Electricity load forecasting is a crucial undertaking within all the deregulated markets globally. In contemporary times, the transition from conventional electricity grids to Smart Grids constitutes an area where extensive research is conducted on a global scale. Among the research challenges, the investigation of Deep Transfer Learning (DTL) in the field of electricity load forecasting represents a fundamental effort that imparts generality to Artificial Intelligence applications, due to new capabilities, such as knowledge transfer and computational power reduction. In this paper a comprehensive study is conducted for day-ahead electricity load forecasting. For this purpose, three Sequence-to-Sequence (Seq2seq) Deep Learning (DL) models are used, namely the Multilayer Perceptron (MLP), the Convolutional Neural Network (CNN) and the Ensemble Learning Model (ELM), which is consisted of the weighted combination of the outputs of MLP and CNN models. Also, the study focuses on the development of different forecasting strategies based on DTL and emphasizing the way the datasets are trained and fine-tuning for higher forecasting accuracy. In order to implement the forecasting strategies using Deep Learning models, load datasets from three Greek islands, Rhodes, Lesvos, and Chios, are used. The main purpose is to apply DTL for day-ahead predictions (1-24 hours) for each month of the year for Chios dataset after training and fine-tuning the models using the datasets of the three islands in various combinations. After several trials, four DTL strategies are illustrated. In the first strategy (DTL Case 1), each of the three DL models is trained using only Lesvos dataset, while fine-tuning is performed on the dataset of Chios island, in order to create day-ahead predictions for Chios load. In the second strategy (DTL Case 2), data from both Lesvos and Rhodes concurrently are used for the DL model training period, and fine-tuning is performed on the data from Chios. The third DTL strategy (DTL Case 3) contains the training of the DL models using Lesvos dataset, and the testing period performed directly on the Chios dataset without fine-tuning. The fourth strategy is a Multi-task Deep Learning (MTDL) approach, which has been extensively studied in recent years. In MTDL, the three DL models are trained simultaneously on all three datasets and the final predictions are made on the unknown part of the dataset of Chios. In this paper, we explore the performance of DTL and compare the results with those produced with MTDL. The results demonstrated that DTL can be applied with high efficiency for day-ahead load forecasting. Specifically, the two cases with fine-tuning (DTL Case 1 and 2) outperformed MTDL in terms of load prediction accuracy. Regarding the DL models, all three exhibit very high prediction accuracy, especially in the two cases with fine-tuning. The ELM excels compared to the single models. More specifically, for conducting day-ahead predictions, it has been concluded that the MLP model presents best monthly forecasts with a MAPE of 6.24% and 6.01% for the first two cases, the CNN model presents best monthly forecasts with a MAPE of 5.57% and 5.60% respectively and the ELM model achieves best monthly forecasts with a MAPE of 5.29% and 5.31%, respectively, indicating the very high accuracy it can achieve.

Much research has been conducted to determine how hair regeneration is regulated, as this could provide therapeutic, cosmetic, and even psychological interventions for hair loss. The current study focused on the hair growth effect and effective utilization of fatty oil obtained from Bryde's whales through high-throughput DNA microarray approach in conjunction with immunohistochemical observations. The research also examined the mechanisms and factors involved in hair growth. In an experiment using female C57BL/6J mice, the vehicle control group (VC: propylene glycol: ethanol: water), the positive control group (MXD: 3% minoxidil), and the experimental group (WO: 20% Whale Oil) were topically applied to the back of the mouse. The results showed that 3% MXD and 20% WO were more effective than VC in promoting hair growth, especially 20% WO. Furthermore, in hematoxylin and eosin-stained skin tissue, an increase in the number of hair follicles and subcutaneous tissue thickness was observed with 20% WO. Whole-genome transcriptomic analysis also showed that 20% WO may have lower stress- and inflammation-related responses than 3% MXD. Therefore, whale oil can be expected to be used as a safe hair growth agent.

