Background: Historically, in the United States and globally, women have supported other women before, during, and after childbirth. Birth doulas are considered an important component to eliminating racial disparities in maternal morbidity and mortality. To address disparities in birth outcomes, Healthy Women Healthy Futures (HWHF) provides free birth and postpartum doula services to low-income women and communities of color in New York City. Methods: Secondary analysis of program data (n=364) collected between 2020 and 2021 was conducted. Univariate and multivariable analyses focused on: method of delivery, preterm birth, low-birthweight birth, breastfeeding, maternal-infant skin contact. The key exposure variable was total doula hours. Results: Clients who received prenatal doula support had low rates of preterm birth (8.8%) and low birthweight (7.1%), and high rates of vaginal delivery (69.1%), breastfeeding in the hospital (90.9%), and maternal-infant skin contact (78.2%). Multivariable analysis did not identify an association between number of doula hours and any of the five outcomes examined. Conclusion: While descriptive results point to positive birth outcomes, these effects did not persist in multivariable analyses. Data quality concerns from this intervention likely hindered the ability to detect a program impact, emphasizing the importance of funding to support data collection and management activities.

This study aims to evaluate the utilization and effectiveness of artificial intelligence (AI) applications in managing symptoms of anxiety and depression. The primary objectives are to identify current AI tools, analyze their practicality and efficacy, and assess their potential benefits and risks. A comprehensive literature review was conducted using databases such as ScienceDirect, Google Scholar, PubMed, and ResearchGate, focusing on publications from the last five years. The search utilized keywords including "artificial intelligence," "applications," "mental health," "anxiety," "LLMs" and "depression". Various AI tools, including chatbots, mobile applications, wearables, virtual reality settings, and large language models (LLMs), were examined and categorized based on their functions in mental health care. The findings indicate that AI applications, including LLMs, show significant promise in symptom management, offering accessible and personalized interventions that can complement traditional mental health treatments. Tools such as AI-driven chatbots, mobile apps, and LLMs have demonstrated efficacy in reducing symptoms of anxiety and depression, improving user engagement and mental health outcomes. LLMs, in particular, have shown potential in enhancing therapeutic chatbots, diagnostic tools, and personalized treatment plans by providing immediate support and resources, thus reducing the workload on mental health professionals. However, limitations include concerns over data privacy, the potential for over-reliance on technology, and the need for human oversight to ensure comprehensive care. Ethical considerations, such as data security and the balance between AI and human interaction, were also addressed. The study concludes that while AI, including LLMs, has the potential to significantly aid mental health care, it should be used as a complement to, rather than a replacement for, human therapists. Future research should focus on enhancing data security measures, integrating AI tools with traditional therapeutic methods, and exploring the long-term effects of AI interventions on mental health. Further investigation is also needed to evaluate the effectiveness of AI applications across diverse populations and settings.

Out-of-hospital cardiac arrest (OHCA) represents a significant global public health burden, characterized by low survival and few established diagnostic tools to guide intervention. OHCA presents with a wide variety of etiologies in a heterogeneous population, posing a clinical challenge to care teams. In this review, we describe evolving research focused on diagnostic approaches to OHCA following resuscitation, including electrocardiography, coronary angiography, computed tomography, ultrasonography, and serologic biomarker assessment. These diagnostic tools have been employed in post-resuscitative efforts for diagnosing ischemic and non-ischemic cardiac, respiratory, neurologic, vascular, traumatic, and metabolic causes of arrest.

Paper presents proposition of possible extension of The Standard Model Classification of Particles and Fields in way to include gravitation into it.

Background: To evaluate the effectiveness of Defocus Incorporated Multiple Segments (DIMS) in slowing myopia progression in pediatric patients as a function of age. Methods: This was a non-randomized experimenter-masked retrospective controlled observational study of European individuals aged 6 -16 years with progressive myopia but no ocular pathology. We retrospectively reviewed the charts of the participants allocated to receive DIMS spectacles (Hoya® MiyoSmart®) or single vision spectacle lenses (control group). Cycloplegic spherical equivalent (SE) and axial length (AL), were measured at baseline and at 36 month follow up. The results were stratified by age into four groups: patients that wore DIMS spectacles oldest or youngest than 10 years of age (respectively, group A, 20 patients mean age 13.6±2.2 and group C, 20 patients mean age 9.0±1.2) and age-matched control groups (group B, 18 patients mean age 13.2±2.5 and group D, 22 patients mean age 8.5±0.9). Results: At 36 months, SE and AL increase resulted significantly reduced in groups A and C, respectively compared to groups B and D (p

The awareness of the vulnerability of existing structures under both seismic and energy viewpoints highlight the need to develop integrated retrofit solutions combining the structural and thermal performances. In this perspective, the study explores the efficacy of the Resisto 5.9 Tube system, a seismic coat that improves the seismic behaviour of masonry and reinforced concrete (RC) structures, also enhancing their energy performances, thanks to the thermal coat integrated in the basic steel system. The research involves the application of a design procedure specifically developed for this retrofit system from the seismic perspective. Once all the system elements are designed, non-linear static analyses are performed with a Finite Element software comparing the building’s seismic performances before and after the application of Resisto 5.9 Tube. The results demonstrate a significant increase in seismic safety coefficient, proving that this intervention type can be useful to obtain the seismic upgrading of existing RC buildings.

Developing short-term forecasting model for global atmospheric temperature and wind in the near space is crucial for understanding atmospheric dynamics and supporting human activities in this region. While numerical models have been extensively developed, deep learning techniques have recently shown promise in improving atmospheric forecasting accuracy. In this study, convolutional long short-term memory (ConvLSTM) and convolutional gated recurrent unit (ConvGRU) neural networks were applied to build for short-term global-scale forecasting model of atmospheric temperature and wind in the `near space based on the MERRA-2 reanalysis dataset from 2010-2022. The model results showed that the ConvGRU model outperforms the ConvLSTM model in the short-term forecast results. The ConvGRU model achieved a root mean square error in the first three hours of approximately 1.8 K for temperature predictions, and errors of 4.2 m/s and 3.8 m/s for eastward and northward wind predictions, respectively.

Electrolyte disturbances are common in patients with traumatic brain injury (TBI), particularly affecting sodium, potassium, chloride and calcium levels. This study aims to provide insights into these disturbances within the first 24 hours post-injury. We conducted a cross-sectional analysis of 50 TBI patients, excluding those with conditions affecting electrolyte balance. Electrolyte levels were measured, and correlations with demographic data, trauma mechanisms, imaging findings, and Glasgow Coma Scale (GCS) scores were analyzed. Results indicated that chloride levels inversely correlated with GCS scores (ρ = -0.515; p = 0.002), suggesting that elevated chloride may indicate severe neurological impairment. Potassium levels were significantly associated with subdural hematoma (p = 0.032) and subarachnoid hemorrhage (p = 0.043), highlighting their potential as markers for severe brain injuries. No significant associations were found between sodium or calcium levels and the studied variables. These findings underscore the importance of early monitoring of chloride and potassium levels in TBI patients to improve management and outcomes. Future research should focus on larger, multi-center studies to validate these findings and develop comprehensive guidelines for managing electrolyte imbalances in TBI patients.

Xyleborus beetles, a diverse group of ambrosia beetles, present significant challenges to forestry and agriculture due to their damaging burrowing behavior and symbiotic relationships with fungi. This review synthesizes current knowledge on the biology, ecology, and management of Xyleborus. We explore the beetles' life cycle, reproductive strategies, habitat preferences, and feeding habits, emphasizing their ecological and economic impacts. Control and management strategies, including preventive measures, chemical and biological control, and integrated pest management (IPM), are critically evaluated. Recent advances in molecular genetics and behavioral studies offer insights into genetic diversity, population structure, and host selection mechanisms. Despite progress, managing Xyleborus effectively remains challenging. This review identifies future research needs and highlights innovative control methods, such as biopesticides and pheromone-based trapping systems.

Background/Objectives: Bacterial infections (BI) are a major cause of mortality in patients with alcohol-associated hepatitis (AH); however, only a few studies have investigated BI in AH in the last decade. Therefore, we aimed to assess the features and outcomes of BI in patients with AH. Methods: This observational descriptive study included patients with AH admitted to a tertiary academic hospital between 2016–2021. Clinical and complete microbiological data were recorded and complications, including acute-on-chronic liver failure (ACLF), and mortality over 90-days were compared between infected and non-infected patients. Results: Overall, 115 patients with AH were recruited and 75 had severe AH; among them, 66 started corticosteroid treatment. We identified 69 cases of BI in 44 patients; the incidence of BI at hospital discharge was 32.2%, which reached 38.2% at 90 days. The predominant infection site was the chest (35%). Among the identified bacteria (52.1%), half were gram-positive and half gram-negative. A low rate of multidrug-resistant bacteria (14%) was also noted. Infected patients during hospitalization (n=37) exhibited higher rates of hepatic decompensation and ACLF p=0.001) and lower survival (81.8% vs. 95.8%, p=0.015) than did non-infected patients (n=78). In-hospital infected patients (n=22) exhibited worse survival (72.7%) than did those infected upon admission (93.3%) or non-infected patients (94.9%) (p=0.009). Corticosteroid-treated patients displayed a nonsignificant increase in the total number of BI; however, without greater mortality. Conclusions: BI were common in our cohort of patients with AH. Patients with in-hospital infections commonly experienced serious complications, including high ACLF and death rates. Infections diagnosed upon admission were treated without affecting survival.

Background: The different disease forms of cutaneous leishmaniasis (CL) are influenced by parasite and host factors. Malnutrition impairs immunity. It has been found to disrupt immune protection by favoring the production of anti-inflammatory prostaglandins over pro-inflammatory cytokines. In Ethiopia, data on CL patients' nutritional status remains scarce. This study aims to assess clinical polymorphism and its association with the nutritional status of the patient. Methods: A retrospective study was conducted from June to July 2024, and patient’s data was analyzed from those treated for CL. Nutritional status was assessed through MUAC, Z-score, and BMI. Results: A total of 217 CL patient’s statuses were nutritionally defined and 22% of them were found malnourished. Most of the CL problems concentrate on age

The External Occipital Protuberance (EOP) is a notable anatomical landmark connected to neck musculature. With the rise of tech neck syndrome due to prolonged smartphone use, concerns have emerged regarding its influence on EOP morphology. This study compares EEOP characteristics in contemporary individuals (aged 18-30 years) from Abruzzo with ancient skulls from the Opi necropolis (VII-Vth century BC) Methods: Four null hypotheses were tested concerning EEOP prevalence and severity: (1) no gender differences, (2) no differences between modern and ancient populations, (3) no gender-based variations in severity, and (4) no temporal differences in severity. Statistical analyses were conducted to assess the significance of these hypotheses. Results: The study found a higher prevalence of EEOP in modern individuals compared to ancient populations, with no significant gender differences in prevalence. However, severity of EEOP showed significant variation by gender and historical period, with modern individuals exhibiting greater severity. Conclusions: The observed increase in EEOP prevalence and severity in modern populations suggests a potential influence of tech neck posture associated with increased screen time. These findings underscore the need for further research into the effects of contemporary lifestyle factors on cranial morphology.

This paper proposes an optimal path type classification scheme for the three-point Dubins problem. It allows to directly extract the shortest path type from a Dubins set, evaluating only the relative initial and final configurations with the via point position using a suitable partition of the Cartesian plane. Two alternative approaches are proposed to address the problem: an analytical approach and a heuristic one. The latter was revealed to be much faster from a computational point of view. The proposed classification logic makes the path planning for the three-point Dubins problem much more effective and suitable for real-time applications. Numerical examples are provided to show the efficiency of the proposed strategy.

A major reason for failure of the immune system to detect tumor antigens (TA) is the insufficient uptake, processing, and presentation of TA by antigen-presenting-cells (APC). Immunogenicity of public and private TA of the individual patient can be markedly increased by in situ targeting of tumor cells for uptake by APC, without the need to identify and characterize the TA. This is feasible by intra-tumoral administration of alpha-gal micelles comprised of glycolipids presenting the carbohydrate-antigen “alpha-gal epitope” (Galalpha1-3Gal beta1-4GlcNAc-R). Humans produce a natural antibody called “anti-Gal” (constituting ~1% of immunoglobulins) which binds alpha-gal epitopes. Tumor injected alpha-gal micelles spontaneously insert into tumor cell membranes, so that multiple alpha-gal epitopes present on tumor cells. Anti-Gal binding to these epitopes activates the complement system, resulting in killing of tumor cells, and recruitment of multiple APC (dendritic cells and macrophages) into treated tumors by chemotactic complement cleavage peptides C5a and C3a. In this process of converting the treated tumor into personalized TA vaccine, recruited APC internalize anti-Gal opsonized tumor cells and cell membranes, process the internalized TA and transport them to regional lymph-nodes. TA peptides presented on APC activate TA specific T and B cells to proliferate and destroy metastatic tumor cells presenting the TA. Studies in anti-Gal producing mice demonstrated induction of effective protection against distant metastases of the highly tumorigenic B16 melanoma following injection of natural and synthetic alpha-gal micelles into primary tumors. This treatment was further found to synergize with anti-PD1 antibody. Phase-1 clinical-trials indicated that this immunotherapy is safe and can induce infiltration of CD4+ and CD8+ T cells into untreated distant metastases. It is suggested that in addition to converting treated metastases into autologous TA vaccine, this treatment should be considered as neo-adjuvant therapy administering alpha-gal micelles into primary tumors immediately following their detection. Such immunotherapy will convert tumors into personalized anti-TA vaccine for the period prior to their resection.

