Synopsis Corneal epithelial wavefront error and epithelial thickness variance qualify as highly sensitive and specific biomarkers for epithelial basement membrane dystrophy (EBMD). The biomarkers show a normalization after treatment of EBMD with phototherapeutic keratectomy. Purpose: To gauge the diagnostic value of a novel spectral-domain optical coherence tomography (SD-OCT) based imaging modality for simultaneous morphological (thickness profile) and refractive (optical wavefront) assessment of the corneal epithelial layer in one of the most common but often underdiagnosed corneal dystrophies: epithelial basement membrane dystrophy (EBMD). Methods: In this prospective observational study, a total of 32 eyes of 32 patients diagnosed with EBMD and 32 eyes of 32 healthy control subjects were examined with high-resolution anterior segment SD-OCT (MS-39; CSO, Florence, Italy). Various epithelial thickness and epithelial wavefront derived terms were compared between groups and receiver operating characteristic (ROC) curves were computed to analyze the diagnostic capacity of the respective parameters. A total of 17 of 32 EBMD patients underwent treatment with phototherapeutic keratectomy (PTK) and were followed up for 3 months. Results: Epithelial thickness variance (60.4 ± 56.7 µm versus 7.6 ± 6.1 µm) and interquartile range (11.0±6.9 versus 3.3±1.9 µm) were markedly elevated in EBMD patients as compared with healthy controls (both with p < 0.001). Epithelial wavefront analysis showed a highly statistically significant excess in all examined aberration terms in EBMD patients (all with p < 0.001). Significantly greater areas under the curve (AUC) were yielded by the epithelial wavefront derived parameters (e.g. total epithelial wavefront error: AUC = 0.966; 95% confidence interval (CI) 0.932 – 1) than by the epithelial thickness-derived parameters (e.g., variance: AUC = 0.919; 95% CI 0.848 – 0.990). Conclusion: Corneal epithelial wavefront aberrometry proved valuable as an objective biomarker for EBMD with high sensitivity and specificity. PTK resulted in a reduction of morphological and refractive epithelial irregularities in EBMD.

Community Acquired Urinary Tract Infections account for 15% of all outpatient use of antibiotics, women are primarily affected; major causative microorganisms are uro-pathogenic E. Coli. Treatment is indicated for cystitis and pyelonephritis and includes B-lactams (amoxicillin-clavulanic acid or third generation cephalosporins), fluoroquin-olones (ciprofloxacin or levofloxacin), nitrofurantoin, fosfomycin, and trime-thoprim-sulfamethoxazole. Resistance to antibiotic treatment is of concern, several mecha-nisms have been associated with the acquisition of genes that confer antimicrobial re-sistance to fluoroquinolones, which often are associated with other patterns of resistance, especially in extended spectrum beta lactases (ESBL) producers. Several studies have ad-dressed the prevalence of uropathogens producing ESBL, but only a few have focused on resistance against fluoroquinolones and to our knowledge, none has been addressing the prevalence of isolates mutations that confer antimicrobial resistance to fluoroquinolones. The focus of the present review was to analyze recent published papers that describe the E. coli phylotype causing community acquired UTIs in association to fluoroquinolones re-sistance.

In computer vision, human action recognition is a hot topic, popularized by the development of deep learning. Current models have achieved high accuracy results on public datasets. Despite this success, they require significant computational resources for training. Given that transfer learning based techniques allow reusing what other models have already learned and training models with less computational resources, in this work we propose using a transfer learning based approach for action recognition in videos. We describe a methodology for human action recognition using transfer learning techniques in a custom dataset. The proposed method consists of four stages: 1) human detection and tracking, 2) video preprocessing, 3) feature extraction (using pretrained models with ImageNet), and 4) action recognition using a two-stream model consisting of TCNs, LSTMs, and CNNs layers. The custom dataset is imbalanced with 189, 390, 490, 854, and 890 videos per class, respectively. For feature extraction, we analyzed the performance of seven pretrained models: Inception-v3, MobileNet-v2, MobileNet-v3-L, VGG-16, VGG-19, Xception, and ConvNeXt-L. We show that the best results were obtained with the last one. Finally, using pretrained models for feature extraction allowed training in a PC with a single GPU with an accuracy of 94.9%.

The Sarcoma Assessment Measure (SAM) was developed as a sarcoma-specific patient-reported outcome measure to be used in clinical practice. We have reported in detail how SAM has been developed in collaboration with patients and healthcare professionals. The aim of this paper is to report the preliminary validation of SAM. The 22-item SAM was administered alongside a validated quality of life questionnaire and measure of activities of daily living. Linear modelling was used to build a measure, which had predictive validity in comparison to more established outcome measures. Of the 762 patients who participated in the study, 44.1% identified as male, and participant age ranged from 13-82 years. Clinically, participants presented with a range of soft tissue (82.2%) and bone (21.8%) sarcomas. Our preliminary analysis indicates that SAM accounts for 35% of the Global quality of life scale and 18% of the TESS so psychometrically it overlaps with quality of life and activities of daily living, but also measures distinct concerns. This demonstrates that this measure picks up issues that are important to patients with sarcoma that are not reflected in other measures. We have established the preliminary validity of SAM and believe it has utility as a patient-reported outcome measure both as a research tool and for assessing the impact of symptoms and dysfunction related to sarcoma as part of clinical care. Further validation using a larger and more clinically diverse sample is now needed.

Commonwealth Partnerships for Antimicrobial Stewardship (AMS) uses a health partnership model to establish AMS in Commonwealth countries. The University Hospital of Kwame Nkrumah University of Science and Technology in partnership with Ulster University, in Northern Ireland undertook an AMS project from November 2021 to May 2022. We report on the implementation and its effect on antibiotic use and infections management at the University Hospital. The Global-Point Prevalence Survey (PPS) protocol was used to assess antibiotics use at the hospital at the beginning, midpoint and end of the project. Feedback on each PPS was given to staff to inform behaviour change and improve antibiotic prescribing. Antibiotic use reduced from 65% at baseline to 59.7% at the end of the project. The rate of health-associated infections also reduced from 17.5% at baseline to 6.5%. In addition, the use of antibiotics belonging to the WHO Access group at the hospital was 40% initially but increased to 50% at the project endpoint. Culture and antibiotic susceptibility requests increased from the beginning of the project from 111 total requests to 330 requests over 7 months. The AMS model implemented improved antibiotic use as well as requests for culture and susceptibility test which must be sustained.

Coronavirus disease 2019 (COVID-19) has detrimental multi-system consequences. Symptoms may appear during the acute phase of infection, but literature on long-term recovery of young adults after mild-to-moderate infection is lacking. Heart rate variability (HRV) allows observation of autonomic nervous system (ANS) modulation post SARS-CoV-2 infection. Additionally, physical activity (PA) helps improve ANS modulation, where investigation of PA influence on ANS recovery is vital to reduce risk and severity of symptoms. Clinicians may use this research to aid development of non-medication interventions. At baseline, 18 control (CT) and 20 post-COVID-19 (PCOV) participants were observed where general amnamnesis was performed, followed by HRV and PA assessment. 10 CT and 7 PCOV subjects returned for follow-up (FU) evaluation 6 weeks after complete immunization (2 doses) and assessments were repeated. Over the follow-up period, decrease in sympathetic (SNS) activity (mean heart rate: p=0.0024, CI=-24.67- -3.26; SNS index: p=0.0068, CI=-2.50- -0.32) and increase in parasympathetic (PNS) activity (mean RR:p=0.0097, CI=33.72-225.51; PNS index: p=0.0091, CI=-0.20-1.47) were observed. At follow-up, HRV was not different between groups (p>0.05). Additionally, no differences were observed in PA between moments and groups. This study provides evidence of ANS recovery after SARS-CoV-2 insult in young adults over a follow-up period, independent of changes in PA.

Hospital readmission within 30 days of discharge (30-day readmission) is a high-priority quality measure and cost target. The purpose of this study was to explore the feasibility and efficacy of the Diabetes Transition of Hospital Care (DiaTOHC) Program on readmission risk in high-risk adults with diabetes. This was a non-blinded pilot randomized controlled trial (RCT) that compared usual care (UC) to DiaTOHC at a safety-net hospital. The primary outcome was all-cause 30-day readmission. Between 10/16/2017 and 05/30/2019, 115 patients were randomized. In the intention-to-treat (ITT) population, 14 (31.1%) of 45 DiaTOHC subjects and 15 (32.6%) of 46 UC subjects had a 30-day readmission (p=0.88) while 35.6% DiaTOHC and 39.1% UC subjects had a 30-day readmission or ED visit (p=0.72). The Intervention:UC cost ratio was 0.33 (0.13-0.79)95%CI (p<0.01). Among the 69 subjects with baseline HbA1c >7.0% (53 mmol/mol), 30-day readmission rates were 23.5% (DiaTOHC) and 31.4% (UC, p=0.46) and composite 30-day readmission or ED visit rates were 26.5% (DiaTOHC) and 40.0% (UC, p=0.23). In this subgroup, the Intervention:UC cost ratio was 0.21 (0.08-0.58)95%CI (p=0.002). The DiaTOHC Program is feasible and may decrease combined 30-day readmission/ED visit risk as well as healthcare costs among patients with higher HbA1c levels.

Abstract: Ambulatory cancer centers face fluctuating patient demand and deploy specialized personnel who have variable availability. This undermines operational stability through misa-lignment of resources to patient needs, resulting in overscheduled clinics, budget deficits, and wait times exceeding provincial targets. We describe deployment of a Learning Health System framework for operational improvements within the entire ambulatory center. Known methods of value stream mapping, operations research and statistical process control were applied to achieve organizational high performance that is data-informed, agile and adaptive. We transitioned from a fixed template model by individual physician to a caseload management by disease site model that is realigned quarterly. We adapted a block schedule model for the ambulatory oncology clinic to align the regional demand for specialized services with optimized human and physical resources. We demonstrated improved utilization of clinical space, increased weekly consistency and im-proved distribution of activity across the workweek. Increased value, represented as the ratio of monthly encounters per nursing worked hours, and increased percentage of services delivered by full-time nurses were benefits realized in our cancer system. The creation of a data-informed demand capacity model enables application of predictive analytics and business intelligence tools that will further enhance clinical responsiveness..

Pulmonary embolism (PE) is one of the leading causes of cardiovascular mortality, therefore new parameters regarding risk stratification are sought after. In patients admitted for acute PE we investigated associations between the initial coagulation impairment, expressed by prothrombin time international normalised ratio (INR), and parameters reflecting PE severity. Furthermore, in-hospital, 30-day and long-term mortality were also evaluated. The analysis included 848 patients who were divided into two groups: with normal INR≤1.2, and elevated INR>1.2 (252 patients, 29.7%). The group with elevated INR presented higher incidence of tachycardia and lower systolic blood pressure, higher CRP, d-dimer, and NT-proBNP. This group presented higher estimated systolic pulmonary artery pressure (49 IQR39-62mmHg vs 43 IQR32-53mmHg, p<0.001) and shorter pulmonary artery acceleration time (65 IQR55-85ms vs 81 IQR63-102ms; p<0.001). Patients with elevated INR had more often a sPESI of 1 or higher (78%vs60%, p=0.003). Cox regression model revealed that age, leukocyte level, SBP, neoplasm, and INR are associated with higher risk of death (p<0.001). Finally, elevated INR was associated with higher in-hospital (13%vs3%; p<0.001), 30-day (19%vs6%; p<0.001), and long-term mortality (p<0.001). Summing up, elevated INR on admission is frequent in patients with PE, reflects worse clinical condition and is related to PE severity and prognosis.

The COVID-19 pandemic is shifting teaching to an online setting all over the world. The Galaxy framework facilitates the online learning process and makes it accessible by providing a library of high-quality community-curated training materials, enabling easy access to data and tools, and facilitates sharing achievements and progress between students and instructors. By combining Galaxy with robust communication channels, effective instruction can be designed inclusively, regardless of the students' environments.

Here we review and describe a set of research priorities to meet present and future challenges posed to farmed animal production that build on progress, successes and resources from the Functional Annotation of ANimal Genomes (FAANG) project.

In 2010, Parties to the Convention on Biological Diversity (CBD) adopted the Strategic Plan for Biodiversity 2011–2020 to address the loss and degradation of nature. Subsequently, most biodiversity indicators continued to decline. Nevertheless, conservation actions can make a positive difference for biodiversity. The emerging Post-2020 Global Biodiversity Framework has potential to catalyze efforts to ‘bend the curve’ of biodiversity loss. Thus, the inclusion of a goal on species, articulated as Goal B in the Zero Draft of the Post-2020 Framework, is essential. However, as currently formulated, this goal is inadequate for preventing extinctions, and reversing population declines; both of which are required to achieve the CBD’s 2030 mission. We contend it is unacceptable that Goal B could be met while most threatened species deteriorated in status and many avoidable species extinctions occurred. We examine the limitations of the current wording and propose an articulation with robust scientific basis. A goal for species that strives to end extinctions and recover populations of all species that have experienced population declines, and especially those at risk of extinction, would help to align actors towards the transformative actions and interventions needed for humans to live in harmony with nature.

Woody vegetation in farmland acts as a carbon sink and provides ecosystem services for local people, but no macro-scale assessments of the impact of management and climate on woody cover exists for drylands. Here we make use of very high spatial resolution satellite imagery to derive wall-to-wall woody cover patterns in tropical West African drylands. In arid and semi-arid Sahel, areas of more people are associated with more trees: mean woody cover is greater in farmlands (12%) than in savannas (6%), and likewise it is higher close to villages than further away. In sub-humid savannas of West Africa, woody cover is generally above 20% and decreases with increasing population density, but remains around 15% in farmlands, independent of rainfall. In the region as a whole, rainfall, terrain and soil are the most important (80%) determinants of woody cover, while management factors play a smaller (20%) role. We conclude that agricultural expansion cannot generally be claimed to cause woody cover losses, and that observations in Sahel contradict simplistic ideas of a high negative correlation between population density and woody cover.