The search of DNA polymorphisms useful for the genetic improvement of dairy farm animals lasts more than 40 years with relevant findings in cattle for milk traits, where the best combination of alleles for dairy processing have been found in casein genes and in the DGAT1. Nowadays, similar results are not reached yet in river buffaloes despite advanced genomic technologies and accurate phenotype records are available. The aim of the present study was to investigate and validate in a larger buffalo population the effect on six milk traits of four single nucleotide polymorphisms (SNP) in the CSN1S1, CSN3, SCD and LPL genes, previously reported to be associated with or affect dairy traits in smaller populations often belonging to one farm. A total of 800 buffaloes were genotyped. Daily milk yield (dMY, kg), protein yield (dPY, kg) and fat yields (dFY, kg), fat and protein contents (dFP, % and dPP, %), somatic cell count (SCC, 103cell/ml) and urea (mg/dl) were individually recorded in each month for the whole lactation from 2010 to 2021. A total of 15,742 individual milk test day records (2,496 lactations) were available on 680 buffalo cows with 3.6±1.7 parity (from 1 to 13) and 6.1±1.2 test day records per lactation on average. Three out four SNP in CSN1S1, CSN3 and LPL were associated with at least one of analyzed traits. In particular, the CSN1S1 (AJ005430:c.578C>T) gave favorable associations with all yield traits (dMY, p=0.022; dPY, p=0.014 ; dFY, p=0.029) and SCS (p=0.032), whereas the CSN3 (HQ677596: c.536C>T) positively associated with SCS (p=0.005) and milk urea (p=0.04). Favorable effect on dMY (p=0.028), dFP (p=0.027) and dPP (p=0.050) were observed for the LPL. Conversely, SCD did not show any association with milk traits. This is the first example of confirmation study carried out in the Mediterranean river buffalo for genes of economic interest in dairy field and it represents a very important indication for the preselection of young bulls destined to breeding programs in the view of a more sustainable dairy production.

Melioidosis is an endemic infectious disease caused by Burkholderia pseudomallei bacteria, which contaminates soil and water. To better understand the environmental changes that have contributed to melioidosis outbreaks, this study used spatiotemporal analyses to clarify the distribution pattern of melioidosis and the relationship between melioidosis morbidity rate and local environmental indicators (land surface temperature, normalised difference vegetation index, normalised difference water index) and rainfall. A retrospective study was conducted from January 2013 to December 2022, covering data from 219 sub-districts, with each exhibiting varying morbidity rate of melioidosis on a monthly basis. Spatial autocorrelation was determined using local Moran’s I, and the relationship between melioidosis morbidity rate and the environmental indicators was evaluated using geographically weighted Poisson regression. The results revealed clustered spatiotemporal patterns of melioidosis morbidity rate across sub-districts, with hotspots predominantly observed in the northern region. Furthermore, we observed a range of coefficients for the environmental indicators, varying from negative to positive, which provided insights into their relative contributions to melioidosis in each local area and month. These findings highlight the presence of spatial heterogeneity driven by environmental indicators and underscore the importance of public health offices implementing targeted monitoring and surveillance strategies for melioidosis in different locations.

This research presents a comprehensive framework for efficiently generating forest fire datasets from Google Earth Engine data sources. The primary contribution of this work lies in providing a methodology to swiftly extract forest fire factors without the need for permissions or access to private datasets, rendering the dataset openly accessible and shared without barriers. Furthermore, given that the remote sensing data used is a global dataset, it can be applied in any region without restrictions. In this study, Peninsular Malaysia is chosen as a case study to demonstrate the framework's effectiveness. The generated dataset includes essential variables including the climate and environment, landcover, topography, and anthropogenic factors facilitating the analysis of fire occurrences. The methodology empowers data scientists, enabling them to leverage their analytical skills on the extracted dataset without requiring specialized remote sensing knowledge. Additionally, this study also showcases the adoption of large language models, specifically GPT-4 with the Noteable plugin, as a tool for conducting preliminary analyses on the generated dataset. Sample analyses reveal that several key features, including the KBDI, LST, PDSI, climate water deficit, and precipitation, significantly impact forest fire occurrences in Peninsular Malaysia. Despite the successful application of the GPT-4 with Noteable plugin, certain limitations and challenges are identified, highlighting the necessity for further validation of the tool's applicability and limitations. This study encourages future research to (1) adopt the proposed framework in other regions, (2) explore more detailed analyses encompassing all variables, and (3) leverage machine learning for advanced forecasting.

