This research will investigate how heat treatments affect the behaviour of 3D printed gears made from Polyamide 6 (PA6), a thermoplastic polymer with excellent mechanical properties. However, imperfect structures can result from the 3D printing process, which involves rapid cooling of the molten polymer. Gears were manufactured from PA6 by means of a dedicated 3D printer and their behaviour in gears was then analysed by means of various specific test protocols. Some of the gears were subjected to annealing heat treatments to determine material behaviour, which was a key aspect of this study. Finite Element Analysis (FEA) was used to investigate the effect of heat treatments on the mechanical properties of PA6 thermoplastic material, specifically in the area of 3D printed gear mechanisms. The simulations included both static and transient conditions to determine the influence of different heat treatments on the mechanical properties of PA6. Through the use of comprehensive FEA, the research investigates the deformation, stress distribution and strain rates in 3D printed gears and elucidates the correlation between the mechanical properties and the contact pressure on the tooth flanks during gear operation. As conclusion the study mainly uses numerical simulations based on mechanical characteristics determined in our laboratory. The contribution of the study lies in the novelty of highlighting, through the results obtained, the influence of heat treatments on wear and mechanical stress related factors.

The blood-brain barrier (BBB) acts as a structural and functional barrier for brain homeostasis. This review highlights the pathological contribution of BBB dysfunction to neuroimmunological diseases, including multiple sclerosis (MS), neuromyelitis optica spectrum disorder (NMOSD), myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), autoimmune encephalitis (AE) and paraneoplastic neurological syndrome (PNS). The transmigration of massive lymphocytes across the BBB caused by the activation of cell adhesion molecules is involved in the early phase of MS, and dysfunction of the cortical BBB is associated with the atrophy of gray matter in the late phase of MS. In the onset of NMOSD, increased permeability of the BBB causes the entry of circulating AQP4 autoantibodies into the central nervous system (CNS). Recent reports have shown the importance of glucose-regulated protein (GRP) autoantibodies as BBB-reactive autoantibodies in NMOSD, inducing antibody-mediated BBB dysfunction. BBB breakdown has also been observed in MOGAD, NPSLE, and AE with anti-NMDAR antibodies. Our recent report demonstrated the presence of GRP78 autoantibodies in patients with MOGAD and the molecular mechanism responsible for GRP78 autoantibody-mediated BBB impairment. Disruption of the BBB may explain the symptoms in the brain and cerebellum in the development of PNS, as it induces the entry of pathogenic autoantibodies or lymphocytes into the CNS by autoimmunity against tumors in the periphery. GRP78 autoantibodies were detected in paraneoplastic cerebellar degeneration and Lambert-Eaton myasthenic syndrome and were associated with cerebellar ataxia with anti-P/Q type voltage-gated calcium channel antibodies. This review reports that therapies affecting the BBB that are currently available for disease-modifying therapies for neuroimmunological diseases have the potential to prevent BBB damage.

Background/Objectives: RAS is associated with coronary artery disease (CAD), exacerbation of arterial hypertension and progression to heart failure, but remains frequently unrecognised in clinical practice. Methods: We conducted a systematic review and meta-analysis of studies by pooling data of patients undergoing CAG due to suspected or stable CAD that received a bilateral renal artery angiography; Results: A total of 31 studies with 31,689 patients were included (mean age 63.2±8.7 years, 20.9% were female). Overall, 13.4% (95%CI 10.5-16.7%) of patients undergoing coronary angiography had significant RAS, with 6.5% (95% CI 4.5-8.9%) and 3.7% (95%CI 2.5-5.2%) having severe and bilateral RAS. The mean weighted proportion of patients with 3-vessel coronary disease (3VD) was 25.1 (95%CI 19.6-30.9%) while 4.2% (95%CI 2.6-6.2%) had leftmain (LM) coronary disease. Patients with RAS compared to those without RAS were significantly older (mean difference - MD 4.2 years, (95%CI 3.8-4.6). The relative risk of RAS was greater for the female sex (risk ratio, 95%CI; RR 1.3, 1.03-1.57), presence of diabetes (RR 1.2, 1.10-1.36), arterial hypertension (RR 1.3, 1.21-1.46), dyslipidemia (RR 1.1, 1.06-1.14), peripheral artery disease-PAD (RR 2.1, 1.40-3.16), chronic kidney disease-CKD (RR 2.6, 2.04-3.37), 3VD (RR 1.6, 1.30-1.87), and LM disease (RR 1.8, 1.28-2.47). Smoking had a neutral effect on the risk of RAS occurrence (RR 1.0, 0.94-1.06); Conclusions: RAS is common in patients undergoing coronary angiography. CKD, PAD, older age, and severe CAD were among the strongest predictors for the presence of significant RAS.

Background: Multisensory integration (MSI) avoids cognitive overload, and the traditional all-or-nothing perspective for dysfunctional MSI in schizophrenia has been increasingly challenged. This study aimed to systematically review and meta-analyze extant evidence on audiovisual MSI in schizophrenia. Methods: We searched Web of Science, PubMed, PsycINFO and PsycARTICLES databases from inception until April 16^th, 2024. Studies using appropriate audiovisual integration tasks to compare either behavioral or neural responses between schizophrenia individuals and healthy controls were included. Primary outcome measures included between-group differences (Hedge’s g) and symptomatic correlations (Fisher’s z) in three components of audiovisual integration tasks, including audiovisual processing, adaptation and integration. The multilevel random-effects models were used to address statistical dependency. Results: In total, 209 between-group and 116 correlational effect sizes were synthesized from 46 studies, representing 1,108 non-overlapped schizophrenia participants and 1,084 healthy controls. The overall dysfunctional audiovisual MSI in schizophrenia (g = -0.50, [95% CI, -0.64 to -0.37]) was primarily ascribed to the impaired audiovisual processing (g = -0.53, [95% CI, -0.71 to -0.35]) and adaptation (g = -0.71, [95% CI, -0.99 to -0.42]), rather than integration itself (g = -0.23, [95% CI, -0.56 to 0.11]). Pooled correlational effect size was extremely small (z = 0.16, [95% CI, 0.03 to 0.30]). Conclusions: Individuals with schizophrenia show dysfunctional multisensory processing and adaptation, but preserve a less impaired multisensory integration ability. Our findings provide implications for clinical interventions, as the relatively preserved audiovisual integration ability may serve as a possible avenue for cognitive training programs.

The emergence of superhydrophobicity-based antibacterial materials represents a promising approach to upholding surface cleanliness and hygiene, effectively preventing bacterial adhesion. This research describes the synthesis of a superhydrophobic coating with antibacterial and bacteriostatic properties using silica nanoparticles (SiO2 NPs) modified with 1H,1H,2H,2H-Perfluorodecyltriethoxysilane (PFDTES). TEM, XRD, EDS, SEM, and FTIR analyses were conducted to study its morphology and surface characterization. Additionally, the coating was applied on glass substrates using the spray coating method, varying the number of layers to evaluate antibacterial and bacteriostatic properties through turbidimetry and inhibition halo measurement techniques. The durability of the coatings was also assessed by exposing them to outdoor conditions for 35 days. This study aimed to evaluate the antibacterial capacity of the superhydrophobic coating and its weather resistance. The results demonstrate that a superhydrophobic coating with a contact angle ≥150° and a sliding angle ≤10° was successfully synthesized using SiO2 NPs smaller than 10 nm modified with PFDTES. The coating exhibited the ability to inhibit bacterial growth by preventing the adhesion of bacteria such as Escherichia coli and Staphylococcus aureus; moreover, the number of layers correlated with enhanced antibacterial properties. The coating also showed good durability under outdoor conditions. These results support the potential application of superhydrophobic coatings to prevent these bacteria from adhering and growing in areas where they can be harmful.

Community engagement involves five phases: informing, consulting, involvement, collaboration, and empowerment. This study explored the experiences of community stakeholders during the collaborative phase of community engagement co-developed by researchers and community members for the implementation of projects. The study was carried out in uMkhanyakude District, South Africa. A qualitative case study approach was used to explore the collaboration phase. Data was collected from key community stakeholders through key informant interviews, focus group discussions, and direct observations. The findings indicated that village headmen, community advisory board members and community research assistants can collaborate as trustworthy partners to address community health challenges. Community research assistants complement the role of participatory-based research appropriately, as they get to be involved hands-on together with the researchers. However, despite the significant role community research assistants played in the projects implemented by the KwaZulu-Natal Ecohealth Program, maintaining collaborative relationships was marred with unforeseen difficulties due to many barriers which included stretched work hours, lack of breaks, miscommunication around compensation, inappropriate behavior from the research team, and humiliation/oppression over language. Initiatives for community-based participatory research have proven to be effective as a collaborative approach that combines methodical research, involvement, and action to address health-related problems. However, it is necessary to consider the local socio-cultural aspects that could lead to barriers and misunderstandings between the locals and the researchers. Collaborative partnerships should ultimately result in community empowerment.

Selective Laser Melting (SLM) is a complex additive manufacturing process that requires precise control of thermal conditions to ensure the quality and reliability of produced parts. The main challenge lies in accurately predicting the thermal behavior during SLM, which is influenced by rapid heating and cooling cycles, high thermal gradients, and temperature-dependent material properties. This study addresses this challenge by developing a comprehensive thermal model for the SLM process of 316L stainless steel (316L SS) and Ti6Al4V titanium alloy using Finite Element Analysis (FEA) in Abaqus. The model incorporates temperature-dependent material properties and phase transformations to simulate the temperature distribution and thermal history during SLM. To validate the model, experimental studies were conducted using custom-designed argon chambers and stainless-steel powder. The experimental results showed strong agreement with the simulated melt pool dimensions and thermal histories, confirming the model's accuracy. Key findings include the model's ability to predict the effects of varying processing parameters such as laser power and scanning speed on thermal behavior and melt pool characteristics. This validated model serves as a valuable tool for optimizing SLM processing parameters, enhancing the un-derstanding of thermal phenomena in additive manufacturing, and improving the quality and reliability of manufactured parts. Due to budget constraints, experimental validation was initially performed only on 316L SS. This approach allowed for the tuning of the finite element model before extending its application to Ti6Al4V. The successful validation with 316L SS provides a solid foundation for applying the model to more challenging materials like Ti6Al4V, ensuring cost-effectiveness and safety in initial experimentation. The novelty of this research lies in its detailed and validated thermal model, which bridges the gap between experimental and numerical approaches in SLM. By accurately simulating and validating the thermal processes involved in SLM, this study contributes to the advancement of additive manufacturing technologies and offers practical insights for industrial applications.

Accurate assessment of shale gas reserves hinges on a detailed characterization of gas and water distribution within shale reservoirs. Despite its importance, the nanoscale behavior of water and methane in deep shale formations, especially under elevated temperatures and pressures, remains poorly understood. This study proposes a novel molecular modeling approach to represent the complex nanocomposite porous media found in deep shale matrices. Leveraging quantitative data from experimental analyses of shale pore composition, we developed a molecular model that accurately reflects the intricate pore-slit structure within a composite of kerogen and illite, common constituents of shale. Employing a hybrid grand canonical Monte Carlo and molecular dynamics simulation technique, we investigated the micro-scale distribution and preferential adsorption sites of water and methane within the shale matrix. Our research further elucidates the impact of water on the pore structure of shale and delineates the co-occurrence patterns of water and methane. The simulations reveal that water and methane share similar adsorption preferences on kerogen surfaces, while methane does not exhibit specific adsorption preferences on water-bearing illite. We also find that the presence of water significantly alters the illite pore space, leading to a reduction in larger pore volumes and a concomitant increase in smaller pores. The decrease in methane content with increasing water content is more pronounced in the shrinkage cracks compared to the kerogen matrix pores and is particularly notable in the macropores of illite. The findings underscore the differential sensitivity of methane content to water levels across various shale pore types. These insights contribute to a deeper theoretical understanding of gas and water distribution mechanisms in deep shale reservoirs, offering valuable support for the evaluation of deep shale gas resource potential.

Financial institutions are currently undergoing a significant shift from traditional robo-advisors to more advanced generative artificial intelligence (GenAI) technologies. This transformation has motivated us to investigate the factors influencing consumer responses to GenAI-driven financial advice. Despite extensive research on the adoption of robo-advisors, there is a gap in understanding the specific contributors and differences in consumer attitudes and reactions to GenAI-based financial guidance, particularly in the context of GenAI. This study aims to address this gap by analyzing the impact of personalized investment suggestions, human-like empathy, and the continuous improvement of GenAI-provided financial advice on consumers' perceived authenticity, their utilitarian attitude towards the use of GenAI for financial advice, and their reactions to GenAI-generated financial suggestions. A comprehensive research model was developed based on Service-Dominant Logic (SDL) and Artificial Intelligence Device Use Acceptance (AIDUA). The model was subsequently employed in a structural equation modeling (SEM) analysis of survey data from 822 mobile banking users. The findings of this study indicate that personalized investment suggestions, human-like empathy, and the continuous improvement of GenAI's recommendations have a positive influence on consumers' perception of its authenticity. Moreover, we discovered a positive correlation between utilitarian attitudes and perceived authenticity, which ultimately influences consumers' responses to GenAI's financial advisory solutions. This is manifested as either a willingness to engage or resistance to communication. This study contributes to the research on GenAI-powered financial services and underscores the significance of integrating GenAI financial guidance into the routine operations of financial institutions. Our work builds upon previous research on robo-advisors, offering practical insights for financial institutions seeking to leverage GenAI-driven technologies to enhance their services and customer experiences.

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

Machine learning (ML) has transformed the financial industry by enabling advanced applications such as credit scoring, fraud detection, and market forecasting. At the core of this transformation is deep learning (DL), a subset of ML that is robust at processing and analyzing complex and large datasets. This paper provides a concise overview of key deep learning models, including Convolutional Neural Networks (CNNs), Long Short-Term Memory networks (LSTMs), Deep Belief Networks (DBNs), Transformers, Generative Adversarial Networks (GANs), and Deep Reinforcement Learning (Deep RL). The study examines their learning processes, mathematical foundations, and practical applications in finance. It also explores recent advances and emerging trends in the financial industry alongside critical challenges such as data quality, model interpretability, and computational complexity, offering insights into future research directions that can guide the development of more robust and explainable financial models.

