In this study, the structural behavior of a short threaded anchor with a 20 mm diameter and an embedment length of 50 mm (2.5Ø) in UHPFRC is investigated using non-linear Finite Element models. UHPFRC is assumed to exhibit tensile strain-hardening behavior, with tensile strengths of 7 MPa and 11 MPa, respectively. The modelled anchor was subjected to a continuously increasing uniaxial pull-out force. The results indicate that the fracture mechanism of threaded anchors in UHPFRC is primarily characterized by the formation of a tensile membrane within the UHPFRC, which acts as the main resisting element against the pull-out force. Additionally, the influence of UHPFRC's tensile properties on the pull-out behavior and ultimate resistance of the threaded anchors was determined.

Deuterium is a non-radioactive isotope of hydrogen, containing a neutron as well as a proton, which makes it twice as heavy as hydrogen. Deuterium is a natural element found at 156 parts per million in seawater. Human metabolism employs clever strategies to minimize the amount of deuterium in mitochondrial water, because it causes a stutter in ATPase pumps, introducing excess reactive oxygen species and inefficiencies in ATP production. Gut microbes produce hydrogen gas that is 80% depleted in deuterium (deupleted), and this gas is recycled into organic matter that supplies deupleted nutrients to the host, such as acetate, butyrate, formate, methionine, and choline. Mitochondrial dysfunction is associated with many chronic diseases, most notably, cancer. Dehydrogenases are flavoproteins that typically have a high deuterium kinetic isotope effect, and they supply deupleted protons to NAD⁺ to produce NADH, which supplies protons to the ATPase pumps. Here, we examine the unique metabolic policies of cancer cells in a new light, and we propose that a tumor may arise as a strategy to help repair the mitochondria of tumor-resident immune cells overburdened with deuterium. While lactate accumulation in the tumor microenvironment promotes tumor growth, it also provides a valuable deuterium depleted nutrient to the tumor-resident immune cells. We provide strong evidence that deuterium depleted water (DDW) is a promising treatment for cancer.

The accurate detection and assessment of stress play a pivotal role in enhancing individual well-being and healthcare outcomes. Traditional methods of stress detection often grapple with limitations in accuracy and scalability. With the advent of machine learning (ML), the potential to revolutionize stress detection has emerged. This paper presents a comprehensive study on the application of ML algorithms for stress detection, with a focus on physiological and behavioral data analysis. Central to our approach is the integration of SHapley Additive exPlanations (SHAP), an Explainable Artificial Intelligence (XAI) technique, to interpret ML models. SHAP provides a novel lens to understand the impact of individual features in the complex decision-making processes of ML models, thereby enhancing the transparency and reliability of stress predictions. We demonstrate how SHAP not only aids in elucidating model decisions but also contributes to refining the models for greater accuracy. Our results highlight the effectiveness of ML in detecting stress and the pivotal role of XAI in making these models more interpretable and trustworthy. This study underscores the synergy between advanced ML techniques and XAI, paving the way for more nuanced and reliable stress detection methodologies that are essential in diverse settings, from healthcare to workplace environments.

Human space exploration is evolving, with private and government organizations working to develop the new generation of astronauts and technology for future colonization of the Moon and other extreme locations. The coming decade is promising, which is reflected in a number of emerging habitats to simulate analog missions around the world. Analog missions have always been at the forefront of advancing knowledge and now this method is widely used by space enthusiasts and professionals. The Analog Astronaut Training Center is designed to simulate one of the major challenges of human space exploration, namely isolation with limited resources, and focuses on collecting data based on various parameters such as environment, physiology and psychology. The environmental monitoring of the habitat conditions is remotely controlled, allowing the Mission Control Center to receive the mission data in real time. The data obtained, together with physiological and psychological inputs, allow monitoring of human adaptations to limited resources and sustainable living in extreme conditions. This paper presents an overview of the sensors used and the data collected during organized analogue simulations, which help to optimize the design of future life-support systems.

Background/Objectives: Distance or urbanisation settings may affect active commuting to school (ACS). This study aimed to (i) detect home-school threshold distances of walking to school and (ii) predict walkable distances among adolescents in different urbanisation settings and both sexes, and (iii) to identify variables predicting adolescents’ ACS, in a central Spain region. Methods: The PACOyPACA (Spanish acronym for Pedal-and-Walk to School, Pedal-and-Walk Home) study evaluated adolescents attending urban, semi-urban and rural schools from Castilla-La Mancha region. The sample included 448 adolescents [48.9% females, mean age 14.80 (SD=0.60)] living closer than 5,100m from school. Distance was divided into deciles to detect which adolescents walked more. Most walkable distances within the whole sample, by sex and by urbanisation settings were predicted using Receiver Operating Characteristic (ROC) curves. Variables affecting ACS were found with binary logistic regression. Significance was set at p≤0.05. Results: Most adolescents walked to school (73.1%). Commuting modes differed significantly by urbanisation settings (p=0.001), but not by sex. Most walked when living around 1,400m from school or closer within the whole sample, in both sexes and in urban and semi-urban settings, and adolescents within rural settings did it until 750-900m. Walkable distances were 1,350m for the whole sample and both sexes, and 1,450, 1,350 and 800 within urban, semi-urban and rural settings, respectively. Distance was the only predictor of ACS (p<0.001). Conclusions: Walkable home-school distances differed based on urbanisation settings, which may be due to the classification of urbanisation settings. This study addresses schools within scarcely populated areas.

Background: The aim of this systematic review was to evaluate diagnostic accuracy of molecular-based LTPs serum IgE for the diagnosis of food allergies in patients with suspected allergy to one of the LTPs-containing food. Methods: cohort, prospective or retrospective cross- sectional studies were considered for inclusion in the review. Oral food challenge (both open and double-blind placebo-controlled) was the reference standard for the diagnosis. Pubmed (MEDLINE), Web of Science, Scopus, and ClinicalTrial.org were searched for relevant papers. Risk of bias was assigned by QUADAS-2 tool. Data were reported as sensitivity and specificity. Study protocol was registered in the PROSPERO database (CRD42022321985). Results: Fifteen articles, including 2395 individuals, were included. Sensitivity of Ara h 9 for peanut allergy diagnosis ranged from 6 to 61%; specificity ranged from 57 to 100%. Cor a 8 sensitivity ranged from 11 to 43%, with specificity ranging from 59 to 94%. Conclusions: Ara h9 and Cor a 8 serum IgE may be useful to confirm diagnosis of peanut and hazelnut allergy in symptomatic patients, although diagnostic accuracy is limited by low sensitivity. More investigation on other LTPs and in adult population may be important to define the clinical role of this test in food allergies diagnostics.

Chronic urticaria (CU) is a debilitating skin condition affecting up to 20% of the global popula-tion, characterized by erythematous, maculo-papular lesions and significant quality of life im-pairment. This study focused on the role of interleukin 33 (IL-33) and its polymorphisms, partic-ularly SNP rs1929992, in chronic spontaneous urticaria (CSU). Using demographic, clinical, and laboratory data from CU patients and controls, we aestimated allele and genotype frequencies, Hardy-Weinberg equilibrium condition, and serum IL-33 levels, using unconditional binomial logistic regression for association analysis. Results revealed that CU patients had significantly higher frequencies of the minor allele of IL33 rs1929992 compared to controls (31.25% vs. 17.35%, p = 0.024), and carriers of the AG genotype exhibited increased odds of CU (adjusted OR = 2.208, p ≤ 0.001). Additionally, serum IL-33 levels were markedly elevated in CU patients, par-ticularly those with the GA genotype. The findings suggest that the IL-33 SNP rs1929992 is asso-ciated with an increased susceptibility to CSU, emphasizing its potential as a diagnostic and therapeutic biomarker. This study underscores the genetic and immunological underpinnings of CSU, paving the way for personalized treatment approaches.

The precise localisation of epileptic foci with the help of EEG or ECoG signals is still a clinical challenge that is rarely successful, except in the case of foci that are very close to the surface and allow a clear assignment to a single electrode. On the research side, dipole reconstruction of instantaneous excitation fields via the lead-field matrix or the evaluation of time-dependent phase shifts in the measurements seem to be still possible and are under development. For the latter, we have investigated the necessary correlation of signals in the time range up to a few hundred milliseconds in an EEG of a healthy subject (self-experiment). We find periods of up to 190 msec in length in which a correlation over short latencies succeeds very well, alternating with periods in which long-range correlations occur while the short latencies come to a standstill. An automatic propagation time focus localisation to be developed therefore appears possible if an underlying state monitoring system independently recognises the suitable time periods and then successfully performs the comparatively shortest-range triangulation calculations over these.

The flow of mapping the development and direction of research on Socioeconomic Factors in the Education Ecosystem is known through published articles with the Scopus database index. Quantitative approach is used as the article research with bibliometric data analysis techniques to explore all publications indexed in the Scopus database on Socioeconomic Factors in the Education Ecosystem from 1990 to 2023. The data obtained were analyzed using Excel and R/R-Studio. VOSViewer is used to perform visual analysis of keyword occurrence and document citations stimulantly. Researchers found 772 publications that fit the function, subject, and criteria that had been set. The annual growth rate is seen in the data obtained. The papers are analyzed in terms of publications by field of science, the number of studies published annually. The bibliometric data analysis performed was limited to Scopus data. Other national and international databases were not taken into account in the study. The limitation of this study is only taking data sets or meta data in publications indexed by Scopus. This article presents a brief overview of the literature accessible to researchers working in the field of Socioeconomic Factors in the Education Ecosystem as well as provides recommendations for future research.

This paper addresses the capability to alter the hydrophilic wettability characteristics of poly(vinyl alcohol) (PVA) polymer films doped with glycerol. Films of PVA and glycerol-choline chloride (GCC) blends have been prepared using the solution casting method with different glycerol dopants ranging from 0% to 10% (wt %). The results show that as the GCC dopant content increases from 0% to 10%, the wettability increases, thus increasing the surface energy of the solid film. The wettability changes are observed by identifying the contact angle of 10 µL deionized water droplet which altered from 55^o to 28^o as dopant content changed from 0% to 10% per PVA solution weight. The results show that the roughness of film surfaces increases as the content of dopant (GCC) increases in the film indicating that roughness has a strong influence on the wettability of the casted films.

Machine unlearning, the process of selectively forgetting or removing the influence of specific data points from a machine learning model, is increasingly important for privacy and compliance with regulations like the GDPR. This paper explores the concept of exact unlearning, focusing on its implementation in models trained using convex and non-convex functions. Convex functions, due to their well-behaved optimization landscapes, lend themselves to efficient unlearning through methods such as inverse optimization, duality-based approaches, and incremental learning. In contrast, non-convex functions, common in deep learning models, present more complex challenges due to their multiple local minima and high-dimensional parameter spaces. Techniques like checkpoint-based retraining, gradient inversion, and meta-learning are discussed as viable, though computationally expensive, methods for non-convex exact unlearning. The paper also highlights real-world applications in fields such as finance and healthcare, where exact unlearning can enhance privacy and security without compromising model performance. Finally, it outlines key challenges and future research directions, particularly the need for more efficient unlearning algorithms in non-convex settings and the development of secure, adversarial-resistant methods for sensitive data removal.

Road safety is a critical public health concern in Nepal, especially in urban areas where inadequate infrastructure exacerbates traffic incidents. This study reviews and synthesizes 21 peer-reviewed papers to investigate how road infrastructure contributes to traffic accidents. Key factors include poor road conditions, reckless driving, and inadequate traffic management. Findings indicate that road traffic accidents (RTAs) significantly increase morbidity, mortality, and economic burdens in Nepal. To address these issues, the study recommends infrastructure improvements, stricter enforcement of traffic laws, and enhanced public education on road safety.

We propose the Ramsey approach for the analysis of behavior of isolated mechanical systems containing interacting particles. The total momentum of the system in the frame of the center of masses is zero. The mechanical system is described by the Ramsey, bi-colored, complete graph. Vectors of momenta of the particles pi serve as the vertices of the graph. We start from the graph representing the system in the frame of the center of masses, the momenta of the particles in this system are pcmi. If (pcmi(t)∙pcmj(t))≥0 is true, vectors of momenta of the particles are connected with the red link; if (pcmi(t)∙pcmj(t))<0 takes place, the vectors of momenta are connected with the green link. Thus, the complete, bi-colored graph emerges. Consider the isolated system built of six interacting particles. According to the Ramsey Theorem, the graph inevitably comprises at least one monochromatic triangle. The coloring procedure is invariant relatively to inertial frames; thus, the graph representing the system contains at least one monochromatic triangle in any of inertial frames. This gives rise to the novel kind of a mechanical invariant. Similar coloring is introduced for the angular momenta of the particles.

Generic text embeddings have demonstrated considerable success across a multitude of applications. However, these embeddings are typically derived by modeling the co-occurrence patterns within text-only corpora, which can limit their ability to generalize effectively across diverse contexts. In this study, we investigate methodologies that incorporate visual information into textual representations to overcome these limitations. Through extensive ablation studies, we introduce a novel and straightforward architecture named VisualText Fusion Network (VTFN). This architecture not only surpasses existing multimodal approaches on a range of well-established benchmark datasets but also achieves state-of-the-art performance on image-related textual datasets while utilizing significantly less training data. Our findings underscore the potential of integrating visual modalities to substantially enhance the robustness and applicability of text embeddings, paving the way for more nuanced and contextually rich semantic representations.

