfusion parameters were evaluated. Results The median arterial blood flow, arterial blood volume, and permeability of the pancreas graft were 115.1 [99.7;130.3] mL/100 mL/min, 46.7 [37.4;56.9] mL/min and 8.6 [4.1;11.4] mL/100 mL/min, respectively. No statistically significant differences in the averaged perfusion values were found in the head, body, and tail of the pancreas graft. The post-transplantation timing and the number of arteries involved in graft revascularization did not have a significant effect on the volumetric perfusion of the graft. Conclusion The volumetric perfusion results of the pancreas graft correspond to those obtained in the study of pancreatic perfusion in healthy participants.

The research of tangible creativity support tools (T-CSTs) has been increasing in recent years. However, there is a lack of review that interprets what T-CSTs trends must be considered and how challenging opinions should be broken. Hence, a focused and critical review of existing studies is necessary. This paper analyzed 86 studies related to T-CSTs following the PRISMA protocol. First, the research tendencies were extracted and provided a basic knowledge construction. Then, we extracted primary research questions, categorized the adopted design and technological solutions, and identified the researchers’ hypotheses-validation. Last, we proposed research gap, challenge and potential opportunities for future researchers and designers. This review will benefit people in the fields of tangible interaction, design studies and education.

This research evaluates the feasibility of addressing computer vision problems with limited resources, particularly in the context of medical data where patient privacy concerns restrict data availability. (1) Background: The study focuses on diagnosing skin diseases using five distinct transfer learning models based on convolutional neural networks. Two versions of the dataset were created, one imbalanced (4092 samples) and the other balanced (5182 samples), using simple data augmentation techniques. Preprocessing techniques were employed to enhance the quality and utility of the data, including image resizing, noise removal, and blur techniques. The performance of each model was assessed using fresh data after preprocessing. According to the research findings, (2) Methods: the VGG-19 model achieved an accuracy of 95.00% on the imbalanced dataset. After applying augmentation on the balanced data, the best-performing model was VGG-16-Aug with an accuracy of 97.07%. (3) Results: These results suggest that low-resource approaches, coupled with preprocessing techniques, can effectively identify skin diseases, particularly when utilizing the VGG-16-Aug model with a balanced dataset. (4) Conclusions: The study addresses rare skin disorders that have received limited attention in past research, including acne, vitiligo, hyperpigmentation, nail psoriasis, and SJS-TEN. The findings highlight the potential of simple data augmentation techniques moreover, explainable AI: Grad-CAM interpreted the model outcome by showing image contours visually as well as identifying uncommon skin conditions and overcoming the data scarcity challenge. The implications of these research findings are significant for the development of machine learning-based diagnostic systems in the medical field. Further investigation is necessary to explore the generalizability of these findings to other medical datasets.

Heterosis of growth traits in economic fish has benefited the production of aquaculture for many years, yet its genetic and molecular basis has been remained obscure. Nowadays, a new germplasm of hybrid Jinhu grouper (Epinephelus fuscoguttatus♀ × E. tukula♂), exhibiting paternal-biased growth heterosis, has provided an excellent model for investigating the potential regulatory mechanisms of heterosis. We integrated transcriptome and methylome to unravel the changes of gene expression, epigenetic modification, and subgenome dominance in Jinhu grouper compared with maternal E. fuscoguttatus. Integration analyses showed that the heterotic hybrids showed lower genomic DNA methylation levels than the purebred parent, and the up-regulated genes were mostly DNA hypomethylation. Furthermore, allele-specific expression (ASE) detected paternal subgenome dominance regulated paternal-biased heterosis, and paternal bias differentially expressed genes (DEGs) were wholly up-regulated in the muscle. Muti-omics results highlighted the role of lipid metabolism, particularly “Fatty acid synthesis”, “EPA biosynthesis”, and “Signaling lipids”, in Jinhu grouper heterosis formation. Coherently, our studies have proved that the eicosapentaenoic acid (EPA) of Jinhu grouper was greater than that of maternal E. fuscoguttatus (8.46% vs 7.46%). Finally, we constructed a potential regulatory network for control of the heterosis formation in Jinhu grouper. Among them, fasn, pparg, dgat1, igf1, pomca, fgf8a, and fgfr4, were identified as key genes. Our results provide new and valuable clues for understanding paternal-biased growth heterosis in Jinhu grouper, taking a significant step towards the molecular basis of heterosis.

