Human sepsis is one of the leading cause of death worldwide and is known to be a harmful damaging host inflammatory condition, primarily caused by endotoxin released by gram-negative bacteria. Despite antibiotics administration being widely used to treat disease, effective targeted therapeutic strategies for the sepsis are still lacking. Here, we demonstrate that CM1, a derivative of natural polyphenol chrysin, exerts anti-inflammatory activity by inducing the ubiquitin-editing protein TNFAIP3 and NAD-dependent deacetylase sirtuin 1 (SIRT1). We found that CM1 attenuated Toll-like receptor 4 (TLR4)-induced the generation of inflammatory cytokines by inhibiting the extracellular-signal-regulated kinase (ERK)/MAPK and nuclear factor kappa B (NF-κB) signaling pathway. In addition, the treatment of macrophages with CM1 induced the expression of TNFAIP3 and SIRT1 in TLR4-stimulated primary macrophages, however the anti-inflammatory properties of CM1 was disappeared by siRNA silencing of TNFAPI3 or by the genetic and pharmacologic inhibition of SIRT1. Importantly, intravenously administration of CM1 resulted in the decreased susceptibility to endotoxin-induced sepsis, leading to inhibition of the generation of proinflammatory cytokines and neutrophils infiltration into lung than control mice. Collectively, these findings suggest that CM1 has the potential to be a treatment candidate for diverse inflammatory diseases including sepsis.

Subacute sclerosing panencephalitis (SSPE) is a progressive neurological complication that affects the central nervous system. It occurs as a late complication of the measles infection the young children and adolescents who are commonly affected present with personality changes and neurological deficits. The diagnosis can be done via clinical features, electroencephalography, and cerebrospinal fluid analysis. At present, there is no cure for SSPE. The immunisation against measles is the main strategy in preventing this condition. Here, we present a case of a 22-year-old Indian male diagnosed with Subacute sclerosing panencephalitis.

Urinary tract infections (UTIs) are among the most common bacterial infections in community and hospital settings. Infections of the urinary system can range from pyelonephritis to urethritis. Acute renal infections encompass entities such as acute pyelonephritis, acute focal bacterial nephritis, renal and perinephric abscesses, emphysematous pyelonephritis, and pyonephrosis,while xanthogranulomatous pyelonephritis is a chronic granulomatous inflammatory condition that affects the kidneys. The diagnosis of UTIs predominantly relies on clinical assessment and confirmation through abnormal laboratory results. Therefore, routine medical imaging is typically reserved for complicated cases, aiming to identify contributing factors such as renal calculi, determine the type of infection, and evaluate the extent of the infection and its associated complications. Furthermore, imaging has become crucial for radiologists during interventional procedures in the treatment of pyonephrosis and renal abscesses. Traditional imaging tools, like abdominal X-rays, are vital for identifying renal calculi and gas shadows in emphysematous pyelonephritis, while ultrasonography emerges as an excellent modality for assessing urinary infections in emergency scenarios, pregnancy, and paediatric cases. Contrast-enhanced computed tomography (CECT) or non-contrast computed tomography (NCCT) is the imaging method of choice in the most complex situations, allowing for precise assessment of the disease burden. Current MRI sequences yield promising results in specific scenarios, such as pregnancy and paediatric subjects, where minimising radiation exposure is a concern. This article focuses on elucidating the essential radiological modalities and their distinctive features in the context of renal infections, offering valuable guidance to microbiologists and physicians.

The classification and summarization of online reviews using machine learning and deep learningbased approaches are the subject of this systematic literature review. Consumers, companies, and researchers can now find vital information from online reviews. Automatically categorizing and summarizing these reviews can offer useful information and facilitate decision-making. The purpose of this study is to offer a thorough overview of the current methodology, approaches, and developments in this area. The review concentrates on machine learning-based methods for categorization and summarizing tasks, highlighting their advantages, drawbacks, and new developments. This systematic review provides insights into the most recent methodologies and indicates prospective directions for further investigation by synthesizing the data from a wide range of pertinent research publications

Abstract: The septum pellucidum is a thin, translucent double-membrane structure located between the anterior horns of the lateral ventricles. This mini-review explores the gross and radiological anatomy, variations, and clinical significance of the septum pellucidum. The article elaborates on the different types of variations, including cavum septum pellucidum (CSP), cavum vergae (CV), and cavum veli interpositi (CVI). The CSP is a fluid-filled pocket located within the two leaflets of the SP. It forms during fetal development and gradually obliterates before birth. However, the fusion may be prolonged or persist into adulthood in some individuals. The CV is formed when the two commissural plates fail to fuse completely during foetal development. When associated with CSP, the CV is collectively known as the cavum septum pellucidum et vergae (CSPV). However, the isolated CV is rare. The CVI is a CSF-filled space between two tela choroidea layers and communicates with the quadrigeminal cistern, superior to the pineal gland. This article discusses the radiological features of these variations using imaging techniques such as ultrasound, magnetic resonance imaging (MRI), and computed tomography (CT). Ultrasonography is particularly useful for evaluating the SP in fetuses and infants, while MRI and CT scans provide detailed visualisation of the SP and its variations. The SP has the potential to be associated with cerebral anomalies, hydrocephalus, mental disorders, and neurological symptoms. Knowing the related anatomy and detecting variations using imaging modalities are crucial for accurately diagnosing and managing these conditions.

Gene therapy is becoming increasingly prevalent, with new gene therapy medicinal products (GTMPs) being approved for use every year. Hospital pharmacists are expected to prepare and dispense these products, but there is substantial heterogeneity in the availability of up-to-date, practical guidance at a national level in Europe. Many institutions have no or very limited experience in handling GTMPs. As such, there is a need for updated, practical guidance to aid hospital pharmacy teams in developing institutional standard operating procedures (SOPs) for the safe handling of GTMPs across the entire workflow. Here, we present the European Association of Hospital Pharmacists’ updated guidance on the handling of GTMPs, developed by a team of recognised experts from around Europe. Each aspect of the GTMP handling process is addressed, including receipt and storage, dispensing and reconstitution, transportation, administration, waste disposal, decontamination of spills and accidental exposure. A series of charts are provided to aid the development of practical workflows. This guidance document is intended as a framework to help develop institutional SOPs and should always be used in conjunction with local regulations.

The material undergoes high temperature and high strain rate deformation process during cutting process, may induce the dynamic recrystallization behavior and result the evolution of dynamic mechanical properties of the material to be machined. In this paper, the modified Johnson-Cook(J-C) model for Nickel based powder metallurgy superalloy considering dynamic recrystallization behavior in high strain rate and temperature is proposed. The dynamic mechanical properties of the material under different strain rates and temperature conditions are obtained by quasi-static compression test and split Hopkinson pressure bar (SHPB) test. The coefficients of the modified J-C model are obtained by linear regression method. The modified model is verified by comparison with experimental and model prediction results. The results show that the modified J-C model proposed in this paper can accurately describe the mechanical properties of nickel-based powder metallurgy superalloys at high temperature and high strain rate. Which provides help for studying the cutting mechanism and finite element simulation of nickel-based powder metallurgy superalloy.

Antibiotic Resistance (ABR) is increasing the mortality and morbidity associated with infectious diseases, besides increasing the cost of healthcare, saturating health-system capacity, and adversely affecting food security. Framing an appropriate narrative and engaging local communities through ‘One Health’ approach is essential to complement the top down measures. However, the absence of objective criteria to measure the performance of ABR interventions at community settings make it difficult to mobilize interest and investment for such interventions. An exercise was therefore done to develop an indicator framework for this purpose. An exhaustive list of indicators was developed from experiences gathered through community engagement work in a local panchayat (small administrative area) in Kerala, India, and a consultative process with health, veterinary, environment, and development experts. A prioritization exercise was done, looking at appropriateness, feasibility and validity, by global experts on ABR. A 15-point indicator framework was designed based on the prioritization process. The final set of indicators covers human health, animal health, environment management and Water Sanitation and hygiene (WASH) domains. The indicator framework was piloted in the panchayat(located in Kerala), which attained a score of 34 (maximum 45). The score increased when interventions were implemented to mitigate the ABR drives, indicating the framework is sensitive to change. Simultaneously, the indicator framework was tested in four sites from three other Indian states with different socioeconomic and health profiles, yielding different scores. Those collecting the field data were able to use it with minimal training. To conclude, this indicator framework can help policymakers broadly understand the factors contributing to ABR and measure the performance of interventions they choose to implement in the community

Physical activity is especially important of children's everyday life with chronic disease. The aim of the study was to show whether asthma is a barrier to physical activity in our society. The correlation between the severity of the disease, body mass index, and physical activity were analyzed, and, parents' opinion whether children should participate in active sports was assessed. Physical activity of children with asthma was analyzed by questionnaires and activity-measuring armbands. 93 parents and their children were involved in the survey, while 20 children were wearing the armband. The age of children was 12.6±3.5 years (mean±SD), 69.9% were boys, 30.1% were girls. 93.4% of the respondents participated in physical education program and 56.5% also attended sporting activities on a regular basis. 61.2% of the children had mild, 37.6% moderate, and 1.2% severe asthma. 6.5% of the respondents stated that their illness had been consistently or frequently limiting the performance concerning their school or home duties over the past 4 weeks. Twelve percent of parents felt that physical activity was not appropriate in the context of this disease. We conclude, that fear of the consequences of physical activity depends largely on education which should involve their parents, teachers and coaches.

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.

In the realm of molecular science, intricate relationships between molecular structures and their biomedical and pharmacological characteristics have been revealed through empirical experiments. This exploration hinges on the application of numerical descriptors, known as Topological Indices, which illuminate the inherent properties of diverse molecular structures. With particular significance in the medical and pharmaceutical domains, these indices facilitate the prediction of biological features for new chemical compounds and drugs by quantifying weighted entropies. In the context of this paper, we delve into the concept of graph entropy, weaving it intricately with the topological properties of the crystalline framework of the copper oxide molecule, denoted as Cu\textsubscript{2}O$[i,j,t]$. Our primary objective is to unravel the mathematical symphony underlying the structural intricacies of Cu\textsubscript{2}O$[i,j,t]$ and to imbue it with the conceptual essence of entropy. We accomplish this through the computation of entropy, leveraging various topological indices, including weight. In addition to our analytical journey, we present a graphical comparison that juxtaposes the computed indices and entropies, shedding light on the interplay between mathematical analysis and the structural elegance of Cu\textsubscript{2}O$[i,j,t]$. This endeavor contributes to a deeper understanding of the material's multifaceted applications, spanning domains from chemical sensors to solar cells, photocatalysis, and batteries, where Cu\textsubscript{2}O's crystallographic structure plays a pivotal role.

Natural Gas (NG) processing is a prominent industrial separation process. Among the available techniques, the innovative membrane process shows potential for efficient removal of impurities, including carbon dioxide (CO₂). This study focuses on utilizing breakthroughs in membrane separation to drive sustainable CO₂ extraction from natural gas. Through comprehensive research and analysis, we explore the effectiveness and feasibility of membrane-based systems in removing CO₂ impurities from NG, thus promoting greener and more sustainable industrial practices. Our findings underscore the transformative nature of membrane separation technology, presenting new possibilities for a more environmentally-friendly and sustainable approach to CO₂ extraction from natural gas.Natural Gas (NG) processing utilizes various techniques for impurity removal, with the membrane process emerging as a promising option for efficient carbon dioxide (CO₂) extraction. This research proposes the integration of a simple mathematical model into ASPEN HYSYS to design a membrane system for CO₂/CH₄ separation. The study also investigates parameter sensitivities by altering operating conditions, such as feed composition and pressure, as well as membrane properties, including selectivity. By analyzing these variables, we aim to optimize the performance and efficiency of the membrane system, facilitating the sustainable extraction of CO₂ from NG. The findings contribute to advancing the design and operation of membrane-based processes for CO₂ separation, paving the way for greener and more sustainable industrial practices. In addition, this study explores various configurations for optimizing the design of the membrane system, including single-stage with and without recycling as well as double-stage configurations. The investigation demonstrates that methane recovery can be enhanced through the recycling of the permeate stream and by implementing a double stage membrane system. These findings highlight the potential for improving the efficiency and performance of the membrane system, enabling higher methane recovery rates. By considering different configurations, this research contributes to the development of more effective and sustainable CO₂ extraction processes from natural gas.

The majority of EGFR mutations (85–90%) are exon 19 deletions and L858R point mutation of exon 21, characterized by high sensitivity to EGFR-tyrosine kinase inhibitors (TKIs). Less is known about uncommon mutations (10-15% of EGFR mutations). Predominant mutation types in this category include exon 18 point mutations, exon 21 L861X, exon 20 insertions and exon 20 S768I. This group presents a heterogeneous prevalence, partly due to the different testing methods and to the presence of compound mutation, which in some cases leads to shorter overall survival and different sensitivity to different TKIs than simple mutations. EGFR-TKI sensitivity may also vary depending on the specific mutation and the tertiary structure of the protein. The best strategy remains uncertain and the data of TKIs efficacy are founded of few prospective and some retrospective series. Newer investigational agents are still under study and there are no other approved specific treatment targeting uncommon EGFR mutations. Defining the best treatment option for this patient population remain un unmet medical need. The objective of this review is to evaluate existing data on outcomes, epidemiology and clinical characteristics of lung cancer patients with rare EGFR mutations, with a focus on intracranial activity and response to immunotherapy.