Artificial intelligence (AI) apps, such as ChatGPT, Gemini, and Siri, have taken society and higher education institutions by storm. Yet, there is a paucity of empirical studies recording and analysing university social sciences students’ attitudes toward AI. Hence, the present study draws upon a sample of 190 university students (82.45% female) from a Greek social sciences department to query what are the students’ attitudes toward AI in education and future employment and what factors correlated with these attitudes. Descriptive statistics revealed that students’ attitudes toward AI were mostly positive. A principal components analysis confirmed a three-component solution of attitudes toward AI, comprising cognitive, behavioural, and emotional dimensions. Comparative analysis of the three components indicated that the emotional dimension was the highest ranked, followed by the cognitive and behavioural dimensions. Pairwise correlation analyses revealed that the strongest correlate of cognitive, behavioural, and emotional components of attitudes toward AI was the future frequency of AI use, followed by general feelings of safety with technology. In conclusion, students display more emotional and cognitive favourable dispositions toward AI. The social background of the students and the prospective future use of AI play a key role in the formulation of attitudes toward AI. University educators need to provide more teaching and learning about AI to improve students’ attitudes toward AI and future AI use.

This paper reveals some properties of the cumulative entropy of consecutive k-out-of-n:F system's lifetime. First, we introduce a method for calculating the cumulative entropy of their lifetime and explore its preservation properties using established stochastic orders. Ad- ditionally, we obtain useful bounds that can used in situations where the distribution function of the system's component lifetimes are complicated or systems have large components. To support practical applications, we present two nonparametric estimators for the cumulative entropy of these systems. The efficiency and performance of these estimators are illustrated with simulated datasets and further validated with real data sets.

It is commonly held that gravitation is a major force field influencing matter. Existing models regard gravitational interaction as a singular weak force; the weakest among the four fundamental forces defined in physics. Recent experimental findings, in both controlled laboratory experiments and natural occurrences, nevertheless, have unveiled the presence of a gravitational repulsion alongside gravitational attraction in the universe. This series of studies reveals that the observed gravitational force results from two immensely powerful distinct forces—gravitational repulsion and attraction—nearly equal and opposing thus in a state of near equilibrium in nature. While the theory of 'Universal Gravitation' established the proportionality of the gravitational force to mass, the recognition of gravitational repulsion force proportional to the temperature as a manifestation of thermal energy has only emerged from present experimental insights. Furthermore, the imbalance between these two forces has been identified as the Newtonian force, initiating the motion of an object. It provides a compelling explanation for the accelerating expansion of the universe: during atomic fusion in stars, a portion of mass is converted into energy. This process increases the energy and decreases the mass of stellar objects. The increase in energy enhances the repulsive force among them, while the reduction in mass diminishes their gravitational attraction, leading to the accelerating expansion of the universe.This paper introduces a model elucidating the characteristics of gravitational forces and the transmission of energy within matter through the concept of 'Gravitational Currents.' A set of postulates is formulated to elucidate the interaction of gravitational fields with matter and the presence of gravitational currents. The discussion is supported by experimental evidence substantiating these concepts.In this series of experiments, a gyroscope - a standard apparatus in the scientific community with a spinning wheel mounted at one end of a freely pivoted rod having full degrees of freedom - is utilized. When the wheel is set in rotation, the rod carrying the wheel precesses[1] around the vertical axis at the pivoted end, while levitating in free space defying the Earth's gravitational attraction. This paper establishes that the conventional explanation involving the cross product of two vectors—the torque due to weight and the angular force (change of angular momentum) of the wheel—fails to account for the observed revolving and lifting forces. Instead, it is demonstrated that these forces result from the upward shear force (which is the lifting force in this case) generated within the axis of the rod and the wheel itself. This phenomenon is attributed to the flow of energy, conceptualized as gravitational current, within the axial rod in the Earth's gravitational field. The described process can be envisioned as a gravitational motor with gravitational current flowing through matter in a gravitational field.The results of the experiments substantiate the conclusion that there exist two fields defined as the intrinsic field and the natural force fields. The intrinsic gravity field is innate (linked) to every object, matter or entity in the universe, and it is dispersed in all directions in free space independent of other entities. The actual force fields manifest between any two objects in the universe once they become cognizant of each other's existence through their intrinsic fields.The inherent force field exhibits a preference/tendency for existence within a medium rather than in free space, akin to the way a magnetic field runs within ferromagnetic materials rather than in open space. If external force fields pass/runs through the medium, it affects the internal force fields of the medium, depending on the magnitudes and the directions of the external force fields and intrinsic force fields. This implies that energy moves through the force field, and under the influence of the gravitational field, this energy flow can be conceptualized as a gravitational current.Gravitational waves and electromagnetic waves share similarities in their roles in transmitting energy through open space. The potential for an analogy within a unified theoretical framework connecting electromagnetic fields and gravitational fields has surfaced, echoing Einstein's attempted unified theory proposed in 1916. The paper delves into the parallels between electromagnetic motors and gravitational motors.Furthermore, alongside the concept of gravitational currents addressed in this paper, the research also elucidated a precise definition of the [Newtonian/mechanical] “force” and mechanism for its origination and function, termed: Intrinsic Energy Spin Force (IESpinF). The analysis presented here demonstrates that the Newtonian/mechanical force arises from a perturbation or imbalance within the equilibrium of gravitational IESpinF, which includes both repulsion and attraction forces. [1] One of the main properties of gyroscopic action is “precession”. Precession is a change in the orientation of the rotational axis of a rotating body. If the axis of rotation of a body is itself rotating about a second axis, that body is said to be precessing about the second axis.

Interpore hydrates are the main occurrence forms of marine gas hydrates. Pore characteristics are a vital factor affecting the thermodynamic properties of hydrates and their distribution in sediments. Currently, the characterization of the pore system for hydrate-bearing reservoirs are little reported. Therefore this paper focus on the Krishna-Godavari Basin, via varies methods to characterize the hydrate-bearing sediments in the region. The results showed that X-ray Diffraction(XRD) combined with Scanning Electron Microscope (SEM)and Cast Thin Section (CTS) can better characterize the mineral composition in the reservoir, High Pressure Mercury Injection (HPMI) focused on the contribution of pore size to permeability, Constant Rate Mercury Injection(CRMI) had the advantage of distinguishing between pore space and pore throat, and Nuclear Magnetic Resonance Cryoporometry (NMRC) technique can not only obtain the pore size distribution of nanopores with a characterization range greater than Nitrogen Gas Adsorption (N2GA), but also quantitatively describe the trend of fluids in the pore system with temperature. As for pore system, Samples 58 and 68 all developed nanopores, the mineral distribution was relatively scattered, and they were rich in paleontological shells such as foraminifera, among which Sample 68 had more pyrite content, and abundant pyrite framboid was observed, which made the intergranular pore develop and provide more nanopores. Sample 58 has a high concentration of pore and throat, high pore connectivity, low pore curvature, and pores with a diameter of 10μm contributing to the main permeability, with an average pore radius of 2.495μm, whereas Sample 68 has poor pore connectivity, high curvature, and pores with a diameter of 1μm contributing to the main permeability, with an average pore diameter of 60 nm, which explains the obvious difference in permeability between the two samples.

Background: Interleukin-6 is dysregulated in multiple pathological conditions, e.g. cancer and inflammatory diseases. Aim: To investigate new mechanisms for regulation of pathological IL-6 production. Methods: PBMC produce interleukin-6 (IL-6) stimulated by cancer serum factors or specific peptides. Immunoregulatory albumin neo-structures and peptides were identified with 2D-gel electrophoresis and MALDI-TOF-MS analyses. Il-6 and albumin neo-structures were determined by ELISA. Results: Conformational changes of normal serum albumin by proteolytic degradation generates an IL-6 inducing neo-structure, IL-6 inducing factor (IL-6IF), which is immunogenic eliciting production of autoantibodies. IL-6 production induced by IL-6IF and cancer patient sera is inhibited by specific antibodies. The serum concentration of IL-6IF, is significantly higher in advanced cancer stages and its presence is significantly correlated to the survival of the patients. Conclusion: A new mechanism for induction IL-6 synthesis is presented. Based on this mechanism the pathological IL-6 production related to an enhanced proteolytic activity can be diagnosed and selectively inhibited by specific antibodies. Such antibodies have been identified and purified. Thus, the neo-structure, inducing pathological IL-6 production, associated with a reduced survival of cancer patients can be selectively removed by therapeutic administration of antibodies leaving the function of IL-6 needed for the normal activity of the immune system intact.

The paper presents theoretical notions with practical applications for establishing of one dental bur lifetime (durability and reliability based on the active part wear considering a series of statistical indicators. For the justification application of theoretical notions in practice, a conical-cylindrical dental bur was studied experimentally, to obtain a series of data in the work process, necessary for statistical calculation. The parameter taken into consideration in this paper is mass lost through the dental bur active part wear, tested. This is useful for the dental bur lifetime establishment and its extension or even optimization in operation. The loss of mass of the dental bur active part is analyzed in the work process by the results and experimental data obtained and validated by a numerical calculation statistical-mathematical. The numerical calculation approximates very well the mass lost through the wear at different rotation speeds and operation times, with those experimentally determined ones, based on which it was established lifetime. The results showed that the dental bur works with high yield in the first 20 hours of work, , after which it should be replaced with a new one.

The Internet of Things (IoT) technology connects the real world and the network world by integrating sensors and internet technology, which has greatly changed people's lifestyles, showing its broad application prospects. However, traditional materials for the sensors and power components used in IoT limit its development to high-precision detection, long-term endurance, and multi-scenario applications. Metal halide perovskite, with the unique advantages such as excellent photoelectric properties, adjustable bandgap, flexibility, and mild process, exhibiting enormous potential to meet the requirements for IoT development. This paper provides a comprehensive review of metal halide perovskites' application in sensors and energy supply modules within IoT systems. Advances on perovskite-based sensors were discussed as to gas, humidity, photoelectric, and optical sensors. The application of indoor photovoltaics based on perovskite in IoT systems were also discussed. At last, the application prospects and challenges of perovskite-based devices in IoT are summarized.

We studied yeast hand carriage of 260 students from medicine (78), nursing (89), and medical laboratory scientist (93). We isolated yeasts in 27 students (10.4%), with no differences between careers or gender. A significant lower prevalence of carriage was shown in the clinical cycle (2.7%) compared to the basic cycle (13.5%) (p=0.022) and the preclinical cycle (13.5%) (p=0.014).Increased handwashing frequency and alcohol gel use decreased yeast carriage. Students who applied moisturizing hand cream two or more times a day had a lower frequency of yeast carriage (3.4%) compared to those who did not use it or used it only once a day (16.5%), showing a significant difference (p=0.016). The most prevalent species was C. parapsilosis sensu stricto (81.5%), followed by Meyerozyma guilliermondii (C. guillermondii) (7.4%), Trichosporon mucoides (7.4%), and R. mucilagenosa (3.7%). And one case showed mixed carriage of C. parapsilosis and C. albicans. All strains were sensitive to voriconazole, caspofungin, and anidulafungin. This study shows the yeast carriage on the hands of health students, especially of C. parapsilosis, and its reduction with the frequent use of infection control measures and moisturizing hand cream.

Harmful algal blooms are a serious problem for humanity, so the development of tools and methods for their timely detection is an urgent task. The use of optical methods often allows scientists to solve problems of remote and automated monitoring. Temperature spectra of fluorescence can be used as distinctive features of algae, and the fluorescence parameters obtained from them can be used for identification. The paper presents a description of the fluorescence parameters of Alexandrium catenella, and shows their stability during cumulative cultivation. In addition, the cytometric properties of the culture and its pigment composition were studied. In addition, the article compares all the studied properties of this microalga with the alga Prorocentrum cordatum. We demonstrated clear differences in their fluorescence parameters, which makes it possible to distinguish these microalgae by optical methods, for example, during their dominant blooms.

Background and Objectives: Infections are the most common and potentially life-threatening complications of the treatment of children with acute lymphoblastic leukemia (ALL). The aim of this study was to determine epidemiological, clinical and microbiological characteristics of infections in pediatric patients with ALL. Materials and Methods:  Twenty-three children (16 male and 7 female, mean age 5.9 years [range 1.3 to 12.2 years]) with ALL, treated at the Division of Hematology, Oncology and Clinical Genetics, Department of Pediatrics, Clinical Hospital Center Rijeka, Croatia, from January 1, 2015 to December 31, 2020, were included in the study Results: One hundred and four infectious episodes (IEs) were reported (average 4.5 IE per patient). IEs were more frequent in the intensive phases of antileukemic treatment. Neutropenia was present in 48 IEs (46.2%) with a duration greater than 7 days in 28 IEs (58.3%). The respiratory tract was the most common infection site (48.1%). We documented 49 bacterial (47.1%), 4 viral (3.9%), 4 fungal (3.9%) and 10 mixed isolates (9.6%), while in 37 IEs (35.6%) pathogen was not isolated. The most common causes of bacteremia were coagulase-positive staphylococci. The most frequent empirical therapy was third- and fourth-generation cephalosporins, followed by piperacillin/tazobactam. Modification of the first-line antimicrobial therapy was performed in 56.9% of IEs. Granulocyte-colony stimulating factor was administered in 53.8% of IEs, and intravenous immunoglobulins in 62.5% of IEs. One patient required admission to the intensive care unit. No infection-related mortality was reported. Conclusions: ALL patients have frequent IEs. Close monitoring, identification of risk factors, rapid empirical use of antibiotics in febrile neutropenia, and timely modification of antimicrobial therapy play a key role in reducing infection-related morbidity and mortality in children with ALL.

