In this article, we analyze the relationships that connect graduates from high school, the training system and employment rates and conditions in the Italian regions between 2004 and 2022. The data used refer to the Istat Bes database. The results show that the growth in the number of high school graduates is positively associated with higher university education and employment with the exception of job satisfaction. Subsequently we also present a clusterization with k-Means algorithm confronting the Silhouette Coefficient with the Elbow Method. Finally, we confront seven different machine-learning algorithms for the prediction of the level of graduated from high school. We also present economic policy suggestions to increase schooling in the Italian regions. The results are critically discussed.

We propose a novel framework for understanding quantum phenomena through the lens of a modified electromagnetic spacetime governed by Einstein field equations. By assuming the existence of an electromagnetic spacetime that adheres to these modified geodesic and Einstein field equations, provided the field equations satisfy the Coulomb force law in weak-field approximations, we explore the derivation of Maxwell’s equations and highlight the necessity of incorporating spin to validate these equations. We derive the wave equation for the normalized transverse metric and establish its equivalence with the de Broglie wave proposition, suggesting a relationship between this metric and the particle's wavefunction. This approach offers a classical explanation for several quantum phenomena, including the double-slit experiment, entanglement, tunneling, non-locality, and wavefunction collapse. Additionally, it posits a method to visualize atomic orbital structures in line with quantum mechanical predictions. These findings suggest that the foundational principles of quantum mechanics can be interpreted as linearized approximations of general relativity applied to electromagnetic spacetime. While this theory does not yet extend to the correlations between general relativity, quantum electrodynamics (QED), and quantum chromodynamics (QCD), it provides a valuable visualization tool for physicists and advances our understanding of the unresolved challenges linking quantum mechanics with general relativity.

Algorithmic systems used in healthcare contexts are primarily developed for the benefit of the public. It is therefore essential that these systems are trusted by the individuals for whose benefit they are deployed. Drawing inspiration from the principles embedded in the testing of the safety, efficacy and effectiveness of new medicinal products, concurrent design engineering and pro-fessional certification requirements, the authors propose, for the first time, a preliminary com-petency-based ‘Algorithmic Ethics’ Effectiveness Impact Assessment’ framework for developers of AI systems used in healthcare contexts. They concluded that this set of principles should en-compass the algorithmic systems ‘production lifecycle’, to guarantee the optimized use of the AI technologies, avoiding biases and discrimination while ensuring the best possible outcomes, simultaneously increasing decision-making capacity and the accuracy of the results. As AI is as good as those who program it and the system in which it operates, the robustness and trustworthiness of their ‘creators’ and ‘deployers’, should be fostered by a certification system guaranteeing the latter’s knowledge and understanding of ethical aspects as well as their com-petencies in integrating these aspects in trustworthy AI systems when used in healthcare con-texts.

In directional forming processes such as rolling and extrusion, the microstructure is strongly elongated in the forming direction. This results in a preferred alignment of the crystal orientations of the initially randomly oriented grains. These preferred orientations – the texture – and elongations of the grains are the cause of the material anisotropy. This anisotropy leads to phenomena such as earing, which occur during further forming processes, e.g., during deep drawing of sheet metal. Considering anisotropic properties in numerical simulations allows to investigate the effects of texture-dependent defects in forming processes and the development of possible solutions. Purely phenomenological models for modelling anisotropy work by fitting material parameters or applying measured R-values in experiments which are applied to all elements of the part and remain constant over the duration of the simulation. In contrast, methods such as the Visco-Plastic Self-Consistent (VPSC) model, which has been used in this work, provide a deeper insight into the development of the material microstructure. By experimentally measuring the initial texture and using it as an initial condition for the simulations, it is possible to predict the evolution of the microstructure and the resulting effect on the mechanical properties during forming operations. The results of the simulations with VPSC show good qualitative agreement with tests typically used for rolled stock.

This article develops duality principles and numerical results for a large class of non-convex variational models. The main results are based on fundamental tools of convex analysis, duality theory and calculus of variations. More specifically the approach is established for a class of non-convex functionals similar as those found in some models in phase transition. Finally, in the last section we present a concerning numerical example and the respective software.

Syndemics theory has been applied to study interactions between biomedical and social factors leading to clustering of diseases. Because syndemics theory focuses on interactions that enhance risk, the concept of vulnerability is central to this approach. We conducted a scoping review to better understand how syndemics theory helped to define, operationalize, and tackle issues of vulnerability during the COVID-19 pandemic. Original research, review, and opinion pieces elaborating on syndemics, vulnerability and COVID-19, published between December 2019 and October 2022 and available in PubMed, were eligible. We analysed 40 records and identified three framings of syndemics operating during this period: (1) interactions between COVID-19, diseases/health conditions and specific social factors; (2) interactions between COVID-19 and social determinants of health; and (3) impacts of COVID-19 on specific populations. Emerging conceptualizations described vulnerability to COVID-19 as a systemic issue; explained the impact of COVID-19 control measures on increased vulnerability; and presented COVID-19 as a syndemic on its own. However, this theory's potential for deepening our understanding of vulnerability during this pandemic was constrained by superficial explorations of the interactions between biomedical and social spheres, and insufficient theoretical and methodological support from the social sciences.

In the present work, an innovative range of foams, based on flax gum-filled epoxy resin was developed, reinforced or not by flax fibers. Foams and composites with different gum and epoxy resin contents were produced and characterized for mechanical and thermal performances. To enhance the organic flax gum filler's cross-linking, we exploited the oxidized components' reactivity with the amine hardener (isophorone diamine). We compared the materials obtained with those derived from the native components. Flax gum and fibers were primarily characterized by chemical analysis, NMR, and FTIR to evaluate the mild oxidation of native materials. The formation of chemical bonds between oxidized polymer chains, epoxy resin, and hardener has been evidenced by FTIR, and the materials were then studied by SEM, X-ray computed micro-tomography (CT), and submitted to mechanical and thermal tests. The relevance of oxidation treatment was highlighted, through a significant increase in density and mechanical performances (+36% and +81%, respectively for the 100% flax gum material). The positive effect of flax fibers on homogeneity evidenced through micro-CT analysis was also clearly addressed. This set of promising results paves the way for future development of fully flax-based insulation composite materials.

A novel scaffold design has been created to enhance tissue engineering and regenerative medicine by optimizing the controlled, prolonged release of hepatocyte growth factor (HGF), a powerful chemoattractant for endogenous mesenchymal stem cells. We present a new stacked scaffold that is made up of three different fibrin gel layers, each of which has HGF integrated into the matrix. The design attempts to preserve HGF's regenerative properties for long periods of time, which is necessary for complex tissue regeneration. These multi-layered fibrin gels have been mechanically evaluated using rheometry, and their degradation behavior has been studied using D-Dimer ELISA. Understanding the kinetics of HGF release from this novel scaffold configuration is essential for understanding HGF's long-term sustained bioactivity. A range of cell-based tests were carried out to verify the functionality of HGF following extended incorporation. These tests included 2-photon microscopy using phalloidin staining to examine cellular morphology, SEM analysis for scaffold-cell interactions, and scratch and scatter assays to assess migration and motility. The analyses show that the novel stacking scaffold promotes vital cellular processes for tissue regeneration in addition to supporting HGF's bioactivity. This scaffold design was developed for in situ tissue engineering. Using the body as a bioreactor, the scaffold should recruit mesenchymal stem cells from their niche thus combining the regenerative abilities of HGF and MSCs to promote tissue remodeling and wound repair.

Background Main treatment modality for spinal meningiomas (SM) is gross total resection (GTR). However, optimal timing of surgery, especially in cases with absent or mild neurological symptoms remains unclear. The aim of this study is to assess the impact of early-stage resection on neurological outcome, quality of life (QoL) and quality of care. The primary objective was a favorable neurological outcome (McCormick scale 1); Methods: We retrospectively analyzed data from patients operated on SM between 2011 and 2021. Patients with mild neurological symptoms preoperatively (McCormick scale 1 and 2) were compared to those with more severe neurological symptoms (McCormick scale 3-5). Disabilities and QoL were assessed according to validated questionnaires (SF36, ODI, NDI). Results: Age, spinal cord edema, thoracic localization, and spinal canal occupancy ratio were associated with more severe neurological symptoms (all p<.05). Patients presented with mild symptoms were associated with favorable neurological outcome (OR: 14.778 (95%CI 3.918-55.746, p<.001), which is associated with shorter hospitalization, better QoL and less disabilities (p<.05). Quality of care was comparable in both cohorts; Conclusions: Early surgical intervention of SM, before the development of severe neurological deficits, should be considered as it is associated with a favorable neurological outcome and quality of life.

The open data market is growing, driven by laws requiring governments to make data publicly available. However, the true value of this market lies in the products and services derived from open data. In Slovenia, the open data market has been growing since 2015, especially in the field of mobility. Platforms such as Avtolog.si facilitate the retrieval of vehicle data via vehicle identification numbers, while tocen.si, ojpp.si, and brezavta.si aggregate mobility data, focusing on sustainable and micromobile public transportation services. These platforms use open government data and private sector open data, and are freely accessible. This study examines the use of open data in the Slovenian mobility applications and similar solutions developed in other countries. By mapping these applications, we gain valuable insights into potential advances in the field, and provide a useful resource for future developers worldwide. By focusing on the socio-economic impact of these innovations, the study identifies methods for evaluating such applications. This approach highlights how transforming open data into user-friendly products and services can deepen our understanding of their broader societal and economic benefits. While open data is valuable in its own right, its full transformative potential is realized through innovative products that support sustainable lifestyles and promote environmentally conscious behavior.

CAD-CAE software companies have introduced numerous tools aimed at facilitating topology optimization through Finite Element Simulation, thereby enhancing accessibility for designers via user-friendly interfaces. However, the imposition of intricate constraint conditions or additional restrictions during calculations may introduce instability into the resultant outcomes. In this paper, an algorithm for updating the design variables called Adaptive Variable Design is proposed to keep the final design space volume of the optimized part always under the target value while giving the main algorithm multiple chances to update the optimization parameters and search for a valid design. This algorithm aims to producing results that are more conducive to manufacturability and potentially more straightforward in interpretation. A comparison between several commercial software and the proposed algorithm, implemented in MATLAB, is carried out to prove the robustness of the latter. By simulating identical parts under similar conditions, we seek to generate comparable results and underscore the advantages stemming from the adoption and comprehension of the proposed topology optimization methodology. Our findings reveal that the integrated enhancements within MATLAB pertaining to the topology optimization process yield favourable outcomes with respect to discretization, and the manufacturability of resultant geometries. Furthermore, we assert that the methodology evaluated within MATLAB holds promise for potential integration into commercial packages, thereby enhancing the efficiency of topology optimization processes.

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

Androgenetic alopecia, the most common cause of hair loss affecting both men and women, is typically treated using pharmaceutical options such as minoxidil and finasteride. While these medications work for many individuals, they are not suitable options for all. To date, the only non-pharmaceutical option that the United States Food and Drug Administration has cleared as a treatment for androgenetic alopecia is low-level laser therapy (LLLT). Various clinical trials utilizing LLLT devices of various types are available. However, a myriad of other physical treatments for this form of hair loss are reported in the literature. This review evaluated the effectiveness of microneedling, pulsed-electromagnetic field (PEMF) therapy, low-level laser therapy (LLLT), fractional laser therapy, and non-ablative laser therapy for the treatment of androgenetic alopecia (AGA). It also explores the potential of multimodal treatments combining these physical therapies. LLLT has the majority of evidence in the literature as a physical therapy for androgenetic alopecia. However, other physical treatments, such as non-ablative laser treatments, and multimodal approaches, such as PEMF-LLLT, seem to have the potential to be equally or more promising and merit further exploration.

Solid-state batteries (SSBs) have emerged as a promising alternative to conventional lithium-ion batteries, with notable advantages in safety, energy density, and longevity, yet the environmental implications of their lifecycle, from manufacturing to disposal, remain a critical concern. This review paper examines the environmental impacts associated with the production, use, and end-of-life management of SSBs, starting with the extraction and processing of raw materials which highlights significant natural resource consumption, energy use, and emissions. A comparative analysis with traditional battery manufacturing underscores the environmental hazards of novel materials specific to SSBs. The review also assesses the operational environmental impact of SSBs by evaluating their energy efficiency and carbon footprint in comparison to conventional batteries, followed by an exploration of end-of-life challenges including disposal risks, regulatory frameworks, and the shortcomings of existing waste management practices. A significant focus is placed on recycling and reuse strategies, reviewing current methodologies like mechanical, pyrometallurgical, and hydrometallurgical processes, along with emerging technologies that aim to overcome recycling barriers, while also analyzing the economic and technological challenges of these processes. Additionally, real-world case studies are presented, serving as benchmarks for best practices and highlighting lessons learned in the field. In conclusion, the paper identifies research gaps and future directions for reducing the environmental footprint of SSBs, underscoring the need for interdisciplinary collaboration to advance sustainable SSB technologies and contribute to balancing technological advancements with environmental stewardship, thereby supporting the transition to a more sustainable energy future.

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

The Saudi Vision 2030 is critical to boosting national development, notably in the construction industry. The construction industry is getting a lot of attention in a variety of ways, the most visible of which is the promotion of best practices, including project management office (PMO) applications. Hail province, like others, is experiencing project delivery issues. Thus, the purpose of this research is to explore the suitable PMO model for Hail public construction projects. A literature review included the drive factors for establishing PMO in construction firms, as well as PMO models and typologies that describe functions. Therefore, those drive factors and PMO models were subjected to a focus group to explore their suitability in the context of Hail. The research findings reveal that the Enterprise PMO is the main for Hail public construction pro-jects, followed respectively by the Program Management Office model and the Project Management Center of Excellence (PMCOE). This method of selection a PMO model is driving construction companies and related businesses to change in order to improve the sector while also ad-dressing construction project delivery challenges in Hail province.