This Systematic Review examines studies focusing on tooth bleaching and its effect on healthy enamel or incipient caries and bacterial adhesion. The aim is to explore the impact of different bleaching agents on incipient caries lesions and healthy enamel. Randomized controlled trials, clinical trials, observational studies, and in vitro studies that compared at least two groups were included. A comprehensive search strategy was used to select studies from Pubmed and Scopus databases. Two evaluators performed data extraction, screening, and quality assessment independently. Only studies written in English were included. From 968 initial records, 28 studies were selected for a full-text evaluation. 7 studies were classified as cluster 1 (bacterial adherence on teeth), 12 studies as cluster 2 (no bacteria involved), 4 studies as cluster 3 (no teeth deployment), and 5 clinical studies were cluster 4. Of the selected studies, 6 (21.43%) supported increased bacterial attachment capacity and cariogenic dynamics, 4 (14.29%) decreased adhesion and cariogenic activity, 7 (25%) no difference, and 11 (39.28%) followed a differentiated methodological approach and could not be categorized. Due to different methodology strategies used in the studies of all clusters, the risk of bias was high. Thus, we cannot reach a confident conclusion.

Lactoperoxidase system (LPS) effect on quality of raw and pasteurized milk under real conditions along the dairy value chain in Ethiopia was evaluated. A total of 250 milk samples were collected from farmers, collectors, and factories. Experimental samples were LPS-activated of morning and overnight milk. The samples were tested with several chemical and microbiological tests such as total bacterial count (TBC), total coliform count (TCC) and Escherichia coli count (EC). Results indicated that all LPS-activated milk samples had a higher quality than all the control samples. For instance, both the morning and overnight farm milk samples had a mean TBCs of 5.79 log and 6.55 log cfu/ml which is significantly (p

Under the development mode of deep blending of emerging technologies, major projects are important for enhancing China's comprehensive national strength and independent innovation capability. Based on the social benefits of major projects, and considering the influence of reputation factors, an evolutionary game model composed of a general contractor and subcontractor of major projects is established. This paper studies the influence of various factors including the income distribution coefficient of collaborative innovation, and MATLAB simulation software is analyzed the influence of factors on an evolutionary path. The results show that a reasonable income distribution coefficient can promote the game behavior of both parties to the direction of active collaborative innovation; The reduction of innovation cost and the improvement of spillover technology absorption capacity can make innovation subjects tend to choose active collaborative innovation strategies. In addition, reputation loss above a specific threshold can effectively inhibit free-riding behavior and encourage innovation subjects to choose active collaborative innovation strategies. The research results provide reference for promoting major projects' technology innovation.

Sharding shows great potential for extending the blockchain. The current challenge facing sharded blockchain technology lies in addressing the extended transaction confirmation times caused by isolated states between shards and unbalanced transaction allocation strategies. These factors contribute to an increase in cross-shard transactions and disproportionate shard workload, ultimately resulting in indefinite confirmation delays for cross-shard transactions. A critical priority for sharded blockchain systems is to conduct a comprehensive qualitative analysis to better understand and mitigate the prolonged transaction confirmation times. We introduce a Product-Form Queue Network (PFQN) model to address the transaction confirmation time problem in sharded blockchains and incorporate a new confirmation queue to more accurately simulate the actual transaction confirmation process in the blockchain. In addition, we provide a detailed quantitative analysis of the relationship between network load, consensus efficiency, and security in sharded blockchains, laying a theoretical foundation for achieving robustness and efficiency in sharded blockchains. This research not only contributes to addressing the scalability issues in sharded blockchains but also offers a new perspective for future research directions.

Chymotrypsin from the digestive organs of bigfin reef squid, a major commercial squid species in Thailand, was purified to 41.27-fold with 5.74% yield by a sequential purification process including ammonium sulfate precipitation, size exclusion and ion exchange chromatography. According to SDS-PAGE, the molecular weight of purified chymotrypsin was 43 kDa. Native-PAGE analysis revealed a single band for this purified enzyme. Optimum pH and temperature for chymotrypsin activity of the purified enzyme were pH of 7.0 with a temperatures of 55°C. The purified chymotrypsin remained stable throughout a wide range of pH levels (6–11) and at relatively high temperature (50°C). It was significantly inhibited by PMSF and TPCK. The values of the kinetic constants Km and Kcat were found to be 1.33 mM and 31.46 s‒1, respectively. The purified chymotrypsin has the N-terminal amino acid IVGGQEATPGEWPWQAALQV. This study provided new information about the biochemical properties of pure chymotrypsin from bigfin reef squid, which is useful in the future investigation, aquaculture and application of bigfin reef squid.