High-flow oscillatory ventilation (HFOV) is a common rescue treatment in infants and children with respiratory failure. This type of ventilation is an effective technique in numerous diseases that affect a child in the postnatal period, such as ARDS, meconium aspiration syndrome (MIS), postnatal pulmonary bleeding and idiopathic pulmonary hypertension (IPH). Although this ventilation technique is commonly recognized as a valuable therapeutic option in the general pediatric population, this is not the same for children with congenital cardiovascular diseases. The key mechanism of oscillatory ventilation is continuous positive pressure administered within the airways via a small tidal volume at high frequency. Tidal volumes are between 1 and 3 ml/kg delivered at 5 – 15 Hz equivalent to 300 – 900 breaths per minute. Few older studies conducted on humans and animals highlight that HFOV may be dangerous for congenital heart patients. According to these evidences, hemodynamic parameters such as blood pressure, wedge pressure, central venous pressure, heart rate and inotrope level can be dangerously changed for patients with congenital heart disease, therefore oscillatory ventilation should be avoided. Numerous retrospective studies have pointed out how oscillatory ventilation constitutes a valid therapeutic option in children with congenital heart disease. Recently, new evidences have highlighted how hemodynamic parameters are modified in a non-significant way by this type of ventilation, remaining beneficial as in the normal pediatric population. This narrative review aims to describe the mechanisms of oscillatory ventilation and collect all the available evidences to support its use in pediatric patients with congenital heart problems.

It seems that natural compounds with bioactivity are the food constituents, present in the diets, that may provide protective effects on health due to their biochemical effects. The main benefits appear to be decline in oxidative stress and inflammation that are crucial in the pathogenesis of obesity, diabetes and metabolic syndrome. Apart from anti-inflammatory activity, these molecules also possess antifungal, and anti-infective preventative effects. Further evidence indicate that these bioactive molecules are the constituents, which are known to increase function of the foods. This review aims to emphasize that plant based diet is rich in phytochemicals such as antioxidants, vitamins, minerals, polyphenolics and flavonoids, amino acids and fatty acids, that are able to cause benefits via these compounds. These bioactive molecules can target mechanisms of oxidative stress and inflammation that are crucial in the management of metabolic syndrome. These antioxidant compounds appear to be essential component of plant based diets and are crucial for healthiness. Most investigators have proposed that bioactive compounds act as nutraceuticals which are able to regulate certain patho-physiological mechanisms responsible for metabolic diseases. The bioactive compoundspresent in the plant based diets are primary and secondary metabolites of nutritive and non-nutritive natural components generating health benefits by preventing or managing chronic disease or its symptoms. The bioactive compounds are known for their beneficial effects to health. Despite their small quantity in the diets, these bioactive compounds may trigger certain mechanisms that may cause alteration with improvement in health. It seems that most of the bioactive compounds co-existing in the plant-based diets, may be extremely healthful. However, if they are taken in excess, they can cause toxic effects. There is an urgent need to evaluate each bioactive compound to establish a beneficial quantity and a threshold of toxicity, while treating metabolic syndrome.

Several studies report an impact of the neurotransmitter dopamine (DA) on human immune cells, with effects dependent on immune cell type addressed and their activation status. Another contributing factor appears to be sex, as sex-specific differences in the dopaminergic pathway are described in the neurological context as well as in autoimmune diseases. However, a deeper understanding of these differences in peripheral immune cells remains limited. In this study, we investigated the effects of dopaminergic stimulation on activation and cytokine secretion of peripheral blood mononuclear cells from women and men using flow cytometry, ELISA and multiplex assay. We found a B cell-driven downregulation in cytokine secretion of monocytes exclusively from women under physiological conditions. Moreover, B cells from men showed higher dopamine receptor (DR) expression, which was shown to be further increased by sex hormones only in men. In monocytes from women, an acute inflammatory stimulus via CpG combined with dopaminergic stimulation caused a switch to a proinflammatory phenotype, which was less pronounced in men. These novel findings in sex-specific responses to dopaminergic stimulation are crucial for understanding DA’s function in the healthy and activated immune system and provide evidence to treat DA-related pathologies in a sex-specific manner.

Vertex-degree-based (VDB) topological indices have been applied in QSPR/QSAR. As an important category, the general logarithmic VDB topological index $T_{lnf}(G)$, is defined as the summation of $ln{f(d(u),d(v))}$, where the summation over all $uv\in E(G)$. In this paper, we give the sufficient conditions for that (1) the path $P_{n}$ is the only tree with the minimal $T_{lnf}$; (2) the star $S_n$ is the only tree with the maximal and the minimal $T_{lnf}$, respectively. As applications, the minimal and maximal trees of some logarithmic VDB indices are determined.

According to current knowledge, although the beneficial effects of regular exercise training are well recognized, there are conflicting data regarding its relation with the occurrence of atrial fibrillation (AF) in competitive athletes. The aim of this literature review was to demonstrate a comprehensive report of incidence, pathophysiology and management of AF in elite athletes. The frequency of AF to be 2 to 10 times greater in high intensity endurance athletes compared to sedentary individuals. A U-shaped relationship between male elite athletes and AF has been observed, while the type and the dose of physical activity seems to play a major role in AF development. Male gender, increasing age, endurance sports, and time of training are associated with AF, thereby confirming a likely association between athleticism and AF. Pathophysiology of AF still remains unclear but, there are suggested theories that include complex mechanisms such as alterations of autonomic tone, left atrial enlargement and fibrosis, electrical remodeling, and increased inflammation. Elite athletes with AF require a comprehensive clinical evaluation and risk factor optimization, similar to that for nonathletes. Although anticoagulation and rate or rhythm control are corner stones for AF management, however, there are still no specific guidelines for elite athletes.

Developmental tasks are formed from an analysis of the culture and social demands in which the individual lives and interacts. Developmental psychology defines Milestones as substantial progress in a developmental task. When a person is able to complete developmental tasks at his stage, that person will be happy and consider his development according to his stage. So far, the current developmental tasks are different from the situation and social demands in Indonesia. Thus, the overview of development tasks has yet to be depicted in the psychological development of Indonesians. The aim of the study was to formulate developmental tasks according to the social environment. This research method was carried out through a survey that was distributed online in all regions of Indonesia. The development task screening questionnaire was prepared according to Havighurst's developmental tasks, including a description of open input at each stage. Respondents involved in the study were 345 participants, with a ratio of 78 men and 287 women. The age range of the respondents was 17 years to 63 years. Respondents came from 19 provinces, which means 50 percent of the total number of new provinces in Indonesia. Based on the number of major islands in Indonesia, the respondents represented 4 out of 5 islands or 80%. Hence, the research results can be used to describe Indonesian people. The results show that each stage of development has task contradictions, loss of developmental tasks, addition of developmental tasks and mutual substitution at the previous and subsequent stages. The details at each stage are possible to be elaborated in further studies.

Kolmogorov–Arnold Network (KAN) is an emerging interpretable neural network compared to fully black-box MLPs. Recently, emerging works focus on comprehensive and fair comparisons between KAN and MLP in various tasks. However, these works didn't focus on the strongest advantage of KAN: generating symbolic outputs. The ability of KAN to provide scientific insights or even discover new science is under-examined. In this work, we propose several novel metrics to measure how well a KAN performs on symbolic function fitting: R^2-Mean, weighted R^2-complexity loss, and ranking metrics. We also propose a metric to determine mathematical complexity of a target function and evaluate KAN with several functions of different mathematical complexity. Additionally, we also tried inputs with different ranges to find the effect of normalization.

Background: Before the COVID-19 outbreak, food microbiology was crucial in identifying and preventing foodborne pathogens like Salmonella and E. coli. The pandemic underscored the importance of this discipline, highlighting the need for enhanced surveillance and microbiological control in the food chain to prevent future global public health threats. This research aimed to advance knowledge management in Bioeconomy, focusing on Eco-Intensification and biotechnology applications that directly affect food microbiology, especially in the context of the COVID-19 crisis. Methodology: The study involved a comprehensive literature review grounded in the epistemological principles of Bioeconomy, utilizing the Bibliometric Scopus database. This approach facilitated the exploration of the development of eco-intensification and biotechnology applications within food safety and nutrition microbiology. Results: The findings emphasize the importance of understanding the social and economic impacts of microbiological activities in food intake through a Bioeconomy lens. The research highlights the need for integrating microbiological insights into broader bioeconomic frameworks to address food safety and sustainability challenges effectively. Conclusion: Recommendations are provided for decision-makers to enhance public health agendas from a bioeconomic perspective. These recommendations aim to strengthen the focus on Bioeconomy and improve the management of interactions between food microbiology and the challenges exacerbated by the COVID-19 pandemic.

Background- Fertilizers are essential to enhancing food security by enhancing crop growth. The selection of chemical fertilizers over organic fertilizers brings environmental consequences. The government is trying to achieve food security and promote organic fertilizers over chemical fertilizers by implementing various programs. Aim- The study is carried out to understand the effect of government policies on farmers' chemical fertilizer consumption patterns. Design- The data of fifteen years of chemical fertilizer consumption was divided into three sub-groups. Statistical analysis was done to understand the trend of chemical fertilizer consumption of the farmers. Results- The analysis of data clearly shows the steadily increasing pattern of chemical fertilizer consumption. Conclusions- The study clearly shows there is no effect of sustainable agriculture policies framed by the government on the consumption of chemical fertilizers by farmers. Across the study period, farmers were inclined to use chemical fertilizers, related to a lack of awareness of the principles of appropriate fertilizer management that can limit environmental damage.

Veterinary science has benefitted from technological advancements in the past and will hopefully continue to do so, especially in the field of equine gait analysis. There is a need for rapid and easy to use technology that is accurate and portable, but at the same time is also readily interpretable. This manuscript presents two new approaches to equine gait analysis, both of which are commer-cial devices. The use of Acoustic MyoGraphy (AMG) has been proven in the field of muscle func-tion and performance as well as ligament health, but it can also provide details concerning gait when placed on the wall of the hoof of a horse. The TendibootTM system is a limb focused unit that can be easily attached, activated and used in a Veterinary clinic setting, rapidly providing gait details for equine diagnostic purposes. In conclusion this manuscript provides an insight into gait parameters from recent research trials that are novel and challenge current thinking.

Detecting small objects in images poses significant challenges due to their limited pixel representation and the difficulty in extracting sufficient features, often leading to missed or false detections. To address these challenges and enhance detection accuracy, this paper presents an improved small object detection algorithm, CRL-YOLOv5. The proposed approach integrates the CBAM attention mechanism into the C3 module of the backbone network, which enhances the localization accuracy of small objects. Additionally, the Receptive Field Block (RFB) module is introduced to expand the model's receptive field, thereby fully leveraging contextual information. Furthermore, the network architecture is restructured to include an additional detection layer specifically for small objects, allowing for deeper feature extraction from shallow layers. When tested on the VisDrone2019 small object dataset, CRL-YOLOv5 achieved an mAP50 of 39.2%, representing a 5.4% improvement over the original YOLOv5, effectively boosting the detection precision for small objects in images.

Background: Three-dimensional gait analysis plays a crucial role in the rehabilitation assessment of post-stroke hemiplegic patients. However, the data generated from such analysis is often complex and difficult to interpret in clinical practice, requiring extensive time and complicated procedures. The Gait Deviation Index (GDI) serves as a simplified metric for quantifying the severity of pathological gait. Although isokinetic dynamometry is widely employed in muscle function assessment and rehabilitation, its application in gait analysis remains underexplored. Objective: This study aims to investigate the use of isokinetic muscle strength data obtained from the Biodex system, combined with machine learning techniques, to predict the GDI in hemiplegic patients. Methods: A cohort of 150 post-stroke hemiplegic patients was evaluated. The peak torque, peak torque/body weight, maximum work of repeated actions, coefficient of variation, average power, total work, acceleration time, deceleration time, range of motion, and average peak torque for both flexor and extensor muscles on the affected side were measured at three angular velocities (60°/s, 90°/s, and 120°/s) using the Biodex System 4 Pro. GDI was calculated using data from a Vicon three-dimensional motion capture system. The study employed four machine learning models—Lasso regression, random forest (RF), support vector regression (SVR), and BP neural networks—to model and validate the data. Model performance was evaluated using mean squared error (MSE), the coefficient of determination (R²), and mean absolute error (MAE). SHapley Additive exPlanations (SHAP) analysis was used to enhance model interpretability. Results: The RF model outperformed others in predicting GDI, with an MSE of 16.18, an R² of 0.89, and an MAE of 2.99. In contrast, the Lasso regression model yielded an MSE of 22.29, an R² of 0.85, and an MAE of 3.71. The SVR model had an MSE of 31.58, an R² of 0.82, and an MAE of 7.68, while the BP neural network exhibited the poorest performance with an MSE of 50.38, an R² of 0.79, and an MAE of 9.59. SHAP analysis identified the maximum work of repeated actions of the extensor muscles at 60°/s and 120°/s as the most critical features for predicting GDI, underscoring the importance of muscle strength metrics at varying speeds in rehabilitation assessments. Conclusion: This study highlights the potential of machine learning techniques in analyzing complex clinical data. The developed GDI prediction model, based on isokinetic dynamometry data, offers a novel, streamlined, and effective tool for assessing rehabilitation progress in post-stroke hemiplegic patients, with promising implications for broader clinical application.

The aim of this work was to classify the business incubators in Spain according to the four phases of the startup’s incubation process. Considering that the graduation rate implies greater survival and business success of the incubated companies, they have been identified at each stage of the incubation (spread of entrepreneurship, pre-incubation, advanced incubation, and graduation). The activities that present higher impacts on the success of the incubated companies and the activities carried out by the business incubator that have a greater relevance on the graduation of the companies have concretely been considered. Principal component (PC) cluster analysis has been applied. All the incubation variables were used simultaneously, reducing their number, and grouping them into factors. Finally, the cases were grouped according to these latent variables. Principal components analysis reduced dimensionality to 8 factors with a 74 % of explained variance. Factor 1 was positively related to pre-incubation variables, factor 2 was linked to training and collaboration variables within the entrepreneurship diffusion phase. Factor 3, named activity monitoring and control, was related to phase 3 or basic incubation variables. Cluster analysis facilitates the grouping of business incubators into three clusters: Group 1 (16 % of the total), incubators with strong deficits in incubation phases 1, 2 and 3. They are small sized business incubators, often located in rural areas or cities and low graduation rate. Group 2 (30 %), business incubators with very high graduation rate, and strongly positive values in factors 1 and 2. Factor 3, although positive, it is susceptible to improvement. They are the largest group of business incubators and usually located in industrial and technological parks. Group 3 (54 %) is the majority, with values close to cluster 2 and 3.