Depression is the most common chronic mental illness and is characterized by low mood, insomnia, and affective disorders. However, the pathological mechanisms of depression remain unclear. Numerous studies have suggested that the ghrelin/GHSR system may be involved in the pathophysiologic process of depression. Ghrelin plays a dual role in the experimental animals, increasing depressed behavior and decreasing anxiety. By combining several neuropeptides and traditional neurotransmitter systems to construct neural networks, it modifies signals connected to depression. The present review emphasizes the role of ghrelin in neuritogenesis, astrocyte protection, inflammatory factor production, and endocrine disruption in depression. Furthermore, ghrelin/GHSR can activate multiple signaling pathways to produce antidepressant effects, including cAMP/CREB/BDNF, PI3K/Akt, Jak2/STAT3, and p38-MAPK. Given the antidepressant effects of ghrelin/GHSR1a system, it is expected to become a potential therapeutic target for the treatment of depression.

GRK2 and arrestin3, key players in the functional regulation of G protein-coupled receptors (GPCRs), are ubiquitinated by Mdm2, a nuclear protein. The agonist-induced increase in arrestin3 ubiquitination occurs in the nucleus, underscoring the crucial role of its nuclear translocation in this process. Agonist-induced increase in the ubiquitination of arrestin3 occurs in the nucleus, highlighting the pivotal role of its nuclear translocation in this process. In contrast, GRK2 cannot translocate into the nucleus, thus facilitating the cytosolic translocation of nuclear Mdm2 is required to ubiquitinate GRK2 in the cytosol. Among the cellular components and processes explored, arrestin, Gβγ, clathrin, and receptor phosphorylation were required for the nuclear import of arrestin3, ubiquitination of arrestin3 in the nucleus, nuclear export of Mdm2, and the ubiquitination of GRK2 in the cytosol. In conclusion, our findings demonstrate that agonist-induced ubiquitination of arrestin3 in the nucleus is interconnected to the cytosolic GRK2 ubiquitination.

Abstract: In this paper we describe how the administration of drone brood homoge-nate (DBH) influenced intestinal secretion of IgA, MUC-2, morphometric parameters, peripheral blood values, and expression of cytokines. A total of 12 pigs were divided into three groups, two experimental, first fed with 100 mg DBH.kg-1 (E1), second with 200 mg DBH.kg-1 (E2) of body weight, and a control (C) group without DBH in the di-et. Animals didn't show significant changes in average weight gains and feed conver-sion among evaluated groups. Feeding a diet containing 200 mg DBH.kg-1 of body weight in the E2 group produced an increase (p < 0.05) in the red cell distribution width, the percentage of metabolic activity of blood phagocytes in the peripheral blood, as well as splenic cell subpopulations CD4+ and CD21+. The villi height and their cutting surface were increased in the E2 group (p < 0.01), together with a gradual decrease in the concentration of MUC-2 and sIgA (p < 0.001). Upregulation of IL-8 (p < 0.0001), IL-10 (p < 0.05), and IL-18 (p < 0.001) was found mainly in E2 group. Results suggest, that supplementation of DBH in the feed of pigs formed optimal intestinal homeostasis.drone

In the ongoing transition from fossil fuels to renewable energies, advances are particularly expected regarding safe and cost-effective solutions. Publicising instances of such advances and emphasising safety considerations constitute the rationale for this communication. Knowing that high-strength steels can prove economically relevant for transporting hydrogen in pipelines by limiting the pipe wall thickness required to withstand high pressure, one advance relates to a bench designed for contributing to study the safety of the gaseous transport or renewable-energy-related buffer storage of hydrogen. That bench has been specifically implemented at technology readiness level TRL 6 for testing initially intact, damaged, or pre-notched DN 300/NPS 12, DN 600/NPS 24, and DN 900/NPS 36 pipe sections in order to provide data allowing for the possible validation of fully satisfactory predictive models in terms of hydrogen embrittlement and potential corollary ruin. The other advance relates to the reactivation of a previously fruitful applied research into mass solid-state hydrogen storage through a new public-private partnership. This latest development comes at a time when markets have started driving the hydrogen economy, bearing in mind that phase-change materials decisively allow levelling the heat transfers during the absorption/melting and solidification/desorption cycles and attaining an overall energy efficiency of up to 80% for MgH₂-based compacts doped with expanded natural graphite.

Bearing component damage contributes significantly to rotating machinery failures. It is vital for the rotor-bearing system to be in good condition to ensure proper functioning of the machine. Over recent decades, extensive research has been devoted to the condition monitoring of rotational machinery, with a particular focus on bearing health. This paper provides a comprehensive literature review of recent advancements in intelligent condition monitoring technologies for rolling element bearings. Fundamental monitoring strategies are introduced, covering various sensing, signal processing, and feature extraction techniques for detecting defects in rolling element bearings. While vibration-based monitoring remains prevalent, alternative sensor types are also explored, offering complementary diagnostic capabilities or detecting different defect types compared to accelerometers alone. Signal processing and feature extraction techniques, including time domain, frequency domain, and time-frequency domain analysis, are discussed for their ability to provide diverse perspectives for signal representation, revealing unique insights relevant to condition monitoring. Special attention is given to information fusion methodologies and the application of intelligent algorithms. Multisensor systems, whether homogeneous or heterogeneous, integrated with information fusion techniques, hold promise in enhancing accuracy and reliability by overcoming limitations associated with single sensor monitoring. Furthermore, the adoption of AI techniques, such as machine learning and metaheuristic optimisation, has led to significant advancements in condition monitoring, yielding successful outcomes in various studies. Finally, avenues for further advancements to improve monitoring accuracy and reliability are identified, offering insights into future research directions.

The field of microbial pathogenesis seeks to identify the agents and mechanisms responsible for disease causation. Since Robert Koch introduced postulates that were used to guide the characterization of microbial pathogens, technological advances have substantially increased the capacity to rapidly identify a causative infectious agent. Research efforts currently focus on causation at the molecular level with a search for virulence factors (VFs) that contribute to different stages of the infectious process. We note that the quest to identify and characterize VFs sometimes lacks scientific rigor, and this suggests a need to examine the epistemology of VF characterization. We took this premise as an opportunity to explore the epistemology of VF characterization. In this perspective, we discuss how the characterization of various gene products that evolved to facilitate bacterial survival in the broader environment have potentially been prematurely mischaracterized as VFs that contribute to pathogenesis in the context of human biology. Examples of the reasoning that can affect misinterpretation, or at least premature assignment of mechanistic causation, are provided. Our aim is to refine categorization of VFs by emphasizing a broader biological view of their origin.

(1) Background : When placing implants in the maxillary posterior region with insufficient alveolar bone, a maxillary sinus elevation is necessary. Autogenous bone, though biologically ideal, poses risks and discomfort due to donor site harvesting. Block-type autogenous tooth bone graft material, made from the patient’s own extracted tooth, offers similar biological stability without these drawbacks; (2) Methods : This study observed the progress of 19 implant patients who were treated with maxillary sinus elevation procedures using block-type autogenous tooth bone graft material at the Daegu Catholic University Medical Center. Extracted teeth were processed into demineralized tooth block bone. After elevating the sinus membrane, implants and the tooth bone graft material were placed in the space, and the bony window was repositioned. Postoperative evaluations through clinical observation and radiographic imaging assessed sinus membrane elevation, alveolar bone height increase, and implant osseointegration; (3) Results : Results showed proportional increases in alveolar bone height to the graft material size, with long-term stability. No postoperative complications occurred, even with sinus membrane perforation, and implants remained stable; (4) Conclusions : The study concludes that maxillary sinus lifts using block-type autogenous tooth bone graft material provide excellent bone induction and biocompatibility, making it a highly beneficial method for both dentists and patients.

Hybrid electric vehicles (HEVs) are perceived as a first step towards the future of sustainable transport. Of course, battery electric vehicles (EVs) are currently ideal for what is wanted to stand for transport in the future. The lack of infrastructure for these vehicles makes many potential users choose hybrid vehicles in these conditions. This paper analyzes the influence of the engine and electric motor of hybrid vehicles on their performances. Three engines with slightly different power and close characteristics were considered for configured models. Also, two electric motors with very different power but having a very close maximum continuous torque have been used in models. One is an induction motor, and the other is a permanent magnet synchronous motor. ADVISOR software has been used for vehicles configuration and simulation. Series and parallel hybrid vehicles have been considered. The main dynamic performances and the fuel consumption in two driving cycles were compared for the configured models. Three conventional models with the same engines used in HEVs have also been simulated for reference. The results highlight that in the case of HEVs, the choice of combination engine/electric motor is crucial in obtaining the best report between dynamic performances and low fuel consumption, and implicitly a low negative impact on the environment.

Background and Objectives: Pulmonary Hypertension (PH) is a clinical condition with high mortality rates, particularly in patients over 65. Current guidelines recommend assessing the Probability of Pulmonary Hypertension (PHP) using advanced echocardiography, before pro-ceeding to right heart catheterization. This study proposes using the common femoral vein (CFV), an accessible vein that reflects right atrial pressure, as an alternative method to assess the like-lihood of severe PHP. Materials and Methods: This prospective observational study included 175 emergency patients from three hospitals. Ultrasound assessed the Pulsed Wave Doppler (PW-Doppler) morphology of the CFV. This diagnostic yield for high PHP was evaluated along-side traditional ultrasound parameters (right-to-left ventricular basal diameter ratio greater than 1 (RV>LV), septal flattening, right ventricular outflow acceleration time of less than 105 ms and/or mesosystolic notching, pulmonary artery diameter greater than the aortic root diameter or over 25 mm, early pulmonary regurgitation maximum velocity >2.2 m/s, TAPSE/PASP less than 0.55, in-ferior vena cava (IVC) diameter over 21 mm with decreased inspiratory collapse, and right atrial (RA) area over 18 cm²). Results: The CFV's PW-Doppler cardiac pattern correlated strongly with high PHP, showing a sensitivity (Sn) of 72% and a specificity (Sp) of 96%. RA dilation and TAPSE/PASP < 0.55 also played significant diagnostic roles. Conclusions: The CFV's PW-Doppler cardiac pattern is an effective indicator of high PHP, allowing reliable exclusion of this condition when absent. This approach could simplify initial PHP evaluation in emergency settings or where echocardiographic resources are limited.

As the largest contributor of carbon emissions in China, the building sector currently relies mostly on enterprises’ own effort to report carbon emissions, which usually results in challenges related to information transparency and workload for regulatory bodies, who play an otherwise vital role in controlling the building sector’s carbon footprint. In this study, we established a novel regulatory model known as QCEPM (Quantitative Carbon Emission Prediction Model) by conducting multiple linear regression analysis using the quantities of concrete, rebar, and masonry structures as independent variables, and the embodied carbon emissions of a building as the dependent variable. We processed the data in the detailed quantity list of 20 multi-story frame-structure buildings and fed them to QCEPM for solution. Comparison of the QCEPM-calculated results against the time-consuming and error-prone manual calculation results suggested a mean absolute percentage error (MAPE) of 2.26%. Using this simplified model, regulatory bodies can efficiently supervise the embodied carbon emissions in multi-storey frame structures by setting up carbon quota for a project in its approval stage, allowing the construction enterprise to carry out dynamic control over the audited three most important building materials throughout a project’s planning and implementation phase.

The surface characterization of indium tin oxide (ITO) films was processed by oxygen (O2) plasma gas using a magnetron sputtering method of varying O2-plasma gas from 20 sccm to 100 sccm for potentially fostering in electronic devices applications on dye-sensitize solar cells (DSSC) in this work. In order to gain an outstanding performance rate with high-quality thin films, the affect of correlation between the electrical, optical, and morphology properties was significantly investigated. Clearly, the content of investigation exhibited that the films properties was changed by variation of the gas composition. These changes have contemporary relevance to the sputtering gas during the deposition process. To conclude, the greatest electrical properties was displayed by O2 -plasma gas flow rate of 20 sccm, which showed the lowest resistivity. In addition to this, the final products were practically fabricated to active layers for dye-sensitize solar cells (DSSC) applications. The highest efficiency of DSSC device was indicated of approximately 0.35% which was located by 40 sccm of the O2-plasma gas. Consequently, the study could be a possibility way of preparing ITO thin films with improved special properties of substantial applications for solar cells devices in the near future.

The use of thiosemicarbazones (TSCs) as ligands for the functionalization of nanoparticles (NP) for various purposes, such as the covalent immobilization is fueled by their modular character (thiosemicarbazides + carbonyl compound), allowing enormously broad variation of up to four substituents on the main R1R2C=N(1)–NH–C(S)–N(4)R3R4 core. For R1 and R2 we introduced di-2-pyridyl ketone for the coordination of metals and 9-anthraldehyde for luminescence. R3 and R4 substituents were varied for various purposes. Amino acids were functionalized at the N4 position to [R1R2TSC–spacer–amino acid] conjugates for future peptide conjugation or for direct anchoring to NP via their carboxylic function. Further direct NP anchoring functions such as phosphonic acid (OP(OH)2), glucose, o-hydroquinone, OH, and thiol (SH) were introduced with or without separation through hydrocarbon spacer units such as phenyl, cyclohexyl, benzyl, ethyl and methyl in [R1R2TSC–spacer–anchor group] conjugates. [R1R2TSC–spacer–end group] conjugates including OH, S-Bn (Bn = benzyl), NH-Boc (Boc = tert-butyloxycarbonyl), COOtBu, or N3 end groups were produced for the facile formation of amide, ester, or triazine conjugates through click chemistry. The synthesis of the thiosemicarbazides H2NH–C(S)–NR3R4 starting from amines, including amino acids, SCCl2 or CS2, and hydrazine and their condensation with dipyridyl ketone and anthraldehyde lead finally to 34 new TSC derivatives. They were synthesized in up to six steps with overall yields ranging from 10 to 85% and were characterized by a combination of elemental analyses, mass spectrometry, and magnetic nuclear resonance spectroscopy. UV-vis absorption and photoluminescence spectroscopy allowed to easily trace the dipyridyl imine and anthracene chromophores.