A recent study showed the potential of DA Perten 7200 NIR Spectrometer in detecting chlorpyrifos-methyl pesticide residue in rough, brown, and milled rice. However, this instrument is still lab-based and generally suited for point-of-sale testing in many countries. To provide a field deployable version of this technique, an existing light emitting diode (LED)-based instrument which provide discrete NIR wavelength illumination and reflectance spectra over the range of 850-1550 nm was tested. Spectra were collected from rough, brown, and milled rice at different pesticide concentrations and analysed for quantitative and qualitative measurement using partial least squares regression (PLS) and discriminant analysis (DA). Simulations for LED-based instruments were also evaluated using segments of spectra from the DA7200 to represent LED illumination. For the simulation of the existing LED-based instrument (LEDPrototype1) using their wavelengths range yielded 70.4% to 100% correct classification. Simulation of a second LED instrument, LEDPrototype2, with spectral segments selected based on significant wavelength regions from PLS regressions coefficients obtained from the DA7200 showed improved performance with R2 of 0.59 to 0.82 and correct classifications of 71.3 to 100%. An actual LED based instrument with this capability could provide a quick screening tool to determine if MRLs are exceeded.

In Thailand, thousands of children living with perinatal HIV have been exposed to HIV-related stigma/discrimination but its frequency and expressions have been little studied. Our objective was to assess stigma/discrimination prevalence, associated risks factors and its expressions among adolescents. All caregivers of adolescents aged 12-19 years living with perinatal HIV and receiving antiretrovirals in 20 hospitals throughout Thailand were invited to complete a face-to-face questionnaire on their adolescent’s life and medical history. Of the 572 adolescents living in family settings, 464 had their HIV-status known in the community. The overall stigma/discrimination prevalence was 46%. Factors associated included living in the north-east region (OR: 2.80, 95%CI: 1.19-4.96), having a low intellectual ability (OR:2.68, 95%CI: 1.45-5.16), a lower Body Mass Index (BMI) (OR BMI &gt; 18.5: 0.61, 95%CI: 0.37-0.98), conflicts with caregivers (OR: 1.86, 95%CI: 1.26-2.76) and caregivers being members of a support group (OR: 2.34, 95%CI: 1.58-3.48). Expressions of stigma/discrimination included bullying, social isolation, behavioral discrimination and public disclosure. The prevalence of stigma/discrimination among adolescents living with perinatal HIV is high. Despite existing policies, stigma eradication remains necessary to normalize their life as they grow into adulthood.

Background and Objectives: Down syndrome (DS) is the most common chromosomal disorder in the world. It is caused by the imbalance of the chromosomal constitution of 21, by free trisomy, translocation or mosaicism. Children and adolescents with Down syndrome have immune dysregulation and are more susceptible to infections. This study aims to evaluate hospitalizations of children and adolescents with DS in the pediatric ward of Botucatu Clinics Hospital (HCFMB), to classify the population of children included in the study regarding age, diagnosis, outpatient follow-up, length of stay and need for Intensive Care Unit (ICU). Thus, it will be possible to improve care for these children, aiming to reduce these hospitalizations. Materials and Methods: It was an observational, cross-sectional study, with retrospective data collection from the last 10 years of hospitalization, from January 2013 to December 2021, of children and adolescents with DS, in the pediatric ward, emergency room and ICU of HCFMB. Children hospitalized in this period in the pediatric ward and ICU, in the age range of 30 days to 15 years (age of acceptance for admission to this service) were included in this study. Those who at some point had the exclusion of the diagnosis of DS were excluded. The evaluation of comorbidities that culminated in the need for hospitalization in this population can be the focus of actions to improve diagnoses and conducts for this population, to prevent worsening and hospitalizations in future populations. Results: The statistical analysis of the data was performed. In this analysis, 80 children with DS were evaluated, with a total of 283 hospitalizations and it was noticed that 46 of them had more than one hospitalization in this period. The most prevalent age group was 1 to 3 years, and the main cause was due to problems in respiratory system (99 cases). Among respiratory causes, the main cause of hospitalization was due to pneumonia, in 50% of cases, followed by acute respiratory failure, in 14%. The average hospitalization time was 8 days and in 49 hospitalizations the children required the ICU. The main cause of hospitalization in the ICU was due to respiratory causes (36%), followed by cardiac malformations (14%). During the ICU hospitalizations, there were 13 deaths, and we observed a higher prevalence of heart conditions and, in some cases, positive urine cultures in these children. Conclusions: preventive actions, such as vaccinations and improved monitoring of these children, without outpatient follow-up or during hospitalization, should be carried out. Thus, it has been developed a proposal for a risk score for mortality in children and adolescents with DS admitted to the ICU, and those patients with five or more points should be monitored more closely. A meeting will be held with the genetics, cardiology, and pediatric ICU teams to discuss this score and propose a surveillance plan for these patients at the HCFMB and potentially for the pediatric community in the future.

Chronic kidney disease (CKD) is a progressive condition that affects more than 10% of the world's population. Monitoring urine albumin and creatinine ratio (µACR) has become the gold standard for nephropathy diagnosis and control. The objective of the present study was to develop a simple, accurate, sensitive, and rapid point-of-care test (PoCT) device - MYμALBUMIN that community healthcare professionals can use in resource-limited facilities and by patients in their own homes for screening the risk and monitoring the progress of CKD. Albumin and creatinine concentrations in urine samples were determined using spectrophotometric dye (tetrabromophenol blue)-binding and colorimetric Jaffe’assay, respectively. Urine samples were diluted with distilled water (1:80) and mixed separately with albumin and creatinine reaction mixture. The creatinine reaction was incubated at room temperature (25oC) for 30 minutes before analysis. Optical density (OD) was measured at the wavelengths of 625 nm (albumin) and 515 nm (creatinine). All calibration curves (2-60 mg/L and 0.25-2 mg/dL for albumin and creatinine) yielded linear relationships with correlation coefficients (r2) of &gt; 0.999. Good accuracy (%DMV &lt; + 2.88%) and precision (%CV &lt; 3.0%) were observed from both the intra- or interday assays for the determination of albumin and creatinine by MYµALBUMIN. The limit of quantification (LOQ) of albumin and creatinine in urine samples determined by MYµALBUMIN and laboratory spectrophotometer were 2 mg/L and 0.1 mg/dL, respectively, using 37.5 μL urine samples. The device was well applied with clinical samples from 13 CKD patients. The median (range) of %DMV of the central (hospital) laboratory method (immune-based assay) was 3.18 (-10.11 to 14.12)%, with a high correlation coefficient (r2 &gt;0.99). In conclusion, MYμALBUMIN showed satisfactory test performance in terms of accuracy, reproducibility, sensitivity, and specificity. The device would have significant economic benefits besides obviously improving clinical decision-making processes.

Recent studies, typically using patient cerebrospinal fluid (CSF), have suggested that different autoantibodies (Aabs) acting on their respective receptors, may underlie neuropsychiatric disorders. The NR1 subunit of the N-methyl-D-aspartate receptor (NMDAR) has been identified as a target of anti-NMDAR Aabs in a number of central nervous system (CNS) diseases including encephalitis and autoimmune epilepsy. However, the role or the nature of Aabs responsible for effects on neuronal excitability and synaptic plasticity is yet to be established fully. Patient-derived anti-NMDAR Aabs have been shown to bind to specific regions within the NR1 subunit; here, peptide immunisation was used to generate Aabs against selected specific NR1 extracellular sequences. ‘Protein A’ purification was used to obtain total IgG and further peptide purification used to obtain a greater percentage of NMDAR-target specific IgG Aabs. Binding and specificity of these anti-NMDAR Aabs was determined using a range of methodologies including enzyme-linked immunosorbent assay, immunocytochemistry and immunoblotting. Functional effects were determined using different in vitro electrophysiology techniques: two-electrode voltage-clamp in Xenopus oocytes and measures of long-term potentiation (LTP) in ex vivo hippocampal brain slices using multi-electrode arrays. We show that anti-NMDAR Aabs generated from peptide immunisation had specificity for NR1 immunisation peptides as well as target-specific binding to the native protein. Anti-NMDAR Aabs had no clear effect on isolated NMDARs in an oocyte expression system. However, we show that peptide-purified anti-NMDAR Aabs prevented the induction of LTP at Schaffer collateral-CA1 synapses in ex vivo brain slices. Our data demonstrate that anti-NMDAR Aabs cause synaptic NMDAR hypofunction at a network level. This work provides a solid basis to address outstanding questions regarding anti-NMDAR Aabs mechanisms of action and, potentially, development of therapies against CNS diseases.

The effectiveness of simple weirs and the ability of rural farmers to construct durable weirs are still areas of concern in rural areas in Zambia. The objective of this study is to investigate the factors contributing to the varying levels of durability of the simple weir structures used for the diversion of river flows. This study was conducted in 5 districts where 33 SWs located in similar geographical zones were analyzed for their longevity. The research delved into catchment and climatic variables, and the social and psychological perception of simple weirs. The study conducted interviews with key informants who were familiar with the use of SWs in 5 districts in Muchinga provinces between 26 December 2023 and 15 January 2024 using semi-structured questions. The findings of this study indicated that simple weirs constructed on relatively square-shaped catchments and narrow-shaped catchment areas were less vulnerable to damage and easy to operate and maintain. The study also found that climatic factors such as storm rainfall events had little impact on the operation and maintenance of these weirs in Muchinga province, as most sites are in the rainfall shadow while farmers` views about the structures varied from site to site. Overly, planning is necessary for implementing small or large irrigation structures.

Leaf mass per area (LMA) is a key structural parameter that reflects the functional traits of leaves and plays a vital role in simulating the material and energy cycle of plant ecosystems. In this study, vertical whorl-by-whorl sampling of LMA was conducted in a young Larix principis-rupprechtii plantation during the growing season at the Saihanba Forest Farm. The vertical and seasonal variations in LMA were analysed. Subsequently, a predictive model of LMA was constructed. The results revealed that the LMA varied significantly between different crown whorls and growing periods. In the vertical direction of the crown, the LMA decreased with increasing crown depth, but the range of LMA values from the tree top to the bottom was, on average, 30.4 g/m2, which was approximately 2.5 times greater in the fully expanded phase than in the early leaf-expanding phase. The LMA exhibited an allometric growth trend that increased during the leaf-expanding phase and then tended to stabilize. However, the range of LMA values throughout the growing period was, on average, 40.4 g/m2. Among the univariate models, the leaf dry matter content (LDMC) performed well (Ra2=0.45, RMSE=13.48 g/m2) in estimating the LMA. The correlation between LMA and LDMC significantly differed at different growth stages and at different vertical crown whorls. The dynamic predictive model of LMA constructed with the RDINC and DOY as independent variables was reliable in both the assessments (Ra2=0.68, RMSE=10.25 g/m2) and the validation (MAE=8.05 g/m2, FI=0.682). Dynamic simulations of crown LMA provide a basis for elucidating the mechanism of crown development and laying the foundation for the construction of an ecological process model..

The technical feasibility of solar photovoltaic (PV) direct current (DC) nanogrids are well-established, but the components of nanogrids are primarily commercially focused on alternating current (AC)-based systems. Thus, DC converter-based designs at the system level require personnel with high degree of technical knowledge and this results in high costs. To enable a democratization of the technology by reducing the costs this study provides a novel modular plug-and-play open source DC nanogrid. The system can be customized according to consumer requirements, enabling the supply of various voltage levels to accommodate different device voltage needs. The step-by-step design process of the converter, controller, data logger, and assembly of the complete system is provided. A time-domain simulation and stability analysis of the designed system were conducted in MATLAB/Simulink as well as experimental validation. The results show transforming the nanogrid from a distribution network to a device makes it suitable for various user-specific applications, such as remotely supplying power to campsites, emergency vehicles like ambulances, and small houses lacking grid electricity. The modular DC nanogrid includes all the features available in a DC distribution network as well as data logging, which enhances the user experience and promotes the use of solar-powered DC grid systems.

Ondol, a heating system unique to Korean homes, raises indoor temperatures by supplying hot water through pipes embedded in the floor slab. Known for its comfort and sustained heat advantages, Ondol has garnered international interest in countries requiring efficient heating solutions. Given the inherent challenges during installation and operation, timely inspection is crucial due to difficulties in detecting and pinpointing defects in the buried concrete pipes, often leading to costly rework and removal. Yet, specialized inspection systems tailored for Ondol pipes remain underexplored. Therefore, this study proposes a robotic inspection system capable of assessing the condition of Ondol pipelines. We analyzed the characteristics of Ondol piping to establish the system requirements and developed a prototype of a compact capsule-shaped inspection robot tailored for Ondol pipe inspection. Subsequent laboratory testing validated its performance and usability, confirming its capability for field application through tests on curvature maneuverability and image reception quality. This research aims to motivate advancements in Ondol-specific system implementation and performance validation, potentially contributing to the smartification of Ondol maintenance practices.

