The current research investigates the effects of material and riblets on cavitation-induced erosion morphology, depth, and cross-sectional area through experimental approaches. To achieve these aims, the erosion of pure aluminum (1xxxAl or Al) and alpha brass (CuZn37 or CZ108) in the presence and absence of bio-inspired sawtooth riblets was examined after exposure to multiple collapses of single cavitation bubbles with a wall distance of 1.8. The results indicate that the erosion morphology resembles a rounded cone with a circular cross-section. Brass provides 21.6% more erosion resistance compared to Al in terms of material properties. Furthermore, the erosion for both Al (depth by 3.8% and width by 18.3%) and brass (depth by 7.9% and width by 27.4%) decreases in the presence of riblets compared to flat surfaces. The greater erosion resistance of brass compared to Al is attributed to the superior mechanical stability of brass, making it a potentially suitable alloy for propellers and hulls. In sum, the results reveal that riblet-provided materials with high mechanical durability are promising erosion-resistant materials for the shipping industry. However, the potential for chemical reactions in a cathodic environment should be addressed to provide a comprehensive perspective on reducing corrosion intensity.

Flexible electronics have revolutionized the field by overcoming the rigid limitations of traditional devices, offering superior flexibility and adaptability. Conductive ink performance is crucial, directly impacting the stability of flexible electronics. While metal filler-based inks exhibit excellent conductivity, they often lack mechanical stability. To address this challenge, we present a novel conductive ink utilizing a ternary composite filler system: liquid metal and two micron-sized silver morphologies (particles and flakes). We systematically investigated the influence of filler type, mass ratio, and sintering process parameters on the composite ink's conductivity and mechanical stability. Our results demonstrate that flexible wires fabricated with the liquid metal/micron silver particle/micron silver flake composite filler exhibit remarkable conductivity and exceptional bending stability. Interestingly, increasing the liquid metal content results in a trade-off, compromising conductivity while enhancing mechanical performance. After enduring 5000 bending cycles, the resistance change in wires formulated with a 4:1 mass ratio of micron silver particles to flakes is only half that of wires with a 1:1 ratio. This study further investigates the mechanism governing resistance variation during flexible wire bending. Additionally, we observed a positive correlation between sintering temperature and pressure with the conductivity of flexible wires. The significance of sintering parameters on conductivity follows a descending order: sintering temperature, sintering pressure, and sintering time. Finally, we demonstrate the practical application of this technology by integrating the composite ink-based flexible wires with conductive polymer-based strain sensors. This combination successfully achieved the detection of human movements, including finger and wrist bending.

In response to increasing urbanization and the need for infrastructure resilient to natural hazards, this study introduces an AI-driven predictive model designed to assess the risk of soil liquefaction. Utilizing advanced ensemble machine learning techniques, the model integrates geotechnical and geographical data to accurately predict the potential for soil liquefaction in urban areas, with a specific focus on Yokohama, Japan. This methodology leverages comprehensive datasets from geological surveys and seismic activity to enhance urban planning and infrastructure development in smart cities. The primary outputs include detailed soil liquefaction risk maps that are essential for effective urban risk management. These maps support urban planners and engineers in making informed decisions, prioritizing safety, and promoting sustainability. The model employs a robust combination of neural networks and gradient boosting decision trees to analyze and predict data points, assessing soil susceptibility to liquefaction during seismic events. Notably, the model achieves high accuracy in predicting soil classifications and N-values, which are critical for evaluating soil liquefaction risk. Validation against an extensive dataset from geotechnical surveys confirms the model’s practical effectiveness. Moreover, the results highlight the transformative potential of AI in enhancing geotechnical risk assessments and improving the resilience of urban areas against natural hazards.

It is of great academic significance to understand how the atomic structure of interfaces and boundaries in materials impacts the magnetic coupling nature across the boundaries and encourage development of state-of-the-art magnetic devices. Here, we carry out a systematic investigation of the atomic and electronic structures of twin boundaries (TBs) in LiFe5O8 thin films and determine their concurrent magnetic couplings using atomic-resolution transmission electron microscopy and atomistic first-principles calculations. The results show ferromagnetic or antiferromagnetic coupling can exist across the different TBs in LiFe5O8 (LFO) thin films and electrical structures within a few atomic layers directly rely on the TB atomic core structures. Uncovering one-to-one relationship between the magnetic properties of individual TB and the local atomic structures will clarify a thorough comprehension of numerous fascinating magnetic properties of commonly utilized magnetic materials, which will undoubtedly encourage the progress of sophisticated magnetic materials and devices.

The imperative to achieve carbon neutrality has driven significant advancements in the construction sector, particularly in the production and utilization of building materials. This paper explores innovative strategies and practices designed to reduce the carbon footprint of construction materials, with a focus on both the production processes and the application of sustainable materials. Key innovations include the development of low-carbon and carbon-negative materials, the integration of renewable energy sources in production, and the implementation of advanced recycling technologies. Case studies of successful projects demonstrate how these strategies can be applied in real-world scenarios, highlighting both the benefits and challenges encountered. The analysis also delves into the technical and economic aspects of these innovations, addressing the barriers to their widespread adoption and proposing solutions to overcome these challenges. Through a comprehensive examination of current practices and future trends, this paper aims to provide a roadmap for the construction industry to achieve carbon neutrality, contributing to broader climate change mitigation efforts and fostering a more sustainable built environment.

The research showsThis paperstudy presents a theoretical model of sustainable tourism in protected areas based on the experiences obtained in fromthrough field work carried out in the Machalilla national park. The units of analysis that compose it and their theoretical–-methodological foundation, and as well as the indications for their practical implementation in the face of the changes imposed by future tourism are exposed. Using the deductive method, the an analysis of the problem and the general theories linked to sustainable tourism in protected areas was carried out., the This involved establishingment of the premises and the developingment of the objectives to reach conclusions on the topic studied. A qualitative investigation is presented that allowed for the integration of contributions from the analyszes carried out for the treatment and processing of information. Among the results, the systematization of theoretical models linked to tourism in protected areas and, from a practical point of view, the application of a sustainable tourism model was were achieved. The results show the relevance of the proposed theoretical model that is proposed as a contribution to the scientific development of tourism. This model highlights, the systemic nature of its components from a new perspective of analysis, which considerings the need for changes as a development factor.

Tadpole shrimp (Triops longicaudatus) has become a major pest for California rice farmers. Currently, management relies solely on the insecticide lambda-cyhalothrin. However, resistance to this pyrethroid was confirmed in 2016, thus identifying an effective and practical biological control method for TPS is a priority. Field trials were conducted from 2017 to 2018 to: (1) evaluate the efficacy of the predatory fish Gambusia affinis and the predatory beetles, Laccophilus maculosus (Say) and Tropisternus lateralis (Fabricius), in controlling TPS, (2) test the efficacy of several inoculation rates of Gambusia affinis at controlling TPS and (3) to explore early indicators of TPS activity and damage as monitoring tools. Both Gambusia affinis and the predatory beetle treatments were not significantly different from the commercial standard (lambda-cyhalothrin). Both four and five Gambusia per 1 m2 controlled TPS as well as lambda-cyhalothrin, and we observed that Gambusia affinis was able to reproduce in the field. Water turbidity was significantly correlated with TPS counts (R = 0.85, N = 20, P < 0.0001 (2017); R = 0.58, N = 30, P = 0.0007 (2018)). The number of dislodged seedlings was less reliably correlated with TPS count; in 2017 correlations were significant (R = 0.84, N = 20, P < 0.0001), however, in 2018 correlations were not significant (R = 0.18, N = 30, P = 0.35). With further refinement water turbidity could play a valuable role in monitoring TPS populations.

We studied the dynamics of stable carbon (δ13C) and nitrogen (δ15N) isotopes in litters from Norway spruce (NSL) (Picea abies) and Scots pine (SPL) (Pinus silvestris) during in situ decomposition over a period of more than 4 years. Relative to initial values, δ13CNSL showed a weak enrichment (0.33‰), whereas δ13CSPL resulted in depletion (-0.74‰) at the end of decomposition. Both litter types experienced a depletion in δ15N during decomposition; δ15NNSL decreased by -1.74‰ and δ15NSPL decreased by -1.99‰. The effect of the selective preservation of or acid unhydrolyzable residue (AUR) in lowering δ13C of the residual litter was evident only in SPL. In the NSL, only in the initial stage C/N had a large effect on the δ13C values. In the later stages, there was a non-linear decrease in δ13CNSL with a simultaneous increase in AUR concentrations , but the effect size was large, suggesting the role of lignin in driving δ13C of residues in later stages. Depletion in 15N of the residual litters concomitant with the increase in N concentration suggests bacterial transformation of the litter over fungal components. A consistent decline in δ15N values further implies that bacterial dominance prompted this by immobilizing nitrate depleted in 15N in the residual litter.

In this work, to gain a complete understanding of quark color theory in the framework of complex octonionic space, we have derived the relationship between octonions and the SU(3)c color group. With the help of Feynman diagrams, we examined the octonionic interaction of color quarks (such as quark-quark, quark anti-quark, and anti-quarks anti-quarks interactions). For the interactions, we have obtained the octonion algebraic form of the interaction term, propagator, vertex factor, and color factor.

We present 4 cases of patients diagnosed with multiple myeloma initially treated without monoclonal antibodies. It was decided to provide the benefit of the drug after maintenance with lenalidomide was initiated to consolidate the post-maintenance response followed by monitoring without any kind of treatment. In this series of 4 cases 100% of the patients achieved a strict complete response with undetectable Minimal Residual Disease (MRD) for flow cytometry after post-maintenance consolidation with daratumumab regardless of the scheme used as induction/consolidation, as well as whether they had received HSCT. Until the last follow-up the patients are under surveillance with no evidence of progression. It should be noted that 3 of 4 of these patients debuted with high-risk disease.

Abstract: Patients with Cleft Lip Palate (CLP) require comprehensive treatment, so the people who take care of them must constantly provide care and support, along with continuous care and support from their caregivers, often extending until youth. The purpose was to compare the Quality of Life (QoL) of caregivers of children with CLP with those without the condition. A cross-sectional paired study was conducted at the Dental Clinic of the Escuela Nacional de Estudios Superiores (ENES León), National Autonomous University of Mexico (UNAM), from May to December 2021. Primary caregivers of patients with CLP (n=70) were included as well as those of the patients without CLP (n=70) of the same institution. Sample size was calculated considering an OR=2.5, establishing a convenience selection. Caregivers answered the WHOQoL Bref instrument to assess QoL. Of the total sample analyzed, 88.6% of the caregivers were female (p>0.05). Caregivers of patients with CLP reported poor QoL (64.8%), compared to caregivers in the control group (p

Understanding and preventing the “great obstetrical syndromes” has been the focus of pregnancy research for decades. The combined global impact from these syndromes on maternal and perinatal morbidity and mortality is compounded by increased long-term risk of adverse health effects following pregnancy. Accumulating evidence indicates that conditions such as pre-eclampsia, fetal growth restriction, spontaneous preterm labour, and stillbirth, are syndromes with etiologic heterogeneity that share common pathophysiologic pathways involving placental dysfunction. Recently, the importance of the interaction between fetal and maternal genomes has been extended to include the epigenetic impact of pre-existing maternal pathophysiology on placental development and highlights the importance of nutritional and environmental factors in altered placentation. Validated first-trimester screening algorithms for preeclampsia can identify high-risk women and prophylactic treatment with low-dose aspirin can be initiated. High-risk women can be monitored during the second trimester using clinical assessment, ultrasound, and biochemical markers, that are able to predict complications prior to the development of clinical signs and symptoms. The integration of lifestyle interventions, pregnancy screening, and medical management represents a conceptual advance in pregnancy care. This approach has the potential to significantly reduce pregnancy complications, maternal and perinatal morbidity and mortality, adverse health outcomes later in life, and health-care costs.

Abiotic stress is a significant factor restricting the normal growth and development of plants. Under abiotic stress, plants maintain their life and continuous growth by reconfiguring transcriptional regulation and metabolic networks. In recent years, with the development of sequencing technology and mass spectrometry technology, transcriptomics and metabolomics have emerged as new disciplines following genomics and proteomics, which are conducive to identifying metabolites and regulatory genes in plants under abiotic stress. In this review, we mainly analyzes the technical characteristics, advantages, and disadvantages of transcriptomics and metabolomics, focusing on reviewing the research progress in the field of plant responses to abiotic stress (temperature stress, salt stress, water stress, and heavy metal stress) using transcriptomics and metabolomics both domestically and internationally in recent years. It also provides a prospective view on current issues, which helps accelerate the understanding of the mechanisms of plant responses to abiotic stress and provides new ideas for breeding stress-resistant varieties in the future.

Rutin, a flavonoid compound found in various plants, has gained attention for its potential applications in the cosmetic industry due to its antioxidant, anti-inflammatory, and potential photoprotective properties. Our review explored the use of rutin (rutoside, 3-O-rutinoside-quercetin) in cosmetics/dermocosmetics, focusing on its physicochemical properties and stability, cutaneous permeability, and efficacy in sunscreen systems, involving in vitro tests and the current state of clinical trials. Rutin's ability to scavenge free radicals, prevent peroxidation, and reduce vascular fragility makes this flavonoid a promising ingredient for photoprotection. Studies have shown that rutin can enhance the sun protection factor (SPF) of sunscreen formulations, especially when combined with organic UV filters. The encapsulation of rutin in nanostructures has also been investigated to improve its applicability. Overall, rutin shows potential as a safe and effective ingredient in cosmetic/dermocosmetic formulations, offering protection against the harmful effects of UV radiation and oxidative stress on the skin.