Seawater contamination is a global challenge due to its hazardous effects on marine organisms and human health. Twenty-three surface seawater samples were collected from Al Lith intertidal area along the Saudi Red Sea coast to evaluate the ecological risks and document the potential sources of Cr, Cd, Fe, Zn, and Pb. Contamination factor (CF), contamination degree (Cd), water quality index (WQI), and heavy metal pollution index (HPI), as well as multivariate tools were applied. The averages of HMs (μg/L) had the following order: Zn (6.616) &gt; Pb (0.284) &gt; Cd and Cr (0.268) &gt; Fe (0.197). Results of CF showed moderate contamination of seawater with Cd and low contamination for Cr, Fe, Zn, and Pb. However, 26.09% of the samples showed considerable contamination for Cd. Average Cd values revealed low contamination for HMs, while 17.39% of the samples showed moderate contamination. HPI average values indicated medium pollution for Al Lith seawater, meanwhile 13 samples reported high pollution. The higher HPI values were reported in samples characterized by higher concentration of HMs, particularly Cd and Zn. Correlation matrix and principal component analysis suggested anthropogenic sources for Pb and Zn, mostly from industrial and agricultural effluents, landfilling and domestic wastewaters, apart from their natural sources.

In the field of 2-D image processing and computer vision, accurately detecting and segmenting objects in scenarios where they overlap or are obscured remains a challenge. This difficulty is worse in the analysis of shoeprints used in forensic investigations because they are embedded in noisy environments such as the ground and can be indistinct. Traditional Convolutional Neural Networks (CNNs), despite their success in various image analysis tasks, struggle with accurately delineating overlapping objects due to the complexity of segmenting intertwined textures and boundaries against a background of noise. This study introduces employs the YOLO (You Only Look Once) model enhanced by edge detection and image segmentation techniques to improve the detection of overlapping shoeprints. By focusing on the critical boundary information between shoeprint textures and the ground, our method demonstrates improvements in sensitivity and precision, achieving confidence levels above 85% for minimally overlapped images and maintaining above 70% for extensively overlapped instances. Heatmaps of convolution layers were generated to show how the network converges towards successful detection using these enhancements. This research may provide a potential methodology for addressing the broader challenge of detecting multiple overlapping objects against noisy backgrounds.

Background/Objectives Bowel endometriosis (BE) is defined as the presence of endometrial-like tissue in the muscular layer of the bowel wall. When BE does not cause severe obstruction to fecal transit, not leading to (sub)occlusive symptoms, the decision to operate becomes challenging as intestinal surgery is associated with higher complication rates and long-term bowel dysfunction. The aim of this cross-sectional study is to evaluate the quality of life (QoL) in patients with BE undergoing medical therapy or expectant management, investigating the impact of characteristics of BE nodules on QoL and intestinal function. Methods A retrospective cross-sectional analysis was conducted on 580 patients with BE who did not undergo surgery but were treated conservatively by medical therapy or expectant management between January 2017 and August 2022. The diagnosis of BE was done by transvaginal ultrasound and confirmed at double contrast barium enema. After at least one year of follow-up, QoL and intestinal function of patients were evaluated by the Endometriosis Health Profile-5 (EHP-5) questionnaire and Bowel Endometriosis Symptom score (BENS), whereas pain symptoms were assessed by the Visual Analogic Scale (VAS 0-10). Statistical analysis was performed to investigate possible associations between QoL and characteristics of bowel nodules (dimension, location, and evidence of stenosis) as well as type and length of eventual medical therapy. Results Patients with BE had a satisfying overall QoL with a mean EHP-5 score of 105.42 ± 99.98 points and VAS lower than 3 for all pain domains; additionally, they did not show a significant impartment of bowel function with mean BENS score of 4.89 ± 5.28 points. Notably, patients under medical therapy had a better QoL than patients without therapy (p

Background: The increase in the prevalence of obesity in South Africa is a problem and weight management play an important role in the treatment of the high prevalence. For this purpose, a quantitative study was carried out using a structured questionnaire to assess predictors of attempt and failure to lose weight. Methods: One thousand and fifty adults were enrolled in the study and 54% (n=562) were overweight and obese (BMI &gt;/25kg/m2). Descriptive statistics were analysed. Inferential statistical tests (chi-square tests, logistic regression, and Pearson’s correlation coefficients) were used to determine the relationship between variables. Results: The results revealed that age, sex, marital status, educational level, employment status, income level, area of residence, ethnic groups, and self-perceived BMI (normal weight, overweight, and obese) were predictors of attempt and failure to lose weight. There was a positive correlation between self-perceived BMI and the attempt and failure to lose weight. Conclusion: Weight management is important in the realm of public health and can be regarded as an investment in the population, as it leads people toward weight control strategies grounded in empirical evidence. Additionally, the findings can inform public health policies and interventions to improve weight management strategies at the population level.

Seed longevity is a crucial trait for the seed industry and genetic resource preservation. To develop excellent cultivars with extended seed lifespans, it is important to understand the mechanism of keeping seed germinability long-term and to find useful genetic resources as prospective breeding materials. This study was conducted to identify the best cultivars with a high and stable seed longevity trait in the germplasm of rice (Oryza sativa L.) and to analyse the correlation between seed longevity and embryonic RNA integrity. Seeds from 69 cultivars of the world rice core collection selected by the NIAS in Japan were harvested in different years and subjected to long-term storage or controlled deterioration treatment (CDT). The long-term storage (4 °C, RH under 35%, 10 years) was performed on seeds harvested in 2010 and 2013. The seeds harvested in 2016 and 2019 were used for CDT (36 °C, RH of 80%, 40 days). Seed longevity and embryonic RNA integrity were estimated by a decrease in germination rate and RNA integrity number (RIN) after long-term storage, or CDT. The RIN value was obtained by electrophoresis of total RNA extracted from seed embryos. Seeds of ‘Vandaran (Indica)’, ‘Tupa 729 (Japonica)’, and ‘Badari Dhan (Indica)’ consistently showed higher seed longevity and embryonic RNA integrity both under long-term storage and CDT conditions, regardless of the harvest year. A strong correlation (R2 = 0.93) was observed between germination rates and RIN values of the seeds after long-term storage or CDT among nine cultivars selected based on differences in their seed longevity. The study findings revealed the relationship between rice seed longevity and embryo RNA stability and suggested potential breeding materials, including both Japonica and Indica cultivars, for improving rice seed longevity.

Citizen science has emerged as a potent approach for environmental monitoring, leveraging the collective efforts of volunteers to gather data at unprecedented scales. Within the framework of the I-CHANGE project, MeteoTracker, a citizen science initiative, was employed to collect and analyze meteorological measurements. This paper presents the results of our analysis, demonstrating the effectiveness of citizen science in generating valuable environmental data. Through MeteoTracker, volunteers contributed to a comprehensive dataset, enabling insights into local weather patterns and trends. Our findings underscore the potential of citizen science to augment traditional monitoring efforts and inform decision-making processes in environmental research and management. The paper discusses the methodology employed, including data collection and statistical analysis techniques. Results highlight the reliability and accuracy of citizen-generated data, as well as the strengths of the MeteoTracker platform. The implications of our findings for environmental research, policy development, and public engagement are discussed, along with recommendations for enhancing the effectiveness of citizen science initiatives in environmental monitoring.

The study looks at how joining live video chats with native English speakers on TikTok helps people who are learning English feel more ready to talk in English and less nervous about it. This study looks at EFL students who join TikTok live sessions. The researcher wants to understand how confident and nervous the students feel when they communicate. He uses qualitative research methods to do this. The study shows that using TikTok in a fun and calming way could help people learn a new language and reduce feelings of worry. This is helpful for teachers and language experts who want to use social media to help people learn languages.

Due to advances in power electronics technology and the evolution of automation devices, the number of electrical devices that are sensitive to power quality is rapidly increasing, and for this reason, users are increasing their demand for high quality. To meet power quality demands, many power conversion devices are used, including dynamic voltage restorers (DVRs). DVRs are rec-ognized as devices that can effectively manage problems such as voltage segment, swells, and harmonics. DVR control requires many samples for harmonic compensation, which has the dis-advantage of being complicated to implement due to fast digital signal processing computation and the application of the cyclic discrete Fourier transform. In this paper, a high-precision DVR system configuration is proposed that compensates for harmonics using a periodically equivalent time-interval sampling technique and a novel circular structured memory filter. The proposed circular structured multi-pointer memory filter is an effective filter algorithm for high-precision input voltage measurement because it can remove noise and compensate for the delay of the phase angle of the filter in voltage measurement. A simulation and DVR prototype system was built, and the feasibility and effectiveness of the phase angle multi-filter voltage detection method and the compensation method were verified by experiments.

This study explores the properties and behavior of bi-close-to-convex functions, introducing new subclasses defined by their relationship with fractional differential operator and bi-univalent functions. Using the Faber polynomial technique, we derive upper bounds for the n^{th} coefficient of functions in these classes. We also investigate the erratic behavior of initial coefficients in bi-close-to-convex functions, as characterized by the (λ,q)-fractional differintegral operator. Furthermore, we address Fekete-Szegö problems and present notable findings from our investigation, contributing to the continued growth and refinement of geometric function theory, yielding new insights and practical uses.

In an era characterized by technological disruption and unprecedented challenges posed by the COVID-19 pandemic, this scholarly investigation explores the role of Artificial Intelligence (AI) in shaping Leadership Dynamics in Higher Education Institutions (LDHE) within the specific socio-cultural and regulatory environment of China. Utilizing Structural Equation Modeling (SEM) as operationalized through the SMART_PLS software, this research harnessed data from a robust sample of 381 key stakeholders in China higher education. The study's empirical findings indicate a noteworthy impact of AI-informed decision-making processes on LDHE, which was further mediated by the variable of AI Literacy among leadership. Moreover, the consequences of the ongoing pandemic served as a moderating factor in this relationship. These nuanced outcomes not only contribute to the theoretical discourse surrounding educational leadership and technological integration but also provide actionable insights for policy formulation and institutional strategies in an increasingly complex educational landscape.

Atmospheric pollens were investigated using the Lanzoni VPSS 2000 device for 2 years between 2012 and 2013 in the Sarıkamış district of Kars province, one of the highest regions of Türkiye. A total of 37909 pollen grains were collected; 15,298 pollen grains in 2012 and 22611 pollen grains in 2013. Out of 43 identified taxa, 21 were arboreal and 22 were non arboreal. Pollen from arboreal plants accounted for 36.34% (13778 pollen) of the total, while pollen from non arboreal plants accounted for 63.56% (24095 pollen). The most frequent arboreal plants pollen in the Sarıkamış atmosphere were Pinaceae (29.79%), Cupressaceae/Taxaceae (2.54%), and Morus (1.30%). The main non arboreal plants pollen in the atmosphere of Sarıkamış were Poaceae (44.60%), Artemisia (2.98%), Amaranthaceae (2.79%), Rumex (2.41%), Urticaceae (2.33%), Plantago (2.19%), and Boraginaceae (1.40%). The maximum pollen concentration was observed in June.

Let $\mathcal{\mathcal{S}}_{\cos}^{\ast}$ denote the class of normalized analytic functions $f$ in the open unit disk $\mathbb{D}$ satisfying the subordination $\dfrac{zf^{\prime}(z)}{f(z)}\prec\cos z$. In the second section of this article we find the sharp upper bounds for the initial coefficients $a_{3}$, $a_{4}$ and $a_{5}$ and the sharp upper bound for module of the Hankel determinant $|H_{2,3}(f)|$ for the functions from the class $\mathcal{S}_{\cos}^{\ast}$. The first result of the next section deals with the sharp upper bounds of the logarithmic coefficients $\gamma_{3}$ and $\gamma_{4}$ and we found in addition the sharp upper bound for $\left|H_{2,2}\left(F_{f}/2\right)\right|$. For obtaining these results we used the very useful and appropriate Lemma 2.4 of N.E. Cho et al. [Filomat 34(6) (2020), 2061--2072], and the technique for finding the maximum value of a three variable function on a closed cuboid. All the maximum found values were checked by using MAPLE\texttrademark{} computare software, and we also found the extremal functions in each cases. All of our present results are the best ones and give sharp versions of those recently published in [Hacet. J. Math. Stat. 52, 596--618, 2023].

Researchers are increasingly concerned about microplastics (MPs) since they have proven to be detrimental to the environment and humans. They not only contribute to the accumulation of plastics in the environment, but they can also help spread micropollutants through absorption. MPs have entered the environment through a variety of channels, including direct discharge through human activities, the textile industry, and wastewater treatment systems. Wastewater treatment plants (WWTPs) are seen as the final line of defense, forming a barrier between MPs and the environment. The most common MPs found in wastewater are polyethylene terephthalate (PET), polyethylene (PE), polypropylene (PP), and polystyrene. The purpose of this study is to investigate and measure the efficacy of conventional and advanced technologies in removing microplastic. The fate of MPs in WWTPs and their impact on various wastewater treatment processes will be thoroughly examined. Both conventional and advanced methods of treatment will be discussed. Conventional methods include coagulation/flocculation, sedimentation, and filtration. Advanced treatment methods that will be discussed include membrane bioreactors, rapid sand filtration, electrocoagulation, and photocatalytic degradation. Despite the high removal of MPs, WWTPs remain an important entry point into aquatic and terrestrial systems due to the large volumes involved and the quantity of sludge reused through land application. Also, the complex interactions between MPs and other environmental pollutants may broaden MPs' effects on wastewater treatment processes, which have yet to be fully researched. Furthermore, potential issues with MP removal from treatment procedures and microplastic remediation techniques in drinking water was discussed.