The isotopic and nuclear techniques discussed, namely: Fallout Radionuclide, Fingerprint, and Isotope Hydrology, are linked to the evaluation of soil and water degradation processes. A traditional literature review was conducted to gain the most comprehensive understanding of both the current state of the art and the subject matter, with the aim of proposing a hypothesis that integrates the synergistic convergence of these techniques in order to offer results that are more reliable. A case study is presented as a synthesis of the preceding discussion.

Background: Over the past two decades, the Copenhagen Psychosocial Questionnaire (COPSOQ) has been established as a valid instrument to measure psychosocial stress at work. Currently, the COPSOQ international network is responsible for monitoring and improving COPSOQ. In 2019, a new questionnaire was published, and the Greek version is now being validated. Methods: The measurement qualities of the Greek COPSOQ III have been explored in accordance with the usual requirements of a validation study as defined by DIN EN ISO 10075-3. A sample of observations from 2,189 participants surveyed with the COPSOQ in Greece was used to validate the current version with appropriate statistical analyses. Exploratory factor analysis was used to assess the statistical relationships for many scales. Results: With its 108 items and 40 scales, the Greek COPSOQ III includes all psychosocial work factors that have been internationally validated and remain compatible with approximately 72% of the COPSOQ III German version content. In addition to the primary results, congruence with widely used theoretical approaches such as the demand-control (−support) model (DCM) or the job demands-resources model (JDR) is generally satisfactory. In summary, our validation study for the Greek COPSOQ III version showed adequate reliability and validity, which is in line with the findings of the COPSOQ III questionnaire from other European countries, and it is also compatible with the validation of the German COPSOQ III (Lincke, 2021). Our regression analysis revealed that 34 psychosocial work factors (34 “context” scales) could adequately predict the scores of the satisfactory and health scales (6 “outcome” scales). The analysis also revealed the top five (5) predictors (context variables) for each of the six (6) “effect” scales (outcome variables). Conclusions: With the launch of COPSOQ III in Greece, current and new workplace psychosocial aspects could be explored. COPSOQ III (GR) is a beneficial instrument for enterprise research and risk assessment.

Ti-Al based alloys, particularly TiAl and Ti3Al two-phase alloys, have garnered significant attention as potential replacements for various high-temperature structural materials due to their exceptional properties, including low density, oxidation resistance, and high strength at elevated temperatures. Despite these advantages, experimental studies on the microstructure evolution of Ti-Al based alloys under complex conditions remain challenging to observe and characterize. This review article examines the current research on molecular dynamics (MD) simulations of Ti-Al based alloys, focusing on two-phase Ti-Al alloys, Ti-Al amorphous alloys, Ti-Al composite materials, and the welding and multi-layer/film applications of Ti-Al alloys. The review highlights the unique capabilities of MD simulations in predicting the behavior of Ti-Al based alloys and addresses existing scientific challenges. Furthermore, the article discusses future research directions and development prospects in this field.

Microorganisms have colonized all barrier tissues and are present on the skin and all mucous membranes since birth. Bacteria have many ways of influencing the host organism: activation of innate immunity receptors by PAMPs; synthesis of various chemical compounds, such as vitamins, short-chain fatty acids, bacteriocins, toxins. Bacteria, using extracellular vesicles, can introduce high-molecular compounds, such as proteins and nucleic acids, into the cell, regulating the metabolic pathways of the host cells. Epithelial cells and immune cells recognize bacterial bioregulators and, depending on the microenvironment and context, determine the direction and intensity of the immune response. A large number of factors influence the maintenance of symbiotic microflora, the diversity of which protects host against pathogen colonization. Reduced bacterial diversity is associated with pathogen dominance and allergic diseases of the skin, gastrointestinal tract, upper and lower respiratory tract, as seen in atopic dermatitis, allergic rhinitis, chronic rhinosinusitis, food allergies, and asthma. Understanding the multifactorial influence of microflora on maintaining health and disease determines the effectiveness of therapy and disease prevention, changes our food preferences and lifestyle to maintain health and active longevity.

In 2018, Iran witnessed approximately 21,000 fatalities resulting from road accidents, ranking it as the fifth leading cause of death across all age groups. These incidents carry substantial economic and social burden for the nation, claiming more than 5% of its GDP. Human behavior emerges as a significant contributing factor to high-risk driving offenses. It has been proposed that by influencing general deterrence, a rigorous defense can be established against such violations. Various theories posit that by reinforcing or diminishing influential factors, general deterrence perception can be molded, presenting a potential avenue for an effective deterrent against traffic infractions. This study examines deterrence perceptions prevailing among the public in Iran regarding the enforcement of traffic laws. Employing Structural Equation Modeling (SEM), we delve into the intricate relationships between variables, allowing for a comprehensive exploration of the factors influencing general deterrence. The study draws on the data derived from a survey comprising 548 questionnaires for modeling purposes. An innovative concept, private sector enforcement, is introduced and incorporated into the questioning and modeling process. The findings reveal that socioeconomic status (p-value<0.01), police enforcement (p-value<0.05), private sector enforcement (p-value<0.05), specific deterrence (p-value<0.01), and the use of technology (p-value<0.01) have direct and indirect impacts on the general deterrence perception of drivers.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive impairment and memory loss. Oxidative stress (OS) has emerged as a central element in the pathophysiology of AD, linking various pathological features including amyloid-β (Aβ) plaque formation, tau hyperphosphorylation, and synaptic dysfunction. This review comprehensively examines the role of OS in AD, focusing on the mechanisms of reactive oxygen species (ROS) production, mitochondrial dysfunction, and their impact on neuronal integrity. Additionally, the review highlights recent advances in antioxidant therapy. Elevated ROS levels in the aging brain exacerbate oxidative damage to lipids, proteins, and DNA, contributing to neuronal atrophy and synaptic loss. Mitochondrial dysfunction further amplifies OS, disrupting cellular energy metabolism and promoting neurodegeneration. Despite the strong association between OS and AD, antioxidant therapies have shown inconsistent clinical outcomes. Emerging strategies targeting offer promising avenues for therapeutic intervention. This review highlights the need for a multifaceted approach in understanding and mitigating OS-related damage in AD, aiming to pave the way for more effective treatments and improved patient outcomes.

The bulk LiNa5Mo9O30 (LNM) crystals were successfully grown in the [010] and [001] directions without internal inclusions and cracks by the Czochralskii method with low temperature gradient. The crystal grown in the [010] direction showed a tendency to twinning. The crystal grown in the [001] direction demonstrated high structural perfection (FWHM=13'') for the (001) plane and high optical quality Δn≈210-5. The laser induced damage threshold was measured along a, b and c axes and was 15.7, 27.0 and 27.5 J/cm2 respectively. The thermo-optical coefficient dn/dT was measured for the main crystallographic axes, which was -5.7510-6, -2.0210-5 and 3.6510-6 K-1 along the a, b and c axes, respectively. The second harmonic generation (SHG) is conducted in crystalline LNM sample. The maximum efficiency value of 3.5% at pump power of 12 W had been achieved.

This study employs a bibliometric analysis of the emerging trends in the area of Money Laundering for Ter-rorism Financing to provide direction for future research in the area. The authors used VOSviewer and an-alysed 2577 published documents generated from the SCOPUS search using the PRISMA methodology. The findings reveal a growing research interest in this area, with a focus on understanding the complex inter-play between money laundering and terrorism financing. Emerging trends such as the use of cryptocurren-cies, trade-based money laundering, and the role of non-profit organizations in facilitating these activities are highlighted. The research contributes to the broader understanding of money laundering for terrorist financing by providing insights into the evolving research landscape and identifying areas for future re-search.

The current globally dominant SARS-CoV-2 variants are showing immune escape and reduced susceptibility to antiviral drugs. Therefore, agencies responsible for drug evaluation and regulation such as the FDA and EMA are revising their emergency authorization use of several COVID-19 neutralizing antibodies. These MAbs proved to be unlikely effective against new variants especially Omicron descendants and several pharmaceutical companies are pursuing the development of more potent neutralizing antibodies. To address this issue, we used In Silico method we previously developed to assess 10 anti-SARS-CoV-2 antibodies propensity to neutralize the new Omicron’s subvariants EG.5, BA.2.86 and JN.1, based on comparative binding affinity of 3D generated models and previous experimental and clinical observations. Nine of these MAbs were once granted emergency use authorization, and one is currently under clinical investigation. The results showed that one antibody showed a marked increase of the binding energy for EG.5 compared to two antibodies that showed a significant increase with Pirola (BA.2.86) and JN.1. This data indicates that the new SARS-CoV-2 variant escapes neutralization of most of the available therapeutic NAbs. Furthermore, the data showed new potential therapeutic MAbs combination that could be effective for the treatment countermeasure of the new Omicron’s descendants or potential novel variants.

IntroductionGlycogen synthase kinase 3 (GSK-3) has been associated with a lot of diseases, such as Alzheimer’s Disease and diabetes. Its role in depression is connected to stress and neuroinflammation. Lithium is an essential inhibitor of GSK-3. Some studies have suggested that the use of this psychiatric medication may lower suicide rates. Here, we outline the current understanding and discoveries regarding the link between GSK-3 and suicide. MethodWe used the PRISMA statement and defined the PECOS strategy, such as Population (P) = individuals; exposure (E) = GSK-3 alteration function; comparison (C) = without GSK-3 alteration function; outcome (O) = suicide; and study design(S) = all kinds of studies with an association between GSK-3 and suicide.ResultsTwelve studies were included in this review. GSK-3 appears to be related to suicidal behavior by activating inflammatory pathways, activating genes, altering neurotransmission, and increasing impulsivity. Clinical studies do not present robust results that allow defining an epidemiological profile of greater risk for suicidal behavior in association with changes in the functioning of GSK-3.ConclusionThe interference of GSK-3 functioning in suicidal behavior seems inevitable, with solid evidence from laboratory animal studies. However, there is a need for further clinical studies on this crucial topic to answer better some questions about the association between GSK-3 and suicide.

In this letter, we show that the effects usually attributed to the presence of dark matter in the Universe can equally be seen as the ”external” effect on our Universe due to extra dimensions. For this, we consider a braneworld scenario where our universe, which is a 3-brane, is immersed in a 6D Minkowski bulk. We derive the 1/r force on the 3-brane at large distances as a response of cosmic fluid to external force due to extra dimensions. This scaling reproduces the effect of dark matter, such as the flat rotation curves of galaxies and a higher deflection angle around some gravitational lenses. It also explains the large-scale structure formation of the universe. This approach thus offers a novel perspective on dark matter, suggesting that higher-dimensional physics can account for these cosmic phenomena.

The medicinal herb Centaurium erythraea is well-known for its natural ability to treat digestive issues like dyspepsia and liver insufficiency by promoting the secretions of the liver and esophagus. This study aimed to analyze the effectiveness of Centaurium erythraea extracts in treating diabetes. Decoction and Soxhlet procedures were used to examine the extracts, with water serving as the solvent. The extracts were tested for antioxidant capacity, antimicrobial effects, and inhibitory effects on alpha-amylase activity. In comparison to the aqueous extract, the decocted extract had higher levels of polyphenols, total tannins, and anthocyanins, as well as more effective antioxidant capacities. Due to its reduction of alpha-amylase activity and enteric absorption of glucose, Centaurium erythraea has also shown considerable anti-hyperglycemic action.

The measurement of the grounding resistance of protection grids in large installations as well as grounding electrodes in urban areas is addressed in this article. The resistance value is obtained using a three-pin array by measuring the fall-of-potential on the ground surface. The resistance measured by this method is corrected using the so-called correction factor that adjusts the measured resistance value to its real value. The proposed measurement method obtains correct values of the grounding resistance even when the auxiliary and potential electrodes of the tree-pin array are close to the electrode to be measured. Thus, it can be applied to large electrodes as well as electrodes in urban areas. Several simulated examples are used to illustrate the method, and some real cases with field measurements are presented for a final validation of the method.

The rapid urbanization process in recent decades has altered the carbon cycle and exacerbated the impact of climate change, prompting many cities to develop tree planting and green area preservation as mitigation and adaptation measures. While numerous studies have estimated the carbon stocks of urban trees in temperate and subtropical cities, data from tropical regions, including tropical botanic gardens, are scarce. This study aimed to quantify the aboveground biomass and carbon (AGB and AGC, respectively) stocks in trees at the Rio de Janeiro Botanical Garden arboretum, Rio de Janeiro, Brazil. Our survey included 6793 stems with a diameter at breast height (DBH) ≥ 10 cm. The total AGB was 8,047.24 Mg, representing 4,023.62 Mg of AGC. The AGB density was 207.4 Mg.ha-1 (AGC = 103.7 Mg.ha-1), which is slightly lower than the density stored in Brazil's main forest complexes: the Atlantic and Amazon forests, but much higher than in many cities worldwide. Our results suggest that, in addition to their global importance for plant conservation, tropical botanic gardens could function as significant carbon sinks within the urban matrix.