This study focuses on calibrating the linear Drucker-Prager yield criterion for polypropylene under multiaxial loading conditions, using the Arcana machine to achieve a wide range of triaxiality states. The Drucker-Prager criterion has been adapted for polymers, composites, and metals due to its ability to account for the influence of hydrostatic pressure on yield stress. This study employs the Arcana machine, which allows for testing flat plate samples under various angles, thereby simulating different stress states from pure shear to biaxial tension. Additionally, uniaxial compression tests were conducted to extend the range of triaxiality. The material used in this study is Sabic 83MF10, a polypropylene polymer. Samples were prepared by injection molding and cut to specific dimensions. Tests were performed using a universal testing machine with the Arcana handle, and the results were analyzed to determine the yield strength, pressure, and triaxiality for each sample. The results showed a linear relationship between von Mises stress and hydrostatic pressure, with a friction angle (β) of 20.65° and material cohesion (d) of 27.81. The numerical simulations in Abaqus confirmed the validity of the Drucker-Prager model, accurately reflecting the moment of yielding for the tested samples.

Ming-style round-backed armchairs as a classic Chinese chair design are renowned for the blend of ergonomics, practicality, and elegance. Although the Chinese armchair furniture industry has made strides in sustainability, there is still a need for further improvements in material selection, manufacturing processes, and supply chain management to fully support the development of sustainable furniture. Laminated bamboo lumber as new sustainable materials are becoming a popular option for furniture designers in the era of "sustainable design". This research aims to investigate the feasibility and application of laminated bamboo lumber in the design of Chinese armchair furniture and proposes innovative ideas for optimizing the armchair's design. First, an empirical study was conducted to comprehensively understand the classification of Ming-style round-backed armchairs’ structure to develop a 3D model. Secondly, an experimental research method was then employed to explore the parameters of laminated bamboo lumber for future studies. Additionally, a validation experiment was conducted to compare real-world scenarios with simulations using finite element analysis in Ansys. Finally, finite element analysis was used to test the feasibility and application of laminated bamboo lumber in furniture design, focusing on the material’s mechanical properties. Results indicated that laminated bamboo lumber has excellent mechanical properties as furniture design materials, subsequently, using the optimized results, the use of 0.6319 kg of steel was successfully reduced by 23.68% to ensure the armchair’s stability. This provides a reference for the future compter-assist and standardized innovative design of Chinese armchair. By incorporating compter-assist design and lightweight optimization, it is possible to save materials and make more efficient use of resources, thereby contributing to sustainable development goals in the field of furniture design.

Honeypots are vital security tools that enable cybersecurity specialists to scrutinize the tactics employed by attackers. By doing so, they can get valuable insights into existing and upcoming internet dangers. Cyber-attacks are in a perpetual evolution, increasingly sophisticated and tailored to exploit specific vulnerabilities. Hence, it is imperative for both organizations and individuals not only to consider but also implement methods to safeguard themselves against cyberattacks and malware. This paper assesses a specific group of honeypot systems by considering detection range, emulation accuracy, data quality, dependability, scalability, performance, extensibility, installation options, setup difficulty, and maintenance requirements. Furthermore, it provides conclusions regarding the relative effectiveness of diverse honeypot systems in different situations. As a part of the research, it analyzes the latest progress and innovations in honeypot development, including enhancements in machine learning, heightened automation, integration with other security tools, cloud-based honeypots, and deception technology by using simulated assaults to showcase the logging and recording capabilities of these honeypots in capturing attack information. After carefully analyzing each honeypot, each has unique advantages, disadvantages, and special characteristics.

Trehalose, a disaccharide made of two D-glucose molecules, is found in various organisms like bacteria, yeast, fungi, insects, and plants. It serves as an energy and carbon source in plants and has signaling functions in yeast and plants, affecting metabolic pathways and growth regulation. It also plays a role in protecting proteins and cell membranes from damage caused by stress. This study aims to determine the best level of trehalose supplementation in layer diets between 34 to 49 weeks of age, due to limited literature on its impact on laying hen productivity. Experimental diets were based on nutritional recommendations and included six trehalose levels. The study was conducted over five periods of 21 days each, evaluating various parameters such as feed intake, egg production, egg quality, and bone characteristics. The results showed that trehalose supplementation influenced the performance of laying hens, as well as some aspects of egg and bone quality.

To investigate the effects of predation of the paddle crab Charybdis japonica on the culture and survival of scallops (Mizuhopecten yessoensis) during bottom culture, we investigated the behavioral characteristics of three sizes (small, medium, and large) of scallops in response to exposure to crabs. We also measured the activities of superoxide dismutase, catalase, arginine kinase, and octopine dehydrogenase in the gill, adductor muscle, and mantle of scallops before and after exposure to predation. Tissues that showed significant differences between control and test specimens were selected for deep sequencing of the transcriptome to identify and validate the key genes that were sensitive to predation. We found when M. yessoensis is stimulated by the presence of predators, its behavioral characteristics and related physiological and ecological indexes undergo significant changes. The results are relevant for developing specifications for M. yessoensis seedling casting during bottom culture.

Detrital zircons from two samples of metaterrigenous rocks from the Lykhmanivka Syncline, Middle Dnieper Domain of the Ukrainian Shield (Skelevate Formation of the Kryvyi Rih Group), have been dated by the LA-ICP-MS U-Pb method. Metasandstones from the northern part of the Syncline yield zircons belonging to four age groups: 3205 ± 20 Ma, 3089 ± 11 Ma, 2939 ± 8 Ma, and 2059 ± 4 Ma. In contrast, zircon from metasediments from the southern end of the Lykhmanivka Syncline fall within two age groups: 3174 ± 13 Ma, and 2038 ± 9 Ma. The source area was dominated by rocks of the Auly Group (3.27–3.18 Ga) and the Sura Complex (3.17–2.94 Ga). The proportion of zircons dated at 2.07–2.03 Ga, which reflects the timing of metamorphism, is 5%. The metamorphic nature of the Paleoproterozoic zircon allows us to define the maximum depositional age of the metaterrigenous rocks of the Lykhmanivka Syncline at ca. 2.9 Ga, which is in good agreement with the earlier results from the metaterrigenous rocks of the Kryvyi Rih – Kremenchuk basin. Our data also indicate the local nature of sedimentation and the absence of significant transport and mixing of detrital material within the basin.

The combination of micro- or nanofluidics and strong light–matter coupling has gained much interest in the past decade, which has led to the development of advanced systems and devices with numerous potential applications in different fields, such as chemistry, biosensing, and material science. Strong light–matter coupling is achieved by placing a dipole (e.g. an atom or a molecule) into a confined electromagnetic field, with molecular transitions being in resonance with the field and the coupling strength exceeding the average dissipation rate. Despite intense research and encouraging results in this field, some challenges still need to be overcome, related to the fabrication of nano- and microscale optical cavities, stability, scaling up and production, sensitivity, signal-to-noise ratio, and real-time control and monitoring. The goal of this paper is to summarize recent developments of micro- and nanofluidic systems employing strong light–matter coupling. An overview of various methods and techniques used to achieve strong light–matter coupling in micro- or nanofluidic systems is presented, preceded by a brief outline of the fundamentals of strong light–matter coupling and optofluidics operating in the strong coupling regime. The potential applications of these integrated systems in sensing, optofluidics, and quantum technologies are explored. The challenges and prospects in this rapidly developing field are discussed.

Fungi inhabiting deep subseafloor sediments have been shown to possess anaerobic methane (CH₄) production capabilities under atmospheric conditions. However, their ability to produce CH₄ under in situ conditions with high hydrostatic pressure (HHP) remains unclear. Here, Schizophyllum commune 20R-7-F01, isolated from ~ 2 km below the seafloor, was cultured in Seawater Medium (SM) in culture bottles fitted with sterile syringes for pressure equilibration. Subsequently, these culture bottles were transferred into 1-liter stainless steel pressure vessels at 30 °C for 5 days to simulate in situ HHP and anaerobic environments. Our comprehensive analysis of bioactivity, biomass, transcriptomics revealed that S. commune not only survived but significantly enhanced CH₄ production, reaching approximately 2.5 times higher levels under 35 MPa HHP compared to 0.1 MPa standard atmospheric pressure. Pathways associated with carbohydrate metabolism, methylation, hydrolase activity, cysteine and methionine metabolism, and oxidoreductase activity were notably activated under HHP. Specifically, key genes involved in fungal anaerobic CH₄ synthesis, including methyltransferase mct1 and dehalogenase dh3, were upregulated 7.9- and 12.5-fold, respectively, under HHP. Enhanced CH₄ production under HHP was primarily attributed to oxidative stress induced by pressure, supported by intracellular Reactive Oxygen Species (ROS) levels and comparative treatments with cadmium chloride and hydrogen peroxide. These findings suggest that fungi persisting in deep-sea sediments over millions of years have the potential to significantly contribute to global CH₄ flux.

Electronic waste generation has been following a continuously rising trend. With electronics containing a myriad of materials some of which are hazardous, toxic, extremely rare or precious combined with more stringent legislative laws which encourage the reuse and optimised recycling of the materials included in e-waste, the need for a holistic approach is inevitable. Such an approach should not only identify the materials found in the various types of e-waste and their respective quantities but also needs to highlight the possible handling techniques and their respective impacts and associated hazards whether to the environment or human health. Performing such a task manually would be exasperating and costly while requiring extensive resources which might not be met with a justifiable economic gain; thus, the use of the advancement in computational sustainability to draw a complete picture and aid in an informed decision-making process is crucial. The e-waste ontology developed in this paper is one way of addressing the problem since it covers the treatment domain, the hazard and the materials contained within the different types of e-waste. The ontology developed can be used directly from the protégé software or by embedding it into a developed Decision Support System.

Pulmonary arterial hypertension (PAH) is a complex and devastating disease that the underlying cellular and molecular mechanisms are largely remains unknown. This study aimed to elucidate the key hub genes and pathways in PAH by bioinformatics analysis. In the current study, we performed WGCNA analysis to systematically identify the hub genes for PAH using transcriptome microarray data. From the Gene Expression Omnibus (GEO) database, one microarray dataset (GSE113439) was downloaded for this study. There were 26 samples in this data set, including 15 PHA samples and 11 normal controls. Based on weighted correlation network analysis, 11 modules were identified and the MEgreenyellow module showed a significantly positive correlation with PAH (r = 0.93, P = 1e−06). The genes in greenyellow module were mainly significantly enriched in mitophagy related pathways by KEGG analyses. Combined with the protein–protein interaction (PPI) and co-expression networks, ten hub genes were identified as candidate biomarkers for PAH in the greenyellow module, including CTNNB1, NIPBL, ROCK2, ROCK1, SCAF11, JAK1, BIRC6, KIF5B, PPP1R12A and XRN1. These hub genes might be potential targets for clinical therapy against PAH. The molecular mechanisms involved in these genes that affected the prognosis of PAH should be further validated through biological and basic studies.

An optical fiber scale sensor based on the detection principle of surface plasmon resonance (SPR) was developed for the rapid, high-sensitivity real-time evaluation of scale precipitation from geothermal fluids. The optical fiber SPR scale sensor was fabricated by depositing a gold thin film on the surface of an optical fiber with an exposed core. The optimal gold film thickness of the sensor was determined to be 30 nm, which achieved a refractive index sensitivity of 2140 nm per refractive index unit. A field test was conducted using geothermal brine from the Obama Binary Geothermal Power Plant in Unzen, Nagasaki Prefecture. A conventional optical fiber scale sensor and the SPR sensor were simultaneously assessed using raw and pH-adjusted brines. For the SPR sensor, a peak shift of 0.27 nm/min was observed at a response time of 1 min, whereas no change in transmittance was observed for the conventional sensor until 180 min. After the experiments, scanning electron microscopy–energy-dispersive spectroscopy analysis was conducted on the sensors, and findings showed that the deposition of Mg–SiO2 scale did not significantly differ between the two sensors. The developed SPR sensor achieved faster scale precipitation detection (tens of minutes to hours) than the conventional sensor.

Background: Anxiety disorders can be both an independent risk factor of many somatic conditions and the cause of complications of various organic disorders leading to poor prognosis. Objectives: The purpose of this study is to compare the heart rate variability (HRV) recorded both during the day and at night in patients with anxiety disorders and healthy individuals. Methods: The study was conducted on fifty consecutive outpatients with anxiety disorders who participated in intensive group psychotherapy. The diagnosis was made according to DSM-IV-TR criteria using the PSE-10 questionnaire. Out of 50 patients under study, 17 were diagnosed with panic disorder (PD) and 21 with generalized anxiety disorder (GAD). The control group consisted of 40 healthy people. The resulting three groups were compared in terms of circadian HRV using the Oxford Medilog Suprima Holter System. Results: The HRV analysis showed the nocturnal falls in the time and frequency parameters related to parasympathetic activity (rMSSD, pNN50, HF). The most unfavourable alterations were observed in the PD group, which comprised the disappearance of day vs. night amplitude of the majority of HRV parameters. Hence, the PD group was particularly susceptible to the arrhythmic events. It was noticeable that nocturnal vagotonia in the PD group was significantly lower as compared with the GAD and control group. Conclusions: The innovative aspect of the present study was to find a distinct profile of HRV with regard to the types of anxiety disorders because of the existing considerable differences between the nature of PD and GAD.