Introduction: This population-based retrospective cohort study assesses rates of adverse events (AEs) involving cerebral thromboembolism (CTE) after COVID-19 vaccines. Methods: Data were collected from the U.S. Centers for Disease Control and Prevention (CDC) and Food and Drug Administration (FDA) Vaccine Adverse Event Reporting System (VAERS) database from January 1, 1990 to December 31, 2023. CTE AEs after COVID-19 vaccines were compared to those after influenza vaccines and after all other vaccines using proportional reporting ratio (PRR) analysis by time. Results: There are 5137 cerebral thromboembolism AEs reported in the 3 years (36 months) after COVID-19 vaccines compared to 52 AEs for the influenza vaccines over the past 34 years (408 months) and 282 AEs for all other vaccines (excluding COVID-19) over the past 34 years (408 months). The PRR’s are significant when comparing AEs by time from COVID-19 vaccines to that of the influenza vaccines (p < 0.0001) or to that of all other vaccines (p < 0.0001). The CTE AEs PRR by time (95% confidence intervals) for the COVID-19 vaccine AEs vs influenza AEs is 1120 (95% confidence interval (723-1730), p < 0.0001) and for COVID-19 vaccines vs all others is 207 (95% confidence interval (144-296), p < 0.0001). Cerebral venous thromboembolism AEs are female predominant with a female/male odds ratio of 1.63 (95% confidence interval (1.52-1.74), p < 0.0001). Conversely, cerebral arterial thromboembolism has a nonsignificant male preponderance. Cerebral venous thromboembolism is far more common than cerebral arterial thromboembolism over 36 months with an odds ratio (OR) of 14.8 (95% confidence interval 14.0-15.5, p < 0.0001). Atrial fibrillation, the most common identifiable cause of cerebral arterial thromboembolism, occurs far more commonly after the COVID-19 as compared to all other vaccines with a PRR of 123 (95% CI 88.3-172, p < 0.0001) Conclusions: There is an alarming breach in the safety signal threshold concerning cerebral thrombosis AEs after COVID-19 vaccines compared to that of the influenza vaccines and even when compared to that of all other vaccines. An immediate global moratorium on the use of COVID-19 vaccines is necessary with an absolute contraindication in women of reproductive age.

This paper presents a new proof of the infinite nature of prime numbers. Grounded in fundamental Set theory and Analysis, the proof uses the method of contradiction to demonstrate the absurdity of assuming the set of all prime numbers to be finite.

Acrylates and methacrylates are widely used, especially in the dental industry, but can cause adverse skin reactions. These compounds, including 2-hydroxyethyl methacrylate, triethylene glycol dimethacrylate, and bisphenol A-glycidyl methacrylate, are strong contact irritants or allergens. Found in dental prostheses, composite resins, dentin bonding materials, and glass ionomers, they pose a higher risk of exposure for dental personnel. Clinically, acrylate allergies manifest as facial rashes, eczema with cracked skin on fingers (pulpitis), nail dystrophy, and periungual dermatitis. Recently, the highest frequency of allergic reactions to acrylates has shifted from dentistry to the beauty industry due to increased use in artificial nails, eyelashes, and hair extensions. This has led to greater sensitization. Acrylates are also used in medical applications, such as bone cement for orthopedic endoprostheses, soft contact lenses, hearing aids, histological preparations, and wound dressings, which can also cause allergic reactions. Severe dermatitis from surgical glue containing acrylates has been documented, and diabetic medical devices are potential sources of allergic contact dermatitis. Given the extensive use and prolonged skin contact of products containing acrylates and methacrylates, this review aims to present current knowledge and literature on reactions to these compounds across different industries.

SETD7 is a member of the SET domain-containing lysine methyltransferase family and is a crucial component in the development and spread of a number of human cancers. However, the specific function of the SETD7 gene in ovarian cancer (OC) is still unclear. The purpose of this research was to elucidate the expression and role of SETD7 in OC. In comparison to normal controls, OC tissues (83%, 73/88) and cell lines exhibited higher protein levels of SETD7 (p < 0.001). High SETD7 protein levels were substantially correlated with M category (p = 0.019) and FIGO stage (p = 0.021). Furthermore, the high mRNA levels of SETD7 were correlated to poor progression-free survival (PFS) in all patients and serous patients with OC (p < 0.05). Importantly, the biological function experiments showed that SETD7 behaved as an oncogene in OC by dramatically facilitating the proliferation and migration of A2780 and SKOV3 cells. Additionally, SETD7 might promote cell migration via accelerating the EMT process in A2780 and SKOV3 cells. Our findings reveal that SETD7 may be a valuable molecular marker for identifying and anticipating the development of OC.

An 8-year-old, entire male, Domestic Shorthair cat was presented due to acute onset of dyspnoea/tachypnoea. Thoracic x-ray revealed presence of significant amount of bilateral pleural effusion. Fluid analysis indicated chylous effusion. The CT examination revealed many thoracic and abdominal abnormalities without a clear explanation for chylothorax. CT-lymphangiogram followed by surgical management were recommended. These options were declined by the owner due to high cost, however, a consent was given for attempt at percutaneous thoracic duct embolization. A percutaneous access to the cisterna chyli was successfully performed with an 18G vascular access needle via a right-sided sublumbar approach under ultrasound guidance. Subsequently, a 3F microcatheter and a 0.014-inch guidewire were introduced through the needle to canulate the thoracic duct. Thoracic duct lymphangiography was performed with 50:50 iohexol: 0.9% sodium chloride mixture revealing presence of dilated, tortuous and leaky cranial mediastinal lymphatics. Two helical microcoils were deployed within the caudal thoracic duct. Embolization of both the thoracic duct and the cisterna chyli was completed with mixture of n-butyl-2-cyanoacrylate: ethiodized oil mixture in 1:2 (glue-to-oil) ratio using a ‘pull-back’ technique. The cat recovered uneventfully from the procedure with immediate resolution of chylothorax. However, the patient continued to suffer from non-chylous pleural effusion.

This qualitative research explores the intricate relationship between cultural influences on supply chain practices and their implications for marketing strategies. Cultural dimensions such as individualism versus collectivism, uncertainty avoidance, and contextuality significantly shape decision-making processes, risk management strategies, and relationship dynamics within global supply chains. Through semi-structured interviews with supply chain managers, marketing executives, and cultural experts across diverse industries and regions, this study investigates how cultural values impact supply chain operations and consumer engagement strategies. Key findings highlight that collectivist cultures prioritize consensus-building and long-term relationships, fostering trust and collaboration among supply chain partners. In contrast, individualist cultures emphasize efficiency and accountability but may face challenges in relationship building. Risk management practices vary with cultural orientations towards uncertainty, influencing the adoption of structured versus flexible approaches to mitigate disruptions. In terms of marketing implications, the study underscores the importance of cultural sensitivity in crafting effective strategies. High-context cultures require marketing messages that resonate emotionally through implicit communication and cultural symbolism, while low-context cultures prefer clear, direct messaging focusing on product benefits. The study concludes by advocating for cultural competence as a strategic imperative for global businesses, enabling them to leverage cultural diversity for innovation and competitive advantage. It emphasizes the need for continuous adaptation to cultural nuances and market dynamics to foster inclusive collaboration and achieve sustainable growth in a globalized economy.

Consumer protection in the financial market has several dimensions. From a formal point of view, consumer rights are guaranteed by law. Market asymmetries are eliminated through the obligation to provide consumers with complete and objective information about financial products and services, honest marketing communication and professional sales practices. Programs are implemented in schools and the media to promote knowledge and responsible use of financial products and services. Despite the efforts made, the number of incorrect and suboptimal financial decisions is so high that the risk of households falling into excessive debt remains significant. The limited effectiveness of the law led to the claim that only effective education can reduce the risk of suboptimal financial decisions. Unfortunately, the efforts made in this area are not fully satisfactory. The aim of the article is to review scientific research on the financial knowledge of consumers in Central Europe and compare it to the results of a study conducted in Poland in January 2024. The results of the analysis could indicate the direction of further research on the possibilities of eliminating suboptimal financial decisions of consumers without limiting - for their better protection - access to financial products.

Dairy farming dates to the early Neolithic era in Europe, Middle East, Asia, and Africa. Over time, the industry has evolved from small ranches and farmhouses milk processing units to large, intensive dairy farms and big, high-tech processing units. Despite the industry’s contribution to the economy and food production, multiple studies have tainted cattle farming as a main contributor to climate change. This study explores literature in dairy farming and sustainable development goals (SDGs) to identify current scholarly developments since the formulation and adoption of SDGs in 2015 and themes for future research. This paper argues that dairy animals are not the source of sustainability shortfalls as depicted by multiple scholarly articles, but human processes associated with dairy farming. Data was analyzed using R package, Excel, NVIVO, and VoS Viewer. A review of literature shows that dairy farming and its contribution to sustainability has gained more intensive scientific interest since 2015. Moreover, livestock management, feed production and management, stakeholder’s management, logistics and supply chain management, and waste management are the sources of environmental adversities associated with dairy farming. Notably, these are human processes developed from commercialization of dairy farming and involve multiple stakeholders across the supply chain. While solutions are embedded within these processes, innovation emerges as a key driver of sustainability and source of opportunities to strengthen sustainability in dairy farming sector and achieve the sustainable development goals.

Storage, transmission and processing of data become a significant problem when large digital data files or databases are involved, as in the case of decentralized online global databases such as blockchain. Here we propose a novel method that allows the scalability of digital assets, including blockchain databases in the download, validation and confidentiality process, by developing a lightweight blockchain technology called Entropic Blockchain. This is a computer-implemented mathematical method to generate an information-entropic numerical representation of a digital asset, which can be utilized on its own, or as an optically machine-readable entropic barcode, for data secure transmission, processing, labelling, identification, one-way encryption and compression, validation, and digital tamper-proof check.

A feeding study was conducted to evaluate the different diets supplemented with vitamin solution effect on broodstock reproduction, growth performances, and the survival rates of larvae and fry of Pangasius catfish during over-spawning season. The experiment of broodstock cultivation was set up as a diet supplement design with six different diets consisting of vitamin solution, each diet fed to triplicate groups of fish, the stocking density of 10 broodstock fish (07 females and 03 males) per hapa net. Fish larvae and fry were reared in the hatchery for 45 days after hatching to evaluate growth performances and survival rates of fish fingerling. The growth and reproductive performances of breeders fed with different test diets showed that there were differences among the six tested diets (P < 0.05). The highest final body weight (FBW), weight gain (WG), daily weight gain (DWG), specific growth rate (SGR) of broodstock and survival rate of Pangasius fingerlings were found in Treatment 5, which contained 0.6% H-OVN for Pangasius Broodstock mixed with 12.6% algal oil and Treatment 3, which contained 0.6% vitamin premix H-OVN for Pangasius Broodstock compared to other Treatments. With these test diets, the Gonadosomatic index (GSI), relative fecundity index (RFI), fertilized egg, hatching rates of eggs, and survival rate of fingerling ranged between a 6.7–12.8%, 104,267–199,512 eggs/kg, 62.2–93.6%, 43.5–76.2%, and 45.3–66.3%, respectively (P < 0.05). The findings of this study showed that the diet containing 35% CP contents supplemented with 0.6% vitamin premix H-OVN mixed with algal oils showed the highest results in terms of growth, reproductive performance indices, and survival rates of Pangasius catfish fingerling.

It is unclear whether delayed access to treatment/health assessment impacted psychological distress for these populations. This study aimed to fill this literature gap by using a cross-sectional survey, which aimed to evaluate the impact of COVID-19 pandemic on Chinese immigrants in North America during the second wave of the pandemic. The study focused on Chinese immigrants aged 16 or older in Canada. Covariates included sociodemographic variables, delayed access to treatment/health assessment, and other COVID-19 related variables. We used logistic LASSO regression for model selection and multivariate logistic regression models to evaluate the association between delayed access to treatment/health assessment and psychological distress outcome. Missing data were handled using multiple imputation. Our study included 746 respondents, with 47.18% normal CPDI group and 36.82% mild to severe CPDI group. Most respondents were originally from Mainland China and residing in Ontario. Over half have stayed in Canada for at least 15 years. The multivariate logistic regression models unveiled a significantly positive association between psychological distress and delayed access to treatment/health assessment (OR=1.362, 95% CI: 1.078–1.720, p= 0.0095), fear of COVID-19 (OR=1.604, 95% CI: 1.293–1.989, p<.0001), social loneliness (OR=1.408, 95%CI: 1.314–1.508, p<.0001). Sociodemographic variables and other COVID-19 related-variates did not significantly impact the study’s outcome. Reliable health information, mental health supports, and virtual care tailored to immigrants should be considered to mitigate this impact and optimize overall health and well-being.

The Metaverse of Things (MoT) is an advanced technology that has the potential to revolutionise urban living in the present era. This article explores the advantages, uses, and transformative outcomes of MoT in smart cities. The covered subjects encompass sustainability, urban planning, citizen participation, infrastructure management, and various more. MoT integrates the Internet of Things (IoT) with metaverse technologies. The ultimate objective is to develop virtual environments that are highly interactive, interconnected, and immersive while maintaining a high level of fidelity to reality. The IoT utilises virtual reality (VR), augmented reality (AR), and other digital technologies to gather data, facilitate communication, and automate certain processes, thereby enhancing several elements of urban living. It is all a component of the metaverse. The IoT will bring about a profound transformation in the way cities gather and utilise data to enhance services and optimise efficiency. Cities that can efficiently distribute this data can enhance public safety, optimise energy usage, regulate traffic, and manage waste properly. MoT apps that utilise immersive technologies and the IoT can be used to generate more intelligent and captivating cityscapes. The implementation of MoT can greatly enhance the quality of life for residents of smart cities through improvements in transportation, healthcare, education, and community engagement. The study's author examined how smart cities utilise the IoT to enhance the daily experiences of their inhabitants. This study examines the technical structure, possible advantages, and difficulties of implementing MoT in urban settings, aiming to enhance the resilience, responsiveness, and adaptability of cities. The findings emphasise the importance of robust legislative frameworks, stringent security requirements, and well-developed infrastructure to facilitate the extensive use of MoT technology. These factors are crucial for establishing a highly interconnected and efficient urban environment.