The study focused on utilizing post-process osmotic solution enriched with inulin or maltodextrin, evaluating its potential for spray drying. Parameters such as yield, energy consumption, and the physical properties of the dried solutions and powders—including moisture content (Mc), water activity (Aw), color, true and bulk density, porosity, and glass transition temperature—were analyzed. The effects of carrier type, concentration, and inlet temperature (Tin) were systematically examined. Samples dried with maltodextrin demonstrated over 50% higher yield than those with inulin, with the highest yield of 32.13±0.64% and the lowest yield of 2.75±0.48%. Higher Tin improved drying efficiency by reducing Mc but also caused darker powders. Energy consumption increased with rising Tin, peaking at 2295±51 kJ. The Spray Drying Energy Index (SDEI) was introduced to assess energy consumption relative to powder yield, with the most favorable SDEI values observed for processes with the highest total energy consumption. These same samples exhibited lower Mc and Aw values. The lowest bulk density was 0.455±0.004 g·cm-3, while porosity was 58.3±0.7%. The results highlight the potential of spray drying as a sustainable method for utilizing by-products from osmotic dehydration, aligning with the principles of sustainable food practices.

This study reports a 50-year-old patient presented with eczematous drug-eruption induced by selpercatinib after the treatment of non-small cell lung cancer (NSCLC). The patient has symmetric erythematous papules and plaques all over the body with dry, scaly skin accompanied by severe pruritus and visible scarring. After systemic treatment with glucocorticoids, the skin lesions of the patient were well reduced. Currently, the medical literature on the incidence of selpercatinib-induced cutaneous eczematous reactions and their clinical management is scarce. Therefore, this study provides novel evidence for the treatment of selpercatinib-induced cutaneous eczematous reactions.

By tonnage, corn (Zea mays L.) is the #1 crop produced globally, and recent research has suggested that no-till (NT) systems can lead to reduced yields of this important crop. Additionally, there is a lack of long-term data about the effects of tillage and N management on cropping systems. Corn is the most nitrogen (N)-fertilized crop in the USA, and N losses to the environment contribute to significant impacts on air and water quality. We conducted long-term studies on conventional tillage (CT), and conservation tillage systems such as strip tillage (ST) and NT, under different N rates. We found that immediately after conversion to NT, yields from NT were significantly lower than yields from CT (P<0.1), but after five years of NT, the NT yields were 1.5% higher than the CT yields (P<0.1). Initially, the NT yields were lower than the ST (P<0.01), but after seven years of NT, the NT yields were comparable to ST grain yields. Although the total aboveground N uptake with NT immediately after conversion to NT was lower than with CT and ST, these differences were not significant in the long run. The nitrogen use efficiency (NUE) with NT increased over time. The present work highlights the importance of long-term research for determining the cumulative impacts of best management practices such as NT. We found that NT becomes a more viable practice after five or seven years of implementation, demonstrating the high importance of long-term research.

Aβ1-42 (amyloid beta) oligomers, the major neurotoxic culprits in Alzheimer's disease, initiate early pathophysiological events, including neuronal hyperactivity, that underlie aberrant network activity and cognitive impairment. Although several synaptotoxic effects have been extensively studied, neuronal hyperexcitability which may also contribute to cognitive deficits is not fully understood. Here, we found several adverse effects of in vivo injection of Aβ1-42 oligomers on contextual memory and intrinsic properties of CA1 pyramidal neurons. Male rats underwent behavioral and electrophysiological studies 1 week after microinjections into the dorsal CA1 region, followed by histological analysis. After 1 week, Aβ1-42 oligomers impaired contextual learning without affecting basic physiological functions and triggered training-induced neuronal excitability. Furthermore, riluzole, a persistent sodium current (INaP) blocker, dose-dependently reduced Aβ1-42 oligomer-induced hyperexcitability. Congo red staining, which detects insoluble amyloid deposits, further identified labeling of CA1 pyramidal neurons while immunohistochemistry with lecanemab, which detects soluble Aβ oligomers, revealed immunoreactivity of both pyramidal and non-pyramidal cells in the target area. Therefore, our study suggests that a single injection of Aβ1-42 oligomers resulted in contextual memory deficits along with concomitant neuronal hyperexcitability and amyloid deposition in the CA1 region after 1 week.

Low-grade endotoxemia by lipopolysaccharide (LPS) has been detected in COVID-19 and could favour thrombosis via eliciting a pro-inflammatory and pro-coagulant state. The aim of the study was to analyse the mechanism accounting for low-grade endotoxemia and its relationship with oxidative stress and clotting activation thrombosis in COVID-19. We measured serum levels of sNOX2-dp, zonulin, LPS, D-dimer and albumin in 175 patients with COVID-19, classified as having or not acute respiratory distress syndrome (ARDS), and 50 healthy subjects. Baseline levels of sNOX2-dp, LPS, zonulin, D-dimer, albumin and hs-CRP were significantly higher in COVID-19 compared to controls. In COVID-19 patients with ARDS, sNOX2-dp, LPS, zonulin, D-dimer and hs-CRP were significantly higher compared to COVID-19 patients without ARDS. Conversely, concentration of albumin was lower in patients with compared with those without ARDS and inversely associated with LPS. In COVID-19 cohort, the number of patients with ARDS progressively increased according to sNOX2-dp and LPS quartiles; a significant correlation between LPS and sNOX2-dp, and LPS and D-Dimer was detected in COVID-19. In a multivariable logistic regression model, LPS/Albumin levels and D-dimer predicted thrombotic events. In COVID-19 patients, LPS is significantly associated with a hypercoagulation state and disease severity. In vitro, LPS can increase endothelial oxidative stress and coagulation biomarkers, that were reduced by the treatment with albumin. In conclusion, impaired gut barrier permeability, increased NOX2 activation and low serum albumin may account for low-grade endotoxemia, and they may be implicated in thrombotic events in COVID-19.

Meat drying is a traditional method of preserving meat that has a rich past in many cultures. 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. The most important ingredient that gives the product its characteristic features is in its content: a paste containing fenugreek seed flour, garlic, milled red capia pepper, and water. Among ethnic meat products, pastırma is familiar with dry-cured meat products such as jerky, kadid, cecina, and carne de sol. In this 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. 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.

Background: Adverse pregnancy outcomes correlate with blood glucose levels in women with type 1 diabetes. There is a gap between glycaemic targets and blood glucose control achieved in pregnancy. Aims: To investigate the impact of an intensive weekly service on glycaemic control compared with our previous care model in pregnancies affected by type 1 diabetes. Materials and Methods: This is a retrospective cross-sectional pre / post study comparing measures of glycaemic control in women with type 1 diabetes at each trimester of pregnancy, in the 12 months before and the 8 months after the commencement of an intensive weekly insulin stabilisation service (ISS). Results: The study utilised data from Dexcom continuous glucose monitoring (CGM) reports for analysis of pregnancy-specific glycaemic data (incorporating time in range 3.5-7.8 mmol/L). 16 women provided data for 35 trimesters pre ISS and 17 women provided data for 38 trimesters post ISS. There was an improvement in pregnancy-specific time-in-range for trimester 3 following the commencement of an intensive weekly insulin stabilization service (mean pre 49.6%, post 61.4%, p=0.042). Similar results were seen when women using hybrid closed loop technology were excluded, albeit not then reaching statistical significance. It was not possible to assess the effect of the intervention on the first trimester. There were no statistically significant changes in glycaemia for trimester 2. Conclusions: In a small group of pregnant women with type 1 diabetes, improvement in pregnancy specific time-in-range occurred in trimester 3, but not in trimester 1 or 2, following the introduction of intensive weekly clinical support.

Obesity is one of the world's major public health challenges. Its pathogenesis and comorbid metabolic disorders share common mechanisms, such as mitochondrial or endoplasmic reticulum dysfunction or oxidative stress, gut dysbiosis, chronic in-flammation and altered autophagy. Numerous pro-autophagy dietary interventions are being investigated for their potential obesity-preventing or therapeutic effects. In this review, we summarize current data on the relationship between autophagy and obesity and discuss various non-pharmacological dietary interventions as regu-lators of autophagy-related genes in the prevention and ultimately treatment of obe-sity in humans, available in scientific databases and published through July 2024. Lifestyle modification (such as calorie restriction, intermittent fasting, physical exer-cise), a diet rich in flavonoids, antioxidants, specific fatty acids, specific amino acids and others have shown a beneficial role in the induction of this process. Induction of autophagy by heterogeneous interventions elicits a relatively homogeneous response characterized by activation of specific kinases (AMPK, IKK, JNK1, TAK1, ULK1, VPS34), inhibition of others (such as mTORC1), protein deacetylation reactions (at least in part providing SIRT1 activation and/or EP300 inhibition), and reversal of in-hibitory interactions such as those between BECN1 and members of the Bcl-2 family.

The female pelvis is often evolutionarily described as a compromise to accommodate the birthing process and bipedalism. This compromise puts a mother and baby at risk for fetopelvic disproportion, the mismatch between the size of the fetus and the mother's pelvis, impacting the ease at which the vaginal birthing process occurs. Obstructed labor, commonly caused by fetopelvic disproportion, is a leading cause of maternal mortality and morbidity and has serious medical sequelae for the fetus. In this review, this evolutionary aspect of fetopelvic disproportion is being reconsidered within a broader sociocultural and environmental approach related to a change of paradigm from a more reductionist Neo-Darwinist to a more encompassing Extended Evolutionary Synthesis view. The review explores a more comprehensive understanding of several factors related to fetopelvic disproportion, including socioeconomic factors and ethnic disparities amongst individuals that might lead to a higher likelihood of obstructed labor and maternal and fetal morbidity and mortality.

This study, based on proactive motivation theory, explores the relationship between perceived overqualification, digital leadership, and constructive deviant behavior, as well as generational differences. Using data collected in two waves from 596 employees, the results show that perceived overqualification positively influences constructive deviant behavior, and digital leadership enhances this effect. Employees born in the 1980s are most influenced by both factors, followed by those born in the 1990s, where the effect of digital leadership is less significant. The study suggests that effectively utilizing digital leadership and recognizing generational differences in perceived overqualification can help organizations better manage overqualified talent, improving employee satisfaction and productivity.

Background: Depression is a common disorder in older people. It affects their physical recovery and general well-being, leading to longer hospital stays and higher healthcare costs. Under-standing the prevalence of depression and its impact on functional outcomes in the population is crucial for improving strategies and patient care. This study aims to determine the prevalence of depression in elderly patients in geriatric rehabilitation and assess its impact on their functional abilities during the rehabilitation process; Methods: A retrospective cohort study was conducted at the Lucerne Cantonal Hospital Wolhusen, Switzerland, between 2015 and 2020, involving 1,159 patients aged 65 years and older. Depression was assessed using the Geriatric Depression Scale (GDS) Short Form, while functional abilities were measured using the Functional Independence Measure (FIM) and the Tinetti test. The data was analyzed using TIBCO Statistica 13.3, with sta-tistical significance set at p < 0.05; Results: The study found that 25.4% of participants had depressive symptoms, with higher rates in women (27.8%) than in men (21.2%). Based on FIM and Tinetti scores, these patients had lower functional abilities at admission and discharge. However, all patients, regardless of depression status, showed significant improvements in functional scores during rehabilitation; Conclusions: Depression is proving to be a problem in older people par-ticipating in geriatric rehabilitation that significantly impairs their functional progress. These findings underline the importance of recognizing and treating depressive symptoms to increase the effectiveness of rehabilitation and improve the well-being of older patients. Integrating mental health support into geriatric rehabilitation programs is critical to optimizing patient outcomes.

Interleukin-12 (IL-12) is considered to be a promising cytokine for enhancing anti-tumor immune response. However, recombinant IL-12 had significant toxicity and limited efficacy in early clinical trials. Recently, many strategies for delivering IL-12 to tumor tissues have been developed, such as modifying IL-12, utilizing viral vectors, non-viral vectors and cellular vectors. Previous studies have found that IL-12 fusion with extracellular matrix proteins, collagen and immune factors is a way to enhance its therapeutic potential. In addition, studies have demonstrated that viral vectors are a good platform, and a variety of viruses such as oncolytic viruses, adenoviruses and poxviruses have been used to deliver IL-12, and testing has been conducted in various cancer models. Local expression of IL-12 in tumors based on viral delivery avoids systemic toxicity while inducing effective anti-tumor immunity and acting synergistically with other therapies without compromising safety. Also, lipid nanoparticles are currently considered to be the most mature drug delivery system. Moreover, cells are also considered to be drug carriers because they can effectively deliver therapeutic substances to tumors. In this article, we will systematically discuss the antitumor effects of IL-12 on its own or in combination with other therapies based on different delivery strategies.

(1) Polycyclic aromatic hydrocarbons (PAHs) are hazardous organic compounds with known carcinogenic and toxic properties. Exposure to PAHs occurs through various sources, including diet, inhalation, and skin contact, and they can transfer into breast milk following maternal exposure, potentially endangering breastfeeding infants. (2) This study aimed to determine the PAH content in breast milk samples from 50 Hungarian mothers using high-performance liquid chromatography with fluorescence detection (HPLC/FLD). The carcinogenic risk to infants was estimated using the Incremental Life Risk Calculation (IRCL) model. (3) Total PAH concentrations ranged from 0 to 78 ng/mL, with fluorene (5.3 ng/mL), phenanthrene (3.2 ng/mL), and pyrene (2.5 ng/mL) being the most abundant. PAHs were detected in 48 of the 50 samples, with phenanthrene present in 92% of samples. Dibenzo (a,h)anthracene was not detected. (4) Based on IRCL calculations, 10% of the samples were classified as safe, while 88% presented an acceptable carcinogenic risk for infants. Statistical analysis of questionnaires completed by the mothers indicated that factors such as diet, residence, and education may influence PAH levels in breast milk.