Introduction: Urological conditions significantly impact global health, with increasing demand for urologists in both developed and developing countries. Disparities in access to surgical care between high-income countries (HICs) and low- and middle-income countries (LMICs) are evident. Despite advancements in urology, LMIC training programs often follow outdated curricula and traditional methods. Methodology: A comprehensive search strategy identified urology training programs in LMICs using the EduRank website, Google searches, and PubMed. Data were collected from literature, official documents, and online resources, focusing on variables such as program duration, research requirements, and resident salaries. Results: The analysis revealed significant variability in program structures and requirements across LMICs. Residency training durations ranged from 4 to 6 years, with inconsistent research obligations and resident salaries averaging $12,857 annually, with a range from 5,412 to 18,174$. Fellowship opportunities were limited, with only a small number of programs achieving international accreditation. Conclusion: The study highlights substantial disparities in urology training between HICs and LMICs. There is an urgent need for standardized and locally tailored training frameworks to enhance the quality of urology education in LMICs. Future research should focus on developing strategies to improve training opportunities, ensuring equitable access to advanced urological care and education globally.

Global climate change primarily affects the spatiotemporal variation of physical quantities such as relative humidity, atmospheric pressure, ambient temperature, and notably, precipitation levels. Accurate precipitation predictions remain elusive, necessitating tools for detailed spatiotemporal analysis to better understand climate impacts on the environment, agriculture, and society. This study compares three learning models: ARIMA (Autoregressive Integrated Moving Average), RF-R (Random Forest Regression), and LSTM-NN (Long Short-Term Memory Neural Network), utilizing monthly precipitation data (in millimeters) from 757 locations in Boyacá, Colombia. The LSTM-NN model outperformed others, precisely replicating precipitation observations in both training and testing datasets, significantly reducing the root mean square error (RMSE) with average monthly deviations of approximately 19 mm per location. Evaluation metrics (RMSE, MAE, R², MSE) underscore the LSTM model’s robustness and accuracy in capturing precipitation patterns. Consequently, the LSTM model was chosen to predict precipitation over a 16-month period starting from August 2023, offering a reliable tool for future meteorological forecasting and planning in the region.

Art therapy fosters emotional healing and growth. This process can offer healthcare professionals (HCPs) novel insights into patients’ medication experiences. We developed a Metaverse Art Gal-lery of Image Chronicles (MAGIC), which depicted patients’ medication experiences symbolically as hero-villain portrayals. This gallery aimed to enhance healthcare students’ learning through re-latable insights into patients’ medication therapies. A character sheet was used to craft patients’ personifications of their medication experiences. ChatGPT, NightCafe, Canva, HeyGen and Cam-tasia were used to generate hero-villain portraits based on the character traits and mounted in MAGIC, which consisted of three virtual realms, each with a unique theme. Alpha-testing among sixteen Generation Z healthcare learners indicated that the content in MAGIC enabled them to understand the concepts of medication adherence (93.7%), art therapy (87.5%) and how patients related to their medications (81.3%). Perceived playfulness (rs=0.925, p

Assessing observation noise is a critical step in the development of a stochastic model for GNSS navigation and positioning. This process ensures that the statistical properties of the observational data are accurately characterized, leading to more reliable and precise positioning results. Traditionally, the one sigma values for observation noise, 0.3 m for code and 3 mm for carrier phase, alongside elevation-dependent weighting schemes, have been standard. However, these may no longer be suitable due to significant advancements in GNSS systems, receivers, and antennas. Previous research predominantly focused on code type and PPP techniques, often limited by the inability to separately assess observation types across different frequency bands due to ionospheric delay. Furthermore, these studies were generally constrained by limited experimental data. This research advocates for the use of ultra-short baselines to eliminate atmospheric delay and other error sources, providing a detailed assessment of observation noise for various frequency bands, GNSS systems, and receiver & antenna types over an extensive period and across multiple baselines. The findings suggest a need to reconsider traditional one sigma values and elevation-dependent weighting schemes for current applications.

(1) Background: Alzheimer’s disease (AD) presents a significant challenge in terms of discovering novel diagnostic methods and therapies. Previous research has shed light on the neuroprotective properties of Apelin-13 in neurodegenerative disorders. However, elucidating the mechanism underlying its efficacy in combating AD-related nerve injury is imperative. In this study, we aimed to investigate the mechanism of action of Apelin-13 in an in vivo model of AD induced by streptozocin (STZ); (2) Methods: We utilized an STZ-induced nerve injury model of AD in mice to investigate the effects of Apelin-13 administration. The Apelin-13 was administered intranasally, and cognitive impairment was assessed using standardized behavioral tests. The main methods included behavioral assessment, histological analysis, and biochemical assays to evaluate synaptic plasticity and oxidative stress signaling pathways; (3) Results: Our findings indicate that intranasal administration of Apelin-13 ameliorated cognitive impairment in the STZ-induced AD model. Furthermore, we observed that this effect was potentially mediated through the enhancement of synaptic plasticity and attenuation of oxidative stress signaling pathways; (4) Conclusions: The results of this study suggest that intranasal administration of Apelin-13 holds promise as a therapeutic strategy for preventing neurodegenerative diseases such as AD. By improving synaptic plasticity and mitigating oxidative stress, Apelin-13 may offer a novel approach to neuroprotection in AD and related conditions.

Isothermal Nucleic Acid Amplification based-Lateral Flow Testing (INAA-LFT) has emerged as a robust technique for on-site pathogen detection, providing a visible indication of pathogen nucleic acid amplification that rivals or even surpasses the sensitivity of real-time quantitative PCR. The isothermal nature of INAA-LFT ensures consistent conditions for nucleic acid amplification, establishing it as a crucial technology for rapid on-site pathogen detection. However, despite its considerable promise, the widespread application of isothermal INAA amplification-based lateral flow testing faces several challenges. This review provides an overview of the INAA-LFT procedure, highlighting its advancements in detecting plant viruses. Moreover, the review underscores the imperative to address existing limitations and emphasizes ongoing research efforts dedicated to enhancing the applicability and performance of this technology in the realm of rapid on-site testing.

Developing effective trend estimators is a main method to solve the online portfolio selection problem. Although the existing portfolio strategies have demonstrated good performance through the development of various trend estimators, it is still challenging to determine in advance which estimator will yield the maximum final cumulative wealth in online portfolio selection tasks. This paper studies an online ensemble approach for online portfolio selection by leveraging the strengths of multiple trend estimators. Specifically, a return-based loss function and a cross-entropy-based loss function are first designed to evaluate the adaptiveness of different trend estimators in a financial environment. On this basis, a passive aggressive ensemble model is proposed to weigh these trend estimators within a unit simplex according to their adaptiveness. Extensive experiments are conducted on benchmark datasets from various real-world stock markets to evaluate the performance. The results show that the proposed strategy achieves the state-of-the-art performance including efficiency and cumulative return.

Many agonists for the estrogen receptor are known to disrupt endocrine functioning. We have developed a computational model that predicts agonists for the estrogen receptor ligand-binding domain in an assay system. Our model was entered into the Tox21 Data Challenge 2014, a computational toxicology competition organized by the National Center for Advancing Translational Sciences. This competition aims to find high-performance predictive models for various adverse-outcome pathways, including the estrogen receptor. Our predictive model, which is based on the random forest method, delivered the best performance in its competition category. In the current study, the predictive performance of the random forest models was improved by strictly adjusting the hyperparameters to avoid overfitting. The random forest models were optimized from 4,000 descriptors simultaneously applied to 10,000 activity assay results for the estrogen receptor ligand-binding domain, which have been measured and compiled by Tox21. At this time, our model delivers the highest predictive power on estrogen receptor agonists in the world. Furthermore, analysis of the optimized model revealed some important features of the agonists, such as the number of hydroxyl groups in the molecules.

Dyslipidemia presents high levels of serum cholesterol, being characterized as a risk factor for cardiovascular diseases, especially for the development of atherosclerosis. E. oleracea (OFEO), A. esculentus (OFAE), B. orellana (OFBO) and granulated (CHR) oils are rich in bioactive compounds with potential to treat changes in lipid metabolism. This study investigated the effects of treatments with oils from A. esculentus, E. oleracea, B. orellana and granules (Chronic SM®) on saturated fat-induced dyslipidemia Cocos nucifera L. The chromatographic profile showed the majority of unsaturated fatty acids in the tested oils. The quantification of tocotrienols and geranylgeraniol was obtained in OFBO and CHR. Treatments with OFEO, OFAE, OFBO and CHR were able to significantly reduce glycemia with p&gt;0.001, as well as hypertriglyceridemia, total cholesterol and LDL-cholesterol, in addition to increasing HDL-cholesterol. The treatments inhibited the formation of atheromatous plaques in the vascular endothelium of the treated rats. The obtained results suggest that the OFEO, OFAE, OFBO and CHR groups have antidyslipidemic effects and antiatherogenic activity.

This study investigates the fabrication and optimization of Co-Fe-P catalysts on Cu foam using electroless deposition, focusing on their hydrogen generation efficiency. Deposition times were varied from 1 to 10 minutes, resulting in spherical Co-Fe-P particles growing from sub-micron to several microns in size. The optimal hydrogen generation rate of 27.66 ml/min was achieved with a 5-minute deposition. Extending the deposition to 10 minutes led to particle aggregation, reducing the efficiency per unit weight. The impact of bath temperatures from 30°C to 60°C was also assessed, with temperatures of 50°C and above promoting the development of larger 3D structures and increasing Fe and P contents (~9.3 wt.% and 10 wt.%). This enhanced hydrogen generation, peaking again at 27.66 ml/min. NaOH concentrations were varied from 0.5 M to 0.9 M, showing that concentrations over 0.8 M improved catalyst morphology and performance, increasing hydrogen generation to 10.03 ml/min. Among substrates tested, Co-Fe-P on Cu foam demonstrated the highest hydrogen generation rate due to better catalyst distribution and surface area. The study underscores the importance of deposition conditions and substrate choice in optimizing Co-Fe-P catalysts for hydrogen generation.

Let S be a Fermat surface of degree 5 and let k be an algebraically closed field of characteristic p = 2. We give a fibration ƒ: S → P with upper limit 1 and lower limit k, and investigate the geometric properties of fiber of ƒ. Furthermore, we investigate the fibration-preserving automorphisms group Aut_{Pwith upper limit 1 and lower limit k}(S) of ƒ. We obtain that Aut_{Pwith upper limit 1 and lower limit k}(S) is a p-group of order 256.

Digital weight-loss services (DWLSs) combining pharmacotherapy and health coaching have the potential to make a major contribution to the global struggle against obesity. However, there is currently no evidence to counter the widespread concern that these services enable large numbers of unsuitable patients to obtain Glucagon-like peptide-1 receptor agonists (GLP-1 RA). This study retrospectively analysed the rate at which the partner pharmacy network of Australia’s largest DWLS provider committed GLP-1 RA dispensing errors over a 6-month period. The analysis found that 191 (0.14%) of the 135131 dispensed Semaglutide orders contained an error. Non-compliant dose escalation (44.5%) and dispatch errors (32.5%) were the two most common error types. Most errors (89%) were deemed to have been of medium urgency, with 6.8% considered high urgency. A disproportionate number of high urgency cases were from wrong medication (31%) and general complaint errors (15%). A Chi-square test revealed a statistically higher dispensing error rate among orders to female patients (0.16%) compared to males (0.076%). The results lay an important foundation in digital pharmacy literature and suggest that comprehensive DWLSs have the potential to safely collaborate with third-party pharmacies in dispensing GLP-1 RAs.

In these days of information overload and high-throughput analysis, it is easy to lose focus on the study of individual proteins. It is our conjecture that such investigations are still crucially important and offer uniquely penetrative insights. We thus present a discussion of biophysical methods to allow readers to get to know their protein of interest better. Although this perspective is not written with the expert in mind, we hope that for interdisciplinary scientists, or researchers who do not routinely perform biophysical analyses, the content will be helpful and inspiring.

We examine the impact of temperature (T) on the Seebeck coefficient S, i.e., the T dependence of S for the single-component molecular conductor Pd(dddt)_2] (dddt = 5,6-dihydro-1,4-dithiin-2,3-dithiolate) with a half-filled band, where the coefficient is obtained from a ratio of the thermal conductivity to the electrical conductivity. The conductor exhibits Dirac electrons with a nodal line, which shows the energy variation around the chemical potential and the density of states (DOS) with a minimum. Using a three-dimensional tight-binding (TB) model in the presence of both impurity and electron--phonon (e--p) scatterings, we study the Seebeck coefficient S_y for the molecular stacking and the most conducting direction. The impact of T on S_y exhibits a sign change, where S_y > 0 with a maximum at high temperatures and S_y < 0 with a minimum at low temperatures. The T dependence of S_y suggests that the contribution from the conduction (valence) band is dominant at low (high) temperatures.The result is examined using a spectral conductivity \sigma_y(\epsilon,T) as a function of the energy $\epsilon$ close to the chemical potential \mu. Further, the Seebeck coefficients for perpendicular directions (x and z) are examined, to show both S_x and S_z being positive and no sign change in contrast to S_y.

We investigate emergent conductive phenomena triggered by collinear antiferromagnetic orderings. We show that an up-down-zero spin configuration in a triangle cluster leads to linear and nonlinear spin conductivities even without the relativistic spin–orbit coupling; the linear spin conductivity is characterized by the Drude-type one, while the nonlinear spin conductivity is characterized by the Hall-type one. We demonstrate the emergence of both spin conductivities in the breathing kagome system consisting of a triangle cluster. The nonlinear spin conductivity becomes larger than the linear one when the Fermi level lies near the region where a small partial band gap opens. Our results indicate that collinear antiferromagnets with the triangle geometry give rise to rich spin conductive phenomena.