This paper proposes a methodology for the development and its Verification and Validation(V&amp;V) of safety-rated software. The development methodology is based on the structured analysis and structured design methodology, which has been proven in the field of safety software development during long period. The suggested the development and the V&amp;V methodology additionally focuses on the quality attributes 3C+T (completeness, Correctness, Consistency and traceability), which are important criteria in IEC international standards. The software development life cycle is compiled from IEC international standardization, which are of the requirements analysis phase, design phase, implementation phase, testing phase, installation/commissioning phase, and operation &amp; maintenance phases. The activities of the development process method were defined from requirements analysis to implementation, and the activities of the verification and validation were defined to include the scope of the developer's activities and then to include the test phase, installation/commissioning phase, and operation phases additionally. In other words, testing phase performed by the developer was defined as informal testing, and testing performed by the verifier according to test criteria, test plans, and test procedures was defined as formal testing. According to proposed methodology, the requirements phase defines the sequence of Entity Relationship Diagram (ERD)-Context Diagram-Data Flow Diagram (DFD), functional decomposition process and defines operational scenario. In the design phase, module design such as task analysis and task allocation were defined. In the implementation phase, we listed the coding guidelines that must be followed for safety-related system. The test phase defined the test criteria, test plan, test procedure, and test result report activities. In the installation/commissioning and operation phases, recommendations for improving reliability, quality, and safety were proposed for deliverables such as user documentation and technical documentation.

This paper describes the proposal and development of a proof of concept (PoC) for a data logger system designed for operation and fault detection in bench testing of combustion engines. The main objective was to develop a data logger system that collects data on vibration, sound, temperature, and CO2 levels to identify ignition and combustion faults, thereby contributing to reducing greenhouse gas emissions (GHG). The paper presents (i) the proposal and development and (ii) the open-source code: proof of concept for a data logger system focused on detecting faults and monitoring the operational condition of benchtop combustion engines. The results indicate the feasibility of the PoC for data acquisition and dataset creation for Research and Development purposes.

This pilot randomized controlled trial (RCT) aimed to explore whether depression and anxiety could be reduced by psychiatric home healthcare supporters offering brief cognitive behavioral therapy for psychosis (CBTp) at home using a workbook for patients with schizophrenia. Eighteen patients with schizophrenia treated in a psychiatric home nursing service were randomly assigned to two groups: one group received CBTp in addition to usual care (CBTp + TAU group; n=8) and the other received only usual care (TAU group; n=8); 2 patients were excluded due to hospitalization or withdrawal of consent. Eight weekly CBTp sessions were conducted; anxiety/depression, quality of life, self-esteem, and overall functioning were assessed at baseline, week 9, and week 13. There was no significant difference in the primary evaluation; however, a significant improvement (p=0.014) was observed in the secondary evaluation of quality of life. The effect size was 0.95 for primary evaluation and 1.33 for the secondary evaluation, indicating a large effect. This study showed that nurses and occupational therapists can provide CBTp in psychiatric home care for patients with schizophrenia to potentially alleviate anxiety and depression compared to standard psychiatric home care alone. Therefore, larger RCTs with larger sample sizes are recommended.

Ghana, blessed with abundant solar resources and has strategically invested in solar photovoltaic (PV) technologies to diversify its energy mix and reduce the environmental impacts of traditional energy technologies. The 50 MW solar PV installation by the Bui Power Authority exemplifies the nation's dedication to utilizing clean energy for sustainable growth. This study seeks to close the knowledge gap by providing a detailed analysis of the system's performance under different weather conditions, particularly on days with abundant sunshine and those with cloudy skies. The research consists of one-year monitoring data of the climatic and AC energy output fed into the grid. This data was used to analyze PV performance on each month's sunniest and cloudiest days. The results show that the total amount of AC energy output fed into the grid each month on the sunniest day varies between 229.3 MWh in December and 278.0 MWh in November, while the total amount of AC energy output fed into the grid each month on the cloudiest day varies between16.1 MWh in August and 192.8 MWh in February. Also, the percentage variation in energy produced between the sunniest and cloudiest days within a month ranges from 16.9% (December) to 94.1% (August). The reference and system yield analysis showed that the PV plant has a high conversion efficiency of 91.3%; however, only the sunniest and overcast days had an efficiency of 38% and 92%, respectively. The BPA plant's performance can be enhanced by using this analysis to identify erratic power generation on sunny days and schedule timely maintenance to keep the plant's performance from deteriorating. Optimizing a solar PV system's design, installation, and operation can significantly improve its AC energy output, performance ratio, and capacity factor on sunny and cloudy days.

Self-sustained learning (SSL) is considered a crucial factor in promoting students’ long-term learning and development in a sustainable society. To deepen the understanding of SSL, especially in the context of learning English as a second language, the current study examined the influence of intercultural communicative skills, language mindset, and positive L2 self on SSL in English learning among 1,238 college students in China. The results showed that students not only had a strong language mindset, positive L2 self, and intercultural communicative skills but also scored higher in long-term self-sustained English learning. Findings from the Structural Equation Modeling indicated that both language mindset and intercultural communicative skills positively predicted positive L2 self and self-sustained English learning. Furthermore, language mindset and intercultural communicative skills had an indirect impact on self-sustained English learning through positive L2 self. These findings suggest that to promote English learners’ SSL, instructors should help facilitate students’ intercultural communicative skills and foster a growth language mindset, as well as positive language learning beliefs.

As the digital transformation accelerates in our society, open data is being increasingly recognized as a key resource for digital innovation in the public sector. This study explores the following two research questions: 1) Can a machine learning approach be appropriately used for measuring and evaluating open data utilization? 2) Should different machine learning models be applied for measuring open data utilization depending on open data attributes (field and usage type)? This study used single-model (Random Forest, XGBoost, LightGBM, CatBoost) and multi-model (Stacking Ensemble) machine learning methods. A key finding is that the best-performing models differed depending on open data attributes (field and type of use). The applicability of the machine learning approach for measuring and evaluating open data utilization in advance was also confirmed. This study contributes to open data utilization and to the application of its intrinsic value to society.

Brazil became a major player in the global beef market, after the market liberalization in the 1990’s, and experiencing a substantial development. Nonetheless, the environmental impact of beef production associated with land use and greenhouse gas emissions has been under discussion. The necessity of increased adoption of sustainable technologies, however, may preclude some farmers to keep up to date with technological advances. This article describes the major historical changes in beef farming and how they have been shifting production systems toward a sustainable intensification of grass-fed beef, with likely impacts for farmers. We combined an extensive literature review, public data and our own insights, as senior researchers, to achieve that. The trajectory shown here evidenced the substantial technological development underway in Brazilian beef farming, with strong support of public policies for decarbonizing agriculture. Nonetheless, the pace of this sustainable transition may affect small to medium farmers unable to cope. Our recommendations, therefore, involve a broad program of technical assistance and training on sustainable technologies and other supportive practices, including financial and digital literacy. Additionally, we suggest an alternative credit system, with progressive borrowing allowances to ensure financial resources to support a sustainable and inclusive transition of Brazilian beef farming.

COVID-19 infection is extremely dangerous for persons with comorbidities such as kidney disease and diabetes. Although many people of all ages and socioeconomic backgrounds have suffered due to this pandemic, those with underlying medical conditions like kidney disease and diabetes are more vulnerable to becoming infected with COVID-19 related to weak immunity. However, the role of vaccination in the co-infection of COVID-19 with diabetics is not available in the literature. Therefore, we examine the unique challenges presented by the co-infection of COVID-19 in individuals with diabetes, focusing on its disease transmission dynamics. A mathematical modelling technique is to be employed in this work to analyse the dynamics of COVID-19 outbreaks with seven compartments, including vaccination with comorbidities such as diabetes. We also investigated analytically by displaying the solutions' existence, boundedness, positivity and sensitivity. After calculating the basic reproduction numbers, the stability analysis of model equilibrium points is also covered. If the reproduction numbers are less than unity, the disease-free equilibrium points of the model appear to be both locally and globally stable. The findings of this study are that as the vaccination rate rises, the incidence of COVID-19 and its co-infections with diabetes decreases. Effective disease treatment strategies may be based partly on the possible impact of vaccination on the co-infection of COVID-19 related to diabetic disease insights.

In this paper glass crystallization behavior of 50ZnO:47B2O3:3Nb2O3:0.5Eu2O3 (G-0h) glass has been investigated in detail by DSC, XRD and TEM analysis. The luminescent properties of resulted glass-ceramics were also investigated. By XRD and TEM analysis crystallization of several crystalline phases have been proved (α-Zn3B2O6, β-Zn3B2O6 and ZnNb2O6). By calculating of crystal parameters it was found that europium ions are successfully incorporated in the β-Zn3B2O6. Photo-luminescent spectra show an increased emission in the resulting glass-ceramic samples as compared with the parent glass sample because of the higher asymmetry of Eu3+ ions in the crystalline phases obtained. It was established that the optimum emission intensity is registered for glass-ceramic sample obtained after 25 hours heat treatment of the parent glass.

Tuberculosis (TB) is an infectious disease declared a global emergency by the World Health Organization and continues as one of the world’s top ten causes of death. TB diagnosis is more critical in developing countries where demanded infrastructure for detection, and treatment complicates the efforts against the disease. These aspects related to limited resources are significant, especially in areas away from the main cities, with few mechanisms to make a timely diagnosis that contributes to successfully addressing the possible patients. Artificial intelligence has begun to be essential in providing additional strategies in the diagnosis processes for health professionals’ support. This paper uses natural language processing (NLP) and machine learning (ML) techniques to create models that can supply TB diagnosis when the needed infrastructure is unavailable. Two different sources were explored: text extracted from electronic medical records (EMR) and patient clinical data (CD). Four proposals using five different machine learning models were implemented. The first two models employed ML and each data source independently. Then, two additional approaches developed a data fusion from both sources. This strategy’s employment was analyzed with physicians according to their pertinence in the process and understanding of the EMR. Finally, the results of the data fusion were compared to each source, obtaining better performance at using only the CD, where an area under the ROC curve of 69.9±2.3% was obtained. However, the advantage of analyzing physician’s reports is the availability of this information contrasted to clinical-specific data, which can be more useful in places far from the main cities without enough basic structure for its obtaining.

Ship detection from synthetic aperture radar (SAR) imagery is crucial for various fields in real-world applications. Numerous deep learning-based detectors have been investigated for SAR ship detection, which require a substantial amount of labeled data for training. However, SAR data annotation is time-consuming and demands specialized expertise, resulting in that deep learning-based SAR ship detectors struggle due to a lack of annotations. With limited labeled data, semi-supervised learning is a popular approach for boosting detection performance by excavating valuable information from unlabeled data. In this paper, a semi-supervised SAR ship detection network is proposed, termed as Multi-Teacher Dempster-Shafer Evidence Fusion Net-work (MTDSEFN). The MTDSEFN is an enhanced framework based on the basic teacher-student skeleton frame, comprising two branches: the Teacher Group (TG) and the Agency Teacher (AT). The TG utilizes multiple teachers to generate pseudo-labels for different augmentation versions of unlabeled samples, which are then refined to obtain high-quality pseudo-labels by using Dempster-Shafer (D-S) fusion. The AT not only serves to deliver weights of its own teacher to the TG at the end of each epoch, but also updates its own weights after each iteration, enabling the model to effectively learn rich information from unlabeled data. The combination of TG and AT guarantees both reliable pseudo-label generation and learning comprehensive diversity information from numerous unlabeled samples. Extensive experiments were performed on two public SAR ship datasets, and the results demonstrated the effectiveness and superiority of the proposed approach.

Coastal environments are complex systems that are influenced by a combination of natural processes and human activities. Scientific interest in the effects of coastal erosion/accretion and climatic change-related processes greatly increased in recent decades due to the growing human development along coastal areas. This paper investigates the state and evolution of beach-dune systems for the 1977-2001 and 2001-2019 periods of the Mediterranean coast of Andalusia (Spain) using two different proxies: the dune toe line, which was used to track foredunes evolution, and the high-water line, which was used to assess shoreline evolution. Results showed a general erosional behavior of the studied beach-dune systems and identified cases where the main trend was altered through human interventions. In the 1977-2001 period, 54% of foredunes showed erosion, 24% accretion and 22% stability while and 34% of shorelines showed erosion, 40% accretion and 34% stability. In the 2001-2019 period, 42% of foredunes showed erosion, 28% accretion and 30% stability, and 40% of shorelines showed erosion, 34% accretion and 26% stability. Combining the evolution classes of each proxy (dune toe/shoreline) allows the behavior of both shoreline proxies to be assed together and provides insights additional to those derive from the use of a single proxy. In this regard, Erosion/Erosion (EE) was the most frequent behavior, with 25% and 27% in the first and second periods respectively, and Accretion/Accretion (AA), with 17% in both periods. Erosion of foredunes combined with stability or accretion of the shoreline (ES and EA) were the most common pairings in the first period, while stability of dunes combined with accretion of the shoreline (SA) and Stability/Stability (SS) dominated in the second period. The results obtained provide additional insights on the nature and drivers of coastal change that aid local coastal managers and administrations in understanding erosion processes. The method can be applied at other areas around the world where a similar data base is available.

Clematis Florida (CF) is a folk medicinal herb in the southeast of China, which is traditionally used for treating osteoarticular diseases. However, the mechanism of action remains unclear. The present study used network pharmacology and experimental validation to explore the mechanism of CF in the treatment of rheumatoid arthritis (RA). Liquid chromatography-mass spectrometry (LC-MS/MS) identified 50 main compounds of CF, then the targets of them were obtained from TCMSP, ETCM, ITCM and Swiss TargetPrediction databases. RA disease related targets were obtained from DisGenet, OMIM and GeneCards databases. 99 overlapped targets were obtained using Venn diagram. The protein-protein interaction network (PPI)、the compound-target network (CT) and the compound-potential target genes-signaling pathways network (CPS) were built and analyzed. The results showed that the core compounds were screened as oleanolic acid, oleic acid, ferulic acid, caffeic acid, and syringic acid. And the core therapeutic targets were identified as PTGS2 (COX-2), MAPK1, NF-κB1, TNF, RELA by network pharmacology analysis, which belong to the MAPK signaling pathway and NF-κB signaling pathway. The animal experiments indicated that topical application of CF showed significant anti-inflammatory activity in mice model of xylene-induced ear edema and strong analgesic effect on acetic acid-induced withing. Furthermore, in the rat model of adjuvant arthritis (AA), topical administration of CF could alleviate toe swelling and ameliorate joint damage. The elevation of serum content of IL-6, COX-2, TNF-α, IL-1β, and RF caused by adjuvant arthritis were reduced by CF treatment. Western blotting tests showed that CF may exert regulation on the ERK and NF-κB pathway. The results provided a new perspective for the topical application of CF on RA.