Post-transplant lymphoproliferative disorders (PTLD) pose significant risks following organ transplantation, characterized by potential aggressiveness. This report aims to discuss a case of PTLD presenting as B-cell large cell lymphoma (DLBCL) post-kidney and pancreas transplantation. A 44-year-old female with type 1 diabetes underwent kidney and pancreas transplantation. She presented with fever, night sweats, and weakness, revealing multiple lesions on CT, including in transplanted and native kidneys, pancreas and lung. Biopsy of transplant kidney confirmed PTLD, DLBCL subtype, with complex immunohistochemical findings. Chemotherapy (R-CHOP) was initiated but complicated by infusion reactions and bowel perforation necessitating surgery and antibiotics. Despite the complications, the normal function of the transplanted kidney is maintained, which made it possible to implement the standard chemotherapy protocol. This case underscores the diagnostic challenges and therapeutic complexities of PTLD, specifically DLBCL, in transplant recipients. Comprehensive evaluation and vigilant management are crucial for successful outcomes in such cases.

Basic education is a foundational component of the national education system and human resource development, providing crucial support for the sustainable development of various aspects of human society, including economy, social welfare, and technology. The advancement of basic education is intrinsically linked to national innovation, the well-being of the populace, and the sustainable high-quality development of society. Enhancing the ecological carrying capacity of basic education at the provincial level is critical and pragmatically significant for the coordinated, sustainable, and high-quality development of the region's socioeconomic landscape.Based on panel data from the Guangxi Zhuang Autonomous Region (hereinafter referred to as Guangxi) from 2013 to 2022, and utilizing the DPSIR theoretical model, a comprehensive evaluation index system has been established. Through statistical analysis and spatial analysis methods, this study explores the temporal and spatial evolution characteristics of the ecological carrying capacity of basic education in various regions under Guangxi's jurisdiction. A multiple linear regression model is employed to analyze the differential impacts of changes in economic structure on the ecological carrying capacity of basic education.The findings reveal a steady upward trend in the ecological carrying capacity of basic education across the municipal districts of Guangxi. The development of five subsystems—Pressure, Driving-force, and others—has also become increasingly balanced; however, the impact of each subsystem on the overall carrying capacity varies. From a formation mechanism perspective, the ecological carrying capacity of basic education in Guangxi is the result of the complex interactions of multiple factors, with notable differences in influencing factors at various stages of development.Therefore, to bridge the regional disparities in the ecological carrying capacity of basic education across the different areas of Guangxi, it is essential to adopt a range of measures that promote coordinated, balanced, and high-quality educational development among regions, effectively ensuring the long-term sustainable development of Guangxi's economy and society.

The utilization of sustainable biomaterials in pharmaceutical and medical applications has garnered significant attention in recent years due to their potential to address environmental concerns while meeting the demands of modern healthcare. This review provides a comprehensive overview of the latest advancements and applications of sustainable biomaterials in the pharmaceutical and medical fields. Beginning with an exploration of sustainable sourcing methods and production techniques, the review highlights the importance of eco-friendly practices in biomaterial development. Subsequently, it delves into the diverse range of sustainable biomaterials, including biopolymers, natural extracts, and bio-based nanoparticles, elucidating their properties and biomedical applications. Moreover, the chapter discusses the role of sustainable biomaterials in drug delivery systems, tissue engineering, wound healing, and medical device fabrication, emphasizing their biocompatibility, biodegradability, and therapeutic efficacy. Along with discussions on regulatory issues and commercialization prospects, the potential and challenges related to the integration of sustainable biomaterials into pharmaceutical and medical practices are also critically reviewed. By elucidating the advancements and potential of sustainable biomaterials, this article aims to inspire further research and innovation in the pursuit of environmentally friendly and effective solutions for healthcare applications.

The issue of managing waste bread is a global concern, with significant environmental and the economic implications. The utilisation of waste bread for bioethanol production, employing energy-saving tech-nology, could prevent these consequences and reduce the consumption of traditionally used fossil fuels. The objective of this study was to evaluate the influence of the type of waste bread (wheat and wheat-rye sourdough) and the mash preparation method on the results of alcoholic fermentation and the concen-tration of selected congeners in the distillates. The highest fermentation efficiency (96% of theoretical) was achieved for both types of bread through the utilisation of the pressureless starch liberation method combined with simultaneous saccharification and fermentation. The separate saccharification of starch did not result in an enhanced efficiency of the process. Despite a slight reduction in efficiency of the process, the hydrolysis of native starch was regarded as a promising solution for the processing of waste bread to ethanol. All of the obtained distillates exhibited a low concentration of methanol. The elevated acidity and aldehydes levels, in relation to the national recommendations, indicate the potential necessity for the separation of the volatile congeners depending on the intended use of the obtained spirit distillates.

There is a global demand for alternative energy sources away from unsustainable fossil fuels. COP26 agreed that fossil fuels should be phased down; at COP27, anxiety about the cost and availability of energy was raised, and COP28 reiterated the phasedown of coal power. Solar technology in the form of Perovskite solar cells is one such alternative energy source. This article considers the fabrication of the Perovskite layer in a solar cell and postulates the extent to which Material Flow Cost Accounting (MFCA) could be used as a feasible costing method, among other things, to address byproduct and waste generation. Through MFCA, the monetary and physical flows of materials are identified and can be applied throughout the supply chain to facilitate affordability, from the extraction of the ore, transportation, fabrication of the chemicals, manufacturing and distribution of the solar cell and panels, and finally, the recycling of the panel. Informed by these observations, a conceptual framework for applying MFCA in fabricating the Perovskite layer in the supply chain is developed based on sets of qualitative propositions. Future work will be researching the processes of manufacturing solar cells, costing raw materials, energy flows, and solar cell manufacturing emissions.

Statins are the main cholesterol-lowering treatments, but often they are stopped because of statin myopathy. Expensive second-line treatments are then prescribed, causing a burden on the health system. Creatine supplementation may be a safe, effective and cheap alternative this shift. We investigated tolerability and possible effectiveness of creatine supplementation in statin myopathy. Our data confirmed previous findings showing that creatine supplementation is safe and well tolerated even in this elder population. In fact, 11 of the 13 enrolled patients completed the study, and only one patient interrupted the study because of a creatine-related issue (elevation of serum creatinine). Creatine supplementation significantly reduced the Shewmon and Craig’s “myopathy score”, while it did not reduce serum creatine kinase (CK), a marker of muscle structural damage. Notably, creatine supplementation was effective at the dose of 1g. t.i.d., lower that usually prescribed in international literature and within the recommendations of health agencies like the Italian Ministry of Health. Thus, creatine supplementation may improve statin myopathy in its milder and/or earlier form, when serum CK is not elevated. Moreover, creatine supplementation may prevent or delay switching from statins to the very expensive second-line anti-cholesterol treatments.

Cyclic peptides have higher stability and better properties as therapeutic agents than their linear peptide analogues. Consequently, intramolecular click chemistry is becoming an increasingly popular method for the synthesis of cyclic peptides from their isomeric linear peptides. However, assessing the purity of these cyclic peptides by mass spectrometry is a significant challenge, as the linear and cyclic peptides have identical masses. In this paper, we have evaluated the analytical capabilities of energy-resolved mass spectrometry (ER MS) and mid-infrared microscopy (IR) to address this challenge. On the one hand, mixtures of both peptides were subjected to Collision Induced Dissociation tandem mass spectrometry (CID MS/MS) experiments in an ion trap mass spectrometer at several excitation energies. Two different calibration models were used: a univariate model (at a single excitation voltage) and a multivariate model (using multiple excitation voltages). The multivariate model demonstrated slightly enhanced analytical performance, which can be attributed to more effective signal averaging when multiple excitation voltages are considered. On the other hand, IR microscopy was used for the quantification of the relative amount of linear peptide. This was achieved through univariate calibration, based on the absorbance of an alkyne band specific to the linear peptide, and through Partial Least Squares (PLS) multivariate calibration. The PLS calibration model demonstrated superior performance in comparison to univariate calibration, indicating that consideration of the full IR spectrum is preferable to focusing on the specific peak of the linear peptide. The advantage of IR microscopy is that it is linear across the entire working interval, from linear peptide molar ratios of 0 (equivalent to pure cyclic peptide) up to 1 (pure linear peptide). In contrast, the ER MS calibration models exhibited linearity only up to 0.3 linear peptide molar ratio. However, ER MS showed better performances in terms of limit of detection, intermediate precision and root-mean-square-error of calibration. Therefore, ER MS is the optimal choice for the detection and quantification of the lowest relative amounts of linear peptide.

This study investigates user behavior in urban green spaces (UGS) in downtown Shanghai prior to the COVID-19 pandemic. UGS are essential public infrastructure, contributing to urban sustainability, quality of life, and social cohesion. Although widely studied, there remains a gap in urban studies and environmental behavior research regarding UGS use from the perspective of space appropriation. This study addresses this by analyzing user demographics, frequency, and spatial activity patterns to assess how different forms of space use can be evaluated across varying levels of appropriation. Using a mixed-methods design, non-participant observation and behavior mapping were conducted across three comprehensive parks in Shanghai, divided into nine observation zones. Data were analyzed using the Pandas library in Python 3.6, descriptive statistics, and qualitative coding. Findings revealed sixty distinct activity types, predominance of elderly male users, absence of teenagers, and activity peaks in the early morning and late after-noon. Structured patterns of engagement suggest a soft to moderate level of appropriation. This research underscores the effectiveness of observational methods, validates appropriation as an analytical category, and emphasizes the importance of structured classification systems for improving understanding of UGS use and its societal role.

This paper investigates the integration of Graph Neural Networks (GNNs) and incremental learning for blockchain applications, with a focus on fraud detection, anomaly detection, and smart contract verification. By leveraging graph structure exploitation, GNNs can propagate information across nodes, reducing label dependency. Incremental learning enhances the model's adaptability to evolving blockchain networks, allowing continual learning without full retraining. Together, these technologies provide a scalable, efficient solution for improving security, performance, and adaptability in decentralized financial systems and smart contract environments.

Background/Objectives: Thyroid cancer, particularly well-differentiated thyroid cancer, is one of the most prevalent endocrine malignancies, with a rising incidence. Although it generally has a favorable prognosis, recurrence is common. Accurate prediction of recurrence is crucial for optimizing treatment plans and improving patient outcomes. This study aimed to advance the state-of-the-art in thyroid cancer recurrence prediction by refining feature engineering techniques and exploring a diverse ensemble of machine learning algorithms and an artificial neural network, using the differentiated thyroid cancer dataset from the UCI Machine Learning Repository; Methods: Various unsupervised data engineering methods, such as dimensionality reduction and clustering, were employed to enhance feature quality and mitigate noise, using stratified 10-fold cross-validation. The best-performing dimensionality reduction techniques were used to build classification model pipelines employing each of several machine learning models and an artificial neural network. The performance of these classification pipelines were assessed using metrics sensitive to class imbalance; Results: Principal Component Analysis and Truncated Singular Value Decomposition achieved superior clustering performance and moderate variances in their first principal components. Logistic Regression, Random Forest, Support Vector Machine, K-Nearest Neighbors, and Feedforward Neural Network models all achieved high performance, with Logistic Regression pipelines demonstrating balanced accuracy, F1 score, AUC, sensitivity, specificity, and precision—all greater than 0.93 on the test set and slightly lower in 10-fold cross-validation. Gradient Boosting classification pipelines performed the lowest, though still with respectable metrics; Conclusions: This study shows that employing feature engineering techniques like Principal Component Analysis or Truncated Singular Value Decomposition in Logistic Regression, Random Forest, Feedforward Neural Networks, Support Vector Machine, and K-Nearest Neighbors classification pipelines can improve thyroid cancer recurrence prediction accuracy and reliability, supporting more personalized treatment strategies in post-treatment patients.

In this paper, we conduct a comprehensive analysis of the RounD dataset to enhance the understanding of motion forecasting for autonomous vehicles in complex roundabout environments. We implement a trajectory prediction framework that combines Long Short-Term Memory (LSTM) networks with graph-based modules to model vehicle interactions. Our primary objective is to assess the generalizability of a standard trajectory prediction model across diverse training and testing datasets. Through extensive experiments, we analyze how varying data distributions, including different road configurations and recording times, influence the model’s prediction accuracy and robustness. This study provides key insights into the challenges of domain generalization in autonomous vehicle trajectory prediction.

Companies operating in the PayTech and online e-commerce sectors play a crucial role in critical infrastructure, functioning within the dynamic digital landscape. This study focuses on the recovery process after cyber-attacks and examines the contrasting perspectives of internal and external professionals. The research reveals notable differences in the perceptions of recovery strategies between internal stakeholders such as investor relations, reputation management, and Chief Information Security Officers, representing companies belonging to critical infrastructure and external auditors, who provide just and emergency support and perform specific tasks. Importantly, the study underscores the current attitudes towards future information security strategies and their influence on the financial recovery and reputation of reliable companies following cyber incidents. This research contributes to the existing knowledge by shedding light on the perspectives of both a company's internal and external specialists involved in the recovery process and cyber resilience strategies in critical infrastructure sectors.

