Background: The effect of velamentous cord insertion (VCI) on perinatal outcomes in twin pregnancies is unclear due to conflicting findings. This retrospective study aimed to examine VCI prevalence and related risk factors in twin pregnancies and its association with adverse perinatal outcomes. Methods: Women with twin pregnancies who delivered between January 2012 and December 2021 in a single tertiary hospital were included. The participants were divided into dichorionic (DC) and monochorionic diamniotic (MCDA) groups, and their maternal and fetal characteristics and VCI rates were compared. Logistic regression models were used to identify risk factors for VCI and VCI-related perinatal outcomes. Results: Among the 694 twin pregnancies included in this study, the VCI rate was significantly higher in MCDA than in DC twins. Body mass index and MCDA twins were significant risk factors for VCI, whereas assisted reproductive technology pregnancy was a significant protective factor against VCI. In DC twins, VCI did not affect perinatal outcomes. Conclusion: In MCDA twins, VCI was a significant risk factor for fetal growth restriction, twin-to-twin transfusion syndrome, and preterm birth at

Background/Objectives: Women with subclinical hypothyroidism (SCH) were reported to be at an increased perinatal risk. We aimed to investigate the relationship between SCH and perinatal outcomes in singleton pregnancies resulting from assisted reproduction technology (ART). Methods: We retrospectively examined the perinatal outcomes of ART singleton pregnancies in women who underwent thyroid function screening before conception and delivered at our hospital from January 2020 to July 2023. We defined SCH as thyroid-stimulating hormone (TSH) levels <2.5 mU/L and normal free T₄ levels. The patients were divided into three groups: normal thyroid function (group A), SCH without levothyroxine therapy (group B), and SCH with levothyroxine therapy (group C). The risks of preterm birth, preeclampsia, fetal growth restriction, manual placental removal, and blood loss at delivery were compared among the three groups. Results: Out of the 650 ART singleton deliveries, 581 were placed in group A, 34 in group B, and 35 in group C. The preterm birth rate at <34 weeks was significantly higher in group B and significantly lower in group C than in group A. The rate of preterm delivery at <34 weeks increased in correlation with TSH levels. Levothyroxine therapy was the significant preventive factor for preterm birth at <34 weeks. Conclusions: The preterm birth rate before 34 weeks was significantly higher in the SCH group. Levothyroxine therapy is a significant protective factor against preterm birth before 34 weeks. Universal screening for thyroid function and appropriate hormone therapy in pregnant women may help reduce perinatal risks, including preterm birth.

Background Community infections of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have increased rapidly since the emergence of the Omicron strain. During the eighth and ninth pandemic waves—when movement restrictions in the community were eased—the all-case registration system was changed, and the actual status of infection became uncertain. Methods We conducted regular rapid antigen tests (R-RAT) once or twice a week to examine the actual state of coronavirus disease (COVID-19) diagnosis among healthcare employees. Results Overall, 320 (1.42/day) and 299 (1.76/day) employees were infected in the eighth and ninth pandemic waves. During both periods, 59/263 doctors (22.4%), 335/806 nurses (41.6%), 92/194 administrative employees (47.4%), and 129/218 clinical laboratory technicians (59.2%) were infected. In the eighth wave, 56 of 195 employees were infected through close contact; in the ninth wave, 26 of 62 employees were infected. No significant difference was observed in the number of vaccinations between infected and non-infected employees. The positivity rate of R-RAT was 0.41% and 0.45% in the eighth and ninth waves. R-RAT detected infection in 212 and 229 employees during the eighth and ninth waves, respectively; the ratio of R-RAT-detected positive employees to those who reported infection was significantly higher during the ninth wave (odds ratio: 1.67, 95% confidence interval: 1.17–2.37, p

Macrophages as a source and target of GDF-15

Bartonella species, intracellular parasitic zoonotic pathogens, has drawn increasing attention for their diverse host range and associated human diseases. This study investigates Bartonella infection in small mammals in Yunnan Province, China, focusing on tissue tropism. 333 small mammals were sampled from 13 species, 3 orders, 4 families, and 4 genera in Heqing and Gongshan Counties. Conventional PCR and real-time quantitative PCR (qPCR) were utilized for detection and quantification, followed by bioinformatic analysis of obtained DNA sequences. Results show a 31.5% detection rate, varying across species. Notably, Apodemus chevrieri, Eothenomys eleusis, Niviventer fulvescens, Rattus tanezumi, Episoriculus leucops, Anourosorex squamipes, and Ochotona Thibetana exhibited infection rates of 44.4%, 27.7%, 100.0%, 6.3%, 60.0%, 23.5%, and 22.2%, respectively. Genetic analysis identified 30, 10, and 5 strains based on ssrA, rpoB, and gltA genes, with nucleotide identities ranging from 92.1% to 100.0%. Bartonella strains were assigned to B. grahamii, B. rochalimae, B. sendai, B. koshimizu, B. phoceensis, B. taylorii, and a new species identified in the Episoriculus leucops (GS136). Tissue distribution analysis revealed varied copy numbers across different tissues, with the highest load in spleen. These findings underscore Bartonella's diverse species and host range in Yunnan Province, highlighting its broad tissue tropism in small mammals.

Zanthoxylum armatum is an forest tree with apomixis characteristic, and RWP-RKs are plant-specific transcription factors known to regulate nitrogen response and embryonic development. However, the genome-wide analysis of RWP-RK family genes in Z.armatum is unclear. In this study, 36 ZaRWP-RK transcription factors were identified in the genome of Z.armatum, among which 15 genes were belonged to the RKD subfamily and 21 belonged to the NLP subfamily. Duplication events of ZaRWP-RK genes were mainly segmental duplication, and synteny analysis revealed close phylogenetic relationship between Z.armatum and Arabidopsis. The analysis of cis-elements indicated that ZaRWP-RK genes may be involved in the regulation of embryonic development of Z.armatum by responding to plant hormones such as abscisic acid, auxin, and gibberellin. Real-time PCR showed that the expression levels of most ZaRWP-RK genes were significantly increased from flowers to young fruits. Protein-protein interaction network analysis further revealed the potential roles of the ZaRWP-RK proteins in apomixis. Collectively, this study provide a theoretical basis for future investigations into the ZaRWP-RK genes and their regulatory mechanisms in the apomixis process of Z.armatum.

The unravelling of the human genome created new perceptions on the origin and evolution of diseases and for cancer in particular, it established the notion that neoplasia has been a companion of life since its ap-pearance on earth. It is not surprising that neoplasms, in various forms, develop in numerous species of animals and even in plants. Unmistakable accounts of cancer with clinical features as are understood today, begin in the 5th c. B.C. The principles and practice of the Hippocratic and Galenic tradition dominated cancer care virtually into the 20th century. Advanced sequencing technologies at the dawn of the 21st century, generate new ther-apeutic opportunities with immunotherapy, oncolytic virotherapy and gene transfer, the latter especially in cases of hereditary cancer.

Keywords: mHealth; peritoneal dialysis; functionality; usability

Glaucoma is one of the primary causes of blindness worldwide. Canal opening surgery, a type of minimally invasive glaucoma surgery (MIGS) applied in cases of mild to moderate glaucoma, has gained increasing popularity in recent years due to its efficacy in reducing intraocular pressure, its safety profile, the simplicity of its technique, and the reduced likelihood of compromised vision. Nevertheless, the existing body of histopathological studies remains insufficient for a comprehensive understanding of post-surgical wound healing. Consequently, debates persist among researchers regarding the mechanism through which Schlemm’s canal opening surgery reduces intraocular pressure, as well as the surgical techniques that may impact the outcomes and the factors influencing surgical success. As the history of MIGS is relatively short and lacks sufficient systemic reviews or meta-analysis evaluating the influence of individual factors, this review was conducted to illuminate disparities in the researchers’ opinions at the current stage of research.

For enhancing the maximized profit from bank as well as customer perspective, term deposit can accelerate finance fields. This paper focuses on likelihood of term deposit subscription taken by the customers. Bank campaign efforts and customer details are influential while considering possibilities of taking term deposit subscription. An automated system is provided in this paper that approaches towards prediction of term deposit investment possibilities in advance. Neural network(NN) along with stratified 10-fold cross-validation methodology is proposed as predictive model which is later compared with other benchmark classifiers such as k-Nearest Neighbor (k-NN), Decision tree classifier (DT), and Multi-layer perceptron classifier (MLP). Experimental study concluded that proposed model provides significant prediction results over other baseline models with an accuracy of 88.32% and Mean Squared Error (MSE) of 0.1168.

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

The many limitations of implementing anticancer strategies under the term “precision oncology” have been extensively discussed. While some authors propose promising future directions, others are less optimistic and use phrases such as illusion, hype and false hypotheses. The reality is revealed by practicing clinicians and cancer patients in various online publications, one of which has stated that “in the quest for the next cancer cure, few researchers bother to look back at the graveyard of failed medicines to figure out what went wrong.” The message is clear: novel therapeutic strategies with catchy names (e.g., synthetic “lethality”) have not fulfilled their promises despite decades of extensive research and clinical trials. The main purpose of this review is to discuss key challenges in solid tumor therapy that surprisingly continue to be overlooked by the nomenclature committee on cell death and numerous other authors. These challenges include: the impact of chemotherapy-induced genome chaos (e.g., multinucleation) on resistance and relapse, oncogenic function of caspase 3, cancer cell anastasis (recovery from late stages of apoptosis), and pitfalls of ubiquitously used preclinical chemosensitivity assays (e.g., cell “viability” and tumor growth delay studies in live animals) that score such pro-survival responses as “lethal” events. Studies outline herein underscore the need for new direction in the management of solid tumors.

Numerous approaches address over-fitting in neural networks: by imposing a penalty on the parameters of the network (L1, L2, etc); by changing the network stochastically (drop-out, Gaussian noise, etc.); or by transforming the input data (batch normalization, etc.). In contrast, we aim to ensure that a minimum amount of supporting evidence is present when fitting the model parameters to the training data. This, at the single neuron level, is equivalent to ensuring that both sides of the separating hyperplane (for a standard artificial neuron) have a minimum number of data points — noting that these points need not belong to the same class for the inner layers. We firstly benchmark the results of this approach on the standard Fashion-MINST dataset, comparing it to various regularization techniques. Interestingly, we note that by nudging each neuron to divide, at least in part, its input data, the resulting networks make use of each neuron, avoiding a hyperplane completely on one side of its input data (which is equivalent to a constant into the next layers). To illustrate this point, we study the prevalence of saturated nodes throughout training, showing that neurons are activated more frequently and earlier in training when using this regularization approach. A direct consequence of the improved neuron activation is that deep networks are now easier to train. This is crucially important when the network topology is not known a priori and fitting often remains stuck in a suboptimal local minima. We demonstrate this property by training a network of increasing depth (and constant width): most regularization approaches will result in increasingly frequent training failures (over different random seeds) whilst the proposed evidence-based regularization significantly outperforms in its ability to train deep networks.

Purpose. This paper aims to present a unique perspective that emphasizes the intricate interplay between energy, dietary proteins, and amino acid composition, underscoring their mutual dependence for health-related considerations. Energy and protein synthesis are fundamental to biological processes, crucial for the sustenance of life and growth of organisms. Methods and Results. We explore the intricate relationship between energy metabolism, protein synthesis, regulatory mechanisms, protein sources, amino acid availability, and autophagy, in order to elucidate how these elements collectively maintain cellular homeostasis. We underscore the vital role this dynamic interplay has in preserving cell life. Conclusion. A deeper understanding of the link between energy and protein synthesis is essential to comprehend fundamental cellular processes. This insight could have wide-ranging impact in several medical fields, such as nutrition, metabolism, and disease management.

Exosomes are produced by all cell types, their biogenesis is of endosomal origin, originating as a result of cell membrane invagination. Furthermore, physiochemical characteristics are important prerequisites for their commercial application. The representative size range of exosomes is 50-200 nm. Whereas, comparative to animal cell, exosomes from plant cell sources have a relatively larger size range, moreover, exhibit broader therapeutic potential. In this review study, we have briefly discussed the research potential of plant-derived exosomes. Including their earlier studies on biogenesis, characterization, isolation methods, and possible therapeutic applications. Additionally, we have quoted targeted drug delivery for targeted therapies and have provided insights of methods for customizing exosomes produced from plants with various drugs. Most-importantly, here we have embodied exosomes from plant sources are natural nano-inducers possessing the ability for inter-kingdom communication, resulting in cross-kingdom regulations.

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.

Background: Post-acute sequelae of SARS-CoV-2 infection (PASC) is a complicated disease that affects millions of people all over the world. Previous studies have shown that PASC impacts 10% of SARS-CoV-2 infected patients of which 50-70% are hospitalized. It has also been shown that 10-12% of those vaccinated against COVID-19 were affected with PASC and its complications. The severity and the later development of PASC symptoms is positively associated with the early intensity of the infection. Results: The generated health complications caused by PASC involve a vast variety of organ systems. Patients affected by PASC have been diagnosed with neuropsychiatric and neurological symptoms. Cardiovascular system also has been involved and several diseases such as myocarditis, pericarditis, and coronary artery diseases were reported. Chronic hematological problems such as thrombotic endothelialitis and hypercoagulability were described as a condition that could increase the risk of clotting disorders and coagulopathy in PASC patients. Chest pain, breathlessness, and cough in PASC patients were associated with respiratory system in long COVID-19 causing respiratory distress syndrome. The observed immune complications were notable, involving several diseases. Renal system also was impacted and result in raising the risk of diseases such as thrombotic issues, fibrosis, and sepsis. Endocrine gland malfunction can lead to diabetes, thyroiditis, and male infertility. Symptoms such as diarrhea, nausea, loss of appetite and taste were also among reported observations due to several gastrointestinal disorders. Skin abnormalities might be an indication of infection and long-term implications such as persistent cutaneous complaints were linked to PASC. Conclusions: Long COVID is a multidimensional syndrome with considerable public health implications, affecting several physiological systems and demanding thorough medical therapy as well as more study to address its underlying causes and long-term effects.