There is a lack of studies on the level of stress and health of families of workers in road transport. This study aimed to evaluate the perceived stress level and Family Effectiveness of family members of road transport workers. A quantitative study was carried out with family members of road transport workers in the southern region of Brazil. For the data collection, a sociodemographic form, the Perceived Stress Scale (PSS), and the Evaluation of Family Effectiveness Strategies were used. The data were analyzed by simple frequency, Spearman correlation coefficient (ρ) (p &lt; 0.05), and descriptive analysis from the perspective of the Systemic Organization. 49 family members of road transport workers were participants. Perceived stress was higher in family members who had more than nine years of schooling, the targets of Control and Growth were higher in the evaluation of Family Effectiveness. The Control target was also higher in families with more than three people. The Coherence dimension had higher levels in families with health problems and whose income was less than $792.00 US dollars per month. In the Individuation dimension, income over $792.00 had better results. The Maintenance dimension of the system was higher in families whose drivers’ activity was as an intercity driver, as well as in the Stability target. In conclusion, the social factors such as schooling, income, diseases, type of worker activity in road transport, and number of people in the family influenced perceived stress and Family Effectiveness, which demonstrates the need to increase the promotion of health care of the families of road transport workers.

Despite copious research, the methods for assessing upper- and lower-limb motor coordination are limited. We devised a simplified evaluation method based on upper- and lower-limb motor coordination jumping and conducted a practical examination of the characteristics of the motion and applicability of the evaluation method. Overall, 88 high-school athletes with comparable competitive abilities were included in this study. The participants were divided into two groups based on their prior experience with motor coordination training (24 in the experienced group; 64 in the inexperienced group). First, a population proportion test was employed to assess the success rate of the four upper- and lower-limb motions in each task. This revealed significant difference between all tasks, except for the fourth motion, indicating that different motions have varying degrees of difficulty and that the combination of motions with differing difficulty coefficients can result in the creation of entirely new tasks with varying degrees of difficulty. Second, the experienced group demonstrated significantly superior performance compared to the inexperienced group by a t-test. These results confirmed that athletes (with the same level of competitive ability) trained in upper and lower limb motor coordination were able to excel in this evaluation method, confirming its validity.

The optical characteristics and electrical behavior of zinc oxide nanorods (ZnO-NR) and silver nanoparticles (Ag-NP) were investigated using advanced scanning probe microscopy and spectroscopy techniques. The study revealed that the ZnO nanorods have a length of about 350 nm, while the Ag nanoparticles are spherical with heights ranging from 5 to 14 nm. Measurements with Kelvin Probe Force Microscopy (KPFM) showed that the work functions of ZnO nanorods are approximately 4.55 eV, higher than that of bulk ZnO, and the work function of Ag nanoparticles ranges from 4.54 to 4.56 eV. The electrical characterization of ZnO nanorods, silver nanoparticles, and their hybrid was also conducted using conductive atomic force microscopy (C-AFM) to determine the local current-voltage (I-V) characteristics, which revealed a characteristic similar to that of a Schottky diode. The current-voltage characteristic curves of ZnO nanorods and Ag nanoparticles both show an increase in current at around 1V, and the hybrid ZnONRs/AgNP exhibits an increase in turn-on voltage at around 2.5 Volts. This suggests that the presence of Ag nanoparticles enhances the electrical properties of ZnO nanorods, improving charge carrier mobility and conduction mechanisms through a Schottky junction. The investigation also explored the optical properties of ZnO-NR, AgNP, and their hybrid, revealing absorption bands at 3.11 eV and 3.18 eV for ZnO-NR and AgNP, respectively. The hybrid material showed absorption at 3.13 eV, indicating enhanced absorption, and the presence of AgNP affected the optical properties of ZnO-NR, resulting in increased photoluminescence intensity and slightly changes in peak positions.

The use of individual protective covers (IPCs) to protect newly planted citrus trees from HLB infection is being widely adopted in Florida, an HLB endemic citrus producing area. It is known that IPCs positively influence most horticultural traits, increasing tree growth, flush expansion, and leaf size enabling trees to sustain a balanced carbohydrate metabolism by preventing CLas infection and induced higher leaf chlorophyll levels. This may result in more productive trees. However, as the tree grows IPCs eventually are removed, typically between 2 and 3 years after initial installation. Once IPCs are removed, trees become exposed to the ACPs and ultimately become infected. In this work we covered trees from Valencia sweet orange with IPCs for 30 months, until the trees entered fruit bearing age. We investigated how IPC protection of newly planted trees for 30 months influenced fruit quality and yield of ‘Valencia’ trees for three consecutive seasons after IPC removal compared to non-covered trees. The use of IPCs kick-started the newly planted citrus trees, resulting in more yield and fruits with better internal and external quality. After 30 months of IPC protection, tree canopies were larger and denser supporting more fruit per tree than in non-protected trees for three consecutive seasons even though by the end of the first season after IPC removal trees were HLB positive. Tree height, scion diameter, canopy volume, and leaf area were significantly improved as compared to non-covered trees. Additionally, fruit quality was significantly improved in the three seasons following IPC removal as compared to non-covered trees. However, a decline in quality was measurable in fruit from IPC trees after the second harvesting season, with trees affected by HLB. Based on the results from this study, we conclude that benefits from IPC protection may last for at least three consecutive seasons once trees enter the productive age despite CLas-infection within 12 months after IPC removal.