Computational animation of spatiotemporal models for 3-D shape and motion is considered as core of dynamic real-time vision. This is based on sets of features evaluated from multi-focal image streams. Subjects are defined as special objects capable of sensing environmental parameters and of initiating own actions in combination with stored knowledge. Object/subject recognition and scene understanding are achieved on different levels. Multiple objects are tracked individually for perceiving their actual state (‘here and now’). Fast saccadic jumps in gaze direction allow flexible concentration on objects or parts of actual interest. By analyzing motion of relevant objects/subjects over a larger time scale on the level of state variables and documenting them in the ‘scene tree representation’ (computer graphics), the situation with respect to decision making is assessed. Various behavioral capabilities of subjects are represented on an abstract level for characterizing their potential behaviors. These are generated by stereotypical feed-forward and feedback control applications on a separate level close to the actuator hardware with corresponding methods. This dual representation on one level for decision making and one on the implementation level allows for flexibility and easy adaptation or extension. Results are shown for road vehicle guidance based on three cameras on a gaze-controlled platform.

The emergence of decentralized finance (DeFi) signifies a fundamental change in the financial sector, utilizing blockchain technology to revolutionize conventional financial structures. This study aims to investigate the development, underlying principles, and practical applications of DeFi while analyzing the regulatory factors, upcoming patterns, and policy consequences. This study employs a thorough research methodology encompassing a literature review and case studies to examine the fundamental elements, uses, and instances of success in DeFi. It emphasizes the potential for transformation and the obstacles it faces. The study identified legal ambiguity, difficulties in achieving scale, and constraints related to compliance as primary concerns for policymakers. The fundamental discoveries encompass the pivotal function of blockchain technology in facilitating DeFi platforms, the tangible implementations of DeFi in lending, borrowing, and trading, and the necessity for clear regulations and global cooperation. The policy implications encompass the significance of maintaining a balance between innovation and compliance, promoting international collaboration, and prioritizing consumer protection measures. In summary, this study enhances our comprehension of the emergence of DeFi and its consequences for conventional finance. It offers valuable insights for policymakers, industry participants, and scholars in effectively navigating the changing realm of decentralized finance.

First, this paper broaches the epistemological status of scientific tenets and approaches: phenomenological (descriptive only), well-founded (solid first principles, conducive to deep understanding), provisional (can be falsified if universal and verified if existential), and imaginary (fictitious entities or processes, conducive to empirically unsupported beliefs). The ΛCDM “concordance model” involves such beliefs: the emanation of the universe out of a non-physical stage, cosmic inflation (invented ad hoc), Λ (fictitious energy), and exotic dark matter. Big Bang cosmology further faces conceptual and pragmatic problems in delimiting what expands from what does not. The problems dissolve after untying inertia from space. The cosmology that emerges appears immediately compatible with the considered observations and the ‘perfect cosmological principle’. Waves and field perturbations that propagate at c expand exponentially with distance (a gravitational effect). The cosmic web of galaxies does not. Potential -Φ varies as H/(cz) instead of 1/r. Inertial forces arise from the gravitational action of the rest of the universe. Due to dilatation, they are reduced disproportionately at low accelerations. A cut-off value a₀ = 0.168 cH is deduced. This explains the successful description of galaxy rotation curves by MoND. A fully elaborated physical theory is still pending. Wider implications are briefly discussed.

A new bisthiourea compound, 1,3,1',3'-(dinaphthalene-1,8-diyl)bisthiourea, was synthesized. Its structure was characterized by elemental analysis, FT-IR and 1H-, 13C-NMR and MS spectroscopic techniques.

This study contributes to the Sybil nodes detecting algorithm in Online Social Networks (OSNs). As major communication platforms, online social networks get significantly guarded from malicious activity. A thorough literature review identified various detection and prevention Sybil attack algorithms. Additional exploration of distinct reputation systems and their practical application led to the study’s discovery of machine learning algorithms, i.e., the KNN, Support Vector Machines, and Random Forest algorithms. The study details the data cleansing process for the employed dataset in its process for optimizing the computational demands required to train machine learning algorithms, achieved through dataset partitioning. Such a process led to explaining and analysis of conducting experiments and comparing their results. Such experiments demonstrate the algorithm’s ability to detect Sybil nodes in OSNs (100% accuracy in SVM, 99.6% in Random Forest, and 97% in KNN algorithms); thus concluding by proposing future research opportunities.

This study utilizes a regional numerical weather model incorporating multilayer urban canopy parameterization alongside a building energy model (BEP + BEM) to examine the sensitivity of various urban parameters, including those defining urban materials and building environments, during a real-case heatwave event in the Chicago Metropolitan Area (CMA) in August 2023. The application of local climate zones further refines this analysis. Findings indicate that wall conductivity and ground albedo play significant roles in affecting urban near-surface temperatures. Conversely, alterations in other urban parameters are found to exert minimal influence on near-surface temperatures throughout the heatwave. In terms of building energy consumption, the selection of the target indoor temperature emerges as a pivotal factor. While adjustments in ventilation rates also bear considerable effects, other variables appear to have a subdued impact on energy usage. Additionally, the marginal effect of wall emissivity on energy consumption highlights the intricate balance between different heat transfer mechanisms and the adaptive capacity of building heating and cooling systems.

Fortified human milk is the first choice for preterm infants. Although individualized fortification is recommended, the optimal method for this population remains uncertain. We conducted a comparative study assessing the growth effects of adjusted (AF) and targeted fortification (TF) in extremely low birth weight (ELBW) infants. This single-center, randomized, controlled clinical trial was conducted at a tertiary neonatal unit in Spain. Eligible participants were premature infants with a birthweight <1000g exclusively fed with human milk. A total of 38 patients were enrolled, 15 of them randomised to AF group and 23 to TF group. AF was based on BUN concentration and TF on human milk analysis. The primary outcome was weight gain velocity (g/kg/day).No significant differences were found in weight gain velocity at 28 days, at 36 weeks of postmenstrual age, at discharge nor during intervention. Protein intake was significantly higher in AF group (5.02 g/kg/day vs 4.48 g/kg/day, p= 0.001). No differences were found in lipids, carbohydrates and energy intake; neither in weight z score change between the different time points; nor in length and head circumference growth. Both AF and TF are comparable methods of fortification and provide appropriate growth rate in ELBW infants.

The number of connected IoT devices is increasing significantly due to their many benefits, including automation, improved efficiency and quality of life, and waste reducing. However, these devices have several vulnerabilities that have led to the rapid growth in the number of attacks. Therefore, several machine learning-based Intrusion Detection Systems (IDS) tools have been developed to detect intrusions and suspicious activity to and from a host (HIDS - Host IDS) or, in general, within the traffic of a network (NIDS - Network IDS). The proposed work performs a comparative analysis and an ablative study among recent machine learning-based NIDS to develop a benchmark of the different proposed strategies. The proposed work compares both shallow learning algorithms, such as Decision Trees, Random Forest, Naïve Bayes, Logistic Regression, XGBoost, and Support Vector Machine, and deep learning algorithms, such as DNN, CNN, and LSTM, whose approach is relatively new in the literature. The algorithms are evaluated on the KDD-99, NSL-KDD, UNSW-NB15, and IoT-23 datasets. The results show that the NIDS tools based on deep learning approaches achieve better performance in detecting network anomalies than shallow learning approaches.

Soybean a pulse of considerable nutritional value due to its high protein, fibers and polyunsaturated fatty acid (PUFA) contents, also contains phytoestrogenic compounds that definitely hinder its recommendation for general consumption. Contrarily to ancient times when soybeans were boiled, modern commercial soy-foods can contain up to 150 mg/100g of estrogenic isoflavones. Interestingly, current estimations of isoflavone intake in the literature do not distinguish between the origins of soy-food i.e. home-made or commercial. As a result, the isoflavone exposure in Asian countries may well be over-estimated. This study aims to demonstrate, based on step-by-step monitoring of isoflavones, that traditional and domestic treatments, leveraging isoflavones water-solubility, can indeed significantly reduce their content in soy-foods. Indeed, when compared to commercial foods, the isoflavone contents was found to be 20, 2.6, 4.5 and 9.8 times lower in “home-made” soy-juice, tofu, tempeh and miso, respectively. Additionally, water soaking was found to reduce the isoflavones levels in soy-textured-proteins by more than 70%. Hence, this simple process has the potential to help drastically reduce overall xenoestrogens exposure. This study could serve as a basis for establishing the isoflavones Reference Dose and issuing food safety guidelines.

Background: Glioblastoma remains a challenging brain tumor to treat due to its infiltrative nature. Accurately identifying tumor boundaries during surgery is crucial for successful tumor resection. This study introduces an innovative intraoperative visualization method utilizing a surgical fluorescence microscope to precisely locate tumor cells. The focus of the study is on IR-Glint, a novel preparation comprising Cy7.5-labeled aptamers Gli-233nt and Gli-55_3L specific to human glioblastoma. Methods: The aptamers were modified using molecular modeling and quantum chemical techniques. The effectiveness of the preparation was assessed using flow cytometry and microscopy on primary cultures of human glioblastoma. In vivo studies were conducted on mouse and rabbit models, employing orthotopic xenotransplantation of human brain glioblastoma with various imaging techniques, including PET/CT, in vivo fluorescence visualization, confocal laser scanning, and surgical microscopy. Results: The experiments validated the potential of IR-Glint for intraoperative visualization of glioblastoma using infrared imaging. Surface application of the aptamer-based formulation on the brain allowed clear visualization of the tumor, aiding surgeons in tumor resection. This approach also reduces the dosage required and mitigates potential toxic effects on the patient. Conclusions: This study demonstrates the promising potential of using in-frared dye-labeled aptamers for intraoperative visualization of glioblastoma. By improving surgical treatment outcomes in neurosurgery, this novel approach may pave the way for future advancements in the field.

Introduction: Biliary Atresia (BA) is a common cause of neonatal cholestatic jaundice which, if recognized and treated early, can be life-saving for the infant. If the liver biopsy suggests the presence of BA, exploratory laparotomy is then carried out to confirm the diagnosis, along with the Kasai procedure to provide drainage to the bile secreted by the liver. The purpose of this study is to get a deep dive into all the various imaging modalities that can diagnose BA more effectively and with absolute certitude, thus helping prevent several children from a grave prognosis.Methodology: For the collection of the data, a search was done by two individuals using PubMed, Google Scholar, and Cochrane Library databases for all relevant literature. Each qualifying paper was evaluated independently by two reviewers. Each article was analyzed for the number of patients, their age, procedure modality, complexity of ethology, and incidence of the pre-decided complications. The statistical software packages RevMan (Review Manager, version 5.3), SPSS (Statistical Package for the Social Sciences, version 20), Google Sheets, and Excel in Stata 14 were used to perform the statistical analyses. The data was obtained and entered into analytic software.Results: A total of 39 studies with 3,679 subjects were selected for the study, out of which 7 studies showed sensitivity above or equal to 95%, and an astounding 14 studies showed specificity above 95%. The value of True Positive (TP) was 1280, that of True Negative (TN) was 1817, that of False Positive (FP) was 239, and that of False Negative (FN) was 343. With a confidence interval of 95%, sensitivity, specificity, and positive predictive values were calculated. The sensitivity of Ultrasonography for Biliary Atresia is 0.79, with a CI of 95% in a range of 0.77 to 0.81. The specificity of Ultrasonography for Biliary Atresia is 0.88, with a CI of 95% in a range of 0.87 to 0.90. Conclusion: Even though several radiological techniques at present help to detect BA, USG of the abdomen proves to be an effective diagnostic and a modest screening test for the detection of BA.

Habenaria, a member of Orchidaceae family is the cosmopolitan distributions, which has significant medicinal and ornamental values. Regardless of morphology and molecular data that have been studied in recent times, the phylogenetic relationship is still under debate. Here, we sequenced, assembled, and annotated the whole chloroplast (cp) genome of two species (Habenaria aitchisonii Rchb.f. and Habenaria tibetica Schltr.ex Limpricht) of Habenaria grown on the Qinghai-Tibetan Plateau (QTP), and combined with seven already published cp genomes which may assist to uncover their genomic profiling. The two genomes ranged from 155259-155269 bp in length and both encoded 132 genes, including 86 protein, 38 tRNA and 8 rRNA. In the cp genomes, the tandem repeats (797), SSRs (2195) and diverse loci (3214) were identified. Comparative analyses of codon usage, amino frequency, microsatellite, oligo repeats and transition and transversion substitutions showed similarities among the species. Moreover, we identified 16 highly polymorphic regions with nucleotide diversity above 0.02, which may be suitable for robust authentic barcoding and inferring in the phylogeny of Habenaria species. Among the polymorphic regions, positive selection was significantly exerted on the several genes such as cemA, petA, and ycf1. This may suggest that the important adaptation stratagem for two Habenaria species on the QTP. The phylogenetic relationship displayed that H.aitchisonii and H. tibetica have closer relationship than others and the rest seven species clustered in the other three groups. Our findings also supported the idea that Habenaria could be divided into different sections. This study enriched the genomics resources of Habenaria, which may be helpful for the conservation efforts of these endangered species.

Solid polymer electrolytes and composite polymer electrolytes serve as crucial components in all-solid-state energy storage devices. Structural batteries and supercapacitors present a promising alternative for electric vehicles, integrating structural functionality with energy storage capability. However, despite their potential, these applications are hampered by various challenges, particularly in the realm of developing new solid polymer electrolytes that require more investigations. In this study, novel solid polymer electrolytes and composite polymer electrolytes were synthesized using epoxy resin blends, ionic liquid, lithium salt, and alumina nanoparticles, and subsequently characterized. Among the formulations tested, the optimal system, designated as L70P30ILE40Li1MAl2 and containing 40 wt.% of ionic liquid and 5.7 wt.% of lithium salt, exhibited exceptional mechanical properties. It displayed a remarkable storage modulus of 1.2 GPa and reached ionic conductivities of 0.085 mS/cm at 60°C. Furthermore, a proof-of-concept supercapacitor was fabricated, demonstrating the practical application of the developed electrolyte system.

