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

Nanomagnetism and spintronics are currently active areas of research, with one of the main goals being the creation of low-energy-consuming magnetic memories based on nanomagnet switching. These types of devices could also be implemented in neuromorphic computing by crafting artificial neurons (ANs) that emulate the characteristics of biological neurons, through the implementation of neuron models such as the widely used leaky integrate-and-fire (LIF) with a refractory period. In this study, we have carried out numerical simulations of a 120 nm diameter, 250 nm length ferromagnetic nanowire (NW) with the aim of exploring the design of an artificial neuron based on the creation and destruction of a Bloch-point domain wall. To replicate signal integration, we applied pulsed trains of spin-currents to the opposite faces of the ferromagnetic NW. These pulsed currents (previously studied only in the continuous form) are responsible for inducing transitions between the stable single vortex (SV) state to the metastable Bloch point domain wall (BP-DW) state. To ensure the system exhibits the leak and refractory properties, the NW was placed in an homogeneous magnetic field of the order of mT in the axial direction. The suggested configuration fulfills the requirements and characteristics of a biological neuron, potentially leading to the future creation of Artificial Neural Networks (ANNs) based on reversible changes in the topology of magnetic NWs.

Exponential increase in the number of individuals using internet has been observed in last ten years. The term "internet addiction" (IA) describes a compulsive behavior associated with any online activity that disrupts everyday social interactions. Main aim of this research was to determine variables and development predictors of Internet addiction. A total of 1,669 respondents participated in this research; 1,040 of them (62.3%) were female, 590 (35.4%) were male, and 39 (2.3%) did not want to declare their gender. The average age of the respondents was 15.09±1.757. Data were collected using an online form consisted of demographic data, questions related to the use of the Internet, the Internet Addiction Scale, and the Temperament Evaluation of Memphis, Pisa, Paris, and San Diego-auto questionnaire version (TEMPS-A) for adolescents. According to the findings of the present study, the relationship between Internet addiction and age, addictive substance use frequency, purpose, time spent on the internet, and type of temperament has been proven. Analysis results indicate that the risk of developing internet addiction is higher if an adolescent spends 1-3 hours and more than 3 hours daily (2.8 and 8.2 times, respectively). Increasing age numbers for 1 unit (year), the risk of internet addiction developing is decreasing by 11.3%. Hyperthymic temperament type decreases the risk of 70.9% of internet addiction developing. It is important to highlight importance of our results since practitioners can utilize our findings to create targeted treatments and prevent internet addiction in adolescents.

Background: Routine childhood vaccination, e.g., for diphtheria-tetanus-pertussis (DTP), might provide an additional protection towards SARS-CoV-2 infection. This concept of heterologous immunity was explored in healthy children receiving both DTP and inactivated SARS-CoV-2 vaccines. Methods: A cross-sectional study was performed on 154 healthy children aged 6–8 years old in Jakarta, Indonesia. Their vaccination status of DTP (including diphtheria-tetanus booster vaccine at 5 years old) and CoronaVac (from 6 years old) were recorded. Peripheral blood samples were collected from all participants, in which anti-diphtheria toxoid IgG, anti-SARS-CoV-2 S-RBD antibodies and T cell-derived IFN-g were measured. Results: Study participants with complete DTP vaccination had significantly higher titer of anti-diphtheria toxoid IgG than the ones without (median=0.9349 versus 0.2113 IU/mL; p<0.0001). Upon stratification based on DTP and CoronaVac vaccination statuses, participants with complete DTP and CoronaVac vaccinations had the highest titer of anti-SARS-CoV-2 S-RBD antibodies (median=1,196 U/mL) and the highest concentration of SARS-CoV-2-specific T cell-derived IFN-g (median=560.9 mIU/mL) among all groups. Conclusion: Healthy children aged 6-8 years old with complete DTP and CoronaVac vaccinations exhibited higher SARS-CoV-2-specific adaptive immune responses, particularly on their T-cell response. This suggests an additional benefit of routine childhood vaccination to generate protection against novel pathogens, presumably via heterologous immunity.

An increasing need for better agricultural practices that are sustainable to provide increased yields of crops for the ever increasing food demand to be met for the growing world population is a current necessity. It is estimated by the UN that in 2050 the world’s populace may be as much as 9.8 billion global, yet, farmers still face several obstacles, which includes soil degradation, extreme temperatures, and drought which as increasingly becoming more severe with climate changes. Plant health monitoring is a method that will help to increase awareness about plant enhancing by studying how to increase crop yields while decreasing the environmental impacts. The use of low-cost, controlled environments, soil quality, water levels, and pathogenic and pests attacks can be regularly monitored. Currently, several diagnostic technologies and portable point-of-use methods and technologies are employed for detection of diseases, although, the current available lab-based methods used for plant’s diagnostics test are inadequate for plant point-of-use monitoring. The promotion of use of these point of use methods will enable pathogen detection, poor plant growth, unsuitable environmental conditions and nutrient use efficiency allowing for immediate and timely corrective actions to ensure minimal damage to the plants with maximal yield. Increase in the use of sustainable agri practices are required for ensuring higher yields with minimal inputs and that are non-destructive to the land and the use of improved methodologies and technologies will be useful tools for achieving sustainable agriculture.

Traditional path planning algorithms have drawbacks in unmanned vehicle path planning, such as low efficiency, unsuitability for dynamic environments, and high computational complexity. To address these issues, this paper proposes a dynamic path planning method for unmanned vehicles that combines the A* algorithm with an improved Dynamic Window Approach (DWA). Firstly, a collision risk function is incorporated into the DWA algorithm to evaluate scores based on the braking distance corresponding to the current vehicle speed and the distance to obstacles, determining whether timely braking or obstacle avoidance is feasible. The earlier the braking or obstacle avoidance, the higher the score, thereby enhancing the evaluation algorithm of the DWA. Secondly, the key points extracted by the A* algorithm are used as temporary target points for the DWA algorithm, reducing the eight search directions to five. Finally, the key points of the A* algorithm’s path are set as the temporary end points for the DWA algorithm, integrating the two algorithms to plan a smoother curved path that can avoid unknown and dynamic obstacles. Simulation data demonstrates that compared to traditional artificial potential field methods, RRT, and Dijkstra’s algorithm, the new fusion algorithm reduces time by 11.71 seconds, a decrease of 6.9%, and shortens path length by 3.093 meters, a reduction of 4.16%, while increasing average linear velocity by 2.9%. The proposed algorithm ensures smoother paths while also making paths more rational and efficient

Background: In 2023, ChatGPT-4 has been impactful across several sectors including healthcare, where it aids in medical information analysis and education. Electronic Patient-Reported Outcomes (ePROs) play a crucial role in monitoring cancer patients’ post-treatment symptoms, enabling early in-terventions. However, managing the voluminous ePRO data presents significant challenges. This study assesses the feasibility of utilizing ChatGPT-4 for analyzing side effect data from ePROs. Methods: Thirty cancer patients were consecutively collected via a web-based ePRO platform, reporting side effects over 4 weeks. ChatGPT-4, simulating oncologists, dietitians, and nurses, analyzed this data and offered improvement suggestions, which were then reviewed by professionals in those fields. Results: Two oncologists, two dieticians and two nurses evaluated the AI’s performance across roles with 540 reviews. ChatGPT-4 excelled in data accuracy and completeness, and was noted for its empathy and support, enhancing communication and reducing caregiver stress. It was particularly effective as a dietician. Discussion: ChatGPT-4 shows promise in processing ePRO data with high accuracy, suggesting that AI can enhance clinical decision-making. Nevertheless, its limitations in emotional engagement highlight the need for AI to supplement, not replace, human care. Emphasizing the role of dietitians underscores the importance of nutritional advice in cancer care. Future studies will further explore the feasible application of AI and ePRO in cancer care clinical processes.

The solar energy can mitigate the power supply shortage in remote regions for portable irrigation systems. The accurate prediction of solar irradiance is crucial for determining the quantity of solar panels and the power capacity of photovoltaic power generation (PVPG) systems for mobile sprinkler machines. In this study, a prediction method is proposed to forecast the solar irradiance of typical irrigation areas. The impact of the meteorological parameters on the solar irradiance is studied, and four different parameter combinations are formed and considered as input to the prediction model. Based on meteorological data provided by ten typical radiation stations uniformly distributed nationwide, an Extreme Gradient Boosting (XGBoost) model optimized using the Whale Optimization Algorithm (WOA) is developed to predict the solar radiation. The prediction accuracy and stability of the proposed method are then evaluated for different input parameters through training and testing. The differences between the prediction performances of models trained based on single-station data and mixed data from multiple stations are also compared. The obtained results show that the proposed model achieves the highest prediction accuracy when the maximum temperature, minimum temperature, sunshine hours ratio, relative humidity, wind speed, and extraterrestrial radiation are used as the input parameters. The prediction effectiveness is also verified based on measured data. The WOA-XGBoost model has higher prediction accuracy than the XGBoost model, with predicted values falling within acceptable ranges. The model developed using mixed data of multiple stations can be applied for forecasting solar irradiance in different regions. This study provides a foundation for the optimization of the configuration of PVPG systems for mobile sprinkler machines.

Abstract Plant diseases are responsible for over 10% loss in global food production and have serious impacts on world-wide food security across several countries. Amongst these diseases, those caused by viroids are highly significant, accounting for extensive damage to crops every year and pose a major economic threat to agricultural crops. Combined infections with viroids, plant viruses and their satellites further exacerbate the situation. Vector transmission of viroids necessitates the use of pesticides, thus incurring high costs in addition to eliciting several detrimental effects on the ecosystem due to the noxious outcomes of pesticide use. The current review addresses the major economic impacts of viroids on crops, costs to the world economy and impacts on regions, farmers and consumers in addition to describing remediation measures to mitigate the losses caused by these subviral agents. Also described are issues relating to the pros and cons of pesticide use, the compelling need towards sustainable agricultrual practices while reducing pesticide use. In particular, the role of RNAi and genome editing technologies towards amelioration of agricultural loss is discussed.

This review delves into using natural antimicrobials in the dairy industry and examines various sources of these compounds, including microbial, plant, and animal sources. It highlights dairy products' most commonly used natural antimicrobials, such as nisin, lysozyme, lactoferrin, chitosan, and essential oils. It discusses the mechanisms by which they inhibit microbial growth and improve the shelf life of dairy products. Moreover, the review explores encapsulation technology as a promising approach for increasing the viability of natural antimicrobials. It discusses how encapsulation technology can protect these compounds from environmental factors that can reduce their effectiveness, such as pH, temperature, and oxygen exposure. The review also highlights the different materials that can be used for encapsulation, such as alginate, chitosan, and starch, and discusses their properties and suitability for encapsulating different natural antimicrobials. Finally, the review examines the benefits and challenges of using natural antimicrobials in dairy products. While natural antimicrobials offer several advantages, including improved safety, quality, and sensory properties of dairy products, it's crucial to be aware of the challenges associated with their use, such as potential allergenicity, regulatory requirements, and consumer perception. The review concludes by emphasizing the need for further research to identify and develop effective and safe natural antimicrobials for the dairy industry to ensure the quality and safety of dairy products for consumers.

Abstract: The aim of this study was to find out the incidence of anemia in pregnant women of Swat District; to analyze the iron variations and its dietary effects.Data were collected during the periods of January – September 2016. The study of samples comprised of 250 pregnant women in the different trimester. Blood sample from each woman was collected and full blood count (FBC) was conducted through Mindray BC-3000 plus hem analyzer for all pregnant individuals. Confirmed anemic cases were then examined for IDA with serum ferritin, serum iron, total iron binding capacity (TIBC) through Randox kit and serum transferrin saturation was estimated by formula (serum ferritin saturation =serum iron ×100/TIBC). The total number of participants in the first trimester were 50, among them 26 women were suffer from iron deficiency anemia (IDA) with 52% weightage of prevalence rate, (mean Hb concentration 9.602 ± 0.87 g/dl). The rates of IDA were 63.3%; ( mean Hb concentration 8.48 ± 1.24 g/dl) and 54%; ( mean Hb concentration 9.18 ± 1.28 g/dl), among 150 and 50 participants in the second and third trimester, respectively. A significant correlation was found between serum ferritin and Hb, serum ferritin against MCV and serum ferritin against MCH. The high prevalence of anemia was found 78.2% in the age group from 26-30 followed by 78.2% in the age group 36-40 years compared to those of other age groups in the second trimester. In this study the prevalence of IDA in third trimester is lower compared to first and second trimester.

This study addresses the critical issue of cardiovascular diseases (CVD) as the leading cause of death globally, emphasizing the importance of stent delivery catheter manufacturing. Traditional manufacturing processes, reliant on destructive end-of-batch sampling, present significant financial and quality challenges. The research highlights the need for non-destructive Process Analytical Technologies (PAT) to meet the increasing demand for these life-saving devices. The study employs a mixed-method approach, combining qualitative literature review and quantitative artefact development, to propose a closed-loop Cyber Physical Production System (CPPS). The proposed system aims to enhance real-time quality control, minimize costs, and improve manufacturing efficiency. Initial results demonstrate the system's effectiveness in reducing cycle times, improving stability, and significantly decreasing production misses. The findings suggest substantial financial savings and quality improvements, underscoring the potential of advanced control strategies in regulated medical device manufacturing. This study proposes a generalized CPPS framework to be applicable across diverse regulated manufacturing environments, ensuring optimal processing conditions and adherence to regulatory standards. The research concludes with the successful demonstration of innovative approaches and technologies, leading to improved product quality, patient safety, and operational efficiency in the medical device industry.

