In Ethiopia, there are a lot of national and regional parks and the objective is to conserve wild animals and plants on site. Botanical gardens are essential to the study and preservation of plant biodiversity, both in situ and ex situ. Botanical gardens are vitally essential establishments that protect the environment from ever-increasing environmental concerns, provide recreational possibilities, educate the public about environmental issues, and carry out a variety of conservation and research projects. Their goal is to preserve collections of live plants with documentation for use in scientific study, preservation, exhibition, and teaching. Botanical gardens engage in a wide range of scientific endeavors, including the study of seeds, taxonomy, systematics, genetics, biotechnology, propagation, horticulture, public education, restoration ecology, and many other subjects. The functions of parks and botanical gardens include; scientific research, natural science, Reduction of Wind and Water Loss, shelter for Fish, Wild Habitat, Noise, Pollution Control, and Serving as a Buffer Zone.

How Nature discovered genetic coding is a largely ignored question, yet the answer is key to explaining the transition from biochemical building blocks to life. Other, related puzzles also fall inside the aegis enclosing the codes themselves. The peptide bond is unstable with respect to hydrolysis. So, it requires some form of chemical free energy to drive it. Amino acid activation and acyl-transfer are also slow and call for catalysis. All living things must thus also convert free energy and synchronize cellular chemistry. Most importantly, functional proteins occupy only small, isolated regions of sequence space. Nature evolved heritable symbolic data processing to seek out and use those sequences. That system has three parts: a memory of how amino acids behave in solution and inside proteins, a set of code-keys to access that memory, and a scoring function. The code-keys themselves are the genes for cognate pairs of tRNA and aminoacyl-tRNA synthetases, AARS. I outline the surprising links between all these questions and the structural duality of the base-pairing that holds genes together and how those links arise from the experiments.

This review provides a detailed analysis of hemodiafiltration (HDF), its progress from an emerging technique to a potential conventional treatment for chronic hemodialysis patients, and its current status. The article covers advances, methodologies, and clinical benefits of HDF, spe-cifically focusing on its impact on cardiovascular health, survival rates, and overall well-being. The text also addresses concerns about the safety of HDF and provides evidence to dispel worries re-lated to the elimination of beneficial substances and infection risks. Additionally, the article ex-plores the potential implications of expanded hemodialysis (HDx) as an alternative to HDF, its classification, safety profile, and an ongoing trial assessing its non-inferiority to HDF. Supported by evidence from randomized controlled trials and observational studies, the review emphasizes the superiority of HDF as a hemodialysis modality, advocating for its positioning as the gold standard in treatment. However, it acknowledges the need for extensive research to define the role of HDx in comprehensive treatment approaches for individuals undergoing dialysis. The synthesis of current knowledge underscores the importance of ongoing exploration and research to refine hemodialysis practices for optimal patient outcomes.

To obtain long-term data on the use of everolimus in patients who underwent liver transplantation for hepatocellular carcinoma, we conducted a retrospective, single-center analysis of adult recipients transplanted between 2013 and 2021. Patients on everolimus-incorporating immunosuppression were matched with those on tacrolimus using an inverse probability of treatment weighting methodology. Two propensity-matched groups of patients were thus compared: 233 (45.6%) receiving everolimus versus 278 (54.4%) on tacrolimus. At a median (interquartile range) follow-up of 4.4 (3.8) years after transplantation, everolimus patients showed a reduced risk of recurrence versus tacrolimus (7.7% versus 16.9%; RR=0.45; P=0.002). At multivariable analysis, microvascular infiltration (HR=1.22; P<0.04) and a higher tumor grading (HR=1.27; P<0.04) were associated with higher recurrence rate while being within Milan criteria at transplant (HR=0.56; P<0.001), a successful pre-transplant downstaging (HR=0.63; P=0.01) and use of everolimus (HR=0.46; P<0.001) had a positive impact on the risk of post-transplant recurrence. EVR patients with earlier drug introduction (30 days; P<0.001), longer treatment duration (P<0.001), and higher drug exposure (5.9ng/mL; P<0.001) showed lower recurrence rates versus TAC. Based on our experience, everolimus provides a reduction of the relative risk of hepatocellular carcinoma recurrence, especially for advanced-stage patients and those with earlier drug administration, higher drug exposure, and longer time on treatment. These data advocate for early everolimus introduction after liver transplantation to reduce the attrition rate consequent to chronic immunosuppression.

Open Education, Open Educational Practices (OEP), and Open Educational Resources (OER) have emerged as significant opportunities for enhancing global sustainability information sharing. However, the creation and sharing of OER, as well as the usage of OEP in Higher Education for Sustainable Development (HESD), remain limited. This study explores the implementation of OEP in HESD, aiming to empower students to co-produce OER on Sustainable Development (SD). This study, drawing on the theoretical approach of the principle of constructive alignment, proposes the development of students’ digital competence in OER production. A two-group pre-test post-test analysis of 409 students (Psychology, Economics, Education, Geography) reveals a significant increase in digital competence over time among students who produced OER on SD, compared to their peers enrolled in courses unrelated to OER content development. We delve into the practical implications for designing OEP in HESD and strategize to support students in their OER production processes.

This review delves into the critical role of automation and sensor technologies in optimizing parameters for thermal treatments within electricity power generation. The demand for efficient and sustainable power generation has led to a significant reliance on thermal treatments in power plants. However, ensuring precise control over these treatments remains challenging, necessitating the integration of advanced automation and sensor systems. This paper evaluates the pivotal aspects of automation, emphasizing its capacity to streamline operations, enhance safety, and optimize energy efficiency in thermal treatment processes. Additionally, it highlights the indispensable role of sensors in monitoring and regulating crucial parameters such as temperature, pressure, and flow rates. These sensors enable real-time data acquisition, facilitating immediate adjustments to maintain optimal operating conditions and prevent system failures. It explores the recent technological advancements, including machine learning algorithms and IoT integration, which have revolutionized automation and sensor capabilities in thermal treatment control. Incorporating these innovations has significantly improved the precision and adaptability of control systems, resulting in heightened performance and reduced environmental impact. This review underscores the imperative nature of automation and sensor technologies in thermal treatments for electricity power generation, emphasizing their pivotal role in enhancing operational efficiency, ensuring reliability, and advancing sustainability in power generation processes.

We present our preliminary experience with transarterial radioembolization (TARE) with Yt-trium-90, and investigate the influence of additional treatments, injected activity, mean dose to the tumor on overall survival (OS). Our database was interrogated to retrieve patients who had undergone TARE with Yttrium-90 (90Y) glass or resin microspheres. The following information were searched: 1) type of pathology; 2) sex; 3) age; 4) administered activity; 5) mean dose to the tumor; 6) additional treatments; 7) OS. The OS of the different groups of patients were compared (p<0.05). A bivariate correlation (p<0.05) was used to investigate the association between injected activity and OS, and between mean dose to the tumor on OS. Thirty-nine patients were retrieved (Sex: 27 M, 12 F; mean age: 61.26 ± 14.95 years): 23 with hepatocellular carcinoma (HCC) and 16 with colorectal cancer (CRC) liver metastasis. Globally, patients with HCC demonstrated a sig-nificantly longer OS than those with CRC liver metastasis (22.66±19.11 vs. 10.41±8.75 months; p=0.022). Among patients with CRC liver metastasis, those receiving TARE and additional treatment demonstrated a longer OS than patients receiving only TARE (23.50±19.76 months vs. 8.54±5.31; p=0.018), there was a direct correlation between injected activity and OS (R=0.55, p=0.034) and between mean activity reaching the tumor and OS (R=0.812; p=0.008). Patients with HCC receiving TARE achieved a longer OS than those with CRC liver metastasis. Additional treatments, increasing injected activity and higher mean dose to the tumor seem beneficial for outcome, especially in patients with CRC liver metastases.

Despite being small and simple structured in comparison to their victims, virus particles have the potential to harm severly and even kill highly developed species such as humans. To face upcoming virus pandemics, detailed quantitative biophysical understanding of intracellular virus replication mechanisms is inevitable. Unveiling the relationship of form and function might allow to determine putative attack points relevant for the systematic development of direct antiviral agents (DAA) and potent vaccines. Biophysical investigations of spatio-temporal dynamics of intracellular virus replication so far are rare. We are developing a framework to allow for fully spatio-temporal resolved virus replication dynamics simulations based on partial differential equations models (PDE) and evaluated with advanced numerical mathematical methods on leading supercomputers. This study presents an advanced highly nonlinear model of the genome replication cycle of a specific RNA virus, the Hepatitis C virus (HCV). The diffusion-reaction model mimics the interplay of the major components of the viral RNA (vRNA) cycle, namely non structural viral proteins (NSP), vRNA and a generic host factor. Technically, we couple surface PDEs (sufPDEs) on the 3D embedded 2D Endoplasmatic Reticulum (ER) manifold with PDEs in the 3D membranous web (MW) and cytosol volume. (The MWs are the replication factories growing on the ER induced by NSPs.) The sufPDE/PDE model is evaluated at realistic reconstructed cell geometries which are based on experimental data. The simulations couple the effects of NSPs which are restricted to the ER surface with effects appearing in the volume. The volume effects include the host factor supply from the cytosol and the MW dynamics. Special emphasis is put to the exchange of components between ER surface, MWs and cytosol volume. As the vRNA spatial properties are not fully understood so far in experiment, the model allows for vRNA both restricted to the ER and moving in the cytosol. The visualization of the simulation resembles a look into some sort of fully 3D resolved “in silico microscopes” to mirror and complement in vitro / in vivo experiments for the intracellular vRNA cycle dynamics. The output data are quantitatively consistent with experimental data and provoke advanced experimental studies to validate the model.

This study introduces a technique to uncover concealed patterns in satellite altimetry data, reflecting sea level variations in inland water bodies. We applied the methodology to the Caspian Sea, using altimetry data from four satellite missions over 27 years (1993-2020): TOPEX/Poseidon, Jason1, Jason2, and Jason3. The approach involves two steps: estimating sea level trends and identifying breakpoints that indicate trend shifts; and leveraging time lags between breakpoints at various locations to classify water drainage areas according to their degree of influence on each period. By revealing concealed patterns in the altimetry data, this technique can provide insights to understand the impacts of global warming and local climate changes on sea level fluctuations in the Caspian Sea. We hope that our study can facilitate subsequent interdisciplinary research on the intricate interplay between climate change and hydrological processes in inland water bodies.

The paper focuses on the different dynamical systems for the prey-predator model for different cases which includes greater depth of the food chain and varying number of preys and predators. We simulate the different postulated models and provide a comparative study for the same.

It has been more than a century since Erlang published his paper in 1909. The classical queueing system for the M/D/c queue has been investigated by many authors. The key is to find the roots of an equation using explicit or numerical methods. We present an alternate form of explicit solution(s) of this/these root(s) using the Lambert-W function in this paper. In addition, the unsaturated probabilities of the number of customers in the system is derived explicitly in terms of this/these root(s). Finally, the mean number of customers in the system and the mean queueing delay are obtained from these probabilities. The exact queueing delay formula for the M/D/c queue is expressed in closed-form in terms of the root(s). Numerical results show that they are in excellent agreement with the numerical results published by Seelen, Tijms and Van Hoorn.

Background: Patients with bipolar disorder (BD) receive traditional Chinese Medicine (TCM) for unmet clinical needs with psychotropic medications. However, the clinical characteristics of practices and outcomes of TCM in BD are not fully understood. This cohort study investigated the clinical characteristics, principal diagnoses, TCM interventions, and TCM prescriptions in patients with BD. Methods: 12,113 patients with BD were withdrawn from Taiwan's longitudinal health insurance database 2000 (LHID 2000) between 1996 and 2013. Chi-squared test for categorical variables and independent t-test for continuous variables. A p-value less than 0.05 indicated significance. Results: One-thousand and three hundred nineteen patients who visited TCM clinics after the diagnosis of BD were in the TCM group, while those who never visited TCM were in the non-TCM group (N= 1,053). Compared to the non-TCM group, patients in the TCM group had younger average age, a higher percentage of female individuals, more comorbidities of anxiety and alcohol use disorders, and higher mood stabilizer usage rates. The TCM group exhibited pain-related indications, including joint pain, myalgia, myositis, headache, and sleep disturbances. Corydalis yanhusuo and Shu-Jing-Huo-Xue-Tang were the most useful single herb and herbal formulas. Conclusions: Physicians need to be aware of the use of TCM in Patients with BD.

Rising demand and urbanization have led to the global increase and intensification of livestock production. Intensive production has harmful effects on the environment, public health (due to the emergence of zoonotic diseases), and animal welfare. In order to better understand how livestock production intensifies as countries develop and incomes rise, we examine the relationship between income per capita and intensification of poultry and cattle, using the states of India as a study region. We also replicate this analysis at the district level to test whether the relationship holds at different spatial scales. We identify outlying states and districts to see if there are policies that can keep agriculture production largely extensive, even as economic growth occurs. The results support the relationship of income being positively correlated with the proportion of livestock in intensive conditions. However, there are notable outlier states which have grown wealthy while still maintaining largely extensive production, indicating that there may be some cases where economic growth can occur without intensification.