Fermented foods have long been known to have immunomodulatory capabilities and fermentates derived from the lactic acid bacteria of dairy products can modulate the immune system. We have used skimmed milk powder to generate novel fermentates using Lb. helveticus strains SC234 and SC232 and we demonstrate here that these fermentates can enhance key immune mechanisms that are critical to the immune response to viruses. We show that our novel fermentates SC234 and SC232 can positively impact on cytokine and chemokine secretion, nitric oxide (NO) production, cell surface marker expression, and phagocytosis in macrophage models. We demonstrate that fermentates SC234 and SC232 increase the secretion of cytokines IL-1β, IL-6, TNF-α, IL-27, and IL-10, promote an M1 proinflammatory phenotype for viral immunity via NO induction, decreases chemokine expression of Monocyte Chemoattractant Protein (MCP), increasing cell surface marker expression, and enhance phagocytosis in comparison to their starting material. These data suggest that these novel fermentates have potential as novel functional food ingredients for the treatment, management and control of viral infection.

Automated Machine Learning (AutoML) is revolutionizing how businesses utilize data, making advanced analytics accessible to a broader range of organizations. By automating complex tasks like data preprocessing, model selection, and hyperparameter tuning, AutoML reduces the time and resources needed to develop and deploy machine learning models. This accelerates decision-making and enables quicker responses to market changes. AutoML empowers businesses to build accurate predictive models using sophisticated algorithms, optimizing model performance for reliable insights and better outcomes. A key advantage of AutoML is its accessibility; even organizations without a dedicated data science team can leverage machine learning, reducing technical barriers and democratizing innovation. As businesses grow, AutoML scales to handle larger datasets and more complex problems without extensive manual intervention. AutoML enhances efficiency, accuracy, and scalability, becoming a crucial driver of business innovation and success. The systematic review will examine the bibliometric literature on how AutoML can boost business, analyzing 74 academic and scientific documents from the Scopus database.

The increasing adoption of student-centred learning environs by the institutions of higher education in business, has led to new mechanisms and methodologies such as the Simulation-Based Learning (SBL), Problem-Based Learning (PBL) and Challenge-Based Learning (CBL). Literature has shown evidence of raising interest in these methodologies towards a more experiential paradigm with regard to upcoming events from the surrounding real-world context. This paper presents a Systematic Bibliographic Literature Review (SBLR) with respect to the integration and application of these innovative and collaborative methodologies in higher education. It aimed to identify its relevant advantages, challenges, and consequences for the future of business education. Bibliographic databases were searched for documents published up to May 2024 to categorize key topics discussed in the literature on SBL, PBL and CBL. The review process identified 89 empirical and non-empirical papers on SBL, PBL and CBL, business related paperwork, which resulted from the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) method. PRISMA is a framework with evidence-based data designed to help authors perform a systematic literature review. Data analysis revealed diverse subthemes for those methodologies uses in business higher education institutions. The research questions “What are the advantages, challenges and implications of SBL, PBL and CBL altogether, in the training of business students?” guided the study. The central output of the research is the discovery of the varying uses of SBL, PBL and CBL overall, to cope with diverse demands arising within environmental context. Future research directions are suggested.

Cambodia is a predominantly agrarian society, with a majority of the population residing in rural areas and relying on agriculture for food and income. The primary sources of food for the Khmer society are rice and fish. However, the country faces vulnerabilities due to climate change, natural disasters, impacts of hydropower and infrastructure development, and land grabs, which disrupt food sources and the livelihoods of local communities. Since 2015, the Royal Government of Cambodia (RGC) has been actively promoting rice production for export, resulting in increased rice farming seasons and annual rice production. Despite these efforts, a significant portion of the population still experiences food insecurity. Therefore, this study aims to explore the reasons why food security issues persist despite the government program to increase rice production. The study involves a review of existing literature and an examination of food security in three provinces in the Cambodian Mekong Delta. It concludes that, on the one hand, the increased rice production has increased food availability, but access to and utilization of food have been challenged by indebtedness, increased cost of production and migration, and on the other hand, the rights to foods have been challenged by land crabs, water conflicts, and lack of sectoral integrations of food systems; and compounded by climate change and environmental degradation, which all contribute to food security.

Menin inhibitors are new and promising agents currently in clinical development that target the HOXA/MEIS1 transcriptional program which is critical for leukemogenesis in histone-lysine N-methyltransferase 2A rearranged (KMT2Ar) and in NPM1-mutated (NPM1mut) acute leukemia. The mechanism of action of this new class of agents is based on the disruption of menin-KMT2A complex (constitute of chromatin remodelling proteins), leading to the differentiation and apoptosis of AML cells expressing KMT2A or mutated NPM1. This new class of drugs has been tested alone, or in combination with synergistic drugs, in phase I and II clinical trials (AUGMENT-01 and 02, KOMET-01 and 07, SAVE, COVALENT trial and others), showing promising results in terms of response rates and safety in heavily pre-treated acute leukemia patients. In this review, we summarise the key findings on menin inhibitors, focusing on the mechanism of action and preliminary clinical data of this emerging and promising class of agents, in particular revumenib and ziftomenib.

(1) Background: The rapid expansion of 4G and 5G networks has raised public concerns about potential health risks associated with electromagnetic radiation. This study addresses these fears by investigating electromagnetic measurements in crowded squares, where human exposure is heightened. Despite rigorous scientific methodologies showing generally low levels of radiation from these technologies, public apprehension persists; (2) Methods: We conducted 496 measurements in Larissa's major squares, using a portable field strength analyzer and GIS mapping. Squares were categorized by traffic and population density; (3) Results: Low-traffic squares exhibited exposure ratios consistently below ICNIRP limits, with median values of 0.0012 and 0.00173 in non-active and active mobile phone cases, respectively. In high-traffic squares, the median exposure ratio was 0.00335 in non-active mobile phone cases, remaining below recommended limits; (4) Conclusions: These findings indicate no significant risk of electromagnetic radiation in crowded squares in Larissa, emphasizing the importance of factual communication and dispelling public misconceptions.

Dry intrusion is an important mid-latitude atmosphere phenomenon within the upper troposphere and lower stratosphere. It is always found to be related to the cyclogenesis, rainstorm, as well as convection generation and precipitation enhancement. Since the atmosphere environment for any of these above-mentioned weather is terribly complicated, those preexisting popular schemes which takes no account of water vapor may not suitable for detecting the dry intrusion related to these weathers. With regard to the merits and demerits of the current preexisting schemes, a new scheme based on Fengyun-2E geo-stationary satellite data is presented in this study to detect the atmospheric dry intrusion. The scheme is set up based on the statistical relationship between water vapor at high level troposphere, the general moist potential vorticity, ozone concentration and upper-level jet. After using the total amount of ozone and ozone profile operational products retrieved by Fengyun-3 Polar Orbiting Meteorological Satellites and the potential vorticity calculated by ECMWF Interim data for validation, this scheme is applied to analyze two typical middle-latitude weather processes. One is the famous Beijing extreme rainfall of 21 July 2012 and the other is a hailstorm occurred on the eastern China during March 19, 2014. A good application effect in both cases suggests that our new method of detecting dry intrusion is feasible and can be helpful in middle-latitude disastrous weather monitoring and forecasting.

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

Accurate prostate volume estimation is crucial for effective prostate disease management. Ultrasound (US) imaging, particularly transrectal ultrasound, offers a cost-effective and rapid assessment. However, US images often suffer from artifacts and poor contrast, making prostate volume estimation challenging. This review explores recent advancements in deep learning (DL) techniques for automatic prostate segmentation in US images as a primary step for prostate volume estimation. We examine various DL architectures, including traditional U-Net modifications and innovative designs incorporating residual connections, multi-directional image data, and attention mechanisms. Additionally, we discuss pre-processing methods to enhance image quality, the integration of shape information, and strategies to improve the consistency and robustness of DL models. The effectiveness of these techniques is evaluated through metrics such as Dice Similarity Coefficient, Jaccard Index, and Hausdorff Distance. The review highlights the potential of DL in improving prostate volume estimation accuracy and reducing clinical workload, while also identifying areas for future research to enhance model performance and generalizability.

Despite advances in our understanding of molecular aspects of oncogenesis, cancer remains a leading cause of death. The malignant behavior of a cancer cell is driven by the inappropriate activation of transcription factors. In particular, signal transducers and activators of transcription (STATs), which regulate many critical cellular processes such as proliferation, apoptosis, and differentiation, are frequently activated inappropriately in a wide spectrum of human cancers. Multiple signaling pathways converge on the STATs, highlighting their importance in the development and progression of oncogenic diseases. STAT3 and STAT5 are two members of the STAT protein family that are the most frequently activated in cancers and can drive cancer pathogenesis directly. The development of inhibitors targeting STAT3 and STAT5 has been the subject of intense investigations in the last decade, although effective treatment options remain limited. In this review, we investigate the specific roles of STAT3 and STAT5 in normal physiology and cancer biology, discuss the opportunities and challenges in pharmacologically targeting STAT proteins and their upstream activators, and offer insights into novel therapeutic strategies to identify STAT inhibitors as cancer therapeutics.

This study investigates the spatial urban growth patterns of cities along the Democratic Republic of Congo (DRC) and Zambia border, a region of significant economic importance characterized by cross-border trade. This activity has led to rapid, but unplanned urban growth. The objective is to quantify the spatial expansion of Congolese cities (Kipushi, Kasumbalesa, Mokambo, and Sakania) bordering Zambia and to evaluate associated landscape changes. The methodology integrates Landsat images from 1990, 2000, 2010, and 2023, coupled with Geographic Information Systems (GIS) and landscape ecology analysis tools. The results reveal substantial landscape transformations in the border cities between 1990 and 2023. These changes are primarily driven by rapid urban expansion, particularly pronounced in Kasumbalesa. Between 1990 and 2023, forest cover declined from 70% to less than 15% in Kipushi, from 80% to 10% in Kasumbalesa, from 90% to 30% in Mokambo, and from 80% to 15% in Sakania. This forest cover loss is accompanied by an increase in landscape element diversity, as indicated by the Shannon diversity index, except in Kipushi, suggesting a transition towards more heterogeneous landscapes. In these border cities, landscape dynamics are also characterized by the expansion of agriculture and savannas, highlighted by an increase in the disturbance index. Spatial pattern changes analysis shows that built-up areas, agriculture, and savannas exhibit trends of patch creation or aggregation, while forests are undergoing processes of dissection and patch attrition. Congolese cities bordering Zambia are undergoing substantial spatial changes propelled by intricate interactions between economic, demographic, and infrastructural factors. Our results highlight the necessity for sustainable development strategies to address challenges such as urban sprawl, deforestation, and fostering cross-border cooperation in border regions.

A novel compressible real gas 1D finite volume thermofluid network modelling methodology is proposed that can be applied in the analysis of supercritical CO₂ (sCO2) power cycles. It is applied to simulate centrifugal compressor performance via a mean line approach that directly solves the mass, energy, and momentum balance equations for the discretized flow channels within the machine along with the associated loss models, component characteristics, and applicable compressible real gas equation of state. This can be integrated seamlessly with the rest of the power cycle components like pipes, valves, heat exchangers, etc., thereby eliminating the need for static performance maps and the associated difficulties to ensure similarity over the whole range of operation. This direct simulation of the internal flows also makes it possible to do integrated cycle design optimization that includes the geometry of the compressors, and to simulate fast transients for dynamic analysis. The methodology was applied to simulate well-documented air and sCO2 centrifugal compressors and compared the generated results with that of conventional thermofluid network incompressible and compressible ideal gas approaches. The results indicate that the proposed compressible real gas approach can capture the stagnation pressure changes and isentropic efficiencies with good accuracy for both cases over the whole range of mass flow rates and shaft rotational speeds. In contrast, the conventional thermofluid network incompressible and compressible ideal gas approaches are only applicable in selected regions of the fluid property regime and suffer from discretization errors and inappropriate treatment of the relationship between stagnation and static pressures. Furthermore, comparative analyses between the newly proposed approach and the traditional mechanical energy balance method are performed, showing that the latter approach needs to be discretized more finely through the compression process to correctly capture the polytropic compression path shape, whereas the former more accurately captures the stagnation pressure changes through the analyzed compressors with only a single increment per compressor component.

Gender has been a rarely addressed aspect in digital game-based learning (DGBL). Likewise, mixed results have been presented regarding the effects according to gender and the conditions that generate these effects. The present work studies the effects of a drill-and-practice mathe-matical game on primary students. The study focused on an analysis by gender, measuring learning performance, and motivation in the practice activity. Also, two instructional mechanics were considered regarding the question answering, a multiple-try (MTF) and a single-try (STF) condition, to search for possible differences. A total of 81 students from 4 courses and 2 schools participated in the experiment. The study's main findings were that: (a) the girls outperformed boys in terms of students' learning gains, (b) girls presented lower levels of competence and autonomy than boys, (c) in the MTF, girls presented lower levels of autonomy but no differences in competence contrasted to boys, (d) in the STF, girls presented lower levels of competence but no differences in autonomy against boys, and (e) no differences existed in interest, effort and value among gender overall o per instructional condition. This study enhances the knowledge of gender differences under diverse instructional settings, in particular providing insights into possible differences by gender when varying the number of attempts provided to students.