Background: The relationship between the intake of artificial sweetener (AS) and adverse pregnancy outcomes is under-researched, and existing studies yield inconsistent conclusions. Methods/Objectives: A mendelian randomization (MR) approach was employed to investigate the causal relationship between the intake of AS and adverse pregnancy outcomes. Instrumental variables related to the exposure phenotype were selected for analysis. The analysis was conducted using genome-wide association studies summary data from public datasets. Inverse variance weighted, MR-Egger, weighted median, simple mode, and weighted mode were used to evaluate the causal relationship between exposure and outcomes. Sensitivity analysis and multivariable mendelian randomization enrolling body mass index, type 2 diabetes mellitus and fasting glucose was employed to further validate the consistency and robustness of results. Results: The intake of AS added to tea was associated with an increased risk of ectopic pregnancy [OR=1.821 (1.118 - 2.967), p=0.016] in univariable MR. The intake of AS added to cereal was linked to a reduced risk of ectopic pregnancy [OR=0.361 (0.145 - 0.895), p=0.028] and premature rupture of membranes [OR=0.116 (0.019 - 0.704), p=0.019], while the intake of artificial sweetener added to coffee was associated with an increased risk of placenta previa [OR=1.617 (1.042 - 2.510), p=0.032] adjusting for body mass index and type 2 diabetes mellitus in multivariable MR. No causal relationship was identified between the intake of artificial sweetener and the other adverse pregnancy outcomes. Conclusions: The consumption of artificial sweeteners during pregnancy warrants careful consideration.

Let's define $\delta(x) = (\sum_{{q\leq x}}{\frac{1}{q}}-\log \log x-B)$, where $B \approx 0.2614972128$ is the Meissel-Mertens constant. The Robin theorem states that $\delta(x)$ changes sign infinitely often. Let's also define $S(x) = \theta(x) - x$, where $\theta(x)$ is the Chebyshev function. It is known that $S(x)$ changes sign infinitely often. We define the another function $\varpi(x) = \left(\sum_{{q\leq x}}{\frac{1}{q}}-\log \log \theta(x)-B \right)$. We prove that when the inequality $\varpi(x) \leq 0$ is satisfied for some number $x \geq 3$, then the Riemann hypothesis should be false. The Riemann hypothesis is also false when the inequalities $\delta(x) \leq 0$ and $S(x)\geq 0$ are satisfied for some number $x \geq 3$ or when $\frac{3 \times \log x + 5}{8 \times \pi \times \sqrt{x} + 1.2 \times \log x + 2} + \frac{\log x}{\log \theta(x)} \leq 1$ is satisfied for some number $x \geq 13.1$.

In some clinical applications pulsating currents are delivered into a body region for therapeutic purposes. In this paper we analyze the generated thermal field with the aim of determining the amplitude, period and duration of those stimuli, guaranteeing that the temperature of the interested tissue stays below the necrosis threshold.

Imbalanced classes can cause machine learning models to classify positive class instances poorly, and the models require hyperparameter sets to optimal values. This study aims to develop random forest (RF) and support vector machine (SVM) models that use the optimal hyperparameters obtained through 5-fold cross-validation data. Both models were trained using optimal hyperparameter pairs that fit two data scenarios, the original and oversampling training sets, to produce the benchmark and best models. The model's performance was evaluated using six metrics, including training and testing data. The acquired optimal RF hyperparameter pair was (500, 10) for the minimum number of instances and tree depth level. In contrast, the acquired optimal SVM hyperparameter pair was (0.001, 500) for the gamma and constant values. The benchmark model performed approximately 98% on Accuracy, Precision, Recall, and F1 score metrics but failed to deliver any performance on Mathew's Correlation Coefficient (MC) and Area under Curve (AUC) metrics. The best RF and SVM perform less than both benchmark models in four famous metrics. Both best models have performance improvements of approximately 6% and 11% for the MCC and AUC metrics, respectively. The best RF performance was slightly better than the best SVM performance.

Objective: This analysis investigates patient experiences regarding pain management during gynecological procedures through a comprehensive survey, aiming to address the lack of clear guidelines in the clinical landscape and emphasize the importance of effective pain management strategies in enhancing patient care and satisfaction. Design: A cross-sectional survey with 258 respondents assessed pain management experiences during gynecological procedures. The survey was distributed via Qualtrics, and 258 responses were obtained. Participants/Materials, Setting, Methods: Participants provided demographic information and responded to questions regarding contraceptive methods, procedures undergone, pain management discussions, anxiety levels, and willingness to accept pain management interventions. Confidentiality and informed consent protocols were strictly observed throughout the study. Results: Most female respondents reported diverse contraceptive methods and procedures. Pain management discussions and provisions varied, with a significant portion reporting never being offered pain management. Many experienced anxiety and pain during procedures, with varying intensities, that were not addressed or discussed by their treating provider. Most expressed willingness to accept pain management interventions. Limitations: This study relies on self-reported data, potentially introducing recall bias, and has limited generalizability due to its cross-sectional design. Conclusions: Findings reveal a significant gap in pain management provision and discussion during gynecological procedures. Improved guidelines and practices are necessary to address patient discomfort effectively. Standardized pain management protocols are crucial to enhance patient experiences and outcomes, with further research needed to tailor strategies to individual patient needs.

Sodium valproate is a established antiepileptic drug of first choice, primarily used to treat epilepsy, but also bipolar disorder and prevent migraine headaches. Valproate increases concentrations of gamma-aminobutyric acid in the brain, due to inhibition of enzymes responsible for the catabolism of gamma-aminobutyric acid. Main goal of this research consisted in the optimization and development for a new sensitive spectrophotometric quantitative analysis method of sodium valproate from tablets in the Visible field. Following the quantitative color reaction of sodium valproate with diazonium salt of alpha naphthylamine in alkaline medium, a light yellow azo dye was formed and spectrophotometrically analyzed at the wavelength of 386 nanometers. The amount of pure sodium valproate found on pharmaceutical extended-release tablet was 492.578 miligrams compared to the official declared pure amount of 500 miligrams on prolonged-release tablet. Amount found was assigned to a percentage content of 98.5156 percent pure sodium valproate in a pharmaceutical tablet. Mean average percentage error (deviation) from the officially stated value was about 1.4844 percent, which was included within normal limits, below five percent maximum limit allowed by European and Romanian Pharmacopoeias rules. Spectrophotometric method was subjected to the statistical validation procedure and was successfully validated.

This study presents a mixed review of research on the competencies of built environment professionals in infrastructure delivery within emerging economies. By integrating bibliometric analysis with a systematic review, the research offers a comprehensive understanding of key themes, trends, and debates in the field. The review process culminated in the selection of 59 publications, which were analyzed to identify critical topics including embedding emerging skills in built environment competencies, competency-based curriculum, technology infrastructure and assessment, municipal competency training, and the role of the Fourth Industrial Revolution (4IR). The findings underscore the importance of evolving educational frameworks to meet the demands of globalization, integrating advanced technologies, and fostering industry-academic collaborations to enhance the skills of professionals in the built environment sector. This approach ensures a robust examination of the competencies necessary for effective infrastructure delivery in emerging economies.

Traditional Chinese medicine requires decoction and consumption, which is time-consuming and labor-intensive. Scientific Chinese medicine (SCM), on the other hand, uses concentrated granules that can be taken with hot water, making it widely welcomed. With the widespread adoption of SCM, the packaging technology has started to receive attention. Whether it is manpower allocation, operation time, or the uniformity and residue of the medicine powder, these factors can become bottlenecks in the process. A traditional SCM pharmacy machine is purely mechanically hardwired. This paper proposes SCMtalk, an Internet of Things (IoT)-based SCM mechanism designed to enhance the efficiency and accuracy of SCM medicine packets generation. We show how SCMtalk develops IoT hardware and software modules for medicine selection, mixing, dispensing, packaging, and cleaning. We also explain how the mechanical IoT hardware is integrated with the corresponding software module to become an individual IoT device. These IoT devices can be transparently replaced, allowing us to easily upgrade the individual components of the SCM packet generation through the IoT concept. Finally, we address quality control issues by leveraging IoT. One contribution of this paper is to introduce an interesting SCM application to IoT experts and to demonstrate how we collaborated with pharmacists and mechanical experts to use a powerful IoT platform to create a smart pharmacy.

The increasing rearrangement is a rewarding instrument in financial risk management. In practice, risk must be managed in different perspectives. A common example is portfolio risk which often can be seen from at least two perspectives: market value and book value. Different perspectives that is different distributions can be coupled by increasing rearrangement. One distribution is regarded as underlying, and the other distribution can be expressed as increasing rearrangement of the underlying distribution. Then, the risk measure for the latter can be expressed in terms of the underlying distribution. Our first objective is to introduce the increasing rearrangement for application in financial risk management and apply the increasing rearrangement to the class of distortion risk measures. We derive formulas to compute risk measures in terms of the underlying distribution. Afterwards, we apply our results to a series of special distortion risk measures, namely Value at Risk, Expected Shortfall, Range Value at Risk, Conditional Value at Risk, Wang's risk measure. Finally, we present the connection of increasing rearrangement to inverse transform sampling, Monte Carlo simulation, and cost-efficient strategies. Butterfly options serve as illustrative example for the method.

Rift Valley fever (RVF) is a mosquito-borne zoonotic viral disease that infects both human and animals. This is a descriptive study summarizes investigation and response to RVF outbreak, using surveillance data. A RVF outbreak occurred in Berber locality in northern Sudan. We identified 246 cases of RVF including seven deaths among humans, 119 deaths and 82 abortions among Livestock. Our entomological surveillance confirmed the presence of Anopheles arabiensis, An. stephensi, Aedes aegypti, Ae. vexans, Culex pipiens, Cx. Quinquefasciatus, and Cx. theileri in the area during the outbreak. In a comparison with another outbreak of Rift Valley fever in nearby area while ago, a multisectoral One Health response strategy has resulted in strengthening the health system through re-innovating health facilities and centres and training about 200 healthcare and emergency responders. Additionally, it reduced cases and fatalities among humans by 78% and 63%, respectively, and loss in livestock due to deaths and/or abortions by 82%. The added-value of implementing One Health strategy was saving more lives and resources, while strengthening the health system. We recommend the systematic institutionalization of One Health strategy in the country as a core part of the national prevention and control strategy for zoonotic diseases epidemics and pandemics.

Recently, the destructive impact of wildfires has proliferated; for instance, the August Complex wildfire in 2020 burned around 4% of California's landmass. This has caused increased economic damage and risk to human life. Additionally, climate change is anticipated to increase the severity of wildfires, making it imperative for accurate and efficient detection of wildfires. Machine Learning approaches allow for the automatic detection of wildfires, simultaneously prioritizing accuracy and efficiency, with minimal human intervention, thus decreasing the likelihood of increased economic damage and increasing firefighting responses. Convolutional Neural Networks (CNNs), while showing promise, are often limited by their inability to learn and capture deep spatial dependencies in satellite imagery tasks. In this paper, we propose FlameViT, a novel wildfire detection architecture based on Vision Transformers (ViT). Satellite images are more efficient to obtain and can cover wide areas prone to wildfires. We obtain a dataset of 40K+ satellite images from Canada's Open Government Portal, allowing FlameViT to be optimized to detect wildfires in satellite imagery. FlameViT uses Patch Extractor and Patch Embedding layers, followed by multiple Transformer Encoder layers with Multi-Head Self-Attention and feed-forward neural networks. FlameViT is hyperparameter-tuned and achieves a validation accuracy of 95%, outperforming various baselines in the wildfire detection task. FlameViT shows the power of Vision Transformers for wildfire detection tasks, and in conjunction with the use of satellite imagery, can provide an efficient and accurate way of detecting wildfires.

Venous and arterial thromboembolism (VTE/ATE) often coexist with onco-hematologic diagnosis. The study aimed to assess the time relationship between the diagnosis of VTE/ATE and blood cancers. The second aim was to identify VTE/ATE risk factors related to the type of hematology disease and cardiac history. 1283 patients underwent cardio-oncology evaluation at the Institute of Hematology and Transfusion Medicine in Warsaw from March 2021 through March 2023 (2 years), and 101 (7.8%) cases were identified with VTE/ATE. ATE compared to VTE significantly more often occurred before the diagnosis and treatment of hematologic malignancy: 33/47 (70.2%) vs. 15/54 (27.8%), p<0.0001. The risk of a VTE episode is exceptionally high in the first months after the diagnosis of an onco-hematological disease. The higher frequency of VTE was associated with acute myeloid leukemia (17 cases/270 patients/6.30%/p = 0.055), acute lymphocytic leukemia (7 cases/76 patients/9.21%/p = 0.025) and chronic myeloproliferative disease (7 cases/48 patients/14.58%/p=0.0003). Only the risk of VTE was significantly increased before (OR=6.79; 95%CI: 1.85-24.95; p=0.004) and after diagnosis of myeloproliferative disease (OR=3.12; 95%CI: 1.06-9.16; p=0.04). ATEs occur more often than VTE before a diagnosis of blood cancer. The risk of VTE is exceptionally high before and after diagnosis of chronic myeloproliferative disease.

Euler's theorem about the relationship between the numbers of individual elements of planar graphs (vertices, edges, faces) is also satisfied when the graph has zero vertices. The problem of the existence or not of such graphs has so far been the subject of very few studies. Plus, research that didn't prove anything. The paper presents an interpretation of this kind of graphs as mathematical formations lying on piecewise smooth surfaces. The lines of intersection of two or more smooth surfaces (faces of a graph) form edges without a vertex of the graph. The elementary properties of such graphs are discussed, the method of counting non-isomorphic 0-vertex graphs and their importance in physics and chemistry are given.

There is an observed general low performance of Ethiopian Sport Governing Bodies (SGBs) in service delivery. Evidence shows that the trend can be corrected with proper understanding and insight into the process of organisational and management factors of these SGBs. This study aimed to investigate the contribution of organisational and management factors on effective sport service delivery in SGBs. For this study, a cross-sectional research design was employed. Purposive sampling was used to choose 350 samples. Pearson Product Moment Correlation Coefficient and multiple regression were used to analyse the data at the 0.05 significant level. The findings confirmed that organisational and management factor variables had a significant positive relationship with sport service delivery (organisational structure (r=0.515), organisational capabilities (r=0.701), communication (r=0.549), management practice (r=0.571), materials &amp; resources (r=0.527) and stakeholders satisfaction (r=0.742). In addition, Management factors were found to be significant contributors for predicting effective sport service delivery (F(3, 329)= 165.868, R2= 0.612). Furthermore, organisational factors had a joint significant contribution to effective sport service delivery (F(3, 329) = 148.743, R2= 0.576). In addition, organisational and management factor variables jointly best predicted effective sport service delivery in Ethiopian SGBs (F(6, 326) =130.81, R2= 0.707). Therefore, this study suggests organisational and management factor variables can be used to predict effective sport service delivery.