Lung cancer remains the leading cause of cancer-related death and it is usually diagnosed in advanced stages (stage III or IV). Recently, the availability of targeted strategies and of immunotherapy with checkpoint inhibitors (ICI) has favorably changed patient prognosis. Treatment outcome is closely related to tumor biology and interaction with the host immune microenvironment (TME). Whether for targeted therapies the response relies on the presence of specific genetic alterations in tumor cells, for ICI accurate biomarkers of response are lacking and clinical outcome likely depends on multiple factors, host and tumor-related. This paper is an overview of the ongoing research on predictive factors both from in-vitro/ex-vivo analysis (ranging from conventional pathology to molecular biology) and in-vivo analysis, where molecular imaging is showing an exponential growth and use due to the technological advancement and to the new bioinformatics approaches applied to image analyses that allow specific features recovery in specific tumor subclones.

Background: Lactate is a metabolic byproduct. It has traditionally been seen as a byproduct of oxygen-deprived glycolysis and ischemia. Therefore, our main goal is to examine the influence of lactate levels (LLs) on clinical outcomes in patients with severe Traumatic brain injury (TBI). Method: This is a level 1 single-center, retrospective study of patients with severe TBI between January 1, 2020- December 31, 2023, inclusive. Only patients with an Abbreviated Injury Scale (AIS), value of 3 or higher were included. Results: Single-factor ANOVA indicated a significant increase in LLs with decreasing age (Hospital admission: p = 1.53E-13, ICU admission: p = 0.0183, Hospital discharge: p = 0.02, Death: p = 0.0149). Linear regression models showed a significant decrease in age compared to Hospital admission LLs (p = 2.65E-09), Intensive Care Unit (ICU) admission LLs (p = 0.01), and Death LLs (p = 0.00295). Prognostic scores such as Injury Severity Scores (ISS) and Glasgow Coma Score (GCS) showed a strong correlation with both Hospital admission and ICU admission LLs. ANOVA indicated higher LLs with increasing ISS (Hospital admission: p = 5.22E-06, ICU admission: p = 1.92E-05) and increasing LLs with decreasing GCS (Admission: p = 3.42E-08, ICU admission: p = 1.74E-09). Linear regressions revealed a strong positive correlation between ISS and LLs (Hospital admission: p = 3.69E-07, ICU admission: p = 2.90E-06). On linear regression, the lactate level measured at hospital admission and ICU admission strongly positively associated with the length of stay (LOS) in the hospital (Hospital admission: p = 0.00342, ICU admission: p = 0.0163), LOS in the ICU (Hospital admission: p = 0.0141, ICU admission: p = 0.0234), ventilator days (Hospital admission: p = 0.002513, ICU admission: p = 8.23E-05), and mortality (Hospital admission: p = 8.13E-05, ICU admission: p = 3.93E-05). Discussion: We discovered that high LLs were linked to longer stays in the hospital and ICU, as well as more days requiring a ventilator, and higher mortality rates in patients with severe TBI. Enhanced LLs had the most notable impact on the number of days on a ventilator and mortality, followed by longer hospital and ICU stays. Therefore, lactate can be considered a strong predictor of poor clinical outcomes in patients with severe TBI.

There is considerable interest in cellulose solubilisation in deep eutectic solvents (DESs) as a new emerging class of green solvents. However, the experimental data have indicated that cellulose is almost insoluble in most of DESs. Carboxylic acid-based DESs are a category of DESs that exhibit a modest ability to solubilise cellulose. However, the molecular-level reasons why carboxylic acid-based DESs can dissolve cellulose are unknown. Such information is crucial in developing DESs with enhanced cellulose solubilising ability. Here, we use molecular dynamics simulations to explore the molecular mechanism of cellulose solubility in oxaline (choline chloride/oxalic acid) as a typical carboxylic acid-based DES and cellulose insolubility in reline (choline chloride/urea) as the most famous DES. It was revealed that oxalic acid possesses a greater ability to weaken the interaction between the chloride anion and the choline cation when compared to other urea in reline. Self-interactions of hydrogen bond donors are also highly attenuated in oxaline than in reline. These results explain the observed more significant melting point depression of oxaline in comparison to reline. We depict a molecular mechanism indicating how oxalic acid synergically works with chloride ion to dissolve cellulose and why urea cannot play such a role in reline.

One of the foundations of Smart Cities is mobility. To manage the efficiency of urban mobility, continuous recording of traffic flows is essential. The road traffic parameters in the cross section of the road network can be registered with the use of various measurement technologies. This is indirectly due to the complexity of the phenomenon of vehicle traffic and the disturbances in physical quantities generated as a result of it. Traffic data carries: sound waves, vibrations, optical waves and other media. The characteristics of these physical media, properly recorded and mathematically transformed, may constitute a superposition of the position of individual vehicles moving in the traffic flow. Moreover, these waves interfere with each other depending on the observed parameters of the movement of individual vehicles at different places of the network. In this context, information obtained from various media is the overall view of traffic. This article focuses on acquiring infrared traffic data. The movement of each vehicle, regardless of its type, is inextricably linked to infrared radiation, the distribution changing as a function of the road network. Each vehicle is a source of heat and therefore also emits infrared radiation (it heats up gradually while driving, with small temperature fluctuations). Therefore, the temperature of a moving vehicle is generally different from the background (road network) temperature. This article presents a successful attempt to analyze the infrared radiation accompanying road traffic in a selected cross section of the road. In order to register infrared radiation in the traffic stream, a prototype of a measuring system consisting of a pyrometer commonly used in thermometers (cost about 10 € and less) was used. Measurements of infrared radiation of the vehicle stream obtained in this way were compared with the measurement data of handheld traffic recorders, the so-called mechanical vehicle counters. The comparison of the results from both recording methods allows for the formulation of further research hypotheses towards extended research in the field of infrared radiation of the traffic stream. In this regard, it is important to research with various disturbances in the measurements that come from other heat sources located in the road network and its immediate vicinity. This study is important from the point of view of smart cities and C-ITS systems (mainly V2I communication). The registration of data describing the traffic flow with the use of a single pyrometer, instead of an expensive IR camera, is a cheap alternative in modern city information networks. This allows you to create intelligent sensor networks using connectivity based on, e.g., mesh networks. Such activities are possible with costs for one measuring point reduced by one or two orders of magnitude compared to the costs incurred with the use of IR cameras ( € 1000, € 10,000 and more). In the current situation of the energy crisis, the search for innovative solutions with lower energy demand is very important in the Smart City policy.

Background/Objectives: Stroke patients generally have balance and gait dysfunction due to decreased range of motion (ROM) and muscle strength of the ankle joint. A therapist can apply a floss band to enhance ROM, pain control, jumping performance, strength, myofascial release, and recovery from fatigue. This study compared the immediate effects of floss band application on ankle ROM, balance, and gait ability in stroke patients.; Methods: This study randomized 40 chronic stroke patients to either the floss (n = 20) or sham (n = 20) band group. Outcome measures were ankle ROM, weight bearing lunge test (WBLT) performance, standing balance, and gait ability. Outcome measures were assessed at baseline and immediately after applying the floss or placebo band.; Results: There were significant improvements in dorsiflexion (DF), WBLT, static balance, and foot strike in those who used the floss band compared to the sham group (all p < 0.05).; Conclusions: The floss band improved ankle DF, balance, and gait, indicating that it is a feasible therapeutic method for improving ankle DF, balance, and gait in chronic stroke patients.

In the aerospace industry, composites based on polymer or metal matrices and fillers made from granite, marble, lime and other rock powders are used. These fillers are similar in composition to cement and glass used for immobilization of radioactive waste (RW). In this paper, it is proposed to grind cemented or vitrified radioactive waste into micro or nanopowder and introduce this powder into a polymer or metal matrix to obtain a composite with improved physical characteristics, which can be used as a structural element or equipment element of automated space stations, satellites or rovers. In this way, it is possible to dispose of a huge amount of accumulated radioactive waste into space as a payload.

Studies on integrating Spiking Neural Networks (SNNs) with the Transformer architecture holds promise for enabling models to achieve ultra-low energy consumption while possessing the performance of the Transformer architecture. Currently, studies on ANN-to-SNN conversion of integrating Spiking Neural Networks (SNNs) with the Transformer architecture mainly focuses on simple activation functions in MLPs, and has not yet addressed the mismatch between the Softmax activation function in the self-attention mechanism and the computation rules of SNNs. Consequently, the ANN-to-SNN conversion efforts have consistently failed to make the Transformer architecture directly applicable to SNNs. To address this challenge, we propose the Spiking-Softmax method, which integrates Spiking Exponential Neuron (SI-exp) and Spiking Collaboration Normalized Neuron (SI-norm). The Spiking-Softmax method accurately simulates the Softmax activation function with only 12 time steps. Building upon this, we propose the Spike Integrated Transformer conversion (SIT-conversion) method, which enables the conversion of the Transformer architecture to SNNs. The SNNs generated by the SIT-conversion of Transformer models of various sizes achieve accuracy nearly identical to their ANNs counterparts, achieving nearly lossless and ultra-low-latency ANN-to-SNN conversion. This work represents the first implementation of simulating the Softmax activation function and fully converting the Transformer architecture into SNNs through spike firing.

The urinary tract, once considered sterile, is now understood to host a diverse community of microorganisms known as the urinary microbiome. This microbiome, which is made up of bacteria, fungi, and viruses, is important for preserving urological health and has been linked to the pathogenesis of a number of urinary tract disorders. In this review, we offer a consolidated overview of the urinary tract bacterial population, including its composition, diversity, and factors influencing its dynamics. We explore its involvement in urinary tract infections, interstitial cystitis/bladder pain syndrome (IC/BPS), urinary stone formation, and other urological diseases, highlighting the importance of understanding its correlation with disease pathology for the development of therapeutic strategies. Additionally, we explore its role in autoimmune diseases of the urinary tract and the potential of leveraging the urinary microbiome for targeted interventions in the treatment of urinary tract infections. Longitudinal studies are emphasized for their ability to elucidate microbial dynamics, establish causality, and ensure consistency and reproducibility across research endeavors. These efforts underscore the necessity for continued research and multidisciplinary collaborations in this rapidly evolving field to advance our understanding and therapeutic strategies for urinary tract disorders.

Background. Fibromyalgia (FM) is a complex condition marked by increased pain sensitivity and central sensitization. Studies often explore the link between FM and depressive-anxiety disorders, but few focus on dysthymia or persistent depressive disorder (PDD), which can be more disabling than major depression (MD). Objective. To identify clinical scales and subscales of the Personality Assessment Inventory (PAI) that effectively describe and differentiate the psychological profile of PDD, with or without comorbid MD, in FM patients with PDD previously dimensionally classified by the Millon Clinical Multiaxial Inventory III (MCMI-III). Method. An observational, cross-sectional study was conducted with 66 women (mean age 49.18, SD=8.09) from Hospital del Mar. The PAI, the MCMI-III, and Fibromyalgia Impact Questionnaire (FIQ) were used to assess the sample. Results. The PAI showed strong discriminative ability in detecting PDD, characterized by high scores in cognitive and emotional depression, and low scores in identity alteration, dominance, and grandeur. High scores in cognitive, emotional, and physiological depression, identity alteration, cognitive anxiety, and suicidal ideation, along with low scores in dominance and grandeur, were needed to detect MD with PDD. Discriminant analysis could differentiate 69.6-73.9% of the PDD group and 84.6% of the PDD+MD group. Group comparisons showed that 72.2% of patients with an affective disorder by PAI were correctly classified in the MCMI-III affective disorder group, and 70% without affective disorder were correctly classified. Conclusions. The PAI effectively identifies PDD in FM patients and detects concurrent MD episodes, aiding in better prognostic and therapeutic guidance.

In the domain of software engineering, the accurate and effective classification of requirements is of paramount importance. Proper classifications of these requirements enable developers to create robust and error-free software solution. Traditional methods of user requirements classification face the issue of the reliance on manual processes, which are time-consuming, labor-intensive, and prone to human error. The limitations of traditional methods underscore the need for more automated, scalable, and robust approaches to user requirements classification in order to meet the demands of modern software development practices. To improve the classification process, we employed a Deep Learning (DL) methodology termed the Bidirectional Long Short-Term Memory (Bi-LSTM) model to conduct feature extraction, after which we merged these feature vectors into ML classifiers. Our research methodology is structured around a five-step process. Initially, the textual input is tokenized and converted to lowercase. Subsequently, we eliminate all punctuation. The pre-processed text is then subjected to a Bi-LSTM (Bidirectional Long Short-Term Memory) model for feature vector extraction. After that, this feature vector is fed into different classifiers such as Medium KNN, Cubic KNN, Linear SVM, Quadratic SVM, and Cubic SVM and obtained an accuracy of around 99.60% to 99.80% on a publicly available dataset of requirements.