Health literacy is a growing research area with specific aspects and different instruments to measure health literacy. This article uses natural language processing model to analyze the academic corpora regarding seven health literacy instruments - Health Literacy Questionnaire, Mental Health Literacy Scale, Rapid Estimate of Adult Literacy in Medicine, Test of Functional Health Literacy in Adults, Health Literacy Survey, The Newest Vital Sign and eHealth Literacy Scale. We apply Structural Topic Modeling to all the abstracts of the selected academic corpora, label the topics based on their focus, and use the topic distribution with metadata to train a Random Forest algorithm for predicting yearly citations. We estimate Regression models based on the ranking of the most relevant features, which serves as a robustness check and to infer their impact on citation dynamics. We have found that Digital Health Literacy is positively associated with yearly citations, while other topics such as Functional Health Literacy and Women's Health reduce citation likelihood. Other article characteristics also have shown a significant role in the citation likelihood, such as the publication year, amount of articles and certain keywords. These findings portray the current landscape of health literacy research, highlighting literature gaps and popular topics.

Correct diagnosis and early treatment of respiratory diseases can significantly improve the health status of patients, reduce healthcare expences, and enhance quality of life. Therefore, there has been extensive interest in developing automatic respiratory disease detection systems. Most of these methods have recently been using machine and deep learning algorithms. The success of machine learning methods depends heavily on the selection of proper features to be used in the classifier. Although metaheuristic-based feature selection methods have been successful in addressing difficulties presented by high-dimensional medical data in various biomedical classification tasks, there is not much research on the utilization of metaheuristic methods in respiratory disease classification. This paper aims to conduct a detailed and comparative analysis of six widely used metaheuristic optimization methods using eight different transfer functions in respiratory disease classification. For this purpose, two different classification cases were examined: binary and multi-class. The findings demonstrate that metaheuristic algorithms using correct transfer functions could effectively reduce data dimensionality while enhancing classification accuracy.

Previous reviews by the authors [1, 2] indicate the continuing development and improvement of thermal protective systems through the introduction of polymer nanocomposites into polymer matrix composites. These materials perform as thermal protective systems for a variety of aerospace applications, such as thermal protection systems (TPS), solid rocket motors (SRM) nozzles, internal insulation of SRM, leading edges of hypersonic vehicles, and missile launch structures. A summary of the most recent, global technical research is presented. Polymeric resin systems continue to emphasize phenolic resins and other materials. New high-temperature organic resins based on phthalonitrile (PN), and polysiloxane are described and extend the increased temperature range of resin matrix systems.

Medication adherence is a vexing challenge with nonadherence at 50% or greater among US adults. With most medications self-administered by patients in the home, home medication management practices, especially where patients store medication in the home and receptivity to guidance from healthcare providers, need to be better understood to improve adherence. We designed and deployed a survey to investigate home medication management. The 1,673 survey respondents reported that the most common home storage locations for medications were nightstand drawers (28%) and atop nightstands (27%). Kitchen cabinets and bathroom vanities were significantly associated with increased odds of having ever forgotten to take a medication. Desks, dining room tables, and nightstand drawers were associated with the greatest statistically significant decrease in odds of having ever forgotten to take a medication. Almost all (96%) respondents were receptive to guidance on medication storage from a healthcare provider. Patients are largely on their own to devise home medication management practices, yet some home storage locations are significantly associated with decreased odds of having forgotten to take a medication. Knowing which practices are associated with adherence may lead to better guidance for patients from healthcare providers and to innovation in the design of medication adherence interventions.

Cryptocurrencies have now become an emerging blockchain-based payment technology. Users’ identities on such networks are pseudo-anonymous in that all transactions made from an address are transparent and searchable by anyone; to preserve their privacy, users often use many different addresses. In recent years, some studies have been conducted regarding analyzing clusters of Bitcoin addresses that, according to certain heuristics, belong to the same entity. Such action allows law enforcement to have relevant information in cases where cryptocurrencies are used for illegal trafficking. Clustering methods based on a single heuristic do not allow the clustering of many addresses in a complete and accurate manner. This paper proposes Bitcoin Address Clustering based on multiple Heuristics (BACH), a tool that uses three different clustering heuristics to identify clusters of Bitcoin addresses, which are displayed through a three-dimensional graph. Based on the results, several analyses were conducted, including a comparison with Wallet Explorer, an address clustering tool similar to BACH. BACH, in addition to introducing the innovative feature of graphical visualization of the internal structure of clusters, is shown to improve address aggregation through the joint use of three heuristics for clustering.

Glycogen storage disorders (GSDs) are a group of inherited metabolic disorders characterized by defects in enzymes involved in glycogen metabolism. Deficiencies in enzymes responsible for glycogen breakdown and synthesis can impair mitochondrial function. For instance, in GSD type II (Pompe disease), acid alpha-glucosidase deficiency leads to lysosomal glycogen accumulation, which secondarily impacts mitochondrial function through dysfunctional mitophagy, which disrupts mitochondrial quality control generating oxidative stress. In GSD type III (Cori disease), the lack of the debranching enzyme causes glycogen accumulation and affects mitochondrial dynamics and biogenesis by disrupting the integrity of muscle fibers. Malfunctional glycogen metabolism can disrupt various cascades thus causing mitochondrial and cell metabolic dysfunction through various mechanisms. These dysfunctions include altered mitochondrial morphology, impaired oxidative phosphorylation, increased production of reactive oxygen species (ROS), and defective mitophagy. The oxidative burden typical of GSDs compromises mitochondrial integrity and exacerbates the metabolic derangements observed in GSDs. The intertwining of mitochondrial dysfunction and GSDs underscores the complexity of these disorders and has significant clinical implications. GSD patients often present with multisystem manifestations, including hepatomegaly, hypoglycemia, and muscle weakness, which can be exacerbated by mitochondrial impairment. Moreover, mitochondrial dysfunction may contribute to the progression of GSD-related complications, such as cardiomyopathy and neurocognitive deficits. Targeting mitochondrial dysfunction thus represents a promising therapeutic avenue in GSDs. Potential strategies include antioxidants to mitigate oxidative stress, compounds that enhance mitochondrial biogenesis, and gene therapy to correct the underlying mitochondrial enzyme deficiencies. Mitochondrial dysfunction plays a critical role in the pathophysiology of GSDs. Recognizing and addressing this aspect can lead to more comprehensive and effective treatments, improving the quality of life of GSD patients. This review aims to elaborate on the intricate relationship between mitochondrial dysfunction and various types of GSDs. The review presents challenges and treatment options for several GSD

Land use land cover change(LULCC) plays a significant role in understanding the global change. Particularly in regions with high population growth and climate change, anthropogenic activities have drastically altered land use and land cover (LULC). The geographic information system (GIS) and remote sensing are prominent tools for monitoring LULC changes. The land use land cover(LULC) analysis and carbon loss assessment were carried out in Ayubia national park. The area was classified into five major LULC classes, namely grassland, built-up areas, mixed forests, conifer forests and bare land. Landsat temporal satellite data of Ayubia national park acquired on 1992,2002,2012 and 2022 were analysed to access land use change and Markov’s Chain Model was used to predict the land use land cover changes for 2040. The accuracy of the images were assessed using Kappa matrix. Our results showed that a total of 371.94 ha forest land has been converted into other land uses from 1992 to 2022 and Indicating the increasing scale of anthropogenic pressure on forest resources of the Park. The carbon pool was assessed in two forest types including temperate coniferous forest and Mixed forest. The estimated carbon value recorded in TCF is 135.19 ±9.74 MgC ha-1, whereas it is in 86.43 ±8.25 MgC ha-1 in MF. Using satellite data, a thorough examination of the forest inventory was conducted to determine the LULCC, the rate of biomass carbon loss, and the factors that influenced these trends.

BACKGROUND: It has been shown that obesity and higher body mass index (BMI) are associated with higher recurrence rate of atrial fibrillation (AF) after successful catheter ablation (CA). The same has been proven for left atrial volume index (LAVI). It has also been shown that there is a correlation between LAVI and BMI. However, whether LAVI prognostic impact on AF recurrence is BMI independent, remains unclear. METHODS: We prospectively included 62 patients with paroxysmal AF who were referred to our institution for CA. All patients underwent radiofrequency CA with standard pulmonary veins isolation. Transthoracic 2-D echocardiography was performed one day after CA to obtain standard measures of cardiac function and morphology. Recurrence was defined as documented AF within 6 months of follow-up period. Patients were also instructed to visit outpatient clinic earlier in case of symptoms suggesting AF recurrence. RESULTS: We observed AF recurrence in 27% of patients after 6 months. The mean BMI in our cohort was 29.65 ± 5.08 kg/cm2 and the mean LAVI was 38.04 ±11.38 ml/m2. We further divided patients into 2 groups according to BMI. Even though LAVI was similar in both groups, we found it to be significant predictor of AF recurrence only in obese patients (BMI ≥ 30), but not in the non-obese group (BMI < 30). There was also no significant difference in AF recurrence between both cohorts. The significance of LAVI as AF recurrence predictor in obesity group was also confirmed in multivariate model. CONCLUSION: According to our results LAVI tends to be significant predictor of AF recurrence after successful catheter ablation in obese patients, but not in normal-weight and overweight patients. This would suggest different mechanisms of AF in non-obese patients in comparison to the obese. Further studies are needed in this regard.

Advances in the treatment of cancer with immunotherapy necessitate a locally administered sustained-delivery system to improve treatment efficacy and reduce toxicity. Towards this end, the encapsulation and release characteristics of human antibody immunoglobulin-G (IgG-FITC) were investigated with the coaxial electrospray technique. The antibody solution was exchanged for a solution at the antibody’s isoelectric pH. The shell solution consisted of PLGA in ethyl acetate. The impact of shell flow rates was investigated in the fabrication of IgG-FITC-loaded PLGA microparticles and the release-profile of IgG-FITC from the PLGA microparticles was characterized. Encapsulation efficiency ranged from 0.04-1.52%. Fluorescence images suggest core localization in the formulation with a lower shell flow rate and shell localization in the formulation with the higher shell flow rate. SEM image analysis revealed that lower shell flow rate resulted in the smaller average particle size with minimal difference in zeta potential between formulations. The lower shell flow rate exhibited a release profile with a t1/2 of 36 hours whereas the higher shell flow rate had a t1/2 &lt; 3 hours. Antibody-fluorescence signals were measured for 28 days and indicated a biphasic release profile with a burst-release followed by a sustained-release in both formulations.

Quantum computing is tipped to lead the future of global technological progress. However, the obstacles related to quantum software development are an actual challenge to overcome. In this scenario, this work presents an implementation of the quantum search algorithm in Atos Quantum Assembly Language (AQASM) using the quantum software stack my Quantum Learning Machine (myQLM). We present the creation of a virtual quantum processor whose configurable architecture allows the analysis of induced quantum noise effects on the quantum algorithms. The codes are available throughout the manuscript so that readers can replicate them and apply the methods discussed in this article to solve their own quantum computing projects. The presented results are consistent with theoretical predictions and demonstrate that AQASM and myQLM are powerful tools for building, implementing, and simulating quantum hardware.

Many people in the USA have lost their lives or become addicted to opioids via prescription opioids given for chronic pain. The chronic pain epidemic has emerged due to a convergence of factors, including the medicalization of pain as well as injuries happening in the workplace, in the home, or during recreation. Opioid prescriptions rose precipitously from the late 1990’s through to approximately 2020, and despite public awareness, still are increasing. This review examines literature on integrative approaches to chronic pain as delineated by pain type. The review is organized by the most common causes of chronic pain, and randomized controlled trials, meta-analyses and systematic reviews are extracted for each cause of chronic pain. Several promising interventions may alleviate chronic pain of some causes, and some interventions may work across pain causes. Lowering inflammation through dietary or lifestyle regimens may be a general way of reducing pain. Pain can be alleviated through several adjunctive and integrative treatment approaches, which may serve to lower the need for opioid medication.

The rapid evolution of technology has given rise to a connected world, where billions of devices interact seamlessly, forming what is known as the Internet of Things (IoT). While IoT offers incredible convenience and efficiency, it presents a significant challenge in cybersecurity and is characterized by various power, capacity, and computational process limitations. Machine learning techniques are employed within Intrusion Detection Systems (IDS) to enhance their capabilities in identifying and responding to security threats. The key features selected to improve IDS efficiency and reduce dataset size, thereby decreasing the time required for attack detection, are drawn from the extensive network dataset. This paper introduces an enhanced feature selection method designed to reduce the computational overhead on IoT resources while simultaneously strengthening intrusion detection capabilities within the IoT environment. Experimental results based on the InSDN dataset demonstrate that our proposed methodology achieves the highest accuracy with the fewest number of features and low computational cost. Specifically, we attain a 99.99% accuracy with 11 features and a computational time of 0.8599 seconds.

The use of natural chloride in the salt fuel has been sometimes promoted for the chlorine based molten salt fast reactor using for example NaCl-UCl4- UCl3. Most of the chemistry based R&D has been carried out on natural chloride, while in reactor physics most of the calculations are based on enriched chloride-37. In any case, the use of natural chloride (75.77% 35Cl and 24.23% 37Cl) induces specific ecological and neutron economical issues. An ecological issue is the production of 36Cl by neutron activation of 35Cl. Chlorine-36 is a soluble long live nuclide that makes it a ‘first’ nuclide in the safety assessment of the repository. We explore the build-up of 36Cl with burnup for various 37Cl (activation product) enrichment. The neutron economical aspect is gained by achieving reactor criticality with a lower amount of fissile material achieved through the use of enriched chloride-37. The criticality (k) of a core is much larger for enriched chloride than for the natural one. The reactor with 99% 37Cl would have a k99/knat of 1.04346 which would allow to reduce the required uranium enrichment and thus the fuel cost. This reactivity gain is evaluated for various 37Cl enrichment factors to estimate uranium enrichment gain achievable through 37Cl enrichment. However, from economical point of view it could be of interest to use as some kind of compromise solution natural NaCl, which will be analysed, too. Production/enrichment of 37Cl can be performed by physical separation e.g. gas centrifugation of 1H35/37Cl or by chemical separation using anion partitioning and elution of 23Na35/37Cl on solid adsorbent columns or in liquid – liquid extraction systems. These techniques require however extensive investigations including chemical thermodynamics and hydrodynamics. Comparisons are suggested on the basis of the separation factor α. Recommendations are finally given for utilising 37Cl in the fast molten salt reactor. The enrichment work for 37Cl is smaller than the work needed for 235U enrichment.