Deuterium is a heavy nonradioactive isotope of hydrogen, having a neutron as well as a proton, making it twice as heavy. It is a natural element, present at 156 parts per million in seawater. The ATPase pumps in the mitochondria utilize proton motive force to drive ATP synthesis, and deuterons damage the pumps, producing a stutter that can cause reactive oxygen release and inefficiencies in ATP synthesis. Cellular metabolism incorporates several novel mechanisms to assure low deuterium content in the mitochondria and other organelles. Nicotinamide adenine dinucleotide (NAD) is a major carrier of deuterium depleted (deupleted) protons to supply the mitochondria. Many enzymes, especially flavoproteins, are able to use proton tunneling to fractionate out deuterium. In this paper, we argue that the amino acid proline is able to trap and sequester deuterium, and that peptidyl prolyl isomerases (PPIases) play a central role in facilitating deuterium trapping in proline-rich proteins, most notably collagen. The endothelial glycocalyx also sequesters deuterium in gelled water lining the blood vessels, creating a battery and promoting low deuterium in the circulation. Excess deuterium promotes cancer growth, and cancer cells release large quantities of lactate via aerobic glycolysis to help reverse deuterium overload, systemically.

Even with 100% certainty of a complete cure for breast cancer (BC), there is still a long way to go toward more efficient treatment. This requires sensitive and timely detection and accurate pre/post-clinical characterizations. Despite the availability of advanced diagnostic tools, many cancer patients lack access to efficient diagnostics that are both highly reliable and affordable. The fluorescence-based optical technique aims to make another significant leap forward in improving patient safety. It offers a convenient operation that reduces healthcare costs compared to visual examination tools (VETs). The primary and metastatic stages of BC consider different cancerous cell lines (MDAs), meaning the highest number of cells in this research (up to 300,000) represents the metastatic stages of BC, and 50,000 represents the primary level of BC developments have been studied based on fluorescence-enhanced photodynamic characterizations. The ability to characterize the fluorescence caused by MDA with 50,000 cells compared to the dominant radiation of MDA with 300,000 cells is emphatic proof of the high potential of fluorescence technique in timely BC detections, specifically before it spreads to the axillary lymph nodes. The specific cell numbers of 50,000 and 300,000 were chosen arbitrarily based on the cultivation of common biological limitations. Comparing the outcomes between 50,000 and 300,000 cells allows for evaluating the fluorescence technique’s diagnostic capability across various stages of breast cancer. This assessment provides valuable insights into the effectiveness of the fluorescence-based characterizing approach in detecting cancerous cells at different stages of the disease. Here, we have assessed fluorescence’s spectral shift and intensity difference as a diagnostic approach to distinguish between cancerous and normal breast cells. This study also presents a two-way structure of the 5-aminolevulinic acid (5-ALA) prodrug and Fluorescein Sodium (FS) effect in BC cell characterization from the perspective of photodynamical procedures and the detection side. 5-ALA induces an accumulation of protoporphyrin IX (PpIX) photosensitizer through a biosynthetic pathway, leading to red radiation of fluorescence measurements depending on different factors, such as temperature, incubation time, added glucose of the culturing medium, as well as photosynthesis processes. The presence and progression of breast cancer can be indicated by elevated levels of Reactive Oxygen Species (ROS), which are associated with the production of PpIX in cells following the administration of 5-ALA. Also, nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FAD) fluorophores are recognized as the main factors for fluorescence emissions at around 420-580 nm emission intervals. Considering the MDA’s high metastatic potential, the impact of 5-ALA on MDA’s cellular morphology and viability has been investigated. The molecular fluorophores are the primary probes to MDA’s cellular photodynamic considerations, allowing this widespread pre/post-clinical approach. The fluorescence signal reduction due to decreased cell viability and increased MDA’s cellular death rate after 24 hours of the 5-ALA-induced staining corresponds to the changes in lipid metabolism enzymes of MDAs cultured at different doses, which could be known as a cell death inducer function. Furthermore, statistical concerns have been studied using PCA multivariate component analysis to differentiate MDA cell lines administrated by 5-ALA.

Severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) continues to be a global threat due to its ability to evolve and generate new subvariants, leading to new waves of infection. Additionally, other coronaviruses like Middle East respiratory syndrome coronavirus (MERS-CoV, formerly known as hCoV-EMC) which first emerged in 2012, persists and continues to present a threat of severe illness to humans. The continued identification of novel coronaviruses, coupled with the potential for genetic recombination between different strains, raises the possibility of new coronavirus clades of global concern emerging. As a result, there is a pressing need for pan-CoV therapeutic drugs and vaccines. After extensive optimization of an HCV protease inhibitor screening hit, a novel 3CLPro inhibitor (MK-7845) was discovered and subsequently profiled. MK-7845 exhibited nanomolar in vitro potency with broad spectrum activity against a panel of clinical SARS-CoV-2 subvariants and MERS-CoV. Furthermore, when administered orally, MK-7845 demonstrated a notable reduction of viral burdens by &gt;6 log orders in the lungs of transgenic mice infected with SARS-CoV-2 (K18-hACE2 mice) and MERS-CoV (K18-hDDP4 mice).

Rice has become the second major food among rural people. It is one of the most nutrient and low-cost food available in Asia. Rice is composed of two major subspecies as Japonica and Indica and it belongs to the Poaceae family. The World Bank predicts that rice demand will grow 51% faster than population growth in 2025. It is high time to develop a model which predicts the type of infected paddy leaf and avoids the loss of grains. In this paper, the proposed hybrid CNN model, three CNN networks with different layer properties are trained parallel. The extracted feature from these CNN networks is combined to provide the classification of the type of infected leaf. Fieldwork was carried and about 340 samples are collected from five different types of classes. The proposed hybrid model was tested with both the fieldwork dataset and also with an available dataset on the internet. The experimental results show that the proposed model outperforms the other CNN network and yields an accuracy value of 98%, a precision value of 95%, and a misclassification rate of 4% respectively.

Underwater imaging presents unique challenges, notably color distortions and reduced contrast due to light attenuation and scattering. Most underwater image enhancement methods, first use linear transformations for color compensation and then enhance the image. We observed that linear transformation for color compensation is not suitable for certain images. For such images, a non-linear mapping is a better choice. Our paper introduces a unique underwater image restoration approach leveraging a streamlined convolutional neural network (CNN) for dynamic weight learning for linear and non-linear mapping. In the first phase, a classifier is applied that classifies the input images into Type-I or Type-II. In the second phase, depending on the classification, the Deep Line Model (DLM) for Type-I images or the Deep Curve Model (DCM) for Type-II images. For mapping an input image to an output image, DML creatively combines color compensation and contrast adjustment in a single step and uses deep lines for transformation, whereas DCM employs higher-order curves. Both models utilize lightweight neural networks that learn per-pixel dynamic weights based on the input image’s characteristics. Comprehensive evaluations on benchmark datasets using metrics like peak signal-to-noise ratio(PSNR) and root mean squares error (RMSE) affirm our method’s effectiveness in accurately restoring underwater images, outperforming existing techniques.

This study is based on the BP neural network regression model optimised by genetic algorithm and dedicated to predicting the amount of car purchase, this study is important for all parties in the automotive industry. By plotting the violins of six indicators, including gender, age, annual salary, credit card debt, net worth, and car purchase amount, we found that, except for gender, the other data showed a trend of dense in the middle gradually decreasing to the upper and lower sides, with an overall normal distribution. The correlation analysis shows that the amount of car purchase has a high positive correlation with age (0.63), followed by annual income (0.62), the correlation between net worth and the amount of car purchase is 0.49, while the correlation between credit card debt and the amount of car purchase is low (0.03). In the experimental part, we analyse the predicted-actual values of the training and test sets in comparison and find that the model predicted values are very close to the actual values. The RMSE of the training set is 11.559 and the RMSE of the test set is 11.4835, which is not much different from each other, indicating that the model has good generalisation ability. In addition, the R2 of both the training and test sets is 1, indicating that the model fits well. The MAE of the training set is 8.2512 and the MAE of the test set is 9.578; the MBE of the training set is -4.3035 and the MBE of the test set is -2.4547.These metrics indicate that the model performs well in predicting the amount of car purchase. In conclusion, this study provides an effective and reliable method to predict the amount of car purchase, creating a useful bridge between car manufacturers, dealers and consumers.

The demand for a more sustainable agriculture, coupled with the need for optimized crop productivity, has driven the use of microorganisms for the biocontrol of diseases and pests, as well as for growth promotion. The use of plant growth-promoting rhizobacteria (PGPR) and plant growth-promoting fungi (PGPF) in Brazilian production systems has become increasingly common, with the number of microbial inoculant registrations in the country growing every year. PGPR and PGPF occupy various niches in the rhizosphere, playing a crucial role in soil nutrient cycling, as well as influencing various plant physiological processes. In this review, we address the main mechanisms used by these microbial agents in growth promotion and the use of strain co-inoculation as a strategy to enhance the efficacy of these products. Subsequently, we conduct an analysis of the available inoculants in Brazil, detailing the microorganisms available for the main Brazilian crops, and the prospects of this market regarding research and development of new products for the coming years based on the current challenges faced.

Transcranial magnetic stimulation (TMS) represents a distinctive technique for non-invasive brain stimulation. Recent advancements in image processing have enabled the enhancement of TMS by integrating magnetic resonance imaging (MRI) modalities with TMS via a neuronavigation system. The aim of this study is to assess the efficacy of navigated TMS for cortical mapping in comparison to surgical mapping using direct electrical stimulation (DES). The study involved 30 neurosurgical procedures for tumors located in or adjacent to the precentral gyrus. The DES points were compared with TMS responses based on the original distances of vectorial modules. There was a notable similarity in the points obtained from the two mapping methods. The distances between the geometric centers of TMS and DCS were 4.85 ± 1.89 mm. A strong correlation was identified between these vectorial points (r = 0.901, p < 0.001). The motor threshold in TMS was highest in the motor cortex adjacent to the tumor compared to the normal cortex (p < 0.001). Patients with deficits exhibited excellent accuracy in both methods. In view of this, TMS demonstrated reliable and precise application in brain mapping, which is a promising method for preoperative functional mapping in motor cortex tumor surgery.

A one-pot, one-step protocol combining hydrogen transfer initiated dehydration (HTID) of 1,3-propanediol (1,3-PDO), catalysed by [Cp*IrCl2(NHC)] (Cp* = pentamethylcyclopentadienyl; NHC = carbene ligand) complexes (1-5H and 1-3F), and self-aldol condensation (SAC) of propanal (2), allowed selective production of aldehyde 2-methyl-pent-2-enal (3), in ionic liquids with high substrate conversion. The Ir(III) pre-catalysts, and the ionic liquids, were recyclable. 3 could also be selectively produced in the presence of water, and in neat 1,3-PDO. The efficient, selective delivery of a value-added chemical from 1,3-PDO, a major product of many whole cell bacterial fermentation processes, shows that the combination of chemo-catalytic processing of the chemical platform via Cp*IrCl2(NHC) - catalysed HTID / SAC with bio-catalysis has the potential to allow direct valorisation of the bio-renewable feedstocks, such as waste glycerol and sugars, into valuable chemicals.

Signal preprocessing and feature extraction are two important and necessary steps of data analysis. In signal analysis, typically these two steps are implemented through multiple algorithms. Moreover, the significant parameters in most algorithms are set empirically. We have developed an algorithm that can preserve and highlight characteristic waveforms while attenuating non-feature waveforms. The parameters in the algorithm are set through difference analysis. We have conducted experiments on both clinical and open-source ECG data, obtaining effective test results.

Springs play a significant role in maintaining hydrological balance in the mountain ecosystem. The communities living in the mountain tops rely entirely on spring water for their daily needs. In recent decades, spring water discharges have decreased drastically in the Himalayan regions and become seasonal. Remote sensing and geographical information system techniques have proved to be essential for understanding the sustainable development of groundwater, particularly where people rely solely on spring water in the mountainous regions of the Himalayas. This study employs the Analytical Hierarchy Process (AHP) to identify groundwater potential zones. It involves overlaying seven thematic layers concerning elements of physical features and land-use/land-cover of the region, using the weighted overlay toolbox in ArcGIS, with each layer being assigned a weight based on its importance. Based on the results, groundwater potential zones have been classified into five categories: poor, fair, good, very good, and excellent. The study found that poor groundwater potential zones cover 1.1% of the area, fair zones cover 27.8%, good zones cover 23.3%, very good zones cover 26.6%, and excellent zones cover 21.2% of the total area. The excellent to very good potential zones are associated with perennial springs that have higher discharge (4.30-30.92 l/m), lineaments, rainfall, forested land, and porous soils, favoring the potentiality of the springs. The fair and poor groundwater potential zones are associated with seasonal flowing springs, consisting of barren land, less rainfall, and low fracture density are influencing the potentiality groundwater. The validation of the groundwater potential zones indicated an Area Under Curve (AUC) value of 0.88, which shows good agreement with observed spring water locations. The identified groundwater potential zones are valuable for prioritizing the area for the sustainable development of spring water. Particularly, it is helpful for the stakeholder departments to involved in developing strategies for sustainable water management at the micro-watershed level and safeguarding spring water resources using integrated watershed management.