Galactic rotation curve was formulated before the Sgr A* had been confirmed. The action of the Sgr A* on the rotation curve has not been considered. Now, it was observed that the fastest stars in the Milky Way is in the distance less than 0.5pc from the Sgr A*. It is contradicted with the current galactic rotation curve in which the orbital velocity near the center of the galaxy is the smallest. And, because of the advance of technology, it was observed that the circular velocity curve of the Milky Way from 5 to 30 kpc is with a significantly faster decline (Keplerian decline) compared to the inner parts. It is contradicted with the current curve in which the out parts could be larger or no decline. And, it was observed that the fast galaxy bar continue challenge the standard cosmology. For the reasons, we present an improved galactic rotation curve.

As a branch of regional innovation theories, social filter theory fundamentally reveals the reasons for the geography of innovation in different countries and regions. However, compared with some other regional innovation theories, social filter theory has been as silent as a sleeping beauty and hasn’t been fully developed. For enriching and developing social filter theory, this article systematically traces the source and comments on four aspects: the concept of social filter, the construction and measurement of indicators of social filter, the mechanism and empirical re-search of social filter affecting regional innovation and innovation transformation. Until recently regional innovation theories primarily focused on the superficial description of the phenomenon of innovation, but lack of attention to the local social filter condition of innovation generation and innovation transformation, which are the pre-condition of constructing mature innovation system. Therefore, additional efforts are still required to fill the current knowledge gap from the recom-mended directions in the article.

Background: Intestinal helminthiases and schistosomiasis are among the neglected tropical diseases targeted by the World Health Organization (WHO) for elimination as a public health issue by 2030. For this, it is important to determine their distribution and predicting factors, after a decade of mass deworming campaigns. In particular, such information is scarce among pre-school aged children who have not been the target for epidemiological studies and schistosomiasis deworming activities. This cross-sectional study and secondary data analysis focused on preschool-aged children and was aimed to determine the prevalence of intestinal helminthiases (Ascaris, ankylostoma, trichirus trichura, taenia) and Schistosomiasis, and identify the factors associated with them in Rwanda. Methods: Data from 4,675 preschool-aged children randomly selected from 17 districts endemic to Schistosoma mansoni were analyzed. Parasitological assessment was performed using the Kato Katz technique. Having at least one intestinal helminthiasis or schistosomiasis case was considered a positive outcome. A structured questionnaire for childcare guardians, literature, and GIS were used to collect information regarding environmental factors. Data were aggregated at village level to calculate village prevalence used in depicting the distribution of intestinal helminthiases and schistosomiasis. Descriptive analysis was performed, and prevalence was assessed as a measure of frequency. The chi-square test was used for bivariate analysis whereas logistic regression was used for multivariable analysis. The confidence level was set at 95%, and the decision was made based on the P-value. Odds ratios (ORs) were assessed as a measure of association. STATA 15 and ArcGIS software were used in this study. Results: The prevalence of intestinal helminthiases and schistosomiasis among preschool-aged children was 20.3%. Ascaris was the most prevalent parasite in this study (15%). Being older than 24 months, having self-employed parents, residence, fetching water into the lake or water body, land cover, clay soil, and high LST are predictors of intestinal helminthiases and schistosomiasis among preschool-aged children in Rwanda. Conclusion: The prevalence of 20.3% is moderate and in the march towards the elimination of these parasitic infections, deworming activities should be coupled with water supply, reinforcement of the use of Early Child Development (ECD), relocating people living in proximity of wetlands and water bodies, and health education are key interventions in preventing preschool-aged children to get intestinal helminthiases and Schistosomiasis.

This paper presents a comparative bibliometric analysis of digital transformation in small and medium enterprises, focusing on the before and after the Covid-19 pandemic. Using data from the Scopus database, the study analyzes 1,566 articles published between 2001 and 2024, focusing on pre-COVID (2001–2018) and post-COVID (2019–2024). Bibliometric tools, including VOSviewer and Biblioshiny, were employed to conduct performance analysis, scientific mapping, and co-occurrence analyses of keywords and co-authorship. The results demonstrate a substantial increase in research output post-COVID, particularly in areas such as the Internet of Things (IoT), cloud computing, and e-commerce. These technologies have become vital for the survival and competitiveness of SMEs in the post-pandemic world. However, the study also highlights significant challenges, including limited financial resources and a lack of skilled personnel, which have hindered SMEs' ability to implement digital transformation fully. Government intervention, through financial assistance and strategic support, is identified as crucial in enabling SMEs to overcome these obstacles and successfully navigate the digital era. This analysis contributes to the growing body of literature on SMEs' digitalization, offering key insights for policymakers, researchers, and businesses aiming to adapt to the evolving digital landscape in a post-pandemic economy.

This paper is a part of the broader research on “Adaptation of Laws in Science” and explores the limitations and challenges involved in adapting mathematical concepts to describe natural reality in physics. Specifically, the analysis focuses on two major examples: Euler's exponential laws and spacetime dilation derived from Lorentz transformations. By examining these concepts, the paper emphasizes that some complex laws are not universally applicable for deeper studies of nature, as they originate from mathematics and are correct only for specific parts of nature to which they have been adapted. These complex laws are particularly unsuitable where there is limited information available for adaptation. Therefore, without appropriate adaptations and a deep understanding of the physical context under investigation, the direct use of complex laws can lead to incorrect results. It is essential to avoid excessive generalization of these laws, once they become part of physics, unless a corresponding adaptation to the research context can be made. Furthermore, this paper supports the correctness of relativity theories by invoking that, like Euler's exponential growth theory, they were initially mathematical concepts. However, the nature of mathematics coincided with that of the phenomena in our universe, although through certain adaptations.

This study examines stress distributions in adhesive joints under various loading and temperature conditions. Finite element analysis (FEA) was employed to compute the peel and shear stresses at the adhesive interface and bondline midpoint. The analytical solutions proposed by Goland and Reissner were analyzed with modifications by Hart-Smith and Zhao. FEA revealed stress distributions at the adhesive/adherend interface and bondline midpoint. DP490 adhesive joints exhibited lower stresses than EA9696 due to a lower Young's modulus and the use of thicker adherends. Temperature variations significantly affected joint behavior, particularly above the adhesive’s glass transition temperature (Tg). Both EA9696 and DP490 adhesive joints displayed distinct responses to stress and temperature changes. The comparison between parabolic and biquadratic solutions for functionally graded adhesive (FGA) joints showed that the biquadratic solution consistently yielded higher shear and peel stress values, with an increase ranging from 15% to 71% compared to the parabolic solution at various temperatures. Comparing stress distributions between peel and shear stresses, emphasizing the importance of selecting adhesives based on stress type, temperature, and solution methods in optimizing adhesive bonding applications. These findings provide valuable insights for thermomechanical applications where thermal stimuli may be used for controlled debonding.

This paper presents and demonstrates the development of a new lightweight coating for aluminium alloy using a novel multicomponent alloy based on the AlSiMgCu system. This coating was applied using a newly designed approach that combined High-Velocity Oxy-Fuel (HVOF) and Plasma Spraying processes. This hybrid technique enables the deposition of coatings with enhanced performance characteristics. The microstructure was studied using optical microscopy (OM) and scanning electron with energy dispersive X-ray spectroscopy (SEM+EDS) microscopy, revealing good adhesion and compaction between the multicomponent coating and the A6061 substrate with 50 to 150 µm thickness. Vickers indentations were performed on the substrate and the new coating material, revealing a 50% improvement in the material's hardness compared to the casted alloy. Additionally, electrical conductivity measurements showed approximative x3.3 times values compared to the alloy in as-cast condition due to high solidification rates altering the morphology of the phases. Corrosion tests demonstrated a lower corrosion rate compared to other multicomponent aluminium alloys and similar to thermal treated A6061 alloy. Finally, tribological results obtained using ball on disc (BOD) test and laser scanning confocal microscopy, confirmed that the new multicomponent coating exhibited reductions in both friction coefficient and wear rate by more than 20% and 50%, respectively. This study demonstrates that using multi-component aluminium coatings could lead to developing of new automotive parts with enhanced properties for corrosion resistance, electrical conductivity, and wear conditions. Optimizing the thermal spraying parameters could further enhance the coating, achieving greater and more homogeneous thicknesses and yielding even higher performance properties.

Commercial production of Choromytilus meridionalis (black mussel) and Mytilus galloprovincialis (Mediterranean mussel) contributes to half of the South African marine aquaculture production per year. However, limited ready-to-eat black mussel products are available. The aim of this preliminary study was to investigate the effects of storage (15 days at room temperature) on the total viable counts (TVC), coliforms, proximate composition, and fat oxidation (TBARS) of a small-scale kitchen-based ready-to-eat hot smoked black mussel product preserved with vegetable oil. Three batches of black mussel meat were smoked at 80ºC for 15 minutes. Half of each batch were packaged in sterile glass jars with heated (50ºC) vegetable oil and half without oil. Microbiological analyses were done at days 1, 3, 9 and 15. Proximate composition was determined at day 1 and TBARS at days 1 and 15. Coliforms for all samples throughout the storage period were undetected. TVC plates for mussels stored without oil had no growth at days 1 to 5, however, reached TVC > 5 log10.g-1 at day 15. TVC for mussels with oil increased from 0 at day 1 to > 5 log10.g-1 at day 3 and remained at counts > 5 log10.g-1. There was no significant difference (P > 0.05) in moisture, protein, and ash for mussels stored with oil and those without oil, while significant differences (P < 0.001) in total fat and carbohydrates (10.27 ± 2.10% and 6.80 ± 2.22% with oil, and 5.05 ± 1.49% and 10.59 ± 3.00% without oil) were detected. These differences were due to the presence of additional fats from the vegetable oil. TBARS at day 15 showed no significant difference (P > 0.05) between mussels stored with oil and those without oil. There were no significant differences in TBARS from day 1 to 15 for both oil and without oil. Small-scale kitchen-based smoked black mussels preserved without vegetable oil could be stored for up to 9 days at room temperature.

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

To meet the dual-carbon objective, China's economy needs to move from a carbon-intensive to a green economy. Green technology innovation and renewable energy development are key to promoting green economic growth. The study uses 2010–2022 provincial panel data from 30 Chinese provinces. The super-efficient SBM model measures the province's green economic growth index. A panel fixed-effects model is used to experimentally evaluate how green technology innovation and renewable energy development affect green economic growth. Green financing moderates and a panel threshold model tests the threshold effect of renewable energy development on green economic growth. The results demonstrate that (1) China's green economic growth is rising and has a "U" shape. (2) all selected variables significantly impact green economic growth. However, population density, government intervention, and industrial structure are inversely associated with GEG. Green economic growth is significantly boosted by the moderate role of green finance in the development of renewable energy and green technological innovation. (3) Renewable energy development has a single threshold non-linear effect on green economic growth, depending on its development level and green technological innovation. Considering China's current condition and research findings, this study examines the green energy transition to promote green economic growth and high-quality economic development. Meanwhile, puts forward some important policy recommendations.

Background: GaitSmart (GS) is a sensor-based digital medical device that can be used with the integrated app vGym to provide a personalised rehabilitation programme for older people undergoing total hip arthroplasty (THA) or total knee arthroplasty (TKA). This study aimed to determine whether the GS intervention used in the rehabilitation of older people undergoing THA or TKA is potentially cost-effective compared to the current standard of care (SoC). Methods: Decision-analytic modelling was conducted to estimate cost-effectiveness over a seventeen- week time horizon, from an NHS perspective. UK clinical and cost data from the GaitSmart randomised clinical trial was used to obtain input parameters, and sensitivity analysis was performed to address uncertainty. Results: Over a seventeen-week time horizon, GS incurred cost savings of £450.56 and a 0.02 gain in quality-adjusted life years (QALYs) compared to the SoC. These results indicate that GS is the dominant intervention because the device demonstrated greater effectiveness and lower costs. Probabilistic sensitivity analyses confirm the robustness of our results. Conclusion: GS appears to offer short-term efficiency benefits and demonstrates cost-effectiveness for the improvement of gait in people undergoing THA or TKA, compared to the SoC. These findings provided new evidence to inform policymakers.

We humans are natural-born engineers. As such, we model after machines not only isolated, naturally occurring systems, but also the basic laws of physics, sharing with machines a local-evolution-of-state `grammar'. However, previous work by the author casts doubt upon this mechanistic paradigm, suggesting that it is to blame for the stubbornness of many open problems in physics. Simple experiments are therefore proposed to identify `non-machines'. In one experiment, `non mechanistic correlations' in the spirit of Bell are sought in a pair of separated but previously coupled (macroscopic) chaotic systems. In another it is tested whether chaotic systems could fuzzily `remember their future' in the sense that a future binary perturbation applied to them could be inferred from their present behavior with probability>1/2. Chaotic systems are chosen as candidates because the long-time application of their (deterministic) mechanistic description is conceptually groundless: All scales are significant and mutually coupled in that regime, down to scales governed by QM, yet the quantum-classical transition remains inexplicable---if only due to the measurement problem. Similarly for non-deterministic chaotic systems, modeled as such purely for defying a short-time deterministic mechanistic description. Should a non mechanistic signature be found in such simple systems, the implications for science as a whole and life sciences in particular cannot be overstated.