This Paper delves into a thorough analysis of the DC-DC buck converter tailored for renewable energy applications. Given the prevalent utilization of renewable resources producing DC voltages, this converter plays a pivotal role in stepping down high-level DC voltages to more manageable levels. The research focuses on varying the duty cycle to assess its impact on the converter's output voltage performance. Simulations conducted using PSIM are meticulously compared with hardware implementation results, demonstrating the converter's efficacy in generating significantly reduced output voltages. The findings underscore the practical applicability of this converter in renewable energy scenarios, offering a succinct yet insightful perspective on its performance and adaptability.

Heavy metals represent a class of chemical elements that includes metalloids, bases and transition metals, lanthanides and actinides. They are distinguished for their toxicity in small concentrations and for their negative effects on the environment and human health. They are present in various samples, mainly in water, industrial waste and food. The determination of heavy metals is carried out mainly by analytical methods, using spectroscopy, spectrometry and electroanalysis, while studies are being carried out for the development of new and faster methodologies and techniques for their analysis, with particular emphasis on voltammetry. This review deals with the determination of heavy metals mainly in environmental samples (water) using voltammetry. In particular, the methods of their determination are evaluated in terms of sensitivity, selectivity and applicability.

Epithelial–mesenchymal transition (EMT) is defined as a cellular process during which epithelial cells acquire mesenchymal phenotypes and behavior following the downregulation of epithelial features. EMT and its reversed process, the mesenchymal-epithelial transition (MET), and the special form of EMT, the endothelial-mesenchymal transition (EndMT), have been thought as a universal dogma controlling developmental and pathological processes. More than half a century of EMT study has made it a large research field and a mainstream concept. However, discrepancies and disputes over EMT and EMT research have also grown over time. Particularly, neither the epithelial and mesenchymal states/properties nor their regulatory networks nor specific markers have been defined, rendering the EMT, MET and EndMT concepts groundless. Moreover, EMT and MET effects should not be a cause, but rather a consequence of or an accompanying effect during developmental and pathological processes. EMT and MET represented by the change in cell shapes or adhesiveness or symbolized by EMT factors are biased interpretation of the overall change in cellular property and regulatory networks during development and cancer progression. The true meaning of EMT effects in some developmental and pathological processes, such as fibrosis, needs re-evaluation. But the core EMT factors are actually a few components of the regulatory networks of neural stemness, which determines tumorigenicity and pluripotency. The EMT effects in cancer progression and neural crest formation are wrong attribution of the role of neural stemness during cancer progression and the cell-intrinsic property of neural crest cells to the unknown mesenchymal state. It is time to reassess the significance of EMT and its related concepts in scientific research.

Searching over a sorted list is a classical problem in computer science. Binary Search takes at most log2n+1 tries to find an item in a sorted list of size n. Interpolation Search achieves an average time complexity of Ο(loglogn) for uniformly distributed data. Hybrids of Binary Search and Interpolation Search are also available to handle data with unknown distributions. This paper analyzes the computation cost of these methods and shows that interpolation can significantly affect their performance — accordingly, a new method, Interpolation Once Binary Search (IOBS), is proposed. The experimental results show that IOBS outperforms the hybrids of Binary Search and Interpolation Search for nonuniformly distributed data.

A novel concept of a finned piston system is presented and analyzed where the compression heat is continuously extracted from the compression chamber. The resulting compression characteristic moves in direction of an isothermal process, reducing so the temperature of the compressed fluid in the compression chamber and reducing the necessary mechanical work for the process. The finned piston concept consists in an integrated heat exchanger inside of the chamber and being constituated of imbricated flat fins placed on the stator part and on the mobile piston. The internal heat exchange surface is strongly increased in comparison with a classical piston/cylinder. The energetic performance of the new system is evaluated with the help of simulation. Pressures, forces and temperature of the compressed gas are simulated as well as the mechanical work needed. The different curves are compared with adiabatic and isothermal characteristics.

Using insights from cybernetics and an information-based understanding of biological systems, a precise, scientifically inspired, definition of free-will is offered and the essential requirements for an agent to possess it in principle are set out. These are: a) there must be a self to self-determine; b) there must be a non-zero probability of more than one option being enacted; c) there must be an internal means of choosing among options (which is not merely random, since randomness is not a choice). For (a) to be fulfilled, the agent of self-determination must be organisationally closed (a `Kantian whole'). For (c) to be fulfilled: d) options must be generated from an internal model of the self which can calculate future states contingent on possible responses; e) choosing among these options requires their evaluation using an internally generated goal defined on an objective function representing the overall `master function' of the agent and f) for `deep free-will', at least two nested levels of choice and goal (d-e) must be enacted by the agent. The agent must also be able to enact its choice in physical reality. The only systems known to meet all these criteria are living organisms, not just humans, but a wide range of organisms. The main impediment to free-will in present-day artificial robots, is their lack of being a Kantian whole. Consciousness does not seem to be a requirement and the minimum complexity for a free-will system may be quite low and include relatively simple life-forms that are at least able to learn.

In this short paper we study some properties of the lines associated with van Aubel’s theorem in the special case when squares are replaced with equilateral triangles constructed on the sides of an arbitrary quadrilateral.

The challenge of this work is to re-define the concept of intelligent agent as a building block of social networks by presenting it as a physical particle with additional non-Newtonian properties. The proposed model of an intelligent agent described by a system of ODE coupled with their Liouville equation has been introduced and discussed. Following the Madelung equation that belongs to this class, non-Newtonian properties such as superposition, entanglement, and probability interference typical for quantum systems have been described. Special attention was paid to the capability to violate the second law of thermodynamics, which makes these systems neither Newtonian, nor quantum. It has been shown that the proposed model can be linked to mathematical models of livings as well as to models of AI. The model is presented in two modifications. The first one is illustrated by the discovery of a stochastic attractor approached by the social network; as an application, it was demonstrated that any statistics can be represented by an attractor of the solution to the corresponding system of ODE coupled with its Liouville equation. It was emphasized that evolution to the attractor reveals possible micro-mechanisms driving random events to the final distribution of the corresponding statistical law. Special attention is concentrated upon the power law and its dynamical interpretation: it is demonstrated that the underlying micro- dynamics supports a “violent reputation” of the power-law statistics. The second modification of the model of social network associated with a decision-making process and applied to solution of NP-complete problems known as being unsolvable neither by classical nor by quantum algorithms. The approach is illustrated by solving a search in unsorted database in polynomial time by resonance between external force representing the address of a required item and the response representing the location of this item.

Providing user confidence in Mobile Government Services (MGS) is essential for the success of mobile government. This study aimed to test the moderating role of techno-skepticism in the impact of crisis management on mobile government. Some scholars have stated that government investment in mobile government services for public administration during the financial crisis is a critical issue for crisis management. In the constantly evolving and changing world, the rapid advancement of technology in modern societies has prompted an acceleration in investments in information and communication technologies. However, due to several inadequacies, citizens seem to respond negatively to the use of certain public technological services, leading them to develop a perspective of techno-skepticism. This issue has been cited in numerous scholarly studies as a critical subject for the effective implementation of technological innovations. The effectiveness of digital technology in the procurement of public services is highly dependent on the perceptions and behaviors of users. In this context, this study measured the attitudes of the participants and the connections between techno-skepticism, mobile government use, and crisis management among Northern Cyprus residents over 18 years old. The study employed a quantitative approach. A 5-point Likert scale was used to collect data by modifying the survey questions to fit the scope of the study. The study participants were selected using the random sampling method to acquire data from a total of 402 citizens. The study findings revealed that techno-skepticism mediates the impact of crisis management on mobile government. As a result, techno-skepticism is a critical and decisive factor in citizens’ mobile government use, affecting its utilization frequency. Techno-skepticism was also found to play a vital role in mobile government use. The current study represents a pioneering effort in testing the moderating role of techno-skepticism in the impact of crisis management on mobile government. It also provides various contributions to theory and practice, particularly in the fields of mobile government and the use of digital technologies.

In order to assess the impact of nitrogen availability on lipid metabolism of Streptomyces coelicolor, we first assessed the global lipid content of 21 strains derived from S. coelicolor M145 deleted for at least one gene involved in nitrogen metabolism. This study revealed that only 7 strains deleted either for genes encoding, proteins involved in polyamine (GlnA2/SCO2241, GlnA3/SCO6962, GlnA4/SCO1613) or protein (Pup/SCO1646) degradation, for the global regulator DasR/SCO5231 that controls negatively the degradation of N acetylglucosamine, a constituant of peptidoglycan, or for two proteins involved in the regulation of nitrogen metabolism, GlnE/SCO2234 and GlnK/SCO5584, had a higher triacylglycerol content than the original strain whereas 5 of these strains (with the exception of glnA2 and pup mutant strains) had a lower cardiolipin content than the original strain. Furthermore, the determination of the level of production of the blue polyketide, actinorhodin (ACT), of these 7 strains grown either in phosphate (Pi) limitation or proficiency, revealed that ACT production was totally abolished in the dasR mutant in both Pi conditions whereas the deletion of pup, glnA2, glnA3 and glnA4 was correlated with a significant increase of total ACT production, in Pi limitation. However, in Pi proficiency, ACT production was only slightly enhanced in the pup, glnA2 and glnA4 mutants and was strongly reduced in the glnA3 mutant. Altogether our data suggest that high TAG and ACT biosynthesis and low cardiolipin biosynthesis might all contribute to the lowering of oxidative stress resulting from nitrogen limitation or from other causes.

Ballistic helmets are individual armor equipment designed to protect a soldier's head from projectiles and fragments. Although very common, these helmets are responsible for several causalities due to their low ballistic resistance and large back face deformation to stop the projectile. Therefore, to enhance helmet performance, studies have focused on the development of new materials and new ballistic protection solutions. The purpose of this study was to develop and evaluate a new ballistic solution using thermoplastic-based matrices. The first matrix was based on high-density polyethylene (HDPE). The second matrix was based on HDPE modified with ex-foliated montmorillonite (MMT). The main manufacturing processes of a thermoplastic-based ballistic helmet are presented, along with its ballistic performance, according to the National Institute of Justice (NIJ) standard 0106.01 and an investigation of its failure mechanisms via a non-destructive technique. All the helmets resulted in level III-A ballistic protection. The postimpact helmets were scanned to evaluate the back face deformation dimensions, which revealed that the global cone deformation was deeper in the HDPE than in the HDPE/MMT. The failure analysis revealed an overall larger deformation area in the HDPE and HDPE/MMT helmet delamination zones in regions with a large radius of curvature than in zones with the lowest radius, which is in accordance with previous simulations from the literature.

Abnormalities in sperm nuclei and chromatin can interfere with normal fertilization, embryonic development, implantation, and pregnancy. We aimed in this study to determine the impact of H2BFWT gene variants in sperm DNA on ICSI outcomes in couples undergoing ART treatment. One hundred and nineteen partners were divided into pregnant (G1) and non-pregnant (G2) groups. After semen analysis, complete DNA was extracted from purified sperm samples. The sequence of the H2BFWT gene was amplified by PCR and then subjected to Sanger sequencing. The results showed that there are three mutations in this gene: rs7885967, rs553509 and rs578953. rs553509 and rs578953 showed significant differences in the distribution of alternative and reference alleles between G1 and G2 (P = 0.0004 and P = 0.0020, respectively). However, there was no association between these SNPs and the studied parameters. This study is the first to shed light on the connection between H2BFWT gene variants in sperm DNA and pregnancy after ICSI therapy. This is a pilot study, so further investigations about these gene variants at the transcriptional and translational levels, in a larger cohort of patients, are needed to determine its functional consequences and to understand the mechanism of how the pregnancy is affected by sperm DNA.

Autoimmune polyglandular syndrome (APS) comprises a complex association of autoimmune pathological conditions. APS Type 1 originates from loss-of-function mutations in the autoimmune regulatory (AIRE) gene. APS2, APS3, and APS4 are linked to specific HLA alleles within the major histocompatibility complex, with single nucleotide polymorphisms (SNPs) in non-HLA genes also contributing to disease. In general, variability in the AIRE locus and the presence of heterozygous loss-of-function mutations can impact self-antigen presentation in the thymus. In this study, Whole Exome Sequencing (WES) was performed on a sixteen-year-old female APS3A/B patient to investigate the genetic basis of her complex phenotype. The analysis identified two variants (p.Arg111Trp and p.Thr101Ile) of the hepatitis A virus cell receptor 2 gene (HAVCR2) encoding for the TIM-3 (T cell immunoglobulin and mucin domain 3) protein. These variants were predicted, through in silico analysis, to impact protein structure and stability, potentially influencing the patient’s autoimmune phenotype. While Confocal Microscopy analysis revealed no alteration in TIM-3 distribution between PBMCs isolated from the patient and those of a healthy donor, RT-qPCR showed reduced TIM-3 expression in the patient’s cells. A screening conducted on a cohort of thirty APS patients indicated that the p.Thr101Ile and p.Arg111Trp mutations were unique for the proband. This study opens the pathway for the search of TIM-3 variants possibly linked to complex autoimmune phenotypes, highlighting the potential of novel variant discovery in contributing to APS classification and diagnosis.