Partial negative allosteric modulators (NAM) of the mGlu5 receptor are an excellent alternative to full antagonists and NAMs because they retain some therapeutic effects and, at the same time, have a much broader therapeutic window. Here, we investigated whether partial mGlu5 NAM, M-5MPEP induced a fast and sustained antidepressant-like effect, characteristic of rapid-acting antidepressant drugs (RAADs) like ketamine, in C57BL/6J mice. M-5MPEP caused a rapid, dose-dependent antidepressant-like action in the tail suspension test (TST) 60 min after injection. This effect was antagonized by an AMPA receptor antagonist (NBQX) and a TrkB receptor antagonist (ANA-12) but not by 5HT1A and 5HT2A/2C receptor antagonists. Furthermore, M-5MPEP (30 mg/kg) induced sustained antidepressant-like effects 24 h after the last of four administrations. These effects were revealed in the splash test, designed to measure apathy-like state, and in the TST. Western blot and ELISA analyses indicated the involvement of the TrkB/BDNF pathway in the sustained M-5MPEP effects. Additionally, prolonged effects of M-5MPEP were entirely reversed by the TrkB receptor antagonist ANA-12 in both the splash test and the TST, confirming the critical role of TrkB receptor activation in the sustained antidepressant-like effect of M-5MPEP. Importantly, M-5MPEP enhanced the subthreshold dose of (R)-ketamine in the TST, indicating both substances' convergent mechanisms of action and the possibility of their practical use in treating depression.

The article discusses how tourism policy has changed since World War II, highlighting how the everchanging political and economic climate has shaped policies that were formerly centered on promoting inbound travel and tourist growth to becoming more inclusive and sustainable. Within that framework, the paper systematically examines the development of Indian tourism policy and thoroughly explores the implications of its most recent version. It concludes that modern tourism policies have evolved into comprehensive frameworks that structure the growth of the industry and make it more inclusive and sustainable. Nations such as India are well-suited to meet the demands of modern tourism and offer appropriate frameworks for sustainable and resilient tourist growth.

The integration of artificial intelligence (AI) into the European Foundation for Quality Management (EFQM) business excellence model is a promising approach to improve the efficiency and effectiveness of excellence in organizations. This research paper’s integrated framework follows the ISO/IEC 23053 standard in addressing some of the concerns related to time and cost associated with the EFQM model, achieving higher EFQM scores, hence operational excellence. A case study involving a UAE government organization serves as a sample to train the AI framework. Historical EFQM results from different years are used as training data. The AI framework utilizes the unsupervised machine learning technique known as k-means clustering (with k=2). This technique follows the ISO/IEC 23053 standard to predict EFQM output total scores based on criteria and sub-criteria inputs. The research paper's main output is a novel AI framework that can predict EFQM scores for organizations at an early stage. If the predicted EFQM score is not high enough, then the AI framework provides feedback to decision makers regarding the criteria that need reconsideration. Continuous use of this integrated framework helps organizations attain operational excellence. This framework is considered valuable for decision makers as it provides early predictions of EFQM total scores and identifies areas that require improvement before officially applying for the EFQM excellence award. This approach can be considered as an innovative contribution and enhancement to knowledge body and organizational practices.

To delve into the structure-function relationship of transmembrane proteins (TMPs), robust protocols are needed to produce them in a pure, stable, and functional state. Among all hosts that express heterologous TMPs, E. coli has the lowest cost and fastest turnover. However, many of the expressed in E. coli TMPs are misfolded. Several strategies have been developed to either direct the foreign TMPs to E. coli’s membrane or retain them in a cytosolic soluble form to overcome this deficiency. Here, we summarize protein engineering methods to produce chimera constructs of the desired TMPs fused to either signal peptide or precursor maltose binding protein (pMBP) to direct the entire construct to the periplasm, therefore depositing the fused TMP in the plasma membrane. We further describe strategies to produce TMPs in soluble form by utilizing N-terminally fused MBP without signal peptide. Depending on its N- or C-terminus location, a fusion to apolipoprotein A-I can either direct the TMP to the membrane or shield the hydrophobic regions of the TMP, maintaining the soluble form. Strategies to produce G-protein coupled receptors, TMPs of Mycobacterium tuberculosis, HIV-1 Vpu, and other TMPs are discussed. This knowledge could increase the scope of TMPs’ expression in E. coli.

The development of new medical monitoring applications requires precise modeling of the human body effects as well as simulating and emulating realistic scenarios and conditions. The first aim of this paper is to develop realistic and adjustable human body 3D emulation platforms which could be used for evaluating emerging microwave-based medical monitoring/sensing applications such as the detection of brain tumors, strokes, breast cancers as well as for capsule endoscopy studies. The new phantom recipes are developed for microwave ranges for the realistic shaped phantom molds. The second aim is to validate the feasibility and reliability of the phantoms for practical scenarios with electromagnetic simulations using tissue layer models and biomedical antennas. The third aim is to investigate the impact of the water temperature in the phantom cooking phase on the dielectric properties of the stabilized phantom. The evaluations show that the dielectric properties of the developed phantoms correspond closely to those of real human tissue. The error in dielectric properties varies between 0.5-8%. In the practical scenario simulations, the differences obtained with phantoms-based simulations in S21 parameters are 0.1-13dB. However, the differences are smaller in the frequency ranges targeted for medical applications.

This paper investigates nonverbal communication in human interactions, with a specific focus on facial expressions. Employing a Long Short-Term Memory (LSTM) architecture and a custom-ized facial expression framework, our approach aims to improve virtual agent interactions by incorporating subtle nonverbal cues. The paper contributes to the emerging field of facial expres-sion generation, addressing gaps in current research and presenting a novel framework within Unreal Engine 5. The model's architecture, trained on the CANDOR corpus, captures temporal dynamics, and refines hyperparameters for optimal performance. During testing, the trained model showed a cosine similarity of -0.95. This enables the algorithm to accurately respond to non-verbal cues and interact with humans in a way that is comparable to human-human interac-tion. Unlike other approaches in the field of facial expression generation, the presented method is more comprehensive and enables the integration of a multi-modal approach for generating facial expressions. Future work involves integrating blendshape generation, real-world testing, and the inclusion of additional modalities to create a comprehensive framework for seamless hu-man-agent interactions beyond facial expressions.

We present a modified version of the Szilard Engine, demonstrating that an explicit measurement procedure is entirely unnecessary for its operation. By considering our modified engine, we are able to provide a new interpretation of Landauer’s original argument for the cost of erasure. From this view, we demonstrate that a reset operation is strictly impossible in a dynamical system with only conservative forces. Then, we prove that to approach a reset yields an unavoidable instability at the reset point. Finally, we present an original proof of Landauer’s principle that is completely independent from the Second Law of Thermodynamics.

The present study focuses on the investigation of fatigue, social support and quality of life that characterizes social workers. Furthermore, the study aims to highlight the effect of demographic and occupational characteristics on the above factors. A total of 400 social workers with an average age of 39.05 years took part in the research. Most were women, single, residents of cities of more than 100,000, and health care workers. Participants were asked to answer online questionnaires (FAS for fatigue, MSPSS for social support and GHQ-28 for quality of life). From the analysis of the data, it was found that the level of fatigue of the social workers is at low levels. At the same time, the level of occurrence of negative symptoms is also low, with physical symptoms appearing more often than the rest. Participants receive a high level of support from their environment, and more so from the "significant other" in their life. Finally, it was found that the fatigue, social support and quality of life of social workers is affected by the age of the social workers, the total years of service, gender, marital status, place of residence, employer and position of responsibility.

Reconstructing a 3D model of a scene from a set of multiple views poses a significant challenge in the field of computer vision. The advent of NeRF has marked a major breakthrough in this domain. However, there is a need to extend the capabilities of the NeRF model to enable editing tasks such as relighting and deformation, as well as to enhance its training efficiency. Neural reflectance fields introduce the concept of the reflectance equation into the NeRF framework to achieve relighting of the NeRF model. We leverage the TensoRF approach, which incorporates tensor decomposition and employs multiple tensors to store features, to expedite the training process of the NeRF model. Our novel method, called StensorR, combines the reflectance equation and tensor decomposition within the radiation field model framework. Differing from previous approaches, we employ a single tensor to store scene features and render the surface color of our scene using a simplified reflectance equation. This approach accelerates model convergence and enables relighting of the NeRF model. Experimental results demonstrate that our method achieves a 50% faster convergence rate compared to existing relighting radiation field models, while successfully enabling relighting and improving the quality of synthesized images from new viewpoints.

Human arteries show structural and functional peculiarities according to the nutrient and oxygen needs of a specific vascular district. This architectural heterogeneity is reflected in the pathological setting of cardiovascular diseases (CVDs). Indeed, the responsiveness to cardiovascular risk factors, the morphological and molecular patterns are discriminating factors among CVDs affecting different vascular beds. Micro-RNAs (miRNAs) are endogenous regulators of gene expression and fine tuners of vascular cell differentiation, thus these non-coding RNAs can modulate the arterial heterogeneity. The identification of a miRNA signature artery-specific would be promising in the therapy of CVDs, especially in frail elderly patients. In the present review we will provide a concise description of the arterial tree heterogeneity on structural and cellular basis, mainly in the pathological context. Secondly, we will address the miRNA potential as crucial mediators of arterial heterogeneity focusing on abdominal aorta and femoral artery, with the final goal of strengthening the search of more targeted therapies in CVDs and stratification approaches in frail elderly patients.

In this paper, we consider particles together with the surrounding space as an indivisible system, and then investigate the maximum symmetry of the system at the quantum level. We introduce a new quantity to describe the evolution of this system before and after measurement. The effective mass of gravity is estimated. We also show that a free quantum particle as the source of energy and momentum do not produce gravity.

Background: Brief Resolved Unexplained Events (BRUEs), formerly known as Apparent Life-Threatening Events (ALTE), are concerning episodes of short duration (typically &lt; 1 min) characterized by a change in breathing, consciousness, muscle tone, and/or skin color. In some cases, SARS-CoV-2 infection has been associated with episodes of BRUEs in previously healthy children.This study aimed to compare the demographic, respiratory, perinatal, and infectious characteristics in children affected by BRUE before the COVID-19 pandemic and after the spread of SARS-CoV-2. Methods: We conducted a retrospective observational study covering January 2018 to March 2020 (pre-COVID-19) and April 2023 (during the ongoing COVID-19 pandemic). Collected variables included clinical information during pregnancy and neonatal details of children with BRUE. Results: The number of children in the pre-COVID-19 period was 186 (41%); after the emergence and spread of SARS-CoV-2, it was 268 (59%). The risk of infection at birth for children developing BRUE was higher during the pandemic. Children were less likely to have ongoing symptomatic infection during BRUE during the pandemic (coefficient B = 0.783; p=0.009). Respiratory symptoms during BRUE were more frequent during the pandemic (coefficient B = 0.654; p=0.052). Fever during BRUE was less likely during the pandemic (coefficient B = -0.465, p=0.046). Conclusions: The study suggests that the COVID-19 pandemic has significantly impacted children with BRUE, potentially due to changes in hygiene practices and maternal-fetal infections.

Background and objectives: Effective management for chronic diseases, hereditary and rare diseases and Thalassaemia in particular constitutes an important indicator for the quality of healthcare systems. We aimed at assessing healthcare services in different countries by using publicly available health indicators and by surveying Thalassaemia patients and their caregivers. Materials and Methods: We reviewed official worldwide databases from the WHO, World Bank, and scientific resources and also used a structured patient tailored self-completed questionnaire to survey Thalassaemia patients and their caregivers in 2023. Results: A total of 2,082 participants were surveyed (mean age 27 years, males 42%). About 1 in 4 respondents had less than high school education, while 24% had a bachelor degree. About a third of respondents were married and had either full- or part-time employment. The vast majority (~80%) had initiated transfusion therapy between 1 – 4 years of age. Only 42% reported no delays in receiving blood transfusion, while 47% reported occasional delays and 8% serious delays. About half of patients reported being very satisfied (11%) or satisfied (38%) with the quality of provided services, while 1 in 3 patients reported being unsatisfied or very unsatisfied, and their access to treatment was difficult or very difficult due to traveling expenses and high cost of treatment. Conclusion: Important improvements in the care of Thalassaemia patients have been documented during the past decades. Nevertheless, our recent survey reveals many unmet needs where additional focus is required through national healthcare systems in order to address them effectively and achieve satisfactory patient outcomes.

The necessity for effective intrusion detection systems (IDS) in big data environments has grown critical due to the rising prevalence of big data systems and the rising amount of security threats. Applying conventional intrusion detection methods to the enormous and intricate data produced by big data ecosystems presents difficulties. Deep learning, has proven to be exceptionally adept at deciphering complex, large-scale data. This study proposes a Deep Learning-based Intrusion Detection System (IDS) created specifically for the Big Data environment. Traditional intrusion detection systems struggle to efficiently identify and prevent cyber threats due to the ever-increasing volume and complexity of data in current networks. We suggest an IDS that makes use of Deep Learning (CNN, LSTM, GAN, etc.), to address this problem. These cutting-edge neural network topologies give the system the ability to process and analyze massive amounts of data for precise intrusion detection. Data collection, data preprocessing, feature engineering, DL model training, intrusion detection, warning generation, and reaction are some of the crucial parts of the suggested IDS. The data collection module mines the Big Data environment for network traffic, system logs, and security event information. To make sure the data is suitable for analysis, it is preprocessed. To improve the detection abilities of the DL models, important features are extracted from the data using feature engineering approaches.

The impact of COVID-19 pandemic on the cardiovascular healthcare services in Croatia has not been systematically examined. In this study, we compared utilization and provision of cardiovascular services in Croatia during the pre-pandemic period (2017 to end of 2019) and pandemic period (2020 to end of 2021) by using large nationwide data from the Croatian Health Insurance Fund, an institution covering 95% of all insurance claims in Croatia. We report that the use of advanced heart failure treatment modalities increased while the number of coronary angiographies decreased while the number of performed percutaneous coronary interventions remained similar, even increasing in the setting of acute myocardial infarction, comparing pandemic to pre-pandemic period. Similarly, the number of transcatheter aortic valve implantations increased significantly during the pandemic era. There was a significant increase in laboratory diagnostic testing with troponin and natriuretic peptide assays during the pandemic period while the use of most cardiovascular services remained stable or only slightly decreased, compared to pre-pandemic period. These data suggest that Croatian cardiovascular healthcare services during COVID-19 pandemic showed resilience and managed to maintain or even increase the number of various diagnostic and interventional procedures despite the widespread societal and logistical challenges encountered during pandemic.