The Ali-Cesaro Stolz theorem, introduced in this paper, extends the classical Cesaro-Stolz theorem by addressing cases where the latter does not yield results or provides a "Does Not Existe (DNE) form. This novel theorem leverages the properties of limits and Z-transforms, offering a robust framework for analyzing sequences and series. The theorem is particularly effective in scenarios where traditional approaches fail, providing new insights and tools for mathematical analysis. This paper presents a detailed formulation of the Ali-Cesaro Stolz theorem, including proofs, applications, and a discussion on its implications and advantages over existing methods.

Viral hepatitis caused by hepatitis B virus (HBV) and hepatitis C virus (HCV) poses a significant global health challenge, with an increasing number of deaths and a substantial burden on healthcare systems. This literature review explores the impact of socioeconomic determinants of health (SDoH) on the prevalence and outcomes of HBV and HCV infections among male prison inmates in Nigeria. By examining factors such as risky behaviors, overcrowding, inadequate healthcare access, and food insecurity, this review highlights how these determinants contribute to the high rates of hepatitis infections in Nigerian prisons. The review underscores the urgent need for a multifaceted approach involving policy changes, improved healthcare access, and enhanced preventive measures to address these health disparities. The findings aim to inform public health strategies and interventions to reduce the transmission and impact of viral hepatitis in prison settings, aligning with global health goals and promoting health equity.

Recommender systems in education are becoming more widespread, typically focusing on recommending courses or study materials. This study proposes a machine learning approach to recommend a university degree based on high school and university standardised test results, incorporating students' socioeconomic information as input variables. The objective is to develop a tool for students’ decision-making, supporting the sustainable development goal of Quality Education by providing a data schema to maximise the likelihood of a successful match between the student's profile and the academic program. With its focus on equity in education, this study provides a data-driven approach to assist students in selecting suitable university degrees, aiming to improve educational outcomes and inspire a more equitable education system.

The research aims to present an innovative methodology to execute the Heritage conservation processes in a collaborative and interdisciplinary BIM project, with an effective management of the deterioration suffered over time, emphasizing the structures and coatings. The research begins with the architectural survey using scanning techniques (TLS) and terrestrial photogrammetry (SfM) and taking as a study the Duomo of Molfetta (Italy), a unique Romanesque architecture of Puglia (Italy). The methodological process is mainly aided by the precise semantic segmentation of global point clouds, a semi-automatic process assisted by classification algorithms implemented in the post-processing software, and which has allowed the classification of the unstructured information provided by the remote sensing equipment when identifying the architectural-structural systems of a building with high historical values. Subsequently, it has been possible to develop an efficient Scan-to-HBIM workflow, where the Heritage-BIM (HBIM) project has fulfilled the function of a database by incorporating and organizing all the information (graphic and non-graphic) to optimize the tasks of auscultation, identification, classification, quantification and, in turn, facilitating the parametric modeling of unique structures and architectural elements. The results have shown great effectiveness in the processes of characterization of architectural and artistic heritage, focusing on the deformations and deterioration of the masonry in columns, and making multidisciplinary conservation work in an HBIM project more flexible. But there are still some difficulties for the automatic interpretation of 3D point cloud data, related to specific systems of the historical architecture. In conclusion, human action and interpretation continues to be a fundamental pillar to achieve precise results in a heritage environment.

The study of localized surface plasmons (LSPs) in nanoscale structures is an essential step towards identifying optimal plasmonic modes that can facilitate robust optomechanical coupling and deepen our understanding of light-matter interactions at the nanoscale. This paper investigates numerically, using the finite element method, LSPs modes in a design comprising two coupled nano-ridges deposited on a gold layer, with an interposing polymer spacer layer. Such a structure, usually referred to as particles-on-mirror, shows exquisite optical properties at the nanoscale. We first examine the LSPs modes of a single nano-ridge through the analysis of its scattering cross-section in the visible and infrared range. To enhance the plasmonic response, a thin polymer layer is placed at the middle of the ridge, which introduces additional LSPs modes confined within the former. Then, we extend the analysis to the dimer configuration, which exhibits more complex and enhanced plasmonic behavior compared to a single nano-ridge. In particular, the dimer configuration yields LSPs resonances with a quality factor enhancement of approximately threefold relative to single nano-ridge. Furthermore, the presence of the polymer layer within the ridges significantly improves plasmon field localization and quality factor. These findings underscore the potential of nano-ridge-based structures in advancing optomechanical coupling and plasmon-phonon interaction studies, offering valuable insights for the development of high-performance acousto-plasmonic devices. In particular, the proposed device could help significantly improve the design of nano-acousto-optic modulators operating in the visible or in the near infrared, that require enhanced light-photon coupling rate.

Fagao is one of China's traditional gluten free staple foods made by rice or corn flour. Corn Fagao prepared by co-fermentation with sourdough and yeast exhibits better quality and less staling compared to traditional yeast-fermented Fagao. The physicochemical properties of corn Fagao batter during the sourdough-yeast co-fermentation were investigated. The results showed that compared with yeast fermentation, the gas production and viscosity of the batter increased by co-fermentation. The co-fermented batter shows higher hydrolysis of starch and less amylose content. The integrity of starch granules in co-fermented batter was damaged more seriously, the crystallinity and short-range ordered structure were less than yeast fermented batter, even though the crystal structure type of starch did not change obviously. The peak viscosity, minimum viscosity, final viscosity, decay value and recovery value of corn batter are reduced by co-fermentation, which can improve the thermal stability of the batter and slow down the aging. Co-fermentation also results in a more pronounced reduction in protein subunit contents than yeast fermentation. The changes in the physicochemical properties of corn Fagao batter help explain the quality improvement of corn Fagao made from co-fermentation method, and may provide theoretical references for co-fermentation with sourdough and yeast to other gluten free foods.

Image generation optimization is an important research direction in the field of deep learning, which aims to improve the performance of image generation models and the quality of generated images. In recent years, researchers have made significant progress in image generation optimization with the development of deep generative models such as generative adversarial networks (GANs) and variational autoencoders (VAEs). These models are able to generate high-quality, realistic images by learning the distribution of image data. In this study, a deep learning-based image generation optimization model was adopted, which combined the advantages of GAN and VAE. The model architecture consists of a generator and a discriminator, where the generator is responsible for generating the image and the discriminator is used to judge the authenticity of the image. In addition, the model also introduces attention mechanism and self-supervised learning strategy to further improve the quality and diversity of generated images. In the training process, a large-scale image dataset is used, and a variety of optimization algorithms are used to improve the stability and efficiency of the model. By evaluating various indicators of the generative model, including image quality, generation speed and model convergence, it was found that the introduced attention mechanism and self-supervised learning strategy significantly improved the performance of the model.

Groundnut is an oil seed cash crop, that can be consumed directly by humans and animals. It is also used as an intelligence in the industrial production of butter and other products. However, Groundnut seeds can become infected with fungi, viruses, pests, physical damage, and high heat, which can negatively impact crop yield, quality, and economic value, and pose health hazards. To address these challenges, computer vision technology detects and classifies defects. This study introduced an ensemble deep learning defected classification model that combines VGG16 and InceptionV3 using seed images. To enhance model performance, collected images are preprocessed using novel techniques tailored to different image types. Preprocessing techniques are chosen based on image-quality evaluation metrics. Watershed segmentation is applied followed by detecting the region of interest in the image using YOLOv3. The image dataset is augmented and balanced using a Generative Adversarial Network (GAN). The model development involves a combination of classical and deep-based features, comparing features extracted with (HOG and GLCM) to those extracted with InceptionV3 and VGG16. The ensemble model achieves an accuracy of 96.25% with a split ratio of 10% for testing, 10% for validation, and 80% for training set. This research benefits farmers looking to improve yield, consumers of groundnut products, and researchers studying seed defects. The work provides valid insights for future researchers regarding dataset creation, augmentation, methods, and feature selection for modeling. However, the model experienced misclassifications due to the similar appearance of sample images in different classes. Future researchers should address these challenges and consider factors such as oil content and defect grading.

The optimal functionality and dependability of mechanical systems are important for the sustained productivity and operational reliability of industrial machinery which has direct impact on it’s longevity and profitability. Therefore, failure of a mechanical system or any of it component would be detrimental to production continuity and availability. Consequently,this study proposes a robust diagnostic framework for analyzing the blade conditions of shot blast industrial machinery. The framework involves analyzing the spectral characteristics of the vibration signals generated by Industrial Shot Blast. Additionally, a peak detection algorithms is introduced to identify and extract the unique features present in the peak magnitudes of each signal spectrum. A feature importance algorithm is then deployed as the feature selection tool, and these selected features are fed into 10 machine learning classifier, with Extreme gradient boosting (XGB) as the core classifier. Results show that the XGB classifier achieved the best accuracy of 98.05%, with a cost-efficient computational cost of 0.83 seconds. Other global assessment metrics were also implemented in the study to further validate the model.

Background: Eosinophilic granulomatosis with polyangiitis (EGPA) is an extremely rare type of vasculitis characterized by inflammation within small blood vessels or tissues that may cause damage to the lungs, heart, kidneys, and other organs. Here, we present a rare case of EGPA with cardiac involvement that presented with acute heart failure. Clinical findings: A 44-year-old woman with a history of bronchial asthma and sinusitis pre-sented with fever, shortness of breath, fatigue, unintentional weight loss, and polyarthritis. Physical examination revealed a fine basal crepitation and mononeuritis multiplex. Diagnosis: The peripheral film revealed dimorphic features, an elevated eosinophil count, low hemoglobin (Hb), and abnormally high lactate dehydrogenase levels. The cardiac enzyme levels were elevated upon admission. Cardiac magnetic resonance imaging (CMR) revealed global hypokinesia and features suggestive of myocarditis. Echocardiography showed a low ejection fraction of 25%. Thus, the patient diagnosed with EPGA and myocarditis presented with acute heart failure. Interventions: The patient was administered high-dose corticosteroids (intravenous bolus methylprednisolone 500 mg for three days, followed by 1 mg/kg of prednisolone) and cyclo-phosphamide 750 mg intravenously. Outcome: After one months, the patient showed a marked improvement in clinical and labora-tory parameters. The ejection fraction improved to 30-40%, the eosinophil count returned to normal, and the hemolytic anemia resolved. The patient was sent home with mycophenolate mofetil 1 g twice a day as maintenance therapy. Conclusion: Patients with EGPA have a higher morbidity and mortality rate when they have cardiac in-volvement. The pathophysiological mechanism of cardiac involvement in EGPA warrants con-sideration of immunosuppressive therapy in addition to standard heart failure treatment.

The high transmissibility, rapid evolution, and immune escape of SARS-CoV-2 variants can influence the course of infection and, in turn, morbidity and mortality in COVID-19, posing a challenge in controlling transmission rates and contributing to the emergence and spread of new variants. The factors that shape viral genetic variation are consequently essential for understanding the evolution and transmission of SARS-CoV-2, especially in vaccinated individuals where immune response plays a role in the progression and spread of this disease. This study assessed. In this context, we evaluated the impact of immunity induced by the CoronaVac vaccine (Butantan/Sinovac) on intra-host genetic diversity, analyzing 118 whole-genome sequences of SARS-CoV-2 from unvaccinated and vaccinated patients infected with the Gamma variant. Vaccination with CoronaVac favors negative selection at the intra-host level in different genomic regions and prevent greater genetic diversity of SARS-CoV-2, which may help reduce the emergence of new mutations, reinforcing the importance of vaccination in reducing virus transmission.

Spatial auto-regressive (SAR) models are widely used in geosciences for spatial analyses; their main feature is the presence of weight (W) matrices, which define the neighboring relationships between the spatial units. The statistical properties of parameter and forecast estimates strongly depend on the structure of such matrices. The least squares (LS) method is the most flexible and can estimate systems of large dimensions; however, it is not consistent in the presence of multilateral (sparse) matrices. Instead, the unilateral specification of SAR models provides triangular weight matrices which allow good statistical properties to LS and enable the implementation of sequential prediction functions. In this paper we show the better performance in out-of-sample forecasting of unilateral SAR and LS with respect to multilateral and maximum likelihood (ML) methods. This conclusion is supported by extensive numerical simulations and applications to real geological data, both on regular lattice and irregular polygonal form.

Comprehending the replication kinetics of SARS-CoV-2 variants helps explain why certain var-iants spread more easily and are more contagious, and pose significant health menaces to the global populations. The replication kinetics of Malaysian isolates of the Alpha, Beta, Delta, and Omicron variants were studied in the Vero E6 cell line. Their replication kinetics were deter-mined using the plaque assay, quantitative real-time PCR (qRT-PCR), and viral growth curve. The Beta variant exhibited the highest replication rate at 24 hours post-infection (h.p.i), as evi-denced by the highest viral titers and lowest viral RNA multiplication threshold. The plaque phenotypes also varied among the variants, in which the Beta and Omicron variants formed the largest and smallest plaques, respectively. All studied variants showed strong cytopathic effects after 48 h.p.i. The whole-genome sequencing highlighted cell-culture adaptation, where the Beta, Delta and Omicron variants acquired mutations at the multibasic cleavage site after three cycles of passaging. The findings suggest a strong link between the replication rates and their respec-tive transmissibility and pathogenicity. This is essential in predicting the impacts of the upcom-ing variants on the local and global populations and is useful in designing preventive measures to curb the virus outbreaks.

