Network Slicing serves as an enabler for the new fifth generation (5G) of mobile networks era as it enhances connectivity and diverse network slice requirements across various user devices. Optimally orchestrating these 5G network slices to meet the varying demands of applications with diverse quality of service (QoS) requirements and stringent high performance metric remains a challenge today [1]. In this paper, a smart and novel machine learning (ML)-based framework, which dynamically sub-slice in real time and optimally orchestrate a 5G network slice is proposed. Our proposed framework incorporates series of supervised machine learning algorithms with the use of LazyPredict module to find and suggest the best-fit model and make intelligent decisions for the specific network data environment being monitored in real time or analysed with historical dataset. Additionally, the framework employs reinforcement-learning techniques to predict future network traffic data pattern thereby optimally allocating network resources and orchestrating alternative best fit bespoke network slice. This alternative network sub-slice is orchestrated as required to reduce the risk of denial of service and improve user experience. This ultimately forms the proposed new vertical Enterprise Network as a Service: Company Network as a Service (CNaaS) in this study. The proposed approach is extensively evaluated through simulations using python with MATLAB and Simulink. This identified the important features and performance metrics for the 5G network data and demonstrated the efficiency and improvement in key metrics such as latency, throughput, jitter, packet loss rate, and available network resource utilisation compared to conventional methods [1]. The results highlight the importance of leveraging the right machine-learning algorithm for each unique network as the demand requirements changes. The proposed Enhanced Sub-Slice (eSS) module with embedded series of machine learning algorithms using the Lazypredict shows that one size does not fit all and demonstrates the significance of leveraging advanced ML techniques and ML pipelines in the context of 5G network slice management and orchestration.

In our recent experimental study we found that variability in sarcomere lengths (SLs) is lower if we get them from A-band centers (visualized by Second Harmonic Generation microscopy, SHG) vs. Z-disks (ANEPPS-staining of t-tubules). In the present study we demonstrate, using a simulation approach, that the extent of variability and “randomness” in SL are directly affected by what “sarcomeric structure” is used to calculate the SL. We simulated randomly dispersed positions of Z-disks and calculated the center points between two Z-disks as A-band centers. We found that variance in SL, if calculated from A-band centers (A-SL), was twice lower vs. variance in Z-disk-based SL (Z-SL), regardless the predefined dispersion of Z-disks. Furthermore, A-SLs were “non-randomly” interrelated – each next A-SL tended to be longer if the preceding one was longer – in contrast to Z-SLs which were truly random. Next, we demonstrated the presence and prevalence of this “non-random” effect for A-SL vs. Z-SL in our previously acquired experimental records. The rationale for this artifact is the “mathematical dependence” of sarcomere center on its edges, and it must always be taken into account in the interpretation of smaller variability of the distance between sarcomeric A-band centers vs. the distance between Z-disks.

Protein 53 (P53) shows different functions either to support or to contrast malignant growth. P53 history tells that discoveries of molecular features have contributed to the emergence of P53 functions. Conversely, the shift of paradigms demonstrates that P53 functions coexist even if are in conflict with one another. Since 1979, five paradigms have been assembled then deconstructed by taking into account P53 functions of viral protein, oncogene, tumor suppressor gene, transcription factor, apoptotic factor. By summarizing the past five disassembled P53 paradigms, in this investigation the current paradigm involving P53 in the modulation of a composite bio-morphological entity namely, tumor immune microenvironment (TIME) is analyzed. The aims of this investigation were to provide an overview of solid and validated knowledge occurring in all P53 paradigms and to determine P53 abilities to modify TIME through manipulation of viruses. As a result, definitive P53 evidence concerns its genetic localization, amino acids composition, its isoforms and subcellular expression in organelles. P53 “mutome” assembles all mutations affecting this complex protein. Lastly, both categories of tumor promoting and non-oncogenic viruses related to P53 were scrutinized. In conclusion, paradigms teach that P53 is undruggable because its drugs inevitably target all P53 functions.

Image restoration plays a vital role in image processing and pattern recognition in producing better recognition accuracy. It was observed that, most of the traditional restoration algorithms were meant for removing a single type of noise and efforts have been made towards the use of partial differential equation model (PDE), to restore different types of images such as super-resolution, bleeding through and deblurring. This research work deployed hybridized shock filter, shock diffusion of higher order PDE to remove degraded images that have been affected by atmospheric turbulence and water smear images. Degraded images of different types were acquired from various sources. The degraded images were subjected to shock filter algorithm, shock diffusion of higher order PDE. The shock filter was combined with PDE, likewise the shock diffusion was also combined with PDE, and the three algorithms were also combined to test the efficiency of the hybridized method on different degraded images. The result was validated using Mean Square Error, Structural Similarity Index Measure (SSIM), Peak-to-Noise-Signal -Ratio (PNSR) and universal quality index (UQI). From the result, it was observed that the combination of many image restoration algorithms does not give better results whereas, the combination of two of the algorithms has really proved effective.

To clarify effects of weathered coal humic acid on water-stable aggregates and pore characteristics of reclaimed cambisol, this research analyzed the evolution characteristics of soil aggregates and pores. Effects of different humic acid dosages (0, 1%, 3%, and 5% by weight) and application period (1 year, 2 years, and 3 years) on soil aggregates and organic carbon components in soil water-stable aggregates were investigated. The results showed that water-stable macroaggregates (>0.25 mm) had the highest content in the first year; but in the third year, water-stable microaggregates (0.053–0.25 mm) had the highest content, and silt and clay (<0.053 mm) were at a maximum. In the third year of 5% treatment, mean weight and geometric mean diameters were the largest, soil structure was the most stable, and TOC and water-stable microaggregates (0.053–0.25 mm) in soil had the highest proportions. For 5% treatment, the majority of irregular pores were independent in the first year, and number of pores decreased in the second year, but average pore volume increased, forming robust connected pores. In the third year, the number of elongated and irregular pores increased. In the third year of 5% treatment, most pores were irregular and of size >100 μm, and soil structure was the most stable.

Background: Despite recent advancements, medical technology has not yet reached its peak. Precision medicine is growing rapidly, thanks to machine learning breakthroughs powered by increased computational capabilities. This article explores a deep-learning application for computer-aided diagnosis in dermatology. Methods: Using a custom model based on EfficientNetB3 and deep learning, we propose an approach for skin lesion classification that offers superior results with smaller, cheaper, and faster inference times compared to other models. The skin images dataset used for this research includes 8,222 files selected from the authors' collection and the ISIC2019 archive, covering six dermatological conditions. Results: The model achieved 95.4% validation accuracy on four categories—melanoma, basal cell carcinoma, benign keratosis-like lesions, and melanocytic nevi—using an average of 1,600 images per category. Adding two categories with fewer images (about 700 each)—squamous cell carcinoma and actinic keratoses—reduced the validation accuracy to 88.8%. The model maintained accuracy on new clinical test images taken under the same conditions as the training dataset. Conclusions: The custom model demonstrated excellent performance on the diverse skin lesions dataset, with significant potential for further enhancements.

Estimating the ocean’s subsurface thermohaline information from satellite measurements is essential for understanding ocean dynamics and El Niño phenomenon. This paper proposes an improved double-output Residual Neural Network (DO-ResNet) model to concurrently estimate the ocean subsurface temperature (OST) and ocean subsurface salinity (OSS) in the tropical Western Pacific using multi-source remote sensing data, including sea surface temperature (SST), sea surface salinity (SSS), sea surface height anomaly(SSHA), sea surface wind (SSW), and geographical information (including longitude (LON) and latitude (LAT)). In the model experiment, Argo data were used to train and validate the model, and the root mean square error (RMSE), normalized root mean square error (NRMSE) and coefficient of determination (R²) were employed to evaluate the model's performance. The results showed that the sea surface parameters selected in this study have a positive effect on the estimation process, and the average RMSE and R² values for estimating OST (OSS) by the proposed model are 0.34 °C (0.05 psu) and 0.91 (0.95), respectively. Under the data conditions considered in this study, DO-ResNet demonstrates superior performance relative to the extreme gradient boosting model, random forest model, and artificial neural network model. Additionally, this study evaluates the model’s accuracy by comparing its estimations of OST and OSS across different depths with Argo-derived data, demonstrating the model's ability to effectively capture the most spatial features, and by comparing NRMSE across different depths and seasons, the model displays strong seasonal adaptability. In conclusion, this research introduces a novel artificial intelligence technique for estimating OST and OSS in the tropical Western Pacific Ocean.

It is shown that if there exists in nature a pair of heavy elementary particles each with a charge equal to that of the proton and with mass energy , then their direct interaction gives rise to a spontaneous fractionation of the two charges into three pairs of elementary particles according to two equiprobable channels, one hadronic and one leptonic. The leptons and quarks produced are in agreement with the first generation of the Standard Model of matter. Fractionation suggests the relative abundances of the elementary particles, introducing some questions about the possibility of the real existence of a currently unknown particle and its role in the formation of an apparent matter-antimatter asymmetry in the universe.

Case studies (CS) attempt to help students increase critical thinking skills and engagement while working through a real-life scenario in various disciplines, including medicine, law, and business. However, the CS method has not been heavily utilized in biological sciences. The present study investigated the effect of the CS method on undergraduate biology students’ conceptual understanding, academic outcomes, and perspectives. A case study was applied in a one-semester undergraduate biology course, which was compared to ten semesters of standard sections. Participants completed course pre- and post-tests, pre- and post-case tests, and an online survey to assess their conceptual understanding and engagement. The initial lowest quartiles were determined from the individual course pre-test scores, which were lower than class averages. Results suggested that the CS method helped students in learning outcomes, critical thinking, and conceptual understanding toward biology. In post-test learning gains, the CS group did 20% better than the non-CS group, with the largest benefit seen in the initially lowest pre-test quartile of the class. Moreover, post-case learning gains were 55% improved in the case test. Survey results indicated that students had positive attitudes toward CS for their engagement in plant biology content. Overall, the distribution of A grades improved by 2.6-fold from standard to CS groups. We conclude that the use of CS may address course content engagement and have the potential to effectively boost academic performance, especially for the initially lowest quartile in undergraduate plant biological sciences courses.

The study aims to utilize the convergence-confinement method (CCM) by considering non-hydrostatic stress assumptions in the analysis of the surrounding rock in a circular tunnel. The rock mass properties should adhere to the criteria of the non-linear Hoek-Brown failure criterion. Through a thorough theoretical analysis approach, an analytical solution is derived to determine the stress and displacement induced by tunnel excavation, particularly in the elastic and plastic zones. This solution, applicable under anisotropic stress conditions, involves accounting for confinement loss incrementally for computational feasibility. The implementation of this analytical solution, facilitated by a straightforward spreadsheet, was validated against existing data to evaluate the impact of non-linear failure criteria on ground reaction behavior. The study scrutinizes the mechanical response at the tunnel's inner curve and assesses stress-displacement distribution across the tunnel cross-section. A comparison between the proposed solution and published results demonstrates a consistent and promising correlation.

This paper presents a comprehensive analysis of the financial factors and risk management strategies essential for optimizing disaster resilience within the Serbian defence industry's critical infrastructure. The significance of this sector is multi-faceted, impacting national security, economic stability, and technological advancement. Primarily, the Serbian defence industry ensures the preservation of vital defence interests, maintaining Serbia's independence from foreign sources for weapons and military equipment in both peacetime and wartime. Economically, it is a significant employer of the working-age population, directly affecting local employment rates, fostering economic development, and ensuring the sustainable growth of this crucial sector. This, in turn, stimulates broader economic activity and enhances social cohesion while strengthening the national balance of payments through increased export potential. From a technological perspective, the defence industry drives scientific, technological, and industrial development, reinforcing Serbia's global political and military standing within the Western Balkans and on the international stage. Consequently, the paper aims to examine the risk management and protection of the Serbian defence industry's critical infrastructure, offering concrete and actionable measures to improve and develop these systems with a particular emphasis on security. The research's utility and contribution lie in identifying similarities and differences in the operational performance of defence industry companies, a vital segment of the national economy. The presentation of these findings focuses on the protection of critical infrastructure. The results will form the basis for further investigation into the underlying causes of business performance and the effective management of critical infrastructure security.

Aortic stenosis continues to be still the most frequently valvular pathology in the elderly population of the Western countries. According to the latest guidelines, the therapeutic choice of aortic stenosis depends on the age of the patient (<75 years or >75 years) and the risk class (STS-Prom/ Euroscore II < o > 4%). Therefore, if the surgical indication is clear in young and low risk patients and percutaneous treatment is the gold standard in older and high-risk patients, the therapeutic choice is still debated in intermediate-risk patients. In this group of patients the aortic valve stenosis treatment depends on the patient's global evaluation, on the experience of the center and no less important on the patient's will. Two main therapeutic options are debated: surgical aortic valve replacement with sutureless prosthesis versus transcatheter aortic valve implantation. In addition, the progressive development of mininvasive techniques for aortic valve surgery (right -anterior minitoracotomy) has also reduced the peri and post -operative risk in this group of patients. The goal of our review is to analyze the literature evidence of the best therapeutic choice in intermediate risk patients with severe aortic stenosis.

Urban ultra-low altitude airspace (ULAA) presents unique challenges for unmanned aerial vehicle (UAV) path planning due to high building density and regulatory constraints. This study analyzes and improves classical path planning algorithms for UAVs in ULAA. Experiments were conducted using A*, RRT, RRT*, and artificial potential field (APF) methods in a simulated environment based on building data from Chengdu City, China. Results show that traditional algorithms struggle in dense obstacle environments, particularly APF due to local minima issues. Enhancements were proposed: a density-aware heuristic for A*, random perturbation for APF, and a hybrid optimization strategy for RRT*. These modifications improved computation time, path length, and obstacle avoidance. The study provides insights into the limitations of classical algorithms and suggests enhancements for more effective UAV path planning in urban environments.