There is a pressing need for tools that can rapidly predict PM2.5 concentrations and assess health impacts under various emission scenarios, aiding in the selection of optimal mitigation strategies. Traditional chemical transport models (CTMs) like CMAQ are accurate but computationally intensive, limiting practical scenario analysis. To address this, we propose a novel method integrating a conditional U-Net surrogate model with health impact assessments, enabling swift estimation of PM2.5 concentrations and related health effects. The U-Net model was trained with 2019 South Korean PM2.5 data, including precursor emissions and boundary conditions. Our model showed high accuracy and significant efficiency, reducing processing times while maintaining reliability. By combining this surrogate model with the EPA’s BenMAP-CE tool, we estimated potential premature deaths under various emission reduction scenarios in South Korea, extending projections to 2050 to account for demographic changes. Additionally, we assessed the required PM2.5 emission reductions needed to counteract the increase in premature deaths due to an aging population. This integrated framework offers an efficient, user-friendly tool that bridges complex air quality modeling with practical policy evaluation, supporting the development of effective strategies to reduce PM2.5-related health risks and estimate economic benefits.

Interactive device design traditionally prioritizes delaying or preventing degradation during the functional phase, as it is generally perceived as a disadvantage. However, the concept of intentionally designing controlled material breakdown can unlock new properties and functions that enhance both the system and its environment. This approach, termed "Degrade to Upgrade", challenges the conventional view of degradation as merely an end-of-life process. Instead, it encourages Human-Computer Interaction (HCI) researchers and designers to see it as an active phase, one that can be leveraged for innovative device design.

Evaluating altered mental status and suspected meningeal disorders in children often begins with imaging, typically before a lumbar puncture. The challenge is that meningeal enhancement is a common finding across a range of pathologies, making diagnosis complex. This review proposes a categorization of meningeal diseases based on their predominant imaging characteristics. It includes a detailed description of the clinical and imaging features of various conditions that lead to leptomeningeal or pachymeningeal enhancement in children and adolescents. These conditions encompass infectious meningitis (viral, bacterial, tuberculous, algal, and fungal), autoimmune diseases (such as anti-MOG demyelination, neurosarcoidosis, Guillain-Barré syndrome, idiopathic hypertrophic pachymeningitis, and NMDA-related encephalitis), primary and secondary tumors (including diffuse glioneuronal tumor of childhood, primary CNS rhabdomyosarcoma, primary CNS tumoral metastasis, extracranial tumor metastasis, and lymphoma), tumor-like diseases (Langerhans cell histiocytosis and ALK-positive histiocytosis), vascular causes (such as pial angiomatosis, ANCA-related vasculitis, and Moyamoya disease), and other disorders like spontaneous intracranial hypotension and posterior reversible encephalopathy syndrome. Despite the nonspecific nature of imaging findings associated with meningeal lesions, narrowing down the differential diagnoses is crucial, as each condition requires a tailored and specific treatment approach.

Introduction: Intraductal papillary mucinous neoplasms (IPMN) are commonly-detected pancreatic cysts that may transform into pancreatic ductal adenocarcinoma (PDAC). Predicting which IPMNs will progress to PDAC remains a clinical challenge. Moreover, identifying those clinically evident IPMNs for which a surveillance approach is best is a dire clinical need. Therefore, we aimed to identify molecular signatures that distinguished between PDAC with and without clinical evidence of a IPMN to identify novel molecular pathways related to IPMN-derived PDAC that could help guide biomarker development. Methods: Data from the Oncology Research Information Exchange Network (ORIEN) multi-institute sequencing project was utilized to analyze 66 PDAC cases from Moffitt Cancer Center and The Ohio State University Wexner Medical Center for which tumor whole transcriptome sequencing datasets were generated. Cases were classified based on whether a tumor had originated from an IPMN (n=16) or presumably through the pancreatic intraepithelial neoplasia (PanIN) pathway (n=50). We then performed differential expression and pathway analysis using Gene-Set Enrichment Analysis (GSEA) and Pathway Analysis with Downweighted Genes (PADOG) algorithms. We also analyzed immune profiles using the Tumor-immune Microenvironment Deconvolution Web-portal for Bulk Transcriptomics (TIMEx). Results: Both GSEA and TIMEx indicate that PanIN-derived PDAC tumors enrich inflammatory pathways (complement, hedgehog signaling, coagulation, inflammatory response, apical surface, IL-2/STAT5, IL-6/STAT3, EMT, KRAS signaling, apical junction, IFN-gamma, allograft rejection) and are comparatively richer in almost all immune cell types than those from IPMN-derived PDAC upon deconvolution. IPMN-derived tumors were enriched in metabolic and energy generating pathways (oxidative phosphorylation, unfolded protein response, pancreas beta cells, adipogenesis, fatty acid metabolism, protein secretion). Further, the metabolic-linked gene signature enriched in the IPMNderived samples is associated with a cluster of early stage and long survival (top 4th quartile) PDAC cases from the Cancer Genome Atlas (TCGA) expression database. Intriguingly, the gene most significantly upregulated for both the improved survival group and IPMN-derived PDAC was gastrokine-2 (GKN2, padj<0.001), a gene upregulated in PDAC precursor lesions (compared to PDAC). Conclusions: Our data suggest that IPMN-derived and PanIN-derived PDACs differ in the expression of immune profiles and metabolic pathways. These initial findings support future studies to assess the accuracy of identifying PDACs arising from IPMN lesions based on either GKN2 expression or their metabolic or immune profiles and explore mechanisms to explain these findings.

The relationship between Portugal and England spans centuries, encompassing political alliances, economic cooperation, cultural exchanges, and significant periods of tension and exploitation. This article provides a comprehensive and critical overview of the historical relations between Portugal and England from medieval times to the present, highlighting both the cooperation and the conflicts that have shaped this complex alliance. It explores key events, treaties, and figures that have influenced the trajectory of the relationship, including the heavy indebtedness Portugal accumulated with England and how this debt was transferred to Brazil in exchange for its independence—a factor that perpetuated social distortions such as slavery and inequality in Brazil. The article also discusses the contemporary context of Portugal-England relations, emphasizing the continued importance and challenges of this partnership in the modern world.

Physical inactivity is a leading risk factor for non-communicable diseases. Climate change is now regarded as the biggest threat to global public health. Electric micromobility (e-micromobility, including e-bikes e-cargo bikes and e-scooters) has the potential to simultaneously increase people’s overall physical activity while decreasing greenhouse gas emissions where it substitutes for motorised transport. The ELEVATE study aims to understand the impacts of e-micromobility, including identifying the people, places and circumstances where they will be most beneficial in terms of improving people’s health while also reducing mobility-related energy demand and carbon emissions. A complex mixed methods design collected detailed quantitative and qualitative data from multiple UK cities. First, a nationally representative (n=2000), city-wide (n = 1200) and targeted study area surveys have collected data on travel behaviour, levels of physical activity, vehicle ownership and use as well as attitudes towards e-micromobility. Then, to provide insights on an understudied type of e-micromobility, 49 households have been recruited to take part in e-cargo bike one-month trials. Self-reported data from participants are validated with objective data using methods such as GPS trackers and smartwatches recording of routes and activities. CO₂ impacts of e-micromobility use are also calculated. Participant interviews provided detailed information on preferences, expectations, experiences, barriers and enablers of e-micromobility.

The objective was to evaluate the effect of 3-nitrooxypropanol (3-NOP) in combination with dif-ferent feed additives on growth performance, carcass traits, meat quality, enteric methane (CH4) emissions, nutrient intake and digestibility, and blood parameters in feedlot beef cattle. In ex-periment (Exp.) 1, one hundred sixty-eight Nellore bulls (initial bodyweight (BW) 410 ± 8 kg) were allocated to 24 pens in a completely randomized block design. In Exp. 2, thirty Nellore bulls (Initial BW 410 ± 3 kg) were allocated to a collective pen in a completely randomized design. Three treatments were applied: Control (CTL): Sodium monensin (26 mg/kg of dry matter, DM), M3NOP: CTL with 3-NOP (100 mg/kg DM) and Combo: 3-NOP (100 mg/kg DM) with essential oils (100 mg/kg DM), 25-Hydroxy-Vit-D3 (0.10 mg/kg DM), organic chromium (4 mg/kg DM), and zinc (60 mg/kg DM). In Exp 1, bulls in Combo had greater (P

You Only Look One (YOLO) and its variants have emerged as the most popular real-time object detection algorithms. They have been widely used in real-time smart transportation applications due to their low-latency detection and high accuracy. However, because of the diverse characteristics of YOLO models, choosing selecting the optimal model according to various applications and environments in smart transportation is critical. In this article, we conduct an empirical evaluation and analysis study for most YOLO versions to assess their performance in smart transportation. To achieve this, we first measure the average precision of YOLO models across multiple datasets (e.g., COCO, PASCAL VOC). Second, we analyze the performance of YOLO models on multiple object categories within each dataset, focusing on classes relevant to road transportation such as those commonly used in smart transportation applications. Third, multiple intersection-over-union (IoU) thresholds are considered in our performance measurement and analysis. By examining the performance of various YOLO models across datasets, IoU thresholds, and object classes, we make six observations on these three aspects while aiming to identify optimal models for road transportation scenarios. Thus, YOLOv5 and YOLOv8 outperform other models in all three aspects due to their novel performance features. For instance, YOLOv5 achieves stable performance thanks to its cross-stage partial darknet-53 (CSPDarknet53) backbone, auto-anchor mechanism, and efficient loss functions including IoU loss, complete IoU loss, focal loss, gradient harmonizing mechanism loss. Similarly, YOLOv8 outperforms others with its upgraded CSPDarknet53 backbone, anchor-free mechanism, and efficient loss functions like complete IoU loss and distribution focal loss.

Text CAPTCHAs are crucial security measures employed on global websites to deter unauthorized intrusions. The presence of anti-attack features incorporated into text CAPTCHAs limits the effectiveness of breaking them, despite CAPTCHA recognition being an effective method for assessing their security. This study introduces a novel color augmentation technique called Variational Color Shift (VCS) to boost the recognition accuracy of different networks. VCS generates a color shift range of every input image and then resamples the image within that range to generate a new image, thus expanding the number of samples of the original dataset to improve training effectiveness. In contrast to Random Color Shift (RCS) which treats the color offsets as hyperparameters, VCS uses the estimated offsets to reparametrize the points sampling from the unit uniform distribution to reconstruct new image pixels, which makes the offsets learnable. To reduce the computational effort of VCS, we also propose two variants of VCS: Sim-VCS and Dilated-VCS. In addition, to solve the overfitting problem caused by many disturbances in CAPTCHAs, we propose an Auto Encoder (AE) based on a Large Separable Kernel Attention (AE-LSKA) to replace the convolutional module in the text CAPTCHA recognizer. This new module employs an AE) to compress the interference while expanding the receptive field using Large Separable Kernel Attention (LSKA), which reduces the impact of local interference on the model training and improves the overall perception of characters. The experimental results show that the recognition rate of the model after integrating the AE-LSKA module is improved by at least 15 percentage points on both M-CAPTCHA and P-CAPTCHA datasets. In addition, experimental results demonstrate that color augmentation using VCS is more effective in enhancing recognition.

Thorium is a weak radioactive element, but the control of its concentration in natural aqueous systems is of great interest for health, because it is a toxic heavy metal. The present paper presents the recovery of thorium from diluted synthetic aqueous systems by nanofiltration. The membranes used for nanofiltration of systems containing thorium species are composites containing 4′-Aminobenzo-15-crown-5 ether (ABCE) and sulfonated poly–ether–ether–ketone (sPEEK). The composite membranes (ABCE–sPEEK) were characterized by scanning electron microscopy (SEM), energy dispersive X–ray spectroscopy EDAX, thermal analysis (TG and DSC) and from the perspective of thorium removal performance. To determine the process performances, the variables were: the nature of the composite membrane, the concentration of thorium in the aqueous systems, the rotation speed of the stirrer, the pressure and the pH of the thorium aqueous system. When using pure water, a permeate flux value of 12 L·m⁻2 h⁻1 was obtained for sPEEK membrane, and up to 15 L·m⁻2 h⁻1 for the ABCE–sPEEK composite membrane. The use of mechanical stirring, with a propeller stirrer, leads to an increase in the permeate flux of pure water by about 20 % for each of the studied membrane. Depending on the concentration of thorium and the pH of the feed solution, retentions between 84.9 % and 98.4 % were obtained. An important observation is the retention jump at pH 2 for the ABCE–sPEEK composite membrane. In the paper, a thorium ion retention mechanism is proposed for the sPEEK membrane and the ABCE–sPEEK composite membrane.

This study examines the transformative potential of Artificial Intelligence (AI) in international trade, highlighting its significant roles in optimizing trade operations, enhancing trade finance, and improving market access. In trade optimization, through advanced machine learning and predictive analytics, AI helps in demand forecasting, route optimization, and customs processes, ensuring efficient logistics and inventory management. In trade finance, AI automates document processing and risk assessment, democratizing access to finance and enhancing transactional transparency through integration with blockchain technology. In improving market access, AI-driven analytics identify consumer trends and competitive dynamics, enabling personalized marketing and overcoming linguistic and cultural barriers. The study includes case studies of leading companies such as Alibaba, DHL, and Maersk, showcasing how they leverage AI to enhance their trade operations, improve customer service, and achieve greater efficiency. These real-world examples demonstrate AI's practical applications and significant benefits in the global trade landscape. However, the adoption of AI in international trade is not without challenges. These include data quality, ethical considerations, technological complexity, and public perception. Ensuring high-quality, accessible data, fostering ethical AI usage, and overcoming technological and regulatory barriers are crucial for successful AI integration. Policy recommendations emphasize the need for robust data infrastructure, ethical AI guidelines, and international cooperation to harmonize data protection regulations. These measures aim to create an environment conducive to AI-driven sustainable economic growth and innovation in global trade.