Unmanned Aerial Vehicles (UAVs) equipped with hyperspectral imagers have emerged as an essential technology for the characterization of inland water bodies. The high spectral and spatial resolutions of these systems enable the retrieval of a plethora of optically-active water quality parameters via band ratio algorithms and machine learning methods. However, fitting and validating these models requires access to sufficient quantities of in situ reference data which are time-consuming and expensive to obtain. In this study, we demonstrate how the Generative Topographic Mapping (GTM), a Bayesian realization of the Self-organizing Map, can be used to visualize high-dimensional hyperspectral imagery and extract spectral signatures corresponding to unique endmembers present in the water. Using data collected across a North Texas pond, we first apply the GTM to visualize the distribution of captured reflectance spectra revealing small-scale spatial variability of water composition. Next, we demonstrate how the nodes of the fitted GTM can be interpreted as unique spectral endmembers. Using extracted endmembers together with the normalized spectral similarity score, we are able to efficiently map the abundance of near shore algae as well as the evolution of a rhodamine tracer dye used to simulate water contamination by a localized source.

Establishing systemic communications between the project plan, stakeholders, and the organization through integrated management meets stakeholders' demands and managerial expectations in project-oriented organizations. Performance assessment can be defined as a control system in any company that reviews its daily operations and evaluates how well it has achieved its goals. This study aims to investigate the impact of an integrated project management system on the financial performance of the Organization for Renovation, Development, and Equipment of Schools. This applied research is descriptive-analytical. The statistical population comprises 2,700 employees of the organization, with a sample size of 340 individuals examined. The reliability of the designed questionnaire was confirmed by experts in the organization using Cronbach's alpha (α=0.91). Data were analyzed using SPSS version 20 and AMOS 18 software through descriptive statistics and confirmatory factor analysis. The results indicate that the seven dimensions of the integrated project management system (cost management, quality management and continuous control, change management, systems and information management, human resources management, interaction and communication management, procurement management) have a positive and significant impact on the financial performance of the Organization for Renovation, Development, and Equipment of Schools.

Decades of illegal hunting (poaching) have adversely affected wildlife populations and thereby limited sustainable wildlife conservation in the Luangwa Valley, Zambia. Despite intervention efforts to address the problem, illegal hunting of wildlife has persisted. Therefore, this study was conducted to understand the persistence of illegal hunting by investigating drivers of poaching and intervention measures using mixed-methods approach. Stratified random sampling was used to collect data from 346 respondents through structured questionnaires. Purposive sampling was used to collect data through nine (9) focus group discussions and three (3) in-depth interviews with experts. The study revealed that persistent illegal hunting was mainly driven by people’s critical needs for survival and sustaining livelihoods and not by inadequate law enforcement as presumed by resource managers. Although law enforcement was the most prevalent intervention measure, it did not deter local illegal hunters because the main motivations for poaching were not effectively addressed. The key implication of findings is that where illegal harvesting of natural resources in protected areas by local resource users is driven by people’s critical needs for survival and livelihoods which are ineffectively addressed, illegal harvesting may persist even with increased law enforcement. The study provides empirical evidence, novel conceptual knowledge and understanding on how prevalent drivers of poaching and other factors may have influenced persistent illegal hunting in the Luangwa Valley.

This study explored differences in student-athletes’ symptoms of depression, anxiety, and stress pre- to post-COVID-19 pandemic. The WHO reported a 25% increase in depression and anxiety rates worldwide with young people disproportionately affected. Student-athletes face many stressors related to their sporting and academic feats but what is not known is how the COVID-19 pandemic affected their experiences of mental illness. A multiple cohort cross-sectional study design was employed, and data collected using physical and online surveys. Participants (M age = 19.98 years, SD = 1.50) were recruited from UK universities (N = 807; 427 pre-pandemic cohort, 380 post-pandemic cohort). Results revealed statistically significant differences in mean depression, anxiety, and stress scores between cohorts. Scores for the post-pandemic cohort were significantly higher than pre-pandemic, suggesting a worsening of symptom severity. Distributions of student-athletes across categories of symptom severity also worsened for depressive and anxiety symptoms post-pandemic and were skewed towards more severe categories. Symptoms of de-pression, anxiety, and stress were a concern pre-pandemic. Rates are higher in the post-pandemic cohort, suggesting a worsening of symptoms. This data adds to evidence on student-athletes’ symptoms of mental illness by exploring a UK sample and comparing scores pre- and post-pandemic.

The regulatory approvals of tumor agnostic therapies have led to reevaluation of the drug development process. Conventional models of drug development are histology-based. On the other hand, tumor agnostic drug development of a new drug (or combination) focuses on targeting a common genomic biomarker in multiple cancers, regardless of histology. Basket-like clinical trials with multiple cohorts allow clinicians to evaluate pan-cancer efficacy and toxicity. There are currently 8 tumor agnostic approvals granted by the Food and Drug Administration (FDA). This includes two immune checkpoint inhibitors, and 5 targeted therapy agents. Pembrolizumab is an anti-PD-1 antibody that was the first FDA approved tumor agnostic treatment for unresectable or metastatic microsatellite instability-high (MSI-H) or deficient mismatch repair (dMMR) solid tumors in 2017. It was later approved for tumor mutational burden-high (TMB-H) solid tumors, although the TMB cut-off used is still debated. Subsequently, in 2021, another anti-PD-1 antibody, Dostarlimab was also approved for dMMR solid tumors in the refractory setting. Patients with fusion-positive cancers are typically difficult to treat due to their rare prevalence and distribution. Gene rearrangements or fusions are present in a variety of tumors. neurotrophic tyrosine kinase (NTRK) fusions are present in a range of pediatric and adult solid tumors in varying frequency. Larotrectinib and entrectinib were approved for neurotrophic tyrosine kinase (NTRK) fusion-positive cancers. Similarly, selpercatinib was approved for Rearranged During Transfection (RET) fusion-positive solid tumors. FDA approved the first combination therapy of dabrafenib, a B-Raf Proto-Oncogene Serine/Threonine Kinase (BRAF) inhibitor, plus trametinib, a mitogen-activated protein kinase (MEK) inhibitor for patients 6 months or older with unresectable or metastatic tumors (except colorectal cancer) carrying BRAFV600E mutation. The most recent FDA tumor agnostic approval is of fam-trastuzumab deruxtecan-nxki (T-Dxd) for HER2-positive solid tumors. It is important to identify and expeditiously develop drugs that have the potential to provide clinical benefit across tumor types.

Breast cancer poses a global health challenge, yet the influence of ethnicity on the tumor microenvironment (TME) remains understudied. In this investigation, we examined immune cell infiltration in 230 breast cancer samples, emphasizing diverse ethnic populations. Leveraging tissue microarrays (TMAs) and core samples, we applied multiplex immunofluorescence (mIF) to dissect immune cell subtypes across TME regions. Our analysis revealed distinct immune cell distribution patterns, particularly enriched in aggressive molecular subtypes triple-negative and HER2-positive tumors. We observed significant correlations between immune cell abundance and key clinicopathological parameters, including tumor size, lymph node involvement, and patient overall survival. Notably, immune cell location within different TME regions showed varying correlations with clinicopathologic parameters. Additionally, ethnicities exhibited diverse distributions of cells, with certain ethnicities showing higher abundance compared to others. In TMA samples, patients of Chinese and Caribbean origin displayed significantly lower numbers of B cells, TAMs, and FOXP3-positive cells. These findings highlight the intricate interplay between immune cells and breast cancer progression, with implications for personalized treatment strategies. Moving forward, integrating advanced imaging techniques, and exploring immune cell heterogeneity in diverse ethnic cohorts can uncover novel immune signatures and guide tailored immunotherapeutic interventions, ultimately improving breast cancer management.

This study aimed to explore the fermentation behavior of selected potential probiotic strains during sorghum fermentation, considering their microbial counts, pH levels, and antibacterial activity, their ability to break down starch. The fermentation processes were conducted in the presence and absence of glucose, and the lactic acid bacterial strains underwent controlled fermentation to assess microbial counts, amylase activity, pH, and lactic acid levels in the presence and absence of glucose. In addition, the inhibitory activity of these potential probiotic strains against pathogenic bacteria (Salmonella typhimurium, Escherichia coli, and Staph-ylococcus aureus) was examined through co-culturing. The results demonstrated that all nine Lactobacillus strains exhibited robust growth in both sugar and sugar-free fermentation experiments. Glucose supple-mentation significantly enhanced lactic acid yield which was in a range of 0.19-0.52 % compared to fer-mentation without glucose with a range of 0.03-0.29 %. The selected Lactobacillus strains effectively lowered the pH to less than 4 after 24 hours, producing substantial lactic acid. Notably, in the absence of glucose, only Lb. helveticus D7 and Lb. amylolyticus D12 achieved pH levels below 4 after 8 hours, producing the highest lactic acid amounts of 0.27 and 0.29 % after 24 hours, respectively. Amylase activity was detected on two strains D7 and D12. Furthermore, most of the tested Lactobacillus strains demonstrated complete inhibition of pathogen growth after 24 hours of co-culturing, suggesting their potential for enhancing the safety quality of sorghum-based fermented products.

In this study, the fundamentals of electroencephalography signals, their categorization into frequency sub-bands, the circuitry used for their acquisition, and the impact of noise interference on signal acquisition are examined. Additionally, design specifications for medical-grade and research-grade EEG circuits and a comprehensive analysis of various analog front-end architectures for electroencephalograph (EEG) circuit design are presented. Three distinct selected case studies are examined in terms of comparative evaluation with generic EEG circuit design templates. Moreover, a novel one-channel battery-supplied EEG analog front-end circuit designed to address the requirements of usage protocols containing strong com-pound muscle movements is introduced. Furthermore, a realistic input signal generator circuit is proposed that models the human body and the Electromagnetic Interference from its surroundings. Experimental simulations are conducted in 50 Hz and 60 Hz electrical grid environments to evaluate the performance of the novel design. The results demonstrate the efficacy of the proposed system, particularly in terms of bandwidth, portability, common mode rejection ratio , gain, suppression of muscle movement artifacts, electrostatic discharge and leakage current protection. Conclusively, the novel design is cost-effective and suitable for both commercial and research single-channel EEG applications. It can be easily incorporated in Brain Computer Interfaces and neurofeedback training systems.

This study analyzes the relevance of governance structure for efficiency in revenue collection by Brazilian Water Utilities (WUs). Data was collected from the National Information System on Sanitation (SNIS) for 127 Brazilian WUs, covering a balanced longitudinal panel from 2018 to 2022. Governance structures evaluated included Ownership (public or private) and Corporatization (publicly traded or not). In scientific databases, we did not find studies on the efficiency of specific WUs in collecting customer bills for services rendered and its relationships with this type of governance; thus, this would be the main innovative contribution of the study to the previous literature. In the first stage, the study utilized the Dynamic Slack Based Model (DSBM) to assess revenue collection efficiency. In the second stage, an econometric model with Generalized Estimating Equations (GEE) to explain the efficiency. The findings revealed a global average inefficiency of 50.47% in revenue collection. Corporatization was linked to higher collection efficiencies, while ownership type was significant, but with lower collection efficiency. Factors such as tariff accessibility, urbanization, and the COVID-19 pandemic also influenced efficiency. The study suggests regulatory bodies should consider these insights to implement policies that prevent inefficiencies from affecting the tariff system for services.

A surprising insight from the advent of genomic sequencing was that many genes are deeply conserved during evolution. With a particular focus on genes that interact with light in animals, I explore the metaphor of genetic toolkits, which can be operationalized as lists of genes involved in a trait of interest. A fascinating observation is that genes of a toolkit are often used again and again during convergent evolution, sometimes across vast phylogenetic distances. Such a pattern in the evolution of toolkits requires three different stages: origin, maintenance, and redeployment of the genes. The functional origins of toolkit genes might often be rooted in interactions with external environments. The origins of light interacting genes in particular may be tied to ancient responses to photo-oxidative stress, inspiring questions about the extent to which the evolution of other toolkits were also impacted by stress. Maintenance of genetic toolkits over long evolutionary timescales requires gene multifunctionality to prevent gene loss when a trait of interest is absent. Finally, the deployment of toolkit genes in convergently evolved traits like eyes sometimes involves the repeated use of similar, ancient genes but other times involves different genes specific to each convergent origin. How often a particular gene family is used time and again for the same function may depend on how many possible biological solutions are available. When few solutions exist and are maintained, evolution is constrained to use the same genes over and over. However, when many different solutions are possible, the innovative possibilities of evolution are often on display. Therefore, a focus on genetic toolkits highlights the combination of legacy plus innovation that drives the evolution of biological diversity.

In these last years, self-healing polymers have emerged as a topic of considerable interest owing to their capability to partially restore material properties and thereby extend the product's lifespan. The main purpose of this study is to investigate the nano-indentation response in terms of hardness, reduced modulus, contact depth and coefficient of friction of a self-healing resin developed for use in aeronautical and aerospace contexts. To achieve this, the bifunctional epoxy precursor underwent tailored functionalization to improve its toughness, facilitating effective compatibilization with a rubber phase dispersed within the host epoxy resin. This approach aimed to highlight the significant impact of the quantity and distribution of rubber domains within the resin on enhancing its mechanical properties. The main results are that pure resin exhibits a higher hardness (about 36.7% more) and reduced modulus (about 7% more), consequently leading to a lower contact depth and coefficient of friction (11.4% less) compared to other formulations that, conversely, are well-suited for preserving damage from mechanical stresses due to their capabilities in absorbing mechanical energy. Furthermore, finite element method (FEM) simulations of the nanoindentation process were conducted. The numerical results were meticulously compared with experimental data, demonstrating a good agreement. This validation of the FEM model underscores its efficacy in predicting the mechanical behavior of nanocomposite materials under nanoindentation. The proposed investigation aims to contribute knowledge and optimization tips about self-healing resins.