Despite UAV multi-target detection exhibits considerable developmental potential worldwide, it suffers distinct challenges compared with traditional tasks in this field. These challenges include insufficient feature extraction capabilities for small targets, limited capabilities for multi-dimensional feature fusion, as well as constraints on hardware computation parameters. Especially in mission scenarios such as disaster detection, these challenges will be further amplified. Consequently, this paper introduces SSE-YOLO, an innovative YOLO framework algorithm specially designed to address these challenges. To enhance the model's feature extraction capability, we employ the SPDConv module to replace the original Conv in the backbone section, utilizing depth-separable convolution instead of traditional convolution pooling. Concurrently, we eliminate the SPPF module at the bottom and address a new Separate Kernel Attention Pyramid Pooling (SKAPP) module, substantially enhancing the feature fusion capability at the model's core. Moreover, to address the challenge of multi-dimensional feature fusion, we replace the Concat module of the neck and head with E-BiFPN, transmitting feature information from the backbone to the lower network through four CBS blocks, which effectively resolves the issue of lost contextual information in the model. Meanwhile, SSE-YOLO undergoes ablation experiments on the VisDrone2019 dataset to evaluate its effectiveness against alternative methods, and experimental results illustrate the model's exceptional precision in detecting UAV targets. In comparison to models with comparable experimental accuracy, SSE-YOLO requires remarkably fewer parameters. On the VisDrone2019-DET-test-dev dataset, SSE-YOLO enhances mAP by 17.3%, with a 42.5% reduction in the parameter amounts. Therefore, the proposed method effectively tackles the challenge of reconciling low parameters and high accuracy, presenting a novel pathway for deep learning-based UAV multi-target detection.

Power grid fault diagnosis technology has been widely used at home and abroad. With the access of distributed power sources and diversified loads, the distribution network has changed from a passive network to an active network, and the current has changed from "one-way" to "two-way". The structure of distribution network, equipment environment and operating conditions are becoming more and more complex, and the fault diagnosis and localization of active distribution network is becoming more and more difficult. With the rapid development of artificial intelligence, power grid fault diagnosis based on intelligence is unprecedented. This paper introduces the research status of distributed photovoltaic grid-connected fault diagnosis technology, and expounds the history of fault diagnosis technology, which mainly includes expert system, artificial neural network, Bayesian network, fuzzy set theory, rough set theory, Petri net analytical model and multi-source information fusion, etc. The applicability and characteristics of these diagnoses are described, and the existing defects and the overall direction of improvement are briefly described Finally, the key technical problems and future directions in the field of power system fault diagnosis are pointed out by combining theory with practice, so as to promote the further development of this field.

he paper offers an innovative cooking utensil design for remote, isolated, and even peri-urban communities at a low price, with high reliability and simple construction. It can alleviate energy poverty and improve food security. This utensil uses only local solar energy directly and allows comfortable indoor cooking. This paper provides the design principles of a solar cooker/frying pan or generic heater, based on a PV panel or a plurality of them, which are directly connected to a plurality of Positive Thermal Coefficient (PTC) resistors to match the power. PTCs are nowadays produced in massive quantities and are widely available at low cost. The proposed device does not require an electronic controller or a battery for its operation. The aim is for family use, although the design can be easily scaled to a larger size or power, maintaining its simplicity. Electric heating inside or attached to the cooking pot, plus the temperature self-limiting effect of PTCs, allows for thermally insulating the cooking pot from its outside using ordinary materials. Insulation en-hances energy efficiency during cooking and keeps cooked food warm for a long time. Clean development would receive a significant impulse with its application. A simple mathematical model describes its functioning and states guidelines for adequate design. The results indicate a successful proof of concept and high efficiency both for water and oil as representatives of cooking.

This work presents a heat transfer and boiling model that computes the evolution of the temperature field in a representative steel workpiece quenched from 850 or 930°C by immersion in water flowing at average velocities of 0.2 or 0.6 m/s, respectively. Under these conditions, all three boiling regimes were present during cooling: stable vapor film, nucleate boiling, and single-phase convection. The model was based on the numerical solution of the heat conduction equation coupled to the solution of the energy and momentum equations for water. The mixture phase approach was adopted using the Lee model to compute the rates of water evaporation-condensation. Heat flux at the wall was calculated for all regimes using a single semi-mechanistic model. Therefore, evolution of boiling regimes at every position on the wall surface was automatically determined. Predictions were validated using laboratory results, namely: a) Videorecording the upward motion of the wetting front along the workpiece wall surface, and b) cooling curves obtained with embedded thermocouples in the steel probe. Wall heat flux calculations were used to determine the importance of the simultaneous presence of all three boiling regimes on the heat flux distribution. It was found that this simultaneous presence leads to high heat flux variations that should be avoided in production lines.

The study aimed to showcase how implementing a patient blood management (PBM) program effectively cut unnecessary red blood cell (RBC) transfusions in a New York City urban community teaching hospital. Analyzing seven years from 2013 to 2019, a retrospective review of RBC transfusions was conducted. Following PBM introduction, considerable improvements were observed annually. These included a drop in mean pretransfusion hemoglobin levels from 7.26g/dL (2013) to 6.58g/dL (2019), a 34% reduction in yearly RBC unit transfusions, and fewer units given to patients with pre-Hgb levels ≥7g/dL (1210 units in 2013 to 310 units in 2019). Furthermore, the study noted a decline in two-unit RBC orders when Hgb levels were ≥7g/dL from 65 orders in 2013 to merely 3 in 2019. The estimated total cost-savings attributed to the six-year PBM program duration after full implementation in 2014 amounted to $2.1 million US dollars. Overall, PBM implementation significantly decreased RBC transfusions and enhanced transfusion practices. The findings emphasize that successful PBM strategies don't always necessitate extensive resources or increased budgets but instead rely on the application of intuitive methods, as evidenced by this study.

This narrative review aims to provide a comprehensive overview of the scientific literature on wheelchair badminton and its distinctive aspects, encompassing abilities and disabilities, propulsion technique, and the use of a racket. The relatively young history of wheelchair badminton is reflected in the scarcity of scientific studies within this domain, highlighting the need for further investigation. The review systematically covers existing articles on wheelchair badminton, offering a nearly exhaustive compilation of knowledge in this area. Findings suggest that WH2 athletes engage in more intense matches with a higher frequency of offensive shots compared to WH1 athletes. Moreover, backward propulsion induces distinct physiological responses and alterations in propulsion kinematics, potentially leading to performance decrements. The use of a badminton racket further influences propulsion kinetics and kinematics, potentially impacting performance and injury risk. Further research is imperative to explore additional perspectives, address existing gaps, and expand the scope of study within the wheelchair badminton domain. This narrative review serves as a foundation for future investigations, emphasizing the necessity of continued research to enhance our understanding of wheelchair badminton.

Carotid intima-media thickness (CIMT) is a surrogate indicator for atherosclerosis and has been shown to predict cardiovascular risk in multiple large studies. Identifying and characterizing molecular markers for carotid atheroma plaque formation can be critical for early intervention and prevention of atherosclerosis. This study performed transcription factor (TF) network analysis of transcriptomic data focusing on two TF genes, ZNF385D, HAND2, whose polymorphisms reportedly associate with carotid atherosclerosis. Gene expression data were measured from pieces of carotid endarterectomy of hypertensive patients each paired with one sample of distant macroscopically intact tissue. TF networks were reconstructed for ZNF385D and HAND2 and their association with carotid atheroma progression examined using gene-set enrichment analysis with high statistical significance (p<6.95e-7) suggesting involvement of expression quantitative loci (eQTL). Examination of the regulation and correlation patterns suggests high clinical and interventional impacts of the two TF genes on impairing carotid atheroma plaque formation and preventing carotid atherosclerosis.

Cutaneous T cell lymphoma (CTCL) is a devastating, potentially fatal T lymphocyte malignancy affecting the skin. Despite all efforts, the etiology of the disease remains unknown. Infectious agents have long been suspected as factors or co-factors in CTCL pathogenesis. This review deals with the panel of bacterial and viral pathogens that have been investigated so far in an attempt to establish a potential link between infection/carriage and CTCL development. A special focus is given to a recently discovered human protoparvovirus, namely the cutavirus (CutaV), which has emerged as a plausible CTCL etiological agent. Available evidence in support of this hypothesis as well as alternative interpretations and uncertainties raised by some conflicting data are discussed. The complexity and the multifacetedness of the Parvoviridae family of viruses are illustrated by presenting another protoparvovirus, the rat H-1 parvovirus (H-1PV). H-1PV belongs to the same genus as the CutaV but carries a considerable potential for therapeutic applications in cutaneous lymphoma.

The quality of veterinary medicinal products (VMP) is essential for efficient disease management. Therefore, VMPs that do not meet the required standards of quality can lead to increased sickness, death, and the development of antimicrobial resistance, posing a danger to both animals and humans. This study aimed to identify substandard and falsified VMPs on the Rwandan market using the Global Pharma Health Fund (GPHF)-Minilab™. VMP samples were purchased and collected in a cross-sectional study from veterinary retail pharmacies from five districts in four provinces of Rwanda, during May and June 2023. These samples were transported to the Veterinary Laboratory of the School of Animal Sciences and Veterinary Medicine, Nyagatare campus, University of Rwanda, and stored until analysis. The samples were subjected to physical and chemical analysis following the GPHF-Minilab™’s guidelines. A total of 130 samples from two categories of VMP were purchased from 10 veterinary retail pharmacies in urban and rural areas. The results of this study revealed that none of the assessed VMP samples failed physical tests (visual inspection, weight verification, and disintegration test). 10 samples (Sulfamethoxazole/Trimethoprim) out of 130 (7.7%) passed the visual inspections but later failed to comply with Thin-Layer Chromatography result specifications. This is an indication of the presence of substandard and falsified VMP circulating in Rwanda that warrants regular inspection and chemical quality control of VMPs along the supply chain.

Background: The association between the individual and combined effects of moderate-to-vigorous physical activity (MVPA) and sleep quality with physical frailty in community-dwelling older adults is still unknown. Subjects and Methods: A cross-sectional study was conducted with a participants pool comprising older adults who had not been officially assessed as requiring nursing care or support services.. Physical frailty was assessed using Liu's definition based on Fried's concept. MVPA was measured by a triaxial accelerometer, and individuals who meet either MPA for ≥300 min/week, VPA for ≥150 min/week, or both of them were defined as "MVA+." "SLP+" was defined as a Pittsburgh Sleep Quality Index score &lt;5.5 points. We performed an ordinal logistic regression analysis to calculate the odds ratios (ORs) and 95% confidence intervals (CI) regarding the relationship between MVPA and sleep quality with physical pre-frailty and frailty. Results: The final analysis included 811 participants. After multivariate adjustment, compared to the MVA+SLP+, the MVA−SLP+ (OR 2.56, 95%CI: 1.80–3.62) and the MVA−SLP− (OR 3.97, 95%CI: 2.33–6.74) participants showed significantly higher ORs for physical pre-frailty and frailty. Conclusion: Community-dwelling older adults who did not meet MVPA criteria, regardless of sleep quality, had a higher risk of physical pre-frailty and frailty.

The swelling behavior of titanium-modified austenitic stainless steel 15-15Ti was investigated by pre-implantation of He at room temperature followed by Ni irradiation at 580 °C to peak doses of 120, 240 and 400 dpa. Relatively smaller cavities were observed in the zone of helium implantation while large cavities appeared in the region near the damage peak. A correction formula of the dpa curve was proposed and applied for samples with large swelling. It is found that the steady-state swelling rate of 15-15Ti keeps at ~1% /dpa even to high doses. By comparing the swelling data of the helium-implanted and helium-free regions at same doses, 70 dpa and 122 dpa, the suppression of excessive helium on swelling can be deduced at such doses.

Objectives: To analyse and detail surgical process improvement activities that achieve the highest economic impact. Methods: Over 4 years, a team of technicians and healthcare professionals implemented a set of Lean surgical process improvement projects at Vall d’Hebron University Hospital (VHUH), Barcelona, Spain. These projects now form part of the daily routine in the surgical process. The economic impact on the hospital's surgical activity budget was analysed. Results: Process improvements have led to annual operational savings of over € 8.5 million. These improvements include better patient flow, better management of information between healthcare professionals, and improved logistic circuits. Conclusions: The current cultural shift towards process management in large hospitals implies shifting towards results-based healthcare, patient-perceived value (VBHC) and value-added payment. A Lean project implementation process requires long-term stability. The reason a considerable number of projects fail to complete process improvement projects is the difficulty involved in establishing the project and improving management routines. Few studies in the literature have investigated the economic impact of implementing Lean management a posteriori, and even fewer have examined actual cases. In this real case study, changes to surgical block management were initiated from zero. After being carefully thought through and designed, changes were carried out and subsequently analysed.

The escalating reliance of modern society on information and communication technology has rendered it vulnerable to an array of cyber-attacks, with distributed denial-of-service (DDoS) at-tacks emerging as one of the most prevalent threats. This paper delves into the intricacies of DDoS attacks, which exploit compromised machines numbering in the thousands or more to disrupt data services and online commercial platforms, resulting in significant downtime and financial losses. Recognizing the gravity of this issue, various detection techniques have been explored, yet the quantitative and prior detection of DDoS attacks has seen a decline in recent methods. This research introduces an innovative approach by integrating evolutionary optimization algorithms and machine learning techniques. Specifically, the study proposes XGB-GA Optimization, RF-GA Optimization, and SVM-GA Optimization methods, employing Evolutionary Algorithms Opti-mization with TOPOT-Genetic Programming. Datasets pertaining to DDoS attacks were utilized to train machine learning models based on XGB, RF, and SVM algorithms, and 10-fold cross-validation was employed. The models were further optimized using evolutionary algo-rithms, achieving remarkable accuracy scores: 99.99% with the XGB-GA method, 99.50% with RF-GA, and 99.99% with SVM-GA. Furthermore, the study employed TPOT to identify the optimal algorithm for constructing a machine learning model, with the genetic algorithm pinpointing XGB-GA as the most effective choice. This research significantly advances the field of DDoS attack detection by presenting a robust and accurate methodology, thereby enhancing the cybersecurity landscape and fortifying digital infrastructures against these pervasive threats.