The large energy band gap associated with titanium oxide nanoparticle is a limitation to its application as a photo catalyst within the solar spectrum. More than 45% of solar radiation can be utilized at a reduced energy band gap of 〖TiO〗_2. Various structural modifications in 〖TiO〗_2 targeted in optimized photo catalyst application include the enhancement of its support system. Activated carbon supported 〖TiO〗_2 nanoparticle may produce the desired reduction in the energy band gap, reduce electron recombination and consequently enhance its photocatalytic activity in the visible region of electromagnetic spectrum. In the current investigation, an activated carbon made from the leaves of an invasive plant (Acacia Saligna) was applied as a support in the synthesis (hydrothermal process) of 〖TiO〗_2 nanoparticle. The determination of energy band-gap of 〖TiO〗_2 supported activated carbon using UV-Vis spectrophotometer gave 2.11 eV. Likewise, Scanning Electron Microscopy (SEM-EDS), Fourier transformer infrared (FTIR), XRD and Brunauer- Emmett-Teller (BET) showed that 〖TiO〗_2was successfully immobilized on the activated carbon’s external surface. The BET results showed that the synthesized 〖TiO〗_2exhibits small hysteresis phenomenon which represent a typical type IV isotherm attributed to mesosoporous material with a low porosity. Meanwhile, these XRD results reveal the presence of mixture of rutile and anatase crystalline phase

As an important part of coastal wetlands, tidal flats provide unique ecosystem services and functions. China's tidal flats are significantly threatened by industrialization, urbanization, aquaculture expansion and coastline reconstruction, and there is an urgent need for sustainable strategies to balance the protection and utilization of tidal flats. Remote sensing technology can realize large-scale spatiotemporal research of tidal flats, comprehensively improve the ecological environment of coastal zones, and help achieve the overall planning goals of major projects for the protection and restoration of important ecosystems in China. In this study, based on GEE (Google Earth Engine) platform, Sentinel-2 (MSI), Landsat 8 (OLI) and Landsat 9 (OLI-2) remote sensing images were used to construct multi-source intensive time series remote sensing image collection, combined with MSIC-OA algorithm. The tidal flat data of China in 2018 and 2023 are extracted and analyzed. The results show as follows: 1) The overall classification accuracy of the tidal flat in 2023 is 95.19%, and the Kappa coefficient is 0.89; In 2018, they were 92.77% and 0.83 respectively. 2) The total tidal flat area in 2018 and 2023 is 8300.34km2 and 8151.54km2, respectively, a decrease of 148.80km2; 3) In 2023, estuarine and bay tidal flats will account for 54.88% of the total area, and most of the tidal flats will be distributed near river inlets and bays; 4) In 2023, the total length of the coastline adjacent to the tidal flat is 10196.17km, of which the artificial shoreline accounts for 67.06%, and the development degree of the tidal flat is 2.04, indicating that most of the tidal flat has been developed and utilized. The research results provide valuable reference for the scientific planning and rational utilization of tidal flat resources in China.

This study aimed to analyse the relationship between environmental, social, and governance disclosure (ESG disclosure) and the performance of Saudi Arabian companies. Looking at the Saudi Arabian context, ESG disclosure guidelines were issued in 2018 to encourage Saudi companies to disclose their ESG practices. Grounded in the frameworks of agency and signalling theory, this study bears profound implications for stakeholders, decision makers, policymakers, and academics alike. Our findings underscore the paramount significance of ESG disclosure practices in enhancing corporate performance and creating long-term value for stakeholders within the Saudi Arabian context. The analysis is based on panel data spanning from 2017 to 2022. Rigorous econometric methods, including fixed effects (FEs), random effects (REs), the Hausman test, and the Generalised Method of Moments (GMM), were employed in the analysis. Furthermore, to evaluate corporate performance, we also used vital indicators, such as the return on assets (ROA), return on equity (ROE), and Tobin’s Q. To score companies’ sustainability practices, we created an ESG index that was obtained through a principal component analysis of individual environmental, social, and governance scores using a sample extracted from the annual reports of the top 100 non-financial listed companies in the Saudi Arabian stock exchange (Tadawul). The results of this study provide a strong confirmation of the significantly positive relationship between ESG disclosure and companies’ key performance variables. These results are consistent with stakeholder theory, which argues that companies that actively manage their stakeholders through comprehensive ESG practices have better financial performance; this is also in agreement with signalling theory, which argues that the positive relations found in this study can be a signal sent to policymakers and decision makers. This finding should instil confidence in the potential of ESG practices to drive companies’ success. Recommendations include strengthened regulatory frameworks, awareness-raising campaigns for ESG philosophies among investors and potential target companies, capability enhancement programs, arrangements for engagement with stakeholders, and effective reward/confirmation mechanisms in credit/debit plans, if possible, to encourage more companies to adopt ESG disclosure and to help stakeholders, decision makers, policymakers, and academics improve their awareness. These measures, if implemented, can significantly enhance the ESG landscape in Saudi Arabia, inspiring a more sustainable and responsible business environment. This research sheds light on the complex processes by which ESG considerations and corporate strategy remain integrated by using advanced econometric methodologies that suggest important policy implications. The findings of this study underscore the critical role of sustainable business practices in enhancing corporate performance, fostering societal development, and ensuring sustainability within the context of Saudi Arabian enterprises

Background: Emerging and re-emerging infectious diseases that infect wildlife, such as African swine fever, avian influenza, and SARS-CoV-2, have highlighted the necessity for wildlife health surveillance (WHS) due to their direct and indirect impacts on wildlife species, ecosystems, domestic animals, and human health. While global policies and guidelines exist, a critical gap remains in local-to-national implementation of WHS systems. A group of local, national, and global actors in WHS have formed a working group to address this gap. Methods and Findings: The working group reports on a theory of change (ToC) developed to implement WHS from local to global scales. Through brainstorming, plenary exercise, and building on peer-reviewed science and existing surveillance systems, we identified six transformative pathways to be implemented via collaborations across scales and contexts: mindset change, policy and investment, user-driven science, user-driven technologies, capacity enhancement, and mobilization of a global community of practice. Interpretation: This ToC serves as a roadmap to develop effective WHS systems that support adaptive management and implementation. WHS is fundamental to understanding the impacts of health threats to biodiversity and human and domestic animal health. This ToC presents an approach to operationalize integration of wildlife health into collaborative One Health surveillance. Funding: The Science for Nature and People Partnership.

This study investigates the transformative impact of technology adoption on retail marketing strategies, focusing on artificial intelligence (AI), big data analytics, augmented reality (AR), virtual reality (VR), mobile technology, and automated customer service solutions. Through qualitative research methods, including interviews and thematic analysis, insights were gathered from industry stakeholders across diverse retail sectors. The findings reveal that AI facilitates personalized marketing through data-driven insights, enhancing customer satisfaction and loyalty. Big data analytics enable retailers to forecast trends, optimize inventory, and tailor marketing strategies to consumer preferences effectively. AR and VR technologies enrich customer experiences by offering immersive and interactive shopping environments, bridging the gap between physical and digital retail spaces. Mobile technology supports omni-channel strategies, providing seamless integration and personalized interactions across platforms. The COVID-19 pandemic accelerated digital transformation in retail, emphasizing the resilience and adaptability of technology-driven strategies in navigating disruptions. AI-powered chatbots and virtual assistants streamline customer service operations, enhancing efficiency and customer satisfaction.

Climate change and the increasing frequency and severity of drought events pose significant challenges for sustainable agriculture worldwide. Soil microorganisms, both beneficial and pathogenic, play a crucial role in mediating plant-environment interactions and shaping the overall functioning of agroecosystems. This review synthesizes the current knowledge on the contrasting adaptive mechanisms utilized by different groups of plant-soil microorganisms focusing on beneficial and pathogenic bacterial and fungal communities in response to drought and desiccation stresses. The review examines the common survival strategies employed by microbes specifically rhizobacteria and arbuscular mycorrhizal fungi, such as the production of osmoprotectants, altered gene expression, and biofilm formation. It also highlights the distinct adaptive mechanisms of pathogenic versus mutualistic microbes, with pathogens tending to prioritize virulence factors and suppress plant growth, while beneficial microbes enhance plant growth and stress tolerance. Genetic exchange such as horizontal gene transfer (HGT) is identified as a key adaptive mechanism, allowing both pathogenic and non-pathogenic microbes to acquire beneficial traits like stress tolerance and virulence factors. Environmental stressors like drought can promote increased genetic exchange and the spread of pathogenic traits within the soil microbiome. The complex interplay between drought-adapted microbes and their interactions with plants is discussed, emphasizing the need for a deeper understanding of soil microbiome dynamics under climate change. This knowledge can be utilized in sustainable agricultural practices to mitigate the impacts of drought on plant health and productivity. This review provides insights into the divergent survival strategies of soil microorganisms in response to drought and desiccation, for managing the resilience of agroecosystems to climate change.

Abstract Background: Temporomandibular disorders (TMD) are a range of clinical problems related to the temporomandibular joint (TMJ), chewing muscles, and surrounding facial structures. Functional magnetic resonance studies suggest that these disorders affect over 5% of the population. The relationship between dental occlusion and TMD has been a topic of debate in dentistry; some researchers suggest using lateral cephalograms and cephalometric data to identify which morphological profiles and types of malocclusion are most likely to cause TMD. The aim of this study is to identify the morphological profiles and associated skeletal malocclusions that have the greatest influence on the development of TMD. This will be accomplished through the analysis of cephalometric data obtained from cephalograms and condylar section images of patients from the Orthognathodontics Department of Chieti, who underwent low-dose cbct during their initial visit. Matherial and methods: This study, conducted at the Orthognathodontics Department of Gabriele D’Annunzio University in Chieti, examined a group of 67 patients (both males and females) presenting with signs of temporomandibular joint disorders (TMD). The inclusion criteria for the study were first-time TMD diagnosis, age 18 and above, and accessible medical records, wide field of view cone beam low dosage, and photographs. Patients with a history of tumor, trauma, surgical interventions in the jaw and facial area, fractures, and other craniofacial anomalies were excluded from the study. The aim of the study is to further understand the morphological profiles and associated skeletal malocclusions that contribute to TMD. Results: male patients: sagittal profile: 56% exhibited a skeletal Class II profile due to mandibular retrognathia. Vertical Profile: 73% were brachyfacial with a hypodivergent pattern. Dental Relationships: Increased overjet and a tendency towards deep bite were observed. 23% exhibited deep bite, 20% were normodivergent, and 8% were dolichofacial. The soft tissue profile tended towards flatness. Condyle Position: in Class II hypodivergent males, the condyle was non-concentric and positioned more posteriorly. In mesiodivergent males, the condyle was concentric, while in hyperdivergent males, it was slightly anterior. Female Patients: Sagittal Profile: 79% had a skeletal Class II profile with mandibular retrognathia. Vertical Profile: 47% were hypodivergent with reduced anterior facial height (105°). Dental Relationships: 17% exhibited deep bite, and 48% of those with a Class II profile had increased overjet. 43% were mesofacial, and 10% were dolichofacial. Condyle Position: In Class II hypodivergent and normodivergent females, the condyle was non-concentric and positioned more posteriorly. In hyperdivergent females, the condyle was positioned more anteriorly and higher in the fossa. Conclusion: The study highlighted significant differences in cephalometric parameters and condyle positions between male and female patients with TMD. A posteriorly positioned condyle was associated with a flattened condylar head, particularly in Class II hypodivergent profiles. These findings underscore the importance of individualized diagnostic and treatment approaches based on detailed cephalometric and condylar assessments. Further research is needed to explore the implications of these variations for TMD management and outcomes.

This work focuses on the well-known issue of mass conservation in the context of the finite element technique for computational fluid dynamic simulations. Specifically, non-conventional finite element families for solving Navier-Stokes equations are investigated to address the mathematical constraint of incompressible flows. Raviart-Thomas finite elements are employed for the achievement of a discrete free-divergence velocity. In particular, the proposed algorithm projects the velocity field into the discrete free-divergence space by using the lowest-order Raviart-Thomas element. This decomposition is applied in the context of the projection method, a numerical algorithm employed for solving Navier-Stokes equations. Numerical examples validate the approach’s effectiveness, considering different types of computational grids. Additionally, the presented paper considers an interface advection problem using marker approximation, in the context of multiphase flow simulations. Numerical tests, equipped with an analytical velocity field for the surface advection, are presented to compare exact and non-exact divergence-free velocity interpolation.

Classifiers face a myriad of challenges in today’s data-driven world, ranging from overfitting and high computational costs to low accuracy, imbalanced training datasets, and the notorious black box effect. Furthermore, many traditional classifiers struggle with the robust handling of noisy and missing feature values. In response to these hurdles, we present classification methods that leverage the power of feature partitioning learning and outranking measures. Our classification algorithms offer an innovative approach, eliminating the need for prior domain knowledge by automatically discerning feature intervals directly from the data. These intervals capture essential patterns and characteristics within the dataset, empowering our classifiers with newfound adaptability and insight. In addition, we employ outranking measures to mitigate the influence of noise and uncertainty in the data. Through pairwise comparisons of alternatives on each feature, we enhance the robustness and reliability of our classification outcomes. The developed classifiers are empirically evaluated on several data sets from UCI repository and are compared with well-known classifiers including k Nearest Neighbors (K-NN), Support Vector Machine (SVM), Random Forest (RF), Neural Network (NN), Naive Bayesian (NB) and Nearest Centroid (NC). The experiments result demonstrate that the classifiers based on feature interval learning and outranking approaches are robust to imbalanced data and to irrelevant features and achieve comparably and even better performances than the well-known classifiers in some cases. Moreover, our proposed classifiers produce more explainable models whilst preserving high predictive performance levels.

Recovery after visual loss is a key goal of neuroscience and treatments able to improve visual function are still largely lacking. Glaucoma, one of the leading causes of visual disability in the world, is usually associated with elevated intraocular pressure (IOP) but a subset of “normal tension glaucoma” patients develops damage without ever manifesting high IOP. Sometimes, even in patients with a good control of IOP, the retinal ganglion cell degeneration can progress forward the blindness. Moreover usually the damage already caused by the disease remains. These considerations underline the needs to find new effective treatments and solution to add to the standard ones. In this paper, we expose the most important data supporting the use of alternating current stimulation, a relatively new option for treating low vision, in glaucoma including the theoretical bases of this approach.

This qualitative study explores supplier collaboration in e-commerce product development, examining motivations, challenges, strategies, outcomes, and ethical considerations. Through in-depth interviews with stakeholders from diverse e-commerce sectors, the study identifies key themes shaping collaboration dynamics. Motivations include innovation, operational efficiency, and strategic partnerships, driving companies to integrate supplier expertise early in product development. Challenges such as global supply chain complexities, goal misalignment, and communication barriers underscore the need for robust governance and cultural sensitivity. Strategies for success include technology adoption, supplier development programs, and collaborative decision-making, enhancing supply chain visibility and mutual benefits. Effective collaboration yields improved product quality, cost efficiencies, and enhanced customer satisfaction, supporting competitive advantage. Ethical sourcing practices and sustainability initiatives are crucial for maintaining trust and regulatory compliance. Cultural and organizational factors, including leadership support and change management, significantly influence collaboration outcomes. The study concludes with implications for theory and practice, emphasizing the role of innovative strategies and continuous improvement in supplier relationships. Future research could explore digital transformation, sustainability trends, and technological impacts on supplier collaboration in e-commerce. Practical applications include optimizing supply chain strategies to navigate complexities and capitalize on market opportunities.