Artificial intelligence methods, especially artificial neural networks (ANNs), have increasingly been utilized for the mathematical description of physical phenomena in (metallic) material processing. Traditional methods often fall short in explaining the complex, real-world data ob-served in production. While ANN models, typically functioning as "black boxes," improve pro-duction efficiency, a deeper understanding of the phenomena, akin to that provided by explicit mathematical formulas, could enhance this efficiency further. This article proposes a general framework that leverages (CAE) ANNs to explain predicted results alongside their graphical presentation, marking a significant improvement over previous approaches and those relied on expert assessments. Unlike existing Explainable AI (XAI) methods, the proposed framework mimics the standard scientific methodology, utilizing minimal parameters for the mathematical representation of physical phenomena and their derivatives. Additionally, it analyzes the relia-bility and accuracy of the predictions using well-known statistical metrics, transitioning from deterministic to probabilistic descriptions for better handling of real-world phenomena. The proposed approach addresses both aleatory and epistemic uncertainties inherent in the data. The concept is demonstrated through the hot extrusion of aluminum alloy 6082, where CAE ANN models and predicts key parameters, and ChatGPT explains the results, enabling researchers and/or engineers to better understand the phenomena and outcomes obtained by ANNs.

Neurofibromatosis type1 (NF1) is an autosomal dominant disorder caused by mutations in the NF1gene. Although congenital pseudarthrosis of the tibia (CPT) has frequently been associated with NF1, the underlying molecular mechanism of CPT in these NF1 patients is yet ill-understood. The aim of the present study was to detect NF1 mutations from genomic DNA and to harbor variants associated with CPT in NF1 patients. Whole-exome sequencing was first carried out with samples from two patients with CPT in one NF1 family, and a novel mutation c.2324A>G (p.E775G) in NF1 gene was identified. Additionally, a missense variant c.455C>T (p.P152L) in BCOR gene completely co-segregated with the CPT phenotype within this family. Subsequently, NF1 and NF2 genes in four other unrelated patients with both NF1 and CPT were screened using targeted sequencing. Four mutations in NF1 gene, including two known mutations (c.2288T>C/p.L763P, c.574 C>T/p.R192*) and two novel mutations (c.768delT/p.F256Lfs*25, c.2229_2230delTG/ p.V744Qfs*23) were detected. Further study confirmed that CPT was present in NF1 families, and NF1 mutations were closely associated with these complex phenotypes. Moreover, the data from the current study indicated that male gender might be a susceptibility factor for CPT in NF1. Therefore, we speculated that BCOR variants might be related to CPT phenotype among male NF1 patients.

Image stitching is a crucial aspect of image processing. However, factors like perspective and environment often lead to irregular shapes in stitched images. Cropping or completion methods typically result in substantial loss of information. This paper proposes a method for rectifying irregularly images into rectangles using deformable meshes and residual networks. The method utilizes a convolutional neural network to quantify rigid structures of images. Choosing the most suitable mesh structure based on the extraction results, offering options such as triangular, rectangular, and hexagonal. Subsequently, the irregularly image, predefined mesh structure, and predicted mesh structure are input into a wide residual neural network for regression. The loss function comprises local and global, aimed at minimizing the loss of image information within the mesh and global target. This method not only significantly reduces information loss during rectification but also adapting to different images with various rigid structures. Validation on the DIR-D dataset shows this method outperforms state-of-the-art methods in image rectification.

Using the example of III-V nitrides crystallizing in a wurtzite structure (GaN, AlN, InN), this review presents the special role of hydrostatic pressure in studying semiconductor properties. Starting with a brief description of high pressure techniques for growing bulk crystals of nitride compounds, we focus on the use of hydrostatic pressure techniques in both experimental and theoretical investigations of special properties of nitride compounds, their alloys and quantum structures. The band gap pressure coefficient is one of the most important parameters in semiconductor physics. Trends in its behavior in nitride structures, together with trends in pressure-induced phase transitions, are discussed in the context of the behavior of other typical semiconductors. Using InN as an example, the pressure-dependent effects typical of very narrow bandgap materials, such as conduction band filling or effective mass behavior, are described. Interesting aspects of bandgap bowing in In-containing nitride alloys, including pressure and clustering effects, are discussed.Hydrostatic pressure also plays an important role in the study of native defects and impurities, as illustrated by the example of nitride compounds and their quantum structures. Experiments and theoretical studies on this topic are reviewed. Special attention is given to hydrostatic pressure and strain effects in short periods nitride superlattices. The explanation of the discrepancies between theory and experiment in the optical emission and its pressure dependence from InN/GaN superlattices led to the well-documented conclusion that InN growth on the GaN substrate is not possible. The built-in electric field present in InGaN/GaN and AlGaN/GaN heterostructures crystallizing in wurtzite lattice can reach several MV/cm, leading to drastic changes in the physical properties of these structures and related devices. It is shown how hydrostatic pressure modifies these effects and helps to understand their origin.

Berberine (BBR), as a natural isoquinoline alkaloid, has been demonstrated various pharmacological activities, and widely applied in the treatment of diseases. The quantitative analysis of BBR is important for its pharmacological researches and clinical applications. In the work, utilizing the specific interaction between BBR and triplex DNA, a sensitive and selective fluorescent detecting method was established with DNA-templated silver nanoclusters (DNA-AgNCs). After binding with the triplex structure in the template of DNA-AgNCs, BBR quenched the fluorescence of DNA-AgNCs and formed BBR-triplex complex with yellow-green fluorescence. The ratiometric fluorescence signal showed a linear relationship with BBR concentration in a range between 10 nM to 1000 nM, with a detect limit of 10 nM. Our method exhibited excellent sensitivity and selectivity, and it was further applied in BBR detection in real samples.

Azobenzene photoswitches are fundamental components in contemporary approaches aimed at light-driven control of intelligent materials. Significant endeavors are directed towards enhancing the light-triggered reactivity of azobenzenes for such applications and obtaining water-soluble molecules able to act as crosslinkers in a hydrogel. Here, we report the rational design and the synthesis of azobenzene/alginate photoresponsive hydrogels endowed with fast reversible sol-gel transition. We started with the synthesis of three cationic azobenzenes (AZO A, B, and C) and then incorporated them in sodium alginate (SA) to obtain photoresponsive supramolecular hydrogels (SMHGs). The photoresponsive properties of the azobenzenes were investigated by UV-Vis and ¹H NMR spectroscopy. Upon irradiation with 365 nm UV light, the azobenzenes demonstrated efficient trans-to-cis isomerization, with complete isomerization occurring within seconds. The return to the trans form took several hours, with AZO C exhibiting the fastest return, possibly due to higher trans isomer stability. In the photoresponsive SMHGs, the minimum gelation concentration (MGC) of azobenzenes was determined for different compositions, indicating that small amounts of azobenzenes could induce gel formation, particularly in 5 wt% SA. Upon exposure to 365 nm UV light, the SMHGs exhibited reversible gel-sol transitions, underscoring their photoresponsive nature. This research offers valuable insights into the synthesis and photoresponsive properties of cationic, water-soluble azobenzenes, as well as their potential application in the development of photoresponsive hydrogels.

Cancer cells show altered antioxidant defense systems, dysregulated redox signaling, and increased generation of reactive oxygen species (ROS). Targeting cancer cells through ROS-mediated mechanisms has emerged as a significant therapeutic strategy due to its implications in cancer progression, survival, and resistance. Extensive research has focused on selective generation of H2O2 in cancer cells for selective cancer cell killing by employing various strategies such as metal-based prodrugs, photodynamic therapy, enzyme-based systems, nano-particle mediated approaches, chemical modulators, and combination therapies. Many of these H2O2-amplifying approaches have demonstrated promising anticancer effects and selectivity in preclinical investigations. They selectively induce cytotoxicity in cancer cells while sparing normal cells, sensitize resistant cells, and modulate the tumor microenvironment. However, challenges remain in achieving selectivity, addressing tumor heterogeneity, ensuring efficient delivery, and managing safety and toxicity. To address those issues, H2O2-generating agents have been combined with other treatments leading to optimized combination therapies. This review focuses on various chemical agents/approaches that kill cancer cells via H2O2-mediated mechanisms. Different categories of compounds that selectively generate H2O2 in cancer cells are summarized, their underlying mechanisms and function are elucidated, preclinical and clinical studies as well as recent advancements are discussed, and their prospects as targeted therapeutic agents and their therapeutic utility in combination with other treatments are explored. By understanding the potential of these compounds, researchers can pave the way for the development of effective and personalized cancer treatments.

Rhodotorula mucilaginosa fungaemia is rare and highly resistance to antifungal therapy. We herein report a case involving a 31-year-old male admitted after a high-velocity road traffic accident. He sustained a grade IV liver injury with right hepatic vein thrombosis, necessitated an urgent laparotomy. Post-operatively, repeated imaging of the abdomen revealed presence of biloma. Percutaneous subdiaphragmatic drainage was done but appeared ineffective, prompting second surgery for a urgent hemi-hepatectomy. Patient then was nursed in the intensive care unit (ICU) however during his stay in the ICU he became more sepsis evident by worsening ventilatory support and rise in septic parameters from the biochemistry parameters. Despite on intravenous piperacillin-tazobactam and fluconazole, his septic parameters did not improve and a full septic workup was done and was found to be positive for Rhodotorula mucilaginosa from the blood cultures. After discussion with the infectious disease physicians and clinical microbiologist, it was decided to initiate a course of intravenous meropenem and amphotericin B based on minimum inhibitory concentration (MIC) values, considering the patient's extended ICU stay and catheter use. Eventually, successful weaning off mechanical ventilation was discharge from ICU care. This case underscores the necessity of individualized approaches, combining timely imaging, appropriate drainage techniques, and tailored treatments to optimize outcomes for such intricate post-traumatic complications.

Dengue virus (DENV), the causative agent of dengue fever (DF), is one of the most important mosquito-borne viruses that can infect humans. Although much effort has been made on prevention and control of dengue, there are currently no anti-viral drugs or worldwide approved vaccines yet. In this study, we immunized six-week-old Balb/c mice with DNA vaccine candidates E and NS1-2a of DENV serotype 2 or the combination of them (E+NS1-2a) via an electroporation (EP)-assisted intramuscular gene delivery system and evaluated the immune response and protection. The highest specific antibody titres and cytokine levels secreted by splenocytes as well as the highest survival rate were observed in the E+NS1-2a group, followed by E group and NS1-2a group. Our data suggested that the combination of E and NS1-2a delivered by EP may be a superior preventive strategy against DENV.

To screen and validate immunosuppressive factors in luminal- and basal-like breast cancer cell lines and tissue samples associated with malignant phenotypes. The mRNA microarray datasets, GSE40057 and GSE1561, were downloaded and remodelled. Differentially expressed genes (DEGs) were identified. Enrichment analyses performed and the online resources, GOBO and Kaplan-Meier Plotter, were employed to screen for immunosuppressive factors associated with breast cancer malignant phenotypes. qRT-PCR and western blot were used to validate the expression of CD274 and IL8 in cell lines and immunohistochemical detected the MIF and VEGFA on tissue microarrays. The results showed that CD274 and IL8 were both upregulated in basal-like cell lines. That MIF expression was dramatically increased in patients with breast cancer metastases (p<0.05) and that VEGFA expression positively correlates with breast cancer pathologic grade (p<0.05).During the formation and development of breast cancer, immune-related genes are always activated, and immunosuppressive factors CD274, IL8, MIF and VEGFA are upregulated. Such molecules could be used as biomarkers for breast cancer prognosis. However, because individual immune-related factors can play several biological roles, the mechanistic relationship between immunosuppressive factors and breast cancer malignant phenotypes and the feasibility of their application as drug targets require further investigation.

Active vitamin D derivatives (VDDs) – 1α,25-dihydroxyvitamin D3/D2 and their synthetic analogs – are well-known inducers of cell maturation with the potential for differentiation therapy of acute myeloid leukemia (AML). However, their dose-limiting calcemic activity is a significant obstacle to using VDDs as an anticancer treatment. We have shown that different activators of the NF-E2-related factor-2/Antioxidant Response Element (Nrf2/ARE) signaling pathway, such as the phenolic antioxidant carnosic acid (CA) or the multiple sclerosis drug monomethyl fumarate (MMF), synergistically enhance the antileukemic effects of various VDDs applied at low concentrations in vitro and in vivo. This study aimed to investigate whether glutathione, the major cellular antioxidant and the product of the Nrf2/ARE pathway, can mediate the Nrf2-dependent differentiation-enhancing activity of CA and MMF in HL60 human AML cells. We report that glutathione depletion using L-buthionine sulfoximine attenuated the enhancing effects of both Nrf2 activators concomitant with downregulating vitamin D receptor (VDR) target genes and the activator protein-1 (AP-1) family protein c-Jun levels and phosphorylation. On the other hand, adding reduced glutathione ethyl ester to dominant negative Nrf2-expressing cells re-stored both the suppressed differentiation responses and the downregulated expression of VDR protein, VDR target genes, as well as c-Jun and P-c-Jun levels. Finally, using the transcription factor decoy strategy, we demonstrated that AP-1 is necessary for the enhancement by CA and MMF of 1α,25-dihydroxyvitamin D3-induced VDR and RXRα protein expression, transactivation of the vitamin D response element, and cell differentiation. Collectively, our findings suggest that glutathione mediates, at least in part, the potentiating effect of Nrf2 activators on VDDs-induced differentiation of AML cells, likely through the positive regulation of AP-1.