Among endocrine cancers, thyroid carcinoma is the most prevalent type of cancer. It's prevalence has been increased throughout the world during the last decades, which shows great regional variations. Considering the increasing prevalence and occurrence of thyroid cancer cases, in this study we: Among endocrine cancers, thyroid carcinoma is the most prevalent type of cancer. It's prevalence has been increased throughout the world during the last decades, which shows great regional variations. Considering the increasing prevalence and occurrence of thyroid cancer cases, in this study we decided to evaluate the clinical and pathological charactristics of this endocrine system cancer in the population of thyroid cancer patients reffered to imam Khomeini Hospital in Sari between March 2014 and March 2021. decided to evaluate the clinical and pathological charactristics of this endocrine system cancer in the population of thyroid cancer patients reffered to imam Khomeini Hospital in Sari between March 2014 and March 2021.

Neuropathic pain is caused by a lesion or disease of the somatosensory system and is one of the most incapacitating pain types, representing a significant non met medical need. Due to the increase in research in the field and since innovative therapeutic strategies are required, namely in intractable neuropathic pain, neurostimulation has been used. Within this approaches, transcranial magnetic stimulation (TMS) that uses a transient magnetic field to produce electrical currents over the cortex emerges in the literature. Since this is an area in expansion and due to the putative role of TMS, we performed a bibliometric analysis in Scopus with the primary objective of identify the scientific production related to the use of TMS to manage neuropathic pain. The research had no restrictions and the analysis focused on the characteristics of the literature retrieved, scientific collaboration and main research topics from inception to July 6, 2023. A total of 474 articles were collected. A biggest co-occurrence between the terms “neuropathic pain” and “transcranial magnetic stimulation” was obtained. The journal “Clinical Neurophysiology” leads the Top 5 most productive sources. The United States is the most productive country with 50% of the documents being “review articles” followed by France with 56% of the documents being “original articles”. Lefaucheur, JP and Saitoh, Y are the two most influents authors. The most frequent type of documents was “original article”. This study allows to perform a general overview in the field of TMS application for neuropathic pain and is useful to establish future directions of research in this field.

Based on acoustic fluid elements, dynamic analysis was performed on liquid sloshing modes and liquid-filled containers considering the fluid-structure interaction (FSI) effect. The liquid sloshing modes in two-dimensional (2D) and three-dimensional (3D) containers were analyzed, and the results were compared with liquid sloshing modes measured in tests and theoretically calculated modes. This thus verifies correctness of the simulation method based on acoustic fluid elements. Cylindrical liquid-filled containers with different water levels were subjected to modal analysis and dynamic and time-historical analysis. Results show that the finite element analysis (FEA) based on acoustic fluid elements can accurately simulate liquid sloshing modes in liquid-filled containers and vibration characteristics of these containers with different liquid levels. The vibration frequency of liquid-filled containers declines obviously with rising liquid level. The liquid level significantly affects distributions of the maximum displacement, maximum acceleration, and maximum von Mises stress on the sidewall of liquid-filled containers. Numerical simulations based on acoustic fluid elements provides an effective and reliable method for dynamic analysis of liquid-filled containers considering the FSI effect.

Cross-institutional secondary use of medical data benefits from structured semantic annotation, which, ideally, enables matching and merging semantically related data items from different sources and sites. While numerous medical terminologies and ontologies, as well as some tooling, exist to support such annotation, cross-institutional data usage based on independently annotated datasets is challenging for multiple reasons: the annotation process is resource intensive and requires a combination of medical and technical expertise since it often requires judgment calls to resolve ambiguities resulting from non-uniqueness of potential mappings to various levels of ontological hierarchies and relational and representational systems. Divergent resolution of such ambiguities can inhibit joint cross-institutional data usage based on semantic annotation since data items with related content from different sites will not be identifiable based on their respective annotations if different choices were made without further steps such as ontological inference, which is still an active area of research. We hypothesize that a collaborative approach to semantic annotation of medical data can contribute to more resource efficient and high-quality annotation by utilizing prior annotational choices of others to inform the annotation process, thus both speeding up the annotation itself and fostering a consensus approach to resolving annotational ambiguities by enabling annotators to discover and follow pre-existing annotational choices. Therefore, we have implemented a prototypical Collaborative Annotation Tool (CoAT), evaluated its usability, and present first inter-institutional experiences with this novel approach to promoting practically relevant interoperability driven by use of standardized ontologies.

Humanity is currently facing several global problems, such as global warming, air pollution, water pollution, deforestation, desertification and land degradation, which are connected to the consequences of negative human activity. One of the possible and effective institutional tools for environmental protection is the environmental education of the general population. It is a relatively well-known and used environmental protection policy tool that governments of all developed countries have in their instrument mix. This qualitative analysis assigned itself the task of investigating whether the ability of environmental education can be affected by certain neuropsychological diseases in addition to thinking about the psychology of environmental education at large. In order to fulfill this main task, the authors asked themselves the following research questions: 1st - Is pedagogical psychology identical and also applicable in the case of environmental education? And 2nd - What effect do some neuropsychological disorders have on the ability of environmental education? Based on the study, analysis, selection and comparison of current professional scientific works obtained from the research activities of current researches on this topic, it is possible to accept the premise that the psychology of environmental education is basically the same as the general psychology of education and that neuropsychological diseases do indeed affect the ability of environmental education similarly to scholarly education.

Recent advancements have revolutionized interplanetary spacecraft missions by combining low-thrust propulsion systems with planetary Gravity-Assist (GA) maneuvers. This study investigates/improved a novel dual-step efficient-robust homotopy algorithm, grounded in indirect optimal control principles, to analyze fuel-optimal bang-bang control problems. The methodology integrates efficient techniques, including the homotopic method, compatible normalization, and improved switching function detection, aimed at enhancing optimal convergence in solving low-thrust gravity-assist spacecraft missions. To illustrate practical application, an Earth-to-Jupiter interplanetary scenario utilizing Mars-GA is examined. Results demonstrate the algorithm's superior efficacy in achieving fuel efficiency, robust convergence, and remarkable accuracy compared to existing solutions.

Purpose: this paper evaluates the effect of thermo-formed aligners with complementary biomechanical attachments (CBA) on periodontal ligaments (PDL) during the expansion process of the maxillary arch using simulations based on the finite element method (FEM). Methods: four types of teeth (canine 3, premolar 4, premolar 5 and molar 6) were modeled using 3D CAD. In addition, aligners, CBAs and PDL were also 3D modeled. With this information, a FEM model was generated, and a clinical rehabilitation scenario was simulated. For the validation of the results, a comparison with medical records was performed. Results: for canine 3, the displacement was 0.134 mm with a maximum stress of 4.822 x10-3MPa in the amelocemental junction. For premolar 4, the displacement was 0.132 mm at a maximum stress of 3.273x10-3MPa in the amelocemental junction. Premolar 5 had a displacement of 0.129 mm and a stress of 1.358 x10-3MPa at 1 mm from the amelocemental junction. Molar 6 had a displacement of 0.124 mm and a maximum stress of 2.440 x10-3MPa. Conclusions: The simulations showed that the use of CBA reduces tooth tipping. The model with Vestibular CBA presented the best results in terms of the dental movement of expansion of the maxillary arch with the use of thermoformed aligners. Significance: Considering the difficulty of performing in vivo tests that evaluate the configuration effectiveness of the different CBA alternatives in thermoformed aligners, FEM techniques were used to reduce time and costs, and get accurate results with minimal errors.

Lentil (Lens culinaris Medik) is an annual herb that belongs to family Fabaceae, it is one of the most ancient food crops that has been grown in the world, and originated from southwestern Asia as early as 7000 BC. In Spain lentil acreage raised 42,200 ha in 2022, two authonomous regions Castilla-León and Castilla-La Mancha are traditionally the large producers. Lentils have the capacity to fix atmospheric N2 in symbiosis with rhizobia and, additionally it is considered moderately tolerant to drought which in turn makes this pulse a low water and carbon fingerprint crop. The aim of this study was to assess the symbiotic responsiveness to rhizobia strains of several lentil accessions from the Spanish germplasm bank, to determine the nutritional value and mineral seed composition and, to evaluate the agronomic performance of six selected accessions in two regions under rainfed conditions and different management systems. The protein content of all genotypes was higher than 25%, with two outstanding seeds from accessions: BGE025596 and BGE026702 which account for >30% of protein and <2% of fat. Accessions BGE016362 and, BGE026702 had an exceptional Fe content, > 1 g/100 g of seed flour. The agronomic performance varied depending upon the cropping región.

To support the development of research evidence and behavioral health policy that aligns with the priorities of youth and families serviced in child and youth mental health systems, this project documents the service outcomes that caregivers value most. A diverse group of caregivers, representing six regions of the United States, participated in two rounds of virtual one-hour focus groups. In round 1, participants identified what they hoped to gain from using behavioral health services for themselves, their families, and their child and discussed what made services a positive experience for them. They then reported their top three most hoped for outcomes. In round 2, groups validated and refined summary findings from round 1. Caregivers prioritize service quality outcomes, primarily. They expressed a desire for an accessible, respectful, and supportive treatment environment underpinned by well-trained and culturally responsive professionals. Caregivers also desire seamless cross-sector provider collaboration and care transitions which integrate the insights and preferences of families and children themselves to craft a customized care plan. Priority outcomes not related to service quality included hoping to gain increased knowledge, resources, and tools and techniques to support the mental health needs of their children, help them improve their daily functioning, and develop more effective interpersonal communication skills. Caregivers also reported hoping to experience less stigma related to the mental health needs of their children and to achieve personal fulfillment for themselves and their children. Research and policies should prioritize and be designed to address the outcomes that matter to youth and families.

The weighted K-nearest neighbors (WKNN) algorithm has been widely used in indoor fingerprint localization, which utilizes fingerprint distance (FD) of pairwise positions to discriminate the physical distance (PD) between them. However, due to the varied states of different wireless access points (APs), their contribution to FD discrimination capability varies. In our study, we analyzed several critical causes that affect APs’ contribution, including AP’s health state, the distance, and the direction between APs and position pairs. Inspired by these insights, a threshold was set for all sample RSS to eliminate the impact of abnormal APs on FD, and a correction quantity for each RSS was provided by the distance between APs and sample positions to reduce the strong signal influence on FD. Furthermore, a priority weight was designed by RSS differences (RSSD) to further optimize FD’s capability to discriminate PD. Integrating the above policies, a new indoor fingerprint localization technique is redefined, referred to FD’s discrimination capability improvement WKNN (FDDC-WKNN), which is suitable for indoor scenes with a large number of APs that are not uniformly managed. Our simulation results show that the correlation and consistency between FD and PD are well improved, with strong correlation increasing from 0 to 76% and high consistency increasing from 26% to 99%, which confirms that the proposed policies can greatly enhance FD’s discrimination capabilities to PD, and we also found that abnormal APs can cause significant impact on FDs’ discrimination Capability. Further, by implementing the FDDC-WKNN algorithm in experiments, we obtained the optimal K value in both the simulation scene and real library scene, under which the average localization errors have been reduced from 2.2732m to 1.2183m and from 3.4295m to 2.2068m, respectively. In addition, compared to not using the FDDC-WKNN, the cumulative distribution function (CDF) of the localization errors curve converged faster and the errors fluctuation is smaller, which demonstrate FDDC-WKNN having stronger robustness and more stable localization performance to the state of APs in indoor environments.

Floor mats are commonly used to improve the impact sound performance of existing homes, but the actual reduction does not consistently appear depending on the test-bed conditions used to determine it. Therefore, this study evaluated the effects of the environmental conditions of the test-bed on the impact sound reduction performance of different floor mats. The Korean Industrial Standard, KS F 2865, specifies the measurement method in the test room and sets the thickness range of the available target floor structure from bare slab 120 mm to 210 mm. The evaluation method is ∆?, which is the difference in standardized impact sound levels before and after the installation of the floor finishing material. In this study, a total of eight types of floor mats were tested in four different test-beds according to KS F 2865. The impact sources used were tapping, bang machines and a rubber ball to consider both light-weight and heavy-weight impact sounds. The results were derived as impact sound reduction performance for each frequency band and a single number quantity. The results showed that light impact sound had a similar minimum reduction characteristic of at least 38 dB, regardless of the floor structure on which the mat was installed. However, the heavy-weight impact sound showed different tendencies depending on the floor mat and the characteristics of the floor structure of the test-bed when a bang machine and a rubber ball were used. In particular, the reduction by the bang machine showed less than half the tendency of the reduction by the rubber ball, and the tendency of the heavy-weight impact sound to be reduced depending on the floor mat was maintained, but the reduction differed depending on the test bed. The reduction was larger in the box-type test room than in the real-life type test room, and among the box-type test rooms, the one with a thicker bare slab showed a relatively larger reduction. In addition, the reliability of the measurement results was discussed through the correlation analysis between the single number quantities depending on the thickness of the bare slab of the test-beds.