Lung cancer (LC) continues to be an important public health problem being the most common form of cancer and a major cause of cancer deaths worldwide. Despite the great bulk of research to identify genetic susceptibility genes by genome-wide association studies, only few loci associated to nicotine dependence have been consistently replicated. Our previously published study in few phenotypically discordant sib-pairs identified a combination of germline truncating mutations in known cancer susceptibility genes in never smoker early-onset LC patient does not present in their healthy sib. These results firstly demonstrated the presence of an oligogenic combination of disrupted cancer predisposing genes in non-smokers patients, giving experimental support to a model of a “private genetic epidemiology”. Here, we used a combination of whole-exome and RNA sequencing coupled with a discordant sib’s model in a novel cohort of pairs of never-smokers early-onset LC patients and in their healthy sibs used as controls. We selected rare germline variants predicted as deleterious by CADD and SVM bio-informatics tools and absent in the healthy sib. Overall, we identified an average of 200 variants per patient, about 10 of which in cancer predisposing genes. In most of them, RNA sequencing data reinforced the pathogenic role of the identified variants showing: i) downregulation in LC tissue (indicating “second hit” in tumor suppressor genes); ii) upregulation in cancer tissue (likely oncogene); iii) downregulation in both normal and cancer tissue (indicating transcript instability). The combination of the two techniques demonstrates that each patient has an average of six (with a range from four to eight) private mutations with functional effect in tumor predisposing genes. The presence of a unique combination of disrupting events in the affected subjects may explain the absence of familial clustering of non-small cell lung cancer. In conclusion, these findings indicate that each patient has his/her own “predisposing signature” to cancer development and suggest the use of personalized therapeutic strategies in lung cancer.

Coppicing has been neglected in recent decades leaving gaps in knowledge on silvicultural interventions, especially the long-term effects on coppices of South-East Europe. Thus, our work aims to define the long-term effects of thinning in sessile oak (Quercus petraea (Matt.) Liebl.) and European beech (Fagus sylvatica L.) sub-mountainous thermophilic low coppices in the Croatian Dinarides. The experiment includes two localities with thinning plots and control plots. Thinning was done in 2002 with 17.71% of wood volume removed in the European beech coppice and 26.09% in the sessile oak coppice. 1276 trees were marked, measured (DBH, tree height, number of stems per stump) and assessed for vitality, origin and six silvicultural features revealing tree quality. Descriptive statistics for all variables, RMANOVA for DBH and height and for continuous variables mean+-+ standard deviation for categorical frequency and relative frequency variables were carried out. The results show a statistically significant positive long-term effect of thinning on tree growth, stem and crown features and support findings that thinning, by increasing growth and quality, is a necessary intervention in European beech and sessile oak low coppices. The recent economic crisis, the sudden increase in energy prices, and the increased demand for assorted wood products have initiated higher interest in coppices in Croatia.

The Um Ara granites are a suite of granitoid rocks located in the south Eastern Desert of Egypt. The combination of Back Scattered Electron imaging (BSE), X-ray compositional mapping, and the data of the Electron Probe Micro Analyzer (EPMA) has provided valuable insights into the alteration process of zircon in the Um Ara granite. The investigated zircon grains have measurable amount of non-formula elements such as U, Th, Hf, REEs, P, Al, Ca, Fe, and Ti, along with extensive structural features indicative of radiation damage. These characteristics point to significant hydrothermal alteration of the zircon following its initial crystallization. The textural and geochemical evidence suggests the alteration of the Um Ara zircons was driven by coupled dissolution-reprecipitation processes influenced by aqueous fluids. The breakdown of accessory minerals like xenotime, thorite, monazite, and apatite during a major hydrothermal event around 1.8 Ga released the non-formula elements (U, Th, P, Ca, Al, Fe, REEs) that were then incorporated into the zircon structures. Subsequent pluvial periods around 50,000-159,000 years ago may have allowed further uptake of these elements during low-temperature alteration. The shear zones within the Um Ara granites facilitated the mobilization and transport of the non-formula element-bearing fluids, likely as carbonate and fluoride complexes. The temperature regime, with fluids remaining below 300°C, was crucial in preserving the radiation damage features in the zircons despite the extensive chemical changes.

Suboptimal nutrition is a leading cause of cardiometabolic disease and mortality. Biological sex is a variable that can play a role in individual response to nutritional factors and may modulate the impact of nutrition on disease. This narrative review explores the intricate interplay between sex, nutrition, and health outcomes, and the consequent importance of considering sex in nutrition research, dietary recommendations, and disease management. We examine the impact of sex on how various dietary patterns, including the Mediterranean diet, macronutrient content and quality, Western diet, and energy restriction associate with or affect metabolic health and disease risk. Understanding how sex influences the response to the diet can inform precision nutrition interventions and approaches for disease prevention and management.

Stagnating low renovation rates, vacancies and underused town centers, unprecedentedly high levels of land sealing and excessive consumption of resources through the construction of new buildings and infrastructure as well as the effects of climate change were some of the reasons for carrying out the monumentum ad usum research project.Thermodynamic simulations were used to carry out in-depth analyses of specific building parameters such as energy balances and how they are influenced by the effects of climate change. Life cycle analyses under ecological and economic aspects examined the aspects of sustainability and the individual behaviour of predominantly listed existing buildings under standardized conditions.The project results show that sustainable refurbishment can significantly increase the attractiveness of using historic and listed buildings for non-profit building owners. The results and conclusions of the project are as varied as the recommendations derived from them. In practice, old buildings consume significantly less energy than predicted in the structural calculations. Correction factors are to be developed and thermodynamic simulation calculations are to be used instead of energy performance certificates for more realistic forecasts of energy requirements and emission savings potential. The aspects of sustainability in refurbishment are essential for the protection of our architectural heritage.

Monensin and essential oils have antimicrobial properties that may impact silage fermentation. The present study investigates the effects of monensin and essential oils as additives in the ensiling of total mixed ration (TMR). In the first assay, TMR was tested with sheep in growth (65% dry matter - DM) using the following treatments: control (no additive), MON35 (35 mg monensin/kg DM), MON45 (45 mg monensin/kg DM), ELO300 (300 mg essential oil/kg DM), and ELO600 (600 mg essential oil/kg DM). In the second assay, the same treatments were used in TMR for lactating cows under two moisture conditions (30% and 40% DM). The parameters assessed included fermentative losses, short-chain fatty acid profile, aerobic stability, chemical-bromatological composition, and in vitro DM digestibility of the silages. In the first assay, the treatments with ELO had the lowest pH values and the highest lactic acid concentrations, with treatment ELO600 leading to the highest aerobic stability (297.88 h). Only the starch contents of the ELO treatments were lower than the others. In the second assay, the silages with the highest moisture contents and ELO600 exhibited the lowest values of DM recovery, lactic acid, and pH. The highest lactic acid:acetic acid ratios were observed in the silages with the most moisture added with MON35 and MON45. The use of MON and ELO increased aerobic stability, with the highest values observed for ELO600 and MON35. The treatments with MON and ELO resulted in silages with the lowest fiber contents and highest ether extract and starch contents when compared with control. Thus, MON and essential oils improve fermentative quality but ELO should be used in lower doses in humid silages to avoid negative fermentation impacts.

Quill mites of the family Syringophilidae are widely distributed parasites of birds inhabiting the interior of feather quills. In this paper, we provide detailed information on the host spectrum and distribution for six previously described species of syringophilines associated with starlings with new host and locality records. Additionally, we describe three new species, Aulonastus indonesianus Marcisova, Skoracki and Patan sp. n. from the Common Hill Myna Gracula religiosa Linnaeus in Indonesia (Java) and the White-necked Myna Streptocitta albicollis (Vieillot) in Indonesia (Celebes), Aulonastus anais Skoracki and Patan sp. n. from the Golden Myna Mino anais (Lesson) in Papua New Guinea, and Syringophiloidus poeopterus Skoracki and Patan sp. n. from the Abbott's Starling Poeoptera femoralis (Richmond) in Tanzania. Finally, we explore the host-parasite interactions within the system comprising starlings and syringophiline mites.

This paper focuses on distributed generation (DG) controller of a PV based Micro Grid. An independent DG controller (IDGC) is designed for PV applications to improve maximum power point tracking (MPPT) in Micro Grid (MG). Extreme learning machine (ELM) based MPPT method exactly estimate the reference input of converter control. They are voltage and current at MPP. Feedback controls employ linear PI schemes or nonlinear, intricate techniques. Here the converter controller, IDGC is improved by measuring directly converter outputs like duty cycle. PWM index in a single DG PV-based MG. It introduces a fast learning Extreme Learning Machine (ELM) using Moore-Penrose pseudo-inverse and an online-sequential ridge re method for robust CR estimation. The approach ensures the stability of the microgrid during PV uncertainties. Internal DG control approach (IDGC) improves the strength of the Micro Grid during, three-phase faults at load bus, partial shading, irradiance change, islanding operation and load change. The model is designed and simulated in MATLAB/SIMULINK platform and some of the results are validated in hardware in simulation (HIL) platform.

In this article we have constructed a basic methodology from which important perspectives for both the Collatz conjecture and Beal's conjecture can be derived. We falsified the conjecture we previously developed on Beal's conjecture and made the falsified conjecture usable for Collatz conjecture. In this regard, we have clearly expressed the numbers that can reach 1 in the Collatz conjecture. Then, using this, we created a limit for the numbers that should be considered for the Collatz conjecture. Thanks to the analysis of this limit, we have clearly expressed the recursive Collatz function in an equation. Using this structure, we wrote a function that indicates how many times the Collatz function repeats certain numbers to reach 1.

Preoperative assessment is crucial in surgical care, traditionally relying on physical examinations and paper-based questionnaires. The emergence of digital tools like Pathpoint® ePOA represents a significant advancement, aiming to enhance the efficiency, accuracy, and standardisation of preoperative evaluations. Pathpoint® ePOA is a cloud-based platform designed to integrate seamlessly with Electronic Health Records (EHRs), providing a comprehensive, data-driven approach to preoperative assessments. It supports improved risk stratification, optimised resource allocation, and enhanced patient engagement through features such as customisable templates and real-time data integration.Current research highlights that digital preoperative tools like ePOA offer notable advantages, including increased clinical capacity, better complexity stratification, and improved patient follow-up. Despite these benefits, gaps remain in comparative studies, detailed clinical outcomes, and patient engagement strategies, indicating areas for further exploration. Pathpoint® ePOA adheres to rigorous safety standards and risk management protocols, ensuring reliability and data security while contributing to improved surgical outcomes. The benefit-risk ratio for ePOA is favourable, underscoring its potential to advance preoperative care by optimising clinical workflows and enhancing patient safety.

House construction is a unique characteristic of the swamp lands in Banjarmasin. Foundations for swampy soil require special handling. The weakness of wood materials and the inability of wood pillar foundations to support building loads are the primary causes of building problems in these swampy areas. Mistakes in foundation construction often arise from the need to expand houses to two stories or renovations. The load-bearing capacity of the wood pillar foundations used is very limited. This study aims to determine the weaknesses of wood pillar foundations to address signs of damage in house construction on swamp land. Field observation research, including the examination of house buildings and individual objects, was conducted at several construction sites in Banjarmasin as part of this study. Data presentation is descriptive. The results indicate that weak wood pillar foundation construction is characterized by damaged piles and floor subsidence. The small size of the wood pillars also limits the load-bearing capacity. The presence of broken 'sunduk' elements is one of the causes of this foundation damage. This research provides new insights into the weaknesses of wood pillar foundations and offers repair recommendations to enhance the resilience and stability of buildings on swamp land.

Background: This study aims to develop a research framework for the Social Life Cycle Assessment (S-LCA) of public services by conducting a systematic review of existing literature from 2013 to 2022. The research question focuses on how the results of the literature review can inform the advancement of S-LCA for public services. Methods: To answer this question, a qualitative and quantitative analysis of data from the Web of Science and Scopus databases was carried out. The quantitative analysis determined the total number of S-LCA and SO-LCA papers published by main journals, and main authors. The qualitative analysis highlighted the different themes and research objectives addressed in the work relating to the S-LCA of products/services and organizations. Results: The results show that 222 papers dealing with S-LCA were published in 94 journals and revealed a scarcity of work on public services, with most papers focusing on products/services and organizations. While there is a lack of direct scientific data, the study identified 17 actors, 74 impact sub-categories, and 178 indicators that could be considered for the S-LCA of public services. Conclusions: Due to the diverse nature of public services, it is crucial to develop specific stakeholder categories, sub-categories, and performance indicators for each public service. This will support the scientific community and S-LCA practitioners in applying assessing the social impacts of public services.

Nucleation is a fundamental and general process at the initial stage of first order phase transition. Although various models based on the classical nucleation theory (CNT) have been proposed to explain the energetics and kinetics of nucleation, detailed understanding on nanoscales are still required. Here we focus on homogeneous bubble nucleation, in which evaluation of the size dependence of bubble free energy is the key issue. We propose application of a formula in stochastic thermodynamics, the Jarzynski’s equality, for data analysis of molecular dynamics (MD) simulation to evaluate the free energy of bubble nucleation. As a test case, we performed a series of MD simulations with Lennard-Jones (LJ) fluid system. By applying an external spherical force field to equilibrated LJ liquid, we evaluated the free energy change during bubble growth as the Jarzynski’s ensemble average of required works. A fairly smooth free energy curve was obtained as a function of bubble radius in metastable liquid of mildly negative pressure conditions.

In the proposed article, the issues of increasing the synchronizing ability of the system of coordinated rotation of asynchronous motors are considered. Based on the T-shaped equivalent circuit, electromechanical relationships were obtained with changes in the value of the total rotor resistance and the supply voltage of individual motors. An algorithm for calculating the torques, stator and rotor currents of the motors of the system has been compiled. Based on the calculations obtained, the mechanical characteristics of the system asynchronous motors are constructed for various values of total resistance, supply voltages and rotor positions. The obtained data and graphs confirm the adequacy of the theory obtained in an analytical way. Functional and structural diagrams in small scales have been compiled, which allow simulating transient operation modes of multi-motor asynchronous electric drives in the Matlab application package. Multi-motor asynchronous electric drives with adjustable supply voltages, as well as with preliminary synchronization and synchronous braking, have been developed. Compilation of a program for the stability of a nonlinear system of a multi-motor asynchronous electric drive (MAEDs) with a thyristor voltage converter (TVC) in Matlab. Also, the modes of soft start, load shedding and surge on the motor shaft are simulated, confirming the stability of the system.