In recent years, the High Dynamic Range (HDR) image has gained widespread popularity 1 across various domains such as security, multimedia, and biomedical fields, owing to its ability 2 to deliver an authentic visual experience. However, the extensive dynamic range and rich detail 3 in HDR images present challenges in assessing their quality. Therefore, current efforts involve 4 constructing subjective databases and proposing objective quality assessment metrics to achieve 5 efficient HDR Image Quality Assessment (IQA). Recognizing the absence of a systematic overview 6 of these approaches, this paper provides a comprehensive survey of existing HDR IQA methods. 7 Furthermore, this paper aims to serve as a valuable resource for researchers by discussing the 8 limitations of current methodologies and potential research directions in the future.

The diagnosis of migraine is based on clear criteria outlined in the International Classification of Headache Disorders version 3 (ICHD-3). Notably, the criteria in ICHD-3 omit the location of migraine. There are increasing reports of migraine in the facial region.(1-3) Facial presentations of migraine are not easy to diagnose as they appear in the lower 2/3rd of the face, often in the maxillary sinus region, around the ear, the upper/lower jaws and teeth.(4) Moreover, the symptomatology of these facial representations of these headaches often resembles sinusitis and dental pathology. We will review these presentations, their diagnosis and possible pathophysiology.

Traditional thermal insulation panels consume large amounts of energy during production and emits pollutants into the environment. To mitigate this impact, the development of bio-based materials is an attractive alternative. In this context, the characteristics of the Eucalyptus fiber bark (EGFB) make it a candidate for insulation applications. However, more knowledge about the manufacturing process and in-service performance is needed. The present study characterized the properties that determinate the in-service behaviour of the EGFB insulation panel. The assessment involved two different manufacturing process. The results indicated that the hot plates and the saturated steam injection manufacturing system can produce panels with similar theoretical and bulk density. The thermal conductivity fluctuated between 0.064 and 0.077 W/m.K, which indicated good insulation. Furthermore, the values obtained for thermal diffusivity and water vapor transmission properties are comparable with other commercially available panels. To guarantee a good in-service performance, the panels need to be treated with flame retardant and antifungal additive. The good performance of the panel is relevant because bio-based Eucalyptus bark panels generate less CO2 eq and require less energy consumption compared to traditional alternatives, contributing to the sustainability of the forestry and the construction industry.

This paper presents a study on developing of a new exoskeleton for ankle joint rehabilitation with three degrees of freedom (3 DOFs). The primary attention is paid to the process of designing and modelling the device aimed at restoring the lost functions of joint mobility. The authors carried out a complex analysis of the functional requirements of the exoskeleton based on the research of potential user’s needs, which allowed them to develop a conceptual model of the proposed de-vice. In this study, a prototype of the exoskeleton is designed using modern additive technolo-gies. A prototype of the proposed device underwent virtual testing in conditions maximally close to the real one, which confirmed its effectiveness and comfort of use. The main results of the work indicate the promising potential of the proposed solution for application in rehabilitation practice, especially for patients with ankle joint injuries and diseases.

Accurate fire severity mapping is essential for understanding the impacts of wildfires on vegetation dynamics in arid savannas. The frequent wildfires in these biomes often cause topkill, where vegetation experiences above-ground combustion, but the below-ground root structures survive, allowing for subsequent regrowth post-burn. Investigating post-fire regrowth is crucial for maintaining ecological balance, elucidating fire regimes, and enhancing the knowledge base of land managers regarding vegetation response. This study examined the relationship between bush fire severity and post-burn coppicing/regeneration events of woody vegetation in the Kalahari Desert of Botswana. Utilizing UAV-derived RGB imagery combined with a Random Forest (RF) classification algorithm, we aimed to enhance the precision of burn severity mapping at a fine spatial resolution. Our research focused on a 1 km2 plot within the Modisa Wildlife Reserve, extensively burnt by the Kgalagadi Transfrontier Fire of 2021. The UAV imagery, captured at various intervals post-burn, provided detailed orthomosaics and canopy height models, facilitating precise land cover classification and burn severity assessment. The RF model achieved an overall accuracy of 79.5% and effectively identified key burn severity indicators, including green vegetation, charred grass, and ash deposits. Our analysis revealed a >50% probability of woody vegetation regrowth in high severity burn areas six months post-burn, highlighting the resilience of these ecosystems. This study demonstrates the efficacy of low-cost UAV photogrammetry for fine scale burn severity assessment and provides valuable insights into post-fire vegetation recovery, thereby aiding land management and conservation efforts in savannas.

Current agriculture intensifies crop cultivation to meet food demand, leading to unsustainable use of chemical fertilizers. This study investigates a few physiological and agronomic responses of common wheat following the inoculation with plant growth-promoting bacteria to reduce nitrogen inputs. A field trial was conducted in 2022-23, in Legnago (Verona, Italy) on Triticum aestivum var. LG-Auriga comparing full (180 kg ha-1) and reduced (130 kg ha-1) N doses, both with and without foliar application at end tillering of the N-fixing bacterium Methylobacterium symbioticum. Biofertilization did not improve shoot growth, while it seldom increased root length density in the arable layer. It delayed leaf senescence, prolonged photosynthetic activity, amplified stomatal conductance and PSII efficiency under reduced N dose. Appreciable ACC-deaminase activity of such bacterium disclosed augmented nitrogen retrieval and reduced ethylene production, explaining ameliorated stay-green. Yield and testing weight were unaffected by biofertilization, while both glutenin-to-gliadin and HMW-to-LMW ratios increased together with dough tenacity. It is concluded that Methylobacterium symbioticum can amplify nitrogen metabolism at reduced nitrogen dose, offering a viable approach to reduce chemical fertilization under suboptimal growing conditions for achieving a more sustainable agriculture. Further research over multiple growing seasons and soil types is necessary to corroborate these preliminary observations.

One of the main objectives of developing new anti-cancer vaccine strategies is to effectively induce CD8+ T cell-mediated anti-tumor immunity. Live recombinant vectors, notably Listeria mono-cytogenes, have been shown to elicit a robust in vivo CD8+ T cell response in preclinical settings. Significantly, it has been demonstrated that Listeria induces inflammatory/immunogenic cell death mechanisms such as pyroptosis and necroptosis in immune cells that favorably control immunological responses. Therefore, we postulated that the host's response to Listeria-based vec-tors and the subsequent induction of CD8+ T cell-mediated immunity would be compromised by the lack of regulatory or effector molecules involved in pyroptosis or necroptosis. To test our hy-pothesis, we used recombinant L. monocytogenes carrying the ovalbumin gene (LM.OVA) to vac-cinate wild-type (WT), caspase-1/11-/-, gsdmd-/-, ripk3-/-, and mlkl-/- C57Bl/6 mice. We performed an in vivo cytotoxicity assay to assess the efficacy of OVA-specific CD8+ T lymphocytes in eliminat-ing target cells in wild-type and genetically deficient backgrounds. Furthermore, we evaluated the specific anti-tumor immune response in mice inoculated with B16F0 and B16F0.OVA mela-noma cell lines. Our findings demonstrated that while caspase-1/11 and GSDMD deficiencies in-terfere with the rapid control LM.OVA infection, of the KO seems to contribute to the early acti-vation of OVA-specific CTL responses. In contrast, individual deficiency of each one of these pro-teins negatively impact the generation of long-lasting effector CD8+ T cells.

Background: Health expenditure in Japan is rising due to an ageing society while simultaneously pressure is mounting to increase spending in other areas such as defense, all in the context of a stagnating economy. Easing pressures on the health care sector through smoking-related cost reductions could thus be a cornerstone to mitigate the looming fiscal threat. Public health policy has encouraged cessation, but this approach has seen limited success. Focusing on cessation alone therefore may not be a sustainable policy strategy and other, new solutions need to be found to reduce smoking-related costs. Methods: Using a status-quo simulation based on hospital resources data derived from the Japanese Ministry of Health, Labour and Welfare, we examine the impact of heated tobacco products (HTPs) on the prevalence of four smoking attributable diseases (chronic obstructive pulmonary disease (COPD), ischemic heart disease (IHD), stroke and lung cancer) and related direct health care costs. Base case scenario assumes a switching rate from combustible smokers to HTPs of 50%. A risk reduction rate of 70% was applied. A sensitivity analysis was performed to determine the impact of parameter changes on output. Results: Our results indicate that 50% of smokers switching to use HTPs instead of combustible tobacco products could reduce the number of patients of the four smoking attributable diseases considered by 12 million cases equivalent to 454 billion JPY in savings. Prefectures located in the north and south of Japan would benefit most. Conclusion: Considering the heterogeneous prevalence rates across population groups and prefectures, a one-size-fits-all, centralized approach to tobacco control is not effective. Health authorities should strategically use multiple interventions to address smoking related health risks and costs. Switching to HTPs should be encouraged in parallel to smoking cessation, and educational efforts should aim to increase the awareness on health risks, especially among younger people.

Background/Objectives: Endocrine disruptors are ubiquitous agents in the environment and are present in everyday consumer products. These agents can interfere with the endocrine system, and subsequently the reproductive system, especially in pregnancy. Increasing research has been conducted to discover and describe the health effects of these agents on humans, including pregnant women, their fetuses, and the placenta. This review discusses prenatal exposure to various endocrine disruptors focusing on Bisphenols, Phthalates, Organophosphates, and Perfluoroalkyl substances, and their effects on pregnancy and fetal development. Methods: We reviewed the literature via PubMed and EBSCO databases and included the most relevant studies. Results: Our findings reveal that several negative health outcomes were linked to endocrine disruptors. However, despite the seriousness of this topic and the abundance of research on these agents, it remains challenging to draw strong conclusions about their effects from the available studies. This does not allow for strong, universal guidelines and might result in poor patient counseling and heterogeneous approaches to regulating endocrine disruptors. Conclusion: The urgency of the matter calls for urgent efforts, as more studies are needed in this realm, to protect pregnant patients ultimately and in the long term, society.

Objectives: The tau protein is essential for stabilizing microtubules. Changes in its phosphorylation are identified in many neurodegenerative diseases, such as frontotemporal dementia and Alzheimer's disease. The hyperphosphorylation of the tau protein is linked to various factors, including stress, which has a substantial impact on depressive illness. The present study aimed to systematically review studies that describe the association between tau protein and depression.Design: The present study used the PRISMA statement 2020 as the inclusion criterion for articles describing tau protein in individuals with depression. The exclusion criterion was the lack of comparison of tau protein levels with individuals without depression.Results: A total of 138 papers were identified, of which 21 were ultimately included. One out of every three articles included demonstrated the statistical significance of the tau protein values between the depression group and controls. Only one had an adequate sample but demonstrated results without any major significance.Conclusions: The association between tau protein and depression remains unclear. Studies with adequate sampling are necessary to answer this question.

Colorectal cancer (CRC) ranks as the third most prevalent cancer globally, with 25% of patients presenting with metastases; of these, 8% have synchronous liver and peritoneal metastases. Although the concurrent presence of liver and peritoneal metastases was previously considered an absolute contraindication, the feasibility of combined surgery is now being re-evaluated. This study assesses 41 patients who underwent liver surgery for CRC metastases at our center between October 2021 and February 2024. Among these patients, 7 underwent concomitant cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC) due to the presence of synchronous liver and peritoneal metastases. We employed simple linear regression to identify parameters that influenced the development of postoperative complications, classified by the Clavien-Dindo (CD) system. The statistical analysis showed only the operative time, the CRS+HIPEC procedure and the length of hospital stay as significative variables on CD outcome, while the different types of liver surgery were not significant. This study suggests that combining liver surgery with CRS+HIPEC may be beneficial for selected patients, potentially improving overall survival without a significant increase in postoperative complications. A multidisciplinary approach is essential to achieve a survival advantage without elevating morbidity rates.

Objective: To report time-loss match injuries in Portugal’s “Divisão de Honra” (Portuguese First Tier) 2022/23 season focusing on injury incidence, injury burden, anatomical region and type of injury. Methods: A cohort prospective observational study was conducted. Data was collected through an online form sent for every team medical department categorizing player position, injury type, location and severity. Injury incidence and burden were calculated per 1000-player-match-hours. Results: The overall injury incidence was 54.4 injuries per 1000 player-match-hours (CI95% 30.3-96.2). Forwards had a higher incidence comparing to backs. Lower limbs were the most affected location (52% of the injuries). Sprain/ligaments injuries were the most common type of injury followed by muscle injuries. Discussion: The injury incidence was higher than what is reported in amateur competitions and lower than professional ones. Injury severity was similar to other studies. Our study suggests a lower injury burden compared to other semi-professional and elite leagues. Further research with broader participation and training injury data is needed.

This study introduces a new approach to modeling galaxy rotation curves by integrating concepts from Perelman’s functional with modifications to General Relativity. While initial numerical simulations indicate that our P-E Integration model may offer a closer fit to observed data than existing theories, we recognize the preliminary nature of these findings [14]. The results, though promising, should be interpreted cautiously. Further validation across different galactic systems and refinement of the model are necessary to confirm its broader applicability [15]. This work aims to contribute to the understanding of galactic dynamics, with the hope of opening new avenues for future research.