The paper suggests that the physical priciple of special relativity's space-time transformation effect is wrong, Uniform linear motion without acceleration does not exist objectively, nor does its same reference frames. Therefore, it is inferred that the space-time transformation effect of special relativity is caused by the acceleration of moving objects, special relativity is only a part of general relativity, not a theoretical system that exists independently from general relativity. The corresponding mathematical demonstration and calculation verification are carried out, and the result proves that the inference of the paper is correct. At the same time, it further explains that the concept of absolute airspace is correct. Special relativity has serious errors in the concept of space, the principle of relativity and the physical principle of space-time transformation effect. Therefore, it is necessary to make a series of revisions to the theory of relativity and to reinterpret some related physical problems.

Throughout the Covid19 period, families were forced to stay indoors, adapting to online school-ing, remote work, and virtual social engagements, inevitably altering the dynamics within households. There is a notable increase in mental health challenges in terms of anxiety and de-pression in children and adolescents. This study intends to explore the psychosocial effects of the Covid-19 pandemic in Italian families adopting self- and proxy-report questionnaires on anxiety, anger, and health-related quality of life. The results showed that approximately 20% obtained a clinical anxiety score and only 10% obtained a clinical anger score. There was found a difference in the perception of the quality of life reported by the child and that perceived by the parent. The stepwise regression model showed that total anxiety scores were predicted by sex, quality of life scores from the parents' self-report version and total anger score. Another stepwise regression model identified physiological and social anxiety as the best predictors that impact the quality of life. Parental well-being actively influences the well-being of children, so it is fundamental to implement preventive programmes and promote child well-being providing parents the most adequate support possible.

Financial fraud poses a severe threat to the integrity of corporate financial statements and market efficiency. While auditors play a crucial role in detecting and preventing such fraud, the unique characteristics of this domain, including class imbalance, high misclassification costs, and am-biguous attributes, pose significant challenges. Traditional classification algorithms may not be optimally suited for this task. This paper proposes a novel stacking ensemble learning approach to enhanced detecting of Financial Statement Scam. By combining the strengths of multiple base learners, including Random Forest, XGBoost, and Gradient Boosting Decision Trees, our model leverages their diverse predictions to improve overall performance. A Logistic Regression me-ta-learner is employed to integrate the outputs of the base learners, capturing their collective wisdom while mitigating individual weaknesses. Extensive experimentation using a real-world dataset shown the superiority of our approach, achieving remarkable recall, precision, accuracy, and area under the curve metrics. The proposed model outperforms individual base learners, under-scoring the efficacy of ensemble learning in tackling the intricate problem of financial fraud detection. This research contributes to the creation of substantial and robust fraud detection systems, fostering trust and transparency in financial markets.

Though nowadays germanium do not reach the range of popularity than other metals, i.e. rare earth elements, its utility in target industries makes of it also a strategic metal. Though germanium can be find in a series of raw materials, the principal source for its recovery is from secondary wastes of the zinc industry, and also, the recycle of germanium-bearing waste materials is becoming of interest. In this recovery, Hydrometallurgy is performing a key role to the successful achievement of this goal. The present work reviews the most recent applications (2023 and 2024 years) of hydrometallurgical operations on the recovery of germanium from different solid and liquid sources.

Paratuberculosis, or Johne's disease, caused by Mycobacterium avium subsp. paratuberculosis (MAP), is a chronic granulomatous enteritis affecting both domestic and wild ruminants. The agent was also found in wild mammals such as wild boar (Sus scrofa), however, the role of wild mammals in the epidemiology of MAP is unclear. During the research period, 941 free-ranging wild boar (S. scrofa) legally hunted in two locations in the Centre-eastern region of Portugal were examined. Ninety-seven wild boar exhibited one or more gross lesions and were tested for the presence of Mycobacterium avium subsp. paratuberculosis using acid-fast staining, mycobacterial culture, poly-merase chain reaction (PCR), and histopathological examination. Forty-five animals (46.4%, 95% CI: 36.5-56.3%) were identified as infected, as indicated by positive results in culture and/or PCR. The findings revealed that the most significant risk factor was being a juvenile compared to year-lings and adults (OR = 10.2, 95% CI: 2.2-48.0). Based on our results, 37.9% (n = 11) of the infected animals were considered suitable for human consumption. Our findings offer novel insights into mycobacterial infections in wild boar populations in Portugal and suggest that wild boar could be a source of human infection if zoonotic potential is considered.

Objective. To evaluate serum neuronal and inflammatory biomarkers in asphyctic newborns treated with hypothermia alone or hypothermia plus melatonin, and whether biomarkers correlate with neurodevelopmental outcomes. Design. This is a pilot multicentre, randomised, controlled, double blind clinical trial. Neuronal glial fibrillary acidic protein (GFAP), granulocyte-macrophage colony-stimulating factor (GM-CSF), and inflammatory cytokines (interleukin (IL)-1, IL-2, IL-7 and IL-13) were measured in serum samples at hospital admission (T0), 24 hours (T1), 72 hours (T2) and 7-10 days of age (T3). Neurodevelopmental outcomes (Bayley Scales of Infant and Toddler Development-III scales, Gross Motor Function Classification System (GMFCS) and the Tardieu scale) were performed at 6 and 18 months. Setting: Level 3 neonatal intensive care unit. Patients and interventions: 25 newborns were recruited. The treated patients received a daily dose of intravenous melatonin, 5 mg per kg body weight, for 3 days. Results. After adjusting the data for severity, in the group treated with melatonin, there is a decrease in plasma levels of GM-CSF, IL-2 and IL-13 at T1 compared to placebo, as well as, at T2, in GM-CSF concentrations, as well as IL-7 and IL-13 at T3. Evolutionarily, we found a significant decrease in GM-CSF concentrations in the treatment group compared to placebo, with no differences for the rest of the biomarkers. It is noteworthy that the sustained decrease in GM-CSF and inflammatory cytokines IL-2, IL-7 and IL-13 correlated with better neurodevelopmental outcomes at 6 and 18 months. Conclusions. In neonates with hypoxic-ischemic encephalopathy, the addition of iv melatonin to hypothermia therapy affects the plasma concentration of biomarkers in the first week of life, with a high correlation with long-term neurological prognosis.

Hazelnut, pistachio and cashew are tree nuts with health benefits but also with allergenic properties being prevalent food allergens in Europe. The allergic characteristics of these tree nuts after processing combining heat, pressure and enzymatic digestion were analyzed through in vitro (Western blot and ELISA) and in vivo test (Prick-Prick). In the analyzed population, the patients sensitized to Cor a 8 (nsLTP) were predominant over those sensitized against hazelnut seed storage proteins (Sprot, Cor a 9 and 14), which displayed higher IgE reactivity. The protease E5 effectively hydrolyzed proteins from hazelnut and pistachio, while E7 was efficient for cashew protein hydrolysis. When combined with pressured heating (autoclave and Controlled Instantaneous Depressurization (DIC)), these proteases notably reduced the allergenic reactivity. The combination of DIC treatment before enzymatic digestion resulted in the most effective methodology to drastically reduce or indeed eliminate the allergenic capacity of tree nuts.

The therapeutic, attenuative, and morphological effects of proprietary neural stem cell-derived extracellular vesicles (NSC EVs, AB126) produced by Aruna Bio, Inc. were assessed in a range of in vitro and in vivo models of stroke. We emphasize that modulation of neuroinflammation is a key target and suggest further studies to advance our understanding of the mechanisms of action and ultimately how best to dose and monitor the benefits of AB126 in stroke patients.

Permafrost covers about 23% ~ 25% of the land in the northern hemisphere, mainly in Russia, Canada, Alaska, Northeast and Qinghai Tibet Plateau (QTP) in China. Many engineering especially the transportation has been in the permafrost regions above. Under the action of highways construction and global warming, permafrost under infrastructures is degraded and causes serious damage. Two phases closed thermosyphon (TPCT) is a widely accepted green countermeasure against the problem in permafrost regions. Although it has been applied to prevent permafrost degradation, their application presents significant challenges on account of the stronger endothermic action of asphalt pavement. This paper focused on the thermosyphon technology and application in the permafrost. Moreover, the article highlighted the excellent working performance of the TPCT that improving the stability of the infrastructures and prevent it degrading due its excellent efficiency of heat transfer. The industrial applications of the TPCT were also summarized, along with their limitations. Finally, the results reported in this paper can provide a valuable guidance for the design of the TPCT and construction of the permafrost regions in the future.

In "genome editing," a type of genetic engineering, DNA is added, taken away, or changed in an organism's genome. Biomedicine, biotechnology, and synthetic biology, just to name a few, have all gained a lot from how often this method is used. Before the editing process can start, a Double-Strand Breaks (DSB) must be made in the DNA at a specific gene. Researchers have made nucleases, which are sometimes called "molecular scissors," to fix this DSB. Transcription activator-like effector nucleases (TALENs), Zinc-finger nucleases (ZFNs), and homing endonucleases are all examples of protein targets that have been studied and changed. The last part gave an overview of these study projects and explained how to make Cas12a for specific uses. The applications of Cas12a have been extensively studied in recent years, but the protein still holds a lot of promise as a treatment and screening tool. In order to give a quick review of CRISPR-Cas12a and its uses, we will briefly talk about the structure and function of the different parts of the reaction pathway that lead up to the catalysis of the target DNA. Cas12a uses a multistep process to make sure that it is selecting the right DNA. This is a good trait for a device that changes the DNA because it makes it less likely that something bad will happen. Even though data shows that a new CRISPR RNAs (crRNA) molecule can stop Cas12a from randomly destroying ssDNA, it may still hurt the host cell while trying to change the genome. The action of Cas12a catalysis, which is a powerful tool for changing the genome, needs to be changed so that it can be more easily controlled and managed. Using what we know about how Cas12a works, we have made mutants that are less active on ssDNA and more active on dsDNA. So far, only Cas9 and Cas12a, which are both part of the CRISPR family, have been used to change the genome. Because of how similar and different these two endonucleases are, CRISPR can now be used for multiple scientific purposes. Cas12a is better than Cas9 because it makes double-strand breaks (DSBs) that favor Homology-Directed Repair (HDR) over Non-homologous end joining (NHEJ) and can change more than one copy of the genome at the same time. Both Cas9 and Cas12a are being changed to make them better at detecting Protospacer Adjacent Motif (PAM) than they are in their natural state. This will make it possible to start focusing on more genes.

This article describes a novel topical composition constituted by gamma-amino butyric acid (GABA) and microbial chondroitin sulfate. This composition exhibits potential for non-invasive intervention in anxiety management, sleep quality enhancement, and promotion of brain-related functions like meditation and nonlocal consciousness. The core component comprises GABA, a key inhibitory neurotransmitter within the central nervous system, complexed with a suitable carrier molecule, microbial chondroitin sulfate. This complexation aims to enhance transdermal absorption and optimize delivery of GABA to target tissues. The proposed mechanism of action involves modulation of GABAergic signal transduction pathways. Application of the topical composition allows GABA penetration into the skin and potentially deeper tissues, where it interacts with GABA receptors. This interaction leads to mental calmness and relaxation as assessed by electroencephalography. The influence of GABAergic signaling on brain circuits demonstrated in this article, when associated with meditation and nonlocal consciousness, suggests potential for the composition to support these practices. The advantage of such an approach consists in avoiding the potential systemic side effects associated with oral or injectable administration of GABA, anxiolytics or hypnotics. Furthermore, the combination of GABA and microbial chondroitin sulfate may offer synergistic benefits, potentially enhancing the overall biological effects. In conclusion, this article presents a novel topical approach for managing anxiety, enhancing sleep quality, and potentially facilitating meditation and nonlocal consciousness through modulation of GABAergic signaling pathways. While further research is necessary, the potential for a non-invasive and potentially side-effect-free intervention in these areas is promising.

Nanoindentation load-depth (P-h) plots is the basis for determination of mechanical properties of the samples and is especially vital for thin coatings deposited on substrates of various mechanical makeup from amorphous-brittle (borosilicate glass) to Silicon (having different crystallographic texture) to ductile substrates like stainless steel as well other aspects like indenter tip shape. The elastic-plastic response by simulated P-h plots as per modified empirical relations have been presented. The outcomes of this computational studies enlighten the database on the P-h plots for various coating/substrate systems and shall aid in the analysis of experimental P-h plots obtained,

Among other fossil fuels, natural gas is a major energy source. It is generally created saturated with water vapor. Dehydration of natural gas is vital in the gas business to remove water vapor from the gas supply, which may cause hydrate development in pipes. Gas dehydration employs Tri ethylene glycol (TEG) to remove water vapor from natural gas flow. The wet gas is dehydrated with lean glycol in an absorber, and the rich glycol is recovered and reused. This work investigates the use of dry natural gas instead of nitrogen in the glycol dehydration re-generator, and compares the results using HYSYS modeling and simulation. The two techniques were compared for capital and utility expenses, while maintaining the identical glycol purity criteria. The wet gas from the stripping mechanisms may also be utilized to run steam pumps and compressors or recycled. The model is based on the real mechanism flow diagram. Finally, the findings of this model might be used to design a new heat and material balance for the plant.