Previous studies have demonstrated that cold pools play a pivotal role in the initiation and organization of convection, yet their influence on the evolution of GFs remains inadequately understood. A destructive wind event associated with a rearward gust front (RGF, 8 grade gale appeared after passing GF) and a prior gust front (PGF, 10 grade gale appeared before passing GF) over the north coast of China on 10 June 2016 was analyzed. Using multiple observation data as well as the four-dimensional Variational Doppler Radar Data Assimilation System (VDRAS), we found that the intensity of the GFs increased with increasing cold pool strength, depth and propagation speed. Two schematic models were proposed to explain the discrepancy between GFs and associated cold pools. The depth and intensity of the cold pool in RGF are found to be relatively shallower and weaker, leading to a correspondingly reduced strength in both outflow and convergence. In contrast, the enhanced vertical shear and boundary northeaster inflow of PGF generate intensified and more organized downdrafts, resulting in a deeper cold pool, robust outflow, and convergence. These findings offer novel insights into the diversity of GFs and associated cold pools.

Food allergy (FA) affects approximately 6–8% of children worldwide causing a significant impact on the quality of life of children and their families. In the years, the possible role of weaning in the development of FA has been studied. According to recent studies, the role of weaning in its development is still controversial and influenced by several factors, such as the type of food, the age at food introduction and family history. In this narrative review, we aimed to collected the most recent evidence about weaning and its role in FA development, organizing the gathered data based on both the type of study and the food.

Street view images can help us better understand the city environment and potential characteristics. With the development of computer vision and deep learning, the technology of semantic segmentation algorithms has become more mature. However, DeeplabV3+, which is commonly used in semantic segmentation, has shortcomings such as a large number of parameters, high requirements for computing resources, and easy loss of detailed information. Therefore, this paper proposes LM-DeeplabV3+, which aims to greatly reduce parameters and computations of the model while ensuring the segmentation accuracy. Firstly, the lightweight network MobileNetV2 is selected as the backbone network, and the ECA attention mechanism is introduced after MobileNetV2 extracts shallow features to improve the ability of feature representation; secondly, the ASPP module is improved, and on its basis, the EPSA attention mechanism is introduced to achieve cross-dimensional channel attention and important feature interaction; thirdly, a loss function named CL loss is designed to balance the training offset of multiple categories and better indicate the segmentation quality. This paper conducted experimental verification on the Cityspaces dataset, and the results showed that the mIoU reached 74.9%, which was an improvement of 3.56% compared to DeeplabV3+; the mPA reached 83.01%, which was an improvement of 2.53% compared to DeeplabV3+.

The excellent properties of carbon fibers, in combination with the high price of carbon fibers, makes it interesting to recycle these fibers. Pyrolysis is already an established recycling method to recover the carbon fibers, but in this process also the sizing is removed which could result in lower mechanical properties because of bad adhesion between the fiber and matrix. In this study, recycled carbon nonwoven reinforcements made from pyrolyzed carbon fibers were pre-treated in order to improve the mechanical properties of recycled carbon polyamide and recycled carbon polypropylene composites. The pre-treatment involves applying a to the matrix adapted primer coating to the nonwoven by spraying. Via compression molding, polyamide and polypropylene composites were prepared with and without pretreatment. The tensile and interlaminar shear strength of these composites were measured to determine the effect of the pretreatment. Results revealed that both strengths could be increased by pretreatment of the carbon nonwoven and the increase was largest for the PP composites.

Objective: The pleiotropic effect of hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors (statins) is responsible for potent defense against inflammatory response. This study evaluated the inhibitory effects of HMG-CoA reductase inhibitors on monosodium urate (MSU)-induced inflammatory response through the regulation of interleukin-37 (IL-37) expression. Methods: Serum was collected from patients with gout (n = 40) and from healthy controls (n = 30). The mRNA and protein expression of target molecules IL-1b, IL-37, caspase-1, and Smad3 was measured in THP-1 cells stimulated with MSU, atorvastatin, or rosuvastatin using real-time quantitative polymerase chain reaction and Western blot assay. Transfection with IL-1b or Smad3 siRNA in THP-1 cells was used to verify the pharmaceutical effect of statins in uric acid-induced inflammation. Results: Serum IL-37 level in gout patients was significantly higher than in controls (p < 0.001) and was associated with serum uric acid level (r = 0.382, p = 0.008). THP-1 cells stimulated with MSU markedly induced IL-37 mRNA expression and transition of IL-37 from cytoplasm to nucleus. Recombinant IL-37 treatment dose-dependently inhibited activation of caspase-1 and IL-1b in MSU-induced inflammation. Atorvastatin and rosuvastatin attenuated caspase-1 activation and mature IL-1b expression but augmented translocation of IL-37 from cytoplasm to nucleus. Atorvastatin and rosuvastatin induced phosphorylation of Smad3 in THP-1 cells treated with MSU crystals. Statins potently attenuated translocation of IL-37 from cytoplasm to nucleus in THP-1 cells transfected with Smad3 siRNA compared to cells with negative control siRNA. Conclusion: This study revealed that statins inhibit MSU-induced inflammatory response through augmentation of phosphorylated Smad3-mediated IL-37 expression in THP-1 cells.

Climate change presents an urgent and impending threat to virtually all global biological systems. In recent years, there has been a surge in research endeavors aimed at investigating the potential relationship between changes in climate patterns and the spread of infectious diseases. This scoping review included studies on global warming and infectious diseases from 2019 to 2023, The studies included in this research were obtained from reputable academic databases such as Web of Science and google scholar. A systematic keyword search was conducted to identify relevant studies, and a predefined set of inclusion criteria was applied to review and select the appropriate studies for analysis. This review found that climate change has a remarkable impact on the dissemination and incidence of many infectious diseases, it increases microbial resistance and may increase the prevalence the arthropods-borne diseases with mild effect on fungal infections, also, the low to middle income countries may be affected more than other countries from these virulent pathogens, this study concluded that a future research in the field of climate change and infectious diseases should involve a thorough examination of the transmission of diseases, considering both direct and indirect modes of transmission

This study aims to determine the impact of the type of ICT usage on household income from main vegetables, agriculture (including main vegetables), and total income. This study is based on surveys and interviews with vegetable farmers using structured questionnaires conducted in three villages in Indonesia, including Cianjur, Sleman, and Malang in West Java, Yogyakarta, and East Java, respectively. The data were collected from 375 respondents selected in each region from November 2021 to March 2022. An econometric model called the multivariate linear regression (MLR) model is used to assess heterogeneous factors that influence the possibility of increasing the income of vegetable farmers. The study found that variables that use ICT as a primary variable, household, marketing, geographical characteristics, and immediate source information in agriculture have a significant impact on household income (P < 0.01) from primary vegetables, agriculture, and total income, with multiple R squares of 70.5, 72.0, 73.7% and F statistics of 28.48, 30.66, and 33.34, respectively. In summary, this novel study shows that the five categories of information technology used in farming and selling of harvest have a positive impact on household incomes

One of the main challenges of the globalization became the increased destabilization and frequent economic crises. In general, managing an economic crisis is a particularly difficult task for any economy (developed or developing, and regardless the size). In the context of globalization, the process faces additional challenges. On the one hand, the world economy witnessed a shift from traditional purely economic instruments to more financial mechanisms of economic development. Indeed, the liberalization of the economy since the 1990s complicated the traditional trends of the world market development, resulting in significant fluctuation of the growth rates between different countries and regions. To respond to this evolution, governments and international organizations changed well-established strategies. For example, financial sector found itself given expanded role in economic development, with, different financial mechanisms used as key variables to evaluate an economic growth. On the other hand, the increased role of financial sector in a globilised world, increased financial relations among individual states and thus, interdependences. This “financial globalization” causes important fluctuations in the system and, as a result, causes instability in socio-economic development. Thus, an economic crisis of any important economy soon becomes a global issue (financial crisis of 2008, economic crisis of 2020).The recent global economic crisis due to the Covid-19 world pandemic, appeared to be unique for several reasons. First, it highlighted the transnational and origin-specific nature of the crisis. Second, it appeared to be the first case when non-economic factors caused a major economic crisis. As a result, this crisis turned out to be particularly difficult to predict and to manage. In this case, the main strategy of the global post-crisis rehabilitation became the restoration of the economy's predictability and ensuring its ability to obey the classical principles. According to the Organic Law on "Economic Freedom" of the European Union (2011), any factor which increases the equilibrium amount of output is reflected in the economic rehabilitation plan. Such exogenous factors are primarily fiscal mechanisms, i.e. - Reduction of taxes and increase of state expenditures. This crisis caused important structural problems with their effects on public expenditures (especially health expenditures, to the public expenditures, economic growth, price stability and budget balance) in both, developed and developing countries. Nearly every state declared an increase in public debt, inflation, and unemployment rates, while an important decrease was shown in growth rates and capital outflows. As the crisis due to the world pandemic was radically different from previous economic crises, it was difficult to manage it efficiently at the initial stage. It was complicated to forecast the scenarios of the unknown crisis with non-standard nature which was more linked to epidemiologic factors than objective economic law. The dynamics of crisis resolution depended on correct forecasting and effective implementation of global, but especially country-based reforms. More importantly, this crisis showed the important role of individual states to manage the global crisis. The traditional function of a government to ensure country’s socio-economic growth and security, increases in an extraordinary environment, such as sharp economic fluctuations and crises. In such contexts, the centralized management functions are sharply activated. The global pandemic processes have updated the economic essence of the state. The large scale of the latest economic crisis due to the world pandemic has determined the need for mutually coordinated development of anti-crisis plans of different countries. In today's dynamic landscape, modern global systems are redefining the standards and priorities of national economic policies. The economic status of countries is changing significantly as a result of their participation in these systems. As a result of these changes, today's global economy is marked by the proliferation of regionalism and the emergence of spatial economic frameworks. Thus, classical economic concepts are evolving, giving rise to a new model known as economic nationalism. This paradigm shift is generating new risks, which are increasing in severity and scope. The overriding objective of economic policy is now to ensure and predict stable development. Reflections are underway to meet the challenges of economic equilibrium and its social and institutional sustainability.In addition to the decentralization of the unified governance system, the global economy is characterized by the activation of centralized governance elements within individual countries. This requires the development of new norms for global cooperation and the careful balancing of national integration and development factors. The question of government's influence on the economy and the delegation of its powers becomes relevant once again. Effective coordination of public administration is based on the principle of decentralized government, which is a key element of a democratic model of society and facilitates the transfer of management tools to the public. The key objectives of this research are focused on the optimal distribution of state functions and the study of hierarchical principles of territorial organization within the country, fiscal mechanisms for the distribution of powers, as well as the particularities of the structuring of the spatial economy and its budgetary provisioning mechanisms.The example of the last two economic crisis showed that contemporary anti-crisis strategies should reflect several considerations. First, it becomes impossible to develop a single unified model of crisis management. Even in the context of important economic and financial globalization, the current decentralization and new spatial economic processes make it necessary to find a balance between the local priorities and global interests. Second, the role of non-economic crisis-causing factors increases compared to economic determinants. That is why international and country-based reforms should aim at not only economic rehabilitation, but also on the social, cultural and environmental restorations. Third, it becomes difficult to correctly predict the consequences of the crisis and thus, the effects of the anti-crisis strategy. Consequently, the success of the post-crisis rehabilitation of the countries' economies depends significantly not only on the effective realization of their own plan, but also, in general, on the specificities of the global economy and on the ability of the world markets to overcome the negative consequences of a crisis. In this context, the development of complex post-crisis platforms and state post-crisis strategies is the priority. The most effective component in the anti-crisis strategy is the monetary instruments of economic management. As for the determinant of successful functioning of economy, the priority should be given to the regulation of exchange rate, interest rate and inflationary processes. A state anti-crisis programs should reflect the crisis prevention strategy, which, on its turn, should differentiate the economic functions of the state and crisis management mechanisms according to the specific trends of given processes. It should aim at gaining stable development of the economy. Additionally, an anti-crisis plan should reflect the role of the society in the development process and its mental changes under crisis conditions. The state should be responsible for establishing and monitoring anti-crisis management mechanisms, financial recovery of the country and formation of correct relations. It is especially important to ensure economic security, to stabilize the development process and standard of living, to support the private sector and small entrepreneurship, to increase economic freedom, to ensure effective distribution of labor and capital, and others. All strategies of the anti-crisis platform should be focused on social results, as it should contribute to a fair distribution of income and to poverty reduction.

Transcranial direct current stimulation (tDCS) is acknowledged for its non-invasive modulation of neuronal activity in psychiatric disorders. However, its application in insomnia research yields varied outcomes depending on different tDCS types and patient conditions. Our primary objective is to elucidate its efficiency and uncover the underlying mechanisms in insomnia treatment. We hypothesized that anodal prefrontal cortex stimulation activates glutaminergic projections from the infralimbic cortex (IL) to ventrolateral preoptic area (VLPO) to promote sleep. After administering 0.06 mA of electrical currents for 8 minutes, our results indicate significant non-rapid eye movement (NREM) enhancement in naïve mice within the initial 3 hours post-stimulation, persisting up to 16-24 hours. In the insomnia group, tDCS enhanced NREM sleep bout numbers during acute stress response and improved NREM and REM sleep duration in subsequent acute insomnia. Sleep quality, assessed through NREM delta powers, remains unaffected. Interference of the IL-VLPO pathway, utilizing designer receptors exclusively activated by designer drugs (DREADDs) with the cre-DIO system, partially blocked tDCS's sleep improvement in stress-induced insomnia. This study elucidated that the activation of the IL-VLPO pathway mediates tDCS's effect on stress-induced insomnia. These findings support the understanding of tDCS effects on sleep disturbances, providing valuable insights for future research and clinical applications in sleep therapy.