BACKGROUND: Scoliosis is a widespread musculoskeletal disorder of bending and twisting of spine. In this medical ailment, spine curves to the side and even in severe cases it can twist and can take several bends. For the diagnosis and treatment of scoliotic patients, the Cobb’s angle is a critical marker of the body’s curvature. OBJECTIVE: There are many researches that have been conducted to automate the manual measurement of the angle and every investigation has their own limita- tions. METHODS: This paper presents a method for precisely measuring the Cobb’s an- gle using deep learning based techniques. Mainly it comprises of feature enhance- ment of augmented dataset, a bespoke code for landmark estimation on the spine, segmentation model based on the U-Net architecture and a custom code for Cobb’s angle measurement. These measured angles are then compared to the given angles for the segmentation on biomedical (X-ray) images. RESULTS: The findings demonstrate that the proposed technique offers an auto- mated and impartial way for precisely measuring this angle with an overall accu- racy of 97% and Root Mean Square Error (RMSE) of 4.99, which can lower the variability, facilitate early detection, accurate diagnosis, and monitoring of scolio- sis progression. Additionally, it aids in the treatment planning and evaluating treat- ment outcomes. CONTRIBUTION: By leveraging the applications of Cobb’s angle measurement, healthcare professionals can enhance the quality of care and can improve long-term outcomes for individuals with scoliosis.

Background: The integration of unmanned aerial vehicles (UAVs), commonly known as drones, into medical logistics offers transformative potential for the transpor-tation of sensitive medical materials, such as blood samples. Traditional car transportation is often hindered by traffic delays, road conditions, and geographic barriers, which can compromise timely delivery. Methods: This study provides a comprehensive analysis comparing high-speed drone transportation with traditional car transportation under various weather conditions. Blood samples, including EDTA whole blood, Serum, Li-Heparin Plasma, and citrate plasma tubes, were transported via both methods across temperatures ranging from 4 to 20 degrees Celsius. The integrity of the samples was assessed using a wide array of analytes and statistical analyses, including Passing-Bablok regression and Bland-Altman plots. Results: The results demonstrated that drone transportation maintains blood sample integrity comparably to traditional car transpor-tation. For serum samples, the correlation coefficients (r) ranged from 0.830 to 1.000, and the slopes varied from 0.913 to 1.111, with minor discrepancies in five analytes (total bilirubin, calcium, ferritin, potassium, and sodium). Similar patterns were observed for EDTA, Lithium-Heparin, and Citrate samples, indicating no significant differences between transportation methods. Conclusions: These findings highlight the potential of drones to enhance the efficiency and reliability of medical sample transport, particularly in scenarios requiring rapid and reliable delivery. Drones could significantly improve logistical operations in healthcare by overcoming traditional transportation challenges.

In machining, there is a constant effort to achieve the expected roughness of the machined surface while maintaining the life of the cutting tool during its operation. The methods used for extending machinability characteristics can be applied due to cooling and lubrication. One of the latest, but not new, targeted cooling techniques have become cryogenic treatment, which uses substances that exhibit extremely low-temperature values of about 123 K. This is a very environmentally friendly technique compared to the current standardized cooling and lubricating fluids. The main task of such cooling is to change the properties of the workpiece so that it exhibits the properties of a brittle material. Bringing the workpiece structure in this way can result in easier material separation through the chip. In the article, the obtained test results can approximate the behavior of various materials during cryogenic cooling.

Non-union is one of the severe complications of traumatic fracture and still no standard therapeutic recommendations currently. A total of eleven patients were treated on the lesions for non-union, after the failure of open reduction internal fixation (ORIF) or total hip replacement, by autologous conditioned serum (ACS) for one to three times monthly and followed up. Seven patients received ACS three times, three patients received it two times, and the only one who underwent total hip replacement received it once. Ten patients achieved union at the last follow-up visit, indicating the effectiveness of ACS on patients who suffered from non-union after ORIF. ACS has the potential as an alternative or adjective treatment for non-union and is worthy to be investigated further for the benefits of patients.

The well-known hop variety Saaz, which gives the Pilsner lager beer characteristic hop aroma may be threatened by climate change in the future. Therefore, new Saaz-related hop varieties, Saaz Late, Saaz Brilliant, Saaz Comfort, and Saaz Shine were bred recently. To evaluate whether these varieties are ac-ceptable for traditional lagers, their comparison was carried out. For this purpose, sensorial and chemical analyses of hops and related beer including namely analysis of hop resins and hop oils were performed. Sensory profiles of Saaz varieties are very similar (fine hoppy aroma, floral, herbal) except for Saaz Comfort which has a little higher aroma intensity, and Saaz Shine which has the most noticeable fruity scent with traces of citrusy of all. Also, the chemical profiles are very close, α-humulene, β-pinene, (E)-β-farnesene, β-caryophyllene, and myrcene are the most abundant. As a result of decoction mashing and kettle-hopping technology with bottom fermentation, are very similar lager beers with hoppy, floral, herbal, fruity, and spicy aromas. Typical hop oils are farnesol, linalool, methyl geranate, β-pinene, and limonene. The high concentration of farnesol in beer correlates with the concentration of (E)-β-farnesene and farnesol in hops. New Saaz varieties are well used for the production of the Pilsner type of lager without affecting the traditional sensory aroma of this widespread style. Varieties have a higher yield and concentration of bitter acids and hop oils. Moreover, Saaz Shine and Saaz Comfort have very good re-sistance to drought, which is an important property from a climate change perspective.

This review provides a comprehensive analysis of the pelvic plexus and its regulation across various mammalian species, including rats, cats, dogs, and pigs. The pelvic and hypogastric nerves play crucial roles in regulating pelvic functions such as micturition, defecation, and erection. The anatomical organization of these nerves varies, forming either well-defined ganglia or complex plexuses. Despite these variations, the neurons within these structures are consistently regulated by key neurotransmitters—norepinephrine and acetylcholine. These neurons also possess receptors for testosterone and prolactin, particularly in rats, indicating the significant role of these hormones in neuronal function and development. Moreover, neuropeptides such as vasoactive intestinal peptide (VIP), substance P, neuropeptide Y (NPY), somatostatin (SOM), galanin (GAL), and calcitonin gene-related peptide (CGRP) are co-released with neurotransmitters to modulate pelvic functions. This review highlights the complex interplay between neurotransmitters, neuropeptides, and hormones in regulating pelvic physiology and emphasizes the importance of hormonal regulation in maintaining the functionality and health of the pelvic plexus across different species.

In the field of Natural Language Processing (NLP), Large Language Models (LLMs) have shown great potential in document-level event extraction tasks, but existing methods face challenges in the design of prompts. To address this issue, we propose an optimization strategy called "Definition-driven Document-level Event Extraction (DDEE)." By adjusting the length of the prompt and enhancing the clarity of heuristics, we have significantly improved the event extraction performance of LLMs. We used data balancing techniques to solve the long-tail effect problem, enhancing the model's generalization ability for event types. At the same time, we refined the prompt to ensure it is both concise and comprehensive, adapting to the sensitivity of LLMs to the style of prompts. In addition, the introduction of structured heuristic methods and strict limiting conditions has improved the precision of event and argument role extraction. These strategies not only solve the prompt engineering problems of LLMs in document-level event extraction but also promote the development of event extraction technology, providing new research perspectives for other tasks in the NLP field.

The activated carbons (ACs) derived from okara powder waste with high surface areas were modified with ammonia aqueous solution impregnation in an autoclave to enhance their CO2 adsorption properties toward CO2. The impregnated ACs were characterized in which surface chemical composition and properties of the ACs were analyzed by SEM-EDS, FTIR. Activated carbons were functionalized with ammonia aqueous solution (25%) through a hydrothermal process within 24; 48, and 72 hours. The adsorption performance of CO2 onto carbon samples was experimentally evaluated through a breakthrough adsorption experimental setup at room temperature. FTIR spectra confirm the N-containing in N-modified activated carbons and the presence of the –C = O stretch and N-H groups. CO2 uptakes of N-modified activated carbons are 0.24; 1.47; and 1.20 mmol/g, which are relatively comparable with those of activated carbons studied in in the literature.

Antibiotic prescription is the first line of treating bacterial diseases. But it affects the composition and function of non-targeted intestinal microbiota. Antimicrobial resistance will be the cause for the death of millions of people worldwide. By considering collateral damage of antibiotics, searching an alternative antimicrobial agent will be a solution to minimize the problems. Probiotics, prebiotics and synbiotics are an alternative to antibiotics. Thanks to GIT microbes as they are responsible for metabolism, energy production, protection from pathogens and immunomodulation. So, it is appreciable if the gut microbiota modulated through consumption of probiotics, prebiotics and synbiotics. Probiotic effects are genus and species specific. To get good health benefit of probiotics, safety of probiotics should be assessed before using them. This is mandatory for prebiotics and synbiotic selection. So this review paper gives information about side effects of antibiotics on gut microbiota, description of probiotics, prebiotics and synbiotics as alternative to antibiotics in modulating GIT microbiota, techniques of assessing safety of probiotics and health benefits of probiotics, prebiotics and synbiotics with scientific evidence in clinical trial and some disagreement and challenges of using probiotics, prebiotics and synbiotics.

(1) Background: Triggering receptor expressed on myeloid cells 2 (TREM2) is involved in neu-roinflammation and HIV-associated neurocognitive impairment (NCI). People with HIV (PWH) using cannabis exhibit lower inflammation and neurological disorders. We hypothesized TREM2 dysfunction mediates HIV neuropathogenesis and can be reversed by cannabinoids. (2) Methods: EcoHIV-infected wildtype (WT) and TREM2R47H mutant mice were used to study HIV's impact on TREM2 and behavior. TREM2 and related gene expressions were examined in mono-cyte-derived macrophages (MDMs) from PWH (n=42) and people without HIV (PWoH; n=19) with varying cannabis use via RNA sequencing and qPCR. Differences in membrane-bound and soluble TREM2 (sTREM2) were evaluated using immunocytochemistry (ICC) and ELISA. (3) Results: EcoHIV increased immature and C-terminal fragment forms of TREM2 in WT mice but not in TREM2R47H mice, with increased IBA1 protein in TREM2R47H hippocampi, correlating with worse memory test performance. TREM2 mRNA levels increased with age in PWoH but not PWH. Cannabidiol (CBD) treatment increased TREM2 mRNA alone and with IL1β. RNA-seq showed upregulation of TREM2-related transcripts in cannabis-using PWH compared to naïve controls. IL1β increased sTREM2 and reduced membrane-bound TREM2, effects partially re-versed by CBD. (4) Conclusions: These findings suggest HIV affects TREM2 expression modu-lated by cannabis and CBD, offering insights for therapeutic strategies.

Tongqi - women married to men who have sex with men (MSM) – from rural China encountered multi stigma with their male partners, family, community, local bureaucracies, and national laws, such as the hukou system, form a complex tapestry of life. The analysis navigates through various dimensions of stigma, reflecting systematically on their mutual implications. Social structures, including class and gender, shape societal norms and behaviors. This study explores the under-researched influence of social interaction, community relationships, and macrostructural factors contributing to the enacted stigma experienced by Tongqi Data collected from 59 rural Tongqi, 11 of whom contracted human immunodeficiency virus (HIV) or acquired immunodeficiency syndrome (AIDs), reveals the significant role of extended kinship networks and macrostructural elements, such as hukou (household registration) and government officers, in shaping the stigma faced by Tongqi. The importance of village-level lineage structures and dynamics highlights how these lineage relationships, interwoven with gender practices, contribute to the enacted stigma, physical and psychological health, and well-being of Tongqi. These include mental health, post-traumatic stress, depression, functional impairment, and permanent disability. Others include reproductive health, unwanted pregnancies, sexually transmitted infections (STIs), and pregnancy complications.

Background: Amidst escalating climate change concerns, sustainable practices in healthcare logistics are critical. This study evaluates the ecological impact and efficiency of medical sample transportation using drones, combustion cars, and electric cars across diverse terrains and weather in Liechtenstein and Switzerland. Methods: We conducted a comparative analysis of CO2 emissions, transport distances, and delivery times for each transportation modality. Data collection involved multiple runs under various conditions, with CO2 emissions measured using onboard systems, and transport efficiency assessed via GPS tracking and time monitoring. Results: Combustion cars exhibited the highest average CO2 emissions at 159.5 grams per kilometer (g/km). Electric cars emitted significantly less, averaging 3.43 g/km, which is 2.15% of combustion car emissions. Drones were the most environmentally friendly, with an average emission of 0.09 g/km, representing 0.07% of combustion car emissions and 2.6% of electric car emissions. Drones also showed substantial transport efficiency, covering 17% shorter distances on flat terrain and 24% shorter in mountainous areas, with time savings ranging from 13% to 80%. Conclusion: This study highlights the potential of drone technology to revolutionize healthcare logistics by reducing environmental impact and optimizing operational efficiency. Integrating drones can significantly lower the carbon footprint, improve sample integrity, and enhance patient care, promoting a greener, more resilient healthcare system.

Long COVID is a phenomenon in which individuals experience persistent symptoms after recovering from COVID-19. The symptoms are discovered to be unique for every individual and can affect multiple organs systems in the body. This study aims to identify effective natural remedies for long COVID by analyzing hub genes associated with the symptoms of the condition and evaluating the repurposed drugs catered and used for treating the symptoms of long COVID. The most common and prevalent symptoms of long COVID were identified; Fatigue, Shortness of Breath, Loss of Smell, Headache, Brain Fog, Chest Pain, Insomnia, Heart Palpitations, Dizziness, Joint Pain, Depression, Anxiety, Tinnitus, Loss of Appetite. Hub genes for each of the symptoms provided an insight on the key biological pathways of the symptom. Repurposed drugs identified, provided the template to identify the natural compounds with similar structure as a potential therapeutic drug. The natural compounds were retrieved using fingerprint search of the repurposed drugs from the NPASS Database. The findings of this study suggest several natural remedies for each symptom based on the molecular docking of the hub gene and natural compound using iGEMDOCK. The identified natural remedies may hold promise in treating long COVID, but further research is required to explore the efficacy and effectiveness of the proposed natural compounds. The results of the study pose important implications for the development of effective treatments for long COVID.