In recent years, an interest in multimedia services has grown expeditiously where the main part is comprised of video. Firms as well as subscribers require higher resolutions, framerates and sampling precision which results to higher amount of data need for processing, storing and transmitting. Therefore, a big challenge arises for researchers to develop new compression standards which should reduce the huge amount of data and keep quality at the same level. This paper examines compression performance of the latest and currently most used video codecs, namely H.266/VVC, AV1, H265/HEVC and H.264/AVC. The test set consists of seven sequences with various content at 8K, Ultra HD and Full HD resolution and encoded to bitrates from 1 to 15 Mbps for Full HD and Ultra HD resolutions and from 5 to 50 Mbps for 8K resolution, respectively. Codec performance was measured using PSNR, SSIM and VMAF objective quality metrics. In terms of the Bjøntegaard-Delta (BD) model, the results showed that H.266/VVC outperforms all other codecs, namely H.264/AVC,H.265/HEVC and AV1, respectively. Averaged bitrate savings were approximately 78\% for H.266/VVC, 63\% for AV1 and 53\% for H.265/HEVC relative to H.264/AVC, 59\% for H.266/VVC, 22\% for AV1 compared to H.264/AVC and 46\% for H.266/VVC relative to AV1, all for 8K resolution. The results also showed that the performance varies depending on resolution – with higher resolution, the efficiency of newly developed codecs such as H.266/VVC and AV1 is greater, which confirmed the fact that the H.266/VVC and AV1 codecs have been primarily developed for videos at high resolutions as 8K and/or UHD.

Background: Severe eosinophilic asthma (SEA) represents a substantial global health burden. Benralizumab has been shown to restore good control of asthma. Robust data on benralizumab effectiveness over periods longer than 2 years are still scarce. Methods: This retrospective multicentric study was conducted on 108 Italian SEA patients treated with benralizumab for up to 36 months. Clinical outcomes were evaluated at 6, 12, 24 and 36 months. Partial and complete clinical remission (CR) were also assessed. Data were analysed either with descriptive statistics or using linear, logistic, and negative binomial mixed-effect regression models. Results: Benralizumab induced a persistent reduction in exacerbation rates (p

In this paper, we present a novel approach for text independent phone-to-audio alignment based on phoneme recognition, representation learning and knowledge transfer. Our method leverages a self-supervised model (wav2vec2) fine-tuned for phoneme recognition using a Connectionist Temporal Classification (CTC) loss, a dimension reduction model and a frame-level phoneme classifier trained thanks to forced-alignment labels (using Montreal Forced Aligner) to produce multi-lingual phonetic representations, thus requiring minimal additional training. We evaluate our model using synthetic native data from the TIMIT dataset and the SCRIBE dataset for American and British English, respectively. Our proposed model outperforms the state-of-the-art (charsiu) in statistical metrics and has applications in language learning and speech processing systems. We leave experiments on other languages for future work but the design of the system makes it easily adaptable to other languages.

Bicycle transport stands at the forefront of sustainable mobility initiatives, a cornerstone of European Union policy. While support for cycling is crucial, its advancement hinges upon the presence of high-quality, secure infrastructure for cyclists. Safety emerges as a paramount concern, influencing the viability of cycling as a mode of transportation, yet its perception varies among user demographics. In light of this, this article endeavors to examine and contrast cycling infrastructure across various European nations, alongside analyzing statistics pertaining to fatal traffic accidents involving cyclists. The findings underscore a substantial correlation between the quality of cycling infrastructure and the incidence of accidents. This correlation underscores the pressing need for robust infrastructure development and safety measures to bolster cycling as a safe and viable transportation option. By understanding the intricate interplay between infrastructure quality and safety outcomes, policymakers can better prioritize resources and enact measures to foster safer cycling environments, thus furthering the objectives of sustainable mobility on a continental scale.

The statistical technique, the multiple regression model, is employed to analyze the relationship between the dependent variable and several independent variables. The multicollinearity problem is one of the assumptions in the multiple regression model that occurred in the relationship among independent variables. The ordinal least square is the standard method to evaluate parameters in the regression model, but the multicollinearity problem affects the unstable estimator. The Liu regression is proposed to approximate the Liu estimators based on the Liu parameter to overcome multicollinearity. For this paper, we have proposed the modified Liu parameter to estimate the biasing parameter in scaling options to compare the ordinal least square estimator with two modified Liu parameters and six standard Liu parameters. The performance of the modified Liu parameter is considered with the generating independent variables from the multivariate normal distribution in the Toeplitz correlation pattern as the multicollinearity data, where the dependent variable is obtained from the independent variable multiplied with a coefficient of regression and with the error from the normal distribution. The mean absolute percentage error is computed as an evaluation criterion of estimation. For application, the Hepatitis C patients dataset is a real dataset to investigate the benefit of the modified Liu parameter. Through the simulation and real dataset, it can be seen from the results that the modified Liu parameter outperforms the other Liu parameters and the ordinal least square estimator. It can recommend the user for estimating parameters by using the modified Liu parameter when the independent variable exits the multicollinearity problem.

Three-dimensional flexible piezoresistive porous sensors have been used in health diagnosis and wearable devices. By utilizing 3D printed sacrificial mold casting with highly conductive polymer composites, porous sensors with high conductivity and complex structures were achieved. Traditional conductive polymer composites are usually heated using external heat sources, which are time and energy consuming. However, in this study, conductive porous sensors with triply periodic minimal surface (TPMS) structures were manufactured using self-resistance electric heating by utilizing the conductive nature of the polymers. The porous structures were designed based on Diamond (D), Gyroid (G), and I-WP (I) unit cells of the TPMS. The use of self-resistance electric heating has improved the compression performance and piezoresistive response of the structures. Among these structures, the D-based structure exhibited the maximum response strain (61 %), with a corresponding resistance response value of 0.97, which increased by 10.26 % compared to that of the structures heated by using the external heat sources. This study offers a new perspective on designing and optimizing porous materials with specific functionalities, particularly in the realm of flexible and portable piezoresistive sensors.

In marine ecosystems communication among microorganisms is crucial since the distance is significant if considered on a microbial scale. One of the ways used by microorganism cells to reduce this gap is the production of extracellular vesicles. Marine bacteria release extracellular vesicles (EVs), small membrane-bound structures of 50 to 250 nm diameter, into their surrounding environment. The vesicles contain various cellular compounds, including lipids, proteins, nucleic acids, and glycans. EVs may mediate the communication between microorganisms in aquatic environments thus influencing ecosystem function and determining the structure and composition of microbial populations. This review will focus on marine bacterial EVs analysing their structure, composition, functions, and applications.

The purpose of the present study was to examine the relationships between bat swing speed (BSS) and muscle thickness and lateral asymmetry of the trunk and limbs in collegiate baseball players. Twenty-four collegiate baseball players participated in this study. The maximum BSS in hitting a teed ball was measured using a motion capture system. The muscle thicknesses of the trunk (upper abdominal rectus, central abdominal rectus, lower abdominal rectus, abdominal wall, and multifidus lumborum), upper limb, and lower limb were measured using a B-mode ultrasonography. Lateral asymmetry between each pair of muscles was determined as the ratio of the thickness of the dominant side to that of the non-dominant side. Significant positive correlations were observed between BSS and muscle thicknesses of the abdominal wall and multifidus lumborum on the dominant side (r = 0.426 and 0.431, respectively; p < 0.05), while nearly significant positive correlations were observed between BSS and muscle thicknesses on the non-dominant side. No significant correlations were found between BSS and lateral asymmetry of all muscles. These findings indicate the importance of the trunk muscles for bat swing, and the lack of association between BSS and lateral asymmetry of muscle size.

The tailoring of the surface properties of cellulose nanocrystals (CNCs) to meet various requirements in environmental, food, and material areas has always been of great interest. In this study, the surface chemistry of CNCs was noncovalently modified by cetyltrimethylammonium bromide (CTAB), followed by characterizations and an application as a coating material for interfacial interaction investigation over various substrates. Due to the CTAB modification, the surface charge of the CNCs was neutralized, resulting in an increased size of each nanocrystal at the aqueous status and the aggregated microfibers when dried up. The CTAB modification not only decreased the crystallinity of the samples from 48.57% to 9.12% but also hydrophobized the CNCs and decreased their total surface energy. Finally, the adsorption behavior of the CNCs and CTAB-CNCs over nonionic, anionic, and cationic polymers was investigated by ellipsometry. Based on the thickness of the CNC and CTAB-CNC layers over 2-Hydroxyethyl cellulose (HEC), carboxymethyl cellulose (CMC), and polyethyleneimine (PEI), we proposed that the adsorption behavior was overall influenced by electrostatic interaction, hydrogen bonding, and van der Waals forces and the thickness of the adsorbed layers could be impacted by both the surface charge and the size of the crystals.

Chronic exposure to the nephrotoxic metal pollutant, cadmium (Cd), has been associated with hypertension, but the mechanism by which it raises blood pressure is not understood. We hypothesize that exposure to Cd reduces the glomerular filtration rate (GFR), which in turn, causes a rise in blood pressure. Data were collected from 447 Thai subjects with a mean age of 51.1 years, of which 48.8% had hypertension, 15.4% had diabetes and 6.9% had an estimated GFR (eGFR) below 60 mL/min/1.73 m2 (low eGFR). The mean blood and urinary Cd concentrations were 2.75 and 4.23 µg/L, respectively. The prevalence odds ratio (POR) for hypertension rose twofold in those with blood Cd levels of 0.61-1.69 µg/L or urinary Cd excretion levels ≥ 0.98 µg/g creatinine. In the hypertensive group, the eGFR was inversely associated with age (β =−0.517), the Cd excretion rate (β = −0.177), and diabetes (β = −0.175). Mean eGFR in the normotensive group was 7.5 mL/min/1.73 m2 higher than the hypertensive with a similar Cd body burden. Mean systolic blood pressure (SBP) in those with low or medium eGFR plus heavy Cd body burden was 9.5 mmHg higher than those with the same Cd body burden and a normal eGFR. By mediation analysis, a 22.7% increase in SBP and a 5% increase in diastolic blood pressure (DBP) were attributable to the effect of Cd on GFR. Thus, a rise of blood pressure appears to be a consequence of GFR loss due to Cd-induced kidney damage. This finding is consistent with a well-known role of the kidney in long-term blood pressure regulation.

Supramolecular solvent (SUPRAS) has received increasing interest as an innovative, efficient, and green solvent for the effective extraction and separation of bioactive compounds from natural resources. However, studies on the use of SUPRAS for the extraction of phenolic components from plants, which are highly valued in food products due to their excellent antioxidant capacity, are still lacking. The present study developed a green ultrasound-assisted and efficient SU-PRAS method to simultaneously determine three phenolic acids in Prunella vulgaris by high-performance liquid chromatography (HPLC) and the experimental parameters were optimized in detail. The efficiency and antioxidant properties of the phenolic compounds obtained by different extraction methods were also compared. Under the optimal conditions, the extraction efficiency of SUPRAS, prepared with octanoic acid reverse micelles dispersed in ethanol-water, was substantially higher than conventional organic reagents. Moreover, this SUPRAS method also showed more significant antioxidant capacities. The confocal laser scanning microscopy (CLSM) images presented the spherical droplet structure of SUPRAS (A well-defined circle), which coincided with the position of the fluorescence position of phenolic acids. The phenolic acids were encapsulated in the vesicles by the SUPRAS droplets, which indicated the efficient extraction capacities of SUPRAS for the target compounds. Finally, combined with the CLSM method, the mechanism of the proposed method was further clarified, and the superior extraction performance of SUPRAS was theoretically demonstrated through molecular dynamics simulations. In comparison with conventional methods, the higher extraction efficiency of SUPRAS can be illustrated by the larger solvent contact surface area, more types of hydrogen bonds between extractants and supramolecular solvents, and stronger and more stable interaction forces. The results of the theoretical studies are in rational agreement with the experimental outcome.

Grayscale Lithography (GSL) is an alternative approach to the standard Binary Lithography in MEMSfabrication, enabling the fabrication of complicated arbitrary 3D structures on the wafer, without the need for multiple masks and exposure steps. Despite its advantages, GSL’s effectiveness is highly dependent on controlled lab conditions, equipment consistency, and finely-tuned photoresist exposure and etching processes. This works presents a thorough investigation of the challenges of GSL for Silicon (Si) wafers and presents a detailed approach on how to minimize the fabrication inaccuracies, aiming to replicate the intended design as closely as possible. Utilizing a maskless laser writer, all aspects of the GSL as analyzed, from photoresist (PR) exposure parameters to Si etching conditions. A practical application of GSL is demonstrated in the fabricationof 4 μm deep Silicon Fresnel Lenses for Long Wave Infrared imaging (8-12 μm). The surface topography of a Fresnel lens is a good case to apply GSL as it has varying shapes and size features that need to be preserved.. The final fabricated lens profiles show good match with the initial design and demonstrate successful etching of coarse and fine features and demonstrating images taken with an LWIR camera.

Electromagnetic actuation can support many fields of technology, such as robotics or biomedical applications. In this context, fully understanding the system behavior and proposing a low-cost package for feedback control is challenging. Modeling the electromagnetic force is particularly tricky because it is a nonlinear function of the actuated object’s position and coil’s current. Measuring in real time the position of the actuated object with the precision required for accurate motion control is also nontrivial. In this study, we propose a novel, cost-effective electromagnetic set-up to achieve position control via visual feedback. We actuate vertically and under different experimental conditions a 10 mm diameter steel ball hanging on a low-stiffness spring, demonstrating good tracking performance (the position error remains within ±0.5 mm with a negligible phase delay in the best scenarios). The experimental results confirm the feasibility of the proposed set-up, which is characterized by minimum complexity and realized with off-the-shelf and cost-effective components. For these reasons, such a contribution helps to understand and apply electromagnetic actuation even further.

With the application of high-precision, enormous rotating equipment and the addition of harsh working conditions, the advantages of dry gas sealing technology are increasingly obvious. Herein, research on the dynamic stability of dry gas seals is reviewed based on their operating mechanism. The influence of the dry gas seal structure, vibration response, and dynamic followability on the reliability of the shaft end sealing system of rotating machinery is the focus of current dry gas sealing technology. This work reviews the research history; analyzes the key coefficient of instability of the sealing system under external disturbances and the existing research on stability models; discusses the influence of starting and stopping characteristics, working conditions, and groove parameters on the stability of dry gas seals; and points out the shortcomings in the existing research. In addition, potential developments in dynamic stability are proposed, including improving model accuracy, improving experimental techniques, or applying intelligent control and optimization methods to enhance the dynamic stability of the sealing system. Finally, the development prospects for dry gas sealing technology in intelligent monitoring and wide temperature range adaptations are discussed, and theoretical guidance for improving the dry gas seal system is provided.