The Atmospheric Dynamics Mission ADM-Aeolus was successfully launched in August 2018 by the European Space Agency (ESA). The Aeolus mission carried a single instrument, the first-ever Doppler Wind Lidar (DWL) in space, called Atmospheric LAser Doppler INstrument (ALADIN). Aeolus circled the Earth in a polar sun-synchronous orbit at about 320 km altitude with a repeat cycle of 7 days, providing vertical profiles of horizontal line-of-sight (HLOS) winds on a global scale. Exceeding scientific expectations, Aeolus, initially designed for a 3-year lifetime, provided global coverage of wind profiles for almost five years. In this long-term validation study, we assessed the accuracy of the Level 2B (L2B) Rayleigh-clear and Mie-cloudy wind products by collecting radiosonde data from three stations in the Brazilian Amazon: Cruzeiro do Sul (7.62° S, 72.67° W), Porto Velho (8.76° S, 63.91° W), and Rio Branco (10.00° S, 67.80° W). Statistical validation was conducted by comparing Aeolus L2B wind products and radiosonde data, launched daily at 12:00 UTC from October 2018 to March 2023. Considering all data collected during the mission period, Pearson’s coefficient (R) of 0.73 was observed in Rayleigh-clear and 0.85 in Mie-cloudy, revealing a strong correlation between Aeolus and radiosonde winds. No significant biases were detected, with values of -0.14 m/s for Rayleigh-clear and -0.40 m/s for Mie-cloud, fulfilling the mission requirement of having absolute biases below 0.7 m/s. However, when analyzed annually, in 2022, the bias for Rayleigh-clear was -0.95 m/s, exceeding the mission requirements.

Globally, over the past several months millions of persons contracted the coronavirus disease 2019 (COVID-19) resulting in significant mortality. Health care systems are negatively impacted including the care of individuals with cancers and other chronic diseases such as chronic active hepatitis, cirrhosis and hepatocellular carcinoma. There are various probable pathogenic mechanisms that have been presented to account for liver injury in COVID-19 patients such as hepatotoxicity cause by therapeutic drugs, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection of the bile duct cells and hepatocytes, hypoxia and systemic inflammatory response. Liver biochemistry tests such as AST, ALT, GGT and ALP are deranged in COVID-19 patients with liver injury. Hepatocellular damage results in the elevation of serum AST and ALT levels in early onset disease while a cholestatic pattern that develops as the disease progress causes higher levels of ALP, GGT, direct and total bilirubin. These liver biochemistry tests are prognostic markers of disease severity and should be carefully monitored in COVID-19 patients. We conducted a systematic review of abnormal liver biochemistry tests in COVID-19 and the possible pathogenesis involved. Significant findings regarding the severity, hepatocellular pattern, incidence and related clinical outcomes in COVID-19 patients are highlighted.

The high penetration of distributed energy resources poses significant challenges to the dispatch and operation of power systems. Improving the accuracy of short-term load forecasting (STLF) can optimize grid management, leading to increased economic and social benefits. Currently, some simple AI and hybrid models has issues to deal with and struggle with multivariate dependencies, long-term dependencies, and non-linear relationships. This paper proposes a novel hybrid model for short-term load forecasting (STLF) that integrates multiple AI models with Lasso regression using the stacking technique. The base learners include ANN, XgBoost, LSTM, Stacked LSTM, and Bi-LSTM, while Lasso regression serves as the meta-learner. By considering factors such as temperature, rainfall, and daily electricity prices, the model aims to more accurately reflect real-world conditions and enhance predictive accuracy. Empirical analyses on real-world datasets from Australia and Spain show significant improvements in forecasting accuracy, with a substantial reduction in Mean Absolute Percentage Error (MAPE) compared to existing hybrid models and individual AI models. This research highlights the efficiency of the stacking technique in improving STLF accuracy, suggesting potential operational efficiency benefits for the power industry.

Atopic dermatitis (AD), a T2 inflammatory skin condition, is widely recognized as one of the most prevalent chronic and recurrent skin disorders. One of the most effective therapy for treating moderate-to-severe AD is Dupilumab, a monoclonal antibody that blocks both IL-4 and IL-13 signaling. At the same time, no comprehensive analysis of cytokines profile was made in AD patients undergoing Dupilumab therapy. The primary objective of our research was to examine the levels of main cytokines to better understanding systemic immune response in AD and to identify potential biomarkers of the effectiveness of Dupilumab treatment. AD patients demonstrated significant clinical improvements one year after initializing of Dupilumab therapy. We identified 16 cytokines that showed major difference between Dupilumab-treated patients and patients without Dupilumab therapy. Six cytokines showed correlation with AD severity and the efficacy of Dupilumab therapy. Jointly revealed cytokines could potentially predict the effectiveness of Dupilumab treatment and help to choose the precision target therapy in AD patients as well.

The properties of the annual, semiannual and triennial oscillations (AO, SAO and TO) in the middle atmosphere have been investigated using the TIMED/SABER temperature data. The Lomb-Scargle and wavelet spectra were used to determine the dominant oscillations in the background temperature field. The AO is prominent at the mid-latitudes. The AO amplitudes present an asymmetry between the two Hemispheres, being larger in the mesosphere than in the stratosphere. The SAO dominates the tropical regions, with three amplitude maxima at altitudes of 45, 75, and 85 km. The SAOs in the upper mesosphere (75 km) are out of phase with those in the mesopause (85 km) in the tropical regions, which can generate an enhancement of 11 K at each equinox, contributing to the lower mesospheric inversion layer. The TO is significant in the tropical region, with amplitude being maximum at 35, 45 and 85 km. Result shows that there may be potential interaction by the TO with SAO at 85km at the equator. The relation between ENSO and TO has also been discussed. The ENSO signal may modulate the amplitude of the TO, mainly in the lower stratosphere. The real origin of the TO may lie in the wave-mean-flow interaction.

Background: The practice of self-medication is common worldwide and is an important component of medical self-care. However, the practice can be dangerous and is linked to various risks for the patients and the entire community. This study aimed to estimate the prevalence and factors associated with self-medication among Bangladeshi adults. Methods: A cross-sectional survey was conducted between April and June 2021 among Bangladeshi adults (aged &gt;19 years) using convenient sampling. A total of 1320 data were collected through face-to-face interviews using a standardized questionnaire. Multivariable logistic regression analysis was used to identify factors associated with self-medication practice (SMP). Results: Overall, 41% of adults in our survey reported SMP. The most common illnesses that prompted SMP were common cold/flu (66.4%), gastric problems (65%), and headache (64.4%). The most frequent reasons for SMP were to get better services (30.59%), perceive SMP without side effects (23.28%), and save time with effectiveness (14.56%). Potential risk factors included 10 years (AOR = 1.91; 95% CI: 1.04 - 3.50) and &gt;12 years of schooling (AOR = 5.03; 95% CI: 2.27 - 11.15), being a businessman (AOR = 4.64; 95% CI: 1.74 - 12.37), having ≤6 family members (AOR = 2.13; 95% CI: 1.40 - 3.24), being a member of a social group (AOR = 1.53; 95% CI: 1.10 - 2.12), a health status check after every six months (AOR = 1.52; 95% CI: 1.08 - 2.13), and current ill-health (AOR = 1.41; 95% CI: 1.06 - 1.87). Protective factors identified included ≤30 years of age (AOR = 0.40; 95% CI: 0.17 - 0.93), and practice of modern (AOR = 0.39; 95% CI: 0.22- 0.69) and herbal (AOR = 0.45; 95% CI: 0.21- 0.97) healing types. Conclusion: More than one-third of the study participants reported practicing self-medication. Increasing the community’s awareness of the extreme consequences of SMP and not just the average experience might sway individuals away from SMP, and implementing strict jurisdiction could be a way to minimize the SMP.

We propose an innovative approach called SMPTC3, designed specifically to enhance security and privacy in cross-chain transaction verification. This approach addresses multi-chain, multi-participant information exchange and large-scale cross-chain transfers, resisting various types of malicious attacks. We leverage the verifiability of cross-chain transactions based on smart contracts and innovatively transform transaction information into confidential sets, organizing them into quadratic secret polynomials. By utilizing secret sharing and random distribution techniques, we construct a secure multiparty computation method, tailored for cross-chain transactions. To enhance the efficiency of cross-chain transactions, we introduce cross-chain batch processing technology, grouping inter-chain transactions into cross-chain transaction sets. Unlike traditional distributed notary technologies, SMPTC3 designates honest participants as a cross-chain notary group, reducing the time required for redundant signature confirmations and significantly lowering the possibility of malicious notaries. Theoretical analysis and empirical experiments demonstrate that SMPTC3 is highly efficient in addressing cross-chain transaction security issues.

Pd EnCat™ 30 is a palladium catalyst broadly used in several hydrogenation and cross-coupling reactions. It is known for its numerous beneficial features, which include high-yielding performance, easy recovery, and reusability. However, the available data regarding its recyclability in Suzuki coupling reactions are limited to a few reaction cycles and, therefore, fail to explore its full potential. Our work focuses on investigating the extent of Pd EnCat™ 30 reusability in Suzuki cross-coupling reactions by measuring its performance according to isolated yields of product. Our findings demonstrate that Pd EnCat™ 30 can be reused over a minimum of 30 reaction cycles, which is advantageous in terms of cost reduction and more sustainable chemical production.

：Non-Euclidean data, such as social networks, and citation relationships between documents, has node information and structural information. Graph Convolutional Network(GCN) can automatically learn node features and association information between nodes. The core ideology of the graph convolutional network is to aggregate node information by using edge information, thereby generating a new node feature. In the process of updating node features, there are two core influencing factors. One is the number of neighboring nodes of the central node, the other is the contribution of the neighboring nodes to the central node. Due to the previous GCN methods not simultaneously considering the numbers and different contributions of neighboring nodes to the central node, we design the Adaptive Attention Mechanism(AAM). To further enhance the representational capability of the model, we utilize Multi-Head Graph Convolution(MHGC). Finally, we adopt cross-entropy(CE) loss function to describe the difference between the predicted results of node categories and the ground truth (GT). Combined with backpropagation, this ultimately achieves accurate node classification. Based on AAM, MHGC and CE, we contrive the novel Graph Adaptive Attention Network (GAAN). Experiments show that the classification accuracy has achieved outstanding performances on Cora, Citeseer and Pubmed datasets.

Multimodal emotion classification (MEC) involves analyzing and identifying human emotions by integrating data from multiple sources, such as audio, video, and text. This approach leverages the complementary strengths of each modality to enhance the accuracy and robustness of emotion recognition systems. However, one significant challenge is effectively integrating these diverse data sources, each with unique characteristics and levels of noise. Additionally, the scarcity of large, annotated multimodal datasets in Bangla limits the training and evaluation of models. In this work, we unveiled a pioneering multimodal Bangla dataset, MAViT-Bangla (Multimodal Audio Video Text Bangla dataset). This dataset, comprising 1002 samples across audio, video, and text modalities, is a unique resource for emotion recognition studies in the Bangla language. It features emotional categories such as anger, fear, joy, and sadness, providing a comprehensive platform for research. Additionally, we developed a framework for emotion recognition that employs a cross-modal attention mechanism among unimodal features. This mechanism fosters the interaction and fusion of features from different modalities, enhancing the model’s ability to capture nuanced emotional cues. The effectiveness of this approach was demonstrated by achieving an F1-score of 0.64, a significant improvement over unimodal methods.

Current VAT rules for cross-border e-commerce companies in the EU are not sustainable, because they are extremely complex and often opaque, due to the lack of tax harmonization. The aim of the research is to explore, using a qualitative method, what kind of harmonization would make the current legislation more uniform, simpler, more transparent, and easier to understand, without conflicting with the rules of any Member State. To this end, the aspects of the new platform regulation introduced on 1 July 2021 and its potential for expansion are assessed through information from possible sales models. The research suggests that the rules on platforms do not cover all possible sales models, which in our view imposes an unnecessary extra administrative burden on some businesses and makes their tax activities less transparent. In the light of the results of the research, we propose that the current EU platform regulation should be extended to cover B2B, B2C transactions and services. As a result of this suggested harmonization, a simpler, more transparent, uniform and sustainable tax system would contribute to the whitening of the economy, generating additional tax revenue for Member States.

Safe water is a global public health concern amid increasing scarcity and pollution. Bottled water production and consumption contribute to these problems. This study examines tap water consumption in Italy, assessing associated sociodemographic factors and related health outcomes such as obesity and self-perceived health status. Data from the Italian National Statistics Institute's "Aspects of daily life" survey (N=45,597) were analyzed. Covariates included education, age, gender, economic status, region, concerns about waste and climate change, consumption of carbonated drinks excluding water, alcohol consumption, consumption of vegetables, consumption of snacks, body mass index, and self-perceived health status. Bivariate analyses and mixed-effect logistic regression models explored the associations. People who drink tap water were 19,674 with a higher prevalence in people aged 45 to 59 old, people with a graduate/post-graduate degree diploma, with optimal economic resources, and concerned about waste production and climate change, coming from the North-East regions of Italy. Underweight people showed a higher prevalence of TW assumption as well as those who drink less than occasionally carbonated drinks, drink alcohol, consume vegetables more than once a day, and snacks less than once a week with a satisfying level perceived health status. Regressions showed that all age classes are less likely to drink tap water than people younger than 20 years old. The category with “inadequate” economic resources is more likely to consume tap water. Low educational classes show a low likelihood of consuming tap water as well as Islands. A concern about waste production and climate change is associated with an increased likelihood of assuming tap water. Tap water consumption was negatively associate with obesity but not with a satisfactory Self-perceived health status. Insights from this study can inform public health strategies.