The Gulf of Mannar, a UNESCO World Biosphere Reserve, faces severe overfishing and habitat degradation threats. In this study, we investigate the pivotal role of ecosystem services in sustaining local livelihoods and overall well-being. By conducting a comprehensive survey of 480 respondents across two districts, we gathered extensive data on demographics, livelihoods, fishing practices, reliance on ecosystem services, and community management participation. The analysis reveals a critical dependence on the Gulf's resources (income, food security, traditions) with gender disparities (men fish, women in pre/post-harvest), but fishing is only allowed in the 10km buffer zone (not the core zone). The findings emphasize the promise of community-based strategies, such as Marine Protected Areas and reviving co-management committees, for achieving sustainable fisheries management. However, we also identify gaps, including the need for more nuanced well-being indicators and improved models for community management participation. To address these challenges, we advocate for sustainable fishing practices, tackling social inequities, especially gender disparities in resource access and decision-making, and investing in healthcare, education, and social safety nets for fishing communities. Promoting alternative livelihoods can alleviate pressure on fish stocks, and empowering local communities through capacity building and community-based management initiatives is crucial for ensuring the long-term sustainability of both the Gulf of Mannar ecosystem and the well-being of its dependent communities. This multifaceted approach holds significant promise for balancing ecological health with human prosperity.

This literature review presents a comparative analysis of cranial morphology in Allosaurus, focusing on its implications for feeding mechanics. Allosaurus, a large theropod dinosaur from the Late Jurassic period, exhibits distinct cranial features that are pivotal for understanding its predatory behaviors and ecological role. By examining fossilized skulls and employing advanced imaging techniques, this research identifies key morphological traits such as tooth structure, jaw articulation, and cranial robusticity. The analysis reveals that Allosaurus had a specialized cranial architecture that supported a powerful bite force and efficient processing of prey. Comparative metrics are applied to assess similarities and differences with other theropods, such as Tyrannosaurus rex, to elucidate variations in feeding strategies among theropods. The findings suggest that Allosaurus possessed adaptations that allowed it to exploit a diverse range of prey, indicating a versatile feeding strategy. These results enhance our understanding of theropod evolution and ecological interactions, providing insights into the functional significance of cranial morphology in dinosaurian predation. This review underscores the importance of cranial features in reconstructing the behavior and diet of extinct species and contributes to the broader field of vertebrate functional morphology.

The dielectric constant (ε) reflects the ability of a material to align and orient electrical dipoles within its structure in response to an externally applied electric field; the greater the polarizability of molecules, the greater the value of dielectric constant. In this study a data set of 86 polymers was investigated to develop a structure-property quantitative relations (QSPR) model to predict the dielectric constant in polymers. An initial set of 1273 descriptors was used to select a best set of descriptors and to construct two machine learning models with Gradient Boosting Regressor (GB_A and GB_B). The best performing model (GB_A) with 8 descriptors, exhibited a performance of (R2train) = 0.938 and (R2test) = 0.802. The models were internally validated by 5 folds cross-validation, demonstrating robustness. Additionally, using the Accumulative Local Effect (ALE) technique, we analyzed the relationship between the 8 descriptors involved and the impact of these descriptors to dielectric constant of polymers.

Ammonia synthesis is one of the most important chemical reactions. Due to thermodynamic restrictions and the reaction requirements of the current commercial iron catalysts, it is also one of the worst reactions for carbon dioxide emissions and energy usage. Ruthenium-based catalysts can substantially improve the environmental impact as they operate at lower pressures and temperatures. In this work, we provide a screening of more than 40 metals as possible promoter options based on a Ru/Pr2O3 catalyst. Cesium was the best alkali promoter and was held constant for the series of double-promoted catalysts. Ten formulations outperformed the Ru-Cs/PrOx benchmark, with barium being the best second promoter studied and the most cost-effective option. Designs of experiments were utilized to optimize both the pretreatment conditions and the promoter weight loadings of the doubly promoted catalyst. As a result, optimization led to more than a five-fold increase in activity compared to the unpromoted catalyst, therefore creating a possibility for low ruthenium ammonia synthesis catalysts to be used at scale. Further, we have explored the roles of promoters using kinetic analysis, XPS, and in situ infrared spectroscopy. Here, we have shown that the role of barium is to act as a hydrogen scavenger and donor, which may permit new active sites for the catalyst, and have demonstrated that the associative reaction mechanism is likely used for the unpromoted Ru/PrOx catalyst with hydrogenation of the triple bond of the dinitrogen occurring first before any dinitrogen bond breakage.

Puerto Rico's geographic and climatic conditions render it highly susceptible to natural disasters, particularly hurricanes. The devastation caused by Hurricane Maria in 2017 highlighted the fragility of the island's centralized energy infrastructure, which led to prolonged power outages and severe disruptions in essential services. This review explores the potential of biomass energy to enhance resilience in post-disaster scenarios, focusing on Puerto Rico as a case study. Biomass energy, derived from organic materials like agricultural residues, woody biomass, and municipal solid waste, offers a renewable and locally sourced power solution that can be rapidly deployed. Key biomass conversion technologies, including direct combustion, gasification, anaerobic digestion, and pyrolysis, are examined for their applicability and benefits in emergency energy provision. The implementation of biomass-powered microgrids in Puerto Rico, such as those by Casa Pueblo and Arensis, demonstrates the feasibility and effectiveness of decentralized energy systems in disaster recovery. These microgrids provide reliable power to critical infrastructure, reduce dependence on fossil fuels, and support waste management efforts. The review also discusses ongoing research and development in advanced biomass technologies, such as second-generation biofuels, algae-based biomass, and biomass-to-hydrogen conversion, which can further enhance energy efficiency and sustainability. Additionally, the economic, environmental, and social impacts of biomass energy are evaluated, highlighting its role in job creation, waste reduction, emission control, and community resilience. Policy recommendations include streamlining permitting processes, enhancing financial incentives, developing feedstock supply chains, and incorporating biomass into disaster recovery plans. The findings suggest that integrating biomass energy into Puerto Rico’s energy strategy can significantly improve its capacity to respond to and recover from natural disasters, promoting long-term sustainability and resilience.

This study presents a novel approach combining computer vision with topology optimization for additive manufacturing. Using specialized photogrammetry software, we capture high-resolution images of the design domain to create precise 3D models through detailed scanning. These models are converted into STL file format and remeshed using an adaptive algorithm within COMSOL 5.3 Multiphysics, managed by a custom MATLAB 2023. This integration allows optimal mesh resolution and accuracy in analyses. We applied this method to design a concrete pillar for 3D printing, aiming for a 75% volume reduction to enhance material efficiency and stability, crucial for extraterrestrial environments. The design, scanned with a 360-degree camera array, informed the MATLAB-based topology optimization process. Combining MATLAB’s optimization algorithms with COMSOL’s meshing and finite element solver solver, we explored material-efficient configurations. The results show significant volume reduction, particularly in the central design area, optimizing material use while maintaining structural stability. The optimization algorithm demonstrated rapid, stable convergence to near-optimal solutions within about 20 iterations, highlighting the method’s efficiency and robustness in complex design optimization.

Focus Group Discussions (FGDs) are widely employed in qualitative research to delve into complex social issues, yet their application in conservation studies lacks standardised guidelines and thorough evaluation. This review assesses the utilisation of FGDs in biodiversity and conservation research from 2000 to April 2022, identifying 170 pertinent articles, primarily published between 2015 and 2022. FGDs, often integrated with other methodologies, predominantly sought to understand community perspectives, evaluate conservation practices, explore challenges, and document indigenous knowledge. Despite their extensive use, methodological intricacies were frequently underreported. This paper underscores the necessity for enhanced reporting standards and comprehensive guidelines to optimise the effectiveness and reliability of FGDs in conservation research. By means of critically investigating existing literature, this study contributes critical important insights into the strengths and limitations of FGDs, ultimately advocating for greater methodological rigour and transparency in their application within the realm of conservation science.

Ichthyosis is a genetic skin disorder marked by hyperkeratosis, pruritus, and scaling. This case study explores a potential association between ichthyosis and scalp paresthesia, a symptom not commonly linked with this dermatological condition. In a longstanding history of ichthyosis patients, we detail the therapeutic use of fluocinolone, a synthetic corticosteroid, in managing scalp paresthesia. The effectiveness of fluocinolone in reducing paresthesia episodes underscores its potential as a critical component in the symptomatic treatment of this complex interplay between skin and neurological symptoms. This case prompts a broader discussion on the need for increased awareness and education among healthcare providers regarding the diverse manifestations of ichthyosis. Enhanced understanding and recognition of these associations can lead to improved patient counseling, tailored management strategies, and, ultimately, better quality of life for individuals affected by ichthyosis.

Abstract Introduction: Long COVID (LC) affects multiple systems and has a significant health impact on patients and society. Therefore, long COVID services should address patients’ needs through a holistic assessment and monitoring of patients’ symptoms. Aim: The aim was to understand which of the symptoms were most and least likely to improve, after our rehabilitation intervention so that the rehabilitation measures in the clinic could be modified to meet patients’ needs. At the same time, we wanted to assess the feasibility of using C19-YRS ELAROS application in monitoring of LC symptoms during and after the rehabilitation clinic attendance. Methodology: In this study, a total of 50 patients who have attended long COVID rehabilitation clinic in Salford, UK; were assessed by using digitalised C19-YRS ELAROS application. A total of 100 eligible initial and final post rehabilitation assessments were analysed. Conclusion: Pain and anxiety symptoms were the two most likely symptoms to improve after intervention at LC rehabilitation clinic, whereas swallowing difficulty is least likely to improve. Issues with caring for family/ social life (symptoms affecting social role) are likely to worsen even after treatment. It is feasible to monitor and track Long COVID symptoms utilising the digitalised version of C19-YRS via the ELAROS App. This also allows the tracking of symptoms overtime.

This paper shows the development of a numerical analysis model which enables the calculation of the life of a reduced-diameter wheel used for freight wagons as a function of its operating factors. Reduced-diameter wheels are being increasingly used for combined transport applications and they can be arranged in a wide range of bogies and operated very differently. Due to the uniqueness of this type of wheels, their life has hardly been analyzed so far. To properly construct the numerical analysis model, it has been necessary to study the rolling phenomenon in-depth, tackle the main problems arising in the vehicle – track interaction and set the relations amongst them. Once the rail-wheel interaction model was built, it was used to calculate the life of an ordinary-diameter wheel, a medium-diameter wheel and a reduced-diameter wheels under the same conditions and compare them. In this way, it is possible to know how long the life of a reduced-diameter wheel is compared to that of an ordinary-diameter one and also the evolution of the life depending on the diameter. The root causes responsible for this evolution can be explained thanks to the comprehension of the rolling phenomenon provided by the full analytical work.

The anterior cruciate ligament (ACL) is a critical structure within the knee joint, primarily responsible for maintaining stability and enabling the knee to perform a wide range of movements essential for both everyday activities and athletic performance. It functions as a key stabilizer by preventing excessive forward movement of the tibia relative to the femur and by controlling rotational forces that occur during activities such as pivoting, cutting, and jumping. The biomechanical integrity provided by the ACL is crucial, especially during dynamic activities that place significant strain on the knee joint, making it indispensable for athletes and active individuals. However, due to its pivotal role and the considerable mechanical demands placed upon it, the ACL is particularly vulnerable to injury. ACL injuries are prevalent, especially among athletes involved in high-risk sports such as soccer, basketball, football, and skiing, where rapid changes in direction, sudden stops, and direct impacts are common. The incidence of ACL injuries is a significant concern in sports medicine, not only because of the immediate impact on an athlete's career but also due to the long-term health implications associated with such injuries. These injuries often result in complex, multifaceted complications, including persistent joint instability that can compromise the structural and functional integrity of the knee, leading to recurrent injuries and reduced performance levels. One of the more insidious consequences of ACL injuries is the loss of proprioception, the body's ability to sense the position, movement, and action of the joints. Proprioception is vital for coordinated movement and balance, and its impairment can lead to a diminished capacity to control knee movements, further increasing the risk of re-injury. Additionally, the long-term sequelae of ACL injuries often include the development of post-traumatic osteoarthritis, a degenerative condition characterized by the gradual breakdown of joint cartilage and underlying bone. This condition not only causes chronic pain and stiffness but can also significantly impair an individual's quality of life, limiting their ability to engage in physical activities and, in severe cases, leading to disability. Despite the remarkable progress made in the fields of orthopedic surgery and sports rehabilitation, the recovery process following an ACL injury remains challenging. Surgical techniques, such as ACL reconstruction, have evolved to offer more reliable outcomes, and rehabilitation protocols have been refined to promote quicker and more effective recovery. However, the reality is that many patients do not achieve the level of recovery needed to return to their pre-injury level of activity or to maintain long-term knee health. This suboptimal recovery is often attributed to the complex interplay of neurophysiological and molecular factors that are not yet fully understood. Neurophysiologically, the recovery from an ACL injury involves not only the physical repair of the ligament but also the re-establishment of neuromuscular control and the adaptation of the central nervous system (CNS) to the altered mechanics of the knee. The CNS plays a crucial role in modulating the body's response to injury, influencing the way muscles activate and coordinate to protect the injured joint. However, disruptions in neuromuscular control post-injury can lead to compensatory movement patterns that may predispose individuals to further injury or hinder their recovery. Understanding these neurophysiological changes is essential for developing rehabilitation strategies that address not just the mechanical aspects of recovery but also the re-training of the neuromuscular system. On the molecular level, the healing process of the ACL involves a cascade of cellular and biochemical events that are critical for tissue repair and regeneration. These processes include the inflammatory response, cell proliferation, and the remodeling of the extracellular matrix, all of which are regulated by various molecular signals and pathways. Advances in molecular biology have begun to unravel the complexities of these processes, offering insights into how they can be manipulated to enhance healing and reduce the risk of complications such as fibrosis or improper tissue regeneration. By integrating molecular biology with clinical practice, there is potential to develop targeted therapies that can optimize the healing environment, improve surgical outcomes, and accelerate the recovery process. This review aims to provide a comprehensive examination of the neurophysiological aspects of ACL injury and the rehabilitation process, while also exploring the potential contributions of molecular biology to improving treatment outcomes. By delving into the intricate mechanisms that underlie ACL injury and recovery, the review seeks to highlight the challenges that remain in the field and to propose new directions for research that could lead to more effective and individualized treatment approaches. The ultimate goal is to enhance our understanding of ACL injuries and to develop strategies that not only restore knee function but also preserve long-term joint health, allowing individuals to return to their desired level of activity with confidence.