Melatonin, a naturally occurring chemical, has pleiotropic effects across various species. It plays a vital role in animals by regulating the body clock, while in plants, it is known to resist aging. Melatonin is associated with various plant physiological processes, including stress response, plant growth, and flowering time. It has prospects in enhancing and promoting plant growth and development, as well as in strengthening crop yield and increasing sustainability in agriculture. This review summarized the potential roles of melatonin in several plant species, as well as its biosynthetic modes. In addition, we described the recently uncovered melatonin features in plants, summarized the issues and challenges facing plant melatonin research and some feasible solution ideas are proposed.

The construction of a house with a stage structure is the uniqueness of Banjarmasin's swampland. Particularly, foundations for swampy terrain necessitate special handling. Building material defects and the basic inability to modify the use and design of wood pillar foundations are the main causes of house building problems. The very limited capacity of a wooden pillar foundation makes house buildings collapse frequently. The aim of the study is to determine the weaknesses of the wooden pillar foundations by examining the indications of damage to the house structure. Field observation investigations, including housing and individual object observations, will be carried out at multiple construction sites in Banjarmasin (Indonesia) as part of this study. The way the data is presented is descriptive. A wooden pillar foundation, which is a frequently used foundation, has a limited load bearing capacity. Because that, there has been no related research that addresses the issue of how this foundation damage. The aim of the study is to determine the early signs of swamp building collapse in the wooden pillar foundations weaknesses by examining the indications of damage to the house structure. The weak construction of a wooden pillar foundation explains some indications of house building damage, such as broken wooden pillars and floor settlement. The existence of evidence that there is a broken 'sunduk’ element is one of the causes of damage to this foundation

The development and utilization of wind energy is of great significance to the sustainable development of China's economy and the realization of the goal of "dual carbon". Under the typhoon system, the randomness and volatility of wind speed become an important basis for affecting the energy efficiency utilization and design of wind turbines. Therefore, based on wind speed and wind direction data at 10m, 30m, 50m and 70m heights of a wind power tower in Yancheng, Jiangsu Province, this paper analyzes the change characteristics of wind speed and wind direction by using BFAST method and Hurst index. Based on typhoon body data, topographic data and mesoscale system wind direction data, the causes of the occurrence and development of wind speed and wind direction of wind tower are further analyzed, and a conclusion is drawn: (1) In BEAST method, there are 5, 5, 6 and 6 change points at the height of 10m, 30m, 50m and 70m respectively. Among them, the change points at the height of 10m, 30m and 50m all change before and after node 325, and the change time point at the height of 70m is inconsistent with other heights. Hurst index results show that the inconsistency at 70m altitude is stronger than that at other altitudes. (2) The wind direction sequence at 10m, 30m, 50m and 70m altitude is fitted by stages, and the direction of wind direction is SE-E-SE-SW-W-NW, where, At the height of 70m, the deviation of the fitting trend line from other altitudes is larger in the wind speed strengthening stage and weakening stage. (3) The wind speed at the height of 10m and 70m has different response degrees to the typhoon body. The correlation between the wind speed and the distance between the wind measurement tower and the typhoon near the center is stronger at the height of 10m than at the height of 70m. The surface type and the wind direction of the mesoscale system also have certain effects on the wind speed and direction. In this paper, the change characteristics and influencing factors of wind speed and direction of wind tower are studied, which provides methods and theoretical support for the study of short-term wind speed when typhoon passes through, and provides reliable support for the selection of wind power forecast indicators and the selection and design of wind turbines under extreme gale weather systems.

The increasing deployment of intermittent renewable energy sources necessitates effective methods for balancing the electrical grid to ensure stability and safety. Energy storage systems that can store excess electrical power during periods of low demand and release it during high demand are crucial for both short-term and long-term applications. Power-to-Gas is an innovative energy storage solution that converts surplus renewable electricity into gas fuels, such as hydrogen, which can be stored and used later. This hydrogen can serve multiple purposes, including energy storage and as fuel for transportation modes like cars, trams, trains, and buses. While most hydrogen today is derived from fossil fuels, solid-oxide electrolysis (SOE) offers a cleaner alternative by producing hydrogen without harmful emissions. SOE is also the most efficient method of electrolysis. This study aims to determine the operational parameters for an SOE system, including lower heating value (LHV)-based efficiency and total input power, using a mathematical model. Results are presented for three different operating temperatures and four different steam utilization ratios. The paper is structured as follows: the introduction provides the context and motivation for the study; the second section outlines the fundamentals of electrolysis and its various types; the third section delves into solid-oxide electrolysis and electrolyser systems; the fourth section describes the methodology, including the mathematical formulation and simulation software used; the fifth section presents the calculation results and conclusions; and the final section summarizes the findings.

This study investigates the impact of integrated marketing strategies on supply chain efficiency in retail businesses. Through qualitative research methods including in-depth interviews and case studies, the study explores how aligning marketing activities with supply chain operations influences various aspects of retail performance. The findings reveal that integrated marketing strategies lead to enhanced demand forecasting accuracy, improved customer satisfaction, and greater operational efficiency. By leveraging technology, such as artificial intelligence and data analytics, retailers can optimize inventory management, personalize offerings, and anticipate consumer preferences in real-time. Cross-functional collaboration and effective leadership emerge as crucial factors in fostering integration and overcoming challenges such as data management and cultural resistance. Additionally, the study highlights the significance of sustainability and entrepreneurship in driving integrated strategies, with implications for long-term competitiveness and brand reputation. The findings underscore the importance of viewing marketing and supply chain functions as interconnected elements of a holistic business strategy, rather than operating in silos. The study offers valuable insights for theory, practice, and future research, emphasizing the need for holistic and collaborative approaches to integration in the dynamic retail landscape. By embracing integrated marketing strategies, retailers can position themselves for success in an increasingly competitive market environment, driving innovation, efficiency, and customer satisfaction.

Literature circles create an interactive and participatory learning atmosphere that greatly increases student participation in the classroom. Through literature circles, students can exchange ideas and gain knowledge from one another in a nurturing learning atmosphere. Students feel more at ease taking chances and voicing their opinions in the classroom when there is a strong sense of community among the students. This research study used a narrative literature review as a qualitative method. Relevant literature in this review showed that literature circles can increase students' reading passion and enthusiasm. Students are more likely to be engaged when they can select their own reading materials and facilitate discussions. Thus, by implementing literature circles, teachers may create a more engaging and encouraging learning environment in the classroom, which will ultimately improve student performance and foster a deeper understanding of literature.

The aim of this manuscript is to synthesize and characterize novel silylated Sm3+ and Eu3+ complexes and incorporate them into mesoporous silica nanoparticles (MSNs) and dense silica nanoparticles (DSNs). Sm3+ and Eu3+ ion complexes were chosen for their strong UV-visible emission, deep-red luminescence, and effective interaction with bidentate organic ligands, such as 2-thenoyltrifluoroacetone (tta) and 1,10-phenanthroline (phen). Silylated ligands were employed as coupling agents to form covalent bonds between the complexes and an oxide matrix via a conventional sol-gel process. This approach aims to enhance the thermal stability and photophysical properties of the resulting hybrid material compared to free complexes. The new silylated-bidentate ligand complexes, using tta and phen as organic ligands and 3-chloropropyltriethoxysilane as the silylating agent, were characterized by FTIR, luminescence spectroscopy, and luminescence decay. After incorporation into silica nanoparticles, the hybrid materials were characterized by SEM, TEM, DLS, zeta potential, SAXS, porosity, surface area measurements, luminescence spectroscopy, and MTT assay. The results confirm the successful synthesis of new luminescent silylated complexes with high luminescence intensity and their incorporation into silica nanoparticles.

Models of subsurface structures are important for successful deposit exploration but are challenged by the need to integrate data from different geophysical methods. In the present study, we evaluated a method of joint inversion in which audio-magnetotelluric (AMT) and dual frequency induced polarization (DFIP) data sets are inverted simultaneously to produce a consistent 2D resistivity model to show a clear image of subsurface structures. To achieve the objectives, we conducted AMT and DFIP surveys first on the same survey line within the Dongjun lead-zinc deposit in inner Mongolia by developing 31 AMT survey sites with an interstation separation of 40 m on a 1440 m survey track and operated in fifty-three frequencies in the range 1–10,400 Hz to record the resistivity distribution of subsurface to depths exceeding 800 m. The same survey setup up was applied to the DFIP method by utilizing the SQ-3C model with a pole-dipole array configuration and conducted measurements at frequencies of 4 Hz and 4/13 Hz. We first separately inverted AMT and DFIP measurements. The two-dimensional (2D) model obtained from AMT data revealed distinct low resistivity anomalies in the middle of the 2D inversion model. In contrast, the DFIP inversion model showed a high resistive body in the same region. In response to the discrepancies observed in the separate 2D inversion models, we implemented a joint inversion for both the AMT and DFIP datasets. The joint inversion resistivity model shows surficial conducting bodies and a high conductive body along the profile with relatively high Percent Frequency Effect (PEF) indicating high chargeability. The final joint inversion resistivity model clearly images the large silica alteration zone and the Pb-Zn mineralization. This study demonstrates the feasibility of a joint inversion methodology and highlights the value of integrating geophysical methods through joint inversion for enhanced characterization and exploration of lead-zinc ores.

YouTube Kids serves as a dynamic and user-friendly resource for young learners to learn English. Its extensive library of instructional materials, which includes captivating animations and interactive movies, provides a rich and varied learning environment. Through the integration of play and exploration into language study, YouTube Kids creates a comfortable and engaging atmosphere that allows kids to improve their English language skills at their own pace. In this research article, a narrative literature review was employed as a qualitative methodology. Based on the gathered relevant literature, YouTube Kids presented such positive and negative impacts as a channel for English language acquisition. YouTube Kids is indeed a beneficial tool for young learners who are trying to learn English, but at the same time, it does have some potential disadvantages, as some videos may not employ the same standard or correctness of English, which could expose kids to improper grammar or pronunciation. Parents and teachers need to carefully select and keep an eye on the content their kids watch to ensure that their children's YouTube Kids content supports their language learning objectives. Through careful supervision and curation, parents and educators may maximize the usefulness of the site as a medium for teaching young learners English language skills while also minimizing any potential downsides.

High-spin states of 192Tl are populated by the heavy ion fusion-evaporation reaction 181Ta(16O, 5n)192Tl at 97 MeV beam energy. A new level scheme with eight new levels is constructed and the level spins are tentatively assigned. The negative-parity yrast band is extended up to 23^{-}\hbar. Subsequently, the systematics of signature splitting and signature inversion are discussed for the negative-parity yrast band of odd-odd Tl isotopes including 192Tl, 194Tl, 196Tl, and 198Tl. With the increase of neutron number signature inversion is found in 196,198Tl at high-spin state in these four Tl isotopes. The reason may be due to the competition between neutron-proton interaction and Coriolis force.

Broad bean paste (BBP) is a traditional fermented soy food, and its high salt content not only prolongs the fermentation time but also threatens human health. In this study, three BBP-meju with different salt concentrations were prepared, and the effects of varying salinity on the fermentation process were comprehensively compared. The results showed that salt-reduced fermentation contributed to the accumulation of amino acid nitrogen, reducing sugars, free amino acids, and organic acids. Alcohols, esters, aldehydes, and acids were the main volatile flavor compounds in BBP-meju, and the highest total volatile flavor compounds were found in medium-salt meju. Bacillus, Staphylococcus, Aspergillus, and Mortierella were the dominant microbial communities during fermentation, and there were also three opportunistic pathogens, Enterobacter, Pantoea, and Brevundimonas, respectively. According to Spearman correlation analysis, Wickerhamomyces, Bacillus, Staphylococcus, and Mortierella all showed highly significant positive correlations with ≥3 key flavor compounds, which may be the core functional flora. Furthermore, the dominant microbial genera worked synergistically to promote the formation of high-quality flavor compounds and inhibit the production of off-flavors during salt-reduced fermentation. This study provides a theoretical reference for the quality and safety control of low-salt fermented soy foods.

The article covers the Surveyor Institute's historical context and its role in the legal order of land rights registration. It highlights the importance of GPS technologies in ensuring the accuracy of registering rights to real estate. The article reviews the role of systematic registrations in clarifying overlapping cadastral data and preventing neighborhood disputes. Additionally, it underscores the challenges related to surveying activities in Georgia and emphasizes the importance of establishing a legal framework for this profession.

This study introduces an integrated method for managing process risks in a Business Process Reengineering (BPR) project, using Robust Data Envelopment Analysis (RDEA) and machine learning (ML). The goal is to prioritize risks based on three standard factors of PFMEA: Severity, Occurrence, and Detection (S-O-D), and incorporating two additional factors (Breakdown Cost and Breakdown Duration) seen as undesirable outputs. The model also accounts for the effect of uncertainty on expert-estimated values by applying disturbance percentages in the linear PFMEA-RDEA model. A machine learning model is proposed to predict new values if partial or total modifications have been made to the processes. The approach was implemented in an au-tomotive sector company, and the results showed the impact of uncertainty on values by com-paring different approaches such as RPN, PFMEA-DEA, and PFMEA-RDEA. A new reduced risk categorization was achieved, who allowed for decision-makers to focus on necessary actions for reengineering.