Necrotizing enterocolitis (NEC) is a major cause of neonatal morbidity and mortality. Although the specific etiology is unknown, previous research shows that maternal environment may be a contributing factor. Gestational stress may lead to the development of NEC by interfering with the barrier function of the intestinal epithelial barrier. The migration of cells from the crypts to the tips of the villi is crucial in maintaining the integrity of the epithelial barrier. Previously, the Martin lab found that pups from psychologically stressed pregnant dams were more susceptible to NEC-like injury. We have also shown that investigated how stress signaling and zinc impact intestinal epithelial wound healing. Through a scratch assay, human Caco-2 cell migration was studied over 24 hours, and the percent wound healing was calculated. We found that only hydrocortisone at the 30 ug/ml concentration led to an inhibition of wound healing, and that zinc was unable to rescue hydrocortisone mediated inhibition.

With the increasing use of automatic transmissions in passenger vehicles, there is a growing need for improved gear shifting control strategies that aim to enhance performance and fuel efficiency. This paper introduces a knowledge-based fuzzy control system designed specifically for automatic transmissions in light vehicles. The proposed system utilizes a fuzzy inference system as the controller, enabling the emulation of the driver’s perceptions during the gear shifting process. Consequently, the input signal consists of variables that are either sensitive to or observable by the driver, while the output represents the selected gear. The paper evaluates three distinct control strategies, each based on different inputs. These inputs include the longitudinal velocity of the vehicle, the angular velocity of the engine, or a combination of both, along with the time-derivative of the throttle valve opening. Through the evaluation, it is observed that the combination of inputs yields significantly improved performance. Therefore, the methodology presented in this paper demonstrates that the combined input approach is more effective for gear shifting control.

The safety concerns associated with current lithium-ion batteries are a significant drawback. A short-circuit within the battery's internal components, such as those caused by a car accident, can lead to ignition or even explosion. To address this issue, a polymer shear thickening electrolyte, free from flammable solvents, has been developed. It comprises a star-shaped oligomer derived from a trimethylolpropane (TMP) core and polyether chains, along with the inclusion of 20 wt.% nanosilica. Notably, the star-shaped oligomer serves a dual function as both the solvent for the lithium salt and the continuous phase of the shear thickening fluid. The obtained electrolytes exhibit an ionic conductivity of 10-6 S cm-1 at 20 °C and 10-4 S cm-1 at 80 °C, with a high Li+ transference number (t+ = 0.79). A nearly thirtyfold increase in viscosity to a value of 1187 Pa s at 25 °C and a critical shear rate of 2 s-1 were achieved. During impact, this electrolyte could enhance cell safety by preventing electrode short-circuiting.

In the rapidly evolving field of real estate economics, the prediction of house prices continues to be a complex challenge, intricately tied to a multitude of socio-economic factors. However, traditional predictive models have often overlooked the spatial interdependencies that play a vital role in shaping housing prices. This study applies Graph Neural Networks (GNNs) on Open Statistics Knowledge Graphs to model spatial dependencies and predict house prices across Scotland’s 2011 data zones. To this end, integrated statistical indicators are retrieved from the official Scottish Open Government Data portal. The three representative GNN algorithms employed - ChebNet, GCN, and GraphSAGE - demonstrate higher prediction accuracy than traditional models, including the tabular-based XGBoost and a simple Multi-Layer Perceptron (MLP). In addition, local and global explainability are employed to increase transparency and trust in the predictions made by the most accurate GNN - GraphSAGE. The global feature importance is determined by a logistic regression surrogate model while the local, region-level understanding of the GNN predictions is achieved through the use of GNNExplainer. Explainaibility results are compared with those from a previous work that applied the XGBoost machine learning algorithm and the SHapley Additive exPlanations (SHAP) explainability framework on the same dataset. Interestingly, both global surrogate model and the SHAP approach underscored the Comparative Illness Factor, a health indicator, and the ratio of detached dwellings as the most crucial features in the global explainability. In the case of local explanations, while both methods showed similar results, the GNN approach provided a richer, more comprehensive understanding of the predictions for two specific data zones.

NACA 0015 and NACA 4415 aerofoil are most common four digits and broadly used aerodynamic shape. Both of the shapes are extensively used for various kind of applications including turbine blade, aircraft wing and so on. NACA 0015 is symmetrical and NACA 4415 is unsymmetrical in shape. Consequently, they have big one-of-a-kind in aerodynamic traits at the side of widespread differences of their utility and performance. Both of them undergo the same fluid principle while applied in any fluid medium giving dissimilar outcomes in aerodynamics behavior. On this work, experimental and numerical investigation of each NACA 0015 and NACA 4415 is done to decide their performance. For this purpose, aerofoil section is tested for a prevalence range attack of angle (AOA). The study addresses the performance of NACA 0015 and NACA 4415 and evaluates the dynamics of flow separation, lift, drag, pressure and velocity contour and so on. This additionally enables to layout new optimistic aerofoil, which is critical to enhance the efficiency and performance of an aircraft in terms of lift enhancement and drag reduction.

Natural vegetation restoration can take decades to achieve and requires information on species composition and trend to inform management strategies. Here we demonstrate the potential and portability of drone, dove and Sentinel-2 imagery for species level classification and trajectory monitoring using three study sites with different revegetation histories. Drone imagery (4 cm) was classified using random forests. Dove (3 m) and Sentinel-2 (10 m) images were acquired close to the anniversary of the drone flights and converted into fractional cover maps showing the proportion of exotics, natives and other land covers using ordinary least squares (OLS) and geographically weighted regression (GWR). The time series of fractional cover maps were converted into positive and negative slope and second-order curvature and summarised as one RGB composite to illustrate trend and observe exotic expansion. Drone classification accuracies ranged from 73%-76% when applied to the full plant species list and between 93% and 97% when grouped into natives, exotics, and other land covers. GWR outperformed OLS for all fractional cover mapping and GWR with dove imagery was more accurate than with Sentinel imagery. The combination of very high-resolution drone acquired imagery with the versatility of dove acquired imagery arms land managers with highly accurate species composition and their spatio-temporal dynamics to promote timely intervention.

Development of the continental shelf has accelerated significantly as nations around the world seek to harness offshore renewable energy. Many areas marked for development align with submerged palaeolandscapes. Poorly understood and difficult to protect, these vulnerable, prehistoric landscapes provide specific challenges for heritage management. Indeed, there now appears to be a schism between what underwater cultural heritage policy intends and what it is achieving in practice. Shortcomings in international and national legislature ensures that large parts of the continental shelf, including areas under development, may have little or no legal protection.

While Europe was beginning to deal with the resurgence of COVID-19 due to the Delta variant, the European football championship took place, June 11 - July 11, 2021. We studied the inversion in the decrease/increase rate of new SARS-COV-2 infections in the countries of the tournament, investigating the hypothesis of an association. Using a Bayesian piecewise regression with a Poisson Generalized Linear Model, we looked for a changepoint in the timeseries of the new SARS-COV-2 cases of each country, expecting it to appear not later than two to three weeks after the date of their first match. The two slopes, before and after the changepoint, were used to discuss the reversal from a decreasing to an increasing rate of the infections. For 17 out of 22 countries (77%) the changepoint came on average 14.97 days after their first match [95% CI 12.29 to 17.47]. For all those 17 countries, the changepoint coincides with an inversion from a decreasing to an increasing rate of the infections. Before the changepoint, the new cases were decreasing, halving on average every 18.07 days [95% CI 11.81 to 29.42]. After the changepoint, the cases begin to increase, doubling every 29.10 days [95% CI 14.12 to 49.78]. This inversion in the SARS-COV-2 case rate, happened during the tournament, provides evidence in favor of a relationship

Wheat, a component of the staple diet globally, is a common food allergen in children. The symptoms of wheat allergy (WA) range from skin rash to shortness of breath, significantly impairing quality of life. Following initial clinical suspicion, individuals may undergo wheat allergen-specific skin prick test (SPT), blood test for serum immunoglobulin E (sIgE) levels or oral food challenge. Conventional management of WA lies in wheat avoidance, yet accidental consumption may be inevitable owing to the ubiquity of wheat in various food products. This article aims to provide an overview of the immunologic pathway of WA, followed by its novel diagnostic methods, namely alcohol-soluble SPT extracts, component-resolved diagnosis and basophil activation test (BAT). The mechanisms underlying wheat allergen-specific oral immunotherapy (OIT) as well as a summary of the efficacy, tolerability and safety of related clinical trials will then be discussed.

Rubber compounds based on styrene-butadiene rubber, ethylene-propylene-diene-monomer rubber and the combinations of both rubbers were cured with different sulfur and peroxide curing systems. In sulfur curing systems, two type of accelerators, namely N-cyclohexyl-2-benzothiazole sulfenamide, tetramethylthiuram disulfide and combinations of both accelerators were used. In peroxide curing systems, dicumyl peroxide, and combination of dicumyl peroxide with zinc diacrylate or zinc dimethacrylate, respectively were applied. The work was focused on investigation of the curing system composition as well as type of the rubber or rubbers combinations on curing process, cross-link density and physical-mechanical properties of vulcanizates. The dynamic-mechanical properties on the selected vulcanizates were examined, too. The result revealed correlation between the cross-link density and physical-mechanical properties. Similarly, there was recorded certain correlation between cross-linking degree and glass transition temperature. The tensile strength of vulcanizates based on rubbers combinations was higher when compared to that based on pure rubbers, which points out the fact that by rubbers combination, not only the features of both elastomers can be combined, but also improved tensile characteristics can be achieved. When compared to vulcanizates cured with dicumyl peroxide, materials cured with sulfur system exhibited higher tensile strength. By application of co-agents in peroxide vulcanization, the tensile strength overcame the tensile behavior of sulfur cured vulcanizates.

β3-Adrenoceptors mediate several functions in rodents that could be beneficial for the treatment of obesity and type 2 diabetes. This includes promotion of insulin release from the pancreas, of cellular glucose uptake, of lipolysis, and of thermogenesis in brown adipose tissue. In combination, they lead to a reduction of body weight in several rodent models including ob/ob mice and Zucker diabetic fatty rats. These findings stimulated drug development programs in various pharmaceutical companies, and at least nine β3-adrenoceptor agonists have been tested in clinical trials. However, all of these projects were discontinued due to lack of clinically relevant changes of body weight. Following a concise historical account of discoveries leading to such drug development programs we discuss species differences that explain why β3-adrenoceptors are not a meaningful drug target for the treatment of obesity and type 2 diabetes in humans.

Genomic surveillance represents an important strategy for understanding evolutionary mechanisms, transmission profile, and infectivity of different SARS-CoV-2 variants. We assessed the epidemiological profile of 366 individuals who tested positive for SARS-CoV-2 from 29 municipalities in Rondônia between December 2021 to March 2022. Samples were collected, RNA was ex-tracted and screened using RT-qPCR for Alpha, Beta, Gamma, Delta and Omicron VOCs and viral quantification was performed. Sequences were analyzed for phylogeny, mutations and lineages. Of the samples analyzed, 93.71% were positive for the Omicron variant and 6.28% were positive for the Delta variant. The symptoms observed were cough, sore throat, and fever, with a mean duration of 5 days; no hospitalizations or deaths were reported. We noted that among the positive individuals, 51% had been immunized with two doses, 22% received three doses, 13% received one dose, and 13% were not immunized. Just 242 samples were amenable to analysis for alignment and phylogenetic characterization; corresponding to variants BA.1 and BA.1.1; a total of 120 mutations were identified, 36% of which were found in the S gene. In conclusion, there was a high frequency of mutations in the SARS-CoV-2 genome, but no record of clinical severity, demonstrating the positive effect of vaccination.

Over a year into the COVID-19 pandemic, there is growing evidence that SARS-CoV-2 infections among dogs are more common than previously thought. In this study, the prevalence of SARS-CoV-2 antibodies was investigated in two dog population. The first group was comprised of 1069 dogs admitted to the Veterinary Teaching Hospital for any given reason. The second group included dogs that shared households with confirmed COVID-19 cases in humans. This study group numbered 78 dogs. In COVID-19 infected households, 43.9% tested ELISA positive, and neutralisation antibodies were detected in 25.64% of dogs. Those data are comparable with the secondary attack rate in the human population. With 14.69% of dogs in the general population testing ELISA positive, there was a surge of SARS-CoV-2 infections within the dog population amid the second wave of the pandemic. Noticeably seroprevalence of SARS-CoV-2 in the dog and the human population did not differ at the end of the study period. Male sex, breed and age were identified as significant risk factors. This study gives strong evidence that while acute dog infections are mostly asymptomatic, they can pose a significant risk to dog health. Seropositive dogs had a 1.97 times greater risk for developing central nervous symptoms.

Despite substantial evidence supporting the efficacy of prebiotics for promoting host health and stress resilience, few experiments present evidence documenting the dynamic changes in microbial ecology and fecal microbial-modified metabolites across time. Furthermore, the literature reports a lack of reproducible effects of prebiotics on specific bacteria and bacterial-modified metabolites. The current experiments examined whether consumption of diets enriched in prebiotics (galactooligosaccharides, GOS and polydextrose, PDX) compared to control diet, would consistently impact the gut microbiome and microbial-modified bile acids across time and between two research sites. Male Sprague Dawley rats were fed control or prebiotic diets for several weeks, and their gut microbiome and metabolome were examined using 16S rRNA gene sequencing and untargeted LC-MS/MS analysis. Dietary prebiotics altered beta diversity, relative abundances of bacterial genera, and microbially modified bile acids across time. PICRUSt2 analyses identified four inferred functional metabolic pathways modified by prebiotic diet. Correlational network analyses between inferred metabolic pathways and microbial-modified bile acids revealed deoxycholic acid as a potential network hub. All these reported effects were consistent between the two research sites supporting the conclusion that dietary prebiotics robustly changed the gut microbial ecosystem. Consistent with our previous work demonstrating that GOS/PDX reduces the negative impacts of stressor exposure, we propose that ingesting a diet enriched in prebiotics facilitates the development of a health-promoting gut microbial ecosystem.