Maxwell's equations accurately describe the propagation of electromagnetic (EM) waves. However, the conventional formulation implies invariance to observers, posing challenges in explaining how the wave is perceived by different observers. For example, Doppler effect shows that observers perceive the same EM wave differently.By employing mathematical transformations, we derive a general form of Maxwell’s wave equations by incorporating a "time scaling" factor to account for observer perception. The original form is shown to be a special case when static. The Doppler effect and Sagnac effect are directly derived from Maxwell’s equations. All the results are consistent with established experiments.Our findings offer a fresh perspective, promising a deeper understanding and unification of EM phenomena. We extend Maxwell’s equations to describe not only the propagation of an EM wave, but also how it will be measured by different observers, say, antennas.

Oxidative stress and chronic inflammation create a perpetual cycle in the elderly, where impaired immune function amplifies susceptibility to oxidative damage, and oxidative stress further weakens the immune response. This cycle is particularly detrimental to the respiratory system of the elderly, which is an easy target for constant exogenous harmful attacks during cold/flu season or under heavy air pollution. Herbal medicines that protect respiratory function are seen as safer alternatives to conventional therapies; however, there is limited availability of scientifically validated, safe, and effective natural supplements for these conditions. In this study, we evaluated a standardized bioflavonoid composition, UP446, which contains bioactives from the roots of Scutellaria baicalensis and the heartwoods of Acacia catechu, as a natural and nutritional supplement for its antioxidative and immunoregulatory effects in oxidative stress-accelerated aging and chemically induced immune suppression mouse models. Immunosenescence was induced by continual subcutaneous injection of D-galactose (D-Gal) at a dose of 500 mg/kg/day in CD-1 mice. UP446 was administered orally at doses of 100 mg/kg and 200 mg/kg starting in the fifth week of immunosenescence induction. The study lasted a total of ten weeks. All mice received a quadrivalent influenza vaccine 14 days before the end of the study. Whole blood, serum, spleen homogenate, and thymus tissues were used for analysis.Cyclophosphamide (Cy)-induced immunosuppression was triggered by three consecutive injections of cyclophosphamide at 80 mg/kg/day, followed by oral administration of UP446 for 18 days at doses of 100 mg/kg and 200 mg/kg. Blood was collected from each animal at necropsy, and serum was isolated for IgA and IgG ELISA analysis. UP446 was found to improve immune response, as evidenced by stimulation of innate (NK cells) and adaptive immune responses (T cells and cytotoxic T cells), an increase in antioxidant capacity (glutathione peroxidase), preservation of vital immune organs (the thymus), and a reduction in NFκB. UP446 also increased serum levels of IgA and IgG. The findings presented in this report demonstrate the antioxidative, anti-inflammatory, and immune-regulatory activities of UP446, suggesting its potential use in respiratory conditions involving immune stress due to aging, oxidative stress, and/or pathogenic challenges.

This study explores the relationship between positive and negative habits and their rewards over time. Using a bibliographic and documentary approach, we analyze how the temporality of rewards influences the formation and maintenance of habits. We developed the "habit chart", which shows that positive habits, such as reading, healthy eating, physical exercise, meditation and personal relationships, offer incremental and lasting rewards. In contrast, negative habits such as sugar consumption, excessive use of social media and a sedentary lifestyle provide immediate gratification followed by a sharp decline. The analysis was based on studies such as those by Warburton et al. (2006), Lally et al. (2010), and Hu (2003) for positive habits, and Malik et al. (2010) and Kross et al. (2013) for negative habits. We conclude that practical strategies, such as financial incentives and creating enabling environments, can make long-term rewards more tangible, promoting the adoption of healthy behaviors. This study reinforces the importance of the temporality of rewards in habit formation and suggests evidence-based interventions to improve quality of life and general well-being.

Jordan is classified as a low- to-middle-income, in which the primary energy sources are imported crude oil and natural gas. The energy expenses represent a high percentage of the country's GDP. Meanwhile, due to its geographical location and its climate, Jordan ranks very high among the world countries with respect to solar energy exploitation potential. Therefore, solar energy is a key resource that can be utilized to significantly improve both the country’s economy and energy security. It has to be highlighted that Jordan focus on a network dedicated to solar energy and it has to be mentioned the Erasmus Plus INNOMED Project based on virtual classrooms, which aims to promote innovative technologies and applications of solar energy in MENA Countries. This paper presents an overview of the solar energy resources in Jordan that includes: the current situation, the potential, and future expectations.

This paper thoroughly assesses the ARM and RISC-V architectures in the context of High-Performance Computing (HPC). It includes an analysis of Docker, Kubernetes, and KVM virtualization integration. Our study aims to evaluate and compare these systems' performance, scalability, and practicality in a general context and then assess the impact that might have on special use cases, like HPC. ARM-based systems exhibited better performance and seamless integration with Docker and Kubernetes, underscoring their advanced development and effectiveness in managing high-performance computing workloads. On the other hand, despite their open-source architecture, RISC-V platforms presented considerable intricacy and difficulties in coordinating with Kubernetes, which hurt their overall effectiveness and ease of management. The results of our study offer valuable insights into the practical consequences of implementing these architectures for HPC, highlighting ARM's preparedness and the potential of RISC-V while acknowledging the increased complexity involved and significant trade-offs at this point.

Nowadays recurrent implantation failure (RIF) after invitro fertilization is common problem that reproductive specialists usually faced. The phenomenon of thin endometrium in RIF patients has yet not completely understood and properly treated. This study aimed to reveal significantly dysregulated selected genes expression between RIF patients with thin endometrium and fertile women. Endometrial samples were collected in the implantation window days (LH+7 – LH+10) of the natural menstrual cycle from RIF patients (n=20) and fertile women (n=14). Ten genes were chosen as target genes regarding their possible relations with the implantation process. Endometrial gene expression levels showed differences in RIF samples compared to fertile samples. The significant downregulation was observed for CXCL1 (p=0.005) and C4BPA (p=0.03) genes. There was no statistically significant difference between the RIF groups and the fertile group in the expression of 8 genes: CXCL8, HPRT1, MMP10, INFG, VEGFB, HAND2, IL15 and TNC (p>0.05). The use of a combination of two markers (C4BPA + CXCL1) allows for good discrimination of RIF patients from fertile women (AUC 0.806).

Influenced by the pluralistic and open-minded cultural ideologies of shamanism, the rulers of the Mongol Yuan Dynasty emphasized the implementation of religious government policies with an emphasis on coexistence, adaptability, and pragmatism. The Mongol ruling elite formed alliances with religious factions in various regions and worked closely with local spiritual leaders. During the era of the Great Mongol State, Kublai Khan valued the wealth of the Han Chinese territories. To maintain the order of Mongol Yuan rule in northern China, he used Han Chinese Buddhism and other religious forces to balance and suppress Quanzhen Dao. As a result, Chinese Buddhism became increasingly politically influential in Mongolia. Using their religious identity and talent, Chinese Buddhist monks became active in Mongolia to regulate the political activities of the Han Chinese religious forces. This led to a shift in the religious landscape of northern China during the transition from the Jin to Yuan dynasties.

This research investigates the relationships between occupational health and safety (OHS), staff resilience (SR), staff engagement (SE), and organizational resilience (HOR) within Saudi Arabian hospitals. Employing a quantitative, cross-sectional design, data were collected from 127 administrative staff members working in both public and private hospitals in Saudi Arabia. Using SmartPLS to test the hypothesized relationships and mediation effects, the findings reveal that OHS significantly impacts both SR and SE, and SR significantly influences HOR. Additionally, SE significantly affects HOR. The study also confirms a partial mediation effect of SE and SR in the relationship between OHS and HOR. The model demonstrates substantial explanatory power for HOR, SE, and SR. These results underscore the critical role of OHS in fostering a resilient healthcare environment by enhancing staff engagement and resilience. The study’s implications highlight the importance of targeted interventions to improve OHS practices, promoting overall hospital resilience in alignment with Saudi Arabia’s Vision 2030.

Gaussian mixture models (GMMs) are powerful tools specifically suited for problems where data distributions are multi-modal. Inspired by Fourier expansion, we propose a concept called GMM expansion to approximate arbitrary densities. A simple learning method is introduced under this framework. Theoretical and numerical analyses are provided to show that densities under GMM expansion are able to approximate arbitrary densities with certain accuracy. The proposed learning algorithm demonstrates better accuracy and time efficiency compared to classic density approximation methods such as the Expectation Maximization (EM) algorithm and Bayesian variational inference (BVI) for Gaussian mixture models. The proposed framework also shows better accommodation of neural networks. Three neural network applications are built to demonstrate its usability. The accuracy of density estimation in neural networks is reported to be significantly improved in one of the applications. Another application shows that latent variables can be easily turned into random variables. This user-friendly method opens up more possibilities in terms of latent manipulation, embedding techniques, and many other potential uses.

The research paper examines ‘aporia,’ ‘Différance,’ ‘binary oppositions’ in Ira Trivedi's "The Great Indian Love Story," and India in Love focusing on the characters Riya, Serena, and Permeet's experiences. Derrida’s deconstructive approach is applied to trace out ‘binaries’, ‘aporia’, and ‘Différance’ of sexuality and stigma in literary texts and real human life. It highlights how these characters seem/likely to challenge Indian societal norms and values, societal prejudices and discrimination that lead them to experiences of marginalization and exclusion of the self from other selves. It is observed that deconstruction is an apt approach to literature not a destructive approach.

Background: Research has consistently shown increased drug use among lesbian, gay, bisexual, transgender, intersex, queer/questioning, and asexual (LGBTQIA+) individuals. This is particularly the case among LGBTQIA+ adolescents. Substance use within this vulnerable community can propagate mental health issues leading to psychiatric disorders, self-harm and even suicide. Therefore, the objective of this scoping review was to evaluate the determinants of drug use among LGBTQIA+ adolescents. Methods: A comprehensive search of mainly primary research was conducted using several databases. Peer-reviewed articles published between 2018 and 2023 were included. The scoping review was conducted using the framework outlined by Joanna Briggs Institute (JBI) and reported using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses- Extension for Scoping Reviews (PRISMA-ScR) statement. Results: A total of 29 articles (including 400194 participants) were included in the analysis. The articles reported that the main determinants of drug use among LGBTQIA+ adolescents include homelessness, peer-peer interactions, mental health, and protective factors. The articles reported that mental health issues, which are mainly triggered by rejection, were the main determinants of drug use among LGBTOIA+ adolescents. Conclusion: Findings from this scoping review provide relatively reliable evidence that homelessness, mental health, peer-peer interactions, and protective factors are the main determinants of illicit drug use among LGBTQ+ adolescents. Rigorous studies that include large sample sizes, and systematic reviews are needed to further confirm these findings and assist in developing interventions to combat the unusually high level of drug use among this group.

The importance of maintaining a healthy indoor climate has recently increased, as has the durability of building structures and for this issue we need prediction of mould growth. The prepare this model under real conditions is challenging, and this work aimed to contribute data to this model. This article presents the findings of a laboratory study investigating the effects of fluctuation relative humidity and temperature conditions on mould growth on pine and spruce. The study compared the results to a previous steady-state experiment, demonstrating that fluctuations in relative humidity and temperature prolonged the onset of mould growth. The mould growth observed depended on the type of wood, with pine or spruce wood exhibiting different growth patterns compared to heartwood or sapwood. In sapwood, mould growth was found to be almost independent of the direction of the fibre. The first microscopic indications of mould growth on pine sapwood were observed around day 76th, with the first macroscopic indications observed around day 90th. On the contrary, spruce sapwood demonstrated a limit for mould growth. The mould growth was only visible under the microscope, with the first indications observed between the 72nd and 80th day. Furthermore, heartwood was found to be unsuitable for mould growth under fluctuating conditions.