As interest in renewable fuels grows, biomass has gained increasing attention for its potential applications. Understanding the kinetic and thermodynamic parameters of biomass pyrolysis and combustion are crucial for optimizing its valorization. In this study, TGA was employed to examine bamboo powder's pyrolysis and combustion behaviors under different temperature ramps in nitrogen and air environments. The TG and DTG curves reveal that bamboo pyrolysis occurs in three distinct stages: drying, devolatilization, and carbonization. Similarly, combustion also proceeds through three stages: drying, devolatilization, and char combustion. Notable differences in the temperature ranges of the key stages were observed between pyrolysis and combustion. Moreover, kinetic parameters were evaluated using the KAS, FWO, and STR model-free approaches. The findings indicate that, the activation energy during the oxidative devolatilization stage of combustion are notably lower compared to those during pyrolysis devolatilization. The disparity in activation energy is even more pronounced in the third stage. Thermodynamic analysis shows that the pyrolysis and combustion of bamboo are endothermic and non-spontaneous. It can be stably converted into value-added energy through pyrolysis or combustion process. This study provides essential data to aid in designing and scaling up the thermochemical conversion processes for bamboo.

Abstract—Traditional automatic modulation classificationmethods operate under the closed-set assumption, which provesto be impractical in real-world scenarios due to the diversenature of wireless technologies and the dynamic characteristicsof wireless propagation environments. Open-set environments introduce substantial technical challenges, particularly in terms ofdetection effectiveness and computational complexity. To addressthe limitations of modulation classification and recognition inopen-set scenarios, this paper proposes a semi-supervised openset recognition approach, termed SOAMC (Semi-SupervisedOpen-Set Automatic Modulation Classification). The primaryobjective of SOAMC is to accurately classify unknown modulation types, even when only a limited subset of samples ismanually labeled. The proposed method consists of three keystages: (1) A signal recognition pre-training model is constructedusing data augmentation and adaptive techniques to enhancerobustness. (2) Feature extraction and embedding are performedvia a specialized extraction network. (3) Label propagation isexecuted using a graph convolutional neural network (GCN) toefficiently annotate the unlabeled signal samples. Experimentalresults demonstrate that SOAMC significantly improves classification accuracy, particularly in challenging scenarios with limitedlabeled data and high signal similarity. These findings are criticalfor the practical identification of complex and diverse modulationsignals in real-world wireless communication systems.

BackgroundContextualising the narrative on energy efficiency as the first fuel in the clean energy transition, the energy efficiency first principle (EE1) was introduced in EU energy and climate policy with the Energy Union communication in 2015 and made nonbinding with the EU Governance Regulation in 2018. In 2023, the EU legislators made EE1 legally binding to apply in policy, planning and investment decisions exceeding 100 million euros each and 175 million euros in the transport sector across all sectors that affect the energy system. Understanding the process through which new legislation is developed and adopted is important for understanding the policy itself, why it was designed in the way it was. Understanding the contextualisation of EE1 is particularly important since it introduced a paradigm shift in EU energy and climate policy. Better knowledge of the process of transformative policy change is important for policy and governance towards a clean energy transition for climate neutrality.ResultsApplying the multiple streams framework as a theoretical lens for analysing policy processes, this paper determines the policy process and the agency of policy entrepreneurs to make EE1 legally binding, from problem formulation to final adoption. Based on qualitative text analysis of policy documents, position papers and reports from EU negotiations, combined with interviews of key actors, the study shows how non-profit and non-governmental organisations such as the Regulatory Assistance Project (RAP), the European Climate Foundation (ECF) and the Energy Efficiency Financial Institutions Group (EEFIG), as well as the European Commission and the rotating Council Presidency, were critical policy entrepreneurs for coupling the problem, policy and politics streams. RAP together with ECF and EEFIG considered the unequal treatment of energy supply and energy demand in energy policy to hamper efficient use of the energy system and suggested the EE1 principle to overcome this problem. Using a broad set of strategies related to cultural-institutional entrepreneurship, such as attention- and support seeking strategies, linking strategies, relational management strategies, and arena strategies, they persuaded the European Commission to propose legislation on EE1. But the initial framing was too technical. for decision-makers to understand. The coupling of the problem–policy package to politics was performed once a policy window was opened by external and internal events such as the Paris Agreement on climate change, the entering office of the Ursula von der Leyen European Commission in late 2019, and the energy crisis in Europe following Russia’s second war on Ukraine. Climate change and security of supply were problems that decision-makers could understand. ConclusionsIt is concluded that coalition-building is important for policy entrepreneurs to gain broad acceptance for their policy proposals. In addition, timing is of great importance for policy entrepreneurs being able to couple a package of problems and policy solutions to the political stream. Political decision-makers must be receptive to the problem and its policy solution. This happens when a policy window of opportunity is opened. In this case, the policy entrepreneurs proposed a solution to what they perceived of as a problem almost seven years before the politics stream was mature and receptive. This led policy entrepreneurs to use ‘salami tactics’ to sequentially introduce policy change whit bits and pieces of the proposed policy instrument being implemented over a long period. It also highlights the need for endurance of policy entrepreneurs.But the study also raises ethical issues that policy entrepreneurship may not only be positive to democratic governance for the clean and just energy transition. The agency of policy entrepreneurs is often technocratic and non-transparent, and they take the role of political decision-makers but with no formal decision-making power, reducing possibilities to claim accountability, legitimacy and justice.

The dynamics of society is enabled, in large part, through an efficient matching between people who have money to lend and people who have a need to borrow. Fair loans serve both the lender and the borrower. This task is handled today mostly via traditional banks. They offer various plans to depositors from whence they serve borrowers. Proposing to replace such rigidity with cyberspace-rooted dynamic ad-hoc global matching of lenders and borrowers. Uniquely here we build a chain of lenders to support a single borrower. Lenders will post a proposition to lend a given amount of money for a stated duration for a set interest rate. Borrowers will post a request to borrow a desired amount of money, for a specified duration, and for which they are ready to pay a stated interest. A virtual digital bank (VDB) will match all the posts, negotiate terms as necessary, and move the money -- everyone benefits. Distributed Digital Lending, DDL, applies to macro, long terms loans, as well as to micro. very short terms loans. DDL efficiency will ensure that all money at rest will be money in growth, and the full global lending capacity will be put to good service through the exact loans borrowers want. DDL is hinged in digital transactions which are immediate, irrevocable, and private, per regulatory allowance. The matching is optimized with AI tools. BitMint*LeVeL is the design standard coin for DDL, but other digital money options will do too.

This study examines the current functioning of Health Care Bioethics Committees (HBCs) in Chile, with the objective of providing recommendations for improving public health care management. Through a comprehensive literature review and a case analysis of the ‘Hospital Clínico de la Universidad de Chile’, the structure, functions and challenges of the CEA are explored. The research reveals the importance of the multidisciplinary composition of the committees, the need for continuing education in bioethics, and the relevance of the consultative role in ethical decision making. The results suggest that the effectiveness of CABs does not necessarily depend on the number of members or the length of their terms of office, but on the quality of their training and experience. It is concluded that for adequate health care management, it is essential to strengthen the role of the CEA in the ethical education of health care personnel and in the development of institutional regulations, as well as to improve their visibility and accessibility within the Chilean health care system.

Recent advances in the research area of 3D magnetic topological solitons (hopfions) in restricted geometries are reviewed. The description of the magnetic solitons is based on macroscopic micromagnetic approach and the Landau-Lifshitz equation of the magnetization motion. The concepts of the gauge emergent vector potential and emergent magnetic field are widely used to calculate 3D topological charge (the Hopf index) of magnetic textures. The relation of the magnetic hopfions with classical field theory is demonstrated and a special role of the curvilinear toroidal coordinates in description of the hopfions is underlined. The hopfion stability and dynamics in ferromagnetic films and dots are considered. Some critical discussion of calculations of the magnetization emergent magnetic field and the Hopf index of the toroidal magnetic hopfions in restricted geometries is presented.

With consumers increasingly aware of the effects of human activity on the environment, tourism products and destinations are increasingly marketed as sustainable and socially responsible. As most sustainable practices lead to additional costs, and tourists’ decisions tend to be price sensitive, achieving sustainability goals necessarily involves understanding how much tourists are willing to pay extra for sustainable practices, as well as the antecedents of such Willingness to Pay (WTP). The present study aims to advance knowledge on the antecedents of WTP for Sustainable Destinations (WTP-4-SD), for which it builds on previous studies employing the Theory of Planned Behavior (TPB) and the New Environmental Paradigm (NEP). In this context, a theoretical model involving Ecotourism Attitudes, Environmental Beliefs, Climate Change-Related Risk Perceptions (CC-RRP), Environmental Concern During trip (ECDT), and Sustainable Consumption Behavior (SCB) as antecedents of WTP-4-SD is proposed. The model was tested based on data collected through an online survey, form a sample of 1,545 Spanish and Portuguese tourists, and analyzed through Structural Equations Modelling (SEM). The findings suggest that a cohesive set of attitudes and beliefs regarding the man-nature relationship, the risks of climate change and the role of tourism – which have been labelled “No Planet-B Attitudes” – is the main driver of WTP-4-SD.

Volunteering has many social, emotional and health benefits and could be an option for people with younger/early onset dementia to engage in stage and age-appropriate, personally meaningful activities within their local communities. This study explored how people with young onset dementia volunteer in the UK, the benefits and barriers, and how we can improve access to volunteering opportunities. Audio data of people with young onset dementia discussing their experiences of volunteering were taken from the Dementia Diaries audio and video diary project (https://dementiadiaries.org/). The data were co-analysed by a co-production team, (X), made up of six researchers living with young onset dementia and two facilitators. The findings suggest that stigma is the overarching concept (or net) which influences people’s experiences of volunteering with dementia. Within the stigma net, three themes were developed that employed a lifespan approach to challenging said stigma: 1) Valuing the past, 2) Valuing the present and 3) Valuing the future, each with additional subthemes. This research contributes to the limited pool of literature that highlights the clear benefits of volunteering for people with young onset dementia, while also considering how dementia stigma can create practical and institutional barriers to accessing volunteering. Guidance is provided for how to deliver meaningful and accessible volunteering opportunities.

This article is aimed at studying new finite difference methods for one-dimensional (1D) and two-dimensional (2D) space Riesz variable-order (VO) nonlinear fractional diffusion equations (SRVONFDEs). In the presented model, fractional derivatives are defined in the Riemann-Liouville type. Based on 4-point weighted-shifted-Gr\"unwald-difference (4WSGD) operators for Riemann-Liouville constant-order (CO) fractional derivatives, which have a free parameter and have at least third order accuracy, we derive 4WSGD operators for space Riesz VO fractional derivatives. In order that the fully discrete schemes have good stability and can handle the nonlinear term efficiently, we apply the implicit Euler (IE) method to discretize the time derivative, which leads to IE-4WSGD schemes for SRVONFDEs. The stability and convergence of the IE-4WSGD schemes are analysed theoretically. In addiction, a parameter selection strategy is derived for 4WSGD schemes and banded preconditioners are put forward to accelerate the GMRES methods for solving the discretization linear systems. Numerical resutls demonstrate the effectiveness of the proposed schemes and preconditioners.

Biobutanol is becoming more relevant as a promising alternative biofuel, primarily due to its advantageous characteristics. These include a higher energy content and density compared to traditional biofuels, as well as its ability to mix effectively with gasoline, further enhancing its viability as a potential replacement. A viable strategy for attaining carbon neutrality, reducing reliance on fossil fuels, and utilizing sustainable and renewable resources is the use of biomass to produce biobutanol. Lignocellulosic materials have gained widespread recognition as highly suitable feedstocks for the synthesis of butanol, together with various value-added byproducts. The successful generation of biobutanol hinges on three crucial factors: effective feedstock pretreatment, the choice of fermentation techniques, and the subsequent enhancement of the produced butanol. While biobutanol holds promise as an alternative biofuel, it is important to acknowledge certain drawbacks associated with its production and utilization. One significant limitation is the relatively high cost of production compared to other biofuels, additionally, the current reliance on lignocellulosic feedstocks necessitates significant advancements in pretreatment and bioconversion technologies to enhance overall process efficiency. Furthermore, the limited availability of biobutanol-compatible infrastructure, such as distribution and storage systems, poses a barrier to its widespread adoption. Addressing these drawbacks is crucial for maximizing the potential benefits of biobutanol as a sustainable fuel source. This document presents an extensive review encompassing the historical development of biobutanol production and explores emerging trends in the field.