This article explores the efficiency of various clustering methods for image segmentation under different luminosity conditions. Image segmentation plays a crucial role in computer vision appli-cations, and clustering algorithms are commonly used for this purpose. The search for an adaptive clustering mechanism aims to ensure maximum symmetry of real objects with objects/segments in their digital representations. However, clustering methods performance can fluctuate with varying lighting conditions during image capture. Therefore, we assess the performance of several clustering algorithms — including k-means, K-Medoids, fuzzy c-means, Possibilistic C-Means, Gus-tafson-Kessel, Entropy-based Fuzzy, Riddler-Calvard, Kohonen Self-Organizing Maps, and Meanshift — across images captured under different illumination conditions. Additionally, we develop an adaptive image segmentation system utilizing empirical data. Conducted experiments highlight varied performance among clustering methods under different luminosity conditions. This research enhance better understanding of luminosity's impact on image segmentation and aiding in method selection for diverse lighting scenarios.

Objective To explore the endoscopic anatomical structures of lumbar surgery. Methods A total of 290 patients who underwent lumbar endoscopic surgery due to lumbar intervertebral disc (IVD) herniation from September 2020 to September 2022 were retrospectively reviewed in our hospital,179 patients had complete surgical video recordings, including 108 males and 71 females, aged from 19 to 65 years, with an average age of 41±16 years. The endoscopic structures through the intervertebral foramen and interlaminar space were independently identified by 3 doctors with more than 3 years of related surgery experience. When there were differences of opinions, the three doctors would discuss and come to a consensus. The probability, location, and neighboring structures of each specific structures were statistically analyzed. Results The anatomical structures observed through the lumbar foramen under endoscopy include muscles and ligaments attached to the superior articular process (SAP), main blood vessels inside the intervertebral foramen, blood vessels on the surface of IVD, and blood vessels on the surface of the dural sac and nerve root. The major anatomical structures observed through interlaminar space are multifidus, the conjugated ligament of ligament flavum and capsule ligament (capsule part of flavum ligaments), edges of the lamina, specific vessel bundle to facet with exit nerve root. Conclusion The anatomical structures under spinal endoscopy have certain characteristics, which are grossly different from those under open surgery. Familiarity with these anatomical structures has important clinical significance.

Background: Preserving health and physical fitness is critical to ensure independent living across the lifespan. Lower levels of physical fitness are associated with age-related cognitive decline and a higher prevalence of mild cognitive impairment (MCI). Thus, this study investigates the influence of a six-month dance intervention on selected measures of physical fitness in older adults with MCI. Methods: In this randomized controlled trial 55 patients with MCI were randomized into a sportive dance training (IG; n=26; Age: 70.7 +/- 5.6 years; 62% female) or an inactive control group (CG; n=24; Age: 69.1 +/- 6.8 years; 46% female).The dance group received two 90-minute dance training sessions per week over a duration of six-months, which focused on learning dance movement patterns. During the training sessions, heartrate was measured to control exercise intensity. Physical fitness was assessed using cardiopulmonary exercise testing (CPET), lower limb functional fitness via sit-to-stand test, handgrip strength and heart rate variability (HRV). Results: We observed that the dance intervention preserved the cardiorespiratory fitness as measured by maximal oxygen uptake (VO2max) during CPET, which decreased in the CG. Furthermore, participants in the IG demonstrated increases in leg and handgrip strength although not statistically significant. HRV displayed a nonsignificant decrease following the intervention. Conclusion: The results of this randomized controlled trial suggest that sportive dance training can preserve physical fitness in older adults with MCI. Although improvements in the other parameters were statistically non-significant, likely due to the small sample size, stabilizing muscular fitness and preventing age-related decline in older adults with MCI is important for maintaining functional independence.

The search for active cellulolytic consortia among soil microorganisms is of significant applied interest, while the dynamics of the formation of such communities remain insufficiently studied. To gain insight into the formation of an active cellulolytic community, the experiment was designed to study the colonization of a sterile substrate (cellulose) by microorganisms from two soil types: sod-podzolic and chernozem. To achieve this, the substrate was placed in the soil and incubated for six months. To assess microbiome dynamics, the experiment employed sequencing of 16S rRNA and ITS2 amplicon libraries at four-time points. It was demonstrated that from the second month of the experiment, the prokaryotic component of the communities reached a state of stability, with a community composition that was specific to each soil type. The results demonstrated that there was no relationship between changes in community diversity and soil respiration. There also was no significant shift in community diversity throughout the chronosequence. Furthermore, the taxonomic composition of the community shifted towards a decrease in the proportion of Proteobacteria and an increase in representatives of the Bacteroidota, Bacillota, and Verrucomicrobiota phyla. The network analysis of the community demonstrated that, in contrast to sod-podzolic soil, chernozem is distinguished by a higher modularity, with the formation of taxon-specific groups of microorganisms at each stage of the chronoseries. These differences are attributed to alterations in the eukaryotic component of the community, particularly in the prevalence of nematodes and predatory fungi, which in turn influenced the cellulolytic community.

The aim of this study is to assess of rare earth elements (REE) content in hair samples in children, living in Lovozero village, near REE mining site, and possible effects of REEs on the prevalence of nervous system diseases in the Lovozersky district (Murmansk region, Kola Peninsula). School-age children (53 persons) were recruited for analysis of REE content in their hair samples. REEs (Y, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu) content was estimated by inductively coupled plasma mass spectrometry (ICP-MS). Analysis of REE content in the hair of children living in the Russia, Kazakhstan and China indicates REEs intake from environment. A possible contribution of REEs to the nervous system disorders is supported by the link between REE content in the hair samples of children, living near REE mining (China) and by manifesting cognitive disorders in these children. It also turn out that highest prevalence of the nervous system diseases in children 15-17 years old manifested in the Lovozersky district then in other area in the Murmansk region. The paper discusses the possible contribution of REEs to the prevalence of episodic paroxysmal disorders (G40-G47), cerebral palsy (G80-G83), epilepsy and status epilepticus (G40-G41).

This study investigates the compliance level with Regional Regulations (PERDA) on building construction in Banjarmasin, focusing on urban areas and riverbanks. The motivation behind this research is the observed low adherence to PERDA, which aims to ensure orderly and safe development. Key issues include unauthorized building modifications, inadequate drainage systems, and poor sanitation, resulting in environmental damage and reduced quality of life. The study employs both qualitative and quantitative methods, including surveys and interviews, to gather data from 100 building samples and various stakeholders. Findings reveal significant non-compliance with land use regulations, building coefficients (KDB, KLB), and green space requirements (KDH), with 27% of buildings lacking necessary permits (IMB, PBG, SLF). Main causes include lack of awareness, high costs, and administrative hurdles. Recommendations for improvement include enhanced public education, streamlined administrative processes, stronger enforcement of regulations, and increased community involvement in planning. Effective inter-agency coordination is also crucial. These measures aim to foster a more organized, safe, and sustainable urban development in Banjarmasin. Enhanced compliance with PERDA will mitigate negative impacts such as flooding and environmental degradation, contributing to the overall welfare of the community.

Decision sciences (DSC) involve studying complex dynamic systems and processes to aid informed choices subject to constraints in uncertain conditions. It integrates multidisciplinary methods, techniques, and strategies to evaluate decision engineering processes, identifying alternatives and providing insights towards enhancing prudent decision-making. This study analyzes the evolutionary trends and innovation in DSC education and research to uncover the transformations over the years. We employ the science mapping method, text analytics, and metadata from bibliographic databases to evaluate thematic and social structures. The results highlight data science methods, including data mining and business/learning analytics as essential components. The evolutionary trends in DSC education and research mirror the development in practice, including technological transformation, computer science advances, and engineering processes. Sustainable education through virtual/online learning also constitutes a significant component of scientific production. The evolutionary trends in DSC education and research highlight innovative pedagogical approaches and strategies, including computer simulation and games ('play and learn'). The current era witnessed generative artificial intelligence (GenAI) adoption (e.g., ChatGPT) in teaching, learning, and scholarly activities amidst challenges (academic integrity, plagiarism, intellectual property violations, and other ethical and legal issues). Future research will implement and integrate AI automatic detection systems to address some GenAI adoption challenges.

Deep learning neural networks require an immense amount of computation, especially in the training phase of the network when networks with multiple layers of intermediate neurons need to be built. In this paper, we will focus on the PSO algorithm with the aim of significantly accelerating the DLNN training phase by taking advantage of the GPGPU architecture and the Apache Spark analytics engine for large-scale data processing tasks. PSO is a bio-inspired stochastic optimization method whose goal is to iteratively improve the solution to a (usually complex) problem by attempting to approximate a given objective. However, parallelizing an efficient PSO is not a straightforward process due to the complexity of the computations performed on the swarm of particles and the iterative execution of the algorithm until a solution close to the objective with minimal error is achieved. In the present work, two parallelizations of the PSO algorithm have been implemented , both designed for a distributed execution environment. The synchronous parallel PSO implementation ensures consistency at the cost of potential idle time due to global synchronization, while the asynchronous parallel PSO approach improves execution time by reducing the need for global synchronization, making it more suitable for large datasets and distributed environments such as Apache Spark. Both variants of PSO have been implemented to distribute the computational load supported by this algorithm –due to the costly fitness evaluation and updating of particle positions– across the different Spark cluster executor nodes to effectively achieve coarse-grained parallelism, resulting in a significant performance increase over current sequential variants of PSO.

: Based on fairness perspective, this paper combines the social vulnerability assessment of natural hazards with multi-objective site selection model to propose a new site selection planning model for central refuges. To begin with, the social vulnerability assessment system of regional natural disasters is founded through literature analysis, and the social vulnerability index of natural disasters is constructed; and based on the exponential differentiation of index to depict regional refuge demand, design vulnerability coverage function quantitive site selection fairness; then taking the shortest weighted evacuation distance, maximum vulnerability coverage and construction cost, the coverage population and refuge quantity as constraint conditions to construct multi-objective optimization model; finally, taking Zigong City, Sichuan Province as the object of empirical research, adapting NSGA-II algorithm to get the Pareto optimal solution set, and using TOPSIS method to get the optimal location scheme. The research results can provide a new method for the location layout of central refuge.

This study analyzed the risk of falls in the elderly and the safety of the environment in a teaching hospital in Brazil. The Morse Falls Scale was used to stratify the risk of falls in 45 hospitalized elderly individuals, and a checklist was used to analyze the hospital environment. The analysis was based on the chi-square test and multiple regression. The moderate risk of falls was predominant (51.1%). The variable age group (p-value = 0.024) showed statistical evidence of association with the risk of falls. However, the multiple regression analysis showed no difference between the age groups and the risk situation for falls. The hospital wards showed an adequate arrangement of furniture, but some aspects had inadequacies, such as objects in the corridors, non-functional bells in some beds, and inadequacy of the toilet bowls in terms of the recommended height, the absence of non-slip flooring and the support bar in some bathrooms. In conclusion, the moderate risk of falls among the elderly and the adequacy of the hospital environment to technical standards were evident, with the exception of failures in the emergency communication system and sanitary installation.

Viral infections leading to inflammation have been implicated in several common diseases such as Alzheimer’s disease (AD) and type 1 diabetes (T1D). Of note, herpes simplex virus 1 (HSV-1) has been reported to be associated with AD. We sought to identify the transcriptomic changes due to HSV-1 infection and anti-viral drug (acyclovir, ACV) treatment of HSV-1 infection in dissoci-ated cells from human cerebral organoids (dcOrgs) versus stem cell-derived pancreatic islets (sc-islets) to gain potential biological insights into the relevance of HSV-1-induced inflammation in AD and T1D. We observed that differentially expressed genes (DEGs) in HSV-1-infected sc-islets were enriched for genes associated with several autoimmune diseases, most significantly T1D but also rheumatoid arthritis, psoriasis, Crohn’s disease, and multiple sclerosis, whereas DEGs in HSV-1-infected dcOrgs were exclusively enriched for genes associated with AD. ACV treatment of sc-islets did not rescue transcript expression of autoimmune disease-associated genes. Finally, we identified gene ontology categories that were enriched for DEGs that were in common across, or unique to, viral treatment of dcOrgs and sc-islets, such as categories involved in the transferase complex, mitochondrial and autophagy function. Collectively, this studies pro-vide insight to the molecular effects of inflammation in AD and T1D.

The relationship of Amyotrophic Lateral Sclerosis, Parkinson Disease and other age-related neurodegenerative diseases associated with mitochondrial dysfunction has led to study of the mitochondrial fission gene Drp1 in Drosophila. Drp1 can interact with mitochondrial proteins including parkin and the Drosophila Bcl-2 proteins. Mutations in Drp1 can lead to mitochondrial dysfunction and neuronal loss. Ddc-Gal4 was exploited to direct the expression of Drp1 and the inhibition of Drp1 in neurons. Here, the inhibition of Drp1 seems to compromise locomotor function throughout life but does not alter longevity. The consequences of Drp1 overexpression can be suppressed through overexpression of pro-survival Bcl-2 gene Buffy or by inhibition of the pro-cell death Bcl-2 homologue Debcl. The expression of Buffy suppresses the poor climbing induced by loss of Drp1 function. Interestingly, the loss of parkin function is rescued by the directed inhibition of Drp1. Alteration of the expression of Drp1 acts to phenocopy neurodegenerative disease phenotypes in Drosophila, while overexpression of Buffy can counteract these phenotypes to improve overall health. The pro-survival effect of Buffy can rescue the phenotypic effect due to the Drp1-induced apoptosis. The diminished health due to either overexpression or inhibition of Drp1 has produced a novel model to investigate mechanisms underlying neurodegenerative disease.

Non-polio enteroviruses (NPEVs), namely coxsackieviruses (CV), echoviruses (E), enteroviruses (EV), and rhinoviruses (RV), are responsible for a wide variety of illnesses. Some infections can progress to life-threatening complications in children or immunocompromised patients. To date, no treatments have been approved. Several molecules have been evaluated through clinical trials without success. To overcome these failures, the multi-target directed ligand (MTDL) strategy can be applied to tackle enterovirus infections. This work analyzes clinical trials to highlight the best candidates and develops filters to apply to a selection for MTDL synthesis. We explicitly stated the methods used to answer the question: Which solution can fight NPEVs effectively? We note the originality and relevance of this proposal in relation to the state of the art in the enterovirus-inhibitors field. Several combinations are possible to broaden the antiviral spectrum and potency. We discuss data related to the virus and data related to each LEAD compound identified. Overall, this study proposes a perspective on different strategies to overcome issues identified in clinical trials and evaluate the “MTDL” potential to improve the efficiency of drugs synergistically, broaden the targeted, and reduce the adverse effects and drug design cost as well as limit the opportunity of drug-resistant viruses.