Arabinoxylans (AXs) are non-starch polysaccharides with complex structures naturally occurring in grains (i.e., barley, corn, and others) providing many health benefits, especially as prebiotics. AXs can be classified as water-extractable (WEAX) and water-unextractable (WUAX) based on their solubility, with properties influenced by grain sources and extraction methods. A large body of evidence shows that AXs exert an im-portant health impact, including glucose and lipid metabolism regulation and immune system enhancement, which is induced by the interactions between AXs and the gut microbiota. Recent research underscores the dependence of AX physiological effects on structure, advocating for a deeper understanding of struc-ture-activity relationships. While systematic studies on WEAX are prevalent, knowledge gaps persist re-garding WUAX, despite its higher grain abundance. Thus, this review reports recent data on WUAX struc-tural properties (chemical structure, branching, MW) in cereals under different treatments. It discusses WUAX applications in baking and its benefits deriving from gut fermentation.

Addressing the significant challenge in high-speed cotton dibbling operations in Xinjiang—specifically, the duck bill’s ("Duck bill" is a type of duck-billed bunch planting mechanism or component). shortened opening duration leading to seed throwing and floating—a new crawler-type delayed hole-forming mechanism has been designed. This mechanism extends the duck bill horizontally, thereby prolonging its opening time, enabling cotton sowing speeds of up to 6 km/h. Following agronomic principles for cotton planting, the overall layout of the crawler-type hole-forming mechanism, the structural parameters of the key components and the trajectory of the hole-forming are determined. We use the Discrete Element Method (DEM) and multi-body dynamics coupling method to simulate and analyze the motion process of the device. The fixed the tilt angle of the duck bill α(A), the depth of the duck bill hole-forming into the soil h(B), and the angle of rotation of the moving duck bill β(C) were taken as the experimental factors, with the longitudinal length of cotton seed hole (Y1) and the hole-forming depth of cotton seed hole (Y2) as the response values. The parameter range of each factor and the preliminary influence on the response value were determined through pre-experiments and single-factor simulation test. Based on RecurDyn-EDEM coupling, a quadratic regression orthogonal rotation combination simulation test was carried out. The results show that the order of the primary and secondary factors affecting the Y1 of the time-lapse hole-forming device was: A > C > B. The order of primary and secondary factors affecting the Y2 of the delayed hole forming device was: B > C > A. When the A was 2.4 °, the B was 42.4 mm, and the C was 30.5 °, the performance of the hole-forming was the best, and the Y1 was 26.4 mm, and the Y2 was 25.0 mm. The bench verification test results show that under the optimized combination of operating parameters, the average Y1 was 29.1 mm, and the average Y2 was 23.2 mm. Compared with the results of the previous coupled simulation model, the average relative errors of the two are 7.23 % and 4.36 %, respectively, indicating the accuracy and effectiveness of the established DEM simulation model and virtual test analysis. The hole-forming area and the opening time of the duck bill after the stable operation of the machine were recorded and measured. The calculated hole dislocation rate Hc was 4.33 %, which did not exceed the national standard requirement of 6 %. The qualified rate of hole distance Hx was 94.33 %, which was much higher than the national standard requirement of 80 %. The average opening time of the duck bill at a speed of 6 km/h is 0.45 s, which is much longer than the time required for cotton seeds to fall from the duck bill 0.11 s. It meets the requirements of high-speed cotton planting in China and facilitating advancements in future high-speed planter technology.

Recently, environmental degradation has become an international issue due to the extensive economic activities around the globe. This aspect demands the policymakers' and new researchers’ emphasis. Hence, the present article examines the impact of corporate social responsibilities (CSR) to community and environment on the environmental performance (ENP) of the manufacturing industry in China. The article also investigates the mediating role of green innovation and environmental strategy among CSR to community, CSR to environment and ENP of manufacturing industry in China. The article gets the primary data from the selected employees of the manufacturing industry using questionnaires. The article also tests the data's validity and reliability, and association among variables using smart-PLS. The outcomes indicated that CSR to environment has a positive association with ENP. The outcomes also revealed that green innovation and environmental strategy significantly mediate among CSR to community, CSR to environment and ENP. The article guides the policymakers in making policies related to improve ENP using CSR to environment and green innovation.

Cutaneous T-cell lymphomas (CTCLs) are a heterogeneous group of T-cell lymphomas characterised by high relapse rates and no curative treatments unless the allogeneic stem cell transplantation. The main complication in the management of this kind of malignancy is the variability that characterises the genetic and clinical features among the CTCL subtypes. JAK/STAT, MAPK/ERK, PI3K/Akt, and NF-kB are those signalling pathways that are found altered in CTCL and that are responsible for promoting both T-cell malignancy and the pro-tumorigenic microenvironment. Thus, targeting key players of these pathways can be an advantageous therapeutic option for CTCL. In this review, we aim to summarise the different approaches that precisely inhibit the kinases of each cited signalling. JAK inhibitors seem to be the most promising kinase inhibitors for CTCL. However, adverse events have been reported especially in patients with immunosuppression or an underlying autoimmune disease. More studies are needed, especially clinical trials, to investigate the benefits of these drugs for the treatment of cutaneous T-cell lymphomas.

Laser-induced fluorescence spectroscopy (LIFS) is actively used for remote sensing of atmospheric aerosols and currently is one of the most sensitive and selective techniques for determining small concentrations of substances inside particles. The use of high-power femtosecond laser sources for LIFS-based remote sensing of aerosol contributes to the development of new-generation fluorescence atmospheric lidars since it makes it possible overcoming the energy threshold for the nonlinear-optical effects of multiphoton absorption in particles and receiving the emission signal at long distances in the atmosphere. Our study is aimed to the development and experimental demonstration the technique of nonlinear laser-induced fluorescence spectroscopy (NLIFS) based on the remote excitation of aerosol fluorescent emission stimulated by a spatially-structured high-power femtosecond laser pulse. Importantly, for the first time to our knowledge, we demonstrate the advances of using stochastically-structured plasma-free intense light channels (postfilaments) specially formed by propagation of femtosecond laser radiation through a turbulent air layer for improving NLIFS efficiency. A multiple increase in the received signal of two-photon-excited fluorescence of polydisperse dyed aqueous aerosol by the structured postfilaments is reported.

This study explores the role of stakeholder engagement in enhancing supply chain sustainability within the renewable energy sector. Through a qualitative research approach, including in-depth interviews with key stakeholders such as government agencies, industry associations, renewable energy companies, community groups, and environmental organizations, the research reveals the complexity and significance of effective stakeholder engagement. Stakeholders highlighted diverse motivations, including environmental, social, economic, and regulatory concerns, driving their participation. The study underscores the importance of tailored engagement strategies that recognize stakeholder heterogeneity and address specific needs and expectations. Collaborative approaches, such as public-private partnerships and multi-stakeholder initiatives, were identified as crucial for pooling resources, sharing knowledge, and addressing common challenges. However, challenges related to power imbalances, conflicting interests, and communication barriers were also noted. Government policies and regulatory frameworks were found to play a pivotal role in shaping stakeholder engagement practices and sustainability outcomes. Regulatory uncertainty and inconsistency were cited as significant concerns that could undermine sustainability initiatives. Community engagement emerged as a critical factor, with local communities often directly impacted by renewable energy projects. Meaningful engagement, including consultation and benefit-sharing mechanisms, is essential for building trust and securing social acceptance. Emotional intelligence and marketing strategies were recognized as important tools for effective stakeholder engagement, emphasizing the role of empathy, active listening, and clear communication. The findings of this study highlight the need for a holistic and integrated approach to stakeholder engagement and supply chain sustainability in the renewable energy sector. By addressing diverse stakeholder needs, fostering collaboration, and aligning policies with sustainability goals, stakeholders can work together to accelerate the transition towards a more sustainable energy future.

Species identification and phylogenetic relationships clarification are fundamental goals in species delimitation. Yet these tasks pose challenges when based on morphologies, geographic distribution, and genomic data. Previously, two new species of fern genus Bolbitis, B. × multipinna and B. longiaurita, were described based on morphological traits, are phylogenetically intertwined with B. sinensis and fail to form monophyletic groups. To address the unclear phylogenetic relationships within the B. sinensis species complex, RAD sequencing was performed on 65 individuals from five populations. Our integrated analysis of phylogenetic tree, neighbor net, and genetic structure, indicate that the B. sinensis species complex should not be considered as separate species. Moreover, our findings reveal differences in the degree of genetic differentiation among five populations, ranged from low to moderate, which might be influenced by geographical distance and gene flow. The Fst values also confirmed that genetic differentiation intensifies with increasing geographic distance. Collectively, this study clarifies the complex phylogenetic relationships within the B. sinensis species complex, elucidates the genetic diversity and differentiation across the studied populations, and offers valuable genetic insights that contribute to the broader study of evolutionary relationships and population genetics within the Bolbitis species.

Global warming and the associated increasing frequency of heatwaves are on the rise leading to numerous health complications. Diabetic patients are more vulnerable to heat exposure than healthy individuals, owing to their impaired sweating ability, however, little is known about how heat exposure may impact the function of skin cells, commonly keratinocytes. Our recent report provided the first proof-of-concept revealing that the metabolic composition of sweat EVs is associated with metabolic changes in healthy individuals and type 2 diabetes patients. Given this and the shared cellular proprieties of eccrine sweat glands with keratinocytes, we questioned whether the metabolic changes in sweat EVs may mirror the responses of keratinocytes upon heat exposure. To this, we exposed HaCat, which were maintained in low (mimicking healthy condition) and high glucose (mimicking diabetes condition) to acute (90 min), chronic (48 h), and repetitive heat exposure at 40 ⁰C. Through conducting a set of experiments including a targeted metabolomics approach, Greiss assay, western blotting analysis, and electron microscopy studies. The data demonstrate that heat exposure results in substantial changes of metabolite levels belonging to amino acids, pyrimidine metabolism, and glycolysis pathways in high glucose maintained HaCat cells when compared to those noted in low glucose condition. Exploring the molecular mechanisms through which heat exposure may impact the metabolic composition in keratinocytes, our discoveries highlight nitric oxide (NO) as a novel biomarker that the level is correlated with heat duration and frequency. Furthermore, data reveal that the HSP-70 protein levels and mitochondrial morphology are consequently altered. This study provides evidence of shared metabolic alterations in keratinocytes and sweat EVs collected from clinical study and proposes, for the first time, NO as a novel biomarker for monitoring changes in health and diabetes upon heat exposure.

Our study utilized density functional theory (DFT) to explore a 2D MoP2 surface for hydrogen storage. Optimization determined a gravimetric capacity for pristine MoP2 of 5.72%, with an adsorption energy of ‒ 0.13 eV/molecule. For this surface with 12.5% Mo vacancies, we achieved 6.02% and ‒ 0.14 eV/molecule. We then introduced a novel criterion to test the attraction forces in hydrogen storage at a given temperature. This involved a first-principles molecular dynamics approach at various temperatures. To determine the number of molecules adsorbed on the surface at temperature T1, we conducted an FPMD calculation at T1, using the optimization as the initial system configuration. Subsequently, we performed a second FPMD calculation at a temperature T2 (with T2 ‹‹ T1), using the stable configuration of the first FPMD calculation as the initial configuration. If there were attraction forces on the molecules, they would move towards the surface. We identified as adsorbed molecules at temperature T1, only those that moved back toward the surface at temperature T2. The defective surface gave the best gravimetric capacity, ranging from 5.27% at 300 K to 6.02% at 77 K. The latter met the requirement from the US-DOE, indicating the potential practical application of our research in hydrogen storage.

Despite the recognized influence of body mass on combat techniques, the relationship between body segment mass (BSM) and combat moves remains unexplored. This study aimed to examine the relationship between striking arm mass (SAM), kicking leg mass (KLM), and body mass (BM) with the dynamic forces of the direct punches (DP), palm strikes (PS), elbow strikes (ES), front kicks (FK), and countermovement jumps (CMJ) performance. Sixteen male military cadets (22.3 ± 1.8 years, 181.4 ± 7.0 cm, 82.1 ± 8.5 kg) performed combat techniques, with performance measured by using a force plate and body segment mass assessed by Dual-energy X-ray absorptiometry. Spearman's correlation analysis, the Wilcoxon test, and Cohen's d were applied. Results indicated the relationship between KLM or BM and FK impulse (r = 0.64, p = 0.01; r = 0.52, p = 0.04, respectively) and CMJ impact force (r = 0.80, p ≤ 0.01; r = 0.70, p ≤ 0.01, respectively). Moreover, FK peak and impact forces were moderately correlated with CMJ jump height (r = 0.74, p ≤ 0.01; r = 0.77, p ≤ 0.01). The highest relationship was found between KLM and FK impulse; however, the difference in variability explained by KLM versus body mass is only 12%. This suggests that knowledge of BSM did not provide a significantly better estimate of the dynamic forces of the punches and FK than BM.

The growing usage of Generative AI tools in scientific writing requires a critical examination of their benefits and challenges. This literature review is aimed at comprehensively analyzing current empirical research articles focused on the application of Generative AI in scientific writing. The Google Scholar database was used to search for the literature. The following keywords were used: "Generative AI" and "academic writing", "LLM" (Large Language Models) and "academic writing", "Generative AI" and "Scientific writing", and "ChatGPT" and "Scientific Writing". The search was restricted to articles published between January 1, 2023, and April 30, 2024. 15 articles were selected as appropriate for the study and analyzed. It was found that, thus far, ChatGPT is the most exploited tool in the studies. AI tools such as Bard (Gemini), Bing, Claude2, and Elicit were also tested. The benefits of Generative AI usage in scientific writing were found to be omnipresent. It can aid in the generation of structured abstracts, titles, introductions, literature reviews, and conclusions of a scientific article. Generative AI also makes writing more efficient and time-saving. Its capabilities in improving language and proofreading are well-established. However, the generation of inaccurate content and references by current commercially available LLMs poses a serious problem. The lack of critical thinking and tendency to produce non-original content are significant drawbacks. Generative AI should be employed with human oversight, serving as an assistant rather than a replacement. Transparency in AI usage in scientific writing is essential, along with the necessity for proper legal regulation.