This paper proposes an unusual method for the dissemination of geological sciences and the promotion of geotourism: the scientific documentary, where a representative itinerary of geological and geomorphological evolution of this portion of the Apennines was presented. The considerations that led to the identification of the geological route proposed to the editorial staff of FOCUS TV are presented in detail. At each stop there was an explanation by academic professors and researchers, mainly from the Geology Division of the University of Camerino (MC), who explained in detail the outcrops. During the episode, insights were also given into the anthropogenic frequentation of the epigean caves in Frasassi (AN), ancient places of frequentation and worship thanks to their suggestiveness and the sense of sublime that they can elicit. In addition to the illustration of the individual stops, the article offers further insights into the geomorphology of the most important geosites depicted, all of which are in nature parks or protected areas and characterized by a high landscape value. The result was the production of an episode of the television program 'Geological Wonders of Italy: The Marche and Umbria Regions', which was broadcast in October 2022 by the Italian national Mediaset group.

The importance of diet shaping the gut microbiota is well known and may help with improving the overall health of an individual. Many other factors also have an influence, such as genetics, age, exercise, antibiotic therapy, or tobacco use. The purpose of this review is to summarize how three distinct dietary types (plant-based diet, Mediterranean diet, and Western diet) affect the composition of gut microbiota and the development of non-communicable diseases (NCDs). PubMed, Web of Science and Scopus databases were used for searching papers with an emphasis on keywords ‘‘dietary pattern’’, ‘‘gut microbiota’’ and ‘‘dysbiosis’’. Plant-based diet and Mediterranean diet promote the production of beneficial bacterial products, and more microbial diversity and therefore are generally considered healthy dietary types. On the other hand, the Western diet is a typical example of an unhealthy approach to nutrition which leads to an overgrowth of pathogenic bacteria. Moreover, understanding the impact of diet on the modulation of gut microbiota may give rise to new therapeutical strategies.

This study delves into the transformative growth of private higher education in China, highlighting the rapid and diverse expansion following the COVID-19 pandemic. Although previous studies have reported expansion and difficulties, a thorough examination of the relationship between institutional adaptation and the development of human capital remains unexplored. This study examines how private higher education institutions modify their job-related courses to suit the demands of the job market, evaluates the effect on the employability of graduates, and investigates ways to control costs without sacrificing academic quality. This study analyzes data from the Ministry of Education, Wind Information, and Shenwan Hongyuan Research to gain insights into the impact of human capital theory and institutional theory on private higher education in China. Enrollment trends, program alignment, financial sustainability, and quality enhancement activities are all examined using detailed analysis. Private higher education institutions play a critical role in developing a skilled labor force by filling skill gaps and meeting the demands of an evolving job market. The findings also emphasize the importance of quality assurance procedures, strategic program development, and collaborations with businesses. In conclusion, the study emphasizes the imperative for more research and policy action. This is crucial to securing the lasting effectiveness and influence of private higher education institutions on China's socioeconomic progress and human capital development in the post-pandemic era.

A favorable physical environment in the soil is necessary and of fundamental importance for the growth and root development of the sorghum crop, in order to maximize the productivity of the planted crops. In this study we evaluated the physical aspects of the soil in no-tillage system in a sorghum grain area intercropped with Urochloa ruziziensis and Crotalaria spectabilis and the productivity of the crop, in off-season (second crop season), based in a long field experiment. The experimental design was a randomized block design in a 4 x 4 factorial arrangement (four cropping systems: sorghum, sorghum + Urochloa ruziziensis, sorghum + Crotalaria spectabilis, sorghum + Urochloa ruziziensis + Crotalaria spectabilis; four soil depths: 0 - 0.10 m, 0.10 - 0.20 m, 0.20 - 0.30 m, 0.30 - 0.40 m). It was analyzed the productivity and the physical soil attributes that were: Soil Bulk Density (DS), Gravimetric Moisture (GM), Total Porosity (TP), Microporosity (MI), Macroporosity (MA) and Resistance to Root Penetration (RP). The study asserts that intercropping sorghum with Crotalaria spectabilis is a promising strategy to increase productivity. The Sorghum + Urochloa ruziziensis + Crotalaria spectabilis combination significantly improves soil structure by reducing penetration resistance and increasing macroporosity, especially at depths greater than 0.20 m. The inclusion of Urochloa enhances moisture retention, while Crotalaria contributes to greater porosity.