The study provides a comprehensive and detailed analysis of the existing key policies and considerations in Taiwan's Other Effective Area-Based Conservation Measures (OECMs), with the objective of providing useful evidence-based insights for formulating new effective environmental-friendly policies and promoting the existing policies. The study adopts a mixed research methodology that entails the combination of qualitative and quantitative research methodological frameworks. The primary source of the quantitative data for the study is the World Database on Protected Areas (WDPA) which provides variable data on OECMs and a component of databases of the Protected Planet Initiative (PPI) which is the joint product of UNEP and IUCN, managed by UNEP-WCMC and the IUCN working with governments, communities and collaborating partners. The qualitative methodological framework for the research adopted a technical systematic review approach based on the three-step framework for systematic reviews that involved planning, conducting and reporting the review. The review was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The sources that were included in the review included scientific research materials that focused on the policies related to OECMs. Taiwan has a total of 92 individual areas that are designated as national protected areas (PAs) and OECMs and formally recognized by the World Database on Protected Areas (WDPA). Out of the 92 designated areas, only seven are managed by the Construction and Planning Agency while the remaining 85 areas are managed by the Forestry Bureau. In terms of designation, 37 areas are designated as major wildlife habitats, 21 areas are designated as nature reserves, 20 areas are designated as wildlife refuges, eight areas are designated as national parks and six areas are designated as forest reserves. The primary themes that were identified were associated with marine spatial planning, environmental impact assessment (EIA) and marine scientific research and included biodiversity, protected area consideration, geographically defined areas, coastal resources and marine ecosystems. Other Effective Area-Based Conservation Measures (OECMs) have not been widely implemented yet, but most countries, including Taiwan, are increasingly aligning their existing policies with the strategies outlined in the OECMs policies to achieve large area-based conservation targets and reduce biodiversity loss.

Impulsive buying is a growing problem of modern society with significant financial and psychological consequences, and it is necessary to examine the mechanisms underlying it. Understanding the mechanisms driving this behaviour is crucial. Impulsive buying consists of two key aspects: a cognitive aspect, characterised by a lack of planning and reflection, and an affective aspect, involving emotional responses that can occur before, during, or after a purchase. This study aimed to explore the relationship between personality traits, as measured by the HEXACO model, and tendencies toward impulsive buying. Specifically, it examined how the HEXACO traits differentially predict the cognitive and affective components of impulsive buying tendencies.

In order to study the influence factors of vertical bearing capacity of pile foundation under the special address condition of multi-layer karst cave, the finite element model of foundation pile in double-layer karst area was established by using a commercial general finite element software Ansys, the bearing capacity of concrete pile foundation with different rock height, different ec-centricity and different elastic modulus under the gradually increasing load was studied. The results show that: (1) Under the condition of constant external load, the maximum displacement of pile foundation increases with the increase of eccentricity; (2) With the increase of concrete strength, the maximum displacement decreases gradually, but the corresponding maximum stress is roughly the same; (3) The height of the rock cave has a great influence on the bearing capacity of the pile foundation. In the construction process, it is necessary to minimize or avoid passing through the area with higher karst caves.

Around 1637, Pierre de Fermat famously wrote in the margin of a book that he had a proof for the equation $a^n + b^n = c^n$ having no positive integer solutions for exponents $n$ greater than 2. This statement, now known as Fermat's Last Theorem, remained unproven for centuries, despite the efforts of countless mathematicians. Andrew Wiles' work in 1994 finally provided a rigorous proof of Fermat's Last Theorem. However, Wiles' proof relied on advanced mathematical techniques that were far beyond the scope of Fermat's time, raising questions about whether Fermat could have truly possessed a proof using the methods available to him. Wiles's achievement was widely celebrated, and he was awarded the Abel Prize in 2016 in recognition of his groundbreaking work. The citation for the award described his proof as a "stunning advance" in mathematics. The present work offers a potential solution to Fermat's Last Theorem that may be more aligned with the original approach that Fermat claimed to have used.

Metabolic syndrome, obesity, and type 2 diabetes are closely related. They are characterized by chronic inflammation and oxidative stress. Obesity is the most important risk factor for metabolic syndrome and type 2 diabetes. Metabolic syndrome is characterized by insulin resistance and elevated blood glucose levels, among other conditions. These disorders contribute to the development of type 2 diabetes, which can exacerbate other metabolic disorders. Numerous studies indicate that diet and nutrients can have a major impact on preventing and treating these conditions. One such ingredient is lycopene. It exhibits antioxidant and anti-inflammatory effects and can affect metabolic processes in the body. According to the research presented, lycopene supplementation may have significant potential in the prevention and treatment of metabolic syndrome, obesity, and type 2 diabetes.

Neurotensin (NT) is a peptide involved in digestion, neuromodulation, and cancer progression. NT and its receptors (NTR1 and SORT1 mainly) have been widely studied in oncology. Data show NT expression is under the control of sex steroid hormones, in particular estradiol. We focused on its involvement in three main female hormone-sensitive cancers: breast, ovarian, and endometrial cancer in a narrative review. NT, NTR1 and SORT1 are mostly expressed in these three cancers and their involvement in oncologic processes such as proliferation and invasion seems to match, as does their impact on prognosis for most. The development of NT receptor-targeted therapies, including theranostics and radioligand treatments, presents a promising avenue for personalized cancer treatment.

Hybrid Power Switches (HPS) combine the advantages of SiC unipolar and Si bipolar devices and therefore can bridge the gap between these technologies. In this paper, the performance of a hybrid power switch configuration based on the latest SiC MOSFET and Si IGBT technologies is presented. The device is evaluated through experimental measurements of its characteristics under various conditions. The results show the HPS can achieve switching losses as low as a SiC MOSFET while offering the high current capability of the IGBT without significant increase in costs.

The paper is dedicated to studying the influence of annealing temperature on the chemical, structural and electrophysical properties of low-k films made from porous organosilicate glasses containing terminal methyl groups. The films were deposited using centrifugation, followed by drying at 200 °C and annealing at temperatures ranging from 350 °C to 900 °C. Changes in refractive index, porosity, pore size, chemical composition, and electrical properties as a function of annealing temperature are evaluated. The results of JV measurements indicate that the methyl-modified film, which was annealed at 450 °С, demonstrates minimal leakage currents. This phenomenon can be explained by the almost complete removal of surfactant residues and non-condensed silanols, as well as the minimal thermal degradation of methyl groups. The results of the study on leakage current models in methyl-modified films, obtained at various annealing temperatures, lead us to conclude that the predominant mechanism of charge carrier transfer is Poole–Frenkel emission.

Background: Stroke is the third leading cause of disability, primarily due to motor, sensory, and cognitive impairments. Virtual reality (VR) has shown promising results in post-stroke rehabilita-tion, particularly for upper limb recovery. The World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0), aligned with the International Classification of Functioning, Disa-bility, and Health (ICF) principles, is a valid tool for measuring disability regardless of its cause. This study aimed to investigate the feasibility of VR TRAVEE system in upper limb rehabilitation for stroke patients. Methods: 14 stroke patients with residual hemiparesis were enrolled in the study. They underwent a 10-day program combining conventional therapy (CnvT) with VR rehabilitation. At baseline (T0), upper limb was assessed using the Modified Ashworth Scale (MAS), Active Range of Motion (AROM), and the Numeric Rating Scale (NRS) for pain. These assessments were repeated after the 10-day rehabilitation program (T1). Additionally, disability was measured using WHODAS 2.0 at T0 and again 30 days after completing the program. Results: Significant im-provements were observed in AROM, MAS scores for the shoulder, elbow, wrist, and metacar-pophalangeal joints as well as in the reduction of shoulder pain (p˂0.001). WHODAS scores de-creased across all six domains, with a statistically significant improvement in the cognition domain (p=0.011). Conclusions: Combining CnvT with VR as a rehabilitation approach enhances motor function in the upper limb. This method has the potential to reduce disability scores and promote neuroplasticity.

Excess sedentary behaviour (SB) and insufficient physical activity (PA) have been identified as risk factors for cardiometabolic diseases in adolescents, some factors may affect how much time they spent on these activities. This study sought to compare the SB and PA patterns as well as the compliance with PA recommendations by sex, geographical location, and time of the week in Mexican adolescents. In a cross-sectional design, we objectively assessed SB and PA in 106 adolescents (15 to 18 y) through waist-worn accelerometers for one week. The time spent in SB and in PA at different intensities was compared by sex, geographical location and time of the week with two-way and three-way repeated measures MANOVAs, while the compliance with physical activity recommendations (i.e. ≥60 min/day) was compared using chi-squared and McNemar tests. Male participants spent more time in moderate, vigorous, and moderate to vigorous PA than females both in the whole week and in weekdays (all p < 0.05). There was no significant difference in SB nor PA by geographical location (i.e., metropolitan vs non-metropolitan areas). Moreover, all participants spent more time on moderate, vigorous, and moderate to vigorous PA on weekdays than on weekends (p < 0.05). Compliance with international PA recommendations also showed a sex difference (males > females) and change between weekdays and weekends with no difference by geographical location. While geographical location does not seem to be a relevant factor, sex and time of the week appear to influence the SB and PA patterns in Mexican adolescents.

Chaos theory is widely used in the design of Pseudorandom Number Generators (PRNG), which produce number sequences with statistically uniform distributions and random appearance. However, certain methods for implementing chaotic maps can lead to dynamic degradation of the generated number sequences. To solve such problem, we develop a method for generating pseudo-random number sequences based on multiple one-dimensional chaotic maps. In particular, we introduce a Bernoulli chaotic map that utilizes function transformations and constraints on its control parameter, covering complementary regions of the phase space. This approach enables the generation of chaotic number sequences with a wide coverage of phase space, increasing uncertainty in the number sequence generation process. Moreover, by incorporating a scaling factor and a sinusoidal function, we develop a robust chaotic map, referred to as the Sine-Multiple Modified Bernoulli Chaotic Map (SM-MBCM), which ensures a high level of randomness, validated through statistical mechanics analysis tools. Using the SM-MBCM, we propose a Chaotic PRNG (CPRNG) and evaluate its quality through correlation coefficient analysis, key sensitivity tests, statistical and entropy analysis, key space evaluation, linear complexity analysis, and performance tests. Furthermore, we present an FPGA-based implementation scheme that leverages equivalent MBCM variants to optimize the electronic implementation process. Finally, we compare the proposed system with existing designs in terms of throughput and key space.

Reiner Gamma is a potential target for low-orbiting spacecraft or even surface-landed missions in the near future. Unfortunately, thus far no comprehensive low altitude (below 20 km) or surface measurements of the magnetic field, magnetic source and plasma environment have been made post-Apollo to complement and complete our understanding of the solar wind interaction with lunar magnetic anomalies and swirl formation. Acquiring the detailed geological knowledge of the Reiner Gamma region is significant for the above scientific targets. In this study, the following research work in the lunar Reiner Gamma magnetic anomaly region was carried out for the regional geological investigation: (1) the topographic and geomorphologic analysis; (2) elements, minerals and sequence analysis; (3) 1:10,000 regional geological map analysis. Our work helps define measurement requirements for possible future low-orbiting or surface-landed missions to the Reiner Gamma area or similarly magnetized regions of the lunar surface.

Schizophrenia can lead to significant and long-lasting deficits in patients' functionality. The present study aims to identify a theoretical index that predicts the ability of an antipsychotic to improve the functionality of patients with schizophrenia. An advantage of such a theoretical index is that it represents an attempt to supplement with theoretical information the data coming from meta-analysis and systematic reviews and could directly compare antipsychotics. Aspects such as pharmacodynamics, pharmacokinetics, and pharmaceutical forms have been considered. A total of 29 typical and atypical antipsychotics were analyzed. It was constructed the Predictive Impact of Antipsychotics on Functionality Index (PIAF). This parameter considers pharmacodynamics and administration comfort, each expressed through other parameters. PIAF is higher for antipsychotics with both high Pharmacodynamic Scores, which are correlated only with the active substance, and good Comfort of Administration Scores, which are correlated with both the pharmaceutical forms of antipsychotics and the active substance. The best ranking was obtained by the only partial agonist dopaminergic D2 antipsychotic with LAI formulation (aripiprazole LAI), followed by the atypical LAI antipsychotic with the rarest administrations (paliperidone LAI 6M). Given this ranking, a better antipsychotic would result from the combination of a partial dopaminergic agonist with the lowest possible administration frequency. According to PIAF, the most favourable for the functionality are atypical LAI antipsychotics. The partial agonist mechanism of D2 dopamine represents an advantage. Based on this functionality index, the clinical psychiatrist could select the most suitable antipsychotic for patients, with the ultimate goal of achieving individual maximum potential.

Industrial products e-commerce refers to the specific application of the e-commerce concept in the field of industrial products transactions. It enables industrial enterprises to conduct transactions via Internet platforms and reduce circulation and operating costs. Industry literature such as policies, reports and standards related to industrial products e-commerce contains abundant and crucial information. Through systematical analysis of the literature information, it is beneficial to explore and grasp the development characteristics and trends of the industrial products e-commerce. To study the characteristics and development status of industrial products e-commerce in China, literature comprising 18 policy documents, 10 industrial reports and 5 standards is deeply analyzed by employing text mining methods. Firstly, natural language processing (NLP) technology is utilized to pre-process the text data related to industrial products commerce. Then, word frequency statistics and TF-IDF keyword extraction are performed, and the results of word frequency statistics are visually displayed. Subsequently, the feature set is obtained by combining the manual screening method. The original text corpus is used as the training set by employing the skip-gram model in word2vec, and the feature words are transformed into word vectors in the multi-dimensional space. The k-means algorithm is used to cluster the feature words into groups. Moreover, the latent dirichlet allocation (LDA) method is also utilized to further group and discover the features. The research results based on text mining provide supportive decisions for uncovering the development characteristics and trends of industrial products e-commerce in China.