Studies at the molecular, systemic, and epidemiological levels have shown that chronic metal exposure is linked to significant health consequences, including cancer, affecting hundreds of millions worldwide. Subtle and convoluted mechanisms underline metals' toxicity and carcinogenicity. The use of sensors for carcinogenic metals' trace detection is on the rise due to their selectivity, simplicity, and affordability. Biotechnology and microelectronics in the development of sensors have grown complementarily in recent years. This study offers a comprehensive overview of current research and advancements in developing sensors for detecting carcinogenic metals. Here, we have focussed on the developed biosensor platforms for group 1 carcinogens, i.e., arsenic, nickel, cadmium, chromium, and beryllium, along with their brief roles in human carcinogenesis. This review also looks at the importance of sensing such metal exposure in humans from a larger perspective, hoping to influence future research toward early prevention and treatment of illnesses like cancer.

[Objective] To investigate the expression of ALDH2 in hepatocellular carcinoma and its correlation with macrophage infiltration and with the activation of specific subtypes of macrophages. [Methods] Transcriptome and clinical data from patients with hepatocellular carcinoma were downloaded from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases and analyzed and collated using R and Perl software. In the TCGA hepatocellular carcinoma dataset, the Wilcoxon test was used to identify macrophage activation-related gene sets that show differential expression between hepatocellular carcinoma and normal tissues. Single-cell sequencing combined with bulk data was used to analyze macrophage infiltration of hepatocellular carcinoma immune cells and the activation and recruitment of different subtypes of macrophages. Single-factor Cox regression and minimum absolute convergence and selection operator (Lasso) were used to identify survival-related genes and construct prognostic models of HCC. The patients were divided into two groups based on their model scores. The Wilcoxon test was used to identify differentially expressed genes (DEGs) between the two groups, and gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses of the DEGs were performed. Single-sample gene set enrichment analysis (ssGSEA) was performed to explore the possible mechanism underlying the differences in prognosis. The reliability of the model was verified using the ICGC hepatocellular carcinoma dataset. A Kaplan‒Meier curve was constructed and used to analyze the influence of macrophage activation-related gene expression on survival and prognosis in patients with hepatocellular carcinoma. The log-rank test and the independent t test were used to analyze survival time data and to compare immune cell infiltration in the two groups. [Results] In a comparison of hepatocellular carcinoma and paracancerous tissues, the expression of six of 137 macrophage activation-related genes (ALDH2, CCNB2, CYP2C9, CYP3A4, F9 and KLKB1) was found to be significantly correlated with overall survival time (OS) in patients with hepatocellular carcinoma. Based on this finding, a prognosis assessment model for hepatocellular carcinoma was constructed. The OS of the patients in the high-scoring group was significantly shorter than the OS of the patients in the low-scoring group (P<0.05), and the model predicted the prognosis of patients with hepatocellular carcinoma independently of sex, age, tumor grade and stage. The area under the receiver operating characteristic (ROC) curve of the model used to predict 1-, 2-, and 3-year survival was greater than 0.7 in both the test set and the validation set. GO enrichment of DEGs between the high- and low-scoring groups of the model suggested that the DEGs are mainly related to immune function. GSEA suggested that the tumor-infiltrating immune cells in the high-scoring group were macrophages, Th2 cells and Treg cells and showed that the number of tumor-infiltrating immune cells, including NK cells, was lower in the high-scoring group than in the low-scoring group. With respect to immune function, the immune checkpoint of the high-scoring group was higher than that of the low-scoring group. Single-cell sequencing data indicated the recruitment of B cells, M0 cells, M1 cells and M2 cells to the hepatocellular carcinoma microenvironment and suggested that ALDH2 regulates related signaling pathways in a way that promotes the differentiation of macrophages into M2-type macrophages. [Conclusion] M2-type macrophages are the dominant type of macrophages associated with immune infiltration in hepatocellular carcinoma. The macrophage-associated activation gene ALDH2 activates the macrophage polarization signaling pathway and negatively regulates the differentiation of macrophages into M2-type macrophages.

Machine learning (ML) based on neural network (NN) facilitates data-driven techniques for handling large amounts of data, either obtained through experiments or simulations at multiple spatio-temporal scales, thereby finding the hidden patterns underlying these data and promoting efficient research methods. The main purpose of this paper is to extend the capabilities of a new solver, called realFluidReactingNNFoam, under development at University of Perugia in OpenFOAM with NN algorithm for replacing complex real-fluid thermophysical property evaluations, using the approach of coupling OpenFOAM and Python-trained NN models. Currently, NN models are trained against data generated using the Peng-Robinson equation of state (PR-EoS) assuming mixture frozen temperature. The OpenFOAM solver, where needed, calls the NN models in each grid-cell with appropriate inputs, and the returned results are used and stored in suitable OpenFOAM data structures. Such inference for the thermophysical properties is achieved via the “Neural Network Inference in C made Easy” (NNICE) library, which proved to be very efficient and robust. The overall model is validated considering a liquid-rocket benchmark comprised of liquid-oxygen (LOX) and gaseous-hydrogen (GH2) streams. The model accounts for real-fluid thermodynamics and transport properties, making use of the PR-EoS and the Chung transport models. First, the development of a real-fluid model (RFM) with artificial neural network is described in detail. Then, the numerical results of the transcritical mixing layer (LOX/GH2) benchmark are presented and analyzed in terms of accuracy and computational ef-ficiency. Results of the overall implementation indicate that the combined OpenFOAM and ML approach provides a speed-up factor higher than seven, while preserving the original solver accuracy.

Contactless charging is evolving fast in many domains and applications such as the electrical vehicles (EV). The principle consists of transferring energy between two systems without having any electrical connection between them. This power transfer can be realized by emitting a magnetic field for Inductive Power Transfer (IPT). In the automotive domain, the application of contactless charging to supply power to the vehicle while driving is one of the solutions envisaged to solve the limited autonomy range of EV and reduced its cost but the system must comply with existing standards (e.g., allocated frequency range and radiated electromagnetic emissions), as summarized in this paper.

: Peach processing generates significant amounts of by-products including peels, pomace, and seeds that are often discarded as waste, despite their rich content of bioactive components. Various extraction methods, such as solvent extraction, ultrasound-assisted extraction, and alkaline and acid hydrolysis, have been employed to recover valuable components from peach by-products and repurpose them in various products. These compounds have shown potential applications in the food, pharmaceutical, and cosmetic industries due to their antioxidant, antimicrobial, and anti-inflammatory properties. Furthermore, these wastes can also be used to produce functional ingredients, natural colorants, dietary supplements Alternative uses consist the use as animal feed, as composting materials and biofuels. This comprehensive review provides an overview of the valorization of peach by-products, focusing on their valorization and extraction techniques and potential applications.

Malnutrition problems are related to diets that lack one or more essential elements, which it is extremely important to food enrichment to improve the content of compounds effective for health. The objective of this study is to evaluate the effect of the addition of Ca2+, K+ and Mg2+ on the induction of nutraceutical quality in grafted tomatoes grown in the NFT (Nutrient Film Technique) system. In the experiment, two factors were evaluated: plants with and without grafting and the foliar application of 10 ml L−1 Ca2+, 4 ml L−1 K+ and 10 ml L−1 Mg2+ cations separately for each case, in addition to the control. The treatments were evaluated using a completely randomized design, with 5 repetitions per treatment. The interactive effects between grafting and foliar application of Ca2+ induced a greater content lycopene, β-carotene and total flavonoids in fruits of tomato. The interactive effects between the graft and the Mg2+ foliar applications obtained the best results in the phenol content. As regards, capacity DPPH and ABTS, the graft decreased concentration, increasing the content of these through foliar applications of calcium. Regarding the enzymatic variables, graft factor increased activity catalase, glutathione peroxidase and phenylalanine ammonium lyase, obtained the best results graft interaction and foliar application of calcium and magnesium. The results obtained demonstrate the influence of the use of grafts and foliar applications of cal-cium and magnesium as tools that could improve the nutraceutical quality content of tomato crop

Water networks are critical infrastructure components, ensuring the continuous supply of high-quality drinking water to consumers. To secure such water supply, regular maintenance, including the replacement of deteriorating pipelines, is essential. In this study, a methodology has been developed for determining optimal pipeline replacement solutions in water supply systems at water utilities with limited data availability. Hydraulic analysis has been conducted on the segment of 25 km of the water supply network using the free software EPANET. Applying water network optimization, eight pipeline replacement projects according to 13 pre-defined criteria have been identified and evaluated. The paper outlines the methods for evaluating the criteria, including defining specific quantitative limits. The Analytical Hierarchical Process (AHP) method was used in the paper to determine the weights of the criteria. The reason for applying this method refers to problems that involve a set of criteria with a mixed structure, including both quantitative and qualitative aspects. Also, the paper describes the steps of the multi-criteria optimization method VIKOR, used to select the optimal project. This paper, considered as case studie, describes a method, i.e. application of a new principles and an innovative way to solve a problem for developing countries.

This study proposes a methodology for identifying time intervals in which time-of-use (ToU) energy tariffs can be set. This is achieved by analyzing the variability in electric power demand and esti-mating the potential for demand flexibility. The proposed methodology is as follows: first, data preprocessing is performed, focusing on the organization and cleaning of individual consumption records. Subsequently, the data are processed and classified by using consumption variability analysis and clustering techniques. Then, representative clusters are selected and time intervals are analyzed to identify periods of high electric power consumption variability. This methodology was tested with real data from smart meters in the Colombian electrical system, in which time intervals with potential for settinh ToU tariffs were ultimately identified. This work promotes the implementation of demand response strategies that enhance sustainability and facilitate the transition to a more resilient energy landscape both nationally and internationally. The findings are expected to contribute to the formulation of tariff schemes that encourage con-scious changes in electric energy consumption patterns.

There are no investigations about the outcomes of idiopathic PVCs catheter ablation (CA) in athletes compared to sedentary population. We conducted a prospective single-centre observational study. The primary and secondary procedural outcomes were premature ventricular contractions (PVCs) post-ablation reduction in athletes vs. non-athletes group and in agonist vs. leisure-time athletes. The third was the evaluation of the resumption of physical activity and the improvement of symptoms in agonist and leisure-time athletes. From January 2020 to October 2022 we enrolled 79 patients with RVOT/LVOT/fascicular PVC presumed origin. The median percentage of decrease between the pre-procedure and post-procedure Holter monitoring in non-athletes group was 96 (IQR 68 – 98) and 98 in athletes group (IQR 92 – 99) (p=0,08). Considering the athletes, the median percentage of decrease in PVCs number was 98 (IQR 93-99) and 98 (IQR 87-99) respectively in leisure-time and agonistic athletes (p=0,42). Sixteen (70%) leisure time and 17 (90%) agonist athletes (p=0,24) have resumed physical activity 3 months after PVCs CA; among agonistic athletes, 59% have resumed competitive physical activity. Much of leisure-time (88%) and agonist (70%) athletes experienced an improvement in symptoms after ablation. PVC CA was effective and safe in both groups, reducing symptoms and allowing a quick and safe return to sports activities in athletes.

The main goal of the research is to assess the effectiveness of aerial ground-penetrating radar (GPR) in delineating boundaries between disturbed clayey ground and rock formations along the old Wadi. The study also tackles technical challenges associated with drone-based GPR applications in urban open areas, considering geological heterogeneity, topographic variations, and environmental conditions. The potential of using drone-based GPR equipped with an unshielded dipole antenna as a transformative tool in geospatial analysis was demonstrated. The research encompasses academic insights and field borehole drilling experiments to validate the accuracy and reliability of drone-based GPR data in real-world scenarios. Anticipated contributions include advancements in understanding drone-based GPR technology for mapping disturbed soil boundaries in foundation engineering applications and other relevant areas and recommendations for optimizing its performance in challenging terrains.

The efficiency and performance of Proton Exchange Membrane Fuel Cells (PEMFCs) are primarily influenced by ORR electrocatalysts. In recent years, atomically dispersed met-al-nitrogen-carbon (M-N-C) catalysts have gained significant attention due to their high active center density, high atomic utilization, and high activity. These catalysts are now considered the preferred alternative to traditional noble metal electrocatalysts. The unique properties of M-N-C catalysts are anticipated to enhance the energy conversion efficiency and lower the manufac-turing cost of the entire system, thereby facilitating the commercialization and widespread ap-plication of fuel cell technology. This article initially delves into the origin of performance and degradation mechanisms of Fe-N-C catalysts from both experimental and theoretical perspectives. Building on this foundation, the focus shifts to strategies aimed at enhancing the activity and durability of atomically dispersed Fe-N-C catalysts. These strategies encompass the use of bi-metallic atoms, atomic clusters, heteroatoms (B, S, and P), and morphology regulation to optimize catalytic active sites. The article concludes by detailing the current challenges and future pro-spects of atomically dispersed Fe-N-C catalysts.

In many developing countries of the world including Pakistan motorcycle steeling is one of the main issue that needs to be dealt with an iron hand as it leads to economic losses as well as crime increase in the society, according to the DOWN REPORT there were 28609 motorcycle stolen in 2019 and this number has been increased to 34908 in 2020. Now due to the increasing motorcycles stealing crime what measures can we take to reduce the number of motorcycle theft the rule of technology is enormous in this regards specially information technology (IT) , information technology can play an important role in the security of motorcycles from being theft by the thieves, Information technology provide us the GSM based control system which can be very help full to construct a security system for motorcycle in order to make it antitheft.