Background/objectives: The health benefits of resistant starch are well known, but there have not been many studies available documenting the effect of basmati rice products containg resistant starch upon blood glucose level and lipid profile in vivo efficacy. Methods: Common cooking methods were used to prepare basmati rice products including two boiling methods viz. boiling 1 (boiling by absorption), boiling 2 (boiling in extra amount of water), frying and pressure cooking. The cooked rice were held at various temperatures and times: it was made fresh (T1), kept at room temperature (20–22°C) for 24 h (T2), kept at 4°C for 24 h (T3), and then reheated after being kept at 4°C for 24 h(T4). Next, the products' proximate composition, total dietary fibre (soluble and insoluble), resistant starch (RS), and In vitro starch digestion rate (rapidly and slowly digested starch) were examined. The effect of RS on blood glucose and lipid profile were measured in humans and rats. Histopathological study of liver and pancreas in rats were also observed. Results: The basmati rice prepared by boiling 1 and stored with T3 was found more effective to control blood glucose and lipid profile. Similarly in rats, the blood glucose level, cholesterol, triglycerides and LDL were reduced about 29.7, 37.9, 31.3 and 30.5% respectively, after consumption of basmsti rice prepared by boiling 1 and stored at T3. Conclusion: Rice products stored at 4⁰C have a high amount of resistant starh, insoluble dietary fibre, slowly digestible starch and low glycemic index. Thus helps to inhibit glycogen and lipid synthesis.

Simple Summary: The distribution of typical bacterial redox enzymes such as pyruvate-ferredoxin oxidoreductase (PFOR) in protozoa remains interestingly puzzling. Previous studies have demonstrated diverse cellular localizations of PFOR in some amitochondriate anaerobic protozoa. PFOR is of particular pharmacological importance because it catalyzes the reductive bio-activation of nitro-based prodrugs to cytotoxic radical metabolites. Metronidazole was developed primarily as an antiprotozoal agent against infections caused by Trichomonas vaginalis. However, its antimicrobial spectrum was subsequently expanded to cover anaerobic bacterial infections. It has been shown that mutations in the genes encoding PFOR result in inherent resistance of PFOR-possessing anaerobic protozoa and bacteria to nitro-based prodrugs. Deciphering the evolutionary history of PFOR is crucial in deepening our understanding of the evolution of anaerobic pathogens and unfold new approaches for drug discovery and targeting in pathogen chemotherapy. Abstract: The present frontrunners in the chemotherapy of infections caused by protozoa are nitro-based prodrugs that are selectively activated by PFOR-mediated redox reactions. This study seeks to analyze the distribution of PFOR in selected protozoa and bacteria by applying comparative bioinformatics approaches to test the hypothesis that PFOR was most likely acquired through horizontal gene transfer (HGT) from bacteria. Furthermore, to identify other genes that were putatively acquired using proteome-wide and gene expression analyses. A plausible explanation for the patchy occurrence of PFOR in protozoa is based on the hypothesis that bacteria are potential sources of genes that enhance optimal adaptation of protozoa in hostile environments. The exclusively expressed proteins obtained from Entamoeba histolytica and the putative gene donor, Desulfovibrio vulgaris, showed an over-expression of eleven genes involved in intermediary metabolism. If these results can be reproduced in other PFOR-possessing protozoa, it would provide a more validated evidence to support the horizontal transfer of pfor from bacteria.

A power factor correction (PFC) rectifier is compulsory for any electronic circuitry connected to the electrical grid. The majority of PFCs that are utilized are based on a step-up converter that supplies high DC voltage at its output terminal. Electric vehicle battery voltage varies from a few hundred to almost a thousand volts. Thus, an additional conversion step is obligatory when designing an all-brand universal charger. This paper presents a new type of front-end versatile step up / down three voltage level PFC. The rectifier can operate in continuous conduction mode or discontinuous conduction mode. First, the rectifier’s principle of operation is described, and then an innovative rectifier is analyzed for continuous and discontinuous conduction modes. Finally, the proposed theory is experimentally validated in a multiplier-less dual loop mode at discontinuous conduction modes. It was shown that although there is no multiplier use in the control circuitry, the power factor is near unity. It was revealed that the rectifier could swing the output voltage from 50 V to 900 V while the input voltage was 230 Vrms. The innovative topology suits any standard PFC rectifier, three-level voltage supplement, and dual-stage low-voltage power supply.