The current developments in the theory of quantum static triplet correlations and their associated structures (real r-space and Fourier k-space) in monatomic fluids are reviewed. The main framework utilized is Feynman’s path integral formalism (PI) and the issues addressed cover quantum diffraction effects and zero-spin bosonic exchange. The structures are associated with the external weak fields that reveal their nature, and due attention is paid to the underlying pair level structures. Without the pair level one cannot fully grasp the triplet extensions in the hierarchical ladder of structures, as both the pair and the triplet structures are essential ingredients in the triplet response functions. Three general classes of PI structures do arise: centroid, total continuous linear response, and instantaneous. Use of functional differentiation techniques is widely made and, as a bonus, this leads to identify an exact extension of the “classical isomorphism” when the centroid structures are considered. In this connection, the direct correlation functions, as borrowed from classical statistical mechanics, play a key role (either exact or approximate) in the corresponding quantum applications. Additionally, as an auxiliary framework, the traditional closure schemes for triplets are also discussed, owing to their potential usefulness for rationalizing PI triplet results. To illustrate some basic concepts, new numerical calculations (path integral Monte Carlo PIMC and closures) are reported. They are focused on the purely diffraction regime and deal with supercritical helium-3 and the quantum hard-sphere fluid.

Bee Pollen (BP) has many advantageous properties relying on its multitargeting potential, a new tendency in handling many challenging illnesses. In cancer and neurodegeneration, the antioxidant, anti-inflammatory, immunomodulatory, and antimutagenic effects of BP could be of unequaled importance and need further pharmacological and clinical investigation. Although being still limited, available data interestingly spotlights some floral sources with new and promising activities in-line with this investigation. In addition, we have identified many crucial bioactivities that are widely recognized to individual BP compounds but remain completely untapped in this valuable bee cocktail. A wide range of these compounds have been recently found to be endowed with great potential in modulating pivotal process in neurodegeneration and cancer pathophysiology, such as epigenetic regulation, microbiota composition and function, autophagy, cell death mechanisms, protein misfolding and aggregation and many other effects that we will detail in our current work. In addition, some widely present compounds in BP have only recently been isolated, while the number of studied BPs remain extremely limited compared to the endless pool of plant species that are distributed worldwide. Nevertheless, we have concomitantly elucidated that clinical profits from these promising perspectives are still impeded by some challenging hurdles such as limited bioavailability of the studied phytocompounds, diversity and lack of phytochemical standardization of BP, and the difficulty of selective targeting in some pathophysiological mechanisms. We finally present some interesting insights to guide future research and pave the way for urgent and simplified clinical investigations.

Introduction: The care of dependent people is eminently family-oriented, and often, there is a high level of dedication to this family care. Constant and continuous care leads to a series of negative psychological consequences. Social support has been related to improved mental health in family caregivers. We found heterogeneous results regarding the relationship between the types of social support received and the perceived level of support. In addition, to our knowledge, no reviews analyze this relationship among family caregivers. Therefore, we aimed to systematically syn-thesize the relationships between perceived and received social support in informal caregivers. Methodology: We have carried out a quantitative systematic review with meta-analysis, regis-tered in PROSPERO (id: CRD42023470047); the systematic search was carried out in the following databases: PubMed, CINAHL, PsycINFO, and Scopus, until November 2023. After the selection and review of the results, 12 studies were obtained, two of which were eliminated due to a high risk of classification bias. Regarding the results, a medium size positive statistical association was found (r = 0.43). The results were consistent, accurate, and robust. The Trim and Fill test showed a vari-ation of 7%. Subgroup analysis indicated no differences in the age group of the people cared for (adults or children), selection bias, and confounding bias. In conclusion, perceived social support is related to more social support received by family caregivers.

Dedifferentiated liposarcoma (DDLPS) is a rare and aggressive type of cancer primarily reported in humans, with no documented cases in animals. In this study, we present the first case of DDLPS in a wild amphibian species, Maculopaa medogensis. The tumor was discovered during a routine examination and diagnosed through a combination of advanced diagnostic methods, including micro-CT imaging, gross anatomical inspection, histological analysis, and immunohistochemistry. The tumor exhibited both well-differentiated and dedifferentiated components, characteristic of DDLPS, with evidence of tissue invasion and multiple metastases. Immunohistochemical analysis revealed strong positive expression of markers such as S100A4, CDK4, MDM2, and CD34, while Leptin expression was negative, further confirming the diagnosis. This is the first reported case of DDLPS in a non-human species, expanding our understanding of cancer in wildlife and underscoring the significance of amphibians as environmental indicators. These findings provide valuable insights for veterinary medicine and wildlife conservation, particularly regarding the role of environmental stressors in cancer development. This study highlights the need for comprehensive diagnostic approaches in wildlife pathology.

Objective: To evaluate the effect of different surface treatment methods on the shear bond strength (SBS) of metal brackets bonded to two types of CAD/CAM composite restorations: milled and 3D-printed. Materials and Methods: A total of 160 flat-shaped specimens (10×10×2 mm³) were prepared from four different CAD-CAM composites; two milled (Lava Ultimate™ [LU], and Grandio™ [GR]) and two 3D-printed (Crowntec™ [CT] and C&B Permanent™ [CB]). These specimens underwent thermocycling (5000 cycles at 5-55 °C), then were categorized based on the surface treatment into four groups (n=10): Group C (control, no surface treatment), Group HF (treated with 9.6 % hydrofluoric acid), Group DB (mechanical roughening by a diamond bur), and Group SB (sandblasting using aluminum oxide). Metal brackets were bonded, stored in artificial saliva for 24 hours, then thermocycled again. Shear bond strength (SBS) was tested using a universal testing machine until bracket debonding occurred. The adhesive remnant index (ARI) was assessed using a stereomicroscope to quantify the residual adhesive following debonding. Result: Regarding material, GR and LU restorations had significantly higher SBS values compared to CT and CB, ranging from 13.90 MPa to 20.35 MPa. Regarding surface treatment, SB and HF groups showed significantly higher SBS values. The ARI scores showed different adhesive modes of failure, with higher instances of scores 0 and 1 which indicate no or minimal adhesive remaining. Conclusion: Both milled and 3D-printed materials had adequate SBS for clinical use, with milled materials showing superior results. Surface treatments like sandblasting and HF significantly improved bond strength, with adhesive failure being common.

Machine unlearning is a critical process designed to allow machine learning models to forget or remove specific data upon request, particularly for privacy protection. While the primary objective of unlearning is to safeguard sensitive information, it introduces substantial privacy and security risks. This paper explores the two major categories of threats to machine unlearning: privacy attacks and security attacks. Privacy attacks, such as membership inference and model inversion, exploit residual information to infer or reconstruct sensitive data that should have been erased. Security attacks, particularly specific data poisoning, involve the injection of malicious data into the training process, which may leave lingering effects even after the unlearning process. In this paper, we provide an in-depth examination of these threats and propose several defense mechanisms. Differential privacy, adversarial training, and query limitations are highlighted as key defenses against privacy attacks, while data validation, adversarial examples, and post-unlearning audits are critical in mitigating security risks. Additionally, we discuss emerging methodologies like data provenance tracking and fine-tuning as crucial for ensuring unlearning processes are thorough and effective. Through these analyses, we aim to provide a comprehensive framework for strengthening the security and privacy of machine unlearning systems, enabling their broader adoption across industries such as healthcare, finance, and AI-driven technologies.

Omega-3 polyunsaturated fatty acids (ω-3 PUFAs, n-3 PUFAs), including eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), and alpha-linolenic acid (ALA), are essential polyunsatu-rated fats primarily obtained from fatty fish and plant-based sources. Compelling evidence from preclinical and epidemiological studies consistently suggests beneficial effects of ω-3 PUFAs on bone health and healthy aging processes. However, clinical trials have yielded mixed results, with some failing to replicate these benefits seen in preclinical models. This contraindication is mainly due to challenges such as low bioavailability, potential adverse effects with higher doses, and susceptibility to oxidation of ω-3 fatty acids, hindering their clinical effectiveness. This review provides an in-depth analysis of recent findings, focusing on clinical perspectives and encom-passing all relevant published studies to date, including preclinical and epidemiological research, with an emphasis on the role of omega-3 fatty acids in promoting bone health and supporting healthy aging. Additionally, it explores strategies to improve ω-3 PUFA efficacy, including na-noparticle encapsulation and incorporation of specialized pro-resolving mediators (SPM) derived from DHA and EPA, to mitigate oxidation and enhance solubility, thereby improving therapeutic potential. By consolidating evidence from various studies, this review underscores current in-sights and future directions in leveraging ω-3 PUFAs for therapeutic applications.

This study examines the evolution of the tourism industry in Chile during the period 2013-2019, focusing on its contribution to the country's Gross Domestic Product (GDP). Using data from the National Tourism Service (SERNATUR) and the Undersecretariat of Tourism, it analyzes the approximation of tourism GDP and its share in the Chilean economy. The results indicate a sustained growth of the tourism sector, with a contribution to GDP that reached 3.3% in 2019. The main Tourism Characteristic Activities (TCAs) contributing to this growth are identified, highlighting administrative and support activities, food services and accommodation. The study reveals growth patterns, fluctuations in the contribution of different TCAs, and the impact of external factors on the sector's performance. This research provides valuable insights for the formulation of tourism development policies and strategies in Chile.

Satellite navigation spoofing is a major challenge in the field of satellite/inertial integrated navigation security. To effectively enhance the anti-spoofing capability of low-cost GNSS/MEMS-SINS integrated navigation system, this paper proposes a method integrating a dual-antenna global navigation satellite system (GNSS) and a micro-inertial measurement unit (MIMU) to determine the two-dimensional (2D) directions of spoofing signal sources. The proposed method evaluates whether the single-difference carrier-phase measurements conform to the corresponding directions given in ephemeris files, and employs the micro-inertial navigation technology to determine the 2D directions of the signal source. Based on a set of short-baseline dual-station measurements, the accuracy of the proposed method in determining the 2D azimuths of satellites in synchronous orbits is verified, and the deviation from the real value is evaluated. The experimental results show that the proposed method can effectively identify the spoofed satellite signals while providing high-precision direction information at three different distances: 100m, 10km, and 36000km.The two-dimensional angles errors do not exceed 0.2 rad, 0.05 rad, and 0.01 rad, respectively.

This study reports the use of Nanotrap® Microbiome A Particles (NMAPs) to capture and concentrate viruses from diluted samples/specimens to improve their recovery and sensitivity of detection by real-time PCR/RT-PCR (qPCR/RT-qPCR). Five highly infectious animal disease viruses including goat pox virus (GTPV), sheep pox virus (SPPV), lumpy skin disease virus (LSDV), peste des petits ruminants virus (PPRV), and African swine fever virus (ASFV) were used in this study. After capture, the viruses remained viable and recoverable by virus isolation (VI) using susceptible cell lines. To assess efficacy of recovery, the viruses were serially diluted in phosphate buffered saline (PBS) or Eagle’s Minimum Essential Medium (EMEM) and then subjected to virus capture using NMAPs. The NMAPs and the captured viruses were clarified on a magnetic stand, reconstituted in PBS or EMEM, and analyzed separately by VI and virus-specific qPCR/RT-qPCR. The results of the qPCR/RT-qPCR showed up to 100-fold increase in the sensitivity of detection of the viruses following virus capture compared to the untreated viruses from the same dilutions. NMAPs were used to capture and concentrate viruses from clinical specimens to determine diagnostic sensitivity (DSe) that were comparable (100%) to the untreated specimens. NMAPs were also used to capture spiked viruses from EDTA whole blood (EWB). Virus capture from EWB was partially blocked, most likely by hemoglobin (HMB), which also binds NMAPs and outcompetes the viruses. The effect of HMB could be removed by either dilution (in PBS) or using HemogloBind™ (Biotech Support Group; Monmouth Junction, NJ) that specifically binds and precipitates HMB. Enhanced recovery and detection of viruses using NMAPs can be applicable to other highly pathogenic animal viruses of agricultural importance.

In this paper, I present a possible explanation for accelerated expansion of the universe, and introduce the cosmic scale, size of the universe and cosmic time, age of the universe. The observed expansion of the universe, which relates the stretching of Shrunk space to the new theory, is derived. This model is based on the two principal long-range forces: the gravitational force and the repulsive force generated by shrunk space. They are the two most basic fundamental quantities in the universe that govern cosmic evolution. They may provide the clockwork mechanism that operates our eternal cyclic universe. This model of Space-time and its unique properties of shrinking and stretching enables us to describe a sequence of events from the Big Bang to the Big Crunch.

High-intensity interval training (HIIT) is widely used in team sports, particularly in soccer. This study aimed to investigate the effects of a short-term, progressive- load HIIT program on the performance of under-15 soccer players. The sample consisted of 30 adolescent soccer players, aged 14, who were randomly divided into two groups: the control group (CG, n=15) and the intervention group (EX, n=15), which performed additional HIIT sessions. The duration of the training program was six weeks, with progressive overload applied every two weeks. Performance indicators, including speed over 10 and 30 meters, change of direction (COD) to the right and left (505 right and left), maximal oxygen uptake (30-15IFT), and repeated sprint ability (RSA) (RSAtotal, RSAmean, RSAdecrement), were measured before and after the training program. Significant improvement were observed in the intervention group in COD (505 right and left), 30-15IFT, and RSAtotal and RSAmean (p=0.027, p=0.005, p=0, p=0.015, p=0.031, p=0.028, respectively). The findings of the present study suggest that a short-term, progressively overloaded HIIT program can enhance direction change ability, aerobic capacity, and repeated sprint performance.