Solid-state transformer (SST) is a promising technology for smart grids due to its flexible power control (better reliability) and high efficacy (by decreasing losses) compared with traditional transformers. The SST is designed in tandem with three stages, i.e., the input, isolation, and output stages. As three converter stages are used to design the SST to make a more reliable device in practice, it is highly prone to instabilities. Moreover, the key objective of SST design is to implement a modern power distribution system to make it more intelligent and reliable. The stability issue can be even more complicated by the presence of distributed energy resources in the distribution system. Thus, the stability of SST must be measured prior to /during the design, and to determine, a state-space model is used, which is developed in this paper. Each stage of SST is modeled with its controller, and the system's stability is measured through the controllability and observability test. Further, the conversion from state-space to transfer function model is done, and the stability of SST is shown using frequency and time-domain diagrams. With these, the different plots, namely, the Bode plot, Nyquist plot, Nichols chart, Root locus, pole-zero plot, and Eigen plot, are used to ascertain the relative and absolute stability. Finally, the SST Simulink model is tested and validated through hardwate-in-the-loop simulation, i.e., OPALRT, to show its effectiveness and applicability.

Traditional methods of non-metallic materials joining for industrial uses are limited to lasers, or induction or conduction heating. The precision and efficiency for large-scale applications are difficult to be achieved at the same time. Here in this paper, we report a precise microwave welding method induced by localized surface plasmon of metallic macro-gaps under microwave excitation. The proposed method utilizes energy from well-developed commercial microwaver, and benefits from the precision of localized surface plasmon, an oscillating electron cloud excited by electromagnetic waves, which is currently under hot investigation only at micro- or nano-scales. The method is applied to the welding of polymers to solve the problems of complex processing equipment and high processing energy consumption in the traditional welding process, so as to cope with the growing energy and environmental crisis. Finite element numerical simulations are used to study the distribution characteristics of electric fields and temperature fields. The results show that the process is a high quality, efficient, low consumption and environmentally friendly green process compared to traditional polymer welding methods.

The cycling of soil phosphorus (P) is inherently linked with soil organic carbon-iron (C-Fe) cycling, yet empirical integration of these processes within paddy soils remains scarce. In this study, we conducted a microcosm experiment using paddy soils subjected to six distinct fertilization regimes involving varying P inputs for five years. In addition to evaluating P activation under reflooding conditions, we assessed the Fe reduction process and characterized the properties of dissolved organic matter (DOM) at the molecular level using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), alongside profiling the composition of soil microbial communities with high-throughput sequencing. Our findings revealed that after 25 days of reflooding, soil Olsen-P content increased by an average of 73% compared to its initial state, showing a strong correlation with the Fe reduction process. Specifically, treatments involving pig manure application exhibited higher Fe reduction rates and enhanced P activation, highlighting the role of organic matter in facilitating Fe reduction. Investigations on the relative abundance of typical iron-reducing microbes further supported their importance in P activation, but the rate of iron reduction is limited by soil organic matter content. Delving deeper into DOM properties, soil DOM composition profiling and network analysis suggested that high-molecular-weight DOM, particularly lignins, served as the primary resources driving Fe reduction by iron-reducing microbes, consequently promoting Fe reduction and P release. Taken together, our study assembled the C-Fe-P cycling dynamics in paddy soils, emphasizing the pivotal role of microbial-driven Fe reduction facilitated by soil DOM in P availability and subsequently sustainable agricultural practices.

This study investigated how broader parental factors including parental happiness, parental play engagement, and parenting stress are related to Korean children’s happiness and weight status across three years via indirect pathways through the children’s energy-related behaviors of healthy and unhealthy food intake, physical activity, and screen time. Data from 1551 Korean parent pairs and 7-yaer-old children in the Panel Study on Korean Children were analyzed. Path analysis and gender-based structural equation modeling were conducted. Maternal happiness was negatively related to child screen time. Maternal play engagement showed positive concurrent associations with child healthy food intake and physical activity and negative associations with screen time. Maternal parenting stress was negatively related to child healthy eating. There was one significant finding related to fathers’ role on children’s energy-related behaviors, happiness, and weight status: the positive association between parental happiness and boys’ unhealthy food intake. Child screen time was positively related to child weight status and negatively to child happiness at each age. Broader maternal parenting factors can serve as a protective factor for childhood happiness and weight status in 7-to 9-year-olds through being associated with a reduction in child screen time.

The decade of research concentrating on the area of Easter Slavonia revealed abundance of large on complex late Neolithic sites. It changed profoundly how we perceive late Neolithic settlement and space size and organization. As s first step in particular site detection we mostly conducted aerial reconnaissance and satellite image analysis but also data from the field such as excavation. On detected potential sites we conducted intensive field surveys and confirmed the attribution to the late Neolithic by surface finds. On those confirmed sites in the vicinity of Đakovo, Croatia, magnetic survey was conducted on 5 sites so far and the results confirmed presence of large scale late Neolithic settlements with complex spatial organization and enclosure(s). Most complex remains so far is site Gorjani Kremenjača and Topole which we present in this paper where a remains of one or two settlements covers the area of 70 hectares and is currently in the process of formal protection as a cultural landscape by the Ministry of Culture and Media of the Republic of Croatia. Special focus of the paper is the application of remote sensing in detection, archaeological confirmation and protection of the position Gorjani Topole.

Background: Poisoning is a growing public problem that has shown increased prevalence in many countries worldwide, contributing to increased costs and mortalities. A lack of or insufficient information regarding the circumstances, chemicals, drugs and people at risk due to imperfect reporting system is regarded as a barrier to successful poisoning prevention and intervention efforts. In Saudi Arabia, poisoning cases are monitored at the central level in the Ministry of Health, with meticulous follow-up of cases across country areas through public health departments. The current study's objective was to describe the poisoning notification and reporting system in Makkah.Subjects and methods: All reports of chemical and drug overdose poisoning delivered to the environmental health and occupational safety department in Makkah Almukarramah over two years (2018-2019) were reviewed, together with verification of all systems, rules and guidelines organizing the performance of the department.Results: The total number of cases reported in 2018 was 209 cases, while it reached 42 cases in 2019. The overwhelming majority of the cases were Saudi (91.6%), with a slight predominance of males (57.4%) over females (42.6%). Generally, almost two-thirds of the cases occurred in children below 13 years (61.4%), most of the poisoning cases resulted from drug overdose (63.3%), while 34.7% were chemical poisoning. The most common drug poisoning was attributed to analgesics followed by antiepileptics, antihypertensive drugs, antipsychotics and antimicrobials, while cleaning and detergent agents were the most commonly poisoned chemicals. The majority of these agents were taken by the oral route. Children's chemical poisoning was significantly higher than that in older age groups (p<0.05). All intentional poisoning occurred in adults; the great majority of them (88.9%) used drug overdosing rather than chemical substances.Conclusion and recommendations: The current study results are consistent with most of the previous studies carried out in different regions in Saudi Arabia. Reviewing the performance and adherence of the “Environmental Health and Occupational Safety Department” to the guidelines and instruction regulating monitoring, notification and reporting of poison cases are satisfactory and the poisoning surveillance system is effective. Further in-depth studies are needed to elaborate other socioeconomic and demographic factors associated with chemical and drug overdose poisoning. Public health plans, policies and legislations should be implemented to reduce these factors, including prohibition over-the-counter pharmaceutical sales, selling the possibly harmful substances in kid-proof bottles and additional stringent rules governing chemical sale and storage. Intensive supervision of children is needed. Suicidal poisoning patients should seek psychiatric help to limit the possibility of attempting suicide again in the future. Furthermore, efforts are needed to plan and implement health education programs and campaigns about the factors proven in the current study to be significantly related to chemical and drug overdose poisoning to raise public knowledge about exposure to chemicals and its consequences. Popular communication media, commercial malls, road ads, learning institutions and workplaces can be used to deliver health education campaigns and programs. Advice on how to store chemicals safely and how to keep kids safe should be focused on during such programs.

The different systems in the nuclear power plants (NPP) are critical and complex which requires a continuous rigorous monitoring for both normal and abnormal conditions. However, due to the nonlinearity of the dynamic behavior of these systems, implementation of artificial intelligence within the NPP components is crucial to enhance the monitoring and the predictability of the key operating parameters trend. On the other hand, lessons learned from large nuclear accident proves that a remote real-time coordination between the different stakeholders involved in the safety of the nuclear reactor is needed. This remote feature can be implemented in the existing power plants by embedding a mobile computing networks within the plant components. This network will send early warning and transmit the NPP data on real-time to different authorities such as the regulatory authority and the decision-making committees, to enhance the interpretability of the nuclear event and deliver a collaborative decision which in return mitigate the risk associated with these events and increase the overall safety of the plant. The integration of AI and mobile computing in NPP would be most of interest in countries where nuclear reactors data are challenged to reach during an accident. For instance, during the meltdown of Chernobyl, the Soviet government covered the accident from the news in an attempt to contain the consequences but there was a spread of radioactive contamination to some other Europe countries. Therefore, in the case of such scenario the implementation of mobile computing and AI would result in different outcomes as the European countries would be notified through the mobile networking and the spread of contamination would be forecasted by the AI algorithms. In this paper, we examine the different modern AI and mobile computing technologies, the different potential application, the associated features and challenges, and future work direction.

Reducing fertilizer-N rate, applying nitrification inhibitor (NI), and incorporating straw are widely recommended to improve N use efficiency of crops and decrease N losses. However, how these practices affect crop N uptake by regulating the fertilizer-N fate during the growing season is not well understood. We conducted a field 15N tracer study to explore the effectiveness of reduced N application, NI, and straw incorporation on fertilizer-N fates for maize cultivation in Northeast China. The following six treatments were used: 1) no N fertilization (control); 2) 200 kg urea-N ha−1 (100%N); 3) 200 kg urea-N ha−1 and 2400 kg dry-straw ha−1 (100%N+S); 4) 160 kg urea-N ha−1 (80%N, i.e., 20% reduction of N fertilization); 5) 160 kg urea-N ha−1 and nitrification inhibitor (Nitrapyrin) (80%N+NI); 6) 160 kg urea-N ha−1, nitrification inhibitor and 2400 kg dry-straw ha−1 (80%N+NI+S). Our results showed that the five N fertilization treatments yielded 16%–25% more grain and 39%–60% more crop N uptake than the control receiving no N fertilizer, but the differences among the five treatments were not statistically significant. In contrast to plant growth, changes in fertilizer-N fates in soil and plant pools were more pronounced. Compared with the 100%N treatment, 20% fertilizer-N reduction (80%N) decreased 15N concentration in topsoil and plant pools but increased the proportion of plant 15N recovery at harvesting (N use efficiency, NUE15N, 60% vs. 50%) (P &lt; 0.05). Nitrapyrin co-application (80%N+NI) delayed soil nitrification and increased soil 15N retention at harvesting (52% vs. 36%), thereby decreasing NUE15N significantly (P &lt; 0.05). Straw incorporation (100%N+S) decreased fertilizer-N retention compared with NI co-application because it promoted NUE15N significantly (P &lt; 0.05). The combined application of NI and straw (80%N+NI+S) was more conducive to fertilizer-N retention in soil. Our findings demonstrate that NI and straw additions are efficient strategies for stabilizing fertilizer-N in soils and potentially minimizing N loss; however, their effects on NUE15N vary and the related mechanism must be further clarified in long-term trials.

There is currently no effective treatment strategy for the recurrent/metastatic adenoid cystic carcinoma (R/M ACC). Furthermore, recent single-agent and combination immunotherapy trials have failed in unselected ACC cohorts unlike non-ACC salivary gland cancers. Genomic profiling revealed no actionable targets but NOTCH1 and KDM6A frameshift and CTCF splice site mutations (no MYB/L fusion) with a low TMB, MSS and negative PD-L1. We recommended anti-PD-1 plus anti-CTLA-4 combination based on TMB 2-fold greater than median TMB in ACC, tumor harboring multiple immunogenic frameshift or splice site mutations, and PD-L1 negativity. Accordingly, we achieved a complete response in a radiotherapy and chemotherapy-refractory patient with locally recurrent lacrimal gland ACC and lung metastasis following personalized immunotherapy in combination with integrative therapeutics. Therefore, it is crucial to assess not only conventional immune biomarkers but also patient-specific parameters.

Immune checkpoint inhibitors (ICIs), including anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) and anti-programmed death-1 (PD-1) antibodies, have initiated a new era in the treatment of malignant melanoma. ICIs can be used in various settings, including as first-line, adjuvant, and neoadjuvant therapy. In the scope of this review, we examined clinical studies utilizing ICIs in the context of treating oral mucosal melanoma, a rare disease albeit with an extremely poor prognosis, with a specific focus on unraveling the intricate web of resistance mechanisms. The absence of a comprehensive review focusing on ICIs in oral mucosal melanoma is notable. Therefore, this review seeks to address this deficiency by offering a novel and thorough analysis of the current status, potential resistance mechanisms, and future prospects of applying ICIs specifically to oral malignant melanoma. Clarifying and thoroughly understanding these mechanisms will facilitate the advancement of effective therapeutic approaches and enhance the prospects for patients suffering from oral mucosal melanoma.