Facing global warming consequences is a major issue of present times. For what concerns climate, projections say that heavy rainfalls are going to increase with high probability together with temperature rise, thus also the hazard related to rainfall induced shallow landslides will likely increase in density over susceptible territories. Different modeling approaches exist and any of them is forced to make simplifications in order to reproduce landslide occurrences over space and time. Process based models can help in quantifying the consequences of heavy rainfall on the different involved processes. In this paper, a narrative review about physically-based deterministic distributed models (PBDDMs) is presented. Models were selected based on: the adoption of the infinite slope scheme (ISS), the use of a deterministic approach (i.e., input and output are treated as absolute values), the inclusion of new approaches in modeling slope stability through the ISS. Models are presented in chronological order with the aim of drawing a timeline of the evolution of PBDDMs and to give researchers and practitioners a basic knowledge on how much has been already done. Results indicate that including vegetation effects on slope stability has raised in importance over time but that there is still the need of finding an efficient way to include them, and that in the last years the literature production seems to be more focused on probabilistic approaches.

Background/Objectives: Survival prospects following SARS-CoV-2 infection may extend beyond the acute phase, influenced by various factors including age, health conditions, and infection se-verity. However, this topic has not been studied in detail. We therefore investigated mortality risk post-acute COVID-19 in the CRIT-COV-U cohort. Methods: We could retrieve survival data from 651 patients and also assess the association between urinary peptides and future death. Data spanning until December 2023 were collected from six countries, comparing mortality trends with age- and sex-matched non-infected controls. A death prediction classifier was developed and validated using pre-existing urinary peptidomics datasets. Results: Notably, 13.98% of post-COVID-19 patients succumbed during the follow-up, with mortality rates significantly higher than non-infected controls, particularly evident in younger individuals (&lt;65 years). These data for the first time demonstrate that SARS-CoV-2 infection highly significantly increases the risk of mortality not only during the acute phase of the disease, but also beyond, for a period of about one year. In our study we were further able to identify 201 Urinary peptides linked to mortality, and integrated these into a predictive classifier (DP201). Higher DP201 scores, alongside age and BMI, significantly predicted death. Conclusions: Our findings underscore the utility of urinary peptides in prognosticating post-acute COVID-19 mortality, offering insights for targeted interventions. Our data also suggest that mortality should be considered as one possible symptom or conse-quence of post-acute sequelae of SARS-CoV-2 infection, a fact that is currently overlooked.

This study aimed to characterize the physicochemical properties of broiler poultry litter (BPL) produced from intensively reared commercial broiler farming areas in tropical zone of Tamil Nadu, India. The BPL samples were collected from 110 commercial poultry farms at the end of the production cycle (6th week), further 20 samples were collected from the point of utility. The dry matter (DM), moisture, ash, organic matter (OM), and organic carbon (OC) from the manure samples were 83.04 ± 0.77, 16.96 ± 0.77, 27.08 ± 1.18, 72.92 ± 1.18 and 42.39 ± 0.69 per cent respectively. The pH, Electrical conductivity (EC) (ds m-1), and Kjeldahl Nitrogen (N) were 8.43 ± 0.06, 5.74 ± 0.13, and 24.2 ± 0.84 g kg-1 respectively. The BPL from the cement floor had higher levels of P and K (12.74 and 13.28 ) than the mud floor (10.88 and 10.96). According to the findings of this study, BPL as such at the end of the production cycle is rich in OM, nitrogen, macro and micro minerals at the same time at the point of utility there was a loss of OM, N, and concentration of minerals was noticed, which advocate proper storage and composting process.

Many definitions of cancer have been proposed over the years to explain cancer’s origins and pathophysiology, but the disease is too variable to allow any single description to completely encompass all of the myriad traits. A true, unifying theory of cancer must not only reveal how all known carcinogens contribute toward malignancy, but must also elucidate why cancers occur predominately in older patients, why they express so many similar behaviors, as well as account for each cancer’s individual variations. A conceptual reorganization of decades of cancer data may reveal the fundamental process that underlies the malignant transformation of cells, which not only provides a new understanding of the etiology of cancers, but also helps to interpret the subsequent events that occur after transformation, which is of significant clinical interest. The revised concepts of initiation, promotion, and progression suggest that cancer is a failed or incomplete attempt at regeneration that occurs when ordinary cellular events unintentionally coincide over time to force the use of a DNA repair pathway that is normally restricted for use in germ cells.

This paper proposes causal economic machine learning (CEML) as a research agenda that utilizes causal machine learning (CML) built on causal economics (CE) decision theory. Causal economics is better suited for use in machine learning optimization than expected utility theory (EUT) and behavioral economics (BE) based on its central feature of causal coupling (CC), which models decisions as requiring upfront costs, some certain and some uncertain, in anticipation of future, uncertain causally-linked benefits. This multi-period, causal-linked process incorporating certainty and uncertainty replaces the single period lottery outcomes augmented with intertemporal discounting used in EUT and BE, providing a more realistic framework for AI machine learning modelling and real world application. It is mathematically demonstrated that EUT and BE are constrained versions of CE. Causal coupling can also be applied at the macroeconomic level to gauge the effectiveness of policies that deliver various levels of cost and benefit coupling for individuals. With the growing interest in natural experiments in statistics and CML across many fields, such as healthcare, economics and business, there is a large potential opportunity to run AI models on CE foundations and compare results to models based on traditional decision making models that focus only on rationality, bounded to various degrees.

In this proposed work, five systems were developed to classify four motor functions—forward hand movement (FW), grasp (GP), release (RL), and reverse hand movement (RV)—from EEG signals. The dataset used is WAY-EEG-GAL, involving participants performing a sequence of hand movements. During preprocessing, bandpass filtering was applied to remove artifacts and focus on the mu and beta frequency bands. The first system, a preliminary study model, explored the overall framework of EEG signal processing and classification. It utilized time-domain features like variance and frequency-domain features like alpha and beta power, with classification performed using a KNN model. Insights from this system informed the development of a baseline system, which uses the same dataset but different feature extraction and classification paradigms. This baseline system combined the common spatial patterns (CSP) method with continuous wavelet transform (CWT) for feature extraction and employed a GoogLeNet classifier with transfer learning. Classification was performed on six unique pairs of events derived from the four motor functions, using both intrasubject and intersubject methods. The baseline system achieved the highest accuracy of 99.73% for the GP-RV pair and the lowest accuracy of 80.87% for the FW-GP pair in intersubject classification. Building on this, three additional systems were developed to perform 4-way classification. Among these, the final model, ML-CSP-OVR, achieved the highest intersubject classification accuracy of 78.08% using all combined data and 76.39% for leave-one-out intersubject classification. This proposed model, which features a novel combination of CSP-OVR, CWT, and GoogLeNet, demonstrates strong potential as a general system for motor imagery (MI) tasks without being subject-dependent.

Despite the lack of evidence that suggests hemodiafiltration (HDF) offers a better survival outcome than standard hemodialysis (HD), the number of patients initiating HDF in Japan continues to rise. This study examined the temporal change in the number of HDF incidents, evaluated factors associated with all-cause mortality, and compared the mortality risk and survival time of patient on HDF with patients receiving standard HD in three sets of 2-year cohorts. The primary analyses included the insurance claims data of 460 HDF patients and propensity score-matched 903 standard HD patients who initiated dialysis therapy between April 1, 2012 and March 31, 2018. Patient follow-up was censored at the time of death or the end of the 2-year study period. The influence of comorbidities on all-cause mortality was investigated, and the survival outcomes between HDF and standard HD patient groups throughout cohorts were compared. The number of HDF patients was increasing throughout cohorts, but the proportions of mortality cases across cohorts slowly decreased. Dementia status increases the mortality risk of patients regardless of dialysis modality. The mortality risk among HDF patients with dementia was more significant than HD patients. Adjusting for all covariates, we observed that HDF patients had a reduced mortality risk and longer survival time than patients on standard HD. This study supports the notion that HDF reduces all-cause mortality compared with standard HD in an incident dialysis population in Fukuoka Prefecture, Japan.

The aim of this study was to investigate the differentially expressed genes associated with intramuscular fat deposition in the longissimus dorsi muscle of Xinjiang Brown Bulls. The longissimus dorsi muscles of 42 Xinjiang Brown Bulls were selected under the same feeding conditions. The intramuscular fat content of muscle samples were determined by Soxhlet extraction method, from which 5 samples with high intramuscular fat content (HIMF group) and 5 samples with low intramuscular fat content (LIMF group) were selected. It was found that the intramuscular fat content of HIMF group was 46.054% higher than that of LIMF group. Muscle samples produced by paraffin section for morphological observation. It was found that the fat richness of the HIMF group was better than that of the LIMF group. Transcriptome sequencing technology was used to analyze the gene expression differences of longissimus dorsi muscle. Through in-depth analysis of the longissimus dorsi muscle by transcriptome sequencing technology, we screened a total of 165 differentially expressed genes. The results of Gene Ontology (GO) enrichment analysis showed that the differentially expressed genes in the two groups were mainly clustered in biological pathways related to carbohydrate metabolic processes, redox processes and oxidoreductase activities. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that the differentially expressed genes were significantly clustered in 15 metabolic pathways, which mainly covered fatty acid metabolism (related to lipid metabolism and glucose metabolism), pentose phosphate pathway, Peroxisome Proliferator-Activated Receptors (PPAR) signalling pathway and other important metabolic processes. The three genes that were predominantly enriched in the glycolipid metabolic pathway by analysis were SCD5, CPT1C, and FBP2, all of which directly or indirectly affect intramuscular fat deposition. In summary, the present study investigated the differences in gene expression between high and low intramuscular fat content in the longissimus dorsi muscle of Xinjiang Brown Bulls by transcriptome sequencing technology, and revealed the related signalling pathways. Therefore, we hypothesized that SCD5, CPT1C, and FBP2 were the key genes responsible for the significant differences in intramuscular fat content of the longissimus dorsi muscles in a population of Xinjiang Brown Bulls. We expect that these findings will provide fundamental support for subsequent studies exploring key genes affecting fat deposition characteristics in Xinjiang Brown Bulls.

Nanocomposites prepared with a terpolymer of poly(L-lactide) (PLLA)–poly(-caprolactone) (PCL)–poly(ethylene glycol) (PEG) and partially oxidized carbon nanotubes (CNTspo) were synthesized and characterized to evaluate their ability to act as an effective nanocarrier of the anticancer drug methotrexate. The homopolymers of PLLA and PCL were synthesized through ring-opening polymerization (ROP) and characterized through gel permeation chromatography (GPC). The PLLA–PCL–PEG terpolymers were synthesized through a four-step chemical route using oxalyl chloride as a linker agent and analyzed through 1H-NMR, 13C-NMR, and FT-IR spectroscopies. Also, the nanocomposites were characterized through FT-IR, 1H-NMR, and X-ray photoelectron spectroscopy (XPS) spectroscopies and, using the differential scanning calorimetry (DSC) technique. XPS analysis revealed that CNTspo is grafted to PLLA–PCL–PEG terpolymer. Besides, evaluation through FT-IR and DSC strongly suggests that the CNTspo are preferentially oriented to the PCL-rich domains. The release tests exhibited a “burst effect” profile, which was more evident in the terpolymers than in the nanocomposites. Five models were used to assess the methotrexate in vitro release. For the nanocomposites, the best fit to the experimental data was obtained using the first-order model, whereas the results obtained from the Korsmeyer–Peppas model indicated that a Fickian diffusion drives the methotrexate release.

Recently, oriented external electric fields (OEEFs) have earned much attention due to the possibility of tuning the properties of electronic systems. From a theoretical perspective, one can resort to electronic structure calculations to understand how the direction and strength of OEEFs affect the properties of electronic systems. However, for multi-reference (MR) systems, calculations employing the popular Kohn-Sham density functional theory with the traditional semilocal and hybrid exchange-correlation energy functionals can yield erroneous results. Owing to its decent compromise between accuracy and efficiency for MR systems at the nanoscale (i.e., MR nanosystems), in this study, thermally-assisted-occupation density functional theory (TAO-DFT) is adopted to explore the electronic properties of n-acenes (n = 2--10), containing n linearly fused benzene rings, in OEEFs, where the OEEFs of various electric field strengths are applied along the long axes of n-acenes. According to our TAO-DFT calculations, the ground states of n-acenes in OEEFs are singlets for all the cases examined. The effect of OEEFs is shown to be significant on the vertical ionization potentials and vertical electron affinities of ground-state n-acenes with odd-number fused benzene rings. Moreover, the MR character of ground-state n-acenes in OEEFs increases with the increase of the acene length and/or the electric field strength.

Cadmium (Cd) contaminated soil is a serious environmental problem due to its effect on crop production, soil microbial community, and risk to human health. The commercial amendments are widely used in the immobilization of heavy metal-contaminated soil because of their cost-effectiveness, eco-friendliness, and community acceptance. This study is conducted to assess the effect of sole commercial amendments including bentonite (B), talc (T), activated carbon (AC), cornstarch (CS), and their combination on exchangeable Cd content in soil, Cd uptake by the plant, and soil microbial community. The results indicated that CS and its composites (T+CS and B+CS) showed the highest effect on reducing Cd mobility in soil (up to 10% in CS), decreasing the Cd uptake by lettuce (up to 78% in T+CS), and increasing the microbial community in soil compared to the control. Furthermore, results from Biolog Ecoplate and realtime-Polymerase chain reaction indicated that the mixture amendments (B+CS and T+CS) showed the highest effect on the microbial community by increasing soil microbial population maximum of 3.81-fold difference (in B+CS) compared to the control. The results indicated that applying composite amendments provided an efficient option for immobilizing Cd in soil, reducing the Cd uptake by plants, and increasing microbial community.