Critical distance concerns precise digital levelling, which has inaccurate results at a certain sighting distance. The influence of critical distance on a measured height difference has been confirmed by calibrating certain digital levels and their appropriate code devices on a vertical comparator under laboratory conditions. The paper describes the research based on experimental measurements done to find the influence of critical distance on height differences obtained by precise digital levels of Leica NA3003 and DNA03. The processing of the measurement results consisted of de-fining a random error on a station by using parameter estimation of an error model to specify a partial error on a station dependent on sighting distance and then the processing phase continues with the finding the relation between sighting distance and dispersion of height differences ac-quired by digital levelling under terrain conditions. The theoretical part involves the development of levelling accuracy theories that vary over time by view on random and systematic error propagation. The numerical and graphical solution of the experimental measurements involves ordering the height differences into sighting groups according to the sighting distances and the computed standard deviations, which represent a measure of height differences dispersion. The suspicious sighting groups are highlighted in the table and compared with theoretical data pro-vided by authors of calibrating the same digital levels

In a motor-controlled hydraulic cylinder (MCC), the two chambers of the cylinder are directly connected to single or multiple fixed-displacement hydraulic pumps driven by electric servo motors. In contrast to a valve-controlled cylinder, an MCC does not have valve throttling, resulting in an improved system energy efficiency. Among various MCC topologies, the two-motor-two-pump (2M2P) MCC distinguishes itself through several notable advantages, including precise cylinder pressure control and eliminating mode switch oscillations. Nevertheless, there are remaining challenges in fully realizing its operations across four quadrants and establishing an effective load-holding function within these operations. This study bridges this gap by implementing a 2M2P MCC prototype on a laboratory knuckle boom crane, enabling operation across all four quadrants. Experimental results indicate that position tracking errors remain within ±2.5 mm across three cases. Furthermore, smooth intersection of cylinder bore side and rod side pressures is observed during transitions between quadrants. In conclusion, the proposed 2M2P MCC demonstrates seamless operation throughout all quadrants, with the load-holding function smoothly activating and deactivating in all four quadrants.

Heavy metals constitute pollutants particularly common in air, water, and soil. They are present in both urban and rural environments, on land and in marine ecosystems, causing serious environmental problems since they do not degrade easily, remain almost unchanged for long periods, and bioaccumulate. Detection, though especially quantification, is a systematic process as monitoring of their levels needs to be carried out at regular intervals since there is often seasonal variation. The need for rapid and low-cost determination of metals is therefore considerable. In the present study atomic absorption spectroscopy (AAS), using a flame or graphite furnace, and square wave anodic stripping voltammetry (SWASV), using a bismuth thin film electrode, a sensitive voltammetric method is being compared and analytically validated. Atomic absorption spectroscopy (AAS) represents a well-established analytical technique while anodic stripping voltammetry is being criticized for its applicability in complicated sample matrices such as soil samples. This sample-handling challenge is being investigated in the present study. The results show that both methods AAS and ASV were satisfactorily correlated and showed that the concentration of metals is lower than the limit values, but with increasing trend. Therefore, continuous monitoring of metal levels in the urban complex of the city is necessary and a matter of great importance. Regarding Cd, the detection limits of Cd are lower compared to those of AAS when using the graphite furnace, while an overestimation was noted when using flame-AAS in comparison with those found with SWASV. The SWASV method has the advantage of being cheaper and faster, enabling the simultaneous determination of heavy elements across the range of concentrations that these elements can occur in Mediterranean soils. Additionally, we applied a dsDNA-modified electrode which can be used in the speciation analysis of Cu(I) and Cu(II). The changes in the characteristic peaks of guanine and adenine can be applied in the redox speciation analysis of copper in soil which represents an issue of great importance.

The production of cheese, a beloved culinary delight worldwide, faces challenges in maintaining consistent product quality and operational efficiency. One crucial stage in this process is determining the precise cutting time during curd formation, which significantly impacts the quality of the cheese. Misjudging this timing can lead to the production of inferior products, harming a company's reputation and revenue. Conventional methods often fall short of accurately assessing variations in coagulation conditions due to the inherent potential for human error. To address this issue, we propose an anomaly detection-based approach. In this approach, we treat the class representing curd formation as the anomaly to be identified. Our proposed solution involves utilizing a one-class, fully convolutional data description network, which we compared against several state-of-the-art methods to detect deviations from the standard coagulation patterns. Encouragingly, our results show F1 scores of up to 0.92, indicating the effectiveness of our approach.

Breast cancer, when advancing to a metastatic stage, involves the liver, impacting over 50% of cases and significantly diminishing survival rates. Presently, a lack of tailored therapeutic protocols for Breast Cancer Liver Metastasis (BCLM) underscores the need for a deeper understanding of molecular patterns governing this complication. Therefore, by analyzing differentially expressed genes (DEGs) between primary breast tumors and BCLM lesions, it aimed to shed light on the diversities of this process. This research investigates Breast cancer liver metastasis relapse by employing a comprehensive approach that integrates data filtering, Gene Ontology and KEGG Pathway Analysis, Overall Survival analysis, identification of the Alteration in the DEGs, Visualization of Protein-Protein Interaction Network, Signor 2.0, identification of positively correlated genes, screening results of the function of hub genes, immune cell infiltration analysis, genetic alternation analysis, Copy number variant analysis, Gene to mRNA interaction, transcription factor analysis , autodocking and identification of Potential Treatment Target. This study’s integrative approach unveils metabolic reprogramming, suggesting altered PCK1 and LPL expression as key in breast cancer metastasis recurrence.

Human microbiome data from genomic sequencing technologies is fast accumulating, giving us insights into bacterial taxa that contribute to health and disease. Predictive modeling of such microbiota count data for classification of human infection from parasitic worms such as helminths can help in detection and management across global populations. Real-world datasets of microbiome experiments are typically sparse containing hundreds of measurements for bacterial species, of which only a few are detected in the bio-specimens that are analyzed. This feature of microbiome data produces the challenge of needing more observations for accurate predictive modeling and has been dealt with previously using different methods of feature reduction. To our knowledge, integrative methods such as transfer learning has not been explored in the microbiome domain yet, as a way to deal with data sparsity by incorporating knowledge of different but related datasets. One way of incorporating this knowledge is by using a meaningful mapping among features of these datasets. In this paper, we claim that this mapping would exist among members of each individual cluster grouped based on phylogenetic dependency among taxa and their association to the phenotype. We validate our claim by showing that models incorporating associations in such a grouped feature space result in no performance deterioration for the given classification task. In this paper, we test our hypothesis using classification models that detect helminth infection in microbiota of human fecal samples obtained from Indonesia and Liberia countries. In our experiments, we first learn binary classifiers for helminth infection detection by using Naive Bayes, Support Vector Machines, Multilayer Perceptrons, and Random Forest methods. In the next step, we add taxonomic modeling using the SMART-scan module to group the data, and learn classifiers using the same four methods, to test the validity of the achieved groupings. We observed a 6% to 23% and 7% to 26% performance improvement based on the Area Under ROC Curve (AUC) and Balanced Accuracy(Bacc) measures, respectively, over 10 runs of 10-fold cross-validation. These results show that using phylogenetic dependency for grouping our microbiota data actually results in a noticeable improvement in classification performance for helminth infection detection. These promising results from this feasibility study demonstrate that methods such as SMART-scan can be utilized in the future for knowledge transfer from different but related microbiome datasets by phylogenetically-related functional mapping, to enable novel integrative biomarker discovery.

Cellular senescence has recently been recognized as a hallmark of cancer, reflecting its association with aging and inflammation, its role as a response to deregulated proliferation and oncogenic stress, and its induction by cancer therapies such as radiation, chemotherapy, and targeted agents. While such therapy-induced senescence (TIS) has been linked to resistance, recurrence, metastasis and normal tissue toxicity, TIS has the potential to enhance therapy response and stimulate anti-tumor immunity. In this review, we examine the Jekyll and Hyde nature of senescent cells (SnCs), with a particular focus on how their persistence while expressing the senescence-associated secretory phenotype (SASP) modulates the tumor microenvironment through autocrine and paracrine mechanisms. Via the SASP, the formation of SnCs may alternately mediate resistance or response to conventional therapy. Further, toward fulfilling the unmet potential of cancer immunotherapy, we consider how SnCs may influence tumor inflammation and serve as a source of antigen to potentiate anti-tumor immunity. This new view suggests treatment strategies based on inducing TIS to enhance immune checkpoint blockade. Finally, we describe strategies for mitigating the detrimental effects of senescence, such as modulating the SASP or targeting SnC persistence, toward enhancing the benefits of cancer treatment.

Accurately predicting drug-drug interactions (DDIs) is crucial for preventing adverse drug events in clinical settings. However, existing methodologies often rely on complex models built from diverse data sources, posing challenges in computational drug discovery. To address the need for precise computational methods in predicting unknown DDIs, this study introduces a novel Deep Neural Network (DNN)-based approach. By leveraging a wide range of drug-related information, including substructure, targets, side effects, pathways, and indications, our method calculates multiple drug similarities. These similarities are then synthesized using a nonlinear fusion method to extract high-level features. Subsequently, a tailored neural network is deployed for interaction prediction. Comparative evaluation against three prominent machine learning classifiers—Extreme Gradient Boosting (XGBoost), Adaptive Gradient Boosting (AdaBoost), and Light Gradient-Boosting Machine (LGBM)—using three benchmark datasets demonstrates the superior performance of DNN. It achieves outstanding accuracy, precision, recall, and F1-score metrics, all reaching 94.6% in cross-validation. Additionally, case studies involving numerous drug pairs confirm the reliability of DNN in accurately predicting unknown DDIs. These findings underscore DNN as a potent and reliable method for DDI prediction, with promising implications for drug discovery and healthcare applications.

Introduction: Caries is a public health problem in Kosovo among children, Caries is a multifactorial microbial disease and connection of this disease with soft drinks and food habits between children and their poor oral health is very strong. Aim: The aim of present study is to evaluate prevalence of caries among 12 to 16 years old students in municipality of Suhareka and to analyze related risk factors that contribute in occurrence of caries. Material and methods: To observe parameters of soft drink we used experimental method and a cross-sectional study was carried out among 120 adolescents in “Sadri Duhla” elementary school in Duhel and “7 Marsi” elementary school in city of Suhareka. Oral clinical examination and self administered questionnaire were used to collect information about dental caries and its correlation to soft drinks and food habits. Examination was done between May and October in the year 2023. Impact of soft drink in caries was assessed through DMFT index and frequency of consumption of soft drinks. The data were collected statistically using SPSS version 26 and presented in tables and graphs. Results: The highest result of DMFT (4.36) with standard deviation 1.23 was noted in the group consuming more than 16 cans per week also the highest score in adolescent compared to frequency of consumed cans per week. Soft drinks found in Kosovo’s mar-kets are acidic with low pH, 93.75% of them had a pH below 4 which are considered erosive and only 6.25% are minimally erosive with a pH > 4, in terms of buffer capacity soft drinks can be ordered like this energy drinks >soda >100% fruit juice > fruit drinks. Improper tooth-brushing, dental visits only in case of pain and not preventive visits were significantly related to dental caries. Conclusion: The results of the research awarned us for high frequency consumption of soft drinks related to dental caries. It is recommended to be aware of the use of soft drinks, regular visits to the doctor, higher maintenance of oral health by using paste with sufficient fluoride content also brushing teeth 1 hour after consuming acidic food.

The main sources of intrinsic noise in excitable cells at the microcircuit and network levels are the stochastic characteristics of ion channel gating and activation of the synaptic conductance. Studies using in vivo, in vitro, and in silico methods to examine the effects of synaptic background activity were not adequately investigated in non-neuronal excitatory cells, where neurotransmitter-based innervation also occurs. We created a mathematical model to replicate the background synaptic noise dynamics in a non-neuronal cell. We utilized the stochastic Ornstein-Uhlenbeck process to represent excitatory synaptic conductance, which was incorporated into a whole-cell model to produce spontaneous and evoked cellular electrical activities. The single-cell model includes many biophysically detailed ion channels represented by a set of ordinary differential equations in Hodgkin-Huxley and Markov formalisms. This paradigm effectively induced irregular spontaneous depolarizations (SDs) and spontaneous action potential (sAP) resembling in vitro-like electrical activity in the cells. The input resistance decreased by multiple factors, and the spontaneous action potential firing rate elevated. The potential to reach the action potential threshold is altered. Background synaptic activity can alter the input/output characteristics of non-neuronal excitatory cells. Suppressing these baseline activities would facilitate the discovery of new pharmaceutical targets for different clinical diseases.

The anthropometric features offer an overall image of the nutritional status. The investigated groups were aged 19 and 21. The anthropometric measurements of height and weight were recorded following standard procedures. The objectives of this study were to evaluate the harmonious body development, the nutrition status and the body composition. The evolution of the stature increases until 20 years after which stagnation follows. The body mass index of subjects was found to be normal. The body fat may vary over time in subjects depending on age and gender. Body water and body muscle mass content increased with age. The harmony of body development was assessed by means of the Amar index. Regarding the constitutional index, the women subjects belong to the leptosome type and the male subjects belong to the picnic type. The status of the investigated subjects is within the average stature.