Pregnancy associated plasma protein-A (PAPP-A) plays an integral role in breast cancer (BC), especially triple negative breast cancer (TNBC). This subtype accounts for the most aggressive BC, possesses high tumor heterogeneity, is least responsive to standard treatments and has the poorest clinical outcomes. There is a critical need to address the lack of effective targeted therapeutic options available. PAPP-A is a protein that is highly elevated during pregnancy. Frequently, higher PAPP-A expression is detected in tumors than in healthy tissues. The increase in expression coincides with increased rates of aggressive cancers. In BC, PAPP-A has been demonstrated to play a role in tumor initiation, progression, metastasis including epithelial-mesenchymal transition (EMT), as well as acting as a biomarker for predicting patient outcomes. In this review, we present the role of PAPP-A, with specific focus on TNBC. The structure and function of PAPP-A, belonging to the pappalysin subfamily, and its proteolytic activity are assessed. We highlight the link of BC and PAPP-A with respect to the IGFBP/IGF axis, EMT, the window of susceptibility and the impact of pregnancy. Importantly, the relevance of PAPP-A as a TNBC clinical marker is reviewed and its influence on immune-related pathways are explored. The relationship and mechanisms involving PAPP-A reveal the potential for more treatment options that can lead to successful immunotherapeutic targets and the ability to assist with better predicting clinical outcomes in TNBC.

Immune checkpoint inhibition therapy (ICIT) is an emerging field in oncology especially opening new horizons to chemotherapy refractory patients. This paper provides deep insight into immune related adverse events (irAEs) posing a major challenge and drawback to ICIT, and presents right management strategies for very complex complications. Moreover, for the first time in literature, a non-linear mathematical model is introduced to measure the ICIT success rate and to decide about the optimum ICIT duration. Furthermore, a strategy is presented to overcome or to delay the progression after initial good response in a subset of patients.

Background/Aim: To evaluate the association between baseline [18F]FDG-PET/CT tumor burden parameters and disease progression rate after first-line target therapy or immunotherapy in advanced melanoma patients. Materials and Methods: 44 melanoma patients who underwent [18F]FDG-PET/CT before first-line target therapy (28/50) or immunotherapy (16/50) were retrospectively analyzed. Whole-body and per-district metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were calculated. Therapy response was assessed according to RECIST 1.1 on CT scan at 3 (early) and 12 (late) months. PET parameters were compared with Mann-Whitney test. Optimal cut-offs for predicting progression were defined using the ROC curve. PFS and OS were studied using Kaplan-Meier analysis. Results: Median(IQR) MTVwb and TLGwb were 13.1 mL and 72.4 respectively. Non-responders patients were 38/44, 26/28 and 12/16 at early evaluation, and in 33/44, 21/28 and 12/16 at late evaluation in the whole-cohort, target and immunotherapy subgroup respectively. At late evaluation, MTVbone and TLGbone were higher in non-responders compared to responder patients (all p<0.037) in the whole-cohort and target subgroup and also MTVwb and TLGwb (all p<0.022) in target subgroup. No significant differences were found for immunotherapy subgroup. No metabolic parameters were able to predict PFS. Controversy, MTVlfn, TLGlfn, MTVsoft+lfn, TLG-soft+lfn, MTVwb and TLGwb were significantly associated (all p<0.05) with OS in both the whole-cohort and target therapy subgroup. Conclusion: Higher values of whole-body and bone metabolic parameters were correlated with poorer outcome, while higher values of whole-body, lymph node and soft tissue metabolic parameters were correlated with OS.

Programmed cell death protein 1 (PD-1) is a biomarker on the surface of cells that has a role in promoting self-tolerance by suppressing the inflammatory activity of T cells. In this work, one peptide of PD-1 was used as the template in molecular imprinting. The magnetic peptide-imprinted poly(ethylene-co-vinyl alcohol) composite nanoparticles (MPIP NPs) were characterized by dynamic light scattering (DLS), high-performance liquid chromatography (HPLC), Brunauer-Emmett-Teller (BET) analysis and superconducting quantum interference device (SQUID) analysis. Natural killer-92 (NK-92) cells were added to these composite nanoparticles and then incubated with human hepatoma (HepG2) cells. The viability and apoptosis pathway of HepG2 were then studied using cell counting kit-8 (CCK8) and the quantitative real-time polymerase chain reaction (qRT-PCR), respectively. These nanoparticles were found significantly enhance the activity of natural killer cells toward HepG2 cells by increasing expression of NK-kB, caspase 8 and especially caspase 3.

a Special Issue of Microorganisms devoted to ‘Microbial Biocatalysis and Biodegradation’ would be incomplete without some form of acknowledgement of the many important roles that dioxygen-dependent enzymes (principally mono- and dioxygenases) play in relevant aspects of biooxygenation. This is reflected by the multiple strategic roles that dioxygen -dependent microbial enzymes play both in generating valuable synthons for chemoenzymatic synthesis, and in facilitating key reactions that drive the global geochemical Carbon Cycle. A useful insight into this relationship can be gained by reviewing the evolution of the current status of 2,5-diketocamphane 1,2-monooxygenase (EC 1.14.14.108) from camphor-grown Pseudomonas putida ATCC 17453. Over the last sixty years, the perceived nature of this monooxygenase has transmogrified significantly. Commencing in the 1960s, extensive initial studies consistently reported that the enzyme was a monomeric true flavoprotein dependent on both FMNH₂ and nonheme iron as bound cofactors. However, over the last decade all those criteria have changed absolutely, and the enzyme is currently acknowledged to be a metal ion-independent homodimeric flavin-dependent two-component monooxygenase deploying FMNH₂ as a cosubstrate. That transition is a paradigm of the ever evolving nature of scientific knowledge.

Flexible surgical robots are emerging as advanced tools for minimally invasive surgeries, offering greater versatility compared to traditional rigid robots. Unlike commercial endoscopes, the overtube should remain fixed to maintain stability, ensure a clear field of view, and allow surgical tools to perform tasks efficiently. While constant curvature bending of the overtube is sufficient for some lesions, certain lesions require the overtube to bend into specific shapes to achieve appropriate positioning. Various methods for creating different bending shapes have been proposed in previous research, typically involving connecting multiple segments. However, this approach complicates control and reduces both space and cost efficiency. This study proposed a conceptual method for adding a shaping tendon to control the bending shape and mathematically analyzed the effect of this shaping tendon, inserted along an arbitrary path in addition to the main driving tendons for constant curvature bending, on the bending shape of the hyper-redundant manipulator with rolling joints. The overall system was modeled and analyzed from an energy perspective, and the validity of the proposed mathematical modeling was verified through comparison with results obtained from physical experiments. In addition, it was identified that the design parameter determining the tendon path is significant element in defining bending shape of the overtube.

As modern technology enables instant access to virtually limitless information, students may perceive memorization of information as lacking in practical importance. The current study investigated the relationship between attitudes toward remembering and metamemory as well as objective memory performance. University students completed the Importance of Remembering questionnaire (IORQ) as a measure of attitudes toward remembering. Subjective components of memory were measured by immediate and delayed judgements of learning (JOLs), global judgements of learning (global JOLs), retroactive confidence judgements (RCJs), as well as subjective mental workload. Objective memory performance was measured using a cued recall test. The IORQ was only significantly correlated with absolute accuracy of delayed judgements of learning for words and pictures such that higher IORQ ratings were associated with less accurate judgments about how well they learned the items. No other correlations were significant. This suggests that a student’s lack of belief in the importance of remembering, at least as conceptualized on the IORQ, may not affect most aspects of memory performance, including those related to academic outcomes.

Background. One of the most important prognostic factors in periampullary and pancreatic cancers is perineural infiltration, whose preoperative detection could be decisive in selecting which patients should not undergo upfront surgery. We evaluated CA 19.9 and the Neutrophil-to-lymphocyte ratio (NLR) as preoperative predictors of perineural invasion (PNI). Methods: Retrospective analysis including patients with periampullary and pancreatic cancers who underwent curative resection from January 2013 to August 2023 in our institution. A univariate analysis and multivariate analysis were performed to analyze the association between the CA 19.9 and NLR with the existence of PNI. Results: A total of 136 patients were included in the study. PNI was observed in 95 (69.9%) patients. The selected cut-off points were NLR: 2.2 and CA 19.9: 37 U/mL. In univariate analysis, NLR (p=0.001) and CA 19.9 (p=0.006) were statistically significantly associated with PNI. In multivariate analysis, baseline NLR levels (p=0.012; OR: 1.95; 95%CI: 1.16-3.29) as well as CA 19.9 levels (p=0.026; OR: 1.67; 95%CI: 1.06-2.64) remained independent prognostic factors for PNI. The area under de ROC curves was 0.67 for CA 19.9 (p=0.004) and 0.72 for NLR (p<0.001). A sensitivity of 65.9% with a positive predictive value of 81.7% were obtained for CA 19.9, and a sensitivity of 62.1% with a positive predictive value of 84.3% were achieved for NLR. Conclusion: Preoperative CA 19.9 and NLR levels seem to be good predictors of PNI. In patients with normal levels of CA 19.9, preoperative NLR above of 2.2 should be an indication for neoadjuvant therapy.

.Citizen or community science (CS) projects in the marine environment rarely consider carbon footprint and sustainability. In this case study, we assessed the effectiveness of ten CS methods used by tourists in the Great Barrier Reef Marine Park (GBRMP) and Coral Sea Marine Park (CSMP). We also assessed baseline coral reef knowledge of the tourists, observations of marine species and the communication of our results to the public. Specifically, the tourists utilised up to ten methods: iNaturalist, CoralWatch, Great Barrier Reef Census, Eye on the Reef (EoR), environ-mental DNA (eDNA) testing kits, photogrammetry, social surveys, and Red Map, as well as ma-rine debris and marine vegetation collections. A total of 10,421 data points were collected across 14 days, including 5,390 records (52 % of the total) uploaded to iNaturalist, comprising 640 plant animal species. Public awareness of the CS expedition reached over 700,000 people based on estimates from advertising, media, social media, family and friends, and conference presenta-tions. We estimated the total carbon footprint for the expedition as 268.7 tonnes of CO2 or 4.47 tonnes of CO2 per person, equivalent to $112 AUD needed to offset this input. Based on these re-sults, our recommendations to leverage CS methods include governmental review strategies, temporal replication to allow the measurement of changes through time, integrating sustainabil-ity into CS ecotourism platforms, and encouraging broad participation.

Pastırma is an ethnic meat product defined as dry-curing, drying, pressing the whole muscles of cattle and buffalo, and coating them with a special paste containing fenugreek seed flour, garlic, milled red capia pepper, and water. In this narrative literature review, historical aspects of pastırma, its definition and classification, detailed production steps, composition and yield, chemical and microbiological properties, pastırma fraud and customer concerns are mentioned. In the shape of the narrative review, relevant studies were identified by searching Scopus, Science Direct, Web of Science, Trdizin, and Google Scholar Search included English- or Turkish-based articles, online reports, books, and electronic books. The keywords "pastırma, pastirma, çemen, cemen, cemening, cemen paste, Fenugreek" were used. The results of this review indicate that future studies on pastırma may focus on related cultural aspects, elimination of unpleasant odour from fenugreek, histological and chemical effects of pressing meat parts, kinetics of drying, osmotic dehydration, and developing new starter combinations.

A new 2 parameter unit Weibull distribution is defined on the unit interval (0,1). The methodology of deducing its PDF, some of its properties and related functions are discussed. The paper is supplied by many figures illustrating the new distribution and how this can make it illegible to fit a wide range of skewed data. The new distribution holds a name (Attia) as a nickname.

The basic helix-loop-helix (bHLH) transcription factor family, is the second-largest superfamily in plants after MYB, which plays a significant role in the physiological processes of plant growth, tissue development, and environmental variation. However, the systematized study of the bHLH transcription factor family has not yet been conducted in A. catechu. Herein, we conducted genome genome-wide investigation of AcbHLH genes located on 16 chromosomes of A. catechu. A phylogenic tree was constructed to adjudge their homology of genes, and 24 subgroups were identified. Finally, we analyzed the dynamic changes of gene-expression levels of nine AcbHLH genes in response to drought and salt in leaves and roots. The expression patterns of 9 AcbHLH genes show differences in leaves and roots. Under stress conditions induced by salt and drought, AcbHLH22, AcbHLH62 and AcbHLH45 are significantly upregulated in both leaves and roots. In conclusion, this study will substantially contribute to the foundation for exploring the role of the bHLH superfamily in A.catechu in dealing with abiotic stresses.

This study presents a novel investigation into the use of Light Emitting Diodes (LEDs) for the in vitro rooting of 'Marubakaido' and 'M9' apple tree rootstocks, marking the first time this approach has been reported in the literature. The research compares four different light sources: blue LED (450 nm), red LED (660 nm), a combination of red and blue LEDs, and traditional fluorescent lamps as a control. Mini-cuttings were inoculated in Murashige &amp; Skoog (MS) medium with reduced nutrient concentrations and supplemented with indoleacetic acid (IAA) and sucrose. The explants were incubated under controlled conditions for 30 days, allowing for a thorough evaluation of the effects of different light sources on various growth metric. The study found that blue LEDs significantly increased dry mass accumulation in 'Marubakaido' seedlings compared to both red LEDs and fluorescent lamps, demonstrating the effectiveness of LEDs in promoting plant growth. Utilizing LEDs not only enhances seedling development but also offers economic benefits over fluorescent lamps. LEDs are known for their high luminous efficiency, low energy consumption, and long lifespan, which can lead to reduced operational costs in plant production systems. This research not only contributes to the understanding of light effects on plant tissue culture but also suggests that the combination of blue and red LEDs can serve as a viable alternative to fluorescent lamps, potentially transforming practices in the field of horticulture and plant propagation.