Black hole X-ray binary systems consist of a black hole accreting mass from its binary companion, forming an accretion disk. As a result, twin relativistic plasma ejections (jets) are launched towards opposite and perpendicular directions. Moreover, multiple broadband emission observations from X-ray binary systems range from radio to high-energy gamma-rays. The emission mechanisms exhibit thermal origins from the disk, stellar companion, and non-thermal jet-related components (i.e., synchrotron emission, inverse comptonization of less energetic photons, etc.). In many attempts at fitting the emitted spectra, a static black hole is often assumed regarding the accretion disk modeling, ignoring the Kerr metric properties that significantly impact the geometry around the usually rotating black hole. In this work, we study the possible implications of the spin inclusion in predictions of the X-ray binary spectrum. We mainly focus on the most significant aspect inserted by the Kerr geometry, the innermost stable circular orbit radius dictating the disk’s inner boundary. The outcome suggests a higher-peaked and hardened X-ray spectrum from the accretion disk and a substantial increase in the inverse compton component of disk-originated photons. Jet-photon absorption is also heavily affected at higher energy regimes dominated by hadron-induced emission mechanisms. Nevertheless, a complete investigation requires the full examination of the spin contribution and the resulting relativistic effects beyond the disk truncation.

Purpose: To analyze the clinical efficacy of superselective renal artery embolization and retroperitoneal laparoscopic partial nephrectomy for the treatment of ruptured hemorrhagic renal angiomyolipoma and to provide a reference for the selection of treatment methods for ruptured hemorrhagic renal angiomyolipoma. Methods: A retrospective analysis was conducted on the clinical data of 24 patients who were diagnosed with ruptured hemorrhagic renal angiomyolipoma at the Second Hospital of Tianjin Medical University between January 2019 and December 2021. Among them, 10 patients were treated with superselective arterial embolization (SAE), and 14 patients were treated with retroperitoneal laparoscopic part nephrectomy (RLPN). The differences between the two treatment methods in terms of hospital stay, hospital costs, anesthesia method, operation time, intraoperative blood loss, postoperative bed rest time, antibiotic dosage, postoperative complication rate, tumor diameter changes, creatinine value changes, hemoglobin value changes, tumor recurrence rate, and reoperation rate were compared. Results: All patients completed the treatment and were discharged. There were no significant differences in length of hospital stay, hospital costs, creatinine change values, or postoperative complication rates between the two groups (P > 0.05). However, there were statistically significant differences (P < 0.05) in surgical time (85.50±19.94 min vs. 141.07±76.33 min), intraoperative blood loss (21.50±14.72 ml vs. 153.57±97.00 ml), postoperative bed rest time (22.7±1.56 h vs. 41.21±3.57 h), preoperative hemoglobin levels (94.7 ±23.62 g/L vs. 113.79 ±17.83 g/L), and hemoglobin changes (-6.60 ±10.36 g/L vs. -15.21 ±8.79 g/L) between the two groups. Both groups of patients had an average follow-up period of 22 months, and patients in the SAE group had a mean reduction of 3.33 cm in tumor diameter within the follow-up period compared with the preembolization period (P < 0.05). None of the patients in the SAE group experienced rebleeding, and there was no tumor recurrence in either group. Conclusion: SAE and RLPN are effective treatments for ruptured renal angiomyolipoma with good outcomes. Furthermore, compared to RLPN, SAE offers advantages such as simplicity of operation, minimal trauma, shorter surgical time, minimal impact on hemoglobin levels, shorter bed rest time, faster postoperative recovery, and maximal preservation of renal units.

In this paper I show that, opposite to what is generally assumed, when a source accretes matter at the so-called Eddington mass accretion rate M˙ed, the generated accretion luminosity Lacc is smaller than Led, the Eddington accretion luminosity that can stop accretion. I demonstrate my thesis using pieces of informations that, one by one, are well known in the accretion theory but that, for some reason, they are not considered altogether. Namely, I use the following facts: i) Lacc, in the ideal case, is equal to the rate at which kinetic energy is deposited into the accreting source; ii) radiation pressure decreases the velocity of the infalling matter; iii) the generally accepted formula Lacc=GMM˙/R is valid only if the matter is in free fall. To give a quantitative demonstration of my thesis I use two accretion models: the first is the very simple spherical accretion of zero-temperature, fully ionized hydrogen; then I use a model developed some years ago where the energy transfer between matter and radiation is taken into account. The fact that M˙ed generates a Lacc&lt;Led can have consequences in all the cases in which one would need to model accretion with M˙&gt;M˙ed to reproduce the observations.

Excessive oxidative stress and exercise-induced fatigue reduce physical performance and can lead to dysfunction in antioxidant systems within muscular and hepatic tissues. Integrating natural substances with exercise may mitigate fatigue via anti-oxidant effects. This study aims to compare and evaluate the effects of exercise and supplementation with Sundarbans honey vs energy drinks on the strength, anxiety physiological profiles, and hepatic antioxidant capacity in mice undergoing extraneous exercise and fatigue. Forty-eight four-week-old Swiss albino mice were randomly assigned to one of eight groups: (1) Control, (2) Speed™ (Sp), (3) Royal Tiger™ (RT), (4) Sundarbans Honey (SH), (5) Exercise (Ex), (6) Exercise + Sundarbans Honey (Ex+SH), (7) Exercise + Speed™ (Ex+Sp), and (8) Exercise + Royal Tiger™ (Ex+RT). Supplements were administered via oral gavage: Sp (2.5 ml/kg BW), RT (2.5 ml/kg BW), and SH (1 g/kg BW), four times a week for 60 days. Mice in the Ex, Ex+SH, Ex+Sp, and Ex+RT groups underwent daily swimming and running. The strength, fatigue, anxiety levels, lipid profiles, and antioxidant biomarkers were evaluated post-treatment. The SH, Ex, and Ex+SH groups exhibited significantly enhanced physical performance (p

The scientific fields of complexity, artificial life (ALife), and artificial intelligence (A.I.) share commonalities: historic, conceptual, methodological, and philosophical. Although their origins trace back to the 1940s birth of cybernetics, they were only able to properly develop as modern information technology became available. In this perspective, I offer a personal (and thus biased) account of the expectations and limitations of these fields, some of which have their roots in the limits of formal systems. I will use interactions, self-organization, emergence, and balance to compare different aspects of complexity, ALife, and A.I. Even when the trajectory of the paper is influenced by my personal experience, the general questions posed (which outweigh the answers) hopefully will be useful to align efforts in these fields toward overcoming --- or accepting --- their limits.

This article serves as a extensive research into proposing a few significant inequalities involving polynomial functions in $\pi(x)$, the \textit{prime counting function}, with an intention of exploring the behaviour of $\pi(x)$ for increasing $x$. The general case for such polynomials has also been discussed in detail towards the later section of the article, where the primary focus was to study the order of polynomials of the form, \begin{align*} P(\pi(x)) - \frac{e x}{\log x} Q(\pi(x/e)) + R(x) \end{align*} $P$, $Q$ and $R$ being arbitrary polynomials, and establish for a particular case that, the polynomial yields negative values for sufficiently large values of $x$. Furthermore, the error term in such estimations is of order $O\left(\frac{x^d}{(\log x)^{d+1}}\right)$, $d$ depends heavily upon $deg(P)$ and $deg(Q)$.

The study delves into the Zaalklapspruit valley-bottom wetland in South Africa, a site designed through ecological engineering and currently impacted by acid mine drainage due to an upstream defunct coal mine. The research conducted in 2022, aimed to uncover the dynamics of contaminant dispersal within such a wetland setting, focusing on the origins, routes, and ultimate recipients of various metals and sulfur compounds. Analysis revealed that the bottom sediment is rich in organic material, with pH levels observed between 6.05 and 6.59, and exhibited notably low oxidation-reduction potentials, reaching down to −219.67 mV at sample point S3. Notably, Manganese displayed the highest adsorption rates, whereas Iron was predominantly absorbed by the roots of Typha capensis and the algae Klebsormidium acidophilum. The wetland's macrophyte rhizospheres hosted a rich array of microbiota, including families like Helicobacteraceae and Hydrogenophilaceae, which are crucial in metal and sulfur processing. This investigation sheds light on the intricate biogeochemical processes taking place involving the wetland's sediment, macrophyte root systems, periphyton, and microbial populations, underscoring the potential of ecologically engineered wetlands in the remediation of waters affected by acid mine drainage.

Fungi are rich sources of secondary metabolites of agrochemical, pharmaceutical and food importances, such as mycotoxins, antibiotics and antitumor agents. Secondary metabolites play vital roles in fungal pathogenesis, growth and development, oxidative status modulation, and adaptation/resistance to various environmental stresses. LaeA contains an S-adenosylmethionine binding site and displays methyltransferase activity. The members of velvet proteins include VeA, VelB, VelC, VelD and VosA, for each member with a velvet domain. LaeA and velvet proteins can form multimeric complexes such as VosA-VelB and VelB-VeA-LaeA. They belong to global regulators and are mainly impacted by light. One of their most important functions is to regulate gene expression that are responsible for secondary metabolite biosynthesis. The aim of this mini-review is to represent the newest cognition on the biosynthetic regulation of mycotoxins and other fungal secondary metabolites by LaeA and velvet proteins. In most cases, LaeA and velvet proteins positively regulated production of fungal secondary metabolites. The regulated fungal species mainly belong to the toxigenic fungi from the genera of Alternaria, Aspergillus, Botrytis, Fusarium, Magnaporthe, Monascus, and Penicillium for the production of mycotoxins. We can control secondary metabolite production to inhibit the production of harmful mycotoxins while promoting the production of useful metabolites by global regulation of LaeA and velvet proteins in fungi. Furthermore, the regulation by LaeA and velvet proteins should be a practical strategy in activating silent biosynthetic gene clusters (BGCs) in fungi to obtain previously undiscovered metabolites.

:. Background and Objectives: Pulmonary embolism, PE, incidence had been increasing in the last ten years. Computed thoracic pulmonary angiography, CTPA, had a major role in confirming PE di-agnosis.The main purpose of the study was to establish the prognostic value of a CTPA parameter: pulmonary artery obstruction index, PAOI, for PE risk assessment . A second objective of the re-search was to investigate the predictive accuracy of biomarkers (D-dimer, and cardiac Troponin T, c-TnT ), and PAOI, in 7-day mortality. The third objective of the study was the relationship between PAOI, and these biomarkers, in different etiologies of PE. Materials and Methods: The study com-prised 109 patients with PE, hospitalized, and treated between February 2021, and August 2022. They had different etiologies: deep vein thrombosis, DVT; persistent atrial fibrillation, AF; chronic obstructive pulmonary disease, COPD, exacerbation; Covid; and cancers. The investigations were the following: clinical examination; D-dimer testing, as a mandatory method for PE suspicion( values ≥ 500 µg/L were highly suggestive for PE); c-TnT , as a marker of myocardial injury(values ≥ 14 ng/L were abnormal); CTPA, with right ventricle dysfunction, RVD, signs, and PAOI. Treat-ments were according to PE risk: systemic thrombolysis (in high risk , and hemodynamic instability); low weight molecular heparins, LWMH, after systemic thrombolysis, or in high risk PE, with he-modynamic stability; direct oral anticoagulants, DOAC (in low, and intermediate risk). Results: The relationship PAOI- D-dimer, and PAOI- c-TnT, had very strong statistical correlation, for the entire sample, and for DVT, AF, COPD, Covid subgroups ( Rho = 0.815-0.982). PAOI had a high predic-tive accuracy for intermediate , and high risk together (area under curve, AUC=0.948), and high risk PE (AUC= 0.993). For 7-day mortality, D-dimer , and c-TnT had high predictive accura-cy(AUC=0.921, and 0.979). PAOI had statistical significance for 7-day mortality in Covid (p=0.045), and cancer (p=0.038) patients. Conclusions: PAOI was an important tool for PE risk as-sessment. D-dimer , and c-TnT were valuable predictors, for 7-day mortality in PE. PAOI, and D-dimer; PAOI, and c-TnT were strongly correlated, for the entire PE sample, and for DVT, AF, COPD, and Covid patients.

The aim of this study was to analyze the relationship between healthy vascular aging (HVA) and the Mediterranean diet alongside other lifestyles in a Spanish population aged 35 to 75 years without previous cardiovascular diseases. Methods: Cross-sectional descriptive study with 501 individuals aged 35 to 75 years recruited from five health centers by random sampling stratified by age and sex (55.90±14.24 years, 49.70% men). HVA was determined in two steps. Step 1: Subjects with vascular damage to the carotid arteries or peripheral arterial disease were classified as non-HVA. Step 2: The study population was classified by age and sex using the percentiles of the vascular aging index (VAI), with VAI ≤p25 considered HVA and >p25 considered non-HVA. The VAI was estimated using the following formula (VAI = (log (1.09) × 10 cIMT + log (1.14) cfPWV) × 39.1 + 4.76. Carotid-femoral pulse wave velocity (cfPWV) was measured with the SphygmoCor® device and carotid intima-media thickness using Sonosite Micromax® ultrasound. Mediterranean diet (MD) adherence, alcohol and tobacco use were recorded through validated questionnaires. Physical activity was assessed with the ActiGraph-GT3X® accelerometer. Results: The mean VAI value was 61.23±12.86; (Men 63.47±13.75 and women 59.04±11.54; p

This research has developed a process for producing ZnO thin film from DEZn deposited onto a PET substrate with low-pressure, high-frequency Ar + O2 plasma using a chemical vapor deposition technique. The aim is to study the film production conditions that affect electrical properties, optical properties, and thin film surfaces. This work highlights the use of plasma energy produced from a mixture of gases between Ar + O2. Plasma production is stimulated with an RF power supply to deliver high chemical energy and push ZnO atoms from the cathode inside the reactor onto the substrate through surface chemical reactions. The results showed that increasing the RF power in plasma production affected the chemical reactions on the substrate surface of film formation. The film preparation at RF power 300 W will give the thickest films. The film has a continuous columnar formation, and the surface has a granular structure. This results in the lowest electrical resistivity of 1.8 x 10-4 Ω-cm. In addition, when fabricated into a DSSC device, the device tested the PCE value and showed the highest value at 5.68%. This is due to the very rough surface nature of the ZnO film, which increases the scattering and storage of sunlight, making cells more efficient. Therefore, the benefit of this research is that it will be a highly efficient prototype of thin film production technology using a chemical process that reduces production costs and can be used in the industrial development of solar cells.