Abstract: (1) Background: Post-COVID syndrome is defined as symptoms that occur simultane-ously with or after COVID-19 infection, last for 12 weeks, and are not due to another diagnosis. Limited data are available on people’s long-term quality of life (QoL) following COVID-19 infection. The aim of this cross-sectional study was to investigate long-term QoL after COVID-19 among employees of the St. Josef Hospital in Paderborn, Germany, and to identify risk factors. (2) Methods: A monocentric, cross-sectional study was conducted using the validated and digitized WHOQOL-BREF questionnaire via Netigate® between 10/2022 and 02/2023. Data on QoL and global health status were collected in the following four domains: physical health, mental health, social relationships, and environment. (3) Results: The response rate was 73.84% (923/1250). Furthermore, 63.45% of hospital staff respondents reported at least one persistent symptom after COVID-19 infection, leading to significant differences in QoL. Pre-existing conditions, persistent symptoms, and disability after COVID-19 infection, as well as high BMI, no partnership, and low educational level were found to significantly contribute to long-term low QoL. (4) Conclusions: Obesity, lack of partnership, and a low level of education were independent risk factors for lower QoL post-COVID-19 infection in this cohort of hospital staff. Further multicenter studies are re-quired to validate the incidence and their suitability as independent risk factors for post-COVID syndrome.

There have been many researches on the surface acoustic wave (SAW) sensors for detecting sulfur-containing toxic or harmful gases. This paper aims to give an overview of the current state of the polymer films used in SAW sensors for detecting deleterious gases. By covering most of the important polymer materials, the structures and types of polymers are summarized, and a variety of devices with different frequency, such as delay lines and array sensors for detecting mustard gas, hydrogen sulfide and sulfur dioxide are introduced. The preparation method of polymer films, the sensitivity of the SAW gas sensor, the limit of detection, the influence of temperature and humidity, and the anti-interference ability are discussed in detail. The advantages and disadvantages of the films are also analyzed, and the potential application of polymer films in the future is also forecasted.

Regarding landscape preferences for highways, there is a dynamic interaction between users and the variety of natural and cultural landscape elements along the roadside, reflecting a balance between the highway and the natural environment. However, the rapid pace of urbanization has accelerated the development of highways, leading to the neglect or destruction of valuable landscapes. This highlights the need for visual preference assessments to protect aesthetic and environmental values. Currently, there is a lack of comprehensive criteria for assessing the visual preference of highway landscapes. Therefore, this study aims to review existing literature and establish complete assessment criteria. This study conducted a systematic literature review by searching for keywords in three databases: Web of Science, Scopus, and Google Scholar. The review included 22 papers published between 2013 and 2023 that met the criteria. An additional four relevant papers were included through a “snowballing” approach to supplement the research and results. The results of the study focused on the relationships between highway landscapes and users, user preferences, preference methods, and related variables. These inter-established relationships were used to complete an assessment framework, which establishes a basic reference standard for professionals.

In 2020, following the World Health Organization's declaration of COVID-19 as a pandemic, dental practices faced unprecedented disruptions globally. This retrospective cross-sectional study, conducted at a leading university dental hospital in the Lisbon Metropolitan Area, investigated the impact of these disruptions on dental caries. The study, spanning June 2019 to June 2021, included a full-mouth X-ray examination, along with sociodemographic, behavioral, and medical data. Our sample comprised 3,380 participants (2,007 females and 1,373 males), aged 18 to 99 years, divided into pre-lockdown and post-lockdown groups. We employed the Decayed, Missing, and Filled Teeth (DMFT) index to measure dental caries. Our findings revealed that nearly 90% of participants in both groups experienced dental caries, indicating a statistically significant difference between the pre-lockdown and post-lockdown periods. However, the impact of COVID-19 confinement varied among different demographic sectors, with age, educational background, and professional status emerging as the key determinants. This study highlights the need for a more nuanced understanding of the impact of the pandemic on oral health, emphasizing the role of sociodemographic factors in shaping dental health outcomes during such global health crises.

Provenance trials provide a valuable opportunity to evaluate the impact of extreme events on growth and wood properties. In this study, we have evaluated 81 Norway spruce provenances, tested in three provenance trials established in the Romanian Carpathians in 1972. The response to drought of the Norway spruce provenances – resistance, recovery, resilience, and relative resilience, has been examined, as well as the relationship between climate and growth, and the correlations between wood traits, the coordinates of origin and drought resilience indices. In each provenance trial, there were significant differences between provenances and years regarding wood widths and latewood percentage (LWP). Regarding the drought extreme events, the years when it occurred in all three provenance trials were 2000 and 2003. Significant differences between provenances for at least one drought resilience index have been found in all provenance trials, for the year 2000. By using subperiods of 25 years, changes in the relationship between climate and growth have been observed. Several provenances with high radial growth and good resistance and/or recovery have been identified. Provenances that performed better in common garden experiments could be used in assisted migration even beyond the current natural range.

Newly designed pentacyclic benzimidazole derivatives, featuring amino or amido side chains, were synthesized to assess their in vitro antiproliferative activity. Additionally, we conducted investigations into their direct interaction with nucleic acids, aiming to uncover potential mechanisms of biological action. These compounds were synthesized using conventional organic synthesis methodologies, alongside photochemical and microwave-assisted reactions. Upon synthesis, the newly derived compounds underwent in vitro testing for their antiproliferative effects on various human cancer cell lines. Notably, derivatives 6 and 9 exhibited significant antiproliferative activity within the submicromolar concentration range. Our biological assessment highlighted that the biological activity was strongly influenced by both the position of the N atom on the quinoline moiety and the position and nature of the side chain on the pentacyclic skeleton. Findings from fluorescence, circular dichroism spectroscopy, and thermal melting assays indicated a mixed binding mode—comprising intercalation and the binding of aggregated compounds along the polynucleotide backbone—of these pentacyclic benzimidazoles with DNA and RNA.

The use of autonomous Unmanned Aerial Vehicles (UAVs) has been increasing, and the autonomy of these systems and their capabilities in dealing with uncertainties is crucial. Autonomous landing is pivotal for the success of an autonomous mission of UAVs. This paper presents an autonomous landing system for quadrotor UAVs with the ability to perform smooth landing even in undesirable conditions like obstruction by obstacles in and around the designated landing area and inability to identify or the absence of a visual marker establishing the designated landing area. We have integrated algorithms like version 5 of You Only Look Once (YOLOv5), DeepSORT, Euclidean distance transform, and Proportional-Integral-Derivative (PID) controller to strengthen the robustness of the overall system. While the YOLOv5 model is trained to identify the visual marker of the landing area and some common obstacles like people, cars, and trees, the DeepSORT algorithm keeps track of the identified objects. Similarly, using the detection of the identified objects and Euclidean distance transform, an open space without any obstacles to land could be identified if necessary. Finally, the PID controller generates appropriate movement values for the UAV using the visual cues of the target landing area and the obstacles. To warrant the validity of the overall system without risking the safety of the involved people, initial tests are performed, and a software-based simulation is performed before executing the tests in real life. A full-blown hardware system with an autonomous landing system is then built and tested in real life. The designed system is tested in various scenarios to verify the effectiveness of the system.

Cultures in Mediterranean climate zones (MCZs) around the world have long been reliant on groundwater and springs as freshwater sources. While their ecology and cultural sustainability are recognized as critically important, inter-relationships between springs and culture in MCZs has received little attention. Here we augmented a global literature review with case studies in MCZ cultural landscapes to examine the intensity of cultural and socio-economic impacts on springs ecohydrogeology. MCZs are often oriented on the west and southern coasts in tectonically active landscapes, which control aquifer structure, the prevalence of westerly winds, and aridity, and generally expose associated habitats to harsh, afternoon sunlight. Cultural appreciation and appropriation of springs ranges widely, from their use as subsitence supplies to profound traditions, such as Greco-Roman nymphs, and Asian and Abrahamic spiritual cleansing and baptism. Commoditization of water resources for agriculture, industry (e.g., mining, water bottling, geothermal resorts), and urban needs is placing ever-increasing, non-sustainable demands on aquifers and springs. When economic values approach or exceed cultural values, these irreplaceable aquatic resources are degraded and lost. Sustainable stewardship of springs and the aquifers that support them are a little-recognized, but central conservation challenge for modern society facing global climate changes.

Background: Musculoskeletal pain is a non-negligible multifaceted condition affecting more than 30% of the global population. Superficial heat therapy (HT) through increasing tissues temperatures plays a role in increasing local metabolism and function and relieving pain. Knee pain and sports represent two relevant fields of superficial HT application. Methods: In the present paper a panel of experts performed a narrative review of the literature regarding the role of superficial HT in the management of knee pain and sport activities. Results: According to the reviewed literature, HT represents a therapeutic option in the management of musculoskeletal pain due to three main effects: pain relief, promotion of healing and return to normal function and activity. Moreover, HT plays a role in sport activities both before and after exercise. Before performing sports, HT helps in preparing muscles for performance. After performing sports, it is capable to promote recovery and healing pathways. Combining and sequencing superficial heat and cold therapy represent an interesting topic of study. Overall, application of heat wraps for superficial HT can be considered safe. Conclusions: Despite being an ancient method, HT shows to be a potentially beneficial and safe option in the management of several conditions including KP and sports. The key in the application of superficial HT is a multimodal and multidisciplinary approach.

This study develops a 7-layer Long Short-Term Memory (LSTM) model to enhance early diabetes detection in Oman, aligning with the theme of 'Artificial Intelligence in Healthcare'. The model focuses on addressing the increasing prevalence of Type 2 diabetes, projected to impact 23.8% of Oman's population by 2050. It employs LSTM neural networks to manage factors contributing to this rise, including obesity and genetic predispositions, and aims to bridge the gap in public health awareness and prevention. The model's performance is evaluated through various metrics. It achieves an accuracy of 99.40%, specificity and sensitivity of 100% for positive cases, a recall of 99.34% for negative cases, an F1 score of 96.24%, and an AUC score of 94.51%. These metrics indicate the model's capability in diabetes detection. The implementation of this LSTM model in Oman's healthcare system is proposed to enhance early detection and prevention of diabetes. This approach reflects an application of AI in addressing a significant health concern, with potential implications for similar healthcare challenges globally.st diagnostic capabilities, representing a significant leap forward in healthcare technology in Oman.

The present article investigates the threshold analysis of yielding in a variable thickness rotating disk based on the Tresca criterion. The analysis is conducted on a Functionally Graded Material (FGM) constructed from tailored materials, following the theory of small deformations and for the case of plane stress. The elasticity modulus, density, and yield stress are assumed to be power functions of the radial coordinate. Poisson’s ratio is considered constant due to small variations in different materials. Additionally, the governing equation for the rotating disk is solved analytically. Besides the material type, another factor affecting the distribution of effective stress magnitudes is the cross-sectional shape (profile) of the disk. The thickness of the cross-sectional disk varies radially as a power function. In the current analysis, different conditions for the onset of yielding and the evolution of plastic flow are considered. For evaluation and validation, the obtained results are compared and validated against similar results for specific cases (homogeneous disk and constant thickness graded disk) available in previous references. The results indicate that considering variable thickness for the disk section significantly affects the stresses and the location of the initiation of yielding

Background. The markerless motion capture system (MLS) is a new technology that uses deep learning to detect body segments from digital images. This study tested the agreement between the MLS and a force-plate based system (FPS, “gold standard”) to quantify stability control and motor performance (MP) during gait initiation (GI). Methods. Healthy adults (young and elderly) and patients with Parkinson’s disease (PD) performed GI series at spontaneous and maximal velocity on an FPS while being filmed by an MLS. Signals from both systems were used to compute the peak of forward center-of-mass velocity (indicator of MP) and the braking index (BI, indicator of stability control). Results. Descriptive statistics indicated that both systems detected between-groups differences and velocity effects similarly, while a Bland-Altman (BA) plot anal-ysis showed that BI and MP mean biases were virtually zero in all groups and conditions. Bayes factor 01 indicated strong (for BI) and moderate (for MP) evidence that both systems provided equivalent values. However, trial-by-trial analysis of BA plots revealed the possibility of differ-ences > 10% between the two systems. Conclusion. Although non-negligible differences do occur, MLS appears to be as efficient as FPS in detecting PD and velocity condition effects on BI and MP

The special affine Fourier transform (SAFT) is a useful and powerful analyzing tool in signal processing, optics and communications. In this paper, we mainly discuss the randomized nonuniform sampling and reconstruction for random signals bandlimited in the SAFT domain. First, we show that the nonuniform sampling is identical to the uniform sampling after a pre-filter in the sense of second order statistic characters. Then, we propose an approximate reconstruction based on sinc interpolation for the nonuniform sampling of random signals bandlimited in the SAFT domain. Finally, we give the mean square error estimate for the proposed approximate recovery approach.

Respiratory allergic diseases, affect over 500 million people globally and pose a substantial burden in terms of morbidity, mortality, and healthcare costs. Restrictive factors such as geographical disparities, infectious pandemics, limitations in resource, and shortage of allergy specialists in underserved areas, impede effective management. Moreover, the well-established suboptimal adherence in patients with respiratory allergies, contribute further to the accelerated loss of disease control. Telemedicine encompasses real-time visits, store-and-forward options triage, and computer-based technologies for establishing and efficient doctor-patient communication. Recent advances in digital technology, including designated applications, informative materials, digital examination devices, wearables, digital inhalers, and integrated platforms, facilitate personalized and evidence-based care delivery. The integration of telemonitoring in respiratory allergy care has shown beneficial effects in disease control, adherence, and quality of life. While the COVID-19 pandemic accelerated the adoption of telemedicine, certain concerns regarding technical requirements, platform quality, safety, reimbursement, and regulatory considerations remain unresolved. Challenges in telemonitoring implementation further include ensuring effective doctor-patient collaboration, addressing privacy concerns, and establishing cost-effective models. The integration of artificial intelligence (AI) in telemonitoring applications holds promise for data analysis, pattern recognition, and personalized treatment plans. Striking the balance between AI-enabled insights and human expertise is crucial for optimizing the benefits of telemonitoring. This overview reports the up- to- date telemedicine approaches in managing patients with respiratory allergies. While telemonitoring exhibits potential in enhancing patient care and healthcare delivery, critical considerations have to be addressed in order to ensure the successful integration of telemonitoring into the healthcare landscape.