In order to achieve the elimination of the negative impacts of transport on road safety, the European Union is taking various measures resulting from its commitment to improve road safety. One of the instruments for achieving the objectives set is social legislation for the work of drivers in road freight and passenger transport. In line with the objective of improving the quality of working conditions for road transport drivers and road safety, the European Union applies Regulation (EC) No 561/2006 on the harmonisation of certain social legislation relating to road transport, which lays down rules on driving times, breaks and rest periods for drivers operating in road freight and passenger transport. The main objective of the paper is to assess the impact of social legislation on road transport safety by means of real research and to identify the factors influencing the violation of the legislation depending on the type of transports carried out in domestic or international road freight transport.

Daridorexant, as the first Dual Orexin Receptor Antagonist (DORA) marketed in Europe, offers a novel therapeutic approach to insomnia. However, data regarding its real-world safety are scarce. Thus, the aim of this study was to assess its safety profile using a large-scale pharma-covigilance database. Daridorexant-related Adverse Drug Reaction (ADR) reports from the FDA Adverse Event Reporting System were scrutinized, and ADRs were selected using reporting odds ratio (ROR) as a measure of disproportionality. Frequencies of events related to daridorexant were compared to all other drugs (reference group, RG1) and only to other DORAs (RG2). Only significant disproportionalities to both RGs were evaluated in-depth. A total of 845 dari-dorexant-related reports were selected; nightmares (n = 146; Dari vs. RG1: ROR = 113.74; 95%CI[95.13, 136]; Dari vs. RG2: ROR = 2.35; 95CI%[1.93, 2.85]), depression (n = 22; Dari vs. RG1: 2.13; [1.39, 3.25]; Dari vs. RG2: ROR = 2.31; 95CI%[1.45, 3.67]), and hangover (n = 20; Dari vs. RG1: ROR = 127.92; 95CI%[81.98, 199.62]; Dari vs. RG2: 3.38; [2.04, 5.61]) were considered as safety signals. These data provide valuable insights into the real-world safety profile of dari-dorexant, supporting the existence of safety signals related to nightmares, depression, and hang-over.

Ensuring access to water, sanitation, and hygiene (WASH) facilities, coupled with behavior change education in schools, is fundamental for fostering a conducive learning environment and promoting principles of inclusion, dignity, and equality. This study focuses on 12 primary schools in Anápolis, Brazil, encompassing 4,394 students and 248 teachers. WASH assessments were conducted through a questionnaire, observation of water and sanitation facilities and structures, and microbiological analysis. Over the period 2018 to 2020, the proportion of schools with safely managed drinking water surged from 42% to 92%. However, sanitation conditions in the schools were categorized as a basic level, with hygiene services rated as limited in 92% of the schools due to the absence of soap. While this study reveals that Anápolis schools generally align with WASH guidelines for basic/advanced drinking water services, there is a crucial need for enhancements in both hardware and software facilities to address sanitation and hygiene challenges.

In his best-selling book An Introduction to Probability Theory and its Applications, W. Feller established a way of ending the St. Petersburg Paradox by the introduction of an entrance fee, and provided it for the case in which the game is played with a fair coin. A natural generalization of his method is to establish the entrance fee for the case in which the probability of head is θ (0 < θ < 1/2). The deduction of those fees is the main result of Section 2. We then propose a Bayesian approach to the problem. When the probability of head is θ (1/2 < θ < 1) the expected gain of the St. Petersburg Game is finite, therefore there is no paradox. However, if one takes θ as a random variable assuming values in (1/2,1) the paradox may hold, what is counter-intuitive. On Section 3 we determine a necessary and sufficient condition for the absence of paradox on the Bayesian approach and on Section 4 we establish the entrance fee for the case in which θ is uniformly distributed in (1/2,1), for in this case there is paradox.

Arylmagnesium and -calcium reagents are easily accessible, however, ether degradation processes limit the storability especially of the calcium-based heavy Grignard reagents. Ortho-bound substituents with phosphanyl donor sites usually block available coordination sites and stabilize such complexes. The reaction of bromo-2,6-bis(diphenylphosphanylmethyl)benzene (1a) with magnesium in tetrahydrofuran yields [Mg{C₆H₃-2,6-(CH₂PPh₂)₂}₂] (2) after recrystallization from 1,2-dimethoxyethane. However, the similarly performed reduction of bromo- (1a) and iodo-2,6-bis(diphenylphosphanylmethyl)benzene (1b) with calcium leads to ether cleavage and subsequent degradation products. α-Deprotonation of THF yields 1,3-bis(diphenylphosphanylmethyl)benzene. Furthermore, the insoluble THF adducts of dimeric calcium diphenylphosphinate halides, [(thf)₃Ca(X)(µ-O₂PPh₂)]₂ [X = Br (3a), I (3b)], precipitate verifying ether decomposition and cleavage of P-C bonds. Ether adducts of calcium halides [such as [(dme)₂(thf)CaBr₂] (4)] form supporting the initial Grignard reaction and a subsequent Schlenk-type dismutation reaction.