This paper explores the increasing use of big data in education to create personalized learning experiences tailored to individual student needs. The trend, driven by vast amounts of educational data, requires the development of new techniques to optimize learning outcomes while addressing the ethical implications of data collection and utilization. The paper emphasizes the necessity for robust policy frameworks to ensure transparency and trust, based on clear guidelines and parental consent. It also discusses how educational institutions are updating curricula to prepare learners for a rapidly evolving workforce, incorporating contemporary AI technologies that impact education systems. The dual influence of AI presents both opportunities and challenges, necessitating a balanced and thoughtful approach. The paper advocates for a holistic strategy in integrating AI in education, emphasizing the importance of collaboration between the AI industry and other sectors to develop comprehensive policy frameworks for the ethical and effective use of AI in education.

Wear phenomena on natural stone of the cultural heritage are induced from various sources. Consequently, the development of multifunctional protective materials which combine two or more useful properties is an effective strategy to address the synergistic effects of various wear mechanisms. A multifunctional coating, consisting of a silane-based precursor and zinc oxide (ZnO) nanoparticles (NPs), is produced and tested for the protection of limestone. The hybrid coating combines the following three properties: superhydrophobicity, including water-repellency, photocatalytic self-cleaning and biocidal activity. The relative concentration of the NPs (0.8% w/w), used for the suggested composite coating, is carefully selected according to wetting studies, colourimetric measurements and durability (tape peeling) tests. The non-wetting state is evidenced on the surface of the composite coating by the large contact angle of water drops (≈153°) and the small contact angle hysteresis (≈5°) which gives rise to the physical self-cleaning scenario (lotus effect). The photocatalytic chemical self-cleaning is shown with the removal of methylene blue, induced by the UV-A radiation. Moreover, it is shown that the suggested coating hinders the incubation of E. coli and S. aureus as the inhibition were 94.8 and 99.9 %, respectively. Finally, preliminary studies revealed the chemical stability of the suggested coating.

Time can be a difficult concept to understand. Albert Einstein, who viewed time as an illusion, explained the passage of time is relative to the observer’s frame of reference in the space-time continuum. However, the state of consciousness of the observer also influences the passage of time. This paper examines the relationship between the experience of time and different states of consciousness including near-death experiences, mystical states of consciousness, and psychedelic medicine-induced states of consciousness. Two different experiences of time are described. These are Chronos and Kairos. Chronos is described as 4th dimensional time whereas Kairos is 5th dimension time. Methods for facilitating the experience of Kairos are discussed and the potential benefits of experiencing Kairos are reviewed.

Differences between the quantum mechanical and relativistic concepts of time observed in GPS satellites are accounted for by applying the equivalence principle to the transitioning electron of an atomic clock. This allows a differential equation of motion to be derived for the electron in the Minkowski space between electron shells. By applying Hamilton’s principle we transform the differential equation into a relativistically correct integral equation of motion, the time integral of a Lagrangian. This newly derived equation accounts for the abstract mathematics of the more familiar non-relativistic model by means of a physical interpretation. Abstract rotations in Hilbert space are replaced by real rotations of particle field geometries in Minkowki space that describe the electron transition and emission of a photon. Because the properties of energy are universal the same integral equations are able to be used to describe the time evolution of galaxies despite vast differences in lifetime. The comparison of gravitational and electromagnetic energy exchanges by means of radial and transverse fields leads to an alternative to the standard model that is based on a field model. It explains the observed properties of galaxies as a superposition of neutrinos localized within the horizon of a black hole with spins aligned. The particle properties of free neutrinos are accounted by means of a classical field geometry; specifically, a spin that is oriented in space with rotational inertia due to energy. A test of the standard model is proposed based on differing views for flavor oscillation.

Deploying search and rescue (SAR) dogs in disaster situations is crucial for effective rescue missions. This study delves into the challenges and obstacles encountered during the use of SAR dogs, particularly focusing on the earthquake that hit Turkey in February 2023. By employing a case study approach, the research explores various factors that impact the efficiency and safety of SAR dog operations, such as environmental conditions, equipment needs, cultural perceptions, and logistical hurdles. Environmental conditions such as extreme weather, hazardous materials, and unstable structures present significant risks to both the dogs and their handlers. The adequacy of equipment, including protective gear and medical supplies, is critical for ensuring the safety and efficiency of rescue operations. Logistical challenges, including the transportation and care of dogs in disaster zones, further complicate their deployment. Cultural barriers also play a crucial role, as perceptions of dogs vary widely across different communities, potentially affecting the acceptance and integration of canine units in rescue efforts. The case study of the earthquake in Turkey highlights these issues, showcasing the successes and setbacks experienced by international rescue teams. The findings indicate that although SAR dogs are invaluable in locating survivors, they face significant dangers, including hazardous materials, extreme weather, and physical injuries. Additionally, cultural differences and logistical issues complicate their deployment. This paper highlights the necessity for improved training, protective measures, and international standards to ensure SAR dogs' well-being and effectiveness in disaster response efforts. The study's implications suggest that addressing these challenges can markedly enhance the preparedness and resilience of SAR teams, leading to more efficient and safer rescue operations in future disaster scenarios.

In this paper, we investigate the proftability of investing in movies for retail investors, focusing on the return on investment (ROI) metric, which is calculated as revenue divided by budget. Our analysis encompasses 5000 movies from the movie database TMDB, examining factors such as production scale, genres, key actors, directors, and more. Additionally, we employ textual analysis techniques like Latent Semantic Analysis (LSA) on movie overviews and tags to incorporate movie themes. We then evaluate various supervised classifcation models including Logistic Regression, Random Forest, and Light Gradient Boosting (LightGBM), comparing their performance. Our fndings highlight the signifcance of production scale, team structure, and movie themes in identifying potential high-return opportunities for investors.

Abstract: Cancer, notably breast cancer, is a significant health concern globally, with a substantial burden in Asia, particularly in Pakistan. Late diagnosis exacerbates mortality rates, emphasizing the importance of robust screening programs. This article examines the effectiveness of breast cancer screening initiatives and intervention four years after initial pilot study that spanned 2015-2019, using data from the Islamabad Federal Breast Screening Centre, to assess readiness for national guideline implementation in Pakistan and beyond. Methods: This retrospective cross-sectional study, conducted at the Federal Breast Screening Center (FBSC), involved 5,580 patients undergoing mammography screening over an four-year period from 2015 to 2023. The study examined patients' data, including Breast Imaging Reporting and Data System (BIRADS) categories through double reading mammography and complementary ultrasound (USG) findings. Demographic information, including age, ethnicity, education status, socio-economic factors, breastfeeding history, breast density, and family history, was recorded to analyze its correlation with breast cancer diagnosis and subsequent management. Data analysis was performed using SPSS 2021. Results: The study included a total of 4337 patients who visited the Federal Breast Screening Centre from 2020 to 2023. The mean age of patients attending screenings from 2020 to 2023 was 48.50 ± 9.55 years, with the most common age group being 41-45 years 1,364 (24.4%), followed by 46-50 years 1,008 (18.1%). The ethnicity with the highest frequency was Punjabi 4,647 (83.3%). The distribution of patients across BI-RADS categories was as follows: BI-RADS 0 (n=175, 3.10%), BI-RADS I (n=1,933, 34.60%), BI-RADS II (n=1,691, 30.30%), BI-RADS III (n=642, 11.50%), BI-RADS IV (n=612, 11.00%), BI-RADS V (n=389, 7.00%), and BI-RADS VI (n=138, 2.50%). The prevalence rate of invasive breast cancer during these four years was 10.4%. Conclusion:In conclusion, breast cancer poses an escalating challenge associated with increasing mortality rates. Pakistan, alongside its South Asian counterparts, is witnessing a surge in cases, emphasizing the urgency for comprehensive interventions. Research endeavors such as this provide valuable insights into demographic profiles, aiding in the formulation of tailored guidelines. Moreover, the establishment of additional federal centers for screening is imperative to enhance patient access and mitigate the issue of delayed diagnoses, aligning Pakistan's healthcare infrastructure with that of developed nations.

We develop an action principle for producing a single fluid, two-constituent system with dissipation in general relativity. The two constituents in the model are particles and entropy. The particle flux creation rate is taken to be zero, while the entropy creation rate is non-zero. Building on previous work, it is demonstrated that a new term (the proper time derivative of the matter space ``metric'') is required in the Lagrangian in order to produce terms typically associated with bulk and shear viscosity. Equations of motion, entropy creation rate, and energy-momentum-stress tensor are derived. Using an Onsager approach of identifying thermodynamic ``forces'' and ``fluxes'' a model is produced which delivers the same entropy creation rate as the standard, relativistic Navier-Stokes equations. This result is then contrasted with a model generated in the spirit of the action principle, which takes as its starting point a specific Lagrangian and then produces the equations of motion, entropy creation rate, and energy-momentum-stress tensor. Unlike the equations derived from Onsager reasoning, where the analogs of the bulk and shear viscosity coefficients are prescribed ``externally'', we find that the form of the coefficients in the second example are a direct result of the specified Lagrangian. Furthermore, the coefficients are shown to satisfy evolution equations along the fluid worldline; also a product of the specific Lagrangian.

Artificial intelligence (AI) driven language models have seen a rapid rise in development, deployment, and adoption over the last few years. This surge has sparked many discussions about their societal and political impact, including political bias. Bias is a crucial topic in the context of large models due to its far-reaching consequences on technology, politics, and society. It significantly influences public perception, decision-making, political discourse, and AI policy governance and ethics. This study investigates political bias through a comparative analysis of four prominent AI models: ChatGPT-4, Perplexity, Google Gemini, and Claude.Through a comprehensive analysis by systematically and categorically evaluating their responses to politically and ideologically charged tests and prompts, utilizing the Pew Research Center’s Political Typology Quiz, the Political Compass assessment, and ISideWith political party quiz, this study identifies significant ideological leanings and the nature of political bias within these models. The findings revealed that ChatGPT-4 and Claude exhibit a liberal bias, Perplexity is more conservative, while Google Gemini adopts more centrist stances. The presence of such biases underscores the critical need for transparency in AI development and the incorporation of diverse training datasets, regular audits, and user education to mitigate these biases. This analysis also advocates for more robust practices and comprehensive frameworks to assess and reduce political bias in AI, ensuring these technologies contribute positively to society and support informed, balanced, and inclusive public discourse, which will point towards neutrality.The results of this study add to the ongoing discourse about the ethical implications and development of AI models, highlighting the critical need to build trust and integrity in AI models. Additionally, future research directions have been outlined to explore and address the complex issue of bias in AI.

Recent studies have suggested significant antimicrobial properties of some metallic nanoparticles during the height of antibiotic resistance. The silver nanoparticle (AgNPs) is one of the most prominent candidates due to its noble nature and better tolerance profile in humans. The synthesis of AgNPs was carried out using silver nitrate using five different chemical reduction methods and comparing their activity with silver nitrate, also known to possess antimicrobial properties. AgNPs have been synthesized with varying combination of reducing agents, and subsequently characterized by UV-visible spectroscopy, thermogravimetric analysis (TGA), scanning electron microscopy (SEM), and dynamic light scattering (DLS). Chemical reduction with both trisodium citrate and sodium borohydride provided better particle size and controlled uniformity, whereas hydrogen peroxide was used as a stabilizer to increase the stability of AgNPs. The minimum bactericidal concentration (MBC) for all AgNP formulations was determined against gram-negative E. coli, and AgNPs synthesized with only trisodium citrate were found to be the most effective. The synthesized AgNPs were tested against the resistant strains of E. coli, Salmonella, Klebsiella, Bacillus, and Staphylococcus by the well diffusion method to evaluate and compare their inhibition zones and AgNPs synthesized with polyethylene glycol and polyvinyl pyrrolidine were found to be the most efficient.

This paper presents a novel approach to designing beam codebooks for downlink multiuser hybrid multiple input multiple output (MIMO) wireless communication systems, leveraging multi-agent reinforcement learning (MARL). The primary objective is to develop an environment-specific beam codebook composed of non-interfering beams, learned by cooperative agents within the MARL framework. Machine learning (ML) based beam codebook design for downlink communications have been based on channel state information (CSI) feedback or only reference signal received power (RSRP) consisting of an offline training and user clustering phase. In massive MIMO, the full CSI feedback data is of large size and is resource-intensive to process, making it challenging to implement efficiently. RSRP alone for a stand-alone base station is not a good marker of the position of a receiver. Hence, in this work, uplink CSI estimated at the base station along with feedback of RSRP and binary acknowledgment of the accuracy of received data is utilized to design the beamforming codebook at the base station. Simulations using sub-array antenna and ray-tracing channel demonstrate the proposed system’s ability to learn topography-aware beam codebook for arbitrary beams serving multiple user groups simultaneously. The proposed method extends beyond mono-lobe and fixed beam architectures by dynamically adapting arbitrary shaped beams to avoid inter-beam interference, enhancing overall system performance. This work leverages MARL’s potential in creating efficient beam codebooks for hybrid MIMO systems, paving the way for enhanced multiuser communication in future wireless networks.

To determine the influence of child abuse on academic performance from the perspective of teachers of a private school from Piura, 2024. Method: The present study is an applied, non-experimental design with a continuous qualitative approach. The technique used was the survey and as an instrument the questionnaire on knowledge of child abuse with 12 questions, with a population of 20 teachers. Results: For the statistical analysis was used through Microsoft Excel 2023 and IBM SPSS software, in addition the Shapiro Wilks statistical test was used, the results show that 85% of respondents, from their perspective, neglect has a high level of influence on academic performance, 65% of respondents, from their perspective, state that psychological maltreatment has a high level of influence on academic performance and 50% of respondents, from their perspective, determine that physical maltreatment has a high level on academic performance. Conclusions: The value of p=0.553 &gt; 0.05, therefore, it is concluded that according to the perspective of the teachers of a private school from Piura, there are no significant changes in the academic performance of students who suffer from child maltreatment.

Coffee is one of the most valuable agricultural products worldwide, and it is crucial to have efficient tools to obtain reliable information about production. This study aims to estimate coffee plantation production using segmentation and deep learning techniques in RGB images. Photographs of coffee plants were taken in Tabaconas, San Ignacio-Cajamarca, to create a dataset of crops during the harvest stage. The images were segmented to detect coffee fruits. A deep learning method was developed with YOLOv5 to detect the fruits and OpenCV to count them. The results showed that YOLOv5 achieved an accuracy of 97.25%, a recall of 95.77%, and an F1-Score of 96.37%, demonstrating high reliability in detecting coffee fruits. The average detection time per image was 17.9 seconds. The metrics were evaluated using a confusion matrix, highlighting the model's good performance. In conclusion, segmentation and deep learning techniques, along with counting algorithms developed with OpenCV, proved effective for estimating coffee production. This approach provides a valuable tool for farmers, improving crop management and facilitating decision-making in precision agriculture.