The soil organic matter (SOM) content and stability in natural gypsum soils and soils from mining/industrial areas were compared, in terms of their physical, chemical and micromorphological properties, to determine whether the old brownfield soils were acting as carbon (C) sinks, counteracting increasing carbon dioxide concentrations in the atmosphere. The mining/industrial soils were 50–400 years old, so had been left sufficiently long for full self-restoration. Despite having very different origins, both natural and brownfield soils stored similar amounts of SOM, and had similar pH values, calcium carbonate contents and textures. They were also fully covered with similar grass plant communities. The mining/industrial soils exhibited similar microstructures to the gypsum soils and were often quite porous. The most striking difference between them and the natural gypsum soils was that the mining/industrial soils were strongly polluted with zinc, lead and cadmium. The 50-year-old brownfield soils differed from the others in terms of having a lower state of SOM transformation, with a much higher C/N ratio, lower aggregate water resistance index, lower dehydrogenase activity and greater areas of undecomposed or slightly decomposed plant residues. These parameters in the older (150–400 years) brownfield soils were similar to those of the natural soils.

This study investigates the effect of perceived discrimination on the mental health of Afghan refugees, and secondly, tests the distress moderating effects of pre-migration traumatic experiences and post-resettlement adjustment factors. In a cross-sectional design, 259 Afghans completed surveys assessing perceived discrimination and a number of other factors using scales developed through inductive techniques. Multivariate analyses consisted of a series of hierarchical regressions testing the effect of perceived discrimination on distress, followed by a sequential analysis of moderator variables. Perceived discrimination was significantly associated with higher distress, and this relationship was stronger among those with a strong intra-ethnic identity, high civic engagement, and high pre-resettlement traumatic experiences. Discrimination is a significant source of stress for Afghan refugees, which may exacerbate stresses associated with other post-migration stressors. Future research is needed to tailor interventions that can help mitigate the stress associated with discrimination among this highly vulnerable group.

OBJECTIVE: To investigate the value of serum inflammatory factor levels in acute ischemic stroke patients after revascularization therapy in assessing acute prognosis. METHODS: 94 patients with acute ischemic stroke who underwent revascularization therapy admitted to our hospital from January 01, 2022 to January 01, 2024 were studied. The main evaluation index was modified Rankin Scale score (mRS) after 3 months, and patients with mRS score >2 were categorized into the poor prognosis group, and the rest were the good prognosis group. As well as the treatment of revascularization in all patients was used as a division into a thrombus extraction group and an intravenous thrombolysis group. Logistic regression analysis was applied to explore the independent risk factors for the prognosis of patients treated with recanalization for acute ischemic stroke. RESULTS: Two groups with good (59 cases) and poor (35 cases) prognosis were divided according to the mRS score. There were some differences in age, gender, emergency GLU, INR, whether they had diabetes or hypertension and other contents between the two groups, but the differences were not statistically significant. The NIHSS score, hospitalization days, previous cardiac history, hospitalization days, LDL, fasting glucose, IL-6, and TNF-a at the time of admission were lower than those in the poor prognosis group, and the difference was statistically significant. In the patients in the embolization group, there were some differences in age, gender, emergency GLU, INR, whether they had diabetes or hypertension and other contents between the two groups, but the differences were not statistically significant. The pre-hospital NHISS score, IL-6, and TNF-a of patients in the good prognosis group were lower than those in the poor prognosis group, and the difference was statistically significant. CONCLUSION: IL-6 and TNF-α may be used as predictors of prognosis after revascularization therapy for acute ischemic stroke, and this conclusion also applies to patients in the embolization group.

Friction stir welding (FSW) is a solid state welding process for joining metallic alloys and dissimilar metals. It has emerged as an alternative technology for welding high strength alloys that are difficult to join with conventional techniques. FSW is used to produce products with better mechanical properties. Now a days aluminum alloys have been widely used in several industrial applications such as aerospace, marine, automobile and commercial applications due to their light weight structure, better mechanical properties and high corrosion resistance.In this work, three welding parameters such as spindle speed, welding speed and plunge depth were considered for friction stir welding. FSW was carried out between dissimilar aluminum alloy plates (AA6061 and AA 8011) to produce butt joint.A Box-Behnken design with three factors and three levels was chosen to minimize the number of experimental conditions .The tensile strength and hardness of the welded regions were evaluated. The optimum level settings and the major parameters that influence the joint strength were obtained by Box-Behnken design.

A sedentary lifestyle associated with unregulated diets rich in high-calorie foods have contributed to the great prevalence of metabolic dysfunction-associated steatotic liver disease (MASLD) latterly, with up to 60% in high-risk population and 25% in the general population. The absence of specific pharmacological strategies for this syndrome represents one of the major problems in the management of MASLD patients. Lifestyle interventions and adherence to a healthy diet are the main cornerstones of current therapies. The identification of nutraceuticals useful in the treatment of MASLD appears to be one of the most promising strategies for the development of new effective and safe treatments for this disease. The onion, one of the most widely studied foods in the field of nutraceuticals, serves as an inexhaustible reservoir of potent compounds with various beneficial effects. The following preliminary study analyses, mediating in silico studies, the iteration of a library of typical onion compounds with 3-hydroxy-3-methylglutaryl-coenzyme A reductase, Liver receptors X α and β as well as Peroxisome proliferator-activated receptors α and γ. In this study fort the first time promising smart molecules from the onion that could have a beneficial action in MASLD patients were identified.

Background We aimed to evaluate the effectiveness of the ALRYNGO channel-type video laryngoscope with an AI-based glottis guidance system in senior emergency medicine residents for endotracheal intubation. Methods We enrolled twenty patients would be adequate for each device (direct laryngoscope, Pentax-AWS, and ALRYNGO). Before intubation, six senior residents wore a personal protective equipment. To randomize the device in this clinical study, a sealed envelope containing a device-specific identification card was utilized. When intubation began, the person who measured the intubation time divided the total intubation time into three-time intervals. The primary outcome was the intubation time. The secondary outcomes were the glottis view using the Cormack-Lehane grade (C-L grade) and the glottis guidance performance of ALRYNGO’s artificial intelligence. Results In Pentax-AWS and ALRYNGO, all intubations were successful, but the intubation time was longer than with the direct laryngoscope. And among the three, the ALRYNGO and Pentax-AWS had the highest frequency of C-L grade I (easiest intubation) at 80%, and the direct laryngoscope had the lowest frequency of 10%. Conclusions Even if healthcare professionals without experience with the channel-type video laryngoscope improve their performance on airway mannequins after training, their intubation performance may differ when applied to actual patients.

Molecularly imprinted polymers (MIPs) were synthesized and applied for the selective extraction of oblongifolin C (OC) from fruit extracts of Garcinia yunnanensis Hu. A series of experiments and computational approaches were employed to improve the efficiency of screening for optimal MIP systems in the study. The molar ratio (1:4) was chosen at last based on the comparison of the binding energy of the complexes between the template (OC) and functional monomers using density functional theory (DFT) at the RI-PBE-D3-gCP/def2-TZVP level of theory. The binding characterization and the molecular recognition mechanism of MIPs were further explained using the molecular modeling method and NMR and IR spectra data. The reusability of this approach was demonstrated in over 20 batch rebinding experiments. 140.5 mg of OC (>95% purity) was obtained from the 5 g extracts with 2 g of MIPs with the best binding properties through gradient elution program from 35% to 70% methanol-water solution. At the same time, another structural analog, 46.5 mg of guttiferone K (GK) (>88% purity), was also obtained by the gradient elution procedure. Our results showed that the structural analogs could be separated from the crude extracts by the molecularly imprinted solid-phase extraction (MISPE) using a gradient elution procedure for the first time.

Introduction: In Part II of this three-part series, we expose techniques that can be used by the U.S. Centers for Disease Control and prevention (CDC) and Food and Drug Administration (FDA) to manipulate and throttle the Vaccine Adverse Event Reporting System (VAERS), a vaccine safety monitoring system open to the public. The U.S. government’s recommendation of COVID-19 vaccines during pregnancy was more a product of propaganda than of science and plagued with conflicts of interest. The extreme breach of COVID-19 vaccine pregnancy complication safety signals documented in VAERS cannot be disregarded or concealed. As a result, CDC/FDA are moving to closed, government captured platforms, including V-safe, Vaccine Safety Datalink (VSD) system, and the Biologics Effectiveness and Safety (BEST) system. Public transparency of adverse events following COVID-19 vaccination in pregnancy should be increased, not thwarted. Methods: In Part I the CDC/FDA Vaccine Adverse Event Reporting System (VAERS) database was queried from January 1, 1990, to April 26, 2024 for adverse events (AEs) involving pregnancy complications following vaccination. In Part II we investigate tactics discovered in VAERS that concealed vaccine injuries and deaths. Conflicts of interest, as well as specific communications and publications from the CDC/FDA and the New England Journal of Medicine (NEJM) are analyzed. Results: Of all VAERS AE reports, 8.47% (138,983) of COVID-19 reports had no vaccination date and thus were missing from the data presented in Part I of this series. We unconcealed data presented in Part I of this series to include VAERS case reports that were excluded when using standard queries because of an “unknown vaccination date”. The unconcealed data in the 37 AE cases reported in this study (Part II) ranged from 0 - 38% with a mean of 8.2% (standard deviation 9.7%) and the significant breaches of VAERS safety signals in Part I of this series were largely underestimated. Another method of concealing vaccine associated AEs is to exclude the specific vaccine type rendering it as an “unknown vaccine type”. “Unknown vaccine type” has logarithmically increased since the rollout of the COVID-19 vaccines in 2021, ranging from 1 to 400 cases between 1990 to 2018 to 11,461 cases in 2021. CDC/FDA granted $67 million via a Cooperative Agreement grant to Massachusetts Department of Public Health (MDPH) between July 1, 2019, to June 30, 2025. MDPH then made subawards under this grant to 21 influential public and private health and civic organizations, including NEJM’s owner, Massachusetts Medical Society (MMS). As one of the subawardees under the grant, MMS as owner of NEJM received over $426,000 in federal HHS/CDC grant money from 2019 to 2020 for “public health and medical emergency preparedness projects”. Conclusions: CDC/FDA has failed to capture and account for a significant number of AE case reports following COVID-19 in VAERS by a variety of techniques in an apparent attempt to sanitize the data. CDC’s Rochelle Walensky and NEJM’s Editor-in-Chief Eric Rubin pushed novel untested COVID-19 vaccines in pregnant women despite clear evidence from multiple sources that safety signals had been breached.

The literature shows that both in laboratory and in industrial conditions, photocatalytic oxidation method copes quite well with the degradation of the most organic substances, including environmental toxins and molecular components of pathogenic microorganisms. However, the effective utilization of photocatalytic processes for environmental decontamination and disinfection require significant technological advancement both in the area of semiconductor material synthesis and its application. Here we focused on the presence and ‘photocatalytic capability‘ of photocatalysts among soil minerals, and their potential contribution to the environmental decontamination in vitro and in vivo. (The issue is sketched from the perspective of chemists and environmental scientist.) Reactions caused by sunlight on the soil surface are involved in its normal redox activity. It appears that some of them may take part in the soil decontamination. However, their importance for decontamination in vivo cannot be overstated due to diversity of soils on the Earth caused by the environmental conditions, such as climate, parent material, relief, vegetation etc. The solar-light induced reactions are just a part of extremely complicated processes dependent on a plethora of environmental determinates. Such multiplicity of affecting factors, which we tried to sketch from the perspective of chemists and environmental scientist, makes us rather sceptical about the effectiveness of the photocatalytic processes in vivo. On the other hand, there is a huge potential of the soils as the alternative source of useful photocatalytic materials of unique properties

This comprehensive article explores Massive MIMO (M-MIMO) design and its associated concepts, focusing on the seamless integration requirements for Beyond 5G (B5G) and 6G networks. Addressing critical aspects such as RF chain reduction, pilot contamination, Cell-Free MIMO, and security considerations, the article delves into the intricacies of M-MIMO in the evolving landscape of B5G. Moreover, the emerging MIMO concepts in this article include AI-enabled M-MIMO three-dimensional beamforming, reconfigurable intelligent surfaces, visible light communication, and THz spectrum utilization. This review highlights challenges and open research issues, including Narrow Aperture Antenna Nodes, Plasmonic Antenna Arrays, Integrated Sensing with M-MIMO, and the application of Federated Learning in M-MIMO systems. By examining these cutting-edge developments, the article aims to contribute to advancing knowledge in the field and inspire future research directions in the exciting realm of B5G and 6G networks.

The AUC-ROC is a widespread measure to assess the performance of a binary classification model across various discrimination thresholds. Yet, it is not apt for unbalanced class problems and is misleading for early retrieval. For instance, link prediction in complex networks is an unbalanced early retrieval problem, whose goal is to offer a ranking of the nonobserved network links, prioritizing a small cohort of positive links (for which we are sure the labels are reliable) on top of a list largely populated by unlabeled links (for which the labels are uncertain). Differently from binary classification, here the evaluation focuses on how the predictor prioritizes the positive class, because the negative class does not exist and is replaced by an unlabeled class. For decades, scholars have been investigating the necessity to correct and to generalize the AUC-ROC to work for both unbalanced classification and early retrieval evaluation, this is requested in many applied domains of computational science. Here we propose the area under the magnified ROC (AUC-mROC), a new measure that adjusts the standard AUC-ROC to work for unbalanced early retrieval problems such as link prediction. Finally, we introduce the area under the generalized ROC (AUC-gROC), which unifies both AUC-mROC and AUC-ROC to provide a universal and reliable evaluation measure that can work for both classification and early retrieval problems, regardless of class proportion.This discovery represents a critical achievement, culminating in success after decades of contentious research. Its solution promises to significantly impact various domains within applied computational science.