This paper investigates the feasibility of a backend design for real-time, multiple-channel processing digital phased array system, particularly for high-performance embedded computing platforms constructed of using general purpose digital signal processors. Frist, we obtained the lab-scale backend performance benchmark from simulating beamforming, pulse compression, and Doppler filtering based on MicroTCA chassis using Serial RapidIO protocol in backplane communication. Next, a field-scale demonstrator of a multifunctional phased array radar is emulated by using the similar configuration. Interestingly, the performance of a barebone design is compared to that of emerging tools that systematically take advantage of parallelism and multicore capabilities, including Open Computing Language.

Tropical cyclones, hurricanes and typhoons (“cyclones”) threaten the lives and livelihoods of many millions of people. The magnitude of this threat justifies scrutiny of all potential mitigation strategies. Here we consider a neglected factor: forests. Forests may influence storm formation, intensity, and behaviour through interactions involving temperature, friction, moisture and aerosols. Understanding these relationships could guide cyclone mitigation and preparedness. With global deforestation continuing and reforestation efforts expanding, the relationships between forests and cyclones are not simply academic—it's a critical consideration for climate adaptation, disaster risk reduction, and sustainable development. Here we show that, despite major unknowns and uncertainties, forest conservation and expansion are likely to reduce cyclone frequency and severity.

Public-Private Partnerships (P3 or PPPs) have been utilized and studied more frequently over the past couple of decades for both infrastructure projects and building development projects. Based upon the records of the outcomes of these projects there is a plethora of data that demonstrates the benefits and challenges that this delivery method poses. As the name suggests, these partnerships allow for public goals to become realized while also providing opportunities for the private sector to gain business success. These two often divergent interests are finding mutual benefit but the process of compromises also comes with some disadvantages that should be understood in order to make decision of whether the risk/reward equation works for all stakeholders. In particular, this paper will focus on how PPPs affect the construction aspects of projects and will assert how to understand the risks and evaluate the benefits from a construction perspective.

Benveniste’s experiments – known in the lay press as the “water memory” phenomenon – are generally considered to be a closed case. However, the amount of data generated by twenty years of well-conducted experiments prevents closing the file so simply. An issue, which has been little highlighted so far, merits to be emphasized. Indeed, if Benveniste failed to persuade his peers of the value of his experiments, it was mainly because of a stumbling block, namely the difficulty of convincingly proving the causal relationship between the supposed cause (“informed water”) and the experimental outcomes in different biological models. To progress in the understanding of this phenomenon, we abandon the idea of any role of water in these experiments (“water memory” and its avatars). In other words, we assume that “control” and “test” conditions to be evaluated were physically identical and differed only by their respective designations. We show in this article how simple probabilistic considerations allow to build a model that accounts for all aspects of Benveniste’s experiments. In this model based on probability amplitudes, constructive and destructive interferences emerge – or not – according to the experimental context. The recording of a statistical regularity shapes the intertwined whole constituted by the probability amplitudes of the states of the experimenter’s cognitive structures and of the experimental system. This model provides an alternative explanation to Benveniste’s experiments where water plays no role and where the place of the experimenter is central.

Background. Gastrointestinal (GI) distress is prevalent and often persistent among cancer survivors, impacting their quality of life, nutrition, daily function, and mortality. GI health screening is important to prevent and manage this distress. However, accurate classification methods for GI health remain unexplored. We aimed to develop machine learning (ML) models to classify GI health status (better vs. worse) by incorporating biological aging and social determinants of health (SDOH) indicators in cancer survivors. Methods. We included 645 adult cancer survivors from the 1999-2002 NHANES survey. Using training and test datasets, we employed six ML models to classify GI health conditions (better vs. worse). These models incorporated leukocyte telomere length (TL), SDOH, and demographic/clinical data. Results. Among the ML models, the random forest (RF) performed the best, achieving a high area under the curve (AUC = 0.98) in the training dataset. The gradient boosting machine (GBM) demonstrated excellent classification performance with a high AUC (0.80) in the test dataset. TL, several socio-economic factors, cancer risk behaviors (including lifestyle choices), and inflammatory markers were associated with GI health. The most significant input features for better GI health in our ML models were longer TL and an annual household income above the poverty level, followed by routine physical activity, low white blood cell counts, and food security. Conclusions. Our findings provide valuable insights into classifying and identifying risk factors related to GI health, including biological aging and SDOH indicators. To enhance model predictability, further longitudinal studies and external clinical validations are necessary.