Postoperative headaches (POH) following retrosigmoid microsurgery for ves-tibular schwannoma (VS) can significantly diminish patients' perceived health benefits (PHB). A survey of 101 VS patients, utilizing the Rostock Headache Compendium, Glasgow Benefit Inventory, Ten-Item Personality Inventory (TI-PI-G), and German pain processing questionnaire (FESV), revealed that almost half experienced POH, leading to a markedly reduced overall PHB compared to those without POH. This decrease in PHB was linked to higher levels of pain-related helplessness, depression, anxiety, and anger. Positive associations were found between PHB and action-planning competence, cognitive restruc-turing, and experience of competence. Personality traits, particularly low emo-tional stability and openness, were associated with pain-related psychological impairment. Interestingly, hearing loss and facial paresis did not impact PHB. The study underscores the influence of pain-related mental interference and coping strategies on PHB in long-term POH patients, suggesting a role for personality traits in their pain management. The findings advocate for short-term psychological interventions, emphasizing adaptive coping mecha-nisms like cognitive restructuring, to enhance PHB in VS patients post-microsurgery.

A simple design of an ultrathin six-band polarization-insensitive terahertz perfect metamaterial absorber (PMMA) composed of a metal cross-cave-patch resonator (CCPR) placed over a ground plane was proposed and investigated numerically. The numerical simulation results demonstrate that the average absorption peaks are up to 95% at six resonance frequencies with high quality-factors (>65). In addition, the absorption properties can be kept stability for both normal incident transverse magnetic (TM) and transverse electric (TE) waves. The physical mechanism behind the observed high level absorption is illustrated by the electric and power loss density distributions. The different absorption mainly originates from the higher order multipolar and multipolar plasmon resonance of the structure, which are sharp different to the most previous studies of the PMMAs. Furthermore, the resonance absorption of the PMMA can be tunable by varying the geometric parameters of the unit cell.

A simple design of an ultrathin six-band polarization-insensitive terahertz perfect metamaterial absorber (PMMA) composed of a metal cross-cave-patch resonator (CCPR) placed over a ground plane was proposed and investigated numerically. The numerical simulation results demonstrate that the average absorption peaks are up to 95% at six resonance frequencies with high quality-factors (>65). In addition, the absorption properties can be kept stability for both normal incident transverse magnetic (TM) and transverse electric (TE) waves. The physical mechanism behind the observed high level absorption is illustrated by the electric and power loss density distributions. The different absorption mainly originates from the higher order multipolar and multipolar plasmon resonance of the structure, which are sharp different to the most previous studies of the PMMAs. Furthermore, the resonance absorption of the PMMA can be tunable by varying the geometric parameters of the unit cell.

Background: Studies have tried to identify predictors of functional markers of keratoconus progression, whereas structural outcomes of collagen cross-linking have not been properly investigated. Objective: find and set up a combination of diagnostic modalities and measurements to reliably reflect CXL efficiency. Material and methods: We retrospectively reviewed the medical histories of 107 KC patients (131 eyes) who underwent CXL in a medical center from January 2018 to December 2022. The dataset included preoperative examinations and follow-up results, which provided a total of 796 observations. The cases of other corneal diseases, repeated CXL, pregnancy, and observations without follow-up examinations were excluded. Results: The study findings revealed a significant drop in the central and corneal thickness during 14.01±9.98 months of observations. Linear and polynomial equations suggested different trends in pachymetry change after CXL. The linear model showed corneal thinning, and according to the polynomials, pachymetry findings return to baseline values two years after CXL. Conclusion: The most reliable prognosis of postoperative corneal thickness is achieved with the models trained on keratometry readings and topography indices. BAD indices are also reliable predictors of the corneal thickness after CXL. A combination of the aforementioned structural parameters and their derivatives can reliably predict CXL efficiency.

Myocardial Infarction with Non-Obstructive Coronary Arteries (MINOCA) is a clinical entity characterized by the absence of significant coronary artery obstruction in epicardial arteries (&lt; 50%) on coronary angiography in the setting of acute myocardial infarction (AMI). This article aims to provide a narrative review of the pathophysiological mechanisms, diagnostic challenges, and prognosis associated with MINOCA focusing only on cases associated with myocardial ischemia but of non-atherosclerotic origin. Etiological factors, including thromboembolism, coronary artery spasm, spontaneous coronary artery dissection, coronary microvascular disease, and supply-demand mismatch are addressed. Imaging modalities such as echocardiography, advances in coronary angiography like intravascular ultrasound (IVUS) and optical coherence tomography (OCT), cardiac magnetic resonance (CMR), and coronary computed tomography angiography (CCTA) are also analyzed. MINOCA patients have a better short-term prognosis compared to those with obstructive coronary artery disease but face significant long-term risks, underscoring the need for precise diagnosis and management strategies. Elevated inflammatory markers and specific genetic predispositions are also associated with adverse outcomes in MINOCA. This review focused on MINOCA from the pathophysiological perspective on ischemic, non-atherosclerotic causes, the diverse underlying mechanisms, the challenges in achieving accurate diagnosis, the importance of a tailored therapeutic approach and the necessity for further investigation of clinical outcomes.

Background: Ultraviolet (UV) radiation from the sunlight can harm skin cells, causing short-term effects, such as sunburns and long-term effects, such as pigmentation changes, changes in the skin's immune responses, and increased risk of skin cancer. These conditions can be largely prevented with proper sun protection measures and behavioural changes. This study aims to assess the knowledge on sun protection behaviour and baseline knowledge of medical students from the “Carol Davila” University of Medicine and Pharmacy, Bucharest, Romania. Methods: Data in this cross-sectional study were collected through a Google Forms questionnaire, which was distributed from November 2023 to December 2023 via digital communication channels to students across all academic years. STROBE guidelines were consulted for data synthesis; Results: A total of 668 stu-dents responded. The student cohort demonstrated a commendable level of awareness of the risks associated with sun exposure and the advantages of employing sun protection factor (SPF); how-ever, the incidence of sunburns remained notably elevated (72.3%). Further analysis revealed cor-relations among gender, academic year, presence of photosensitizing conditions, and adherence to SPF application. Additionally, there is a need to improve understanding of the appropriate appli-cation techniques for SPF, as only 11.5% of the students exhibited proficiency in this regard; Con-clusions: As future healthcare providers, medical students hold significance in promoting healthy behaviours in the broader community. This study indicates that while their knowledge about sun protection is satisfactory, there is scope for enhancement.

(1) Background: The RDW-CV has predictive value in many pregnancy-related conditions. Re-search question: Can the RDW-CV be utilized predictively in pregnant patients with thrombo-philia? Aim of the study: To carry out a detailed analysis of the RDW-CV in pregnant patients with treated thrombophilia as compared with pregnant patients without thrombophilia who de-livered via cesarean section at term. (2) Methods: We studied 160 pregnant patients, including 80 pregnant patients with treated thrombophilia in the study group, and another 80 patients of a similar age and parity. The patients were referred to our hospital for delivery at term by means of a cesarean section between 1/10/2017 and 1/12/2021. Every patient received a sonogram during the first 1–2 days after the cesarean section, and their uterine evaluation was interpreted using the PUUS (Postpartum Uterine Ultrasonographic Scale). (3) Results: Our PUUS≥1 pregnant and postpartum patients with treated thrombophilia were the only group with an RDW-CV value over 14. No deep vein thrombosis was observed during hospitalization, showing that the antico-agulant treatment was necessary and effective. An RDW-CV of 14.5 was the highest value in the Rh-negative group of pregnant patients with treated thrombophilia. An RDW-CV of 14.48 was the highest level in the Rh-negative postpartum patients with treated thrombophilia. (4) Conclu-sion: An RDW-CV of ≥14 can predict uterine hematometra (PUUS≥1). The RDW-CV values were higher in Rh-negative patients.

Objectives: Evaluate the performance of diagnostic measures (sensitivity and specificity) of the intrinsic capacity (IC) construct recommended by the WHO ICOPE guidelines by domain and by age group. Study design: This cross-sectional study included 164 community-dwelling elderly (95 women and 69 men). The participants completed the assessment of the 5 domains of IC (cognition, psychological, vitality, locomotion and sensory). In addition, they were assessed for activities of daily living (ADL), instrumental activities of daily living (IADL), frailty and urinary incontinence. Main outcomes measures: Descriptive statistics were used to summarize the intrinsic capacity and identify which domains were compromised. Comparisons between three or more samples were made by 1-way ANOVA with Bonferroni post-test and those with two samples by the t-test or Mann-Whitney test for quantitative variables. Chi-square test was used for qualitative variables. The sensitivity and specificity of each domain and each domain by age group were evaluated using the ROC curve. Results: Participants with a decline in IC were older, worse ADL, IADL and mental function, low gait speed, and higher depression scores. In addition, people with a decline in IC had frailty, urinary incontinence. Other issues related to the decline in CI were self-reported non-practice of physical activities and level of schooling.The evaluation of each domain did not prove to be a good screening tool (sensitivity or specificity &lt; 80%, but both values &gt; 50%). When the analyses were separated by domain and age group, good performance was found in the psychological (69-69 years and ≥80 years), vitality (≥80 years) and sensory (≥80 years) domains. Conclusions: The ICOPE screening tool performed well in terms of diagnostic measures when applied by domain and age group.

Background: The validation of laser usage during laparoscopic procedures, notably by Camran Nezhat in the late 1980s, has been significant. Lasers offer precision and depth control in tissue vaporization without bleeding. Surgical intervention remains central in managing endometrio-sis-associated pain and infertility, especially for patients unresponsive to hormonal therapy. Methods: This retrospective cohort study included 200 patients with SPE who underwent laparo-scopic laser vaporization. Surgery was performed using a CO2 laser, and histological confirma-tion of endometriosis was obtained for all cases. Pain scores and SF-36 questionnaire domains were assessed preoperatively and postoperatively. Fertility outcomes were evaluated among pa-tients desiring pregnancy. Results: Significant improvements in pain score and SF-36 questionnaire domains were ob-served postoperatively (p-value

Chronic stress, culminating in burnout, evolves gradually and is notoriously difficult to detect due to vague symptoms and individuals' hesitance to acknowledge their struggles. To expedite the identification and recognition of this condition, enabling timely psychological intervention, the integration of Artificial Intelligence (AI) is increasingly considered. This research does not assert the feasibility of an AI system managing all aspects of chronic stress's impact. However, it highlights the capability of current technology to detect stress indicators based on quantifiable data like Heart Rate (HR) and organizational climate dimensions. Although other physiological markers such as oximetry, skin galvanic response, and EKG have been explored, they have not shown reliable differentiation between stress and joy. Focused on the unique context of school principals in the Bedouin regions of Israel, this study investigates the interplay between HR, organizational climate, and stress levels. It introduces a novel application of a fuzzy logic tool that combines HR and organizational climate metrics to aid in stress diagnosis. This tool incorporates the psychologist's expertise to provide real-time data crucial for developing effective coping strategies. While the AI-supported fuzzy system does not replace professional psychological intervention, it significantly enhances the speed of condition identification and intervention planning, thus shortening the response time to stress-related issues in educational leadership within culturally specific settings. The application of such AI-driven tools is pivotal for sustaining the well-being and effectiveness of educational leaders, thereby supporting the broader goal of educational sustainability.

Sentiment analysis plays a crucial role in understanding customer feedback, guiding product development, and informing business decisions. This paper introduces term sentiment entropy (TSE), a novel weighting method that leverages the distribution of sentiment labels associated with words to enhance text classification accuracy. TSE complements traditional TF-IDF techniques by capturing the nuances of sentiment variation across different contexts. Experiments across diverse public datasets demonstrate TSE's potential to improve sentiment analysis performance, especially in capturing subtle sentiment shifts and adapting to specific domains. While computational cost and label quality pose challenges, TSE offers a promising avenue for refining sentiment analysis and opening new research frontiers.

To enhance the safety of power grid operations, this study proposes a high-precision short-term photovoltaic power prediction method that integrates information from surrounding pho-tovoltaic stations and the Conv-LSTM-ATT model. In the deep learning prediction model, not only is numerical weather prediction (NWP) data from the target photovoltaic station used as input features, but also highly correlated features from nearby photovoltaic stations are incor-porated. The research begins by analyzing the correlation between irradiance and power se-quences, along with distance factors, to calculate a composite similarity index between the target and other regional photovoltaic stations. Stations with high similarity indices are then selected as data sources. Subsequently, Bayesian optimization techniques are employed to find the optimal data fusion ratios. Ultimately, using the selected data, power prediction mod-eling is conducted via the Conv-LSTM-ATT deep neural network. Experimental results con-firm the superiority of the proposed model, which demonstrates higher predictive accuracy compared to three other classical models. The data fusion strategy determined by Bayesian optimization significantly enhances prediction accuracy, reducing the root mean square error (RMSE) of the test set by 20.04%, 28.24%, and 30.94% for three weather types, respectively.

Cross-linked polyethylene (XLPE) is a highly all-important material renowned for its exceptional physical and chemical properties, and it is extensively utilized in various industries such as con-struction, piping, cable insulation and medical equipment. The cross-linking process of polyethylene involves chemical or physical bonding of polymer chains to enhance its resistance to heat, chemicals and mechanical stress. This study offers a comprehensive overview of recent research and potential advancements in this field, with a particular focus on the development of efficient techniques and environmentally sustainable cross-linking systems. It evaluates the opportunities and challenges faced by cross-linked polyethylene materials across diverse applications, providing valuable insights for future research in this area.