Limited research has been conducted on the metabolites present in the essential oils (EOs) of Phlomoides rotata (Benth. ex Hook. f.) Mathiesen (PR, syn. Lamiophlomis rotata (Benth.) Kudô), and their potential pharmacological activities, such as antioxidant properties, are often overlooked. We conducted a metabolomics-based screening to identify the characteristic metabolites (CMs) in the EOs extracted from PR. Meanwhile, we evaluated their in vitro antioxidant activities (AOAs). The EOs obtained through hydro-distillation are characterized by a light yellow color and a fresh, elegant fragrance. Cryoprecipitation was used to separate the crystals (Crs) from the EOs, resulting in the crystal-free EOs (CFs). A total of 121 components are identified and quantified in the EOs, Crs, and CFs. Among them, 84 were reported for the first time from such EOs. The major compounds include long-chain fatty acids (LCFAs) and their esters, such as palmitic acid (PA), myristic acid (MA), linoleic acid (LA), oleic acid (OA), stearic acid, and methyl palmitate (MP). Furthermore, 11 kinds of apocarotenoids (also called norisoprenoids) were first systematically investigated. Among them, eight C13-norisoprenoids, with trans-β-damascenone (DN) being particularly notable for its flavor, were identified. A sum of 11 CMs are screened , including PA, MA, LA, OA, MP, hexahydrofarnesyl acetone, phytol (PT), DN, stearic acid, linalool, and hexanal. These CMs are biosynthesized through FAs and 2-C-Methyl-D-erythritol 4-phosphate/1-Deoxy-D-xylulose 5-phosphate pathways. The in vitro AOAs of EOs, Crs, CFs, and seven selected CMs (PA, MA, LA, OA, MP, PT, and DN) were evaluated. Generally, PA and MA exhibited pro-oxidant activities (POAs) or weak AOAs. LA and OA demonstrated POAs or weak AOAs at lower concentrations, but at higher concentrations, they displayed medium to strong AOAs. Importantly, the CFs typically exhibited stronger AOAs compared to the corresponding EOs and Crs, potentially due to variations in their PA content. Overall, this study provides valuable insights into the potential utilization of EOs from PR.

Pedestrian trajectories are crucial for self-driving cars to plan their paths effectively. The sensors implanted in these self-driving vehicles, despite being state-of-the-art ones, often face inaccuracies in the perception of surrounding environments due to technical challenges for adverse weather conditions, interference from other vehicles sensors and electronic devices, and signal reception failure, leading to incompleteness in trajectory data. But for real-time decision making for autonomous driving, the trajectory imputation is no less crucial. Previous attempts to address this issue such as statistical inference and machine learning approaches have shown promise. Yet, the landscape of deep learning is rapidly evolving with new and more robust models emerging. In this research, we have proposed an encoder-decoder architecture, Human Trajectory Imputation Model, coined as HTIM, to tackle these challenges. This architecture aims to fill in the missing parts of pedestrian trajectories. The model has been evaluated using the Intersection drone inD dataset, containing trajectory data at suitable altitudes preserving naturalistic pedestrian behavior with varied dataset sizes. To assess the effectiveness of our model, we have utilized L1, MSE, Quantile and ADE loss. Our experiments have demonstrated that HTIM outperforms the majority of the state-of-the-art methods in this field, thus indicating its superior performance in imputing pedestrian trajectories.

Background: Molecular genetic events are among the numerous factors affecting the clinical course of papillary thyroid carcinoma (PTC). Recent studies have demonstrated that aberrant expression of miRNA, as well as different thyroid-related genes, correlate with the aggressive clinical course of PTC and unfavorable treatment outcome, which opens up new avenues for using them in personalization of the treatment strategy for patients with PTC. In the present work, our goal was to assess the applicability of molecular markers in preoperative diagnosis of aggressive variants of papillary thyroid cancer. Methods: The molecular genetic profile (expression levels of 34 different markers and BRAF mutation) was studied for 108 cytology specimens collected by fine-needle aspiration biopsy in patients with PTC having different clinical manifestations. Results: Statistically significant differences with adjustment for multiple comparisons (p &lt; 0.0015) for clinically aggressive variants of PTC were obtained for four markers: miRNA-146b, miRNA-221, FN1, and CDKN2A. Weak statistical correlation (0.0015&lt; р&lt;0.05) was observed for miRNA-31, -375, -551b, -148b, -125b, mtDNA, CITED1, TPO, HMGA2, CLU, NIS, SERPINA1, TFF3, and TMPRSS4. Conclusions: The recurrence risk of papillary thyroid carcinoma can be preoperatively predicted using miRNA-221, the fibronectin and cyclin-dependent kinase inhibitor 2A genes.

In this research the efficiency of degradation of different organic contaminant classes, including pesticides (tembotrione, clomazone), pharmaceuticals (ciprofloxacin, 17α-ethinyl estradiol) and mycotoxins (zearalenone, deoxynivalenol, fumonisin B1), by subcritical water treatment, was studied in model systems. All experiments were conducted in a house-made batch type pilot reactor. The research was focused on the optimization of the treatment parameters by using moderate treatment conditions. Optimization of the remediation processes of water contaminated with 17α-ethinyl estradiol, tembotrione, clomazone, ciprofloxacin, was conducted by testing different homogeneous and heterogeneous catalysts, as well as different gas atmospheres (nitrogen and carbon-dioxide) for pressurization of the process system. Mycotoxins in water were degraded without catalysts and all experiments were conducted in nitrogen atmosphere. Optimization was conducted by defining the optimal combination of the treatment temperature and time, oriented towards energy saving and minimization of the technical requirements. The degradation efficiency in all tested samples was determined by HPLC analysis.

Almost two decades ago, Ernesto P. Borges and Bruce M. Boghosian embarked on the intricate task of composing a manuscript to honor the profound contributions of Constantino Tsallis to the realm of statistical physics, coupled with a concise exploration of q-Statistics. Fast forward to Constantino Tsallis’ illustrious 80th birthday celebration in 2023, where Deniz Eroglu and Ugur Tirnakli delved into Constantino’s collaborative network, injecting renewed vitality into the project. With hearts brimming with appreciation for Tsallis’ enduring inspiration, Eroglu, Boghosian, Borges and Tirnakli proudly present this meticulously crafted manuscript as a token of their gratitude.

Bioactive peptides are sequences of amino acids, cut from the parent protein with en-zymes or high pressure processing that can impart a tertiary health benefit to the con-sumer that goes beyond basic human nutrition. This study explores mesopelagic fish in-cluding Maurolicus muelleri and Benthosema glaciale as sources of peptides with an-ti-inflammatory, heart health beneficial, antioxidant and other bioactivities. Bioactive peptides were generated post-catch using different enzymatic hydrolysis processes ap-plied to mesopelagic species caught from experimental cruises targeting these fish. Maurolicus muelleri and Benthosema glaciale were the dominant species processed. Bi-oactive hydrolysates included a Maurolicus muelleri Alcalase hydrolysate and a Maurolicus muelleri autolysis. Hundreds of peptide sequences were identified using mass spectrome-try from active hydrolysates. In silico analysis was used to rank identified peptide se-quences in terms of overall bioactivity using Peptide Ranker, anti-inflammatory activity using PrepAIP, ability to impart Umami flavours with Umami-MRNN and dipeptidyl peptidase IV inhibitory potential using AntiDMPpred . Thirty peptides were selected fol-lowing in silico analysis. Several of the selected peptides had sequence homology with peptides derived from other fish proteins including Atlantic salmon (peptide QCPLHR-PWAL) and thin-lipped mullet (peptide FDAFLPM). Seven peptides predicted to have an-ti-inflammatory, anti-type 2 diabetes or Umami potential using in silico strategies were chemically synthesized and their anti-inflammatory activities confirmed using in vitro bioassays with COX-1 and COX-2 enzymes. The peptide QCPLHRPWAL inhibited COX-1 and COX-2 by 82.90% (+/-0.54) and 53.84% respectively and had a selectivity index greater than 10. This peptide warrant further research as a novel anti-inflammatory/pain relief peptide. Other bioactivities associated with DPP-IV inhibition and Umami flavours de-velopment are discussed. Identified peptides offer potential for use in functional foods or topical agents to prevent pain and inflammation associated with diseases like psoriasis, arthritis and inflammatory bowel disease, however further research in vivo is required.

A class of semi-linear elliptic equations with critical Hardy-Sobolev exponent has been considered. This model is widely used in hydrodynamics and glaciology, gas combustion in thermodynamics, quantum field theory and statistical mechanics, as well as gravity balance problems in galaxies. The $\left( PS\right) _{c}$ sequence of energy functional has been investigated, and then the mountain pass lemma was used to prove the existence of at least one nontrivial solution. Also a multiplicity result has been obtained. Some known results have been generalized.

There is a need for strategic healthcare workforce planning to address shortages and ensure universal health coverage, aiming to optimize work-force per population ratio, distribution, and competencies. Amidst rising demands exacerbated by aging populations and events like the COVID-19 pandemic, strategic workforce planning becomes crucial for addressing healthcare inequalities by forecasting needs, bridging skill gaps, and adapting to changing demographics and care models. Israel has invested in strategic planning to tackle healthcare workforce challenges; however, globally there is insufficient planning informed by health labor market analysis, which hinders efforts to address healthcare inequalities. The paper reviews national policies in Israel, Australia, Germany, and Norway, ex-amining statistics and government publications to highlight strategic plan-ning considerations and address challenges in healthcare workforce plan-ning. This paper focuses both on the critical role of physicians in healthcare systems, and on the changing borders between healthcare professions and different national contexts which demand more context dependent strategic workforce planning. We highlight common themes among national policies, including the need for data collection, increasing the capacity of domestic training programs, and the need to address geographic maldistribution of physicians. Ultimately, we aim to guide policy in the development of a re-silient and sustainable healthcare workforce capable of meeting diverse community needs and promoting equity in healthcare services.

Ulleung County, one of the most medically vulnerable areas in South Korea, requires public attention because of the high incidence of liver cancer. This study was conducted as a part of the Ulleung Liver Cancer Prevention and Management Project. The purpose of this study was to estimate the community prevalence of hepatitis B and C viruses and to identify the associated risk factors. The Project’s interagency workgroup established a procedure for conducting blood sampling and health behavior surveys at the Ulleung Public Community Health Center. A total of 1,792 residents aged 40 years and older voluntarily participated in the study between 2019 and 2022. The hepatitis B surface antigen (HBs Ag) and hepatitis C virus antibody (anti-HCV) positive rates in Ulleung were 7.19% and 1.37%, respectively. Low education level and lifetime smoking were associated with HBsAg positivity, whereas cupping therapy at non-medical institutions was associated with anti-HCV positivity. The odds of HBs Ag positivity were lower among those with tattoos than among those without. There was a difference in the risk factors associated with hepatitis B and C viral infection. While a high HBs Ag positivity rate alone may not fully explain the high incidence of liver cancer in Ulleung, it may be a contributing factor.

Ice formation on aircraft surfaces poses significant safety risks, and current detection systems often struggle to provide accurate, real-time predictions. This paper presents the development and comprehensive evaluation of a smart ice control system using a suite of machine learning models. The system utilizes various sensors to detect temperature anomalies and signal potential ice formation. We trained and tested supervised learning models (Logistic Regression, Support Vector Machine, Random Forest), unsupervised learning models (K-means clustering), and neural networks (Multi-Layer Perceptron) to predict and identify ice formation patterns. Experimental results demonstrate that our smart system, driven by machine learning, accurately predicts ice formation in real-time, optimizes de-icing processes, and enhances safety while reducing power consumption. This solution holds the potential for improving ice detection accuracy in aviation and other critical industries requiring robust predictive maintenance.

In a recent paper, Nicolas Gisin suggests that by conducting physics with intuitionistic rather than classical mathematics, rich temporality - that is, passage and tense, and specifically, the future’s openness - can be incorporated into physics. Physics based on classical mathematics is tenseless and deterministic, and that, so he holds, renders it incongruent with experience. According to Gisin, physics ought to represent the indeterminate nature of reality, and he proposes that intuitionistic mathematics is the key to succeeding in doing so. While I share his insistence on the reality of passage and tense, and on the future being real and open, I argue that the amendment he offers does not work. I show that, its attunement to time notwithstanding, intuitionistic mathematics is as tenseless as classical mathematics, and that physics is bound to remain tenseless regardless of the math it employs. There is much to learn about tensed time, but the task belongs to phenomenology and not to physics.

Cellular senescence has recently been recognized as a hallmark of cancer, reflecting its association with aging and inflammation, its role as a response to deregulated proliferation and oncogenic stress, and its induction by cancer therapies such as radiation, chemotherapy, and targeted agents. While such therapy-induced senescence (TIS) has been linked to resistance, recurrence, metastasis and normal tissue toxicity, TIS has the potential to enhance therapy response and stimulate anti-tumor immunity. In this review, we examine the Jekyll and Hyde nature of senescent cells (SnCs), with a particular focus on how their persistence while expressing the senescence-associated secretory phenotype (SASP) modulates the tumor microenvironment through autocrine and paracrine mechanisms. Via the SASP, the formation of SnCs may alternately mediate resistance or response to conventional therapy. Further, toward fulfilling the unmet potential of cancer immunotherapy, we consider how SnCs may influence tumor inflammation and serve as a source of antigen to potentiate anti-tumor immunity. This new view suggests treatment strategies based on inducing TIS to enhance immune checkpoint blockade. Finally, we describe strategies for mitigating the detrimental effects of senescence, such as modulating the SASP or targeting SnC persistence, toward enhancing the benefits of cancer treatment.