Object: Due to the fact that glioma surgery requires manipulation of the brain parenchyma and the expression of inflammatory mediators, there is often a possibility of central nervous system (CNS) infection occurring after surgery. Previous studies on CNS infections related to neurosurgery have uniformly explored the risk factors for CNS infections in all neurosurgery surgeries that require craniotomy, but have not explored the risk factors and clinical characteristics of CNS infections after glioma resection. Methods: We included patients who underwent glioma resection from January 2015 to March 2023, systematically recorded population characteristics, clinical, surgical, laboratory and survival data, analyzed high-risk factors for postoperative CNS infections, summarized cerebrospinal fluid characteristics, antibiotic use, and explored whether CNS infections affects the long-term prognosis of glioma patients after surgery. Results:All 337 patients underwent glioma resection, and 61 patients (18.1%) developed CNS infections after surgery. Ventricle Opening, post-op other systemic infections, post-op maximum cavity diameter, and peripheral blood Monocyte% are independent risk factors for postoperative CNS infections. The median protein content in cerebrospinal fluid of patients with CNS infections is 1.73g/L ([IQR] 1.03-3.06), the median glucose content is 2.7mmol/L ([IQR] 1.90-3.70), and the median WBC is 1478×106cells/L ([IQR] 467-4204.25×106), with a median percentage of multinucleated cells of 84.1% ([IQR] 74.55% -90.83%). Meropenem and Vancomycin are the most commonly used antibiotics, with an average usage time of 7.79 days and 8.41 days, respectively. Survival analysis suggests that the occurrence of CNS infections does not affect the long-term prognosis of glioma patients after surgery. Conclusions: This study separately explored the risk factors for CNS infections in patients with glioma after surgery, instead of all diseases which need craniotomy，and summarized their cerebrospinal fluid characteristics and antibiotic use. Although CNS infection is only one of the possible complications during the treatment of gliomas, we believe that this will make a certain contribution to neurosurgeons' individualized prevention, diagnosis, and treatment of patients in the diagnosis and treatment of gliomas.

Handmade papers, as carriers of paper-based cultural relics, have played a crucial role in the development of human culture, knowledge, and civilization. Understanding the intricate relationship between the structural properties and degradation mechanisms of handmade papers is essential for the conservation of historical documents. In this work, an artificial dry-heat accelerated ageing method was used to investigate the interplay between the mechanical properties of paper, the degree of polymerization (DP) of cellulose, chemical composition, hydrogen bond strength, crystallinity, and degree of hornification. The results show that the mechanical properties of handmade bamboo paper exhibited a first plateau region, a rapid decline region, and sometimes a second plateau region. A critical point in the mechanical properties of the paper occurs when the cellulose DP decreases to a range of 400-600, signifying a shift from the initial plateau to a sharp decline phase. The strengthening of intermolecular hydrogen bonds and the hornification process help counteract the embrittlement of fibers caused by cellulose chain scission due to DP reduction. A secondary plateau emerges when the DP is smaller than 400, cellulose degradation is slow, and the component content, hydrogen bond strength, crystallinity, and degree of hornification reach a secondary plateau.

Breast implant surgery has evolved significantly, yet challenges such as capsular contracture remain a persistent concern. This review presents an in-depth analysis of recent advancements in understanding the immune mechanisms and clinical implications associated with breast implants. The article systematically examines the complex interplay between immune responses and capsular fibrosis, emphasizing the pathophysiological mechanisms of inflammation in the etiology of this fibrotic response. It discusses innovations in biomaterial science, including the development of novel anti-biofilm coatings and immunomodulatory surfaces designed to enhance implant integration and minimize complications. Emphasis is placed on personalized risk assessment strategies, leveraging molecular insights to tailor interventions and improve patient outcomes. Emerging therapeutic targets, advancements in surgical techniques, and the refinement of post-operative care are also explored. Despite notable progress, challenges such as variability in immune responses, long-term efficacy of new interventions, and ethical considerations remain. Future research directions are identified, focusing on personalized medicine, advanced biomaterials, and bridging preclinical findings with clinical applications. As we advance from bench to bedside, this review illuminates the path forward, where interdisciplinary collaboration and continued inquiry weave together to enhance the art and science of breast implant surgery, transforming patient care into a realm of precision and excellence.