In many European countries over the last decades, arable fields dominate agriculture landscapes, leading to a very intensive land-use practices. This reason seems to be the main cause of popula-tions declines for numerous farmland species, including the European hare (Lepus europaeus Pallas, 1778). The Research institute for Animal Production (National Agricultural and Food Centre, Luzianky, Slovakia) has been engaged in a long monitoring project (project currently run-ning), collecting certain indicators of hare population dynamics during hunting season since 1987 to 2023 in the Slovak Danubian Lowland. In the same macro-area (Čiližská Radvaň and Lehnice) a study was conducted on the influence of permanent semi-natural vegetation in relation to re-cruitment, population density and production. The whole monitored period was aggregated into 5-years intervals (for a total of 7 time-intervals), with the aim of analyzing the brown hare popu-lation dynamics. Spring hare density in the Danubian Lowland is currently 20.8 hares/km2, with harvests of 4.6 hares/km2. During all the monitoring period, bag’s animals have been examined following the regular hunting operations for the purpose of age determination (weight of eye lenses), sex ratio and productivity. The results of our analysis showed that the proportion of juve-nile in bag (PYB) among those shot varied from 37.0 % of the last 5-years interval (2018-2023), to a maximum of 51.0 % in interval of years 1998-2002. On total average there were 1.86 juveniles per adult female (r). The proportion of adult females in gamebag varied from 22.58 % (years in-terval 1992-1997) to 31.26 % (years interval 2018-2023). Sex-ratio (SI; males : females) among shot hares showed a value of 0.50, ranged from 0.48 in the period 2008-2012 to 0.52 in the first observed period (years 1987-1991) and in the last one (years 2018-2023). Average weight of shot hares was 4.04 kg (juveniles 3.83 kg, adults 4.27 kg, adult males 4.21 kg and females 4.32 kg). There was a large positive effect of set-aside with special mixtures, created for hares in large-scale farmed agrarian landscape, on hare density, bag and recruitment. In model hunting grounds with such set-asides increased the spring stock by 25 %, bag by 100 % and recruitment by 20 %. This study reveals that the management of European brown hare is not sustainable, and the population is decreasing. It is proved through the decline of harvest hares and by population dynamics parameters. Environmental improvements lead to the stabilization and increasing of requested parameters.

Most of the mid-high permeability sandstone oilfields in China have entered the ultra-high water cut stage, accompanied with the highly-dispersed residual oil, and the control effect of mi-cro-heterogeneity on the residual oil is increasingly prominent. Understanding the microscopic characteristics of pore structural and its evolution during the long-term waterflooding is critical for enhancing the accuracy and efficiency of oil field exploitation. While the previous insights paid more attention to the geometrical and morphological features of pore structure and ignores the relation of pore structure with the fluid flow capacity. In this study, we propose a microscopic pore structure classification method considering pore size and local permeable capacity, which realizes the physical classification and quantitative evaluation of pore structure characteristics for different permeability rocks. The micro-pore structure is classified into 6 types based on the key evaluation parameters of pore diameter and flow flux area. By taking six mid-high permea-bility sandstone core samples from Daqing oilfield in China, a series of long-term waterflooding experiments are carried out and the interior pore structure was captured using high precision CT scanning technique. The results reveals that high-permeability reservoirs exhibit concentrated pores diameters and finer throats, whereas mid-permeability reservoirs exhibit smaller pores and throats in greater quantity. With the increase of water injection volumes, the permeable ca-pacity and connectivity of the high-connectivity pore space in ultra-high- and high-permeability reservoirs are enhanced, and in mid-permeability reservoirs, the micro-heterogeneity intensifies the increase in low-connectivity small pores. These findings provide new insights for the micro-scopic heterogeneity and a solid theoretical basis for investigating the occurrence of microscopic residual oil and optimising enhanced oil recovery strategies at the late stage of ultra-high water cut.

Domain generalization has led to remarkable achievements in Hyperspectral Image (HSI) classification. Inspired by contrastive language-image pre-training (CLIP), the language-aware domain generalization method has been explored to learn cross-domain-invariant representation. However, existing methods face some challenges: 1) The weak capacity to extract long-range contextual information and inter-class correlation. 2) Due to the inadequacies of the large-scale pre-training for HSI data, the spatial-spectral features of HSI and linguistic features can not be straightforwardly alignment. To address the above problems, a novel network has been proposed with a CLIP framework, which consists of an image encoder, based on an encoder-only transformer to obtain the global contextual information and inter-class correlation, a frozen text encoder, and a cross-attention mechanism, named Linguistic-Interact-with-Visual Engager (LIVE), enhances the interaction between two modalities. Extensive experiments demonstrating superior performance over state-of-the-art methods in HSI Domain Generalization with a CLIP framework.

The influence of short term water absorption on the mechanical properties of halloysite nanotubes-multi layer graphene reinforced polyester hybrid nanocomposites has been investigated. The addition of nano-fillers significantly increased the flexural strength; tensile strength and impact strength in dry and wet conditions. After short term water exposure; the maximum microhardness; tensile; flexural and impact toughness values were observed at 0.1 wt% MLG. The microhardness increased up to 50.3%; tensile strength increased up to 40% and flexural strength increased up to 44%. Compared to dry samples; the fracture toughness and surface roughness of all types of produced nanocomposites were increased that may be attributed to plasticization effect. Scanning electron microscopy revealed that the main failure mechanism is caused by the weakening of nano-filler-matrix interface induced by water absorption. It was further observed that synergistic effects were not effective at concentration of 0.1 wt% to produce considerable improvement in mechanical properties of produced hybrid nanocomposites.

Long-term safety of a nutraceutical combination based on agnus castus and magnolia extracts combined with soy isoflavones (SI) and lactobacilli, and effectiveness on vasomotor symptoms and sleep disorders in postmenopausal women, were assessed. A controlled study was carried-out in menopausal women comparing this nutraceutical combination (ESP group) with formulation containing isoflavones alone (C group), at the dosage recommended. Kuppermann index, PSQI, and SF-36 were determined at baseline, 3, 6 and 12 months. Endometrial thickness, mammary density and liver function were evaluated at baseline and after 12 months. 180 women (100 in ESP group and 80 in C group, mean age 55.5 years, in menopause for about 36 months) were enrolled in the study. At the treatment end, mammary density, endometrial thickness, and hepatic function did not show substantial differences between groups. Kuppermann index, and particularly hot flushes, were progressively and significantly decreased in frequency and severity during ESP versus C treatment. No adverse events were observed. Agnus castus and magnolia, combined with SI + lactobacilli, can effectively and safely be used in symptomatic postmenopausal women, mainly when quality of sleep is the most disturbing complaint. Endometrium, mammary glands and liver function, were unaffected after 12 months treatment.

The comfort of the elderly in hospital settings requires a special attention from the involved health care professionals, particularly nurses, since hospitalization often generates suffering and discomfort. In such contexts, it is essential to take into account the specific characteristics of the elderly, considering their life experiences and their needs, to promote the health, well-being, and comfort of this population. Hence, the present work aimed to explore the nursing interventions that promote comfort among the elderly in hospital settings. A mixed descriptive exploratory study was conducted, through the application of a questionnaire, using intentional non-probabilistic sampling. The study encompassed 55 elderly individuals hospitalized in a medical service of a public hospital located in Lisbon. The results show that the participants perceived a reasonable level of comfort (5.65 ± 6.46). The following categories emerged from the content analysis: 1) Physical interventions; 2) Psycho-spiritual interventions; 3) Socio-cultural interventions; and 4) Environmental interventions. These findings help to understand comfort-promoting nursing interventions in the studied population. It was concluded that, to improve care quality, comforting interventions should focus on the elderly patient’s individuality, through support activities, empowerment, and the preservation/correction of the surrounding environment. Additionally, the provided care should be based on the real needs, expectations, preferences, and values of the elderly individual.

This research presents the Cross-Cultural Intelligent Language Learning System (CILS), a novel approach integrating Artificial Intelligence (AI) into language education to enhance cross-cultural communication. CILS utilizes advanced AI technologies to provide adaptive, personalized learning experiences that cater to the unique linguistic and cultural backgrounds of each learner. By dynamically adjusting content and methodology, CILS significantly improves linguistic proficiency and cultural understanding, essential for effective global interactions. The implementation of CILS in platforms such as Busuu and HelloTalk has demonstrated marked improvements in engagement and communication skills among learners. Empirical studies validate the system's effectiveness in real-world settings, showing enhanced learner performance and increased intercultural competence. Additionally, the Technology Acceptance Model (TAM) applied confirms that the usability and perceived usefulness of AI-driven systems strongly influence learner acceptance and sustained use. This study not only underscores the potential of AI in transforming language education but also highlights the critical role of cultural sensitivity in designing educational technologies.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impairments in social interaction and communication, anxiety, hyperactivity, and restricted interest for specific subjects. In addition to the genetic factors, multiple environmental factors have been related to the development of ASD. Animal models can serve as crucial tools for understanding the complexity of ASD and identifying potential therapeutic strategies. In this study, a chemical model of ASD has been developed in zebrafish by exposing embryos to valproic acid (VPA) from 4 to 48 hours post-fertilization. After the exposure, embryos were transferred to fish water and the effects on behavior and neurotransmitters profile were analyzed at both larval and adult stages. Larvae from VPA-treated embryos showed hyperactivity and decreased visual and vibrational escape responses, as well as an altered neurotransmitters profile, with increased glutamate and decreased acetylcholine and norepinephrine levels. Adults from VPA-treated embryos exhibited impaired social behavior characterized by larger shoal sizes and a decreased interest for their conspecifics. Neurotransmitter analysis revealed a significant decrease in dopamine and GABA levels in the brain. These results support the interest of this model in the study of ASD.

(1) Background: Thrombophilia is a tendency towards hypercoagulability, and it is increased by pregnancy, peaking around delivery. Research question: does thrombophilia stimulate the in-flammatory state of the patient, already suppressed by pregnancy? (2) Methods: Eighty thrombo-philia patients admitted for delivery between 1/10/2017 and 1/12/2021 were prospectively stud-ied, together with eighty age- and para-matched control patients. Patients were admitted for de-livery at term by means of cesarean section. The inflammation indexes from the complete blood count values analysis during both the 24 hours before and after labor—extracted from the hospi-tal’s medical records—were calculated and then correlated with uterine involution. (3) Results: Except for the PLR, most of the numerous inflammation indexes studied were not significantly different in treated thrombophilia patients, before and after delivery, compared to non-thrombophilia patients. Only when we split the patients, based on the uterine haematometra in the first 24-48 hours postpartum, we found out that the few treated thrombophilia patients with haematometra (14 with haematometra out of 79 with treated thrombophilia) had elevated SII and AISI antepartum. In pregnant patients treated for thrombophilia, MLR is higher in pa-tients without the Rh factor than in those with the Rh factor. In non-thrombophilia patients, MCVL and NLPR increased with age and before labor, while SII and AISI increased with age postpartum. (4) Conclusions: Thrombophilia did not stimulate the inflammatory state of the pa-tient, already suppressed by pregnancy.

Oritavancin is a novel long-acting lipoglycopeptide with in vitro activity against methicillin-resistant (MR) Gram-positive pathogens and a good bactericidal activity even in presence of biofilm forming bacteria. It has been approved for acute bacterial skin and skin structure infections (ABSSSI), but recent reports have demonstrated possible off-label uses, as for prosthetic joint infections (PJI), which, in more than half of cases, are caused by MR Gram positive organisms. We reported a case of a man in his eighties with a late shoulder PJI caused by methicillin resistant Staphyloccus epidermidis (MRSE) with contraindications for surgical replacement and few oral therapeutic options for a long term suppressive antibiotic therapy. The prosthesis was retained, and the patient received ten outpatient sequential doses of 1200 mg of oritavancin during 28 weeks, based on therapeutic drug monitoring (TDM) as a guide for correct timing of administration of each dose. During oritavancin administration, the patient achieved clinical cure, with disappearance of the pain and regaining pre-infection joint mobility, with no side effects reported and no further surgery or hospitalization needed. The treatment is ongoing as a long-lasting suppressive antimicrobial therapy. Oritavancin could represent an excellent solution for treating PJI caused by MR organism, especially in patients who need a long-term suppressive therapy.

Background: The effect of COVID-19 infection, versus the indirect effect of the pandemic on body composition remains unclear. This study investigates long-term changes in body composition in COVID–19 survivors compared to a contemporary control group. Method: This is a prospective study involving adults who had a pre-pandemic whole-body DXA scan (DXA#1) performed between 2017 and 2019. Participants were asked to return for a repeat whole-body DXA scan (DXA#2) after the pandemic. Detailed data were collected including medical and COVID history. Inflammation markers and fasting lipids were measured. For those participants who had a COVID-19 infection between the 2 DXAs, DXA#2 was acquired at least one year after COVID-19 infection. Results: Overall, 160 adults were enrolled; 32.5% females, 51.8% non-white, with mean age of 43.2 years. Half (n=80) of the participants had documented COVID infection between their 2 DXA scans (COVID+ group), and the other half never had COVID. COVID-negative participants had an increase in annualized trunk fat (g) [922.5 vs. 159.7; P=0.01], total fat (g) [1564.3 vs. 199.9; P=0.2], and LBM (g) [974.9 vs. -64.5; P=0.0002], when compared to COVID+ group. However, among the COVID+ group, no differences were seen in annualized trunk fat, total fat mass, or LBM between those with PASC and without (p>0.05). Conclusion: During the pandemic, both COVID-19-survivors and COVID-negative groups exhibited increases in weight, and total and trunk fat, likely associated with pandemic-linked lifestyle modifications. However, only COVID-19-survivors had a decline in lean body mass over the same period, regardless of PASC symptoms.

Deep underground laboratories offer advantages for conducting high-precision observations of weak geophysical signals, benefitting from a low background noise level. It is both valuable and feasible to enhance strong, noisy ground electromagnetic (EM) field data using synchronously recorded underground EM signals, which typically exhibit a high signal-to-noise ratio. In this study, we propose an EM field reconstruction method employing a Long Short-Term Memory (LSTM) recurrent neural network with referenced deep underground EM observations. Initially, a deep learning model was developed to capture the time-varying features of underground multi-component EM fields using the LSTM recurrent neural network. Subsequently, this model was applied to process synchronously observed strong, noisy data from other conventional observation systems, such as those at surface, to achieve noise suppression through signal reconstructions. Both theoretical analysis and practical observational data suggest that the proposed method effectively suppresses noise and reconstructs clean EM signals. This method is efficient and time-saving, representing an effective approach to fully utilizing the advantages of deep underground observation data. Furthermore, this method could be extended to the processing and analysis of other geophysical data.