Microneedle technology is a novel platform technology that revolutionizes ocular drug delivery and addresses critical challenges in the treatment of ocular diseases. Routine treatment methods, such as eye drops and intravitreal injections, suffer from low bioavailability and poor patient compliance. So, novel advanced platform technologies are required to overcome these challenges. Microneedle is a minimally invasive and promising alternative technique that helps precisely control drug delivery to targeted tissues and organs. This review investigates the potential impact of microneedle technology for eye care, underscoring recent advancements, underlying mechanisms, and emerging preclinical and clinical uses. Different types of microneedles, including solid, coated, dissolvable, and hollow, have demonstrated their potential and capability to bypass several barriers in the cornea and sclera. This ensures effective drug penetration and delivery. The current innovations in material science and fabrication methods have enhanced the safety and efficacy of microneedles, reducing discomfort and the chances of infections. These microneedle technologies offer sustained and controlled drug delivery, which could improve therapeutic outcomes for various disease conditions like age-related macular degeneration, glaucoma, diabetic neuropathy, etc. In the current review, recent preclinical and clinical studies emphasize microneedle-based ocular drug delivery's feasibility and potential benefits. These include improved pharmacokinetics, reduced dosing frequency, enhanced patient adherence, and, most importantly, microneedles offer versatile platforms for delivering a wide range of small and large molecules and gene therapies. Despite the exciting progress, obstacles such as regulatory barriers, scalability, and long-term biocompatibility persist. It will be essential to tackle these challenges through interdisciplinary research and partnerships to integrate microneedle technology into standard clinical use effectively. Ultimately, microneedle drug delivery offers a revolutionary method that has the potential to significantly enhance the treatment and results of ocular diseases, marking the dawn of a new era in eye care.

This study explores the barriers to adopting green supply chain practices from the perspective of industry leaders. By conducting qualitative interviews with key decision-makers in various sectors, the research uncovers the complexities and challenges faced in integrating sustainable practices into supply chain operations. The findings highlight significant obstacles such as cost implications, lack of regulatory support, technological limitations, and resistance to change within organizations. Additionally, the study reveals that while there is a growing awareness and commitment towards sustainability, practical implementation remains fraught with difficulties. The insights gained from industry leaders provide a nuanced understanding of the multifaceted nature of these barriers, offering valuable guidance for businesses and policymakers aiming to promote greener supply chains.

Pump-as-turbines (PAT) have been widely used during the last decade as one of the most interesting technologies in the field of energy recovery. A large number of studies and papers have been published in which the performance of the pumps in the turbine operating regime are analysed. Since horizontal single stage centrifugal norm pumps are most commonly used as PATs, their performances are analysed in this paper. Most of the research was related to individual pump aggregates or smaller groups and to obtaining their performance curves in turbine random mode. In this work, extensive experimental, numerical and theoretical investigations are conducted to obtain complete dimensionless performance characteristics of the single stage centrifugal norm pumps operating as turbines. The main goal of this research was to form a simple analytical expression that will, for this type of aggregate, map the pump operating characteristic to the appropriate turbine operating regime. By using the expressions obtained and presented in the work, engineers are enabled to make the appropriate choice of pump aggregate for operation in the turbine random mode for potential locations. This can allow us to quickly make selection of potential locations and to carry out appropriate techno-economic analyses and analyses of possible energy savings.

Mucus plugging of the respiratory tract occurs in airway diseases, including asthma, chronic obstructive pulmonary disease and cystic fibrosis. It can cause blockage of airways, leading to breathlessness and lung failure. Here, we demonstrate the effect of BromAc® in dissolving mucus plugs in an novel ex-vivo ovine obstructive lung model using a ventilatory setup. Mucus simulant was filled into the trachea of freshly slaughtered ovine lungs and ventilated via an endotracheal tube (ETT) using Continuous Mandatory Ventilation. Predetermined single or repeated doses of Bromelain, Acetylcysteine (Ac), BromAc® and saline control were administered via an Aerogen® vibrating nebuliser and ventilated for 30 or 60 minutes. Ventilatory recording of resistance, compliance, tidal volume was conducted and rheology pre and post treatment were measured. A significant decline in airway resistance (p&lt;0.0001) compared to saline control was observed when treated with Bromelain, Ac and BromAc®, with the latter showing a stronger mucolytic effect than single agents. The decline in resistance was also effective in shorter timepoint (p&lt;0.05) at lower doses of the drugs. Changes in compliance, peak pressure and tidal volume was not observed post-administration of the drugs. Rheology measurements revealed that BromAc®™ significantly reduced the viscosity of the mucin at the end of 30-minute and 60-minute time points (p&lt;0.001) compared to the saline control. BromAc® showed complete dissolution of the respiratory mucus simulant and improved ventilatory airflow parameters in the ex-vivo ovine model.

Bacillus subtilis is a model organism used to study molecular processes in Gram-positive bacteria. Sigma factor B, which associates with RNA polymerase, is one of the transcriptional regulators involved in the cell’s response to environmental stress. Experiments have proven that the amounts of free σB (SigB) are controlled by a system of anti- (RsbW) and anti-anti-sigma (RsbV) factors expressed from the same operon as SigB. Moreover, the phosphorylation state of RsbV is controlled by phosphatases RsbP and RsbU, which directly dephosphorylates RsbV. A set of chemical equations describing the network controlling the levels of free SigB was converted to a set of differential equations quantifying the dynamics of the network. The solution of these equations allowed the simulation of the kinetic behavior of the network and its components under real conditions. In this study, the time series of protein expression measured by mass spectrometry were utilized to investigate the role of the phosphatases RsbU/RsbP in transmitting the environmental signal. Additionally, the influence of kinetic constants and the amounts of other network components on the functioning of the network was investigated. A comparison with the same simulation performed using transcriptomic dataset showed that while the time series between the proteomic and transcriptomic datasets) are not correlated, the results are the same. This indicates that when modeling is done within one dataset, it does not matter whether the data come from the mRNA or protein level. In summary, the computational results based on experimental data provide quantitative insight into the functioning of the SigB-dependent circuit and offer a template for the quantitative study of similar systems.

Increased norepinephrine (NE) release from the sympathetic nerves during pregnancy in women or animal models, as occurs during stress, modifies the fetal environment and increases flow of NE to the fetus, programing the progeny and affecting its cardiovascular and metabolic function in adulthood. In the present work, gestating rats were exposed to stress during gestation and the female progeny was analyzed for heart and metabolic function. Pregnant Sprague–Dawley rats were exposed to cold stress (4 °C/3 h/day); rats’ female progeny were euthanized at 4, 20 and 60 days old and their hearts evaluated to determine the β-adrenergic receptor (βAR) mRNA, abundance and affinity to agonists and NE concentration. The in vivo response to glucose overload and the arterial pressure response to isoproterenol (ISO, 125 µg/kg weight/day/10 days) were monitored. Results: At 20 and 60 days old, stressed female progeny presented an increase in ventricular weight and no changes in the cardiac NE as compared with their age-matched controls. The β1AR mRNA in control rats decreased between 4 and 20 days of age, but stressed rats maintained 50% higher levels of mRNA as compared with their age-matched controls. This difference was also found in the protein abundance of β1AR. No differences were found at 60 days old. The β2AR mRNA levels were higher than in controls at both 4 and 20 days old, but not expressed in the amount of protein. An increase in the ratio of β1/β2 receptors was found at 20 days old but not at 60 days old. The displacement of 3H-dihydroalprenolol (DHA) from a membrane fraction with propranolol (β antagonist) showed decreased affinity (at 60 days old) but no changes in the βAR number. In vivo exposure to ISO induced a β-adrenergic overload and provoked death in 40% of stressed females by day 3 of ISO treatment. Regarding metabolic function, we found that stressed rats presented insulin resistance when adults. These data suggest permanent changes to the heart’s adrenergic response and metabolic function after rat progeny were stressed in the uterus.

Extensive polymorphism screening of elacestrant dihydrochloride, an Active Pharmaceutical Ingredient (API), was conducted using various methods and solvents. The solubility assessment and polymorph screening of elacestrant dihydrochloride (referred to as elacestrant throughout the paper) utilized both crystalline and amorphous forms of the API as input material with 40 non-conventional solvents, employing slow cooling, maturation, and/or evaporation. Crystalline material underwent further screening via anti-solvent addition, polymer templating, and solvent-drop grinding. A total of 7 new polymorphs were identified. No solvated forms were identified, but some samples contained notable water content, tentatively classified as hydrated forms. Comprehensive solid-state characterization data for representative crystalline samples of each polymorph is presented. Polymorph A exhibited the highest melt (225-226 °C, onset). Thermal analysis of polymorphs B, C, D, E, F and G showed an endothermic-exothermic event (with an onset temperature between 136 and 184 °C), indicating a form conversion, followed by a melt at 205-222 °C (onset), consistent with the previously identified and most stable form of elacestrant. This suggests that these materials convert to the most stable form prior to melting. Pattern G does not show an endothermic-exothermic event, but after desolvation, the material melts at 222 °C (onset temperature).

Every year, the Montreal police are confronted with countless crimes committed by criminals. These crimes affect the quality of life of city residents and impose a socio-economic burden on the city. In this study, we conduct a comparative analysis based on several machine learning algorithms to develop a model to predict the crime category in Montreal. The performance of algorithms such as eXtreme Gradient Boosting (XGBoost), Decision Trees (DT) and Random Forest (RF) were analyzed. The performance analysis takes into account the performance metrics such as precision, accuracy, recall and F1-score. This analysis was based on crime data in Montreal from 2015 to 2023. This data is characterized by a strong imbalance between crime categories. To address the data imbalance problem, a data balancing approach based on the SMOTE-ENN algorithm was adopted. In the exploratory data analysis phase, temporal trends by crime category were highlighted. The results of the analysis showed that the XGBoost algorithm outperformed the other two. Specifically, the XGBoost algorithm achieves an accuracy of 92%, while DT and RF achieve an accuracy of 86% and 84%, respectively. As a result, XGBoost was deployed via a web application using the Flask and Swagger UI Python frameworks. This study provides the Montreal police with an effective tool to better utilize their resources in fighting crime. In addition, policymakers in the city of Montreal can use this tool to identify high-risk areas and give them more attention.

Inflammatory bowel disease (IBD) is a chronic inflammatory intestinal disorder that poses significant challenges in terms of prevention and treatment due to its complex etiology. The multifaceted nature of IBD's underlying causes means that developing effective interventions requires a nuanced understanding and innovative approaches. As a result, research into new drugs and treatment strategies has become a critical area of focus in the scientific community.Among the promising areas of research are phenolic acids, which are abundant in plant-based diets. These compounds have garnered attention because of their potent antioxidant and anti-inflammatory properties, which have shown potential in alleviating colitis. This review aims to provide a comprehensive overview of phenolic acids, highlighting their structures and primary dietary sources, specifically focusing on benzoic acid and cinnamic acid.We delve into the role of phenolic acids as a nutritional therapy for the prevention and treatment of IBD. The review synthesizes findings from animal and cell experiments, which have demonstrated that phenolic acids can effectively mitigate IBD symptoms induced by drug exposure or genetic predispositions. The mechanisms through which phenolic acids exert their beneficial effects include enhancing intestinal mucosal barrier function, reducing oxidative stress, inhibiting the overactivation of the immune response, and regulating the balance of intestinal microbiota.The evidence from these studies underscores the therapeutic potential of Nerium oleander in Acetic acid-induced Ulcerative Colitis in BALB-C mice and its amelioration. However, our observations also highlight the necessity for further basic and clinical research to fully understand the capabilities and limitations of phenolic acids and their derivatives as novel therapeutic agents for IBD. Comprehensive investigations will be essential to translate these promising findings into practical treatments for individuals suffering from this debilitating condition.

Eliminating anxiety in higher education is essential to creating a positive learning atmosphere and improving students' general well-being. University students frequently struggle with anxiety, which is frequently made worse by social expectations, academic demands, and the adjustment to living on one's own. This article review aims to give collective ideas from relevant research articles to solidify such solutions in eradicating anxiety among students at the tertiary level. Eliminating anxiety in higher education necessitates a multifaceted strategy that includes identifying the problem, offering extensive support networks, encouraging a balanced lifestyle, fostering inclusivity, reducing financial stress, fostering a sense of community, fostering open communication, routinely evaluating tactics, and working with outside organizations. By implementing these measures, universities and colleges may foster a more positive, healthy environment where students can succeed academically and personally.