The state-of-the-art smart city has been calling for an economic but efficient energy management over large-scale network, especially for the electric power system. It is a critical issue to monitor, analyze and control electric loads of all users in system. In this paper, we employ the popular computer vision techniques of AI to design a non-intrusive load monitoring method for smart electric energy management. First of all, we utilize both signal transforms (including wavelet transform and discrete Fourier transform) and Gramian Angular Field (GAF) methods to map one-dimensional current signals onto two-dimensional color feature images. Second, we propose to recognize all electric loads from color feature images using a deep neural network with multi-scale feature extraction and attention mechanism. Third, we design our method as a cloud-based, non-intrusive monitoring of all users, thereby saving energy cost during electric power system control. Experimental results on both public and our private datasets have demonstrated our method achieves superior performances than its peers, and thus supports efficient energy management over large-scale Internet of Things.

The Imbalance Cost Pass-Through (ICPT) is a flexible component of the Incentive Regulation (IBR) that empowers power producers to adjust tariffs in response to variable fuel prices, thereby enhancing the economic resilience of electricity generation. However, the cost of electricity generation is significantly influenced by the volatility of commodity prices, including coal, gas and LNG. In Malaysia, the Energy Commission has conducted biannual reviews of fuel and other generation costs. Any cost savings or increases identified during these reviews will be passed on to customers in the form of rebates or surcharges. Due to that reason, this study proposes ICPT price forecasting for the electricity market in Peninsular Malaysia. The study aims to construct an ICPT-related baseline model for the peninsular generation data by employing three forecasting methods. The forecasting performance is analysed by a Mean Absolute Percentage Error (MAPE). In findings, the ARIMA method is one of the most accurate forecasting methods for fuel prices compared to the Moving Average (MA) and LSSVM methods. The observed price differences between the ARIMA and LSSVM models for ICPT are minimal. The ICPT price for July-December 2022 and January-June 2023 is MYR 0.21/ kWh for ARIMA and MYR 0.18/kWh for LSSVM, which are close to the actual TNB’s ICPT tariff. As for the forecasting, the ICPT price is expected to drop for the next announcement. The findings of this study may contribute to a positive impact on the sustainability of the energy sector in Malaysia.

Nowadays the relationship between planning land use and actual land use is not so clear in general. A lot of efforts have been put in the failures of regulation for the expansion of construction land. However, it still lacks an integrated approach to study the effectiveness of land use regulation in terms of different land use types. Furthermore, the existing evaluation of land use plan mainly focuses on a general level, a detailed research on the regulation effectiveness of each construction land use type is absent. Therefore, this research tries to evaluate regulation effectiveness of land use plan, which takes Cangwu country, Guangxi Province as an example. The finding by analysis is that the total area of construction land expansion was about 3494.73 ha, nearly 1.1 times of the plan quota. Moreover, the effectiveness differs greatly in various construction land use types. Town, industrial/mining sites can be well regulated through the quota of land use plan. While, the quota regulation system is not as effective for other type of construction land. Thus, we suggest to improve the regulation effectiveness of construction land through different plan instruments.

In this paper we have defined the effect of bulk viscosity on Quintessence model and scaler field potential as well as on classical field. We have shown the same effect for modified gravity with f(R,T)= R+f(T). In the derivation we have predicted the possibility of time dependent evolution of gravitational constant G and anisotropy.

In this 10-year retrospective study we used the data from patients who were operated upon due to acute bowel obstruction, at the Surgical Department of General Hospital of Katerini in Greece, from 2012 to 2022. Patients were classified based on the date of operation, their sex, their age group (ranging from 26 to 92 years) and the etiology of the bowel obstruction. A sample of 197 patients was studied. Out of these, it was found that in 73 (37%) the cause of the obstruction was colorectal cancer. In 46 of those patients (63%) the tumor was resected, while in the remaining 27 (37%), some kind of diverting stoma was installed. In 17(43,5%) of the 39 total patients, who suffered from some kind of rectosigmoid cancer, Hartmann's operation was chosen. Our results showcase that, at district hospitals, the surgeon is sometimes obligated to a damage control approach regarding obstructive colon cancer and thus the majority of the patients will eventually end up with a stoma.

Count data are used in many fields of practice, especially Poisson distribution as a popular choice for the marginal process distribution. If these counts exhibit serial dependence, a popular approach is to use a Poisson INAR(1) model to describe the autocorrelation structure of process. In this paper, the explicit formulas are proposed to evaluate performance characteristics of Double Moving Average control chart (DMA) for Integer valued autoregressive of serial dependence Poisson process. The characteristics of the control chart are frequently measured as Average Run Length (ARL) which means that the average of observations are taken before a system is signaled to be out-of-control. These proposed explicit formulas of ARL are simple and easy to implement for practitioner. The numerical results show that the DMA chart performs better than others when the magnitudes of shift are moderate and large.

Photoreceptor degeneration is a major cause of untreatable blindness worldwide and has recently been targeted by emerging technologies, including cell- and gene-based therapies. Cell types of neural lineage have shown promise for replacing either photoreceptors or retinal pigment epithelial cells following delivery to the subretinal space, while cells of bone marrow lineage have been tested for retinal trophic effects following delivery to the vitreous cavity. Here we explore an alternate approach in which cells from the immature neural retinal are delivered to the vitreous cavity with the goal of providing trophic support for degenerating photoreceptors. Rat and human retinal progenitor cells were transplanted to the vitreous of rats with a well-studied photoreceptor dystrophy, resulting in substantial anatomical preservation and functional rescue of vision. This work provides scientific proof-of-principle for a novel therapeutic approach to photoreceptor degeneration that is currently being evaluated in clinical trials.

Oxidative neurodegeneration causes various neuronal diseases including Alzheimer's disease, Parkinson's disease, and Huntington's disease. This study aimed to demonstrate the protective effect of leaf extracts of Allium senescens on 6-hydroxydopamine (6-OHDA)-stressed SH-SY5Y cells, known as an optimal cell for neurotoxic research. Levels of apoptotic markers were evaluated using quantitative polymerase chain reaction (qPCR) and flow cytometry. The localization of apoptotic cells in vivo was analyzed using whole-mount immunochemistry and the terminal deoxynucleo-tidyl transferase dUTP nick end labeling assay. Additionally, reactive oxygen species (ROS) pro-duction was estimated using flow cytometry. 6-OHDA induced ROS production in neuroblast cells and in vivo, but treatment with the extract protected against the 6-OHDA-induced increase in ROS levels. Under oxidative stress, the extract performs three protective functions: decreases ROS production, prevents mitochondrial apoptosis, and protects the central and ventral nervous systems. These results also suggest that the extract can be useful for the development of functional foods for the prevention of neural damage due to oxidative stress.

There is an increasing concern on the quality of jobs and productivity witnessed in the flexible employment arrangements. The aim of this study is to examine the relationship between various employment arrangements and the workplace performance. Home-based working-teleworking, flexible timing and compressed hours are the main employment types examined using the Workplace Employee Relations Survey (WERS) in years 2004 and 2011. The workplace performance is measured by two outcomes- the financial performance and labour productivity. First, the determinants of those flexible employment types are explored. Second, the ordinary least squares (OLS) method is followed. Third, an instrumental variable (IV) approach is applied to account for plausible endogeneity and to estimate the causal effects. The findings reveal a significant and positive relationship between these types of flexible employment arrangements and the workplace performance. Education, age, wage, quality of relations between managers-employees, years of experience, the area of the market the workplace is operated and the competition are significant factors and are positively associated with the propensity of the flexible employment arrangements implementation. This can have various profound policy implications for employees, employers and the society overall, including family-work balance, coping with family demands, improving the firm performance, reducing traffic congestion and stress among others. It is the first study that explores the relationship between flexible employment types and workplace performance using an IV approach. This allows us to estimate the causal effects of flexible employment types and the possible associated social implications.

Chronic hemodialysis (HD) patients have very high cardiovascular risk. Acute vascular changes during dialysis mediated by factors of the endothelium may have a crucial role in this. Aim: To study acute vascular changes during HD. In 29 consecutive chronic HD patients (age: 65.6±10.4 years) pre-, mid-, and post-HD plasma syndecan-1 (SDC-1) and endothelin-1 (ET-1) levels were measured. Applanation tonometry was performed before HD. SDC-1 levels increased during HD (p=0.004). Males had higher ET-1 levels. Patients were divided into 2 groups based on pulse wave velocity (PWV): PWV≥12 m/s and PWV<12 m/s. Pre-HD and mid-HD SDC-1 levels were higher in the group with PWV≥12 m/s (10.174±2.568 vs. 7.928±1.794 ng/ml, p=0.013, and 10.319±3.482 vs. 8.248±1.793 ng/ml, p=0.044, respectively). Post-HD ET-1 levels were higher in the patient group having PWV≥12 m/s (10.88±3.00 vs. 8.05±3.48 pg/l, p=0.027). Patients having PWV≥12 m/s had higher pre-HD peripheral and aortic systolic blood pressure (p<0.05). Total cholesterol correlated with the SDC-1 decrease during HD (r=0.539; p=0.008). Pre-, mid-, and post-HD SDC-1 correlated with the ultrafiltration (r=0.432, p=0.019; r=0.377, p=0.044; and r=0.401, p=0.012, respectively). SDC-1 and ET-1 contribute to vascular changes observed during HD, and they have correlations with some cardiovascular risk factors.

Due to failure of the continuum hypothesis for higher Knudsen numbers, rarefied gases and microflows of gases are particularly difficult to model. Macroscopic transport equations compete with particle methods, such as DSMC to find accurate solutions in the rarefied gas regime. Due to growing interest in micro flow applications, such as micro fuel cells, it is important to model and understand evaporation in this flow regime. Here, evaporation boundary conditions for the R13 equations, which are macroscopic transport equations with applicability in the rarefied gas regime, are derived. The new equations utilize Onsager relations, linear relations between thermodynamic fluxes and forces, with constant coefficients, that need to be determined. For this, the boundary conditions are fitted to DSMC data and compared to other R13 boundary conditions from kinetic theory and Navier-Stokes-Fourier (NSF) solutions for two one-dimensional steady-state problems. Overall, the suggested fittings of the new phenomenological boundary conditions show better agreement to DSMC than the alternative kinetic theory evaporation boundary conditions for R13. Furthermore, the new evaporation boundary conditions for R13 are implemented in a code for the numerical solution of complex, two-dimensional geometries and compared to NSF solutions. Different flow patterns between R13 and NSF for higher Knudsen numbers are observed.

A mass mortality event of Asian seabass Lates calcarifer juveniles occurred in Zhuhai, the main Asian seabass cultured area in mainland China. The fish samples were pooled for pathogen identification and both high viral loads of ISKNV and NNV were detected by real-time microfluidic quantitative PCR. Immunohistochemistry and immunofluorescence showed that strong ISKNV signals were examined in spleen and liver, while strong NNV signals were detected in brain and eye. The multi-tissue homogenates were inoculated into MFF-1 cell and SSN-1 cell, respectively. After several viral passages, both ISKNV and NNV were purely isolated from each other, and designated as ASB-ISKNV-23 and ASB-NNV-23, respectively. The whole genome sequences of ASB-ISKNV-23 and ASB-NNV-23 were determined and annotated. The result showed that ASB-ISKNV-23 and ASB-NNV-23 are composed of 112,236 bp and 4,538 bp, respectively. Phylogeny analysis showed that ASB-ISKNV-23 belongs to ISKNV-II sub-genotype and ASB-NNV-23 belongs to RGNNV genotype. Collectedly, coinfection of ISKNV-II and RGNNV were firstly documented in mass mortality of Asian seabass in mainland China. Importantly, both ISKNV-II and RGNNV were purely isolated using two different permissive cell lines. Our study provides useful information for better understanding the complex pathogenesis regarding the coinfection with ISKNV and NNV in farmed fish.

Growing concerns about the greenhouse effect, global warming, and adverse climate changes primarily stemming from carbon dioxide (CO2) emissions in traditional Portland cement (OPC) used in civil engineering construction, have prompted a shift toward eco-friendly alternatives like geopolymer cement (GPC). Over the last few decades, significant advancements have been made in developing environmentally sustainable pavement construction materials such as GPC to mitigate global CO2 emissions. The success of geopolymer cement (GPC) as an eco-friendly alternative to OPC has garnered attention for its potential to lower carbon emissions and enhance durability. This is attributed to the sustainable production method of GPC, where industrial cementitious waste materials (such as fly ash (FA), metakaolin (MK), mine tailings (MT), slag, etc.) are combined with an eco-friendly alkaline activator and water through the geopolymerization process. Numerous studies on geopolymer concrete indicate that, like OPC, GPC exhibits comparable mechanical properties, including strength, fire resistance, chemical resistance, and durability. This review explores the properties and applications of GPC as a sustainable material in pavement construction, exploring key studies and advancements in geopolymer technology, particularly its suitability for pavement applications. The assessment covers the mechanical properties, long-term performance, and environmental impact of geopolymer-based pavements, providing a comprehensive overview to inform policymakers, engineers, and researchers about the viability of geopolymer-based materials as a sustainable solution for modern pavement construction.

The Solvency II regulatory framework specifies procedures and parameters for determining solvency capital requirements (SCRs) for insurance companies. The proposed standard SCR calculations involve two steps. The Value–at–Risk (VaR) of each risk driver is measured and, in a second step, all components are aggregated to the company’s overall SCR, using the Standard Formula. This formula has two inputs: the VaRs of the individual risk drivers and their correlations. The appropriate calibration of these input parameters has been the purpose of various Quantitative Impact Studies that have been conducted during recent years. This paper demonstrates that the parameter calibration for the equity–risk module—overall, with about 25%, the most significant risk component—is seriously flawed, giving rise to spurious and highly erratic parameter values. As a consequence, an implementation of the Standard Formula with the currently proposed calibration settings for equity–risk is likely to produce inaccurate, biased and, over time, highly erratic capital requirements.