This paper presents an interpretable support vector machine (SVM) and its application to rehabilitation assessment. We introduce the concept of nearest boundary point to standardize the one-class SVM decision function and determine the shortest path for data from abnormal cases to become those from normal cases. This analytical approach is computationally simple and provides a unique solution. The nearest boundary point of abnormal data can also be used to analyze the cause of abnormal classification and indicate countermeasures for normalization. These properties render the proposed interpretable SVM valuable for medical assessment applications and other problems that require careful consideration of classification results for treatment. Simulation and application results demonstrate the feasibility and effectiveness of the proposed method.

Deep convolutional neural networks (CNNs) have revolutionised computer vision technology by automatically learning hierarchical representations of image data, leading to state-of-the-art performance in visual recognition tasks. This article presents a comprehensive review of deep CNNs, from their evolution and architectures to the current state-of-the-art research. The review also provides the core concepts and building blocks of CNNs and their concise mathematical representations. Furthermore, it explores applications of deep CNNs in three popular domains, including medical diagnosis, remote sensing, and facial recognition. This review will benefit researchers and practitioners in computer vision and artificial intelligence, as well as industry professionals seeking to leverage the latest advancements in deep learning technologies.

In this letter, we construct an effective field theory of gravity at large distances. We obtain to the leading order for large distances: a cosmological constant term and a logarithmic term in addition to the usual General Relativistic terms. The novel logarithmic term has important implications in explaining phenomena such as flat galactic rotation curves and stronger gravitational lensing than predicted that are generally attributed to the presence of dark matter.

Lung cancer remains the most common cancer worldwide with a limited prognosis despite personalized treatment regimens. Low-dose computed tomography (CT) scanning as a means to early diagnosis has been disappointing due to the high false positive rate. Other non-invasive means of testing need to be developed that offer both timely diagnosis and predict prognosis. Methods: In the course of stool testing in a large-scale testing of 2,922 patients at increased risk of CRC we were able to ascertain 112 patients documented to have prospectively been diagnosed with lung cancer. Stool and colonic effluents were tested for p87 with anti-adenoma antibody (Adnab-9) reactivity by ELISA and western blot. Survival data were obtained where available. Results: Of 112 cancers, approximately 27.6% were squamous (SSC), 17.9% were adenocarcinoma, 8% small, 6.25% large cell and 3.57% were designated non-small cell cancer (NSCLC), 0.89% indeterminate, 0.89% lepidic spread (1), 3.57% had metastasis and in 31.25% data was unavailable. 49.1% of the lung cancer patients had fecal Adnab-9 testing. Overall, 60% had positive testing compared to 38%, which was significant (OR2.19[1/06-4.53];p=0.045). Cancers with higher lethality were less likely to test positive (approximately, 8.5% each for both small and large cell lung cancers), and higher, 56% with SCC and 25% for adenocarcinoma. 0% NSCLC). In the larger groups overall survival was worse in those testing positive: 474 testing positive versus 844 days in SCC and 54 testing positive versus 749 days in adenocarcinoma patients. Most importantly, the time from a positive test to the clinical diagnosis ranged from 2.72 years for small cell, 3.13 for adenocarcinoma, 5.07 for NSCLC, 6.07 for SSC, and 6.24 for large cell cancer. In excluded cases where cancer in the lung was believed to be metastatic,83.3% of cancers were positive. Conclusions: At a projected real-world sensitivity of 0.60 and specificity of 0.60 and the ability to predate diagnosis by up to 4.7 years overall, this test could help direct lung cancer screening. In addition, the Adnab-9 testing selectively detects worse tumor types (87.5%) and those with worse prognosis amongst the more common, favorable phenotypes thus making early diagnosis possible in those patients who stand to benefit most from this strategy. Metastatic lung cancer also detected by the test should be identified by the follow-up imaging studies and therefore would not be considered to be a major pitfall.

The study of supermassive black holes has significantly advanced our understanding of galaxy structures, yet fundamental questions remain, particularly concerning the structure and dynamics of massive black holes. This article addresses the core structure of massive black holes, defined as those originating from supernova events. Integrating the concept of "Dachus density," a state of maximum matter density, I propose that the core of all massive black holes exists at this density. The research investigates the size of these cores and their event horizons, using Cygnus X-1 and Sagittarius A* as examples. Calculations reveal that the core size is exceedingly small compared to the overall black hole, with the core's volume being up to ~155 orders of magnitude smaller than the event horizon volume in the case of Sagittarius A*. The article briefly explores the implications of a rotating Dachus core on the black hole's structure, including the "mantle" region between the core and the event horizon. The discussion extends to absolute zero temperature, asserting that for a non-spinning, static Massive black hole, the temperature of its core reaches 0[K] as in this state, particles do not move in relation to each other and do not have any kinetic and in particular rotational Energy.

Emergency Medical Response Systems (EMRS) play a vital role in delivering medical aid during disasters. In Serbia, these systems encounter several obstacles due to economic limitations, scarce resources, and ongoing healthcare reforms, all of which affect their performance. This study focuses on examining the risk factors and effectiveness of Serbia's EMRS, identifying systemic issues, and proposing enhancements to improve emergency preparedness for disasters. A survey was conducted across healthcare institutions in Serbia to gather comprehensive insights. The survey explored various aspects, including organizational structures, resource distribution, communication systems, and the speed of emergency responses. Statistical methods such as Pearson's correlation, multivariate regression analysis and chi-square tests were utilized to interpret data collected from 172 healthcare institutions. The multivariate regression analysis of EMS organization identified that factors such as the structuring of working hours and shift patterns are significant predictors, contributing to small but meaningful variations in various EMS outcomes. In contrast, other factors, such as financial resources and the availability of ambulance vehicles, showed more targeted significance depending on the specific EMS aspect being analyzed. Institutions with written mass casualty plans and procedures demonstrate superior effectiveness in EMS activities, excelling in resource allocation, operational continuity, and emergency preparedness, particularly through enhanced coordination and specialized systems for managing large-scale emergencies. The findings highlighted notable disparities in how EMRS are organized, with only 46% of institutions having specific emergency departments. Resource limitations were evident, as many facilities operated with minimal staff and outdated equipment. The communication systems revealed weaknesses, with just 54% having established protocols for handling emergency calls. Response times frequently surpassed international standards, which negatively affected patient outcomes. Additionally, the study found training deficiencies, with 68% of participants expressing a need for further education. Serbia’s EMRS are significantly impacted by systemic issues such as insufficient funding, disjointed service delivery, and inadequate training. Overcoming these challenges necessitates a comprehensive approach that includes boosting financial support, implementing standardized protocols, and fostering enhanced collaboration across different sectors.

Extreme weather events, such as heat waves and heavy precipitation, are becoming increasingly frequent due to climate change, necessitating the development of effective early warning systems (EWS) to mitigate their impacts. This study introduces an advanced EWS designed specifically for Italy, which integrates the FourCastNet global forecasting model with Elevation-integrated TEmperature and Precipitation SRGAN downscaling (E-TEPS) to enhance the spatial resolution and accuracy of climate predictions. Building on previous work that demonstrated E-TEPS's effectiveness in downscaling temperature and total precipitation variables, this research applies the integrated system to two severe weather events in Central Italy: the Emilia-Romagna floods of 2023 and the Marche floods of 2022. The system's performance was evaluated using key metrics, including Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Pearson Correlation, by comparing downscaled outputs from FourCastNet and ERA5 datasets against high-resolution ground truth data from the Euro-Mediterranean Center on Climate Change (CMCC) dataset. The results indicate that the integrated system offers improved predictive accuracy, particularly in capturing critical climate variables, with the entire EWS delivering high-resolution forecasts and final outputs in under one minute. Although potential limitations were identified due to biases in the underlying datasets, which could affect forecast reliability in regions with complex topography or extreme weather conditions, this research highlights the potential of combining machine learning models with downscaling techniques to enhance EWS precision, providing valuable insights for future climate forecasting and disaster preparedness strategies.

Scholars in the field of environmental economics have extensively examined the relationship between foreign direct investment (FDI) and economic growth. However, they have often failed to consider the crucial roles played by technological innovation and financial development in determining environmental costs. The rapid economic growth and urbanization witnessed in BRICS countries have led to a substantial increase in energy demands, resulting in significant environmental degradation. This study aims to investigate the impact of financial development (including measures such as broad money, domestic credit to the private sector, FDI, and green technological innovation) on carbon emissions in BRICS countries using data from 2001 to 2023. The results of the study demonstrate a strong cross-sectional dependence among the countries in the panel. The Augmented Mean Group (AMG) estimator reveals a negative and statistically significant long-term relationship between broad money, FDI, green technological innovation, and CO2 emissions. On the other hand, domestic credit to the private sector shows a positive and significant association with carbon emissions. To determine the direction of causality, the study utilizes the Dumitrescu and Hurlin panel causality test. The findings indicate a non-directional long-term causality between financial development and CO2 emissions. However, a unidirectional causality is observed between green technological innovation and carbon emissions. Based on these findings, the study suggests that the development of industries, financial institutions, and technological innovation is crucial for attracting high-quality FDI in BRICS countries. However, it also highlights the significant contribution of these developments to environmental degradation, necessitating urgent policy responses.

The Colorado and Mississippi River Basins are crucial for water supply, agriculture, and ecological stability in the U.S., yet climate change, water management practices, and energy sector demands pose significant challenges to their sustainability. This paper highlights the potential of leveraging the Voluntary Carbon Market (VCM) to address these challenges by creating new revenue streams and incentivizing sustainable water management practices. The paper provides high-level estimates by extrapolating from existing literature. The results suggests that water projects in these basins could generate over 45 million carbon credits annually, potentially attracting around $4.5 billion in investments over the next decade. However, challenges such as high costs, complex regulations, and stakeholder coordination must be addressed. The paper also identifies opportunities for advancing water resiliency projects, including increasing public awareness, engaging corporations, and utilizing innovative financing mechanisms. Recommendations include promoting the VCM-water relationship, encouraging methodology innovation, developing pilot programs, investing in digital monitoring technologies, and conducting localized analysis to optimize carbon credit potential in water management. By integrating carbon markets with water management strategies, the paper suggests significant contributions to global climate goals and enhanced water resilience in these critical regions.

This ambitious research project seeks to revolutionize sustainable glucose production by harnessing solar energy for the conversion of atmospheric gases. The process involves water collection, electrolysis for hydrogen and oxygen production, PDMS membrane-based CO2 collection, CO2 splitting, formaldehyde generation, and the synthesis of glucose/sucrose. Key innovations include the strategic application of PDMS membranes with varying pore sizes and non-reactive chemical layers to facilitate selective permeability for specific gases. Our goal is to create a cost-effective, eco-friendly glucose production method, paving the way for renewable and sustainable energy solutions.

New data obtained from core samples of two boreholes in Alba Guyot in the Magellan Seamount Trail (MST), Western Pacific, including 40Ar/39Ar age of basanite, mineralogy of basanite, tuff, tuffite, mantle-derived inclusions in basanite and tuff (lherzolite xenolith and Ol, Cpx, Opx xenocrysts), and calcareous nannofossils biostratigraphy, have implications for the guyot history. Volcanics in the upper part of the Alba Guyot main edifice and its Oma Vlinder satellite, at sea depths between 3600 and 2200 m, were deposited during the Cretaceous 112 to 86 Ma interval. In the following ~60 myr, the Alba Guyot became partly submerged, and denuded with the formation of a flat summit platform while the respective fragment of the Pacific Plate was moving to the Northern Hemisphere. Volcanic activity in the northeastern part of the guyot summit platform rejuvenated in the Miocene (24–15 Ma) and produced onshore basanitic volcanoes and layers of tuff in subaerial and tuffite in shallow-water near-shore conditions. In Middle-Late Miocene (10–6 Мa), after the guyot had submerged, carbonates containing calcareous nannofossils were deposited on the porous surfaces of tuff and tuffite. Precipitation of the Fe-Mn crust (Unit III) recommenced during the Pliocene-Pleistocene (< 1.8 Mа) when the guyot summit reached favorable sea depths. The location of the MST guyots in the northwestern segment of the Pacific Plate near the Mariana Trench, along with the Miocene age and alkali-basaltic signatures of basanite, provide evidence for petit-spot volcanism on the Alba Guyot. This inference agrees with the geochemistry of Cenozoic petit-spot basaltic rocks from the Pacific and Miocene basanite on the Alba Guyot. The numerous volcanic cones reaching up to 750 m high and 5.1 km in base diameter, which were discovered on the Alba summit platform, provide the first evidence of voluminous Miocene petit-spot basanitic volcanism upon the Cretaceous guyots and seamounts of the Pacific.

Chronic stress is a pervasive issue that significantly impacts both physical and mental health. Unlike acute stress, which is short-lived and can be beneficial, chronic stress persists over extended periods, leading to a range of adverse health outcomes. This paper explores the myriad physical, mental, and behavioral consequences of chronic stress, emphasizing the underlying physiological mechanisms and potential long-term health implications. Through a comprehensive literature review and data analysis utilizing Python, we aim to provide an in-depth understanding of chronic stress and its effects. Key findings include the critical roles of cortisol and other stress-related chemicals in exacerbating health issues, and the potential for the normalization of high stress levels as an adaptive yet harmful response.