This letter presents a dual-frequency terahertz amplitude modulator based on a cross-shaped structure and U-shaped metal patches. Its structural unit is a typical metal-substrate structure. The top metal consists of a cross-shaped structure and U-shaped metal patches, and the bottom substrate layer is made of quartz. Amplitude modulation is achieved by adjusting the temperature of the vanadium dioxide (VO2) patches. The modulation depth can be approximately 75%. The mechanism of the resonance frequency is explained by the equivalent circuit model. The proposed structure shows good amplitude modulation capability at different incidence and azimuth angles by changing the location of the VO2 patches. The dual-frequency terahertz amplitude modulator can be used in terahertz communication, imaging, etc.

Understanding the dynamics of teamwork and communication among healthcare professionals is crucial in the face of evolving healthcare challenges. This study assessed relational coordination among healthcare professionals in the South Tyrolean healthcare system in Italy, focusing on communication and teamwork dynamics in a cross-sectional survey. Using the validated Relational Coordination Survey (RCS) instrument and 525 completed online responses, the questionnaire aimed to understand the implications of different levels of relational coordination ratings by general practitioners, hospital physicians, nurses, and administrative personnel (response rate 26%). The demographics of the participants revealed a predominance of female professionals (64%), with an average age of 50 and 18 years of service. The resulting RCS scores varied significantly across professional groups, with nurses reporting the highest within-group scores, indicating moderate coordination, and administrators reporting the lowest scores, reflecting areas of weak coordination. Between-group relational coordination was generally perceived as weak across professional groups, with the least weakness observed between general practitioners and nurses. German or Italian language and health district affiliation emerged as significant factors influencing relational coordination ratings, highlighting the need for differentiated understanding and strategies in multilingual and diverse regional settings. Assessments of interdisciplinary feedback and referral practices highlight the variation in teamwork and communication weaknesses and underscore the need for targeted interventions to improve relational coordination. This study provides insights into the complexity of relational dynamics in health care settings. It suggests that improving relational coordination through tailored strategies could significantly improve team effectiveness, quality of patient care, and overall system efficiency.

Background/Objectives: Vitamin B12 deficiency can cause variable symptoms, which may be irreversible if not diagnosed and treated in a timely manner. We aimed to develop a widely accepted expert consensus to guide the practice of diagnosing and treating B12 deficiency. Methods: We conducted a scoping review of the literature published in PubMed since January 2003. Data were used to design a two-round Delphi survey to study the level of consensus among 42 experts. Results: The panelists agreed on the need for educational and organizational changes in the current medical practices for diagnosing and treating B12 deficiency. Recognition of clinical symptoms should receive the highest priority in establishing the diagnosis. There is agreement that the serum B12 concentration is useful as a screening marker, whereas methylmalonic acid or homocysteine can support the diagnosis. Patient lifestyle, disease history and medications can provide clues to the cause of B12 deficiency. Regardless of the cause of the deficiency, initial treatment with parenteral B12 was regarded as the first choice for patients with acute and severe manifestations of B12 deficiency. The use of high-dose oral B12 at different frequencies may be considered for long-term treatment. Prophylactic B12 supplementation should be considered for specific high-risk groups. Conclusions: There is a consensus that clinical symptoms need to receive more attention in establishing a diagnosis. B12 laboratory markers can support the diagnosis. The severity of clinical symptoms, the causes of B12 deficiency and the treatment goals govern decisions regarding the route and dose of B12 therapy.

Urban tourism has witnessed significant growth in recent years, driven by various factors that foster the transformation of urban areas into tourist hotspots. These factors include a rising interest in culture and heritage, ongoing urban redevelopment and conversion processes, and the introduction of new experiences and activities. Two particularly influential factors contributing to this growth are low-cost travel, which facilitates more accessible access to urban destinations, and the emergence of new types of accommodation, such as short-term rental (also known as local accommodation or Airbnb-type accommodation). This sudden and continuous growth of this type of tourist accommodation brings new challenges to cities and local communities. On the positive side, it contributes to job opportunities, the dynamism of the local economy, and urban revitalization. On the other hand, it also represents more difficulty in retaining the local population in city centers, as more and more buildings are converted into hostels and tourist apartments. In this context, it becomes essential to conduct studies evaluating the impacts of these dynamics in urban areas and how they influence residents' and visitors' perspectives. Therefore, this study aims to identify the main transformations resulting from short-term rental (STR) development, focusing on the impacts felt by tourists and residents in Porto. A questionnaire was distributed to tourists and residents in Porto's city center in June 2023. The results reveal differences in opinions between tourists and residents, particularly concerning historical heritage preservation, local population relocation, and reduced housing availability for residents. Nevertheless, there is a similarity in their opinions regarding the stimulus that local accommodation brings to the economy and the rehabilitation of buildings and urban areas. This study reinforces the need to pay more attention to the future development of tourist accommodation in city centers, especially regarding local policies and territorial planning, to balance better tourism development and local communities' quality of life.

The intense motion of a ship can greatly impacts the comfort of crew members and the safety of the vessel. Therefore, accurately estimating and predicting ship attitudes has become an important issue. This paper introduces the latest development in functional deep learning model called DeepOnet. It takes wave height as input and ship motion as output, using a cause-to-result prediction approach. The modeling data used in this study is sourced from publicly available experimental data from the Iowa Institute of Hydraulic Research. Firstly, parameters system tuning was conducted for the neural network's hyperparameters to determine the appropriate combination of parameters. Secondly, the DeepOnet model for wave height and multi-degree-of-freedom motion was established, and the influence of increasing time steps on prediction accuracy was examined. Finally, a comparison was made between the DeepOnet model and the classical time series model LSTM. It was found that the DeepOnet model had a 10-fold improvement in accuracy for roll and heave attitudes. Moreover, as the forecast duration increased, the advantage of DeepOnet showed a trend of strengthening. As a functional prediction model, DeepOnet provides a new promising tool for very short-term prediction of ship motion.

With the global objectives of achieving a ‘carbon peak’ and ‘carbon neutrality’, along with the implementation of carbon reduction policies, China’s industrial structure has undergone significant adjustments, resulting in constraints on high-energy consumption and high-emission industries while promoting the rapid growth of green industries. Consequently, these changes have led to an increasingly complex power system structure and presented new challenges for electricity demand forecasting. To address this issue, this study proposes a 24-step multivariate time series short-term load forecasting algorithm model based on KNN data imputation and BiTCN bidirectional temporal convolutional networks combined with BiGRU bidirectional gated recurrent units and attention mechanism. The Kepler adaptive optimization algorithm (KOA) is employed for hyperparameter optimization to effectively enhance prediction accuracy. Furthermore, using real load data from a wind farm in Xinjiang as an example, this paper predicts the electricity load from January 1st to December 30th in 2019. Experimental results demonstrate that our comprehensive short-term load forecasting model exhibits lower prediction errors and superior performance compared to traditional methods, thus holding great value for practical applications.

(1) Background: Ectopic pregnancy (EP) is when fertilized ovum implanted outside of uterine cavity. The incidence was 1.5% to 2.0% of all pregnancies [1, 2]. EP decreases fertility ability [3]. This study focused on the pregnancy rate after EP and various parameters influencing pregnancy. (2) Methods: The data was extracted from National Health Insurance Research Database (NHIRD) during 2000-2013. The study group enrolled women with one EP history. Those who did not have EP was put into the control group. Chi-square/Fisher exact test was performed on category variable and t-test was used on continue variables. (3) Results: The EP group had a higher cumulative rate of conceive, 41.55% than control group, 37.14% and 1.16 times higher risk in developing pregnancy (P&lt;0.001). The conceiving rate was lower than the control group in the first 5 years, but higher than the control group in the 10th to 14th years. (4) Conclusions: The fecundability after EP is lower at the beginning, but regained after long term follow.

(1) Background: Sleep disordered breathing represent a growing public health concern, especially among children and adolescents. Full-night polysomnography is considered the gold standard for diagnosing obstructive sleep apnea. Our goals are to identify personal and environmental risk factors for the onset and persistence of sleep respiratory disorders. We also want to investigate the differences in neuropsychological profiles; (2) Methods: This is an observational, retrospective cohort study. We collected information on adenoidectomy or adenotonsillectomy. We reviewed the clinical history and preoperative visits and collected data through a telephone questionnaire. Pediatric Sleep Questionnaire (PSQ) and the Pediatric Quality of Life Inventory (PedsQL) are questionnaires used for screening sleep respiratory disorders in children. The data were statistically analyzed it using SPSS version 22.0 for Windows (SPSS Inc., Chicago, IL); (3) Results: The study involved 138 patients, but only 100 parents participated. A higher percentage of patients with sleep disordered breathing were observed to have mothers who smoked during pregnancy. A smaller proportion of patients with sleep disordered breathing had a habit of using a pacifier. A rise in physical results is associated with a reduction in the PSQ at follow-up (p=0.051). An increase of overall academic achievement is associated with an average decrease in the PSQ at follow-up (p&lt;0.0001). A more significant proportion of patients undergoing adenotonsillectomy were observed to have a history of prematurity and cesarean birth (4) Conclusions: These results provide essential information on the effectiveness and effects of adenotonsillectomy intervention compared to adenoidectomy intervention and the factors associated with SDB in children undergoing these interventions.

Electrifying aircraft, a crucial advancement in the aviation industry, aims to cut pollutive emissions and boost energy efficiency. Traditional aircraft depend on fossil fuels, which contribute significantly to greenhouse gas emissions and environmental pollution. Despite progress in electric propulsion and energy storage technologies, challenges such as low energy density and integration issues persist. This paper provides a comprehensive thematic and bibliometric analysis to map the research landscape in aircraft electrification, identifying key research themes, influential contributors, and emerging trends. The study applies natural language processing to unstructured bibliographic data and cross-sectional statistical methods to analyze publications, citations, and keyword distributions across various categories related to aircraft electrification. The findings reveal significant growth in research output, particularly in energy management and multidisciplinary design analysis. Collaborative networks highlight key international partnerships, with the United States and China being key research hubs, while citation metrics highlight the impact of leading researchers and institutions in these countries. This study provides valuable insights for researchers, policymakers, and industry stakeholders, guiding future research directions and collaborations.

In the context of sustainable development, integrating the work aspect into health promotion systems is essential, ensuring that employees maintain a healthy balance between their professional and personal lives, which respects and amplifies the potential of every individual. Lately, there has been a noticeable shift of medical professionals from the public to the private sector. This trend paints a bleak picture, highlighting the vulnerabilities of a system teetering on the brink of failure, with significant impacts on patient care. Among the myriad reasons behind this shift, burnout stands out prominently. Medical professionals face increasing pressures due to understaffing, limited organizational support, and insufficient resources, leading to feelings of cynicism, exhaustion, and detachment from their roles. Utilizing the Maslach et al. questionnaire, we assessed the risk of burnout among physicians in public hospitals to identify and underscore preventive measures and improvements, correlating our findings with key aspects of organizational empowerment. Our research indicates that enhancing interpersonal relationships and resources—both within teams and between the organization and its physicians—is crucial for the revival of the healthcare system. This approach aims at improving the delivery of healthcare services and offering appropriate recognition to healthcare professionals, aligning with the principles of sustainable employment.

Over recent years globalisation has occasioned a dramatic rise in cross-cultural interactions – until this was disrupted by the COVID-19 pandemic (OECD 2018, Nelson &amp; Luetz 2021). The ability to competently engage in a multicultural world is often considered the “literacy of the future” (UNESCO 2013, OECD 2018). Global interconnectedness has brought studies into intercultural competence to centre stage (UNDP 2004, Bissessar 2018, Nelson et al. 2019). This has increased the demand for cross-cultural education experiences that facilitate such learning. However, there is a dearth of empirical research into the issues and effects surrounding short-term cross-cultural educational experiences for adolescents. This mixed methods study extends previous research by looking specifically into what impact short-term cross-cultural experiences may have on the formation of intercultural competence and emotional intelligence of Australian high school students. This study used two instruments for measuring intercultural competence and emotional intelligence in a pre- and posttest quasi-experimental design (n=14), the GENE Scale and TEQ. Moreover, it conducted in-depth post experience qualitative interviews (n=7) that broadly followed a phenomenological paradigm of inquiry. The findings suggest that fully embodied cross-cultural immersive experiences offer benefits in areas of intercultural competence and emotional intelligence and can offer meaningful application in areas of current affairs. A greater understanding of the linkages between immersive cross-cultural experiences and intercultural competence offers prospects for policy makers, educators, pastoral carers, and other relevant stakeholders who might employ such experiential learning to foster more interculturally and interracially harmonious human relations.

The increase in the frequency of droughts in Africa has increased the interest in crops with drought escape mechanisms like grain Amaranth (Amaranthus hypochondriacus). However, the white-seeded grain Amaranth is easily cross-pollinated by its black seeded wild relatives such as smooth pigweed (Amaranthus hybridus). A study to investigate a minimum isolation distance enough to prevent seed contamination study was carried out at three sites namely Gweru and Bindura (2020/2021 rainy season) and Shamva (2021/2022 rainy season). Smooth pigweed was planted at distances of 3 to 150 m from pure grain Amaranth. Close monitoring of phenology and measurement of meteorological conditions such as temperature, wind speed and direction were done during the anthesis period. Cross-pollination in grain Amaranth was influenced by distance from the pollen source. A maximum of 12.9 % contamination rate was measured within the 10 m radius from the pollen donor plot and a minimum outcrossing rate of 0.45 % was recorded at the widest distance of 150 m. It can be concluded that complete removal of wild relatives of grain Amaranth is important within the field at as far as 150 m from the crop.