This study explores the potential of Federated Learning (FL) to facilitate the sharing and collaboration of medical data in drug development under the premise of privacy protection. While traditional centralized data processing methods limit effective collaboration across agencies due to data privacy and compliance concerns, federated learning avoids the risk of privacy breaches through a distributed architecture that allows participants to train artificial intelligence (AI) models together without sharing raw data. This paper systematically describes the core mechanism of federated learning, including the key technologies such as model parameter updating, differential privacy and homomorphic encryption, and their applications in drug development and medical data processing. Examples, such as NVIDIA Clara's Federated learning application and COVID-19 resource prediction, show that federated learning improves the efficiency of multi-party collaboration and model performance while ensuring data privacy. In addition, this study explores the scalability and generality of federated learning in the medical field, and points out that the technology is not only suitable for drug development, but also has broad cross-industry application potential, especially in areas such as finance and insurance, where data privacy is critical.

Parental willingness is a prerequisite for childhood immunization. This study evaluated whether parental vaccination readiness and willingness, measured using the modified Japanese 7C Vaccination Readiness Scale, predicted vaccination behavior. In December 2021, 2 months before the approval of COVID-19 vaccination for children aged 5–11 years in Japan, we asked 1,190 parents of children in this age groups about their intention regarding vaccinating their children against COVID-19 using an online modified 7C Vaccination Readiness Scale, consisting of seven components, namely, Confidence, Complacency, Constraints, Calculation, Collective responsibility, Compliance, and Conspiracy. The modified 7C components were analyzed for model fit and association with parental intention using structural equation modeling. The model fit of the modified 7C scale was good (goodness-of-fit index: 0.98), and the factor loadings and model fit for parental readiness were high (standardized factor loadings: 0.84). In January 2024, we asked the same parents about their children's COVID-19 vaccination status (valid responses: 536). The components of the modified 7C scale were compared with actual vaccination behavior. Parents with a low readiness to vaccinate their children against COVID-19 had a high actual non-vaccination rate. The use of the modified 7C scale may assist in the development of childhood vaccination interventions.

In the context of constructing new power systems, distribution networks are increasingly incorporating distributed resources such as distributed photovoltaic (PV) systems, decentralized wind turbines (WT), and new types of energy storage system (ESS), which may lead to prominent issues such as voltage overruns and reverse heavy overloads in the distribution network. While distributed resources are valuable for voltage regulation, their regulation characteristics vary with their operation means, and the randomness and volatility of renewable power generation will also influence the optimization and regulation of voltage in the distribution network. This paper proposes a multi-time scale reactive power optimization and regulation method for distribution networks in a multi-source interactive environment. Firstly, the voltage regulation characteristics of distributed PV systems, decentralized ES, and distributed WT are analyzed. Based on this analysis, then a multi-time scale voltage optimization scheme for distribution networks using MPC method is proposed, which optimizes the voltage regulation strategies for each distributed resource in a rolling manner. Furthermore, an event-triggered real-time voltage zoning control strategy based on voltage sensitivity is proposed to address the real-time sudden voltage overlimit problems. The modified IEEE 33-node system is used to verify the performance of proposed method, simulation results indicate that the issue of voltage overruns at distribution network nodes has been improved, and the intraday rolling optimization yields results that are more realistic compared to the day-ahead optimization method.

The learning system is primarily based on teaching, and teaching through digital resources is referred to as e-learning. As the world progresses towards success day by day, the use of technology, digital devices, and modern techniques is becoming increasingly prevalent. The global shift from traditional paperwork to digital learning is one of the most significant changes in the education sector. However, many factors have created numerous hurdles during the online setup. The Covid-19 pandemic has led to serious problems all over the world, with the education sector being one of the most affected. One of the greatest challenges students face during online education is the lack of digital infrastructure, especially in remote areas of Pakistan. The biggest challenge is connecting students with teachers due to limited internet access. Without proper internet connectivity, both students and teachers cannot access educational materials. In this context, the government plays a crucial role in providing adequate facilities to students, particularly in primary schools. If proper infrastructure is not made available during this pandemic, students will be deprived of a good quality education. Therefore, good infrastructure is essential for effective online education. With the proper resources in place, students will be able to receive a quality education.

Chitosan spherical scaffolds, derived from the deacetylation of chitin, are natural polymers with significant potential, though challenges remain in optimizing their properties. The use of chitosan as a carrier for the controlled release of iron chloride is not yet fully established, despite iron’s critical role in various essential biological processes, including as a component of metalloenzymes and in the maintenance of life. Methods: This study aimed to develop a novel protocol for synthesing chitosan scaffolds and to characterize their properties using analytical techniques. Additionally, the release profile of iron was modeled using two primary controlled-release mathematical models. Results: The results demonstrated successful synthesis and physicochemical characterization of the chitosan sphere scaffolds. These scaffolds exhibited appropriate topography for iron loading and cellular interaction, as confirmed by SEM analysis, and contained functional groups as identified by FTIR. The scaffolds were also semi-crystalline (XRD), showed controlled degradation, and were confirmed to be non-toxic biomaterials. Furthermore, the modeling of the controlled release of iron chloride adsorbed on the scaffold surface, as well as the modeling of iron chloride specimens using the MEDUZA software, was successfully conducted. A theoretical curve was generated from the experimental dose-response data collected over time, considering variations in pH and medium concentration. Conclusions: In conclusion, a novel protocol for chitosan-based carriers was successfully developed, enabling thorough physicochemical characterization and modeling of both absorption and controlled release.

The modern world is gradually moving towards a global civilisation that is automated and propelled by technology. Artificial intelligence (AI) is a highly advanced technology that has been acknowledged as a major innovation. The incorporation of this technology into the banking sector has enhanced operational procedures in relation to customer satisfaction, virtual assistance, and risk reduction. This machine is employed to streamline activities and improve how decisions are made in this sector. This study investigates the potential benefits and challenges of implementing artificial intelligence in the banking sector. The methodology ensures a comprehensive understanding of the implementation of artificial intelligence in banking by showcasing its effectiveness, precision, and efficiency, as well as the opportunities it presents. The study data were collected from secondary sources, such as recent publications that demonstrate applications of artificial intelligence from five different banks, as well as the examination of industry reports. The main findings of this study demonstrate the substantial improvement of administrative operations through AI-driven technology, which effectively automates activities that include inputting data and handling information. As a result, the frequency of mistakes caused by people has reduced, leading to a 30% decrease in operational expenditures for all evaluated institutions. However, the banking industry admits the challenges it encounters, such as issues with confidentiality and a scarcity of skilled employees. In the financial services industry, the integration of artificial intelligence into the banking sector is perceived as an advantageous chance instead of a harmful danger, with a greater potential for beneficial impact.

Urbanization degrades natural habitats and creates new urban ecosystems, like domestic gardens. The plant composition of these gardens varies with socio-economic factors and urban planning levels. However, the diversity and impact of introduced species are often poorly assessed, causing potential ecological imbalances, particularly in Lubumbashi (DR Congo). The objective was to analyze the spatial structure, plant diversity, propagation strategies, and ecological functions of domestic gardens. Three distinct neighborhoods were selected: planned, unplanned and residential neighborhood. 20 avenues (with 5 plots per avenue) were chosen to represent the diversity within each neighborhood, and stratified random sampling of plots was conducted to analyze gardening practices. Gardens were classified into types, and their vegetation was evaluated based on species origin and ecological impact. The analysis of domestic gardens in Lubumbashi reveals significant variations across different neighborhood types. Residential neighborhoods exhibit larger average garden sizes (315.1 m²), higher species richness (22 species), and larger plot sizes (1032 m²) compared to unplanned and planned neighborhoods, where garden areas and species richness are notably lower. Rectangular gardens dominate in unplanned areas, while planned neighborhoods feature more intentional landscaping elements, such as flowerbeds and hedges. The use of gardens for food production is prominent in planned areas (40.7%), whereas residential neighborhoods prioritize ornamentation (51.4%). The study identifies 232 species across 68 families, with a predominance of exotic species (80%) in all neighborhoods, particularly in unplanned areas (82.25%). The data reveals that Mangifera indica and Persea americana are abundant in all neighborhoods, illustrating their adaptability to different urban contexts. Herbaceous species are most common, followed by woody plants, with vines being sparse. Species dispersal is primarily driven by human activities (anthropochory), accounting for over 85% in all neighborhoods. These findings highlight the strong human influence on the composition and structure of domestic gardens in Lubumbashi, emphasizing the dominance of exotic species and the importance of anthropogenic factors in shaping urban green spaces. Urban policies should incorporate strategies to minimize the negative impacts of exotic species on native flora.

Recent developments in metallic additive manufacturing (AM) processes for the production of high-performance industrial pieces have been hampered by the limited availability of reliably processable or printable alloys. To date, most of the alloys used in AM are commercial grades that have been previously optimized for different manufacturing techniques. This study aims to design new alloys specifically tailored for AM processes, to minimize defects in the final products and optimize their properties. A computational approach is proposed to design novel and optimized austenitic alloy compositions. This method integrates a suite of predictive tools, including machine learning, calculation of phase diagrams (CALPHAD) and physical models, all piloted by a multi-objective genetic algorithm. Within this framework, several material-dependent criteria are examined and their impact on properties and on the occurrence of defects is identified. To validate our approach, experimental tests are performed on a selected alloy composition: powder is produced by gas atomization and samples are fabricated by laser powder bed fusion. The microstructure and mechanical properties of the alloys are evaluated and its printability is compared to a commercial 316L stainless steel taken as a reference.

Aortic transection, a near-complete tear through the layers of the aorta, is a critical condition often resulting from trauma such as motor vehicle collisions. The urgency of managing aortic transection underscores the critical need for effective interventions. We report the case of a male in his early 50’s with no significant medical history who presented to the emergency department following a motor vehicle collision, sustaining multiple injuries including a descending thoracic aortic transection. Rapid diagnostic assessment confirmed the severity of the injury, necessitating immediate intervention. Endovascular aortic repair (EVAR) was successfully employed, highlighting its efficacy in managing acute aortic injuries. The patient responded well to treatment, underscoring the importance of timely intervention in improving patient outcomes. This case emphasizes the critical role of rapid diagnostic assessment and endovascular intervention in managing life-threatening thoracic aortic injuries, particularly in the acute setting.

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

This study examines the aggregate consumption function of Saudi Arabia from 2000 to 2022, focusing on identifying key determinants of household consumption and evaluating the impacts of disposable income, household wealth, government expenditure, interest rates, and oil revenues. The research uses advanced econometric methods, including the Autoregressive Distributed Lag (ARDL) model and Johansen cointegration test, to analyze the relationships among these variables. The findings reveal that disposable income, household wealth, and government expenditure significantly and positively influence consumption, whereas interest rates show a negative correlation. Oil revenues also play a critical role, reflecting the country's economic reliance on oil. The study highlights the necessity for economic diversification to reduce the impact of oil price volatility on household income and consumption stability. The results offer crucial insights for policymakers, emphasizing the need for strategies that enhance household income and wealth, maintain robust public sector spending, and effectively manage interest rates. These findings also support the importance of consistent and predictable income sources for sustaining consumption. Additionally, this study suggests directions for future research, including developing sophisticated forecasting models to predict consumption trends and exploring other influencing factors such as demographic shifts and technological progress.

The distribution of zakat, which is still carried out directly through mosques or zakat amil bodies, can hinder the payment process due to inaccurate calculations and difficulties in finding zakat amil institutions. In the digital era, information technology is very important in the management of zakat, alms, and infaq. Therefore, a zakat information management system was created. The e-Zakat program, developed using the waterfall method, plays an important role in five main aspects of zakat management: muzaki and mustahiq data collection, zakat collection, zakat distribution, mustahiq development, and reporting. The use of information technology in this program is expected to increase efficiency, accountability, transparency, as well as the reach of zakat and muzaki involvement.

The normative and safeguarding role of ethics and law in the development of biomedical science and technology, as well as their importance in promoting the progress of the industry, analyzed the key role of ethics and law in the field of biomedical science and technology, by restricting scientific research behavior, protecting the rights and safety of subjects, providing a solid guarantee for scientific research activities, and promoting the healthy development of biomedical science and technology. At the same time, the positive role of ethics and law in promoting international cooperation and exchange of biomedical science and technology is also discussed, which will inject strong impetus into the global development of biomedical science and technology. In addition, through case analysis, the paper demonstrates the key role of ethical review in the field of biomedical science and technology, as well as the importance of law in maintaining market order, protecting subjects' rights and interests, and fairness and justice. The successful practice of ethics and law in the development of biomedical science and technology is emphasized, which proves that following ethical principles and legal framework is the key factor to promote the progress of biomedical science and technology. This paper explores the important role of ethics and law in the development of biomedical science and technology, and provides valuable reference and guidance for practitioners in the industry. By following ethical principles and legal norms, we will jointly promote the prosperity and development of biomedical science and technology, and contribute to the common progress of human health.