Sensory processing challenges are crucial yet often neglected aspects in the care of children with neurodevelopmental disorders and genetic conditions. They represent a key area of interest in neuroscience, as they significantly impact children's daily functioning and quality of life. This observational study examines the characteristics of these challenges in a group of 614 children, aged 3 to 14 years and 11 months, divided into three groups: 183 with neurodevelopmental disorders (Autism Spectrum Disorder, Attention Deficit Hyperactivity Disorder, developmental delays, learning disorders), 89 with genetic conditions (22q11.2 Deletion Syndrome, Williams Syndrome, Pseudohypoparathyroidism), and 342 controls. Sensory processing was assessed using the Sensory Profile 2 (SP2). Results indicated that children with neurodevelopmental disorders and genetic conditions exhibited significant sensory processing difficulties compared to controls. The SP2 identified sensory challenges across different sensory systems, with varying configurations depending on the diagnosis. Children with neurodevelopmental disorders and genetic conditions show marked sensory processing challenges impacting daily lives and well-being. These findings highlight the importance of early identification and tailored evidence-based interventions to address these specific sensory processing issues. Further research should explore the long-term impact of these interventions in these different populations and their integration into broader therapeutic programs.

Minimum Inhibitory Concentration (MIC) measures the lowest concentration of antibiotic that inhibits in-vitro growth of microorganisms. Canine pyometra is a frequently occurring reproductive disorder where reliable antibiotics along with surgical excision of uterus predicts better prognosis. Scarce literature is available to facilitate proper antibiotic selection to avoid septicemia in clinical cases. The present study was conducted to determine sensitivity and potency of selected antibacterials based on MIC values against bacterial isolates obtained from Canine Pyometra in Kathmandu district, Nepal by Agar Dilution method. Isolates obtained from 63 intra-uterine samples after ovariohysterectomy were Enterococcus spp (n=41), Klebsiella spp. (n=7), Staphylococcus spp. (n=11) and Streptococcus spp. (n=4). Enrofloxacin and Amikacin were found highly sensitive (0% resistance) with a null hypothesis of resistance to all bacterial isolates and were significantly more potent than other antibacterials tested (p<0.05; Kruskal-Wallis test) based on lower MIC ranks. Similarly, ceftriaxone was found to be least potent and was highly resistant to Enterococcus spp. (75.61%) and completely resistant to other bacterial species tested (100%). Comparative results on sensitivity and potency in the study revealed Enrofloxacin and Amikacin to be better antibacterial of choice in pyometra innervation in in-vitro setting. Further clinical trials considering other equally important variables along with MIC should be conducted to predict actual clinical efficacy of antibacterials during therapeutic management of canine pyometra in Nepal.

Sustainable water resource management in Bangladesh's Gumti River Basin faces challenges from climate change, urbanization, and population growth. This study aimed to calibrate and validate the HEC-HMS model for the Gumti River to enhance flood prediction and water resource planning. The model was set up using precipitation, temperature, and discharge data from 2019-2021, with SRTM elevation data for catchment delineation. Manual calibration was performed for 2019-2020, followed by validation for 2021, using parameters such as Muskingum routing and SCS Curve Number. Model performance was evaluated using R², Nash-Sutcliffe efficiency (NSE), RSR, and PBIAS metrics. Results showed satisfactory to good performance, with R² values of 0.64 and 0.68 for calibration and validation, respectively. NSE values were within the satisfactory range, while PBIAS indicated very good performance with slight underestimation. The study concludes that the calibrated HEC-HMS model provides a reliable tool for simulating the Gumti River's hydrology, though there's room for improvement. Integration with flood frequency analysis, water quality monitoring, and climate change projections is recommended for comprehensive water resource management, alongside the implementation of Sustainable Water Resource Management principles and community engagement strategies.

The immune system is central in controlling acute hepatitis B infection and in patients resolving chronic hepatitis B (CHB). Given that 221 million (75%) of CHB patients reside in low- and middle-income countries, developing a vaccine with therapeutic properties represents a rational and cost-effective approach more than a romantic endeavor. This review systematically analyses the critical variables related to the safety, efficacy, and effectiveness of CHB treatments. HeberNasvac's experience is revisited to address the challenges and potentialities of therapeutic vaccines, as well as the current roadblocks in research and development, registration, and large-scale implementation.

To explore the coupling mechanism between urban-rural transformation (URT) and the ecological environment in counties forms the basis for achieving high-quality and sustainable county development. Despite the richness of research on the relationship between urban and rural development and the ecological environment, the county level remains the basic unit of rural revitalization in China, and further research on the coupling mechanism between URT and the ecological environment at this level is needed. Therefore, the study developed an evaluation system for URT, incorporated NDVI data indicators, and employed the coupling coordination degree (CCD) model along with GIS tools to investigate the spatio-temporal pattern of URT and NDVI evolution, and the CCD in each administrative village within Lingbao City. Additionally, a geoDetector model was employed to analyze the influencing factors affecting the CCD of URT and NDVI. Finally, the study explores the coupling mechanism and optimization path. The result shows that: (1) During the study period, the URT level in administrative villages within the study area markedly improved, while NDVI exhibited an increasing-then-decreasing trend; (2) The CCD between URT and NDVI in the northern and central regions of the study area is higher than that in the southern region, with an overall low level; (3) The spatial heterogeneity of CCD is significant, largely influenced by socio-economy, natural environment, policy funds, and geographical location, where the elements comprising CCD mutually influence each other; (4) Drawing upon the coupling and coordination dynamics between URT and the ecological environment within Lingbao City, this research categorizes it into seven types with distinct optimization paths. This study provides a valuable reference for guiding the high-quality and sustainable development strategies for mountainous and hilly counties within the Yellow River basin.

Background The operator's ability in performing carotid stenting (CAS) has improved clinical outcomes. However, more than 3% of patients need to be treated again after CAS. Most of the cases requiring further intervention are affected by hyperplasia. The recommended procedure is the DEBalloon. On the other hand, the literature reports a small number of carotid neoatherosclerosis cases and is recommended to be treated using elective Micronet-covered stent. Discriminating between the two types of in-stent-restenosis ISR (hyperplasia or neoatherosclerosis) is critical for a positive outcome.Case summary We describe a case in which a patient treated with carotid stenting 8 years before, was diagnosed with ISR. Due to the development of neurological symptoms and progressive increases in Peak Systolic Velocity (PSV) eight years following carotid stenting, a DEBalloon was used in a carotid in-stent-restenosis (ISR) standard procedure. About ten minutes after the procedure, the patient developed hemiplegia consistent with the treated carotid territory. The implantation of a MicroNet-covered stent excluded the thrombus and reverted symptoms with a normal MR control at 24 h. Conclusion This case illustrates that when in-stent stenosis evolves years after the stent implantation, neoatherosclerosis should be assessed, and a MicroNet-covered stent should be considered.

Over the coming decades, global freshwater withdrawals are expected to grow, especially in low and middle-income countries. Unless there are significant improvements in the efficiency of water use by economies, freshwater stress, crises and scarcity will worsen. This paper explores further the economic relationship between water use efficiency and scarcity. Because growing scarcity of freshwater in many regions and countries is not adequately reflected in markets, there is often insufficient incentives for investment and innovation to improve the efficiency of water use. To explore further changes in water use efficiency across countries, we conduct a panel analysis of water productivity changes for 130 countries over 1995 to 2020. Countries with lower initial levels of water use efficiency tended to have higher water productivity growth, whereas more agriculturally dependent economies displayed lower improvements in water use efficiency. Better institutional quality and capacity for innovation may also increase water use efficiency. We discuss the implications of these results for improving water use productivity in economies, and in particular, the opportunities and challenges for improving water markets and trades to alleviate water scarcity. We conclude by identifying further areas of research.

Around $1637$, Pierre de Fermat famously scribbled, and claimed to have a proof for, his statement that equation $a^{n} + b^{n} = c^{n}$ has no positive integer solutions for exponents $n>2$. The theorem stood unproven for centuries until Andrew Wiles' groundbreaking work in $1994$, with a notable caveat: Wiles' proof, while successful, relied on modern tools far beyond Fermat's claimed approach in terms of complexity. The present work potentially offers a solution which is closer in spirit to Fermat's original idea.

Cementitious materials exhibit excellent binding properties and micropore structures that support the stabilization of TiO2 nanoparticles within the matrix. Therefore, these materials are ideal for the development of functional construction products with TiO2 nanoparticles. This study investigated the degree of hydration, microstructure, and mechanical properties of cement-containing TiO2 nanoparticles. The experimental results demonstrated that TiO2 nanoparticles accelerated the hydration rate of cement, reducing the setting times. Moreover, TiO2 nanoparticles changed matrix microstructure, decreasing the porosity and improving early-age strength. Although TiO2 nanoparticles function as nucleation sites in the cement hydration reaction, the tendency of the particles to clump implies that proper dispersion should be ensured when mixing in large quantities. When developing new building materials incorporating TiO2 nanoparticles, considering the effect of TiO2 nanoparticles on the hydration reaction of cementitious materials is crucial.

This article presents a novel resolution of the Collatz Conjecture, centered on the concept of Generative Completeness of the inverse Collatz function. We introduce and rigorously prove that for all N ∈ ℕ⁺, there exists a minimal generator m_N = 1 such that all positive integers up to N can be generated through successive applications of the inverse Collatz function G. This key property, which we term "Generative Completeness", forms the cornerstone of our proof. Building upon this foundation, we establish several crucial results: The boundedness of all Collatz sequences The existence and uniqueness of cycles in Collatz sequences The nature of the unique cycle as {1, 4, 2} We then present three distinct approaches to resolving the Collatz Conjecture, all fundamentally rooted in the Generative Completeness property. These diverse methods not only prove the conjecture but also provide deep insights into the structure of Collatz sequences.

This study aims to investigate the psychological cognitive mechanisms of rural residents amidst the renewal of suburban historical and cultural villages by examining the interplay between nostalgia, collective memory, subjective well-being and place identity in rural tourism destinations. Using Naobao Village as a case study—a suburban historical and cultural village in Hohhot, Inner Mongolia, this research employs a comprehensive approach integrating experimental methods and questionnaire surveys. The findings demonstrate that analyzing the interaction among the four emotions can elucidate the psychological cognitive mechanism of residents. Moreover, it uncovers that tourism effects significantly influence residents' perception of their living environment with positive effects on collective memory, subjective well-being and place identity. In the theoretical model for generating psychological cognition among residents in suburban historical and cultural villages, subjective well-being and collective memory play crucial mediating roles. This study provides a theoretical foundation and practical guidance for spatial reconstruction and cultural evolution of tourist landscapes in suburban rural tourist destinations.

Visual thinking leverages spatial mechanisms in animals for navigation and reasoning. Therefore, given the challenge of abstract mathematics and logic, spatial reasoning-based teaching strategies can be highly effective. Our previous research verified that innovative box and ball coloring activities help teach elementary school students complex notions like quantifiers, logical connectors, and dynamic systems. However, given the richness of the activities, correction is slow, error-prone, and demands high attention and cognitive load from the teacher. Moreover, feedback to the teacher should be immediate. Thus, we propose to provide the teacher with real-time help with LLMs. We explored various prompting techniques with and without context Zero shot, Few shot, Chain of Thought, Visualization of Thought, Self Consistency, logicLM and Emotional to test GPT-4o’s visual, logical, and correction capabilities. We obtained that Visualization of Thought and Self Consistency techniques enabled GPT-4o to correctly evaluate 90% of logical-spatial problems that we tested. Additionally, we propose a novel prompt combining some of these techniques that achieved 100% accuracy on a testing sample, excelling in spatial problems and enhancing logical reasoning.

Background/Objectives: Kinanthropometry is the science that deals with the measurement of variations of the physical dimensions and composition of the human body, according to the age and different degrees of nutrition of a person. This discipline postulates that all the measurements obtained in statics will have an impact on the dynamics. This study’s objective was to evaluate the kinanthropometric differences; Methods: The study was done in a population of 403 persons, aged between 18 and 42 years, who were categorized based on their biological sex and in what sport they usually practiced in a purely recreational way. Measurements and indices were obtained following the protocol of the International Society for the Advancement of Kinanthropometry (ISAK); Results: We observed significant differences in most of the values, for example, men use the presented higher values in relation to weight, height and size of some circumferences, in addition to Body Weight Index (BMI), Relative Index of the Lower Limbs (RILL), percentage of muscle weight (%M) and percentage of residual weight (%R). On the other hand, women presented higher values in most body folds, in addition to the Cormic Index (CI), Body Density Index (BDI), percentage of fat weight (%F) and percentage of bones weight (%B); Conclusions: This work could be useful for people to choose what kind of sport will be better for them according to their morphotype.

Toxicity mechanisms of per- and polyfluoroalkyl substances (PFAS), a chemical class present in diverse ecosystems, are not well characterized in aquatic species. Perfluorooctanesulfonamide (PFOSA, C8H2F17NO2S) is a common precursor of perfluorooctane sulfonic acid (PFOS), a long-chain PFAS. Here, we assessed sub-lethal endpoints related to development, oxidative stress, locomotor activity, and gene expression in zebrafish embryos and larvae following continuous exposure to PFOSA beginning at 6 hours post fertilization (hpf). PFOSA decreased survival in fish treated with 1 µg/L PFOSA, however the effect was modest relative to the controls (difference of 10%). Exposure up to 10 µg/L PFOSA did not affect hatch rate, nor did it induce reactive oxygen species in 7-day-old larvae fish. However, locomotor activity of larval fish treated with 100 µg/L PFOSA was reduced relative to the solvent control. Transcripts related to oxidative stress response and apoptosis were measured and BCL2 associated X, apoptosis regulator (bax), cytochrome c, somatic (cycs), catalase (cat), superoxide dismutase 2 (sod2) were induced with high concentrations of PFOSA. Genes related to neurotoxicity were also measured and transcript levels of acetylcholinesterase (ache), elav-like RNA binding protein 3 (elavl3), growth associated protein 43 (gap43), synapsin II (syn2a), and tubulin 3 (tubb3) levels were all increased in larval fish with higher PFOSA exposure. This study contributes to our knowledge regarding the relative toxicity of PFOSA to fish and contributes data to future risk assessment strategies of these concerning, persistent environmental pollutants.

Reduction of the density operator for quantum subsystems is derived without the use of the Born Rule.