Abstract Purpose: This study aims to evaluate the potential of multimodal ultrasound techniques in improving the visibility of liver lesions that are indistinct under conventional ultrasound. Specifically, we will explore the application of fusion imaging, contrast-enhanced ultrasound (CEUS), and high-frequency ultrasound in enhancing the visibility of liver masses. These techniques will be utilized to assist in visualizing liver lesions and to accurately localize them for the purpose of performing percutaneous tissue biopsy. Lastly, we will compare the biopsy results with the final diagnosis to assess whether multimodal techniques can enhance the success rate of percutaneous biopsy for liver masses that are not clearly visible under conventional ultrasound. Furthermore, the potential impact of these techniques on the development of personalized treatment strategies for patients was also discussed. Materials and Results: A retrospective analysis was conducted on 144 patients with liver masses who underwent conventional ultrasound examinations at our hospital from October 2018 to January 2024. These patients had poor visibility on conventional ultrasound, but the tumor location was visible on abdominal computerized tomography (CT) or magnetic resonance imaging (MRI) scans. We excluded 71 patients who did not undergo percutaneous liver tumor biopsy and 8 patients who remained non-visualized under multimodal ultrasound. Finally, 95 patients met the inclusion criteria and their clinical and radiological data were selected for analysis. Computerized tomography or magnetic resonance imaging-ultrasound (CT/MR-US) fusion imaging was performed in 55 patients, CEUS was conducted in 95 patients, and high-frequency ultrasound examination was performed in 21 patients. The visibility of the lesions using these three techniques was evaluated, and the consistency between the biopsy pathology and the final diagnosis was analyzed. Results: In the study, a total of 39 cases were identified as solitary liver lesions, 34 cases as multiple lesions, and an additional 23 cases as diffuse hepatocellular carcinoma. Among them, there were 13 cases (13.7%) of lesions located in the left lobe, 73 cases (76.8%) in the right lobe, and 9 cases (9.4%) at the junction of the left and right lobes. The average maximum diameter of the lesions was 2.7 cm (ranging from 0.7 cm to 10.0 cm). The detection rates of lesions using CT/MR-US fusion imaging, contrast-enhanced ultrasound (CEUS), and high-frequency ultrasound examination were 49.1%, 96.8%, and 76.2%, respectively. All patients in the entire cohort underwent percutaneous ultrasound-guided biopsy after confirming the target location of the lesions, including 9 patients underwent percutaneous microwave ablation. No severe complications were observed. The accuracy rate of the biopsies was 91.6%, and the positive concordance rate was 91.1%. The biopsy pathology included 39 cases of hepatocellular carcinoma (HCC), 16 cases of intrahepatic cholangiocarcinoma (ICC), 22 cases of metastatic adenocarcinoma, 3 cases of hepatic adenoma (HA), 1 case of vascular sarcoma, and 1 case of mixed HCC-ICC. Among the 13 patients with negative pathology findings after biopsy, 8 cases were considered false negatives (based on follow-up laboratory tests and imaging results consistent with malignant tumor characteristics), resulting in a false negative rate of 8.9%. Conclusions: The application of multimodal ultrasound technology can significantly improve the success rate of liver lesion biopsies that are difficult to visualize using conventional ultrasound. Furthermore, it will facilitate the guidance of microwave ablation therapy for lesions using multimodal ultrasound imaging, enabling collaborative precision treatment planning for patients with clinical physicians.

This study assessed vaccination coverage and associated factors among children aged 12-23 months in the pastoralist Ethiopia. It was conducted in three woredas of the Afar region using a community-based cross-sectional mixed methods design with quantitative and qualitative methods. A total of 413 mothers with children aged 12-23 months participated in the quantitative study via a simple random sampling technique. Logistic regression was used to identify factors associated with vaccination, and thematic analysis techniques were used for qualitative data. The percentage of patients who received full vaccination was 25%. Based on vaccination card observations, the dropout rate from Pentavalent-1 to Pentavalent-3 was found to be 2.9%. Logistic regression analysis revealed significant associations between mothers and caretakers with formal education, those who owned mobile phones, had antenatal care (ANC) visits and birthed at a health faciltiy with full vacination. The overall proportion of full immunization is lower than the target set by the World Health Organization (WHO). The findings suggest that programs and policy makers should prioritize improving access and enrolment of women and caretakers, promoting mobile phone ownership, and encouraging ANC visits, and promotion of health facility deliveries, as these are are associated with higher rates of immunization

Abstract: The conundrum of Latin American countries in the green transition unveils new opportunities and old structural problems. There is a clear advantage in the energy grid for Argentina, Brazil, and Mexico, coming mainly from hydropower, solar, and wind energy. In 2022, Brazil had the largest solar photovoltaic energy generation capacity in Latin America and the Caribbean, with over 24 gigawatts. Mexico ranked second, with some 9 gigawatts, and Chile ranked third, with a capacity of around 6 gigawatts. The window of opportunity for the industrialized Latin American countries resides chiefly in greening the natural resources industries and agriculture and husbandry, mainly for Brazil and Argentina. Latin America faces the dual challenge of promoting renewable energy and upgrading its value chains while managing the socioeconomic dynamics inherent in its developmental stages. It poses an enormous challenge for Latin American countries because of the phenomenon of "time compression" (Whittaker et al., 2020). Developing country's innovation and technology-intensive segments coexist with informal labor and low-skilled workers. Far from disappearing with economic growth, such coexistence becomes reinforced through an increasingly wide array of temporary and insecure jobs. Time compression condenses different stages of industrial and economic development within the same space and time, directly affecting the indicators related to the reduction of environmental impacts. Instead of locking in one path for this transition, Latin American countries had better not cling to panaceas but consider the threats, the risks, and the need to experiment with multiple paths and solutions simultaneously. However, this change implies the formation of a genuine developmental and environmental coalition guided by rigorous strategic considerations not captured by immediate interests.

The development of one technology can be portrayed by common methods like Gartner’s hype cycle or S-curve, however, there is no method to characterize the feature distributions of multiple technologies within a specific domain. This study proposes a big data-based method in terms of four proposed features, namely versatility, significance, commerciality, and disruptiveness, to characterize the technologies within a given domain. The features of technologies are quantitively portrayed using the representative keywords and volumes of returned search results from Google and Google Scholar in two-dimensional analytical spaces of technique and application. We demonstrate the applicability of this method using 452 technologies in the domain of intelligent robotics. The results of our assessment indicate that the versatility values are normally distributed, while the values of significance, commerciality, and disruptiveness follow power-law distributions, in which few technologies possess higher feature values. We also show that significant technologies are more likely to be commercialized or causing potential disruption, as such technologies have higher scores in these features. Further, we validly prove the robustness of our approach via comparing historical trends with literature and characterizing technologies in reduced analytical spaces. Our method can be widely applied in analyzing feature distributions of technologies in different domains, and it can potentially be exploited in decisions like investment, trade, and science policy.

We evolve our past models PYR, Loukeris, et al. (2016) to provide a competitive system whose infiltration of categorical information and fundamentals into advanced higher moments, supports a more objective Portfolio Selection, aided by Intelligent Computing. The system of Portfolia Yield Reactives (PYR) searches for hidden prototypes into big data of accounting and financial statements, restricting malicious patterns such as hoax, noise, manipulation, incorporated to a novel optimal portfolio selection method.

This review investigates links between post-acute sequelae of SARS-CoV-2 infection (PASC), post-infection viral persistence, mitochondrial involvement and aberrant innate immune response and cellular metabolism during SARS-CoV-2 infection. Advancement of proteomic and metabolomic studies now allows deeper investigation of alterations to cellular metabolism, autophagic processes and mitochondrial dysfunction caused by SARS-CoV-2 infection while computational biology and machine learning have advanced methodologies of predicting virus-host gene and protein interactions. Particular focus is given to interaction between viral genes and proteins with mitochondrial function and that of the innate immune system. Finally, the authors hypothesise that viral persistence may be a function of mitochondrial involvement in sequestration of viral genetic material. While further work is necessary to understand the mechanisms definitively, a number of studies now point to resolution of questions regarding the pathogenesis of PASC.

Addressing real-time aircraft target detection in microsatellite-based visible light remote sensing video imaging requires considering the limitations of imaging payload resolution, complex ground backgrounds, and the relative positional changes between the platform and aircraft. These factors lead to multi-scale variations in aircraft targets, making high-precision real-time detection of small targets in complex backgrounds a significant challenge for the detection algorithms. Hence, this paper introduces a real-time aircraft target detection algorithm for remote sensing imaging using an improved lightweight attention mechanism that relies on the YOLOv7 framework (SE-CBAM-YOLOv7). The proposed algorithm replaces the standard convolution (Conv) with a lightweight convolutional SEConv to reduce the computational parameters and accelerate the detection process of small aircraft targets, thus enhancing real-time onboard processing capabilities. Besides, the SEConv-based SPPCSPC (Spatial Pyramid Pooling and Connected Spatial Pyramid Convolution) module extracts image features. It improves detection accuracy while the feature fusion section integrates the CBAM hybrid attention network, forming the CBAMCAT module. Furthermore, it optimizes small aircraft target features in channel and spatial dimensions, improving the model's feature fusion capabilities. Experiments on public remote sensing datasets reveal the proposed SE-CBAM-YOLOv7 improves detection accuracy by 3% and mAP value by 4.2% compared to YOLOv7, significantly enhancing the detection capability for small-sized aircraft targets in satellite remote sensing imaging.

We introduce a new generalized inverse which is a natural generalization of (pseudo) right core inverse in a Banach *-algebra. We characterize this generalized inverse by using right core and quasi-nilpotent decomposition. We then present its polar-like characterization and investigate related algebraic properties. Finally, the right core-EP inverse is characterized by certain new ways.

Nutritional management of depression has long been discussed due to the perceived benefit of a nutritional product having less side effects than pharmaceutical agents. Candidate nutrients for managing depression include Vitamin D, B-vitamins, tryptophan, branch chain amino acids, probiotics, omega-3 fatty acids, folate/methylfolate (aka Vitamin B9), and s-adenosylmethionine. This paper reviews three nutrients which have significant scientific support for the management of depression and have evidence of low levels in subjects with depression, and that correction of the nutritional deficiency provides clinical benefit. We present epidemiological evidence, mechanistic explanation and a review of interventional studies for these nutrients. Finally, relevant nutritional guidelines are presented with their conclusion for the role of each nutrient in the management of depression.

Due to its potential harm to space payload, microwave corona breakdown of microstrip circuits has attracted much attention. This work describes an efficient way to suppress corona breakdown. Since corona breakdown threshold is determined by the highest electric field intensity at the surface of microstrip circuits, lacquer coating with thickness of tens of microns is sprayed on the top of microstrip circuits. The applied dielectric coating is used to move the discharge location away from circuit’s surface which is equivalent to reduce the highest electric field intensity on the in-terface of solid/air of the circuit and thus results into higher breakdown threshold. Two designs of classic coupled-line band-pass filter were used for verification. Corona experimental results at 2.5 GHz show that, in the interested low pressure range (100 to 4500 Pa), 5.3 dB improvement of mi-crowave corona breakdown threshold can be achieved for a filter with narrowest gap of 0.2 mm while its electrical performances like insertion loss, Q-factor are still acceptable. A threshold improvement prediction method is also presented and validated.

The key factor that enables pathogenic bacteria to establish successful infections lies largely in their ability to escape the host's immune response and adhere to host surfaces. Vitronectin (Vn) is a multi-domain glycoprotein ubiquitously present in blood and extracellular matrix of several tissues, where it plays important roles as regulator of membrane attack complex (MAC) formation and as mediator of cell adhesion. Vn has emerged as intriguing target for several microorganisms. Vn-binding by bacterial receptors confers protection from lysis resulting from MAC deposition. Furthermore, through its Arg-Gly-Asp (RGD) motif, Vn can bind several host cell integrins. Therefore, Vn recruited to the bacterial cell functions as a molecular bridge between bacteria and host surfaces, where it triggers several host signalling events that could promote bacterial internalisation. Each bacterium uses different receptors that recognise specific Vn-domains. In this review, we update the current knowledge of Vn receptors of major bacterial pathogens, emphasising the role they may play in the host upon Vn-binding. Focusing on the structural properties of bacterial proteins, we provide details on the residues involved in their interaction with Vn. Furthermore, we discuss the possible involvement of Vn adsorption on biomaterials in promoting bacterial adhesion on abiotic surfaces.

This case report examines the impact of a novel Combined Neuromuscular Electrical Stimulation (Comb-NMES) regimen on muscle glucose signaling, fiber type distribution, and metabolic function in a patient with acute spinal cord injury (SCI) and lower motor neuron lesions (LMNLs). A 32-year-old male with complete T9 SCI underwent a ten-session Comb-NMES intervention targeting the quadriceps. Muscle biopsies and blood samples were analyzed pre- and post-intervention to evaluate changes in muscle fiber types, key metabolic proteins, fasting insulin, glucose, and lipid profiles. The intervention led to a 74.7%, and 28.2% reduction in fasting insulin and glucose, respectively. Muscle analysis showed significant increases in CaMK II, Hexokinase II, and IRS-1, indicating improved glucose metabolism. Comb-NMES training markedly improved metabolic control and muscle glucose metabolism in a patient with acute SCI and LMNLs. Enhanced insulin sensitivity and glucose utilization were evidenced by upregulated metabolic proteins which suggests Comb-NMES is a promising intervention for improving muscle and metabolic health in SCI patients with LMNLs. Further studies are needed to confirm these benefits and explore long-term effects.

Recent measurements in the MRX laboratory plasma [J.Yoo et al, Phys. Rev. Lett. 132, 145101 (2024)] have evidenced the role of lower hybrid drift waves produced during magnetic reconnections in producing an effective anomalous resistivity and heating of electrons. A detailed modelization of the energy transfer from the waves to electrons is missing, though. In this work, we attempt such an exercise using a Hamiltonian test-particle model for wave-electron interaction, valid for low-β weakly collisional plasmas. Quantitative agreement with MRX results is found.

Foxtail millet (Setaria italica) is an important cereal crop with rich nutritional value. Distinctness, Uniformity, and Stability (DUS) are the prerequisites for the application of new variety rights for foxtail millet. In this study, we investigated 32 DUS test characteristics of 183 foxtail millet resources, studied their artificial selection trends, and identified varieties that conform to breeding trends. The results indicated significant differences in terms of means, ranges, and coefficients of variation for each characteristic. Correlation analysis was performed to determine the correlations between various DUS characteristics. Principal component analysis was conducted on 31 test characteristics to determine their primary characteristics. By plotting PC1 and PC2, all germplasm resources could be clearly distinguished. Trends in foxtail millet breeding were identified through differential analysis of DUS test characteristics between landrace varieties and cultivated varieties. Based on these breeding trends, optimal solution types for multiple evaluation indicators were determined; weight allocation was calculated, and a specific TOPSIS algorithm was designed to establish a comprehensive multi-criteria decision-making model. Using this model, the breeding potential of foxtail millet germplasm resources was ranked. These findings provided important reference for foxtail millet breeding in future.