In recent years there has been a clear increase in bottled water consumption, globally which translates to significant health and environmental concerns. This cross-sectional study aims to understand the attitude and preferences of university students in Qatar towards use of bottled and tap water for drinking purposes using an online survey questionnaire. The number of students who responded to the online survey was 14% of the entire student population within the university (n = 688). Overall, majority of the students reported plastic bottled water as the main source of drinking water they preferred to use on campus (n=468; 68.02%), with a higher proportion of females (72.08%) preferring the use of plastic bottled water. Out of the 468 students who preferred plastic bottled water, safety was the most important factor (43.80%) followed by convenience (16.88%) and taste (15.60%). Cost (15.17%), personal/family habits (5.13%), Environmental concerns (2.14%) and minerals (1.28%) were found to be the least important factors. Among the 45 students who preferred tap water over plastic bottled water, cost (46.67%) was the dominant factor followed by convenience (20.00%) and environmental concerns and safety (13.33% each), taste (4.44%), and personal/family habits (2.22%). This study recommends campaigns to focus on attitude and behavior change and not solely emphasize knowledge; 71.7% believed that plastic water bottles are more harmful to the environment, yet the greater majority still resorted to this source. There is an immediate need to further educate students through environmental and health literacy programs on water consumption and quality. Enabling the population to understand the positive and negative aspects of their choices, may be an effective remedy to ensuring a healthy population and healthy environment.

Despite decades of conflict and political instability, drought has also severely affected Afghanistan’s rural population and agriculture sector. Agriculture is a primary livelihood source in the country, and recurring droughts have put cascading pressures on the agricultural economy and food security. Therefore, understanding the key drivers of all risk components through a comprehensive risk assessment is critical for proactive drought risk management. This study assesses agricultural drought risk from an integrated perspective, emphasizing the combined effects of drought hazard, exposure, and vulnerability. Multi-methods research was conducted, employing remote-sensing-based analysis covering a period from 2001 to 2023. We used the Vegetation Condition Index (VCI) to analyze the drought hazard for the agricultural system during the winter growing season. The vulnerability indicators and exposure levels of the agricultural system were determined through spatial analysis combined with a literature review and expert consultation. An adapted conceptual framework of the Intergovernmental Panel on Climate Change (IPCC) was utilized, which incorporates hazard, exposure, and vulnerability to define risk. The results revealed that droughts occur frequently and in changing patterns throughout the country. All provinces have experienced drought over the past two decades, albeit with varying severities and frequencies. Severe droughts were observed in 2001-2002, 2008, 2011, 2018, and consecutively in 2021-2022-2023. Drought vulnerability and exposure vary widely across the country, particularly in the northern, western, and southern provinces. The final calculated risk shows that most provinces in southern and southwestern zones face a high risk of recurrent droughts, further exacerbating agricultural challenges in these regions. Such analyses under a multimethod approach provide information on spatial patterns of drought risk and drivers of agricultural systems that can support decision-makers and policymakers in formulating strategies to reduce drought risk and adapt to the agricultural sector.

Pregnant women (PW) are at a higher risk of diseases and hospitalization from viral respiratory infections, specially influenza, due to cardiopulmonary and immunological changes. This study assessed the impact of viral respiratory infections on PW hospitalized with severe acute respiratory infection (SARI). It´s a cross-sectional study with 42 PW and 85 non-pregnant women (NPW) admitted with SARI to two tertiary hospital between January 2015 and December 2019. The rate of virus prevalence, SARI hospitalization, length of hospital stay, oxygen supplementation, intensive care unit (ICU) admission, and death were comparable between PW and NPW. Multivariate analysis showed that PW had a higher rate of viral SARI hospitalizations (OR = 2.37; 95% CI =1.02 - 5.48) compared to NPW, with influenza virus being the most prevalent (aOR =7.58; 95% CI =1.53 - 37.66). Length of hospital stay (aOR = 0.83; 95% CI = 0.73 – 0.95) and admission to the ICU (aOR=0.028; 95% CI=0.004 - 0.25) were lower in PW compared to hospitalized NPW. Respiratory viruses had a greater impact on the frequency of SARI in the group of PW. Although PW had a higher rate of influenza SARI, they had a better outcome than NPW due to the treatment they received.

Urea cycle disorders (UCDs) are common inborn errors of metabolism, with an incidence of one in 30,000 births. They are caused by deficiencies in any of six enzymes and two carrier proteins, the most common being Ornithine Transcarbamylase Deficiency (OTCD). OTCD results in impairment to excrete nitrogen, causing toxic buildup of ammonia with resultant encephalopathy. Hyperammonemia (HA) induces the conversion of glutamate to glutamine in the brain. Excess glutamine in the brain causes osmotic changes cerebral edema, changes in astrocyte morphology, and cell death. Acute symptoms of HA include vomiting, hyperventilation, seizures, and irritability. Long-term neurological changes include deficits in working memory and executive function. To date, there are no predictors of prognosis of infants with neonatal onset OTCD outside of plasma ammonia level at presentation and duration of hyperammonemic coma. We provide a comprehensive analysis of a 16-year-old male with neonatal onset of OTCD as an example of how brain biomarkers may be useful to monitor disease course and outcome. This male presented at 8 days post natal with plasma ammonia and glutamine of 677 and 4024 micromol/L and had a missense mutation in Exon 4 (p.R129H). Treatment included protein restriction, sodium benzoate, and citrulline, arginine, and iron. He suffered recurrent acute hyperammonemic episodes despite compliance, triggered by infections or catabolic stressors. We discuss the long-term effects of the hyperammonemic episodes by following MRI based disease biomarkers.

This study examines the association of sociodemographic risk factors and the comorbidities of COVID-19. Most COVID-19-related studies were conducted in inpatient settings among patients with severe infection during the first and second waves of the pandemic. The third wave with less severe Omicron variant presented a unique opportunity to observe the adult patients treated in outpatient settings. We conducted a cross-sectional study (117 patients aged &gt; 40 years presented with symptomatic COVID-19). We employed the Charlson Comorbidity Index (CCI) to compute comorbidity burden, Medical Outcomes Survey Short form (SF-12) to measure general health, and Self-care Self- Efficacy Scale (SCSES) to assess self-care ability. Fisher’s exact test and analysis of variance (ANOVA) were used to compute the relationship between comorbidities and demographics. This study report focuses on the distribution of the comorbidities and its relationship to demographic variables. The top five comorbidities were hypertension (42%), diabetes (31%), pulmonary disease/asthma (19%), depression (14%), and cancer (11%). Depression was significantly higher among younger age groups (p&lt;0.01) and women (p&lt;0.05). Age (p&lt;0.0001) and income (p&lt;0.01) were the most significantly associated demographics with the comorbidity burden. Incidence of pulmonary disease showed a positive association to educational status (p=0.05). This was the first study to report a significant prevalence of depression among adults with symptomatic COVID-19.

This study introduces a novel method for early prediction of Kimchi cabbage (Brassica rapa subsp. pekinensis (Lour.) Hanelt) height, utilizing drone imagery and a long short-term memory (LSTM) model. The research was conducted on a testbed at the National Institute of Agricultural Sciences (NAS) in South Korea, encompassing two distinct soil types (loam and sandy loam) to investigate their impact on growth. High-resolution drone images were captured throughout the growing season to generate a canopy height model (CHM) for estimating plant height at various stages. Missing height data were interpolated using a logistic growth curve, and an LSTM model was trained on this data to predict the final height of Kimchi cabbage at harvest. Three LSTM models were developed using time-series data collected at 29, 36, and 44 days after planting (DAP). The model trained on data from DAP 44 demonstrated the highest accuracy with a coefficient of determination (R²) of 0.83, a mean absolute error (MAE) of 2.48 cm, and a root mean square error (RMSE) of 3.26 cm, outperforming models trained on earlier data. Color-coded maps were generated to visualize the spatial distribution of predicted Kimchi cabbage heights, revealing variations in growth patterns across the testbed and confirming the model's potential for site-specific management. Considering the trade-off between accuracy and prediction timing, the model trained on DAP 36 data (MAE = 2.77 cm) was deemed optimal for informing cultivation management decisions. This research demonstrates the feasibility and effectiveness of integrating drone imagery, logistic growth curves, and LSTM models for early and accurate prediction of Kimchi cabbage height. The proposed technology enables data-driven decision-making for farmers, facilitating timely interventions based on predicted growth patterns. This could lead to improved crop yields, resource optimization, and a more sustainable agricultural future. Future research will focus on refining the model's accuracy and exploring its applicability to other crops, further expanding the potential of precision agriculture technologies.

The existing segmentation-based scene text detection methods mostly need complicated post-processing, and the post-processing operation is separated from the training process, which greatly reduces the detection performance. The previous method, DBNet successfully simplified post-processing and integrated the post-processing into a segmentation network. However, the training process of the model took a long time for 1200 epochs and the sensitivity to texts of various scales was lacking, leading to some text instances being missed. Considering the above two problems, we design the text detection Network with Binarization of Hyperbolic Tangent(HTBNet). First of all, we propose Binarization of Hyperbolic Tangent (HTB), optimized along with which, the segmentation network can expedite the initial convergent speed by reducing the amount of epochs from 1200 to 600. Because features of different channels in the same scale feature map focus on the information of different regions in the image, to better represent the important features of all objects in the image, we devise the Multi-Scale Channel Attention(MSCA). Meanwhile considering that multi-scale objects in the image cannot be simultaneously detected, we propose a novel module named Fused Module with Channel and Spatial(FMCS), which can fuse the multi-scale feature maps from channel and spatial dimension. Finally we adopt cross entropy as the loss function, which measures the difference between predicted values and ground truths. The experimental results show that HTBNet compared with lightweight models has achieved competitive performance and speed on Total-Text(F-measure:86.0%, FPS:30) and MSRA-TD500 (F-measure:87.5%, FPS:30).

Despite the importance of influenza vaccination for healthcare workers (HCWs), their uptake remains challenging. This study aimed to measure influenza vaccine hesitancy among HCWs in Nakhon Phanom province, Thailand. A representative cross-sectional survey was conducted at six hospitals during August – September 2020 using a self-administered questionnaire. HCWs delaying getting influenza vaccines, accepting but unsure, or refusing with doubts were categorized as hesitant. Those accepting without any doubts were classified as non-hesitant. Vaccine hesitancy determinants were identified by multivariable logistic regression analysis. A total of 338 participants (97%) completed the questionnaires; most were female nurses working at district hospitals without pre-existing chronic medical conditions. Nearly 60% of participants (197/338) exhibited influenza vaccine hesitancy, and significant factors included age above 50 years adjusted odds ratio [aOR] 3.2, 95% CI 1.3-8.5), fair knowledge of influenza/vaccination (aOR 0.4, 95% CI 0.2-0.8), and negative influence of other HCW (High level– aOR 2.3, 95% CI 1.1-4.8; Moderate level- aOR 2.1, 95% CI 1.1-4.4). Imparting updated information to the HCW combined with positive guidance from influential peers may help reduce this hesitancy.

This study examines the Soil Organic Carbon (SOC) within Greek croplands, offering a comprehensive understanding of its dynamics. SOC, a cornerstone in soil health, nutrient cycling, and global carbon dynamics, assumes critical significance in sustainable agriculture and climate change mitigation. Drawing on diverse soil properties, including pH, soil texture as well as different drainage and slope categories, the research explores the nuanced relationships shaping SOC dynamics in the diverse agroecological landscape of Greece. The investigation transcends local boundaries, emphasizing SOC's global role in climate change mitigation by sequestering carbon dioxide. Two maps were used as data sources: 1) SOC stock baseline map (2010) by JRC, 2) SOC stock map (2021) by the Institute of Soil and Water Resources, Hellenic Agricultural Organization – DIMITRA in collaboration with FAO. Greek croplands emerge as a mosaic of agroecological diversity, where anthropogenic activities wield transformative influences on SOC stock, demanding a delicate balance between agricultural productivity and soil health. The study unveils the influence of Soil Order, weaving a tapestry of SOC variability. Microscopic factors, from soil texture to cation exchange capacity, further shape SOC dynamics, emphasizing the role of clayey soils and coarse materials in carbon retention. Although soil organic carbon decreased from 2010 to 2021 the degree of carbon loss varied. This scientific endeavor synthesizes existing knowledge and unveils novel insights, offering a narrative woven from diverse soil properties. The findings contribute valuable insights for sustainable land management practices and climate change mitigation strategies, underscoring the importance of region-specific approaches in addressing global challenges.

Background/Objectives Bowel endometriosis (BE) is defined as the presence of endometrial-like tissue in the muscular layer of the bowel wall. When BE does not cause severe obstruction to fecal transit, not leading to (sub)occlusive symptoms, the decision to operate becomes challenging as intestinal surgery is associated with higher complication rates and long-term bowel dysfunction. The aim of this cross-sectional study is to evaluate the quality of life (QoL) in patients with BE undergoing medical therapy or expectant management, investigating the impact of characteristics of BE nodules on QoL and intestinal function. Methods A retrospective cross-sectional analysis was conducted on 580 patients with BE who did not undergo surgery but were treated conservatively by medical therapy or expectant management between January 2017 and August 2022. The diagnosis of BE was done by transvaginal ultrasound and confirmed at double contrast barium enema. After at least one year of follow-up, QoL and intestinal function of patients were evaluated by the Endometriosis Health Profile-5 (EHP-5) questionnaire and Bowel Endometriosis Symptom score (BENS), whereas pain symptoms were assessed by the Visual Analogic Scale (VAS 0-10). Statistical analysis was performed to investigate possible associations between QoL and characteristics of bowel nodules (dimension, location, and evidence of stenosis) as well as type and length of eventual medical therapy. Results Patients with BE had a satisfying overall QoL with a mean EHP-5 score of 105.42 ± 99.98 points and VAS lower than 3 for all pain domains; additionally, they did not show a significant impartment of bowel function with mean BENS score of 4.89 ± 5.28 points. Notably, patients under medical therapy had a better QoL than patients without therapy (p

There are many modern and traditional methods in valuing the performance of the company among them EVA, CVA are modern methods where as EPS, ROI, ROE etc. are some of the traditional methods. modern and traditional methods are not only used to check the performance of a company but it also used in investment decisions by the investors. Stern Stewart, managing partner of M/s Stern Stewart & Co. introduced a modified concept of economic profit in 1990 in the name of Economic Value Added (EVA) as measure of business performance and CVA is only a cash consideration in EVA. In this paper an attempt is made to study which method is used by the investors while taking the investment decisions i.e. traditional methods are modern methods. 100 respondents (Investors) are questioned and collected their views, we are assuming that there is no impact of traditional or modern methods while taking investment decisions by the investors.