This bibliometric study explores the cryptocurrency accounting (CA) literature and the connections between authors, institutions, and countries where cryptocurrency activity involves transactions that must be legally recognized in accounting, assure accuracy and reliability for auditing, and adhere to tax compliance. The design involves data selection from Web of Science Core Collection (WoS) and Scopus, published between 2007 - 2023. The technique helps identify influential publications, collaboration networks, thematic clusters, and trends in research on CA using tools VOSviewer, Biblioshiny, and MS Excel. The originality of the study lies in its dual role as a support for accounting professionals and academics to develop innovative solutions for the challenges posed by crypto technology across core accounting areas: financial and managerial accounting, taxation, and auditing. The findings offer insights into the themes mentioned, and even if the collaboration between the authors is not very developed, the innovation and public recognition of the subject could raise researchers' interest. The limitation of the dataset is that it does not cover all relevant publications in a different period from the one in which the data was retrieved, 9-11 May 2024. This review might need periodic updates because the CA landscape is constantly changing.

Evidence is emerging on the role of maternal diet, gut microbiota, and other lifestyle factors in establishing lifelong health and disease, which are determined by trans-generationally inherited epigenetic modifications. Understanding epigenetic mechanisms may help identify novel biomarkers for pregnancy-related exposure, burden, or disease risk. Such biomarkers are essential for developing tools for the early detection of risk factors and exposure levels. It is necessary to establish the exposure threshold to the fetus due to nutrient deficiencies or other environmental factors that can lead to clinically relevant epigenetic changes that modulate disease risks. This narrative review summarizes the latest updates on the roles of maternal nutrients (n-3 fatty acids, polyphenols, vitamins) and gut microbiota on the placental epigenome and its impacts on fetal brain development.

The dynamic landscape of AI adoption and its impact on employment in Malaysia demands a multifaceted approach to navigate the challenges and harness the opportunities presented. While the government's commitment to fostering AI adoption through initiatives like the National AI Framework and the Malaysia Digital Economy Blueprint is commendable, it is imperative to address concerns regarding job displacement and ensure inclusive growth. This study identifies the pressing research problem of workforce readiness for the AI-driven future, emphasizing the need to explore strategies for reskilling and upskilling affected workers. By employing critical lenses such as Marxist, feminist, and postcolonial perspectives, scholars highlight the power dynamics and societal implications inherent in AI deployment, guiding the development of policies and interventions that prioritize workers' interests and address social inequalities. Moving forward, a comprehensive approach combining policy interventions, educational reforms, and inclusive strategies is essential to maximize the benefits of AI adoption while mitigating its potential risks. Longitudinal studies, interdisciplinary research, and comparative analyses will further advance our understanding and inform evidence-based policymaking in this evolving field. Ultimately, by prioritizing workforce preparedness, social equity, and sustainable development, Malaysia can position itself as a leader in the AI-driven global economy, fostering a resilient, inclusive, and prosperous society for all.

Individuals with BPD grapple with unstable relationships, marked by extreme emotional swings and interpersonal conflicts. Emotional instability, a distorted self-image, and impulsivity further complicate matters, often leading to self-harm and suicide attempts as desperate coping mechanisms. Genetics and adverse childhood experiences contribute to BPD's development, shaping brain function and emotional regulation. Diagnosis involves meticulous assessments, paving the way for personalized treatments like dialectical behavior therapy and, in severe cases, hospitalization. Early intervention, professional support, and societal understanding are pivotal for positive outcomes, and challenging mental health stigma.

We show that one of the two important uncertainty principles derived by Maccone and Pati \textit{[Phys. Rev. Lett., 2014]} can be derived for arbitrary maps defined on subsets of $\mathcal{L}^p$ spaces for $1< p<\infty$. Our main tool is the Clarkson inequalities. We also derive a nonlinear uncertainty principle for weak parallelogram spaces and Type-p Banach spaces.

Keywords: Innovation ecosystems, Economic sustainability, Hydrocarbon-based economies, Economic diversification, Qualitative approach

Machine learning is a fundamental aspect of artificial intelligence that involves the development of algorithms and models that allow computers to learn and make predictions or decisions without explicit programming. With the development of neural networks, back-propagation algorithms and deep learning, machine learning has made breakthroughs in the fields of image recognition, natural language processing and handwriting recognition using machine learning techniques. The advent of deep learning has revolutionized the field of handwriting recognition, using convolutional neural networks, recurrent neural networks, and sequence-to-sequence models to provide solutions that go beyond machine learning methods and significantly improve the accuracy and robustness of handwriting recognition systems. But challenges remain, including the need for large labelled datasets, computational resources and addressing potential biases. As research in deep learning techniques continues to drive handwriting recognition closer towards realisability, machine learning approaches remain at the forefront.

Regular weight measurement is important in fattening geese to assess their health status. Failure to gain weight may indicate a potential illness. Standard weight gain analysis involves direct contact with the animal, which can cause stress to the animal, resulting in overall negative impacts on animal welfare. The focus of this study was to design a smart solution for monitoring weight changes in the breeding of farm animals. The proposed IoT system with a weighing device equipped with RFID technology for animal registration aimed to minimise the negative aspects associated with measuring in contact with humans. The designed system aims to incorporate modern approaches in animal husbandry and utilise the acquired data for the potential development of breeding approaches for various animal breeds. The system consisted of three main components: a data acquisition system, a weighing system with RFID, and an environmental monitoring system. In this study, the RFID system accuracy for detecting geese in the weighing system environment was assessed. The entire system evaluation yielded a sensitivity of 93.87%, specificity of 99.94%, accuracy of 99.85%, and precision of 95.09%. Regression analysis revealed a good correlation between observed feeding and RFID registrations with a determination coefficient of R2 = 0.9813.

Albert Einstein, shortly after publishing his General Relativity Theory (GRT) applied it to the entire universe in a paper of 1917. Einstein assumed that such a universe was static in time and possessed a uniform distribution of matter on the largest scales, obtaining a static and finite universe of spherical spatial curvature of radius R. Although this model was refuted by Edwin Hubble's discovery of the expansion of the universe, it is still often studied as a theoretical framework for some problems, such as the twin paradox. This paper will show that Einstein's static universe model leads to a privileged frame of reference, so that any observer moving at the speed v will be able to measure speeds of light other than c depending on the direction of beam transmission. The above will refute the validity of the application to this closed and static universe of the Special Relativity Theory (SRT) proposed by Einstein in 1905 in his article . In addition, a new synchronization convention and new coordinate transformations will be deduced, the "generic" transformations, which will replace those of Lorentz. Finally, the twin paradox in this universe will be solved by making use of them.

The assessment of Histone deacetylases in conjunction with Curcumin, conducted through the Mcule Database employing the Autodock Vina algorithm, involves an examination of molecular interactions. This analysis includes the calculation of binding energies, revealing the strength and stability of the interactions between Curcumin and various Histone deacetylase targets. The comparison encompasses diverse aspects such as binding energies, specific binding sites, interactions across different targets, structural details, and potential implications for biological activity. The results imply that Curcumin shows heightened affinity for Histone deacetylase 4 in comparison to other investigated histone deacetylases.

Background: Hepatic erythrophagocytosis is augmented in NASH and amplifies inflammation and fibrosis. Although various pro-phagocytic signals have been identified on erythrocytes of NASH patients, the role of bound thrombospondin-1 (TSP-1), which acts as an “eat-me” signal, arginase-1, which regulates the levels of nitric oxide in erythrocytes, and phosphatidylethano-lamine (PE) which can amplify erythrophagocytosis and hepatic inflammation have not been explored. Hence, we sought to investigate the levels of arginase-1 and TSP-1 in erythrocyte lysate and PE in erythrocyte membranes of NASH patients. Methods: Twenty-four patients and 14 healthy controls participated in our study. The levels of TSP-1 and arginase were quantified by ELISA in erythrocyte lysates, and the levels of PE in erythrocyte membranes by thin layer chro-matography. Results: Erythrocytes of NAFLD patients exhibit lower levels of arginase-1 and TSP-1 (p<0.01). Erythrocyte-bound TSP-1 levels correlated with the levels of erythrocyte surface CD47. Phosphatidylethanolamine was increased in erythrocytes of NASH patients and was accompanied by increased release, indicating exposure. Conclusion: Our results imply reduced TSP-1 binding by erythrocytes which could allow free TSP-1 molecules to act on macrophages, enhancing erythrophagocytosis. Increased PE which could amplify inflammation after efferocytosis, while downregulation of arginase-1 could lead to defective efferocytosis.

Esophageal cancer is an extremely deadly tumor that accounts for 5% of all cancer deaths. The two main subtypes of the disease are esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC). To date, few studies analyse EAC for transcriptional signatures associated with diagnosis and/or prognosis, while most focus on the analysis of transcriptional profiles of ESCC. In this study, we used single-cell RNA sequencing (scRNA-seq) analysis of CD45+ cells enriched from Tumors and matched Non Tumor tissues from therapy naїve patients to identify all types of immune cells present in tumor immune infiltrate and its transcriptional profile. In addi-tion, we analysed the entire transcriptome in a cohort of 23 patients whose tissue biopsies were taken from Tumors and matched with Non Tumor tissue. The transcriptional signatures we obtained were then used to stratify a large cohort of TCGA EAC patients, demonstrating a strong association with their prognosis, as well as the ability to predict a patient's clinical outcome and better define the prognosis of EAC after surgery. In addition, these features may lead patients to effective therapies including immunotherapy approaches.

Malignant neoplasms arising from the gastrointestinal (GI) tract are among the most common cancer types with a high mortality rate. Despite advances in treatment in a small subgroup harboring targetable mutations, the outcome remains poor, accounting for one in three cancer-related deaths observed globally. As a promising therapeutic option in various tumor types, immunotherapy with immune checkpoint inhibitors has also been evaluated in GI cancer, albeit with limited efficacy except for a small subgroup expressing microsatellite instability. In the quest for more effective treatment options, energetic efforts have been placed to evaluate the role of several immunotherapy approaches comprising of cancer vaccines, adoptive cell therapies and immune checkpoint inhibitors. In this review, we report our experience with personalized dendritic cell cancer vaccine and cytokine-induced killer cell therapy in three patients with GI cancers and summarize current clinical data on combined immunotherapy strategies.

Though early-stage colorectal cancer has a high 5-year survival rate of 65-92% depending on the specific stage, this probability drops to 13% after the cancer metastasizes. Frontline treatments for colorectal cancer such as chemotherapy and radiation often produce dose-limiting toxicities in patients and acquired resistance in cancer cells. Additional targeted treatments are needed to improve patient outcomes and quality of life. Immunotherapy involves treatment with peptides, cells, antibodies, viruses, or small molecules to engage or train the immune system to kill cancer cells. Preclinical and clinical investigations of immunotherapy for treatment of colorectal cancer including immune checkpoint blockade, adoptive cell therapy, monoclonal antibodies, oncolytic viruses, anti-cancer vaccines, and immune system modulators have been promising, but demonstrate limitations for patients with proficient mismatch repair enzymes. In this review, we discuss preclinical and clinical studies investigating immunotherapy for treatment of colorectal cancer and predictive biomarkers for response to these treatments. We also consider open questions including optimal combination treatments to maximize efficacy, minimize toxicity, and prevent acquired resistance and approaches to sensitize mismatch repair proficient patients to immunotherapy.

Gastric cancer is a heterogeneous group of diseases with only a fraction of patients responds to immunotherapy. The relationships between tumor DNA damage response, the immune system and immunotherapy have recently attracted attention. Accumulating evidence indicate that DNA repair landscape is a significant factor in driving response to immune checkpoint blockade (ICB) therapy. In this study, to explore new prognostic and predictive biomarkers for gastric cancer patients who are sensitive and responsible to immunotherapy, we developed a novel 15-DNA repair gene signature (DRGS) and its related scoring system and evaluated the efficiency of DRGS in discriminating different molecular and immune characteristics and therapeutic outcomes of gastric adenocarcinoma. The results showed that DRGS high score patients showed significantly better therapeutic outcomes compared to DRGS low score patients (P < 0.001). Integrated analysis of multi-omics data demonstrated that the patients with high DRGS score were characteristic of high levels of anti-tumor lymphocytes infiltration, tumor mutation burden (TMB) and PD-L1 expression, and these patients exhibited a longer overall survival and may benefit more from ICB therapy, as compared to the low-score patients. Therefore, the DRGS and its scoring system may have implications in tailoring immunotherapy in gastric cancers.

In this perspective, we identify emerging frontiers in clinical and basic research of melanocyte biology and its associated biomedical disciplines. We describe challenges and opportunities in clinical and basic research of normal and diseased melanocytes that impact current approaches to research in melanoma and the dermatological sciences. We focus on four themes: (1) clinical melanoma research, (2) basic melanoma research, (3) clinical dermatology, and (4) basic pigment cell research, with the goal of outlining current highlights, challenges, and frontiers associated with pigmentation and melanocyte biology.