Leafhopper Yamatotettix flavovittatus Matsumura is a phloem feeder that causes significant damage to sugarcane and also transmits sugarcane white leaf (SCWL) disease. Understanding the settling preference, feeding behavior, honeydew production and biophysical factors affecting Y. flavovittatus leafhopper infestation in sugarcane cultivation is crucial for effective pest management strategies. This study investigated these aspects across nine sugarcane cultivars. Significant variability was observed among cultivars in terms of settling behavior, with KK3 and LK92-11 showing the highest number of settled leafhopper adults. Similarly, honeydew production varied significantly among cultivars, with KK3 and LK92-11 exhibiting the highest production. Employing the electrical penetration graph (EPG) technique provided insights into distinct probing behaviors across cultivars, highlighting correlations between settling preference, honeydew production, and specific EPG waveforms. Principal component analysis (PCA) categorized cultivars into four groups based on settling preference, honeydew production, feeding behavior, and biophysical factors. Strong correlations were found between settling preference, honeydew production, and various EPG waveforms, while negative correlations were observed with the number of silica cells and rows per unit area, indicating their potential role in deterring leafhopper settlement. We concluded that TPJ04-768 and K84-200 are promising for resistance to leafhoppers and exploited in sugarcane breeding programs for resistance to insects.

The eutrophication of open water bodies, especially in coastal water area, has received intensive public focuses in recent years. Biological treatment of organic pollutants in industrial and domestic wastewater requires microbial flora to participate. The environmental impact of these microbes, particularly in regard to the spread of antibiotic resistance genes and pathogenicity in coastal water, remains largely unknown. We initiate studies to examine antibiotic resistance genes (ARGs) in microbial flora and study the mode of antibiotic spread in the coastal waters of Bohai Bay, North China by using high performance liquid chromatography-mass spectrum analysis and quantitative polymerase chain reaction. The metabolic features of bacteria related to the presence of ARGs in the coastal area showed the enrichment of Pseudomonadale species with triple resistance properties (ampicillin, kanamycin and gentamycin) at the estuary site locating adjacent to a coastal sewage treatment plant where both type I and type II polyketide synthase genes and b-lactam type antibiotics are detected. Pseudomonadale order is phylogenetically belonged to Proteobacteria Phylum, Gamma-proteobacteria Class and contains Pseudomonadaceae family and Pseudomonas genus. QPCR analysis suggests that the percent occupation of Pseudomonadale species to total Proteobacteria in the examined stations is close to several sampling stations close to sewage treatment plants, where consistent release of organic wastes occurred.

Nowadays, unmanned vehicles are widely used in various fields. However, the safety of unmanned vehicles is directly determined by the autopilot systems, and sensor faults are a very critical factor that affects the normal operation of the autopilot systems. To efficiently and comprehensively test unmanned systems for sensor faults, this paper proposes a chip-level testing platform for unmanned vehicle autopilot systems based on FPGA hardware-in-the-loop simulation. Unlike existing testing platforms, the introduction of FPGA technology allows us to achieve nanosecond real-time simulation frequency, thus realizing chip-level simulation of sensors and black-box automated testing. Firstly, we propose a set of general platform and modeling methods, and the paper presents a detailed application of the four most common necessary sensors in autopilot systems as examples. Secondly, we propose for the first time a chip-level fault testing method for unmanned systems, and build a test platform with a quadrotor vehicle, the PX4 software platform, and the Pixhawk4 hardware platform as examples. Finally, the experimental results verify that the testing platform proposed in this paper can adapt to various autopilot systems and has high simulation test reliability.

Diabetic Kidney Disease (DKD) is a common complication of Type 2 Diabetes Mellitus and a major risk factor for end-stage kidney disease. The immune system plays a significant role in the pathogenesis of DKD, involving infiltration of immune cells in the kidney, upregulation of in-flammatory mediators, downregulation of anti-inflammatory mediators, and disturbance in ad-hesion molecules and growth factors. Dendritic cells are professional antigen-presenting cells acting as a bridge connecting innate and adaptive immune responses. DC is also capable of modulating inflammation. Autologous dendritic cells can be made by in vitro differentiation of peripheral blood monocytes and then utilized as a cell-based therapy. Cell-based therapy for DKD is currently focused on utilizing the anti-inflammatory properties of stem cells. However, research suggests unsatisfactory results due to several limitations. This article highlights the possibility of using DC as a cell-based therapy for DKD through its role in controlling inflammation.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that caused the COVID-19 pandemic still able to infect the population in many countries. The Omicron strain is the most mutated variant of SARS-CoV-2. The high transmissibility of the strain and the ability to evade immunity require a priority study of its properties in order to quickly create effective means of preventing it. The present work is devoted to the study of in silico interaction of piRNAs with the genome of the SARS-CoV-2 (gRNA) in order to identify endogenous piRNAs and propose synthetic piRNAs with high antiviral activity for drug development. The studies were carried out using proven bioinformatic methods of interaction of the entire SARS-CoV-2 genome with more than eight million piRNAs. Binding sites (BSs) of piRNAs in the 5'UTR were located with overlapping nucleotide sequences called clusters of BSs. Several clusters of BSs were found in the nsp3, nsp7, RNA-dependent RNA polymerase, endoRNAse, S surface glycoprotein, ORF7a and nucleocapsid. 16 synthetic piRNAs have been proposed that interact with gRNA with free binding energy from -170 kJ/mol to -175 kJ/mol, which can be used to create drugs that suppress the reproduction of SARS-CoV-2.

(1) Background: When the Omicron variant of SARS-CoV-2 first emerged in Germany in January 2022, data on related disease severity among children and adolescents was not yet available. Given Omicron’s high transmissibility, the ability to assess its impact on admission and hospitalization rates in children’s hospitals is critical for the purpose of understanding the scope of its burden on the German health care system. (2) Methods: From January 24, 2022 to July 31, 2022, SARS-CoV-2 cases admitted to German pediatric hospitals were monitored via a national, clinician-led reporting system (CLRS) established by the German Society for Pediatric Infectious Diseases (DGPI). Cases treated on general wards and intensive care units, as well as patient age and need for respiratory support were recorded. (3) Results: From January to July 2022, a median of 1.7 cases (range 0.4–3) per reporting pediatric hospital per day were hospitalized on general wards, whereas a median of 0.1 cases (range 0–0.4 cases) were on intensive care units. Of all hospitalized patients, 4.2% received respiratory support. (4) Conclusions: Despite the high incidence rates documented in connection with the Omicron variant in early 2022, the number of pediatric hospital admissions, and especially the number of cases with need for intensive care treatment and respiratory support due to a symptomatic SARS-CoV-2 infection, remained relatively low. Higher Omicron incidence rates had only a modest impact on SARS-CoV-2-related admissions and hospitalization in German children’s hospitals.

Motivated by the definition of the type 2 poly-Bernoulli polynomials introduced by Kim-Kim, in the present paper, we consider a class of new generating function for the Frobenius-Genocchi polynomials, called the type 2 poly-Frobenius-Genocchi polynomials, by means of the polyexponential function. Then, we derive some useful relations and properties. We show that the type 2 poly-Frobenius-Genocchi polynomias equal a linear combination of the classical Frobenius-Genocchi polynomials and Stirling numbers of the first kind. In a special case, we give a relation between the type 2 poly-Frobenius-Genocchi polynomials and Bernoulli polynomials of order k. Moreover, inspired by the definition of the unipoly-Bernoulli polynomials introduced by Kim-Kim, we introduce the unipoly-Frobenius-Genocchi polynomials by means of unipoly function and give multifarious properties including derivative and integral properties. Furthermore, we provide a correlation between the unipoly-Frobenius-Genocchi polynomials and the classical Frobenius-Genocchi polynomials.

The outbreak across the globe due to coronavirus disease 2019 (COVID-19) has spread abruptly by infected humans worldwide. The continuous efforts by scientists is on way to understand how pandemic of COVID-19 resembles and differs from serve acute respiratory syndrome coronavirus (SARS-CoV) at transcriptomic and genomic level. The SARS-CoV and COVID-19 exploits the angiotensin converting enzyme 2 (ACE2) receptor to gain entry inside the cells.We analyzed the entry COVID-19 into host cell due to receptor binding domain (RBD) of spike glycoprotein. The proposed simulation data shows similar ternary structures from two viruses shares approximately 80 percent identity in amino acid sequences. Our molecular modeling investigation signifies that angiotensin converting enzyme 2 (ACE2) has stronger interaction with COVID -19 RBD. The Amino acid phenylaniline F486 LOOP plays vital role due to its penetration into hydrophobic pocket in ACE2.The said investigation of S-Glycoprotein RBD of COVID-19 or SARS-CoV-2 via ACE2 provides post genome analysis of protein-protein interaction for rapid assessing transmission of infected patients by deadly CoVID-19. The scientific data extracted implies early guidance to control and viral prevention of CoVID-19.

Urban sprawl propelled by rapid population growth leads to the shrinkage of productive agricultural lands and pristine forests in the suburban areas and, in turn, substantially alters ecosystem services. Hence, the quantification of urban sprawl is crucial for effective urban planning, and environmental and ecosystem management. Like many megacities in fast growing developing countries, Chennai, the capital of Tamilnadu and one of the business hubs in India, has experienced extensive urban sprawl triggered by the doubling of total population over the past three decades. We employed the Random Forest (RF) classification on Landsat imageries from 1991, 2003, and 2016, and computed spatial metrics to quantify the extent of urban sprawl within a 10km suburban buffer of Chennai. The rate of urban sprawl was quantified using Renyi’s entropy, and the urban extent was predicted for 2027 using land-use and land-cover change modeling. A 70.35% increase in urban areas was observed for the suburban periphery of Chennai between 1991 and 2016. The Renyi’s entropy value for year 2016 was ≥ 0.9, exhibiting a two-fold rate of urban sprawl. The spatial metrics values indicate that the existing urban areas of Chennai became denser and the suburban agricultural, forests and barren lands were transformed into fragmented urban settlements. The forecasted urban growth for 2027 predicts a conversion of 13670.33ha (16.57 % of the total landscape) of existing forests and agricultural lands into urban areas with an associated increase in the entropy value of 1.7. Our findings are relevant for urban planning and environmental management in Chennai and provide quantitative measures for addressing the social-ecological consequences of urban sprawl and the protection of ecosystem services.

Background: Schistosome egg deposition in pregnant women may affect the placenta of infected mothers and cause Placental Schistosomiasis (PS). Histopathological examination of placental tissue is an inadequate detection method due to low sensitivity. So far, there has not been any sys-tematic review on PS. Methods: We conducted a systematic literature search on PubMed and in-cluded relevant secondary literature found in the citations of the primarily included publications. Results: We found a total of 8 publications describing PS with a total of 92 cases, describing egg deposition of dead and/or viable eggs and worms of S. haematobium and S. mansoni in placental tissue. One cross-sectional study investigating the prevalence of PS and its association to adverse birth outcomes, found 22% of placentas to be infested using a maceration technique but only < 1% using histologic examination. Additionally, no direct link to deleterious pregnancy outcomes could be shown. Conclusions: PS is a highly unattended and underdiagnosed condition in en-demic populations, due to a lack of awareness as well as low sensitivity of histopathological examinations. However, PS may play an important role in mediating or reinforcing adverse birth outcomes (ABO) such as fetal growth restriction (FGR) in maternal schistosomiasis, possibly by placental inflammation.

The design complexity of the new generation of civil aero-engines results in higher demands on engines’ components, higher component temperature, higher heat generation, and, finally, critical thermal management issues. This paper will propose a methodological approach to create physics-based models for heat loads developed by sources as well as a systematic sensitivity analysis to identify the effects of design parameters on the thermal behaviour of civil aero-engines. The ranges and levels of heat loads generated by heat sources (e.g., accessory gearbox, bearing, pumps, etc.) and heat absorption capacity of heat sinks (e.g., engine fuel, oil, and air) are discussed systematically. The practical research challenges for thermal management system design and development for the new and next generation of turbofan engines will then be addressed through a sensitivity analysis of the heat load values as well as the heat sinks flow rates. The potential solutions for thermal performance enhancements of propulsion systems will be proposed and discussed accordingly.

Major depressive disorder (MDD) and substance use disorder (SUD) are of immense medical and social concerns. Although significant progress on neuronal involvement in mood and reward circuitries has been achieved, only relatively recently the role of glia in these disorders have attracted attention. Detail understanding of the glial function in these devastating diseases could offer novel interventions. Here, following a brief review of circuitries involved in mood regulation and reward perception, specific contribution of the neurotrophic factors, neuroinflammation and gut microbiota to these diseases are highlighted. In this context, the role of specific glial cells (e.g., microglia, astroglia, oligodendrocytes and synantocytes) on phenotypic manifestation of MDD or SUD are emphasized. In addition, potential use of this knowledge in developing novel therapeutics is touched upon.

The increasing prevalence of Metabolic Syndrome (MetS), a serious condition associated with elevated risks of cardiovascular diseases, stroke, and type 2 diabetes, underscores the urgent need for effective diagnostic tools. This research carefully examines the effectiveness of 16 diverse machine learning (ML) models in predicting MetS, a multifaceted health condition linked to increased risks of heart disease and other serious health complications. Utilizing a comprehensive, unpublished dataset of imbalanced blood test results, spanning from 2017 to 2022, from the Laboratory Information System of the General Hospital of Amfissa, Greece, our study embarks on a novel approach to enhance MetS diagnosis. By harnessing the power of advanced ML techniques, we aim to predict MetS with greater accuracy using non-invasive blood test data, thereby reducing the reliance on more invasive diagnostic methods. Central to our methodology is the application of the Borda count method, an innovative technique employed to refine the dataset. This process prioritizes the most relevant variables, as determined by the performance of the leading ML models, ensuring a more focused and effective analysis. Our selection of models, encompassing a wide array of ML techniques, allows for a comprehensive comparison of their individual predictive capabilities in identifying MetS. This study not only illuminates the unique strengths of each ML model in predicting MetS but also reveals the expansive potential of these methods in the broader landscape of health diagnostics. The insights gleaned from our analysis are pivotal in shaping more efficient strategies for the management and prevention of Metabolic Syndrome, thereby addressing a significant concern in public health.