This study explores the role of inflammation and oxidative stress, hallmarks of COVID-19, in accelerating cellular biological aging. We investigated early molecular markers—DNA methylation age (DNAmAge) and telomere length (TL)—in blood leukocytes, nasal cells (NC), and induced sputum (IS) one-year post-infection in pauci- and asymptomatic healthcare workers (HCWs) infected during the first pandemic wave (February-May 2020), compared to COPD patients, model for "aged lung". Data by questionnaires, Work Ability Index (WAI), blood analyses, autonomic cardiac balance assessments, heart rate variability (HRV), and pulmonary function tests were collected. Elevated leukocyte DNAmAge significantly correlated with advancing age, male gender, daytime work, and an aged phenotype characterized by chronic diseases, elevated LDL and glycemia levels, medications affecting HRV, and declines in lung function, WAI, lymphocyte count, hemoglobin levels, and HRV (p&lt;0.05). Increasing age, LDL levels, job positions involving intensive patient contact, and higher leukocyte counts collectively contributed to shortened leukocyte TL (p&lt;0.05). Notably, HCWs exhibited accelerated biological aging in IS cells compared to both blood leukocytes (p≤0.05) and NC (p&lt;0.001), and were biologically older than COPD patients (p&lt;0.05). These findings suggest the need for monitoring aging in pauci- and asymptomatic COVID-19 survivors, who represent the majority of the general population.

Climbing is an Olympic discipline in full development and multidisciplinary in nature, in which the influence of body composition and nutritional status on performance has not yet been clarified despite the quest for low weight in anti-gravity disciplines such as climbing. The present study aimed to do a nutritional (3-day dietary diaries) and body composition (ISAK profile) assessment of sport climbing athletes of different genders and sport levels. The mean age of the forty-six Spanish climbers (22 men and 24 women) was 30 years (SD: 9) with 7.66 years of experience (SD: 6.63). The mean somatotype of the athletes was classified as balanced mesomorph. Negative correlations were observed between fat mass variables and climbing level (p<0.01), and positive correlations with forearm circumference (p<0.05). Mean energy availability (EA) was 33.01 kcal-kg FFM1-d1 (SD: 9.02), with 55.6% of athletes in suboptimal EA status and 35.6% in low energy availability (LEA) status. Carbohydrate and protein intakes were below recommendations in 57.8% and 31.1% of athletes, respectively. There were deficient intakes of all micronutrients except phosphorus in males. These findings suggest that climbing athletes are at high risk of developing low energy availability states and concomitant problems. Optimal nutritional monitoring may be advisable in this type of athlete to try to reduce the risk of LEA.

This systematic review explores the cross-cultural validation of neuropsychological assessments and their clinical applications in cognitive behavioral therapy (CBT), focusing on culturally adapted CBT (CA-CBT) across diverse populations and settings. Methods: Following the PRISMA guidelines, a comprehensive search was conducted in multiple academic databases, including PubMed, PsycINFO, Scopus, and Web of Science. Keywords related to cognitive-behavioral therapy, cultural adaptation, and specific populations were used. Inclusion criteria encompassed randomized controlled trials (RCTs) and pilot studies that assessed CA-CBT for various mental health conditions. Results: The review included studies involving Chinese Americans, Latino caregivers, Syrian refugees, Jordanian children, Malaysian Muslims, Afghan refugees, Iraqi women, Japanese children and adolescents, and Tanzanian and Kenyan children. CA-CBT demonstrated significant effectiveness in reducing symptoms of depression, anxiety, PTSD, and psychosis. For instance, Research has shown that CA-CBT is more effective than standard CBT in reducing depressive symptoms among Chinese Americans and significantly lowering PTSD symptoms in Syrian refugee women. The method has been well-received and feasible in diverse populations, such as Jordanian children and Afghan refugees. Long-term benefits are promising, with sustained improvements reported in various studies. Additionally, digital and remote delivery methods have demonstrated potential for expanding the accessibility of CA-CBT. Conclusions: CA-CBT is a valuable and effective intervention for diverse cultural populations, significantly improving mental health outcomes. However, future research must address limitations such as small sample sizes, short follow-up periods, and variability in assessment tools. Studies should include larger and more diverse sample sizes, longer follow-up periods, rigorous control groups, and comprehensive outcome measures to further validate and enhance the application of CA-CBT across different cultural contexts.

(1) Exoskeletons offer potential benefits for overhead working tasks, but gender effects or differences are unclear. This study aimed to compare the performance, strain, and comfort of men and women using an upper-body exoskeleton. (2) n=20 female and n=16 male participants performed an overhead drilling task with and without a passive upper-body exoskeleton in a randomized cross-over study. Task performance of different movement phases, perceived exertion, and ease of use were measured to compare gender differences. One and two-way analyses were used to com-pare genders in the different conditions. (3) Gender differences after controlling for BMI in task performance were found for error integrals (p <.001) with higher values in male participants. Moreover, there was a significant interaction effect for gender x exoskeleton use. While females showed performance decrements in aiming with exoskeleton use, the male's performance increased (p=.025). No other gender differences were observed. (4) Gender differences in task performance using an upper-body industrial exoskeleton were less detectable than expected after controlling for BMI, indicating that body composition and anthropometrics might be valuable indicators for per-formance including assisting devices. Moreover, future studies should also integrate the examina-tion of muscle activity to gain more insights into potential gender movement control patterns.

The essence of cross-modal generation and retrieval modeling for image-text interactions lies in semantic consistency. Among these, cross-modal representation alignment serves as the foundational requirement for achieving cross-modal semantic consistency. The crux of our proposed method entails the collaborative training of an image captioning model(referred to as the ’captioner’) and a pair of contrastive encoders for image-text matching(referred to as the ’concoder’). This synergistic approach yields concurrent enhancements in concoder’s performance, captioner’s proficiency, and cross-modal semantic coherence. We coin the proposed method as ‘ReCap’. To begin, we initialize the concoder through knowledge distillation from a pre-trained model. During the training process, we use the output of the initialized concoder as input to a residual attention network, jointly training it with the captioner to achieve semantic consistency. Subsequently, we iteratively update the concoder during the image-text momentum encoding phase using the residual attention network, creating a closed-loop for semantic consistency resolution. Upon completion of training, the concoder and captioner modules can be used independently to perform tasks related to cross-modal retrieval and cross-modal generation of text and images. In order to substantiate the efficacy of our proposed method, we initially conducted empirical experiments encompassing image-text retrieval and image captioning tasks, employing a widely recognized benchmark dataset, MSCOCO. Subsequently, we assessed the fine-grained cross-modal alignment performance of the concoder through an image classification task on the iNaturalist 2018 dataset. The achieved performance metrics notably surpassed those achieved by several incumbent state-of-the-art models, thus validating the proficiency of our method. Finally, motivated by the practical requirements of handling the nature conservation image data, we performed caption annotation for the iNaturalist 2018 dataset. Subsequently, we trained the ReCap on this annotated data. Experimental results demonstrate that our proposed method can maintain semantic consistency between cross-modal retrieval and image caption generation for species with similar visual features but distinct semantics. This achievement signifies a meaningful exploration in the field of cross-modal semantic consistency representation, holding significant practical value in the domain of biological research.

Background/Objectives: Adolescence represents a period of heightened vulnerability to risky sexual behaviours. In Portugal, adolescents are initiating sexual activity at increasingly younger ages. Yet, there are no studies evaluating their knowledge about sexually transmitted diseases and prevention methods at an earlier stage of their development. Study how middle school ad-olescents define their sexuality and assess their level of information regarding sexuality, STI, and prevention methods. Additionally, it explores adolescents' sources of information on sexuali-ty-related issues. Methods: A cross-sectional observational study was conducted involving the application of a questionnaire to 750 9th-grade students of Vila Nova de Gaia, Porto, Portugal. The questionnaire covered topics such as perceptions of sexuality, knowledge of sexuality and STI, methods of transmission prevention, and sources of information. Results: The mean age was 14.4 years, with 19.9% reporting having already initiated sexual ac-tivity. Overall, the knowledge about sexually transmitted infections is low, pointing to 7.08 out of a maximum score of 18. Condoms and immunisation are well-recognized preventive measures, but many misconceptions persist. Better knowledge is associated with better attitudes in the likelihood of having sexual intercourse. Conclusions: This study reveals adolescents' limited sexually transmitted infections knowledge, misconceptions about prevention, and reliance on peers and the internet over trusted sources, highlighting the need for comprehensive sexual education in middle school.

This research investigates the relationship between the long-term orientation of top managers and their strategic decision-making processes, emphasising the comprehensiveness, speed, and inventiveness of decisions. The study employed structural equation modelling to look into the suggested connections using a sample of CEOs. The findings demonstrated a high and positive correlation between long-term orientation and decision comprehensiveness and speed, but not for decision creativity. The study contributes to the growing body of research on how human variations, such as temporal orientation, affect business outcomes and strategic decision-making. Moreover, the fact that a number of the results differed from those of other studies carried out in other contexts highlights how important it is to consider the industry and cultural environment when assessing these connections.

Rechargeable solid-state batteries (SSBs) offer enhanced safety, higher energy density, and longer cycle life compared with conventional lithium-ion batteries, making them a promising solution for electric vehicles, grid storage, and other high-demand applications. However, challenges such as interface stability, low ionic conductivity, and manufacturing scalability hinder their commercial viability. This research provides a comprehensive cross-sectional thematic and bibliometric analysis of recent SSB research, focusing on four key areas: electrolyte engineering, electrode engineering, battery architecture, and performance evaluation. By analyzing publications from major databases, this study highlights the latest innovations, including improved solid electrolytes, advanced electrode materials, and novel architectures that enhance both performance and manufacturability. The findings offer valuable insights for researchers, engineers, and industry stakeholders by identifying critical gaps in the field and highlighting future research directions. The work examines progress in interface optimization, ion transport improvements, and scalable production techniques, which are crucial for advancing SSB technology. By presenting a detailed review of key developments and challenges, this study contributes to a deeper understanding of SSB progress and its potential to revolutionize the energy storage industry. The results will guide researchers in targeting high-impact areas and help industry leaders and policymakers strategize the commercial deployment of SSBs in electric vehicles, stationary energy storage, and other applications requiring reliable and efficient energy solutions.

Responsible, efficient, and environmentally conscious energy consumption practices are increasingly essential for ensuring the reliability of the modern electricity grid. This study focuses on leveraging time series analysis to improve forecasting accuracy, crucial for various application domains where real-world time series data often exhibit complex, non-linear patterns. Our approach advocates for utilizing Long Short Term Memory (LSTM) and Bidirectional LSTM (BiLSTM) models for precise time series forecasting. To ensure a fair evaluation, we compare the performance of our proposed approach with traditional neural networks, time-series forecasting methods, and conventional decline curves. Additionally, individual models based on LSTM, Bi-LSTM, and other machine learning methods are implemented for a comprehensive assessment. Experimental results consistently demonstrate that our proposed model outperforms all benchmarking methods in terms of mean absolute error (MAE) across most datasets. Addressing the imbalance between activations by consumer and prosumer groups, our predictions show superior performance compared to several traditional forecasting methods, such as the Autoregressive Integrated Moving Average model (ARIMA) and Seasonal Autoregressive Integrated Moving Average model (SARIMA). Specifically, the root mean square error (RMSE) of Bi-LSTM is 5.35%, 46.08%, and 50.6% lower than LSTM, ARIMA, and SARIMA, respectively, on the May test data.

Background: Pediatric mallet finger injuries lack specific treatment guidelines, necessitating an exploration of effective techniques. Our aim was to evaluate the outcomes of the extension block technique in adolescent mallet finger management. Methods: A comprehensive retrospective analysis was conducted involving 36 adolescents who underwent surgery between 2014 and 2022. Ishiguro’s extension block pinning technique was the primary method employed. Treatment outcomes were evaluated using Crawford's criteria, and complications were also assessed. Results: Bone union was achieved in all cases with a mean union time of 42 days (range: 30-92 days). According to Crawford's criteria, 27 cases (75%) were classified as excellent, 5 cases (14%) as good, and 4 cases (11%) as fair. Minimal complications were observed, including three cases (8%) of superficial infections, one case (3%) of dermal necrosis, and another rare instance (3%) of osteomyelitis. No cases of poor outcomes or significant long-term complications were noted. The average follow-up period was 8.6 months (range: 2-42 months). Conclusions: Ishiguro’s extension block technique is a promising surgical option for adolescent mallet fingers. Its adoption could enhance pediatric orthopedic care, offering a valuable child-friendly treatment alternative.

Background: The Fat-Augmented Latissimus Dorsi (FALD) flap is an autologous flap that combines Latissimus Dorsi (LD) flap with immediate autologous fat transfer (AFT) in order to improve breast reconstruction (BR) volume. In recent years, our team has described the ergonomic FALD flap, an evolution of this technique which helps to achieve a complete BR in a single surgical step. In this long-term study, we analyze morphological variations of the breast after ergonomic FALD flap reconstruction compared to the traditional transverse FALD flap technique. Methods: Between December 2020 and September 2022 we prospectively enroll patients undergoing BR using FALD flap into 2 groups: Group A included ergonomic FALD flap, while Group B included traditional FALD flap. The primary endpoint of the study was to compare the two groups in terms of breast projection (BP), breast width (BW) and breast height (BH), while the second endpoint concerned the analysis of the aesthetic outcomes. Results: 32 FALD flaps (23 patients) were performed for the Group-A and 31 FALD flaps (25 patients) for Group-B. There were no significant differences regarding demographic variables. After propensity score weighting analysis, Group-A showed a statistically significant better breast projection (p<0.0001) compared to Group-B. (6.05 vs 5.60). Final aesthetic analyses showed to be superior in Group-A concerning breast shape (p=0.001) and global score evaluation (p=0.004). Conclusion: The ergonomic FALD flap offers better long-term aesthetic outcomes for autologous BR with higher breast projection compared to the traditional transverse FALD flap.