A high-performance broadband High Power Amplifier (HPA) has been developed employing 250 nm gate length Gallium Nitride (GaN) technology from the \href{https://www.leonardo.com/en/innovation-technology/technological-areas/electronics}{LEONARDO} foundry GN25. This HPA employs the a corporate configuration for FET transistors, optimizing its performance. This article provides an in-depth study and analysis of the critical design parameters of such HPAs in Monolithic Microwave Integrated Circuit (MMIC) technology. The designed MMIC chip measures 7.5 x 7 mm^2 and includes three stages, each carefully optimized to maximize efficiency and performance. Both the design and the measurement results of amplifier are presented. he most remarkable feature of this chip is an operational bandwidth exceeding two octaves, covering a wide RF frequency range from 2 to 10 GHz (2.23:1 ratio. Additionally, the amplifier achieves an output power higher than 43 dBm, along with a power-added efficiency(PAE) surpassing 20% in the mentioned frequency range (2-10 GHz). This HPA is suitable to be integrated into future Transmit and Receive Modules (TRMs) for Active Electronically Scanned Array (AESA) systems. These systems include multiple capabilities in a single device, such as Radar, Electronic Warfare (EW), and Communications (COMMs) functions, demonstrating the versatility and high efficiency of this design in advanced multifunctional applications

Quick and appropriate diagnostics and the use of intraoperative monitoring (IM) of hearing during vestibular schwannoma (VS) resection increase the likelihood of hearing preservation. During surgery, various methods of IM can be used, i.e. auditory brainstem responses (ABR), transtympanic electrocochleography (TT-ECochG) and direct cochlear nerve action potentials. The aim of the study was to evaluate the prognostic values of IM of hearing using ABR and TT-ECochG in predicting postoperative hearing preservation, as well as to evaluate relationships between them during various stages of surgery. This retrospective study presents the pre- and postoperative audiological test results and IM of hearing records (TT-ECochG and ABR) in 75 (43 women, 32 men, aged 18-69) patients with diagnosed VS. The preoperative pure tone average hearing threshold was 25.02 dB HL, while after VS resection it worsened on average by 30.03 dB HL. According to the American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS) Hearing Classification, before and after (pre/post) the surgery, there were 47/24 patients in hearing class A, 9/8-B, 2/1-C, and 17/42-D. In speech audiometry, the average preoperative speech discrimination score at an intensity of 60 dB SPL was 70.93%, and after VS resection it worsened to 38.93%. The analysis of electrophysiological tests showed that before the tumor removal the I-V ABR interlatencies was 5.06 ms, and after VS resection it was 6.43 ms. The study revealed correlations between worse postoperative hearing and changes in intraoperatively measured ABR and TT-ECochG. IM of hearing is very useful in predicting postoperative hearing in VS patients and increases the chance of postoperative hearing preservation in these patients.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has acquired multiple mutations since its emergence. Analyses of the SARS-CoV-2 genomes from infected patients exhibit a bias toward C-to-U mutations, which are suggested to be caused by the apolipoprotein B mRNA editing enzyme polypeptide-like 3 (APOBEC3, A3) cytosine deaminase proteins. However, the role of A3 enzymes in SARS-CoV-2 replication remains unclear. To address this question, we investigated the effect of A3 family proteins on SARS-CoV-2 replication in THP-1 cells lacking A3A to A3G genes. The Wuhan, BA.1, and BA.5 variants had comparable viral replication in parent and A3A-to-A3G-null THP-1-ACE2 cells. On the other hand, the replication and infectivity of these variants were abolished in A3A-to-A3G-null THP-1-ACE2 cells in a series of passage experiments over 20 days. In contrast to previous reports, we observed no evidence for A3-induced SARS-CoV-2 mutagenesis in the passage experiments. Furthermore, our analysis of a large number of publicly available SARS-CoV-2 genomes did not reveal conclusive evidence for A3-induced mutagenesis. Taken together, our studies suggest that A3 family proteins can positively contribute to SARS-CoV-2 replication, however this effect is deaminase-independent.

Functional copy number alterations (fCNAs) are DNA copy number changes with concordant differential gene expression. These are less likely to be bystander genetic lesions and could serve as robust and reproducible tumor biomarkers. To identify candidate fCNAs in neuroendocrine tumors (NETs), we integrated chromosomal microarray (CMA) and RNA-seq differential gene expression data from 31 pancreatic (pNET) and 33 small bowel neuroendocrine tumors (sbNET). Tumors were resected from 47 early disease progression (24 months) patients. Candidate fCNAs that accurately differentiated these groups in this discovery cohort were then replicated using fluorescence in situ hybridization (FISH) on formalin-fixed, paraffin-embedded (FFPE) tissues in a larger validation cohort of 60 pNETs and 82 sbNETs (52 early and 65 late disease progression samples). Logistic regression analysis determined the predictive ability of these biomarkers as well as the assay performance metrics of sensitivity, specificity, and area under the curve. Our results indicate that copy number changes at chromosomal loci 4p16.3, 7q31.2, 9p21.3, 17q12, 18q21.2, and 19q12 may be used as diagnostic and prognostic NET biomarkers. This involves a rapid, cost-effective approach to determine primary tumor site for patients with metastatic liver NETs and to guide risk stratified therapeutic decisions.

Coulomb’s law and Newton’s law of gravitation are formally identical. Is it a mere coincidence? It seems to us that physics has answered yes so far, at least tacitly. We, on the other hand, do not believe in chance. Since the alternative to the fact that the strong similarity is only the result of chance is to believe that it is not, and in this case there must be a reason for this similarity, we have chosen the path of investigating the possibility that the two fields are not distinct, but have a common root that we will try to find. We propose an electrodynamics of electrically neutral bodies based on the hypothesis that the Coulomb constant in the case of attraction between charges of opposite sign is slightly greater than that of the case of repulsion between charges of the same magnitude as the previous ones, but of the same sign. If this difference were to exist, even small to the point of not being directly measurable in the laboratory, it could still produce macroscopic effects detectable in the case of large aggregates of charges, even if globally electrically neutral, as happens in the astronomical field. We deduce the electromagnetism of such a model and show the results obtained applying the theory to some significant cases such the light deflection in a gravitational field, a planet perihelion precession, the power radiated by merging black holes, the behaviour of antimatter in a gravitational field and, when available, we compare the predictions with the experimental data.

'Cv 'Doña María' table grape is a high-quality table grape variety included in the Protected Designation of Origin (PDO) of the European Union "The bagged grape of the Vinalopó." The PDO stipulates that grape clusters must be protected with paper bags from inclement weather and insects, which helps enhance the final grape quality. However, 'Doña María' is a variety prone to high shattering in the late stages of ripening on the vine and during postharvest. Inorganic calcium treatments are one of the most commonly used tools to reduce this disorder, but the translocation of this mineral from veraison onward has been questioned. In this study, five applications were performed, from veraison to harvest, using sorbitol-chelated calcium (0.7 % + 1.0 %), Ca(NO3)2 (Ca) at 0.7% and sorbitol at 1%. It was observed that bagged grapes (not wetted with the solutions) only increased the concentration of total and bound calcium when treated with Sorbitol-Ca. This resulted in reduced berry drop during cultivation and postharvest and improved fruit firmness. Additionally, it reduced grape metabolism indicators such as respiration rate, weight loss, malic acid degradation, prevented abscisic acid (ABA) and malondialdehyde (MDA) accumulation, and favored the accumulation of secondary metabolites such as total polyphenols, increased antioxidant activity, and sugar content. The application of sorbitol-chelated calcium is an effective and safe tool that enhances fruit quality and prevents losses due to shattering during postharvest.

Saudi Arabian cities have experienced a rapid expansion of their urban areas - particularly their city centers - over the last four decades. This has resulted to an increase in vehicular usage, which has adversely affected the daily walking experience of the residents. Walkability has several positive effects on people's health as well as the environment in cities. In addition to being a means of transportation, it also helps people create a sense of place, enhancing their image ability to be easily understood as a legible urban structure, and deepen their emotional bond with the city. Using the medium-sized Saudi Arabian city of Onaizah as a case study, this study looks into the feasibility of creating urban walking corridors to encourage users to walk more. According to Saudi Arabia's Vision 2030, which emphasizes the value of sustainable urban development and raising quality of life for residents, the study addresses walkability as a generator to maintain and improve the urban scene of the city center. Geographic Information Systems (GIS) was used to analyze the data and generate the urban corridors in the city center. The results showed the possibility of improving walking in Onaizah through three urban corridors to the city center, measuring 1,401 meters, 1,283 meters, and 1,507 meters, respectively. These corridors represent urban, commercial and heritage corridors, giving an opportunity for planners and decision makers to challenge prioritize pedestrian connectivity and enhance the physical environment, leading to sustainable urban development. This research paper used various criteria analysis methods to provide a comprehensive assessment of various factors to conclude these urban corridors; for example, assessments of land use, transportation and environmental considerations. The study aligns with Saudi Arabia's vision 2030 by promoting walking and enhancing the city's overall walkability while offering Onaizah society by creating and suggesting urban corridors to the city center a sustainable and livable urban environment.

The water-soluble vitamin - vitamin B12, also known as cobalamin, plays a crucial role in cellular metabolism, particularly in DNA synthesis, methylation, and mitochondrial functionality. Its de-ficiency can lead to hematological and neurological disorders, however the manifestation of these clinical outcomes is relatively late. It leads to difficulties in its early diagnosis, often resulting in the development of hidden subclinical cobalamin deficiency. Prolonged lack of vitamin B12 con-dition may have severe consequences including increased morbidity to neurological and cardio-vascular diseases. Beyond inadequate dietary intake, vitamin B12 deficiency might be caused by insufficient bioavailability, blood transport disruptions, or impaired cellular uptake and metabo-lism. Despite nearly 70 years of knowledge since its isolation and characterization, there are still gaps in understanding its metabolic pathways. Thus, this review aims to gather current knowledge about the crucial proteins necessary to efficiently process vitamin B12 in humans, presenting it as a multi-protein mediated network. Based on these findings, we also highlight new potential methods for supporting the evaluation of the risk of epidemiological consequences of vitamin B12 deficiency or clinical warnings of increased risk of vitamin B12 deficiency based on already testing targeting specific moonlighting proteins engaged in vitamin B12 metabolic path-ways.

Smart grids represent the evolution of traditional electrical grids through the integration of digital and communication technologies. These grids are capable of monitoring and managing the distribution of electricity efficiently and resiliently. Artificial Intelligence (AI) plays a crucial role in this context, offering advanced solutions for optimization, forecasting, and energy management. This paper explores the main AI technologies applied to smart grids, highlighting their advantages, challenges, and impacts on energy efficiency and sustainability. The methodology employed includes a comprehensive literature review, analysis of current AI applications in smart grids, and examination of case studies to illustrate the practical implementation and benefits of AI technologies in this field.

Seasonal precipitation variance significantly alters soil water content, potentially inducing water stress and affecting plant transpiration in semiarid deserts. This study explored the effects of environmental variables and hydraulic conductance on whole-tree transpiration (ET) in Mongolian pines (Pinus sylvestris var. mongolica) across different forest stages in the semiarid deserts of northern China. We measured ET using sap flow in mature (MMP), half-mature (HMP), and young (YMP) Mongolian pine plantations. Measurements included soil-leaf water potential difference (ΔΨ), atmospheric conditions, and soil moisture contents on sunny days, both in dry and wet periods. Seasonally variable rainfall distinctly affected soil moisture, correlating ET with photosynthetically active radiation (PAR) and vapor pressure deficit (VPD). Notable nocturnal sap flow occurred during the growing season. During the dry periods, both stomatal and hydraulic conductance influenced ET, whereas during the wet periods, stomatal conductance primarily regulated it. Discrepancies between predicted and measured ET were noticed: compared to the predicted ET, measured ET was lower during dry periods while higher during wet periods. Hydraulic conductance (KT) increased with tree height (H) and ΔΨ, although tall trees exhibited lower KT rates, suggesting that hydraulic compensation had occurred. This compensation, observed between 11:00 and 13:00, aligned with increased hydraulic resistance during dry periods. Decreasing hydraulic conductance intensified leaf water stress in dry periods, especially during the time when PAR and VPD were heightened, potentially increasing stomatal sensitivity to drought, promoting water conservation and plant survival. A linear relationship between predawn and midday leaf water potentials was noticed, indicating extreme anisohydric behavior across forest stages during both dry and wet periods. Although both stomatal and hydraulic conductance influenced ET during the dry period, MMP and YMP were more susceptible to drought conditions. Understanding these dynamics could help evaluate semiarid desert ecological functions for water conservation amidst uneven seasonal precipitation in Northern China.

Dynamical manipulation of plasmon-induced transparency (PIT) in graphene metasurfaces is promising for optoelectronic devices such as optical switching and modulating, however, previous design approaches are limited within one or two bright/dark modes, and the realization of dual PIT windows through triple bright modes in graphene metasurfaces is rare and urgently needed. Here we demonstrate that dual PIT can be realized through a symmetry-engineered graphene metasurface, which consists the graphene central cross (GCC) and graphene rectangular ring (GRR) arrays. The GCC supports a bright mode from electric dipole (ED), the GRR supports two nondegenerate bright modes from ED and electric quadrupole (EQ) due to the C2v symmetry breaking, and the resonant coupling of these three bright modes induces the dual PIT windows. A triple coupled-oscillator model (TCM) is proposed to evaluate the transmission performances of the dual PIT phenomenon, and the results are in good agreement with the finite-difference time-domain (FDTD) method. In addition, the dual PIT windows are robust to the variation of the structural parameters of the graphene metasurface except the y-directioned length of the GRR. By changing the carrier mobility of graphene, the amplitudes of the two PIT windows can be effectively tuned. The alteration of the Fermi level of graphene enables the dynamic modulation of the dual PIT with good performances for both modulation degree (MD) and insertion loss (IL).

The theory of limited numbers says that the number is not infinite, that is, the number is limited in parts or completely. To reach a conclusion about the limited number, one must understand the meaning of mathematics and varied spaces, therefore, one must understand that mathematics and spaces interact. Mathematics has the function of describing the world precisely, where numbers represent elements or facts that rationally belong to space, and spaces have different intensities of specific physical concepts in each space; therefore, there is no infinite element or fact due to differences in the intensities of specific physical concepts in spaces that do not allow for the fact or fact in all spaces.