This study analyses the changes in land use in the Sado estuary (West-Central Portugal) based on a multitemporal analysis of cartographic data from the 19th century and remote sensing land use maps from the 21st century, updated by field work. A GIS plotting of land-use evolution is summarized in a quantitative table. The comparison shows the changes in land use, with increasing occupation by human economic activities, including extensive agriculture and forestry, as well as localized urbanization and industrialization. The main elements of the landscape impacted by anthropogenic uses were: i) hydrography - river dams affected the flow dynamics and sedimentary processes in the estuary; ii) vegetation – increasing agriculture and forestry reduced the areas of native vegetation, nowadays mostly occupied by vineyards, pine forests and cork oaks. iii) wetlands - tidal and alluvial plains are being occupied by rice cultivation, aquaculture, industries, and ports; iv) coastal dunes – new developments are occupying large areas of Holocene coastal dunes; v) natural environment – mining and dredging affected some habitats and biodiversity. This analysis is intended to help the territorial organization of present and future economic activities, as well as to reduce environmental and social problems, promoting long-term sustainability of this rapidly evolving region.

Mosquito-borne diseases (MBDs) are a group of illnesses transmitted by mosquitoes and can be caused by bacteria, viruses, or parasites. These diseases represent a significant global burden of infectious diseases, including morbidity and mortality. This systematic review delves into the multifaceted factors contributing to the spread of mosquito-borne diseases (MBDs) in the Middle East and North Africa (MENA) region. Following PRISMA guidelines, a thorough analysis of peer-reviewed articles from May 1990 to Jan 2023 was conducted, highlighting the interplay of population, environmental, disease, and mosquito factors in disease transmission and prevalence. The review incorporated 31 studies that revealed a complex relationship between various risk factors and the presence of MBDs. Significant associations were observed with age, certain occupations, environmental conditions such as rainfall and temperature, sanitation practices, specific pathogen variants, clinical symptoms, and Aedes aegypti mosquitoes. Conversely, gender, socioeconomic status, educational status, and certain sanitation-related factors showed inconsistent association with the spread of MBDs. The review underscores the need for targeted interventions, including vector control, improved sanitation, and educational campaigns to mitigate the spread of MBDs in the MENA region. This review could guide research studies to address data gaps and assist in developing effective surveillance programs in the MENA region. This work emphasizes the need for region-specific public health strategies and further research to understand and curb the burden of these diseases effectively.

Transcription is carried out in most eukaryotes by three multimeric complexes (RNA polymerases I, II and III). However, plants contain two additional RNA polymerases (IV and V), which have evolved from RNA polymerase II. RNA polymerases II, IV and V contain both common and specific subunits that may specialize some of their functions. In this study, we conducted a search for the genes that putatively code for the specific subunits of RNA polymerases IV and V, as well as the corresponding of RNA polymerase II in olive. Based on the homology with the genes of Arabidopsis thaliana, we identified 13 genes that putatively code for the specific subunits of polymerases IV and V, and 16 genes that code for the corresponding specific subunits of polymerase II in olive. The transcriptomic analysis by RNA-Seq revealed that the expression of the RNA polymerases IV and V genes was induced during the initial stages of fruit development. Given that RNA polymerases IV and V are involved in the transcription of long non-coding RNAs, we investigated their expression and observed relevant changes in the expression of this type of RNAs. Particularly, the expression of the intergenic and intronic long non-coding RNAs tended to increase in the early steps of fruit development, suggesting their potential role in this process. The positive correlation between the expression of RNA polymerases IV and V subunits and the expression of non-coding RNAs supports the hypothesis that RNA polymerases IV and V may play a role in fruit development throughout the synthesis of this type of RNAs.

This paper reports on the optimization of thin-film coating assisted self-sustainable off-grid hybrid power generation systems for cattle farming in rural areas of Bangladesh. Bangladesh is a lower middle-income country with declining rates of poverty among its 160 million people due to persistent economic growth in conjunction with balanced agricultural improvements. Most of the rural households adopt a mixed farming system by cultivating crops and simultaneously rearing livestock. Among the animals raised, cattle are considered as the most valuable asset for the small/medium-scale farmers in terms of their meat and milk production. Currently, along with the major health issue, the COVID-19 pandemic is hindering the world’s economic growth and has thrust millions into unemployment; Bangladesh is also in this loop. However, natural disasters such as COVID-19 pandemic and floods, largely constrain rural smallholder cattle farmers from climbing out of their poverty. In particular, small and medium-scale cattle farmers face many issues that obstruct them from taking advantage of market opportunities and imposing a greater burden on their families and incomes. An appropriate measure can give a way to make those cattle farmers’ businesses both profitable and sustainable. Optimization of thin-film coating assisted self-sustainable off-grid hybrid power generation system for cattle farming is a new and forward-looking approach for sustainable development of the livestock sector. In this study, we design and optimize a thin-film coating assisted hybrid (photovoltaic-battery-generator) power system by using the Hybrid Optimization of Multiple Energy Resources (HOMER, Version 3.14.0) simulation tool. An analysis of the results has suggested that the off-grid hybrid system is more feasible for small and medium-scale cattle farming systems with long-term sustainability to overcome the significant challenges faced by smallholder cattle farmers in Bangladesh.

(1) Background: Acute myocardial infarction in pregnancy (pAMI) is a rare event, often caused by non-classical factors rather than atherosclerosis. The management of such a complicationrequires a multidisciplinary team and it is important to bring together the specialities involved to ensure that these teams are coordinated and ready to respond. The management of pAMI poses unique challenges as it requires considering both maternal and fetal well-being. (2) Methods: We present the case of a 36-week pregnant woman who presented with antero-lateral ST elevation myocardial infarction (STEMI) complicated by cardiogenic shock. To ensure comprehensive decision-making, an emergency Pregnancy Heart Team meeting was convened, comprising interventional cardi-ologists, gynecologists, and anesthesiologists. The team prioritized interventional treatment for pAMI, according to ESC guidelines, and opted for primary percutaneous coronary intervention (PCI) due to the unstable maternal condition.; (3) Results: The patient underwent primary PCI as the chosen intervention for pAMI. A rapid response gynecology team closely monitored the procedure and was prepared to intervene in case of irreversible hemodynamic compromise leading to cardiac arrest. An emergency caesarean section was deemed necessary if cardiac ac-tivity was not restored within 4 minutes.; (4) Conclusions: Managing pAMI requires a multidis-ciplinary approach that balances the maternal and fetal well-being. In this particular case, the Pregnancy Heart Team decided to prioritize interventional treatment with primary PCI due to the unstable maternal condition. The presence of a closely monitored gynecology team ensured prompt action in case of complications.

Aim: The aim of this study was to use a multi target approach to testing with both serological tests and an in-house real-time molecular test to investigate the prevalence of the caprine arthritis-encephalitis virus (CAEV) in goats from three hobbyist farms in the Republic of Tatarstan, Russia. Materials and Methods: We have approached the detection of using a multi target approach testing with both ELISA and an in-house real-time PCR test to investigate the prevalence of CAEV in goats. Animals from three hobbyist farms were used in this study. The animals from two farms (n=13 for F1 and n=8 for F2) had clinical signs of arthritis and mastitis. In the third farm (n=15 for F3), all goats were homebred and had no contact with imported animals. Results: CAEV antibodies (ELISA targets TM env and gag genes) were detected in serum samples from two farms (F1 and F2), indicating a seroprevalence 87.50-92.31%. Specific CAEV antibodies were also detected in milk samples. CAEV proviral DNA was detected in 53.85-62.50%. Results from all tests performed in the third farm (F3) were negative, indicting all tests were 100% specific.Conclusion: Results of this work show that CAEV is circulating and present in small hobbyist goat farms in Russia. Serological and molecular tests could be of importance for CAEV control and eradication programs in Russia for hobbyist goat farms.

Human T-cell lymphotropic virus (HTLV) infection lacks effective treatment. This review describes the virological, immunological and clinical outcomes of antiretroviral therapy (ART) in people with HTLV infection. This systematic review followed PRISMA reporting guidelines and was registered in PROSPERO: CRD42022350076. The Newcastle-Ottawa Scales, adapted for cross-sectional studies, and Rob-2 were employed to assess the methodological quality of studies. A systematic search was conducted in Medline (PubMed), Scopus (Elsevier), Cochrane Library, and Web of Science (Clarivate Analytics) databases. We retrieved data from 08 methodologically diverse articles, on treatment of patients infected by HTLV-1 or HTLV-2 alone, or coinfected by HIV-1 with Raltegravir, Tenofovir, Lamivudine and Zidovudine. Proviral load decreased in 3 of 7 studies, during 4 to 48 weeks of antiretrovirals use. Cellular immune response (CD4, CD8, CD25, CD69 and CD71 cells) were evaluated in six studies. There was no significant clinical improvement in the studies but all of them detected clinical stability during treatment. Despite the demonstrated antiviral activity of ART, in vitro, clinical improvement was not proven. Most studies showed disease stability during ART use, suggesting potential clinical benefits. There is a need of larger, well-controlled trials, to define the role of ART for treatment of HTLV infection.

The interplay between the human gut microbiota and the peripheral immune system significantly affects the efficacy of immune checkpoint inhibitors (ICIs) in cancer therapy. Despite this profound connection, the practical implications of microbiota dysbiosis in cancer immunotherapy ICIs & and CAR-T remain intricate and poorly understood in practical terms. This paper offers a comprehensive review of current literature on the role of gut microbiota dysbiosis in tumor development, and emerging microbiota modulation interventions, with a focus on fecal microbiota transplantation (FMT). FMT is a cost-effective therapeutic avenue, particularly in addressing diseases rooted in antibiotic-resistant bacteria, such as Clostridium difficile. Here we provided insights into the applications of FMT and other gut microbiota therapies in the landscape of cancer treatment, emphasizing their influence on the tumor microenvironment and the efficacy of ICIs with suggestions for future research directions and their implications for clinical practice.

In this study, Silicon Carbide (SiC) nano-particle based serigraphic printing inks were formulated to fabricate highly sensitive and wide temperature range SiC printed thermistors. Initially, commercial silver ink was screen printed to fabricate inter-digitated electrodes (IDE’s) onto flexible Kapton® substrate via screen printing. Thermistor inks with different weight ratios of SiC nano- particles dispersed in polyimide resin matrix were fabricated. The SiC-polyimide temperature sensing inks were screen printed atop the IDE structures to form fully printed thermistors and encapsulated with a adhesive backed polyimide film for humidity inhibition. The high temperature tolerance of the Kapton® allowed the the sensors to be tested over a wide temperature range form 25◦C to 170◦C. The printed SiC thermistors exhibit excellent repeatability and stability over 15 hours of continuous operation. Optimal device performance was achieved with 30 wt.% SiC-polyimide ink. We report highly sensitive devices with a temperature coefficient of Resistance (TCR) of -0.556 %/◦C, a thermal coefficient of 502 K (β-index) and an activation energy of 0.08 eV which are comparable with printed thermistors previous reported. Further, the thermistor demonstrates an accuracy of ±1.35◦C which is well within the range offered by commercially available high sensitivity thermistors. SiC thermistors exhibit a small 6.5% drift due to changes in relative humidity between 10-90 %RH and a 4.2 % drift in baseline resistance after 100 cycles of aggressive bend testing at a 40°angle. The use of commercially available low cost materials, simplicity of design and fabrication techniques coupled with the chemical inertness of the Kapton® substrate and SiC nanoparticles paves the way to use all-printed SiC thermistors towards a wide range of applications where temperature monitoring is vital for optimal system performance.

Background: Fullerenes and metallofullerenes can be considered promising nanopharmaceuticals themselves and as a basis for chemical modification. As reactive oxygen species homeostasis plays a vital role in cells, the study of their effect on genes involved in oxidative stress and anti-inflammatory response is of particular importance. Methods: Human fetal lung fibroblasts were incubated with aqueous dispersions of C60, C70, and Gd@C82 in concentrations of 5 nM and 1.5 µM for 1, 3, 24, and 72 hours. Cell viability, intracellular ROS, NOX4, NFκB, PRAR-γ, NRF2, heme oxygenase 1, and NAD(P)H quinone dehydrogenase 1 expression have been studied. Results &amp; conclusion: The aqueous dispersions of C60, C70, and Gd@C82 fullerenes are active participants in ROS homeostasis. Low and high concentrations of AFDs have similar effects. C70 was the most inert substance, C60 was the most active substance. All AFDs have both a “prooxidant” and “antioxidant” effect, but with a different balance. Gd@C82 was a substance with more pronounced antioxidant and anti-inflammatory properties, while C70 had more pronounced “prooxidant” properties.

Background The aims of this study were to assess the peri-operative morbidity, mortality and long-term survival of octogenarians undergoing ATAAD repair, and to compare open and closed distal anastomosis techniques. Methods This was a single-centre retrospective study (2007-2021). Open versus closed distal anastomosis were compared. Uni and multi-variable logistic regression analyses were performed to identify independent predictors of in-hospital mortality. Kaplan-Meier and Cox proportional hazards methods were used to compare long-term survival. Results Fifty octogenarians patients were included (median age - 82 years, closed distal – 22, open distal - 28). Median CPB time was 187 minutes (open distal vs closed distal group; 219 minutes vs 115.5 minutes, p30 days or return to theatre; HR; 4.1, p=0.02) predicted adverse survival. Open distal anastomosis did no impact survival. Conclusions – ATAAD repair in selected octogenarians has favourable short and long-term survival. There is no significant difference between open versus closed distal anastomosis strategies.