Smart technology is essential for integrating circular economy principles. This study examines how conflict management strategies including collaboration, accommodation, avoidance, compromise, and competitions impact smart technology adoption, particularly blockchain, in Jordanian SMEs, a context that has been under-explored. Additionally, the research examines the moderating role of customer-centric green supply chain management in the relationship between blockchain adoption and the implementation of circular economy principles. Data were collected from 421 senior managers, department heads, and executives of Jordanian SMEs. Primarily, this study employed robust methodological approach, a structural equation modeling (SEM) technique, to test the hypotheses and analyze complex relationships. This research provides valuable insights into the adoption of blockchain technology in Jordanian SMEs, highlighting the importance of strategic conflict management, a context that is rarely explored. Incorporating customer-centric green supply chain management as a moderating factor enhance the sustainability and competitiveness of SMEs through blockchain technology. This approach offers new insights into how blockchain technology aligns with circular economic principles, highlighting the strategic role of conflict management in driving technological innovation and sustainability. The study results indicate that conflict management strategies have a significant impact on the adoption of blockchain technology among Jordanian SMEs. The results also revealed a unique finding that collaboration and compromise are the most influential strategies. Furthermore, the study found that blockchain adoption positively impacts the implementation of circular economy principles. This study provides theoretical and practical insights for SMEs, especially in the context of Jordan.

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

Increasing efforts have been devoted to promoting sustainable demolition waste management (DWM) from a life cycle-thinking perspective. To this end, facilitating sustainability-oriented de-cision-making for DWM planning requires a sustainability assessment framework for assessing multifaceted criteria. This study develops a BIM-based DWM sustainability assessment ap-proach to facilitate the life cycle assessment (LCA) and decision-making by coupling the enriched IFC model with hybrid Multi-Criteria Decision-Aiding (MCDA) methods using Dynamo visual scripting. To streamline the data-intensive LCA process, this study enriched the BIM properties and accommodated them into the LCA data template to enhance data interoperability, thus achieving seamless data transfer. Moreover, hybrid MCDA methods are integrated into the deci-sion-making workflow for DWM scenario ranking. A pilot study is employed to verify the ap-plicability of the decision-aiding framework. The results unveil that the sustainability score ascended with the recycling rate. The optimal DWM alternative with the highest recycling rate yields the highest sustainability score at 91.63. Conversely, a DWM alternative reflecting the ‘status quo’ in China’s recycling industry has the lowest score at 8.37, significantly lower than the baseline scenario with a 50% recycling rate. It is worth noting that the ‘growth curve’ of the sustainability score continuously flattens as the target recycling rate escalates. The increment in recycling rate from the “Australian standard” scenario to the optimal scenario is 18.4%, while the sustainability score merely increases by 2.3%, signal-ling that the former scenario arrived at an optimum point for maximising the cost-efficiency of DWM under the predefined framework and contexts.

Introduction Image Guided Superficial Radiation Therapy (IGSRT) is a novel technology which combines traditional superficial radiation therapy (SRT) with high resolution dermal ultrasound (HRDUS) to treat non-melanoma skin cancers (NMSC). Since development, IGSRT use has expanded dramatically in outpatient clinics. We review the IGSRT literature and state of the art operating principles in US dermatologic practices. Materials and Methods A literature search of electronic databases (Medline, Pubmed, Cochrane Library, Science Direct) combined with various authors’ published and unpublished documents, procedures and clinical experience with IGSRT were synthesized for this paper. Results Studies have demonstrated IGSRT consistently delivers high cure rates( >99%) with low complications for early stage (stage 0, I, or II) squamous cell and basal cell carcinomas. Control rates are statistically superior to non-image guided SRT and external beam radiation (XRT) as well as Mohs Micrographic Surgery(MMS). This improvement is attributed to in-vivo dermal tumor visualization via HRDUS and using an interdisciplinary approach to deliver care. IGSRT use in the dermatologic clinic for early stage NMSCs has become common practice and continues to expand. Conclusion While the safety and cosmetic benefits of SRT/XRT has been long documented, IGSRT represents a significant leap forward in efficacy (statistically significant) by adding in-vivo dermal tumor imaging. Results rival and appear on one study to surpass tumor control obtained with MMS. A contributing factor to the success may be the availability and use of an interdisciplinary team approach that includes dermatologists, radiation therapists, radiation oncologists and medical physicists. The high tumor control rates, minimal side effects, favorable cosmesis and ability to treat multiple lesions per session using IGSRT is establishing this modality as a standard first line therapy for early stage NMSCs in dermatology clinics. IGSRT may represent the most effective option for the non-surgical treatment of early stage NMSC to date.

This study employed High-Performance Liquid Chromatography coupled with Diode Array De-tector and Mass Spectrometry (HPLC-DAD-MS) to characterize bioactive compounds in olive leaf extracts. The analysis revealed a diverse metabolic profile, predominantly composed of tyrosol, flavonoids, and hydroxycinnamic acid. The antioxidant activity of the extracts demonstrated their efficacy, with variations observed between neutral and acidic pH conditions. Encapsulation was explored as a preservation method, successfully maintaining the integrity of phenolic compounds in both liquid and powdered forms. All four extracts have an undeniable antimicrobial effect. Moreover, the antibacterial activity tested on E. coli ATCC 25922 and S. aureus ATCC 25923 strains significantly improved post-encapsulation, particularly for the acidic pH extract. The findings suggest that encapsulation can potentially conserve and/or enhance the antimicrobial activity of olive leaf extract, paving the way for developing functional products with improved shelf life and nutritional properties. Further investigations are recommended to elucidate underlying mecha-nisms and optimize encapsulation processes to maximize the benefits of olive leaf extract in di-verse applications.

Arsenic trioxide (ATO) is now part of the standard regimen for the treatment of newly diagnosed and relapsed acute promyelocytic leukaemia. The availability of an oral form of ATO has greatly reduced the incidence of cardiotoxicity as compared to intravenous administration. Increasing evidence suggests that ATO has anti-inflammatory properties that may be useful for the treatment of autoimmune diseases. These include the modulation of Treg cell activation, Th1/Th2 and Th17/Treg balance, depletion of activated T cells and plasmacytoid dendritic cells, and influence of B cell differentiation, leading to reduced autoantibody and cytokine production. ATO has also been shown to induce apoptosis of activated fibroblast-like synoviocytes through generation of reactive oxygen species and alter the gut microbiota in collagen-induced arthritis. Despite the emergence of newer treatment modalities, the treatment of systemic lupus erythematosus (SLE), especially refractory manifestations, remains a challenge, owing to the paucity of effective biological and targeted therapies that are devoid of adverse effects. Oral ATO is an attractive option for the treatment of SLE because of the lower cost of production, convenience of administration and reduced cardiotoxicity. This article summarizes the anti-inflammatory mechanisms of ATO and its potential application in the treatment of SLE.

Cybersecurity ecosystem is an important facet in protecting sensitive information and securing critical infrastructure for countering modern cyber threats. With the increasing complexity and frequency of security incidents, there is an escalating demand for development of innovative solutions beyond current human capabilities pertaining to cybersecurity measures. Artificial Intelligence or AI can be utilized in a myriad of areas of cybersecurity. It emerged as a technological innovation to enhance cyber protection by facilitating faster and real-time threat detection for known and unknown threats, automating processes to minimize human error, and optimal decision-making. Harnessing the power of AI in cybersecurity creates formidable defense capabilities against the constantly changing cyber threats of future while empowering the cybersecurity personnel with threat intelligence and proactive foresight to safeguard critical assets and confidential information with unparalleled precision and effectiveness. This research paper aims to investigate the potential of AI-enabled cybersecurity systems and focuses on deducing the benefits of using AI in enhancing cybersecurity processes for organizations seeking to manage their risk profile. Through a comprehensive literature review, the wide-ranging applications of AI in cybersecurity have been analyzed such as intrusion detection, predictive simulation, and automated emergency response management. The study examines the benefits of implementing AI-based cyber defenses such as improved promptness and accuracy in vulnerability assessment and threat management, reduced false positives, and recognize patterns. The future potential of AI in cybersecurity will take a leap forward in expanding protection mechanisms to evaluate the strengths and weaknesses of attack vectors to prevent an adversarial attack.

The Riemann hypothesis is the assertion that all non-trivial zeros are complex numbers with real part $\frac{1}{2}$. It is considered by many to be the most important unsolved problem in pure mathematics. There are several statements equivalent to the famous Riemann hypothesis. Robin's criterion states that the Riemann hypothesis is true if and only if the inequality $\sigma(n) < e^{\gamma} \cdot n \cdot \log \log n$ holds for all natural numbers $n > 5040$, where $\sigma(n)$ is the sum-of-divisors function of $n$, $\gamma \approx 0.57721$ is the Euler-Mascheroni constant and $\log$ is the natural logarithm. We require the properties of superabundant numbers, that is to say left to right maxima of $n \mapsto \frac{\sigma(n)}{n}$. In this note, using Robin's criterion on superabundant numbers, we prove that the Riemann hypothesis is true.

While in the past, especially numerical approaches such as regression models and p-values were utilized to investigate whether the functional form between age and happiness is linear or U-shaped in a given country, recent advances have shown that such approaches can be misleading, and graphical analyses should amend the analyses. However, these have the downside that they rely to some extent on subjective interpretations and are hardly quantifiable. If applied carelessly, they can be misleading as well. We suggest two easily computed statistics to combine graphical and numerical approaches. We demonstrate their usage with ESS data (N > 440,000) and show how they enable a more nuanced investigation of functional forms. Furthermore, we discuss how statistical uncertainty can be handled in the age-happiness debate and emphasize practical significance, which needs to be kept in mind.

This paper proposes a novel economic theory - Economic dynamics, which is the first in a series of articles on the economic dynamics. This paper is divided into four sections. Section 1 discusses the methodology and significance of the economic dynamics. The application of the standard model of theoretical physics as a new conceptual and modeling reference framework for the economic dynamics is an inevitable step beyond the Newtonian mechanics framework. Section 2 briefly outlines the content of the economic dynamics and its standard model, including market dynamics and its quantum electrodynamics model, both sharing the U(1) symmetry group; the sub-economic dynamics and its quantum chromodynamics model, both sharing the SU(3) symmetry group; the economic externality dynamics and its isospin dynamics model, both sharing the SU(2) symmetry group; and the ordinary rationality mechanism and its Higgs mechanism model, both causing spontaneous symmetry breaking. Additionally, through analysis of Pareto efficiency, it outlines economic gravity and its general relativity model. Section 3 provides three necessary foundational theoretical preparations for the economic dynamics, detailing scientific observation theory, economic rationality theory, and monetary pecuniary theory. Scientific observation theory first introduces the concept of observational directionality for empirical sciences, providing a shared orthogonal frame for cross-disciplinary observation, termed the orthogonality principle. By introducing the concept of observational disturbance degree, it distinguishes between high disturbance quadrants and low disturbance quadrants, corresponding to different mathematical paths, termed the diagonal rule. Quantum physics, higher-order cognition, and economic forward observation all fall within the high interference area, belonging to von Neumann's "yes-no" type of measurements, and are suitable for the same mathematical description. Economic rationality Theory, within the decision theory framework, defines three types of rationality theories: Economic rationality (or economic rational man), bounded rationality, and ordinary rationality, and defines the position of each rationality theory in the gauge field theory model of market dynamics. Economic rationality is a personified description of perfect competitive markets, the former being the global gauge potential, while the latter is the global gauge field strength. Bounded rationality describes specific market participants, the former being the local gauge potential, while the latter's market performance is the local gauge field strength. Ordinary rationality is the market ground state, possessing the properties of the Higgs field and the functions of the Higgs mechanism, causing spontaneous symmetry breaking in the market. The monetary pecuniary theory first argues for its light-like nature, thereby establishing a special relativity model of monetary peculiarity. This is a necessary condition for applying the gauge field theory model in market dynamics. Within the special relativity framework, using absolute prices (absolute time), a geometrized global money cone (light cone) can be constructed. Using intrinsic prices (proper time), individualized local wealth cones and poverty cones can be constructed, reflecting individual differences among market participants.

The present contribution introduces the task dependent comfort zone as a base placement strategy for mobile manipulators using different manipulability measures. Four different manipulability measures depending on end-effector velocities, forces, stiffness, and accelerations are considered. By evaluating a discrete subspace of the manipulator workspace with these manipulability measures and by using image processing algorithms, a suitable goal position for the autonomous mobile manipulator was defined within the comfort zone. This always ensures a certain manipulator manipulablity value with a lower limit in respect to the maximum possible manipulability in the discrete subspace. Results are shown for three different mobile manipulators using the velocity dependent manipulability measure in a simulation.

Wastewater genomic surveillance is an efficient and economic approach to track infectious diseases and can help detect unusual epidemiological events. The current study uses this approach for the first time in Morocco to monitor the epidemiology of SARS-CoV-2 and Influenza A, B and RSV virus infections during the third wave of COVID-19 caused by the Omicron variant. The virome was concentrated from wastewater collected from two sewer sheds of two cities, Agadir and Inezgane, using the PEG/NaCl method. The viral copy number was determined using qRT-PCR. All 26 samples in both cities were tested positive for SARS-CoV-2 at various viral loads. For Influenza A virus, two samples were tested positive in Inezgane. The estimated SARS-CoV-2 viral RNA copy numbers observed were then used to estimate the number of infected individuals using the SEIR model. The number of viral copies of SARS-CoV-2 for Agadir and Inezgane varied from 82932 ± 15479 to 507865 ± 58759 copies/L and 61244 ± 8552 to 497506 ± 18061 copies/L, respectively. The estimated number of cases correlates positively with the number of reported cases. Next Generation Sequencing showed that samples contain the following two variants: BA.1 and BA.2 that have been detected in clinical samples. This study demonstrates the effectiveness and feasibility of wastewater genomic surveillance in monitoring pathogens such as SARS-CoV-2 in Morocco.