In this study, we explored the application of deep learning techniques for credit card fraud detection, aiming to improve the performance and reliability of anomaly detection methods in financial transactions. We first utilized the Isolation Forest algorithm, achieving a detection accuracy of 26% for the top 1000 transactions. Subsequently, we experimented with the Autoencoder algorithm, an unsupervised deep neural network model, which enhanced the detection accuracy to 33.6% in the best case despite some fluctuations. The results demonstrate deep learning models' strong feature extraction capability and adaptability, highlighting their potential to surpass traditional methods. However, the high imbalance in the dataset, with only 0.17% of transactions being fraudulent, poses a significant challenge. This study underscores the necessity for further experimentation and optimization of network structures and hyperparameters to achieve more stable and efficient fraud detection. The findings provide valuable insights and reference points for future research in financial fraud detection using deep learning methodologies.

This study explores the effects of tempering on the precipitation behavior and impact toughness of high-nickel steel. The specimens underwent double quenching at 870°C and 770°C, followed by tempering at various temperatures. Advanced characterization techniques including optical microscopy (OM), scanning electron microscopy (SEM), and transmission electron microscopy (TEM) were used to elucidate precipitation phenomena. Additionally, electron backscatter diffraction (EBSD) was employed to assess the misorientation distribution after tempering. Charpy impact tests were performed on specimens tempered at different temperatures to evaluate their toughness. The findings reveal that with increasing tempering temperature, the fraction of low-angle grain boundaries decreases, which correlates positively with enhanced impact toughness. The impact toughness peaks at 580°C and then diminishes with further temperature increases.

The emergence of drug resistance inducing mutations in Hepatitis C virus (HCV) coupled with genotypic heterogeneity has made targeting NS3/4A serine protease difficult. In this work, we investigated the mutagenic variations in the binding pocket of Genotype 3 (G3) HCV NS3/4A and evaluated ligands for efficacious inhibition. We report mutations at 14 positions within the ligand-binding residues of HCV NS3/4A including H57R and S139P within the catalytic triad. We then modeled each mutational variant for pharmacophore-based virtual screening (PBVS) followed by covalent docking towards identifying a potential covalent inhibitor, i.e. cpd-217. The binding stability of cpd-217 was then supported by molecular dynamic simulation followed by MM/GBSA binding free energy calculation. The free energy decomposition analysis indicated that the resistant mutants alter the HCV NS3/4A-ligand interaction, resulting in an unbalanced energy distribution within the binding site leading to drug resistance. cpd-217 was identified to interact with all NS3/4A G3 variants with significant covalent docking scores. In conclusion, cpd-217 emerges as a potential inhibitor of HCV NS3/4A G3 variants that warrants further in vitro and in vivo studies. The study will pave the way for drug design and development of HCV G3 NS3/4A.

The purpose of this study is to identify, and examine the potential characteristics of Siompu Tangerines to be given legal protection for Geographical Indications and examine the efforts of local governments in encouraging legal protection of Siompu Tangerines Geographical Indications, this research uses a type of empirical legal research. The conclusion of this study explains that characteristics of Siompu Tangerines have the potential to be given legal protection for Geographical Indications because they have a distinctive sweet, slightly sour taste and strong aroma with a sugar content scale of 9-10º Brix, the orange has been named the sweetest orange in the National Citrus fruit contest and several times served at official ceremonies at the State palace, the reputation of Siompu Tangerines makes it a National Flagship Orange through the Decree of the Minister of Agriculture number 742 / Kpts / TP. 240/7/1997. Geographical environmental factors from natural conditions and human factors make Siompu Tangerines can only grow well in the Siompu island area. The Regional Government of South Buton Regency has made efforts in terms of the development of Siompu Tangerines but has not been optimal in carrying out legal protection of Geographical Indications, due to a lack of community understanding, and the Regional Government regarding the potential of Siompu Tangerines which can be given protection by registering as a Geographical Indication product, the importance of obtaining legal certainty and obtaining exclusive rights is very useful in improving the community's economy and Farmer Tangerines Siompu.

This study investigates the critical factors of trust, commitment, and adaptation within supplier relationship management (SRM) in the context of e-commerce. Through qualitative research methods, including semi-structured interviews and documentary analysis, the study explores how these factors influence relationship dynamics and organizational outcomes in digital business environments. Trust is examined as foundational to effective SRM, encompassing integrity, reliability, and shared values between buyers and suppliers. Commitment is analyzed in terms of long-term orientation, resource allocation, and relationship-specific investments aimed at mutual growth and sustainability. Adaptation emerges as essential for navigating the dynamic e-commerce landscape, encompassing proactive strategies, flexibility, and innovation to respond to market changes and technological advancements. The findings highlight the interplay and mutual reinforcement among trust, commitment, and adaptation, contributing synergistically to relationship resilience and organizational performance. However, challenges such as information asymmetry, cybersecurity risks, and organizational inertia are identified as barriers to effective SRM. Practical implications include strategies for enhancing trust, fostering commitment, and cultivating adaptive capabilities through continuous learning, collaborative innovation, and technology integration. By integrating these insights, businesses can strengthen supplier relationships, drive sustainable growth, and achieve competitive advantage in the digital economy.

In solid cancer surgery, oxidative stress (OS) is of particular interest because both the malignancy itself and the surgical intervention are major contributors to the modulation of OS levels. This study aimed to investigate the effects of solid cancer surgery on OS levels. Because solid cancer is often accompanied by intense cell death, the study specifically focused on the pathway leading to uric acid formation, (i.e. adenosine deaminase (ADA) and xanthine oxidase (XO). Ische-mia-modified albumin (IMA), a recognized marker of oxidative stress, and plasma redox poten-tial (RP) were also measured. Thirty-six patients undergoing major solid cancer surgery (median age 68 years (58-76), 23 men and 13 women) and thirty controls (62 years (51-80)) were included. During the surgical procedure, serum ADA levels did not change significantly (10.4 International Units (IU) (6.9 – 13.7) vs. 8 IU (6 – 12); p = 0.47). In contrast, XO (IU), IMA (Arbitrary Units(AU)) and redox potential (mV) decreased significantly (22.5 IU (11 – 63) vs. 8.4 IU (5 – 27); p = 0.0041, 89 AU (69 – 105) vs. 74 AU (66 – 80); p = 0.01 and 98 mV (78 – 118) vs. 79 mV (65 – 101); p = 0.033). The correlation between XO and IMA or redox potential was positive (Spearman’s r = 0.32 ; p = 0.007, and r = 0.58; p < 0.001, respectively). XO was negatively correlated with ADA (r = -0.26; p = 0.03). Redox potential was positively correlated with IMA (r = 0.26; p = 0.04) and nega-tively correlated with ADA (r = -0.25 ;p = 0.04). We found that a major source of OS in solid cancer could be the result of an increase in xanthine oxidase activity and that the global effect of solid cancer surgery is a significant decrease in OS levels. We also found that ADA and XO were inversely correlate, suggesting the existence of a negative retrocontrol between the production of free radicals and the production of their sub-strate. Finally, our study highlights the potential value of XO inhibitors as adjuvant therapy in solid tumor surgery.

The lack of quality formulated feeds as supplements or replacements for live feeds has negatively impacted the growth performance and survival rates in the larvae of many fish species, notably African catfish (C. gariepinus). Successful larval rearing relies on the availability of suitable diets that are readily consumed, easily digested, and provide the essential nutrients necessary for optimal growth and health of the fish. This study evaluated the growth performance and survival rates of C. gariepinus larvae when fed locally formulated diets. The experiment was conducted using 12 basins, each with a capacity of 20 liters. Each basin was stocked with 60 larvae in four replicates, averaging 0.03 g in weight. The experimental diets were formulated to contain three different levels of crude protein: 40%, 45%, and 50%. The larvae were fed these diets at a rate of 10-20% of their body weight over 70 days. Initially, the larvae were fed artemia at the onset of feeding in hatchling basins immediately after yolk sac absorption for the first seven days. This was followed by a blend of artemia and formulated feeds for 14 days. After 28 days, the larvae were transitioned to be exclusively fed the formulated dry feeds. The results indicated that the larvae fed on diets containing 45% and 50% crude protein exhibited significantly better overall growth performance compared to those fed on a 40% crude protein diet. Specifically, the larvae that received the 45% and 50% crude protein diets showed higher final mean weight, increased daily weight gain, and improved survival rates, which ranged from 80% to 81.5%. Notably, there was no significant difference in growth performance and survival rates between the larvae fed on 45% and 50% crude protein diets, suggesting that a 45% crude protein-formulated diet is sufficient to achieve the best growth performance and survival rates for C. gariepinus larvae. This study supports the recommendation of feeding C. gariepinus larvae with a dry diet containing 45% crude protein starting from 14 days post-hatching to enhance their growth and survival rates. However, further research is recommended to explore the effects of this feeding regimen across different agroecological zones and aquaculture systems to validate and potentially refine these findings.

Through analysis of the constituent components of the observation data from 12 geoe-lectric field stations located approximately 600 km form the epicenter of the Jishishan Ms6.2 earthquake, this study reveals that during earthquake preparation and occurrence, the geoelec-tric field at each station exhibit non-uniform variations. These variations are characterized by significant decreases or increases in correlation coefficients between different azimuths (δxy) and between long and short polar distances within the same azimuth (δxx). Additionally, there are discrete or extruding changes observed in the dominant azimuth angles of the telluric field at the stations, ranging approximately from 40° to 90°. These anomalies indicate local site effects and exhibit quasi-synchronous temporal characteristics. The study found that stations located in regions with intense tectonic activities, such as Menyuan and Jingtai, experience more significant anomalous changes influenced by the tectonic activities of the Qaidam-Qilian Mountain block. When multiple stations with anomalous changes are used to determine the earthquake epicenter, earthquakes often occur within or near the intersection area of the predicted ranges of these sta-tions. The specific time of earthquake occurrence shows no clear relationship with the locations or tectonic activities of the stations.

The digital world is increasingly invading our reality, which leads to the formation of a significant reflection of the processes and activities taking place in the smart city. Such activities include well-known urban events, celebrations, and those with a very local character. Due to the mass occurrence, events have a comparable influence on the formation of the spirit and the urban atmosphere. This work presents an enhanced semantic version of the ConvTree algorithm - SemConvTree. It allows considering the semantic component of the data obtained by using semi-supervised learning of topic modeling ensemble (consisting of improved models BERTopic, TSB-ARTM, SBert-Zero-Shot). We also present an improved event search algorithm based on both statistical evaluations and semantic analysis of posts. This algorithm allows fine-tuning the mechanism of discovering the required entities with the specified particularity (such as a particular topic). Experimental studies were conducted within the area of New York City. They showed an improvement in the detection of posts devoted to events (about 40% higher f1-score) due to the accurate handling of events of different scales. These results lead in the long term to talk about the potential perspective in creating a semantic platform for the analysis and monitoring of urban events in the future.

The BL Lacertae (BL Lac) object OJ 287 underwent an intense X-ray activity phase, exhibiting its brightest recorded X-ray flare in 2016-2017, characterized by much softer X-ray spectra and, concurrently, its first-ever recorded very-high-energy (VHE) emission (100--560 GeV), reported by the VERITAS observatory. Broadband spectral energy distribution reveals a new jet emission component similar to high-synchrotron-peaked BL Lac objects, thereby implying the soft X-ray spectrum for the synchrotron emission. Using the advantage of simultaneous X-ray and VHE spectral information, as well as the source being a low-synchrotron-peaked BL Lac object, we systematically explored the extragalactic background light (EBL) spectrum by demanding that the VHE spectrum cannot be harder than the X-ray spectrum. We used three different phenomenological forms of the EBL spectral shape (power-law, parabola, and polynomial) motivated by current constraints on the EBL with the Bayesian Monte Carlo approach to infer the credible EBL range. Our study favors an almost flat power-law spectral shape and is consistent with previous studies. The other spectral forms capable of capturing curvature though result in a better statistics value; the improvement is statistically insignificant given the additional parameters.

The growing interest in environmental sustainability issues and, at the same time, the advantages offered by blockchain technology have strong connections between these two topics. This study explores the application of blockchain technology across various environmental domains, such as air quality, climate change impacts, and resource management. The research utilised a dual approach, combining a bibliometric analysis with VOSviewer and a topic analysis using BERT models to assess the discourse within both scientific literature extracted from Scopus and practical blockchain projects obtained from GitHub. The findings reveal that food security, energy, and sustainable agriculture are predominant topics in academic discussions, with a noticeable increase in focus from 2017 onwards. Practical projects are focused on transparent tracking and decentralised management. The overlap between academic and practical spheres is evident in the shared focus on energy and environmental management, demonstrating blockchain’s growing role in addressing global environmental challenges. The study underscores the importance of integrating theoretical research with practical implementations to harness blockchain’s full potential in promoting sustainable environmental practices.

Background P53 gene mutation is a very common event in human neoplasia, and genetic mutations in the P53 gene in a single allele are responsible for a hereditary cancer susceptibility syndrome (Li Fraumeni). These variants encode distinct isoforms of the p53 protein, which may disrupt its transcriptional activity. These point mutant proteins are more stable than the normal protein and the mutant product accumulates at a high level that allows obtaining important information about p53 gene expression in malignant cells, especially in Chronic Lymphocytic Leukemia, (CLL). By Enzyme Linked Immune-Absorbent Assay method, (ELISA), was analyzed the frequency of p53 protein expression to 20 eligible patients diagnosed with CLL for to investigate the relationship of this protein in the stages of the disease and the impact on treatment response and survival. In ELISA technique was used the specific antibodies for isoform p53 protein, PAb 240 antibodies. These antibodies bind specifically to denatured p-53 protein. Species reactivity is for human in conformity with the prospect from Manual, Catalog No. LS-F174, Bio-Rad. Results The average concentrations of p53 proteins in 17 of 20 cases were found 16.76 μg / dl, with CV = 0.5% and the probability index p = 0.034. Very high pathological values in the 3 cases of isoform p53 protein were calculated in 2 men, (PM) in the value of 60 µg / dL, respectively at 40 µg / dL and in the case of females, (PW), in 40 µg / dL value, with the transformation into Diffuse Large Lymphoma, (DLL). Conclusion This ELISA method has proven to be a useful prognostic tool for the application of personalized treatment of on-immune therapy, in cases diagnosed with the type B-CLL.