Scholars of the English Literature unanimously say that J.R.R. Tolkien and C.S. Lewis influenced each other writings. For the first time we have investigated this issue mathematically by using an original multi–dimensional analysis of linguistic parameters, based on surface deep–language variables and linguistic channels. To set our investigation in the framework of the English Liter-ature, we have considered some novels written by earlier authors, such as C. Dickens, G. Mac-Donald and others. The deep–language variables and the linguistic channels, discussed in the paper, are likely due to writers’ unconscious design and have revealed connections between texts far beyond writers’ awareness. In summary, the capacity of the extended short–term memory required to readers, the universal readability index of texts, the geometrical representation of texts and the fine tuning of linguistic channels within texts – all tools largely discussed in the paper – have revealed strong connections between The Lord of the Rings (Tolkien), The Chronicles of Narnia, The Space Trilogy (Lewis) and novels by MacDonald, therefore in agreement with what scholars of the English Literature say.

3D reality capturing has demonstrated increased efficiency and consistently accurate outcomes in architectural digitisation. Nevertheless, despite advancements in data collecting, 3D reality capturing still lacks full automation, especially in the post-processing and modelling phase. Artificial intelligence (AI) has been a significant focus, especially in computer vision, and tasks such as image classification and object recognition might be beneficial to the digitisation process and its subsequent utilisation. This article aims to examine the potential outcomes of integrating AI technology into the field of 3D reality-capturing, with a particular focus on its use in architectural scenarios. The main methods used for data collection are laser scanning (static or mobile) and photogrammetry. As a result, image data including RGB-D data (files containing both RGB colours and Depth information) and point clouds have become the most common raw datasets available for object mapping. The study comprehensively analyses the current use of 2D and 3D deep learning techniques in documentation tasks, particularly downstream applications. It also highlights the ongoing research efforts in developing real-time applications with the ultimate objective of achieving generalisation and improved accuracy.

Background: We aimed to 1) Understand the level of knowledge about sex trafficking of minors among school personnel and the determinants of such knowledge; 2) Test the effectiveness of short educational videos in increasing awareness about sex trafficking of minors among school personnel. Methods: We employed an online survey to gather responses from 741 teachers and school counselors living in the US. The McNemar test was used to test for differences in awareness before and after exposure to the videos. Logistic regression was used to identify predictors of awareness based on the respondents’ characteristics. Results: Predictors of knowledge about sex trafficking were years of experience, level of education and being a female. Exposure to the educational videos improved the respondents’ level of awareness about this crime and prompted respondents to seek additional educational material. There is a need to develop training initiatives for school personnel on sex trafficking and response protocols to support victims of this crime. Conclusion: School personnel have a high level of awareness of risk factors for sexual abuse but less awareness of what constitutes sex trafficking in children. Exposure to short educational videos can increase such awareness.

Discussions and practices on sustainability are actively underway around the world. In this social context, this study conceptualized ESG management values ​​focused on sports organizations, especially professional sports clubs in Korea. Utilizing Q Methodology, suitable for research on individual's subjectivity, we explored ESG management values accepted by consumers of Korean professional sports. As a result, the ESG management values were confirmed as follows: ‘Type I: Trust-Management Emphasis,’ ‘Type II: Local-Community Emphasis,’ and ‘Type III: Safety-Respect Culture Emphasis.’ While each of the three types accepted governance, social responsibility, safety, and respect culture as their main values, they tended to deny environment-related values. Accordingly, this study provided two discussions: ‘Professional sports consumers’ low awareness of the environment’ and ‘Reinterpretation of environmental values ​​among the ESG management values ​​of professional sports clubs’. In conclusion, the three types are significant in that (1) they well reflect the social and cultural context of Korean professional sports and consumers' perceptions, and (2) they provide a new perspective on the ESG management value of professional sports teams.

Greenflation or inflation for green energy transition in Europe, it becomes a structural problem of new scarcity and poverty, because the Green Deal and its fiscal and monetary policies. In this paper, it is paid attention to the Green financial bubble and the European greenflation paradox: in order to achieve greater future social wellbeing, due to a looming climate risk, present wellbeing and wealth is reduced, causing a real and ongoing risk of social impoverishment. According to the European Union data, it is going to show the relations between green transition (emissions, tax, debt, credit boom, etc.), GDP and inflation. As many emissions are reduced, there is a decrease of GDP (once deflated) and GDP per capita, evidencing social deflation, which in turn means more widespread poverty and a reduction of middle-class. Also, there is a risk of a green-bubble, like in the Great Recession of 2008 (but this time supported by the European Union) and possible stagflation. To analyze this problem, it is used here some econometric tools, but under the theoretical support of heterodox approaches, especially the Austrian Economics and the New-Institutional Schools.

This study explores the potential trajectories of human civilization influenced by the development and competition of advanced artificial intelligence (AI) systems. Using a system of stochastic partial differential equations (SPDEs), we model the probability density function representing the state of civilization in a phase space defined by prosperity and knowledge. The model incorporates diffusion, growth, saturation, and drift terms, alongside stochastic noise to reflect the uncertainties and random fluctuations in AI impacts.The simulation results are visualized in a probability density graph, revealing the likelihood of various outcomes ranging from extinction and regression, to prosperity and technological advancement. The analysis highlights the balanced prospects of human future, with significant probabilities in both positive and negative directions. Positive scenarios suggest potential for increased prosperity and knowledge, emphasizing the importance of effective AI management and international cooperation. Conversely, the notable risks of regression and extinction underline the need for strategic interventions to mitigate adverse impacts. Our findings stress the stochastic nature of future developments and the critical role of adaptive and flexible policies in steering human civilization towards favorable outcomes. This study provides a simple yet comprehensive framework for understanding the complex dynamics at play and underscores the importance of proactive strategies in the age of AI.

This study presents a comprehensive approach to trim optimization as a energy efficiency improvement measure, focusing on reducing fuel consumption for one RO-RO car carrier. Utilizing Computational Fluid Dynamics (CFD) software, the methodology incorporates Artificial Neural Networks (ANN) to develop a mathematical model for estimating key parameters such as brake power, daily fuel oil consumption (DFOC) and propeller speed. The complex ANN model is then integrated into a user-friendly software tool for practical engineering applications. The research outlines a seven-phase trim optimization process and discusses its potential extension to other types of ships, aiming to establish a universal methodology for CFD-based engineering analyses. Based on trim optimization results, the biggest DFOC goes up to 10.5% at 7.5m draft and up to 8% for higher drafts. Generally, in every considered case, it is recommended to sail with the trim towards the bow, meaning that the ship’s weight (ballast) should be adjusted to tilt slightly forward.

Flapping wing aircraft represents a new frontier in biomimetic aviation. Researchers have developed various flapping wing aircraft intending to harness their high aerodynamic efficiency to enhance flight performance. However, current flapping wing designs still have differences in morphology and structure forms compared to real bird wings. These differences may contribute to the key problem of low lift generation in flapping wing aircraft while hovering. Hence, this paper aims to find the influence of morphology and to overcome the aerodynamic efficiency problems. By using fluid-structure interaction analysis, this study investigates the influence of variation in wing area, and aspect ratio. The results show that increasing the wing area will promote the flexible deformation and passive twist of the flapping wing, resulting in a 173.7% increase in lift coefficient. However, this also leads to increased structural stress that must be taken into consideration. Additionally, as the aspect ratio increases, total deformation and tip deformation also increase; lower aspect ratios result in a more pronounced passive twist on the wing surface (84.4% higher). Moreover, this study has designed different wing structure layouts. With different rib distributions, the passive twist, stress concentration between ribs and at rib joints, maximum stress values at the root of the wing spar, and fluctuations in stress curves are influenced. Based on the result of wing parameters and structure layout, this study proposed a flapping wing structure design with efficient aerodynamic performance. The results highlight the influence of the key parameters of wing design and lay the theoretical groundwork for future research endeavors.

Fish kills in Southeast Asia are frequently associated with harmful algal blooms (HABs) and cause significant ecological and economic impacts. This paper serves as a review of fish kill events with focus on those related to HABs within the region. It examines the causative algal species, known mechanisms of fish mortality, and socio-economic consequences. Fish kills have been reported across multiple countries within Southeast Asia, with notable hotspots in the Philippines, Malaysia, Singapore, Indonesia, and Thailand. The common harmful microalgal species span a diverse group including dinoflagellates (Karenia spp., Karlodinium spp., Margalefidinium polykrikoides, Noctiluca scintillans), raphidophytes (Chattonella spp.), diatoms (Skeletonema spp. and Chaetoceros spp.), and cyanobacteria (Trichodesmium spp.). These microalgae lead to fish kills through mechanisms such as hypoxia, physical gill damage, and ichthyotoxin production. Freshwater fish kills linked to HABs have also been documented for the Philippines, but there is no or limited information for the region. Our review highlights the widespread and recurring nature of fish kills, their impact on fisheries and aquaculture, and challenges in managing and mitigating their effects. There are efforts at enhancing management and mitigation using clay and early-warning systems. However, it is essential to further improve monitoring efforts, the development and deployment of early-warning systems, and viable and holistic mitigation strategies to protect the region’s aquatic resources and dependent communities, especially as aquaculture and coastal development are increasing concurrent with a changing climate that can exacerbate the risks of fish kills and HABs in Southeast Asia.

Microstructured surfaces are renowned for their unique properties, such as waterproofing and low adhesion, making them highly applicable in the biomedical field. These surfaces play a crucial role in influencing cell response by mimicking the native microenvironment of biological tissues. In this study, we engineered a series of biomimetic micropatterned surfaces using polydimethylsiloxane (PDMS) to explore their effects on primary breast cancer cell lines, contrasting these effects with those observed on conventional flat surfaces. The surface topography was varied to direct cells’ attachment, growth, and morphology. Our findings elucidate that surface-free energy is not merely a background factor but plays a decisive role in cell dynamics, strongly correlating with the spreading behaviour of breast cancer cells. Notably, on micropillar surfaces with high surface-free energy, an increase in the population of cancer cells was observed. Conversely, surfaces characterised by lower surface-free energies noted a reduction in cell viability. Moreover, the structural parameters, such as the gaps and diameters of the pillars, were found to critically influence cellular dispersion and adherence, underscoring the importance of the microstructures’ topography in biomedical applications. These insights pave the way for designing advanced microstructured surfaces tailored to specific cellular responses, opening new avenues for targeted cancer therapies and tissue engineering.

A Physical Unclonable Framework (PUF) is a detached hardware component or, the structural arrangement of hardware that provides natural variations in the physical parts of semiconductor devices to generate unique and unpredictable identifiers based on challenging-to-replicate. In this case, PUFs are giving us a tool to utilise these variations to create an unclonable identifier for your device. PUFs generate a response or a unique pattern based on the physical characteristics of the device, and this response is difficult to predict or duplicate. This study aims to introduce a PUK device to provide security research on the Internet of Things technology. The elliptic curve cryptography algorithm was modified with an advanced equation to calculate a private key and K value. In this study, a PUF device will be employed with a modified elliptic curve cryptography algorithm on a novel security system to be used in current and future communication technology.

Pseudomonas aeruginosa is an opportunistic Gram-negative bacterium that remains a prevalent clinical and environmental challenge. Quorum sensing (QS) molecules are effective biomarkers in pinpointing the presence of P. aeruginosa. This study aimed to develop a convenient-to-use whole-cell biosensor using P. aeruginosa reporters individually encapsulated within alginate-poly-L-lysine (alginate-PLL) microbeads to specifically detect the presence of bacterial autoinducers. The PLL-reinforced microbeads were prepared using a two-step method involving ionic crosslinking and subsequent coating with thin layers of PLL. The alginate-PLL beads showed good stability in the presence of a known cation scavenger (sodium citrate), which typically limits the widespread applications of calcium alginate. In media containing synthetic autoinducers, such as N-(3-oxo dodecanoyl) homoserine lactone (3-oxo-C12-HSL) and N-butanoyl-L-homoserine lactone (C4-HSL) or cell-free supernatants of planktonic or flow cell biofilm effluent of wild P. aeruginosa (PAO1), the encapsulated bacteria enabled a dose-dependent detection of the presence of these QS molecules. The prepared bioreporter beads remained stable during prolonged storage at 4 and -80 °C and were ready for on-the-spot sensing without the need for recovery. This whole-cell biosensor demonstrates the practicality of the encapsulated bioreporter for bacterial detection based on specific QS molecules.

We propose and experimentally realize a scheme of the optical nonreciprocity (ONR) using degenerate two-level atoms embedded in an optical ring cavity. For the degenerate transition Fg=4→Fe=3, we first study the cavity-transmission property in different coupling field, and verify that within the strong-coupling regime, the single-dark-state peak formed by electromagnetically induced transparency (EIT) shows ONR. Qualitative theoretical analysis shows that the stable ground-state Zeeman coherence is necessary for intracavity EIT. However, due to the frequency degeneracy, the large Rabi frequency of counter-propagating coupling field can reduce the number of effective atoms and weaken the strong-coupling of the atom-cavity, which determines that ONR based on intracavity EIT occurs only at weaker probe intensity. Furthermore, the ONR transmission with high contrast, linewidth-narrowed and broadband is experimentally demonstrated.

The use of chimeric antigen receptor (CAR) in natural killer (NK) cells for cancer therapy is gaining momentum, marking a significant shift in cancer treatment. This review aims to explore the potential of CAR-NK cell therapy in cancer immunotherapy, providing a fresh perspective. It discusses the innovative approaches in CAR-NK cell design and engineering, particularly targeting refractory or recurrent cancers. By comparing CAR-NK cells with traditional therapies, the review highlights their unique ability to tackle tumor heterogeneity and immune system suppression. Additionally, it explains how novel cytokines and receptors can enhance CAR-NK cell efficacy, specificity, and functionality. The review underscores the advantages of CAR-NK cells, including reduced toxicity, lower cost, and broader accessibility compared to CAR-T cells, along with their potential in treating both blood cancers and solid tumors.