We investigate the possible laboratory origins of the highly pathogenic avian influenza (HPAI) H5N1 clade 2.3.4.4b genotype B3.13, currently affecting various animal species and causing sporadic human infections. The first detection of HPAI H5N1 clade 2.3.4.4b in the Netherlands in 2020 raises concerns about earlier gain-of-function research. The proximal origins of HPAI H5N1 Clade 2.3.4.4b may be the USDA Southeast Poultry Research Laboratory (SEPRL) in Athens, Georgia and the Erasmus Medical Center in Rotterdam, the Netherlands. Genetic analysis indicates that genotype B3.13 emerged in 2024 and exhibits genetic links to genotype B1.2, which was identified to have originated in Georgia in January 2022 after the start of serial passage research with H5Nx clade 2.3.4.4 in mallard ducks at the USDA Southeast Poultry Research Laboratory (SEPRL) in Athens, Georgia in April 2021. Genotype B1.2 was found in a bottlenose dolphin (Tursiops truncatus) in March 2022 in Florida, indicating sudden new adaptations to different animal species. The NP gene of H5N1 clade 2.3.4.4b (genotype B3.13), which is causing outbreaks in cattle, was reported to have likely originated from an avian influenza A virus derived from mallard ducks. Significant mutations found in recent human cases, including PB2 E627K and PB2 M631L, also suggest links to serial passage experiments. However, further investigation is urgently needed to confirm these findings and to identify all H5N1 laboratory leaks that may have occurred with a focus on mallard ducks and other migratory waterfowl, which have the potential to infect a large number of poultry and livestock facilities around the world. A moratorium on gain-of-function research including serial passage of H5N1 is indicated to prevent a man-made influenza pandemic affecting animals and humans.

Malignant melanoma (MM) is the most fatal form of skin cancer, accounting for 90% of all skin cancer deaths. Multiple dysregulated cellular pathways are involved in MM, including the MAPK/ERK and PI3K/PTEN/AKT pathways, which can be targeted with novel targeted inhibitors. However, these blockades can be overcome through the activation of alternative pathways, leading to treatment resistance. The high immunogenicity of MM has been exploited using checkpoint inhibitors resulting in improved survival outcomes of patients with advanced MM. However, their side effect profile and prohibitive cost remain a challenge and the survival outcomes for patients with metastatic MM remain poor. Treatment resistance has been attributed to the presence of cancer stem cells (CSCs), a small subpopulation of pluripotent, highly tumorigenic cells proposed to drive cancer progression, metastasis, and treatment resistance. CSCs reside within the MM tumor microenvironment (TME) regulated by the immune system, and the paracrine renin-angiotensin system (RAS), expressed in many cancer types, including MM. This article reviews the current treatment of advanced MM with targeted therapy and immune checkpoint blockers, highlights the emergence of mRNA vaccine. It also discusses the MM TME and its relationship with CSCs, and the local immune system and the paracrine RAS. It highlights the regulation of the MAPK/ERK and PI3K/AKT/mTOR pathways by the RAS via prorenin receptor and angiotensin II receptor 1, and how this relates to the CSCs and treatment resistance. This underscores the potential multi-modal therapeutic strategy by concurrent targeting of multiple components of the TME.

Despite the effectiveness of insulin injections in managing hyperglycemia in Type 1 Diabetes, they fall short in addressing autoimmunity and regenerating damaged islets. This review aims to explore the potential of various treatment modalities for T1DM, including mesenchymal stem cells (MSCs), MSC-derived exosomes, gene therapy, islet allotransplantation, and pancreatic islet cell transplantation. Results: MSCs demonstrate efficacy in T1DM treatment through immunomodulation and tissue regeneration, although further research is warranted to optimize their therapeutic potential. Gene therapy presents a promising approach despite challenges such as donor shortage and immune rejection. Pancreatic islet cell transplantation emerges as a viable option, albeit with associated risks including graft rejection and the need for immunosuppression. Teplizumab, an FDA-approved humanized monoclonal antibody, revolutionizes the treatment landscape of Type 1 Diabetes by significantly delaying its onset, offering a paradigm shift since the discovery of insulin Conclusion: Ongoing studies and technological advancements in T1DM management offer a promising outlook for improved treatments and possibly even eradication on a global scale. MSCs, MSC-derived exosomes, gene therapy, and pancreatic islet transplantation hold considerable potential.

Biodiesel has several drawbacks, such as being prone to oxidation, having reduced stability, and having limited storage time. Antioxidants compatible with biodiesel are being used to address its drawbacks. The use of antioxidants in biodiesel has a significant impact on the environment and economy, especially in promoting sustainable energy. The study used blends consisting of 20% biodiesel and 80% diesel fuel. Isatin-thiosemicarbazones were tested as additives in blends at a concentration of 3000 parts per million (ppm) using an oxifast device. Comparing them to the chemical antioxidant Trolox. FT-IR, DSC, and TGA were used to characterize these samples. DSC measured sample crystallization temperatures (Tc). Samples with antioxidants showed decreased values compared to the non-antioxidant diesel sample D100. Several DSC tests were conducted to determine the antioxidant strengths of various samples. The results showed that the FT-IR spectrum's antioxidant effect regions grow clearer with antioxidants. The extra antioxidant is effective. Biodiesel's oxidative stability improves with isatin-thiosemicarbazones at varying concentrations. The kinetics of thermal decomposition of isatin-thiosemicarbazones under non-isothermal conditions have been determined using the Kissinger, Ozawa, and Boswell techniques. The activation energies of compounds 1 and 2 were calculated 137–147 kJ mol-1 and 173–183 kJ mol-1, respectively.

A comprehensive modeling framework for the thermoforming of polymer matrix woven laminate composite was developed. Two numerical indicators, the slip path length and traction magnitude, have been identified to be positively correlated to matrix smearing and wrinkling defects. The material model has been calibrated with picture-frame experimental results, and the prediction accuracy for intra-ply shear and thickness distribution were examined with measurements on the physically formed parts. Finally, a parametric study was conducted to determine the relationship between various process parameters and the quality of the formed part. For the trapezoidal part, orienting the laminate at 45-degrees to the mold axis reduces the likelihood of matrix smear and wrinkling defects. Although this laminate orientation yielded a greater spatial variation of part thickness, the thickness deviation is lower than that for the 0-degree orientation case. Higher forming rates were found to result in more defects due to increased slip path lengths and traction magnitudes. Optimal forming speeds should balance rapid shaping within the operating temperature window while avoiding tear. It was discovered that shallower molds benefit from faster ramp rates, while deeper molds require slower rates to manage extensive shearing, stretching, and bending. Faster forming rates lead to smaller thickness increases at high intra-ply shear regions, indicating a shift from intra-ply shear to out-of-plane bending due to the visco-plastic effect of the molten laminate, and can negatively impact part quality. Lastly, it was shown that a well-conceived strategy using darts could improve the part quality by reducing the magnitude of the defect indicators.

Sustainable development and education in sustainable development (ESD) are crucial and interconnected topics under wide discussion today. Young adults need to be educated in how to help bring about change. Thus, the dynamic relationship between school and home is important. In education, use could be made of English language classes, especially since English is a global language that enables access to the sustainability literature and facilitates discussion in global conferences and meetings. Consequently, English as a foreign language (EFL) students could gain confidence from being able to understand and use the terminology of, for example, sustainability. In this paper, the use of competence-based language teaching (CBLT) is proposed as a means of introducing sustainability topics into EFL writing classes at a university in Saudi Arabia. Students’ competence in sustainable development is therefore considered based on their ability to write about suggested sustainable development topics, measured on a scale for five dimensions of ESD proposed by Michelsen and Fischer (2017). The results demonstrate that the students possessed competence in sustainable development and intended to participate in its implementation. Thus, recommendations are made for the stakeholders in the education sector to include sustainable development topics as an initial offering in the curricula of various specialties using the CBLT approach.

Utilizing deep learning for semantic segmentation of cropland from remote sensing imagery has become a crucial technique in land surveys. Cropland illustrates diverse morphologies and degrees of fragmentation on the Earth’s surface, underscoring the importance of accurately perceiving the complex boundaries of cropland which are crucial for effective segmentation. This paper introduces a UNet-like boundary-aware compensation model BAFormer. Cropland boundaries typically exhibit rapid transformations in pixel values and texture features, often appearing as high-frequency features in remote-sensing images. To enhance the recognition of these high-frequency features as represented by cropland boundaries, the proposed BAFormer integrates a Feature Adaptive Mixer (FAM) and develops a Deep Wide Large Kernel Multi-Layer Perceptron (DWLK-MLP) to enrich the global and local cropland boundaries features separately. Specifically, FAM adaptively mixes high-frequency and low-frequency features through the advantages of convolution and self-attention; DWLK-MLP expands the convolutional receptive field by deeply decomposing large kernel convolutions. The efficacy of BAFormer has been evaluated on the Vaihingen, Potsdam, and LoveDA public datasets, as well as the Mapcup dataset. It has demonstrated advanced performance, achieving mIoU scores of 84.5%, 87.3%, 53.5%, and 83.1% on these datasets respectively. Notably, BAFormer-T, the lightweight iteration of the model, surpasses other lightweight models on the Vaihingen dataset with scores of 91.3% F1 and 84.1% mIoU. The source code is available at https://github.com/WangYouM1999/BAFormer.

In this study, we develop a stochastic partial differential equation (SPDE) model to assess the regional severity of temperature increases due to global warming. The model incorporates various stochastic processes to account for uncertainties such as solar explosions, economic upheavals, rising emissions, and irreversible changes in the climate system. Our base temperature model, influenced by latitude, is enhanced by these random factors to simulate realistic and diverse outcomes of climate change. Numerical simulations on a global grid provide a heatmap representing potential temperature increase severity across different regions. The results highlight the significant impact on tropical and polar regions, demonstrating the utility of SPDE models in understanding and predicting the complex dynamics of climate change. This approach offers valuable insights for policymakers and researchers aiming to develop adaptive strategies for mitigating the adverse effects of global warming.

Background: Gram-negative bacteremia, especially from Klebsiella spp., Escherichia coli, and Pseudomonas aeruginosa, poses a significant public health threat due to multidrug resistance and high mortality rates. Cost-effective treatments are essential in low-middle income countries as Colombia. Methods: This descriptive, phase IV study was conducted in a tertiary care hospital in Colombia. Adult patients with Gram-negative bacteremia treated with generic piperacillin/tazobactam (Penibactam®) were evaluated. Clinical and microbiological responses were assessed over 12 months. Results: The study included 30 critically ill patients with an average APACHE II score of 22.12. The clinical response at day 7 was 66% (n = 20), and the microbiological response was 56.7% (n = 17). By the end of follow-up, clinical improvement was observed in 63.3% (n = 19), with a mortality rate of 23% (n = 7). The cardiovascular system was the most common infection site. Conclusions: Generic piperacillin/tazobactam demonstrated effectiveness and safety comparable to existing literature in treating Gram-negative bacteremia, offering a viable, cost-effective alternative for critically ill patients in real-world settings.

Jump rope is a widely-applied basic training in various sports, yet it is understudied biomechanically. This study investigates the impact of cycle-tempo-induced motor control changes in elite jump rope athletes, addressing the biomechanical gap of cyclic skill control. The hypothesis posited two accelerations per jump cycle—one in front of and one behind the body—and anticipated that increased cycle frequency would alter the distribution of acceleration time within a cycle. Using 3D motion analysis, kinematic parameters were obtained and analyzed. The results confirmed the presence of two distinct accelerations per cycle. As tempo increased, the percentage of rear acceleration time increased while front acceleration time decreased, along with peak velocities increasing significantly (p&lt;0.01). Rope trajectory analysis indicated a consistent movement pattern across tempos, primarily in the sagittal plane. Variations in skill control showed shorter contact phases and reduced vertical range of motion for the center of gravity and feet at higher tempos (p&lt;0.05), along with significant reductions in joint range of motion for the lower limbs (p&lt;0.01). These findings enhance the understanding of motor control adaptations to different tempos and have practical implications for developing coaching programs aimed at optimizing performance, stability, and efficiency in jump rope training.

Laser machining by ultra-short (sub-ps) pulses at high intensity offers high precision, high throughput in terms of area or volume per unit time, and flexibility to adapt processing protocols to different materials on the same workpiece. Here we consider the challenge of optimization for high throughput: how to use the maximum available laser power and larger focal spots for larger ablation volumes by implementing a fast scan. This implies the use of high-intensity pulses approaching ∼PW/cm2 at the threshold where tunnelling ionization starts to contribute to overall ionization. A custom laser micromachining setup was developed and built to enable high speed, large area processing and easy system reconfiguration for different tasks. The main components include laser, stages, scanners, control system, and software. Machining of metals such as Cu, Al, or stainless steel, and fused silica surfaces at high-fluence and high-exposure doses at high scan speeds up to 3 m/s were tested for the fluence scaling of ablation volume, which was found to be linear. Modified surfaces are color-classified for their appearance, which is dependent on surface roughness and chemical modification. Such colour-coding can be used as a feedback parameter for industrial process control.

Social biases may concentrate attention of researchers on a small number of well-known molecules/mechanisms leaving others underexplored. In accordance with this view, central to mechanistic toxicology is a narrow range of molecular pathways that are assumed to be involved in significant part of responses to toxicity. It is unclear, however, if there are other molecular mechanisms which play important role in toxicity events but are overlooked by toxicology. To identify overlooked genes sensitive to chemical exposures we used publicly available databases. First, we used data on published chemical-gene interactions for 17,338 genes to estimate their sensitivity to chemical exposures. Next, we extracted data on publication numbers per gene for 19,243 human genes from Find My Understudied Genes database. Threshold were applied to both datasets using our algorithm to identify chemically sensitive and chemically insensitive genes and well-studied and underexplored genes. 1,110 underexplored genes highly sensitive to chemical exposures were used in GSEA and Shiny GO analyses to identify enriched biological categories. Metabolism of fatty acids, amino acids, and glucose were identified as underexplored molecular mechanisms sensitive to chemical exposures. These findings suggest that future effort is needed to uncover the role of xenobiotics in the current epidemics of metabolic diseases.