In this work is proposed a new unsupervised method to evaluate the behavior of urban green areas in presence of heatwave scenarios analyzing the NDVI, NDMI and LST satellite data. To evaluate how these three indices characterize urban green areas during periods of heat waves, a reclassification of the data raster of each index is carried out. Rather than using standard classifications of the three indices, an unsupervised classification approach is proposed that uses the Elbow method to determine the optimal number of classes and the Jenks thematic classification method. Each class is assigned a Gaussian fuzzy set with means and standard deviations equal to that of the associated thematic class. The green urban areas are classified using zonal statistics operators and the degree of membership in the corresponding fuzzy set is used to assess the reliability of the classification. Finally, for each type of greenery the frequencies of belonging to the NDVI, NDMI and LST classes are analyzed to evaluate the behavior of the type of urban greenery during heatwaves. The framework was tested in an urban area consisting of the city of Naples (Italy). The results show that some types of greenery, such as deciduous forests and olive groves, are not very vulnerable to heatwave scenarios, unlike uncultivated areas which, instead, show critical behaviors during heatwaves.

Elderly individuals frequently perceive companion robots devoid of warmth, resulting in a reluctance to accept these robots' services. This perception has become a significant barrier to the introduction of companion robots into households. To address this issue, this study employs KE methods to translate the elderly's need for warmth perception from companion robots into elements of modelling design. Initially, 20 pairs of affective words and 22 sample images of companion robots were chosen. The "rational-emotional" and "dim-bright" dimensions were identified as positively influencing the elderly's warmth perception of companion robots through SD method analysis. Subsequently, a hierarchical analysis table was established, with warmth perception as the root layer, modelling style and color matching as the basic layer, "rational-emotional" and "dim-bright" as the expansion layer, and the eight characteristic elements of companion robots as the morphological layer. The link between affective imagery and design elements was then established from the sample robots with higher warmth perception scores. Based on the correlation between the two, various design schemes were formed through random combinations. Finally, the design schemes were evaluated using the warmth perception scale, and the warmth perception scores of each sample model were obtained. This research provides design references for designing companion robots for the elderly with a "sense of warmth".

Purpose: To evaluate prognostic factors for visual outcome in patients with diabetes who have undergone vitrectomy (PPV) for severe proliferative diabetic vitreo-retinopathy (PDVR) in at least one eye in the past 15 years. Methods: Medical records of 132 eyes of 66 patients were analyzed (median age 52ys 21-80; patients with type 1/2 diabetes 40/26, median follow-up 38 months 9-125). Correlation between final good visual outcome defined as 0.5≤ best corrected visual acuity (BCVA) and prognostic factors (age, sex, type and duration of diabetes, metabolic status, BCVA, diabetic retinopathy status, data of preoperative management, data of vitrectomy, postoperative complications) were analyzed. Results: BCVA improved significantly in the entire study cohort (from median 0.05 min-max 0.001-1 to 0.32 0.001-1, p <0.000). Visual stabilization was achieved in the majority of patients, and relatively good visual acuity (0.5≤BCVA) was maintained in more than one third of eyes. Multivariable GEE statistics showed that in addition to duration of diabetes and stable HbA1c values, only preoperative tractional macular detachment proved to be an independent significant predictor of visual outcome. Conclusions: Pars plana vitrectomy is a useful tool when performed early before tractional macular detachment. However, long-term visual stability can only be achieved with good metabolic control.

Since the 1960s, forest planners have used linear programming models to develop management plans for large, forested areas. Hundreds of academic papers have presented such models, incorporating multiple objectives, a growing diversity of management interventions, and uncertainty, among other things. Three basic ways to formulate these models have been used: Model I, III, and III. We define these models based on the sequence of management unit states represented by the variables. In Model I, variables represent a sequence of states from the beginning of the planning horizon to the end. In Model II, variables represent a sequence of states from one intervention to the next. Finally, in Model III, variables represent a single arc in a management unit’s decision tree, including only a beginning and an ending state. We formulate each type of model for a case study with three increasingly complex scenarios incorporating additional ecosystem services. Our results indicate that, despite requiring more variables and constraints, Model III requires the least time to formulate, largely because it has the least dense parameter matrix. Model II has the shortest solution times, with Model III close behind. Model I requires both the longest formulation and solution times.

Phelipanche ramosa is a root parasitic plant fully dependent on host plants for nutrition and development. Once germinated, the parasitic seedling develops inside of the infected roots a specific organ, the haustorium, thanks to notably cell wall degrading enzymes of haustorial intrusive cells and induced modifications in host’s cell walls. The model plant Arabidopsis thaliana is susceptible to P. ramosa, thus mutants in cell wall metabolism, notably in pectin remodeling like Atpme3-1, are of interest in studying the involvement of cell wall degrading host’s enzymes in establishment of the plant-plant interaction. Host-parasite co-cultures in mini-rhizotrons systems revealed that parasite attachments are twice more numerous and tubercle growth is quicker on Atpme3-1 roots than on WT roots. When compared to the WT, increase in susceptibility in the mutant is associated to reduction in PME activity in roots and to lowering in the degree of pectin methylation at the host-parasite interface, as detected immunohistochemically in infected roots. In addition, both WT and Atpme3-1 responded to infestation by modulations in expression of PAE and PME encoding genes and in global related enzymes activities in roots, before and after parasite attachment. However, modulations differ in WT and Atpme3-1 and this may contribute to different pectin remodeling in roots and contrasted susceptibility to P. ramosa. By this integrative study, we could define a model of the cell wall response to this particular biotic stress and indicate for the first time the role of PME3 in this parasitic plant-plant interaction.

In recent years, transformer-based models have gained prominence in multivariate long-term time series forecasting (LTSF), demonstrating significant advancements despite facing challenges such as high computational demands, difficulty in capturing temporal dynamics, and managing long-term dependencies. The emergence of LTSF-Linear, with its straightforward linear architecture, has notably outperformed transformer-based counterparts, prompting a reevaluation of the transformer's utility in time series forecasting. In response, this paper presents an adaptation of a recent architecture termed extended LSTM (xLSTM) for LTSF. xLSTM incorporates exponential gating and a revised memory structure with higher capacity that has good potential for LTSF. Our adopted architecture for LTSF termed as xLSTMTime surpasses current approaches. We compare xLSTMTime's performance against various state-of-the-art models across multiple real-world datasets, demonstrating superior forecasting capabilities. Our findings suggest that refined recurrent architectures can offer competitive alternatives to transformer-based models in LTSF tasks, potentially redefining the landscape of time series forecasting.

Diabetes mellitus, a chronic and non-transmissible disease, triggers a wide range of micro- and macrovascular complications. The differentiation of pancreatic β-like cells (PβLCs) from induced pluripotent stem cells (iPSCs) offers a promising avenue for regenerative medicine aimed at treating diabetes. Current differentiation protocols strive to emulate pancreatic embryonic development by utilizing cytokines and small molecules at specific doses to activate and inhibit distinct molecular signaling pathways, directing the differentiation of iPSCs into pancreatic β cells. Despite significant progress and improved protocols, the full spectrum of molecular signaling pathways governing pancreatic development and the physiological characteristics of the differentiated cells are not yet fully understood. Here, we report a specific combination of cofactors and small molecules that successfully differentiate iPSCs into PβLCs. Our protocol has shown to be effective, with the resulting cells exhibiting key functional properties of pancreatic β cells, including the expression of crucial molecular markers (pdx1, nkx6.1, ngn3) and the capability to secrete insulin in response to glucose. Furthermore, the addition of vitamin C and retinoic acid in the final stages of differentiation led to the overexpression of specific β cell genes.

Every individual at some point encounters the progressive biological process of aging which is considered one of the major risk factors for common diseases. The main drivers of aging are oxi-dative stress, senescence, and Reactive oxygen species (ROS). The renin-angiotensin-aldosterone system (RAAS) includes several systematic processes for the regulation of blood pressure which is caused by an imbalance of electrolytes. During activation of RAAS, binding of angiotensin II (ANG II) to angiotensin II type I receptor (AGTR1) activates intracellular NADPH oxidase to generate superoxide anions and promote uncoupling of endothelial NO synthase, which in turn decreases NO availability and increases ROS production. Promoting oxidative stress and DNA damage mediated by ANG II is tightly regulated. Individuals with sodium deficiency-associated diseases such as Gitelman syndrome (GS) and Bartter syndrome (BS) show down-regulation of inflammation-related processes and have reduced oxidative stress and ROS. Additionally, the histone deacetylase-Sirtuin-1(SIRT1) has a significant impact on the aging process with reduced activity with age. However, GS/BS patients generally sustain higher levels of SIRT1 activity than aged-matched healthy individuals. In this review, we highlight the importance of the hallmarks of aging, inflammation, and the RAAS system in GS/BS patients and how this might impact healthy aging. We further propose fu-ture research directions for studying the etiology of GS/BS at the molecular level using pa-tient-derived renal stem cells and induced pluripotent stem cells.

The study evaluated the functional and sensory properties of infant complementary foods formulated from millets, orange-flesh sweet potatoes, carrots, periwinkle and oyster. Experimental/cross-sectional design was used. Millet, orange-flesh sweet potato (OFSP), carrots, periwinkle and oyster were purchased, processed into flour using standard methods. The complementary food was formulated on protein basis for infants 6–12 months. The formulated foods were millet/OFSP flours (70:30), millet/OFSP/carrot/periwinkle (49:29:7:15), and millet/OFSP/carrot/oyster (65:20:5:10). Functional properties were carried out using standard methods. Sixty nursing mothers attending Orogbum Health Centre were systematically sampled for the sensory evaluation. ANOVA was used for the study. The result showed packed density (0.77 g/mL) was significantly higher (p < 0.05) in food formulated from millets/OFSP than in millet/OFSP/carrot/oyster (0.68 g/mL). Loosed density was lowest (0.40 g/mL) in millet/OFSP/carrot/oyster. Carr index from ranged from 42.23 in millet/OFSP/carrot/oyster to 44.41 in millet/OFSP. Wettability was highest (45.03) in millet/OFSP/carrot/periwinkle compared to wettability value (26.53) for millet/OFSP. Solubility ranged from 18.36 to 46.62, with the highest (46.62) in millet/OFSP/carrot/periwinkle. The peak viscosity of the infant complementary food samples ranged from 64.53 rapid visco analyzer units (RVU) to 89.33 RVU. The infant complementary food formulated from millet/OFSP had significantly higher (p < 0.05) acceptability score (6.35).

Orthodontic appliances may cause discomfort for patients. It could influence person‘s psychological well–being. The aim was to examine psychological health of patients wearing orthodontic appliances. It is important to analyze well-being of patients during orthodontic treatment because it is started in a young age and it may affect one’s psychological health. Therefore, for doctors and patients it is important to understand and take every aspect of the treatment into consideration when deciding when to start the treatment and what appliance to choose. 339 patients answered anonymous questionnaire. They were divided into four groups according to their age and type of appliance. Main reasons to seek treatment were crooked teeth and bad bite. Statistically signifi-cant difference was between women and men as women seeked treatment because of crooked teeth, meanwhile men indicated bad bite as main reason. 48.7% of subjects noted that they were feeling good during treatment, however, 4% of all patients noted that they were feeling bad. 45% of subjects stated that they felt unhappy at least sometimes. 43% of subjects felt stress. Even though patients indicated various negative aspects on their well-being during treatment, for the majority of the subjects end results significantly increased their psychological well-being.

The landscape of tourism is undergoing rapid transformation in response to societal shifts, economic fluctuations, and advancements in the tourism sector, particularly in the post-pandemic. Tourists are increasingly inclined towards outdoor activities and natural landscapes, prioritizing experiences that emphasize health and safety. Conversely, cultural tourism emphasizes local heritage and immersive encounters to accommodate evolving preferences. Cultural tour guides play a pivotal role in shaping tourists' perceptions and intentions to revisit. Empirical research conducted among Chinese tourists visiting Nanjing Museum explores this paradigm shift. A questionnaire was distributed to 402 respondents to examine the principal factors influencing intentions to revisit. Factor and regression analyses illustrate the significance of cultural tour guides' competencies, revealing a positive correlation with intentions to revisit. It is noteworthy that tourist empathy moderates this relationship, wherein higher levels of empathy magnify the impact of tour guides' competencies on intentions to revisit. Robustness checks further validate these findings, affirming the nuanced interaction between service competencies, tourist empathy, and intentions to revisit. The study underscores the substantial influence of cultural tour guides on shaping tourist experiences and fostering repeat visits. This is contingent upon both the quality of service provided and the degree of empathy exhibited towards tourists.

Follicular helper CD4+ T cells (TFH) are a major cellular pool for the maintenance of HIV reservoir. Therefore, the delineation of the follicular (F)/germinal center (GC) immune landscape will significantly advance our understanding of HIV pathogenesis. We have applied multiplex confocal imaging, in combination with relevant computational tools, to investigate, F/GC in situ immune dynamics in viremic (vir-HIV), antiretroviral treated (cART HIV) People Living With HIV (PLWH) and compare them to reactive, non-infected controls. Lymph nodes (LNs) from viremic and cART PLWH could be further grouped based on their TFH cell densities in high-TFH and low-TFH subgroups. These subgroups were also characterized by different in situ distribution of PD1hi TFH cells. The significantly accumulated follicular, compared to extrafollicular, FOXP3hi CD4+ T cells found in the low-TFH cART-HIV group were characterized by a less scattered in situ distribution and strongly correlated with the cell density of CD8+ T cells in this group. An inverse correlation between plasma viral load and LN GrzBhiCD8+ T and CD16hiCD15lo cells was found. Our data reveal the complex GC immune landscaping in HIV infection and suggest that follicular FOXP3hi CD4+ T cells could be negative regulators of TFH cell prevalence in cART-HIV.

The present paper deals with research on maintenance strategy and maintenance process improvement procedures to increase the efficiency and quality of the production system. It includes the design of maintenance performance indicators relevant to today's manufacturing systems to track improvements in the sustainable development of the manufacturing system. There are also the basic principles of maintenance strategy with linkages to the manufacturing system and selecting the strategy for the organization. The paper emphasizes maintenance management auditing and quality implementation in maintenance. Further, there is the process of changing the maintenance strategy described. This process includes reassessing the criticality of machines and equipment and their design units, then resource and capacity planning and input for maintenance management. It describes the impact of changing the maintenance management organization and maintenance capacity considering the change of strategy and the evaluation of maintenance choice alternatives, together with an analysis of the optimization procedure, which has an impact on social implication. The paper concludes by presenting the achieved impacts of maintenance strategy are: (1) increase in production efficiency (10%), (2) quality improvement in production (20%), (3) performance improvement (30%), (4) reduction of maintenance process costs (35%).