Brain health is a matter of great importance as we age, where memory loss and other cognitive declines become slowly apparent. There are numerous natural solutions, called nootropics, that can help mitigate this natural process. While some, such as ginkgo biloba, have been traditionally used for centuries, in many cases there is a lack of scientific evidence on their potential mechanisms and efficacy. To this end, the objective of the current study is to evaluate and compare several standardized herb extracts with potential nootropic effects, and from this analysis develop a formula and confirm its effect in healthy volunteers with mild cognitive impairment. A total of 9 standardized herb extracts were chosen based on previous scientific evidence and tested in human neural stem cell cultures exposed to oxidative stress. The expression of nerve growth factor (NGF), NRF2 and vascular endothelial growth factor (VEGF) were also analyzed. As a result, it was observed that an extract from Salvia officinalis revealed to have the most noticeable effect among the herbs analyzed. In further tests it was confirmed that its combination with rutin, a phenolic compound with potential nootropic effects, increased brain derived neurotrophic factor (BDNF) expression, as well as inhibiting acetylcholine esterase (AChE) activity. Finally, a randomized, double-blind placebo-controlled clinical study was conducted, testing the effects of the combination at two different doses, for 12 weeks, in healthy volunteers aged 50+ with mild cognitive impairment. Two questionnaires were applied, the MoCA and ADAS-Cog. As a result, both doses significantly improved several characteristics related to memory, particularly memory recall, with a more noticeable effect in the higher dose. Therefore, the results suggest that the long-term intake, at least 6-12 weeks, of a natural herb blend comprised of Salvia officinalis and rutin can help improve certain brain health-related parameters in healthy subjects with mild cognitive impairment.

Optimal upper extremity motor control and range of motion are necessary to achieve even the basic Activities of Daily Living (ADL) function. Stroke, with resulting hemiparesis, can significantly and negatively impact an individual’s ADL function. Functional Independence Measure (FIM) self-care score can provide assessment of what aspects and to what degree ADL functions are impaired. FIM self-care assessment can also track changes in ADL function during stroke recovery and rehabilitation. Recently, sensor-acquired 3D motion analysis of stroke patients’ upper extremity has shown promise as a potential alternative to assess ADL function. This observational study evaluates whether the sensor-acquired upper extremity reachable workspace (RWS) measure correlates with clinician-evaluated FIM self-care score in stroke patients. Seventeen patients with stroke were enrolled in the study. FIM self-care, NeuroQoL upper extremity, and reachable workspace outcome measures (relative surface area, RSA) were collected upon rehabilitation hospital admission, at discharge, and at 3-month visit. Pearson and Spearman’s rank correlation coefficients as well as multiple linear regression analyses were used to determine the relationships between FIM self-care, NeuroQoL, and reachable workspace RSAs. Moderately strong correlation between total reachable workspace RSA and total FIM self-care score at discharge and at 3-month were noted (r=0.619, r=0.661, p&lt;0.05), and similarly strong correlation was also noted with the upper extremity NeuroQoL total score (r=0.690, r=0.815, p&lt;0.05). Multiple linear regression analyses revealed a change in bilateral total RSA of 0.1 unit from admission to 3-month follow up correlated with respective change in FIM self-care score of 2.011 points (95%CI: 0.663-3.360). Longitudinal improvement in ADL function during stroke rehabilitation and recovery process is correlated with improvement in reachable workspace.

Modern methods of designing and constructing hydraulic pumps can no longer be imagined without the use of appropriate mathematical models, phenomena and processes that take place in concrete constructions. A mathematical model of a process represents an analytical interpretation with certain assumptions. Obtaining a mathematical model requires detailed theoretical research, based on knowledge of the laws of fundamental sciences and scientific disciplines in order to fully understand and interpret the process, based on which assumptions are adopted and model equations are defined. As mobile machines continue to evolve, so do the demands on their hydraulic systems. Efficiency, automation and other major industry trends present ongoing development opportunities for hydraulic systems used in mobile applications. Hydraulic systems remain an important component in a range of mobile applications, from construction and agricultural equipment to heavy trucks because of the power density they can provide for a range of work functions. The power density of hydraulics remains unmatched in many applications. The pump, as an essential hydraulic component, converts mechanical energy into hydraulic energy with a relatively small amount and speed of fluid.

Per- and polyfluoroalkyl substances (PFAS) are arguably the most common water contaminants in the world today. While several research experiments have been done to understand and remove PFAS from the environment, there is still a lot of unknown. Little has been known about the use of Machine learning (ML) to understand PFAS. This work hence reviews some leading ML approaches and applications in PFAS studies in the distribution, transport, removal, and occurrence predictions of PFAS. Several evaluation matrices were examined and used to perform this function. There are still a lot of areas whereby ML can be used to improve our PFAS knowledge base, some of these were briefly stated in this review.

It is argued that the compressibility of individual atoms is distinct from the compressibility of matter as a whole. The latter arises from variations in interatomic spacing, whereas the former is a purely quantum effect, characteristic of a given atomic species. Its magnitude can be deduced by solving the Schrödinger equation for an individual many-electron atom with modified external boundary conditions. Over a wide range of parameter space, quantum dilation or compression remains isoelectronic for neutral atoms but, at ultra-high pressures, reordering of their shell structure can occur. Their compression then ceases to be isoelectronic and their chemical properties, as well as their positioning in the Periodic Table, undergo sudden change.

The aim of this work is to propose an angular positioning solution for the round cutting insert of an indexable insert torus milling cutter, dedicated to the multi-axis milling process under HSM conditions. The solution was based on the development of a wear model using a nonlinear estimation method with an eigenfunction, the development of a tool life model taking into account parameter of the cutter blade working angle and the method of reference marking and insert mounting, as well as the measurement methodology. The own function adopted to approximate the wear of the tool over its useful life is adequate and provides a prediction accuracy of 90%. The developed procedure for angular positioning and measurement enables the entire cutting edge of the cutting blade to be fully used, so that the total lifespan of the tool as an indexable insert tool is significantly extended. In addition, the measured largest defect values between the worn cutting edge and the nominal outline of the insert indicate the location of “notching” type wear.

Glioblastoma is a challenge in neuro-oncology, with survival significantly influenced mainly by extent of resection and molecular markers. Despite advancements, the prognosis for IDH-wildtype glioblastoma remains poor, particularly when surgical resection is not possible. However, some patients exhibit unexpectedly extended survival despite the extent of resection. This study aims to analyze the determinants that contribute to these atypical survival rates among glioblastoma patients who have had solely biopsy procedures. We conducted a retrospective analysis of patients diagnosed with IDH- wildtype glioblastomas at our institution from 2017 to 2021, who underwent biopsy only. The study focused on evaluating the impact of demographic characteristics, clinical features, molecular markers and treatment modalities on survival outcomes (Overall Survival (OS) and Progression-Free Survival (PFS)). Statistical analyses included survival analysis and logistic regression for evaluating associations between OS and preoperative characteristics and postoperative treatments. The cohort included 99 patients, with a median age at diagnosis of 65.5 years. Median OS and PFS were 6.0 and 3.6 months, respectively. The multivariate analysis revealed that higher KPS scores before biopsy, no contrast uptake on imaging and any adjuvant therapy, particularly the use of bevacizumab, were independently associated to increased OS (HR=0.97, p=0.009. HR=0.7, p=0.015; HR=0.27, p=0.002, respectively). Out of 99 patients, 77.8% survived past the 3-month threshold, with 87.0% of this receiving adjuvant treatment. Only 8% of patients survived past 24 months, and in this group of patients, MGMT Methylation was observed in just 25% of cases. Kaplan-Meier analysis indicated a better prognosis with any type of adjuvant therapy across all patients, particularly so in those with KPS ≥70. Age did not significantly affect survival outcomes (OR=1.00, p=0.835). Our findings reveal that any adjuvant treatment, no contrast uptake on imaging and higher preoperative KPS are key determinants of survival in IDH wildtype glioblastoma and should therefore be considered when deciding whether to perform a biopsy.

A prominent class of reactions, reductive aminations are used extensively in research labs and industry to synthesize amines; which are applied in a variety of medicines, agrochemicals, and biomolecules. Amine compounds are essential in many aspects of life; amino groups exist in many natural and agricultural products. New 4-(benzylamino)benzoic acid derivatives with general formula of C14H12NO2R, where [R= (H), (4-Cl), (4-NMe), (4-Br), (3-NO2), (4-NO2), (2-OMe), (3-OMe), (4-OMe), (2,3-OMe), (3,4-OMe), (2-OH, 3-OMe), (3-OMe, 4-OH), (3,5-OMe, 4-OH), (2-OH, 5-Br), (3-OH), (4-SMe), (2,3-OH), (3-CF3)] (compounds 1-19) were obtained by reductive amination reaction via reacting p-amino benzoic acid with benzaldehyde derivatives and sodium borohydride. All prepared compounds has been characterized by a variety of spectroscopic techniques (HRMS, FT-IR, 1H, and 13C{1H} NMR) and elemental analysis. Furthermore, the structure of some of the synthesized derivatives were confirmed by single crystal X-ray diffraction (R = 4-Cl, 4-Br, 2-OMe, 3-OMe, 4-OMe, 2,3-OMe), compounds 2, 4, 7-9 and 11, respectively. Moreover, some of these new compounds have shown somehow moderate antibacterial activities against different strains of bacteria (gram-positive and gram-negative) with MIC values ranging from 64-256 µg/ mL. The anticancer activities of all compounds (IC50 values, µM) were evaluated against different cell lines, HGF (Fibroblasts; normal cell line), A549 (Non-Small Cell Lung Cancer cell line) and H69 (Small Cell Lung Cancer cell line). Compound 18 showed a considerable IC50 value of 90.69 against A549 and an excellent value of 32.22 and H69, respectively.

Five new species of the spider genus Toxopsoides Forster & Wilton, 1973 are described from Tasmanian surveys by DPIPWE and Bush Blitz (T. driesseni, sp. nov, T. tarkayna, sp. nov., T. wybalena, sp. nov., T. deux, sp. nov.) and one from an intensive IBISCA survey (T. ibisca, sp. nov.) in southern Queensland. It is suggested that Toxopsoides is transferred to Cycloctenidae with which it shares most characters.

In today’s business landscape, customer retention has become a critical factor for sustainable growth. Many companies continue to focus on acquisition, which leads to high costs and constant customer turnover. This article highlights the importance of retention, proposing a shift in focus toward loyalty as the key to maximizing customer lifetime value (LTV). Improving retention not only increases LTV but also reduces acquisition costs, enhances virality, and provides financial stability. This paper introduces a scientific approach that allows companies to identify the underlying causes of low retention through observation, hypothesis formulation, and controlled experimentation. Using tools such as data analysis and A/B testing, companies can iteratively optimize their retention strategy, adjusting interventions in real-time based on the results obtained. Continuous experimentation emerges as an indispensable tool for navigating market complexity, enabling organizations to learn and adapt quickly. This data-driven approach not only improves retention but also drives long-term growth by building strong relationships with customers. In an increasingly competitive environment, companies that prioritize retention and experimentation are better positioned to achieve resilient and profitable growth.

Several medical graduates, avoid surgical specialties especially those with complex and delicate anatomy due to their doubt in their visual spatial abilities. Many patients are deemed inoperable, particularly in the field of pediatric cardiology, due to the complexity of the anatomy. On a similar note, stratification of risk of cardiac interventions, and decision making, is a room of significant person-based and center-based bias. Two inter-related technologies, namely immersive virtual reality (VR) and artificial intelligence have made impossible things possible and can help to standardize decision making strategies. This review aimed at reviewing the main anatomical and lesion-based scopes of these advancements in the field of cardiac care, with a special focus on pediatric cardiology.

A system of two nonlinear difference equations under stochastic perturbations is considered. Nonlinearity of the exponential type in each equation of the system under consideration depends on all variables of the system. The stability in probability of a positive equilibrium of the system is studied via the general method of Lyapunov functionals construction and the method of linear matrix inequalities (LMIs). The obtained results are illustrated via examples and figures with numerical simulations of solutions of a considered system of stochastic difference equations. The proposed way of investigation can be applied to nonlinear systems of higher dimension and with other types of nonlinearity, for both difference equations and for delay differential equations.

As an important civil and military infrastructure, airport runway pavement is faced up with threats from cluster munitions, since it is vulnerable to projectile impact with internal explosion. Aiming at the damage assessment of island airport runway pavement under impact, this work dealt with discrete modeling of rigid projectile penetration into concrete pavement and calcareous sand subgrade multi-layer structure. First, Discrete Element Method (DEM) is introduced to model concrete and calcareous sand granular material features like cohesive fracture and strain hardening due to compression, with mesoscale constitutive laws governing the normal and shear interactions between adjacent particles. Second, sequent DEM simulations of uniaxial and triaxial compression were performed to calibrate the DEM parameters for pavement concrete as well as subgrade calcareous sand. Piror to multi-layer structure investigations, penetration into sole concrete or calcareous sand is validated in terms of projectile deceleration and depth of penetration (DOP) with relative error

Although large language models demonstrate impressive capabilities, they sometimes generate irrelevant or nonsensical text, or produce outputs that deviate from the provided source input—an occurrence commonly referred to as hallucination. To mitigate this issue, we introduce a novel decoding method that incorporates both factual and hallucination prompts(DFHP), utilizing a contrastive output distribution to highlight the disparity in output probabilities between model predictions influenced by factual prompts and those affected by hallucination prompts. Experiments on both multiple-choice and text generation tasks show that our approach significantly enhances the factual accuracy of large language models without requiring additional training.