Eggplant or brinjal is one of the most consumed and important nutrient-dense tropical solanaceous vegetable crops grown worldwide. Little leaf is a disease especially widespread in brinjal in India where it is associated with the presence of phytoplasmas. To clarify the epidemiology of this disease and verify its seed transmission potential, seedlings and their progeny derived from symptomatic mother plants field-collected in Dharwad district of Karnataka State, India, were sowed under insect proof conditions in greenhouse. The resulting first- and second-generation seedlings obtained were tested at different times after germination by DNA extraction and amplification of 16S rRNA gene of phytoplasmas. Tissues from field collected symptomatic brinjal plants were also tested following the same procedure. The amplicons obtained were subjected to restriction fragment length polymorphism (RFLP) analysis and sequencing for phytoplasma identification. The detected phytoplasmas belonged to 16SrI, 16SrII, 16SrIII, 16SrV, 16SrVI, and 16SrXII groups. Several fruits produced from the first-generation seedlings showed germination of the seeds inside the fruit and resulted to be phytoplasma positive. This demonstrates the seed transmission of phytoplasmas in eggplants for two subsequent generations. This finding highlights the risk of additional source of infection represented by asymptomatic and infected seedlings under field conditions and contribute to explain the epidemic spread of phytoplasmas in brinjal cultivations in India and in the other eggplant growing areas of the world.

Introduction: Congenital heart defects (CHD) are the most frequent group of major congenital anomalies, accounting for almost 1% of all births. They comprise a very heterogeneous group of birth defects in terms of their severity, clinical management, epidemiology and embryologic origins. Taking this heterogeneity into account is an important imperative to provide reliable prognostic information to patients and their caregivers, as well as to compare results between centers or to assess alternative diagnostic and treatment strategies. The Anatomic and Clinical Classification of CHD (ACC-CHD) aims to facilitate both the CHD coding process and data analysis in clinical and epidemiological studies. Objectives: 1) To describe the long-term childhood survival of newborns with CHD and 2) To develop and validate predictive models of infant mortality based on the ACC-CHD. Materials and Methods: This study is based on data from a population-based, prospective cohort study: Epidemiological Study of Children with Congenital Heart Defects (EPICARD). The final study population comprised 1881 newborns with CHD after excluding cases that were associated with chromosomal and other anomalies. Statistical analysis included non-parametric survival analysis and flexible parametric survival models. The predictive performance of models was assessed by Harrell’s C index and the Royston-Sauerbrei R2 with internal validation by bootstrap. Results: The overall 8-year survival rate for newborns with isolated CHD was 0.96 [0.93- 0.95]. There was a substantial difference between the survival rate of the categories of ACC-CHD. The highest and lowest 8-year survival rates were 0.995 [0.989-0.997] and 0.34 [0.21-0.50] for “interatrial communication abnormalities and ventricular septal defects” and "functionally univentricular heart", respectively. Model discrimination as measured by Harrell’s C was 87% and 89% for the model with ACC-CHD alone and the full model, which included other known predictors of infant mortality, respectively. The predictive performance as measured by R2 was 45% and 50%, for the ACC-CHD alone and the full model. These measures were essentially the same after internal validation by bootstrap. Conclusion: The ACC-CHD classification provided the basis of a highly discriminant survival model with good predictive ability for the 8-year survival of newborns with CHD. Prediction of individual outcomes remains an important clinical and statistical challenge.

Catheter-associated bloodstream infection (CVC-BSI) is a significant cause of morbidity and mortality among hemodialysis patients. In our center was a notable increase in CVC associated with patient age and morbidity. This 10-year retrospective study investigated catheter-associated bloodstream infections (CVC-BSI) in hemodialysis patients. We recorded a total of 67 bacteremia episodes in 52 patients, predominantly linked to Gram-positive microorganisms, particularly Staphylococcus aureus, the study found a mean age of 68 years, 74.6% males, and 88% with tun-neled jugular catheters. Notably, catheter removal occurred in 65.7% of cases, more frequently in Gram-positive instances. Two episodes of endocarditis and five ICU admissions were reported. The study identified a higher incidence in the summer and a significant decrease in bacteremia from 2017, coinciding with the introduction of Tauro-LockTM. Despite enhanced preventive measures during the COVID-19 pandemic, there was no significant impact on catheter infection rates. This research emphasizes the importance of early catheter removal, highlights seasonal variations in incidence, and suggests a potential positive influence of Tauro-LockTM on de-creasing CVC-BSI rates in hemodialysis units.

(1) Background: Most patients with atrial fibrillation, on warfarin therapy, are at higher risk of morbidity and mortality. However, data targeting patients with atrial fibrillation, who take warfarin therapy, are limited in Jordan. This study aimed to provide in-depth analysis of a cohort of patients with atrial fibrillation on warfarin regarding patients’ characteristics, atrial fibrillation related symptoms, interventions, comorbidities, and 12-months outcomes. (2) Methods: The study enrolled 645 patients with atrial fibrillation, on warfarin, from 28 health settings across Jordan. Standardized clinical data form was utilized to collect data upon enrollment, at one, six, and 12 months post initial assessment. Descriptive statistics were used for the description of variables. (3) Results: The most commonly reported symptoms were palpitation (41.4%) shortness of breath (39.1%) and fatigue (26.2%). The prevalent comorbidities associated with atrial fibrillation were congestive heart failure (22.5%), valvular heart diseases (16.6%), and cerebral vascular accident (16.3%). The embolic (32.4%) and thrombotic cerebral vascular accident (16.2%) were the most common type. Major bleeding associated with hospitalization was the most frequent type of bleeding (10 out of 24). (4) Conclusions: Jordanians, using anticoagulation, need to be constantly monitored in terms of their characteristics, symptoms, and any potential complications, to ensure its optimal therapeutic dose and prevent any potential health complications.

This study investigates the effect of dividend policy on firm performance and value in the Korean market, taking into account the unique context of Chaebol ownership structures. Analyzing 5,478 observations from the Korean Composite Stock Price Index, the research employs multiple regression models to explore the effects of various dividend policy measures under alignment and entrenchment theories. The key findings reveal significant impacts of cash dividend payment on firm value, while dividend yield and dividend policy exhibit varying associations. In the Chaebol and non-Chaebol context, mixed results suggest complex interactions between dividend policy and business outcomes. Policy recommendations emphasize transparent communication about dividend policy to mitigate information asymmetry and enhance corporate governance in the Korean market.

Artificial Intelligence (AI) made its first appearance in 1956, and since then it has progressively introduced itself in healthcare system and patients’ information and care. AI functions can be grouped under the following headings: Machine Learning (ML), Deep Learning (DL), Artificial Neural Network (ANN), Convolutional Neural Network (CNN), Computer Vision (CV). Chronic limb-threatening ischemia (CLTI) represents the last stage of peripheral artery disease (PAD), and has increased over recent years, together with the rise in prevalence of diabetes and population ageing. Nowadays AI grants the possibility of developing new diagnostic and treatment solutions in the vascular field, given the possibility of accessing clinical, biological, and imaging data. By assessing the vascular anatomy in every patient, as well as the burden of atherosclerosis, and classifying the level and degree of disease, sizing and planning the best endovascular treatment, defining the perioperative complications risk, integrating experiences and resources between different specialties, identifying latent PAD, thus offering evidence-based solutions and guiding surgeons in the choice of the best surgical technique, AI challenges the role of the physician’s experience in PAD treatment.

Recent studies suggest that the interaction of dietary constituents with taste and olfactory receptors and nociceptor expressed in the oral cavity, nasal cavity and gastrointestinal tract may regulate homeostasis through activation of the neuroendocrine system. Polyphenols, of which 8,000 have been identified to date, represent the greatest diversity of secondary metabolites in plants, most of which are bitter and some of them astringent. Epidemiological studies have shown that polyphenol intake contributes to maintaining and improving cardiovascular, cognitive and sensory health. However, because polyphenols have very low bioavailability, the mechanisms of their beneficial effects are unknown. In this review, we focus on the taste of polyphenols from the perspective of sensory nutrition, summarize the results of previous studies on their relationship with bioregulation, and discuss their future potential.

: A comprehensive analysis was performed, considering blockchain technology (BT) proprieties in digital health, addressing medico-legal, privacy, and regulatory considerations. Adherence to personal data protection and healthcare regulatory guidelines were analyzed and compared for GDPR (Europe), HIPAA (United States), CCPA (California), PIPEDA (Canada), Privacy Act of 1988 (Australia), APPI (Japan), and LGPD (Brazil). Issues such as Health Systems, Strengthening and aligning policy orientations and initiatives, and emphasizing the role of data analysis in shaping health policies were explored. The study addressed conflicts between the legal frameworks and blockchain, comparing and suggesting solutions like revision of laws and integration of com-pliance mechanisms. Additionally, it sought to enhance IT-health literacy by integrating healthcare and legal domains. Ongoing collaboration between legal, health, and IT experts is essential for designing systems that effectively balance privacy rights and data protection while maximizing the benefits of disruptive technologies like blockchain.

This paper explores the application of fisheries management theories to broader environmental issues, including climate change and biodiversity conservation. It underscores the inherent trade-off in fisheries between yield and resource conservation, identifying harvesting as a significant environmental burden. Early recognition of the sustainability concept aimed to address challenges like economic discounts and the tragedy of the commons, contributing to the issue of overfishing. These insights extend beyond fisries to other environmental concerns, particularly climate change. The development of adaptive management, initially tailored to address uncertainties and non-stationarity in fisheries, has found application in diverse environmental issues. Recognizing humans as integral parts of ecosystems highlights the impossibility of achieving zero environmental impact when utilizing natural resources. The paper advocates for passive restoration to prevent overfishing, leveraging nature's resilience. While goals like complete biodiversity restoration are inherent in fisheries, their relevance may not be immediately apparent to other environmentalists. Despite ongoing discussions on the sustainability of ecosystem services, legislation often tends to favor the long-term maximization of fisheries yield. The paper calls for mutual understanding of theories and experiences across various environmental fields, including fisheries, to enhance collaborative efforts in each field.

This review summarizes available data on invasive procedures applied with questionable indications in Russia in the recent past: mastectomy with the removal of muscles, gastrectomy for peptic ulcers, spleno-renal anastomosis for diabetes mellitus, thoracic surgery for bronchial asthma, overuse of surgery in tuberculosis, excessive and compulsory treatments of alcohol-dependent patients, etc. Among factors contributing to the use of invasive procedures with unproven efficiency have been the partial isolation from international scientific community, insufficient consideration of the principles of professional autonomy, informed consent and scientific polemics, training of medical personnel. It is known that invasive procedures can exert a placebo effect, which might have contributed to reported efficiency of some methods discussed here. However, by definition, placebo must be free of risks.

N6-methyladenosine (M6A) modification is the most abundant internal chemical modification on RNA molecules in eukaryotes and can affect mRNA metabolism and regulate RNA transcription, nuclear export, splicing, degradation, translation, ets, and has a significant impact on various aspects of physiology or pathobiology. Radiotherapy is the most common measure of tumor treatment, variety of cellular intrinsic mechanisms affect the responses of cells to ionizing radiation (IR) and effectiveness of cancer radiotherapy. In this review, we summarize and discuss the recent advances about the roles and mechanisms of RNA M6A methylation in cellular responses to radiation-induced DNA damage response, and outcomes of cancer radiotherapy. Insights into the RNA M6A methylation in radiation biology may facilitate the improvement of therapeutic strategies for cancer radiotherapy as well as radioprotection on normal tissues.

In recent years, the advances in sperm morphology and genetic analyses in Perumytilus purpuratus allowed to suggest two evolutionary scenarios for this mussel: 1) the scenario of cryptic species and 2) the scenario of incipient or in progress speciation. To a better understanding of the evolutionary history of P. purpuratus, we performed an extensive sampling effort along a latitudinal gradient of ca. 7,180 km of coastline, from Southern Pacific to Atlantic Oceans and, we have also gone deeper in sperm morphology in P. purpuratus, exploring its association with phylogeny and population genetics to contrast if variability in sperm traits between northern and southern regions are signals of cryptic or incipient species. Overall, our results showed three sperm morphotypes and genetic structure in males of P. purpuratus strongly correlated. Additionally, we found evidence of a genetic admixture between lineages suggesting an introgressive hybridization zone at 38°S. These findings suggest the hypothesis that P. purpuratus is under incomplete reproductive isolation, with the presence of mechanisms of postzygotic isolation between lineages and, therefore, under an incipient or in fraganti speciation process. Finally, we discovered a new long morphotype for this species restricted to southern localities. Overall, our results support the hypothesis of historical events and postglacial recolonization as causal phenomena for the observed divergences.

Data security in the Internet of things (IoT) is often implemented by means of encryption, which can be burdensome for some entities. We propose in this paper a solution based on routing, by which data are forwarded only to entities that are intended to receive them. An IoT network can be seen as a partial order of equivalence classes of entities, and each entity can be labeled according to the position of its equivalence class in the partial order. The partial order can be constructed according to requirements of secrecy (or confidentiality), integrity and conflicts. Routing tables among entities can be compiled by using the labels. The method is demonstrated in this paper for Software defined networking (SDN) routers and controllers. We propose a centralized IoT architecture with a cloud structure using SDN as networking infrastructure, where storage entities (i.e. cloud servers) are associated with application entities. A small ‘hospital’ example is shown for illustration. Procedures for network reconfigurations are discussed. We also demonstrate the method for the normal case where different partial orders coexist among a set of entities. The method proposed does not impose an overhead on the normal functioning of an SDN network, since it requires calculations only when the network must be reconfigured, because of administrative intervention or policies.