In China, preschool teachers have a significant influence on the development of young children aged 3-6. It is imperative to understand their mental health and the factors associated with it to inform policies, optimize their mental well-being, and support their job performance. This study aimed to investigate the factors contributing to anxiety symptoms among preschool teachers. A sample of 393 Chinese preschool teachers (279 females, 114 males) aged 21-56 completed online questionnaires collecting their socio-demographic and work-related information and assessing anxiety symptoms, interpersonal difficulties, personality traits, perceived stress, resilience, and inner strength. Pearson correlation and multiple linear regression analyses identified significant predictors of anxiety symptoms. The prevalence of anxiety symptoms among the studied cohort was found to be 12.2%. Statistically significant factors positively correlated with anxiety symptoms included objective work-related stress (B=0.149, p<.001), interpersonal difficulties (B=0.921, p<.001), perceived stress (B=0.108, p=.001), and neuroticism (B=0.071, p=.002). The findings highlight the urgent need for measures to reduce work-related stress and anxiety. However, when negative mental health predictors were included, the effect of positive psychological factors became nullified. Positive mental health might have a moderating role in such a negative mental health outcome as anxiety. Therefore, further research is required to understand the impact of positive mental health factors more clearly.

Newborn screening (NBS) is hailed as a public health success, but little is known about long-term outcomes following a positive newborn screen. There has been difficulty gathering long-term follow-up (LTFU) data consistently, reliably, and with minimal effort. Six programs developed and tested a core set of minimal LTFU data elements. After an iterative data collection process and the development of a data collection tool, the group agreed on minimal LTFU data elements. The denominator captured all infants with an NBS diagnosis, accounting for children who moved or died prior to the follow-up year. They also agreed on three LTFU outcomes: if the child was still alive, had contact with a specialist, and received appropriate care specific to their diagnosis within the year. The six programs representing NBS public health programs, clinical providers, and research programs provided data across multiple NBS disorders. In 2022, 83.8% (563/672) of the children identified by the LTFU programs were alive and living in the jurisdiction; of those, 92.0% (518/563) saw a specialist, and 87.7% (494/563) received appropriate care. The core LTFU data elements can be applied as a foundation to address the impact of early diagnosis by NBS within and across jurisdictions.

With the rapid development of technology and the advancement of Internet technology, various social networking platforms are gradually coming into people's view and occupying a higher and higher position. In the recommendation scenario, the user-item interaction naturally forms a bipartite heterogeneous graph structure and with the development of graph embedding and graph neural network technologies based on deep learning to process graph domain information, the combination of graph information and recommendation systems shows strong research potential and application prospects. The methodological improvement of the recommendation algorithm based on collaborative filtering takes advantage of the nature that user-items can form a bipartite graph in the recommendation scenario. The existing methods still have some shortcomings. The methods that only use weights or convolutional recurrent neural networks to implicitly model different historical behaviors lack explicit modeling of video switching relationships in serialized behaviors. The user's interest is changing all the time, so it is not possible to recommend based on the user's history, and it is necessary to consider both the long-term and short-term interest of the user according to the video content in order to achieve accurate recommendation of short videos. In this paper, we design a recommendation model based on graph neural network, which models users' long-term and short-term interests by two vector propagation methods, respectively.

This study introduces a comparative analysis of two deep learning (multilayer perceptron neural networks (MLP-NN) and the long short term memory networks (LSTMN)) models for transit travel time prediction. The two models were trained and tested using one-year worth of data for a bus route in Blacksburg, Virginia. In this study, the travel time was predicted between each two successive stations to all the model to be extended to include bus dwell times. Additionally, two additional models were developed for each category (MLP of LSTM): one for only segments including controlled intersections (controlled segments) and another for segments with no control devices along them (uncontrolled segments). The results show that the LSTM models outperform the MLP models with a RMSE of 17.69 sec compared to 18.81 sec. When splitting the data into controlled and uncontrolled segments, the RMSE values reduced to 17.33 sec for the controlled segments and 4.28 sec for the uncontrolled segments when applying the LSTM model. Whereas, the RMSE values were 19.39 sec for the controlled segments and 4.67 sec for the uncontrolled segments when applying the MLP model. These results demonstrate that the uncertainty in traffic conditions introduced by traffic control devices has a significant impact on travel time predictions. Nonetheless, the results demonstrate that the LSTMN is a promising tool that can has the ability to account for the temporal correlation within the data. The developed models are also promising tools for reasonable travel time predictions in transit applications.

Management of chronic inflammation and wounds has always been a key issue in the pharmaceutical and healthcare sector. Curcumin (CCM) is an active ingredient extracted from turmeric rhizomes that has antioxidant, anti-inflammatory, and antibacterial activities, thus showing significant effectiveness toward wound healing. However, its shortcomings such as poor water solubility, poor chemical stability and fast metabolic rate limit its bioavailability and long-term use. In this context, hydrogels appear to be a versatile matrix for carrying and stabilizing drugs due to the biomimetic structure, soft porous microarchitecture, and pleasant biomechanical properties. The drug loading/releasing efficiencies can also be controlled by use of highly crystalline and porous metal organic frameworks (MOFs). Here, a flexible hydrogel composed of sodium alginate (SA) matrix and CCM-loaded MOFs was constructed for long-term drug release and antibacterial activity. The morphology and physicochemical properties of composite hydrogels were analyzed by scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (XRD), ultraviolet visible spectroscopy (UV-Vis), Raman spectroscopy and mechanical property tests. The results showed that the composite hydrogel was highly twistable and bendable to mechanically comply with human skin. The as-prepared hydrogel could capture efficient CCM for slow drug release as well as effective killing of bacteria. Therefore, such composite hydrogel is expected to provide a new management system for chronic wound dressings.

Background: The antisense oligonucleotide against APOC3 mRNA volanesorsen was recently introduced to treat Familial Chylomicronemia Syndrome (FCS). Cases of decreased platelet count are reported among patients treated with volanesorsen. The aim of the study is to evaluate platelet function and thrombin generation (TG) assessment in FCS patients receiving volanesorsen. We performed a cross-sectional study on FCS patients treated with volanesorsen. Methods: changes in PLC were assessed from baseline to Tw12 and Tw36. To assess TG, samples were processed by CAT (with PPP-reagent LOW). The results were expressed by the trombogram graphic (thrombin variation over time); lagTime; Endogenous Thormbin Potential(ETP); peak; time to reach peak(ttpeak), startTail e velocity Index. Platelet aggregation was assessed by testing different agonists using turbidimetry method. Results: Four FCS patients and 4 matched healthy controls were included in the present study. Changes in PLC at Tw12 was 30% and 34% at T36w. Thrombin generation results show values in normal range (for patients and controls respectively lagTime:10,42±4,40 and 9,25±0,99; ttPeak:14,33± 4,01 and 13,10±0,67; startTail:32,13±3,54 and 29,46±1,69; velocityIndex:20,21±3,63 and 33,05±13,21; ETP 599,80±73,47 and 900,2±210,99; peak value 76,84±1,07 and 123,30±39,45) and no significant difference between cases and controls. Platelet aggregation test showed values in range with no significant difference with healthy controls Conclusions: Our study showed for the first time that no significant changes in the general haemostasis assessed by TG and in platelet function have been observed in FCS patients receiving volanesorsen.

This paper compares Demand Response algorithms suitable for Short-term Forecasting based on Advanced Metering Infrastructure (AMI). It selects ARIMA (AutoRegressive Integrated Moving Average), SARIMA (Seasonal ARIMA), LSTM (Long Short-Term Memory), and SVM (Support Vector Machine) as the primary research algorithms and delves into their theoretical foundations and functional characteristics. The theoretical background section explores each algorithm’s applicability in analyzing time-series data, recognizing nonlinear patterns, and solving optimization and classification problems. The methodology section will detail the methods of AMI data collection, the implementation of the algorithms, and the experimental setup. In the experiments and results section, the performance of each algorithm will be assessed by applying AMI data and presenting the outcomes of comparative analyses, with a focus on evaluating the predictive accuracy of the algorithms. The discussion will interpret the experimental results, analyzing the advantages and disadvantages of each algorithm and their applicability in the AMI system. It will also explore the limitations of the current research and directions for future research. The conclusion will summarize the key findings of the study and affirm how this research contributes to understanding and improving short-term forecasting and demand response systems based on AMI.

Cross-lingual sentiment analysis is crucial for understanding and interpreting emotions expressed in text across diverse linguistic contexts. However, cross-lingual sentiment analysis faces challenges such as differences in emotional lexicons, data imbalance, and the need for multi-language sentiment normalization. In this study, we propose a novel approach to address these challenges by leveraging low-resource language training techniques to enhance cross-lingual sentiment analysis. Our method aims to bridge the gap in emotional lexicons by adapting sentiment analysis models to diverse linguistic contexts. Additionally, we tackle issues of data imbalance through innovative data augmentation strategies tailored to each language, and we introduce a multi-language sentiment normalization technique to ensure consistent sentiment interpretation across different languages. Our method achieved state-of-the-art results in twelve languages across four domains, demonstrating superior performance in both text-level and sentence-level sentiment analysis tasks. By conducting comprehensive evaluations across diverse linguistic contexts and domains, we showcase the versatility and effectiveness of our approach in achieving top-tier results in cross-lingual sentiment analysis.

A cross-sectional study was organised to investigate the range, prevalence, and associated factors for occupational health problems related to dental practice among Cambodian dentists; Participants underwent a face-to-face interview to explore dentists work-related health problems; 106 Cambodian dentists participated in this study, 68.9% were male. Ages ranged from 29 to 71 years, averaging 36.1 years, with the majority (77.4%) in the 29-40 age group. They had 5 to 18 years of practice experience, and worked an average of 52.2 hours per week. Commonly reported health issues included back pain (88.7%), headaches (81.1%), shoulder pain (78.3%), arm/hand pain (57.5%), and eye problems (48.1%). 38.7% of participants felt stressed and 19.8% depressed. Some reported suicidal thoughts and taking medication for depression. Despite these challenges, 91.5% enjoyed practicing dentistry; Findings highlight the need for interventions and strategies to address the physical and mental well-being of Cambodian dentists. By addressing these issues, steps can be taken to enhance the working conditions and professional satisfaction of dental professionals, ultimately benefiting both the practitioners and their patients.

The dispersal potential of crown-of-thorns starfish (CoTS) larvae is important in understanding both the initiation and spread of population outbreaks, and is fundamentally dependent upon how long larvae can persist while still retaining the capacity to settle. This study quantified variation in larval survivorship and settlement rates for CoTS maintained at three different chlorophyll concentrations (0.1, 1.0 or 10.0 µg.L^-1), achieved by varying densities of single-celled flagellate phytoplankton, Proteomonas sulcata. Based on the larval starvation hypothesis we expected that low to moderate algal concentrations would significantly constrain both survival and settlement. CoTS larvae were successfully maintained for up to 50 days post-fertilization, but larval survival differed significantly between treatments. Survival was greatest at intermediate (1.0 µg.L^-1) chlorophyll concentrations, and lowest at highest (10.0 µg.L^-1) chlorophyll concentrations. Rates of settlement were also highest at intermediate (1.0 µg.L^-1) chlorophyll concentrations and peaked at 22 days post-fertilization. Peak settlement was delayed at low chlorophyll concentrations, probably reflective of delayed development, but there was no evidence of accelerated development at high chlorophyll concentrations. CoTS larvae were capable of settling 17-43 days post-fertilization, but under optimum conditions with intermediate chlorophyll concentrations, peak settlement occurred at 22 days post-fertilization. Moderate increases in nutrient concentrations and algal densities may increase the number of CoTS that effectively settle, but are unlikely to influence dispersal dynamics.

Transition zones are in the places on the track, with a change in the basic composition of the railway body. There are many sections with a sudden change in the stiffness of the structures built. When the trains are running, a longitudinal shock wave is created from the wheels, which hits these building objects with a higher stiffness and deforms the surroundings of these zones. The greatest attention should be paid mainly to the transition points from the fixed track to the classic track with a track bed, including objects of the railway substructure such as bridges, portals of tunnels, etc. As part of the research sections on the main corridor lines, a long-term inspection and monitoring was carried out with a continuous measurement system using the KRAB trolley. Height changes in the deflections of rails are evidence of their behavior. The measurements took place on a fixed track and a track with a ballast. Changes in the height jumps between the fixed railway track and the track with a gravel bed are significant and have been recorded since the tracks were put into operation. These certain height deflections allow designers to develop new, more durable construction designs.

Direct and indirect effects after mine operations cease must ideally be subject to perpetual monitoring routines in order to detect possible risks or avoid adverse effects on the surrounding ecosystems at an early stage. In this contribution, mining subsidence lakes created inside the nature reserve Kirchheller Heide and Hilsfeld Forest are subjected to analysis for a long-term monitoring scheme. For this purpose, we employ high-resolution unmanned aerial system (UAS)-based multispectral and thermal mapping tools to provide a fast, non-invasive and multitemporal environmental monitoring method. Specifically, we propose to monitor vegetation evolution through multispectral analysis, biotypes identification using machine learning algorithms, and water surface extent detection, together with their thermal behavior. The aim of this contribution is to present the proposed workflow and first results to establish a baseline for future analyses and subsequent surveys for longterm multi-temporal monitoring