Training schedule is a factor that influences sports performance optimization. In a sport like soccer, there is often significant disparity in training schedules among different teams within the same club, without considering whether this may affect players' performance. The aim of this study was to describe differences in nutrient intake and body composition in elite youth soccer players from the Spanish league with different training schedules (morning and evening). A cross-sectional study was conducted to determine differences in anthropometric variables and dietary assessment in a sample of Spanish young soccer players. A total of 41 players participated in this study. After comparing the groups according to their training schedule, no differences were observed in body composition between both groups; the evening-night training group showed higher consumption of lipids and saturated fats. In summary, more experimental studies are needed to determine the effects on various health and performance parameters of different training schedules in young population.

The samples from lunar farside have great significance for the study of the Moon, and even the solar system. Chang’e-6 landed successfully on the southern mare of the Apollo basin and returned ~2 kg samples from lunar farside. To provide a better understanding for the background of the returned samples, we conducted detailed crater size-frequency distribution (CSFD) measurements in the Chang’e-6 landing region, the southern mare of the Apollo basin. The southern mare is divided into western mare (W region) and eastern mare (E region), and then subdivided into five sub-units (W1, W2, W3, W4, W5) and three units (E1, E2, E3), respectively, according to the elevation, Ti and Fe abundances. Within the W2 and W5 region, more detailed sub-units were divided. The results show that the southern mare generally have two epochs, one of the Imbrian period and the other of the Eratothenian period. The basalt eruption lasted for ~1.7 Ga, from 3.28 Ga of the eastern mare to 1.54 Ga of the western mare. W region is younger than E region, while the three units of E region has an age of ~3.2 Ga. The ages of the western mare basalts range from 2.98 Ga to 1.54 Ga, lasting for 1.4 Ga. It’s worth noting that the age of the basalt at the Chang’e-6 sampling site is ~1.68 Ga, indicating the samples returned may include components with this very young age.

Cleft lip and palate are the most common congenital craniofacial anomalies. The etiology of this condition is unclear. The overall incidence of cleft lip and palate is 1/700. Prenatal diagnosis of cleft lip by 3D ultrasound is possible in more than 70% of cases, while it is less effective for cleft palate. There are several classifications of cleft lip and palate that were proposed over the years, however, only few have found clinical application, with none of them generally accepted as most effective and understandable. Allori et al. presented classification of a cleft lip and palate which is comprehensive and uniform, and it can precisely define the vast majority of the clefts, thus enabling easier communication between the health workers during their everyday practice. In this paper, we compared the accuracy of preoperative diagnoses compared to intraoperative diagnoses according to Kernahan and Stark classification from 1958, and these diagnoses were converted according to the Allori et al. classification of cleft lip and palate. Classification of cleft lip and palate presented by Allori et al. is clear, easy to understand, and it can be successful tool in studying the epidemiology of clefts.

Accurate assessment of shale gas reserves hinges on a detailed characterization of gas and water distribution within shale reservoirs. Despite its importance, the nanoscale behavior of water and methane in deep shale formations, especially under elevated temperatures and pressures, remains poorly understood. This study proposes a novel molecular modeling approach to represent the complex nanocomposite porous media found in deep shale matrices. Leveraging quantitative data from experimental analyses of shale pore composition, we developed a molecular model that accurately reflects the intricate pore-slit structure within a composite of kerogen and illite, common constituents of shale. Employing a hybrid grand canonical Monte Carlo and molecular dynamics simulation technique, we investigated the micro-scale distribution and preferential adsorption sites of water and methane within the shale matrix. Our research further elucidates the impact of water on the pore structure of shale and delineates the co-occurrence patterns of water and methane. The simulations reveal that water and methane share similar adsorption preferences on kerogen surfaces, while methane does not exhibit specific adsorption preferences on water-bearing illite. We also find that the presence of water significantly alters the illite pore space, leading to a reduction in larger pore volumes and a concomitant increase in smaller pores. The decrease in methane content with increasing water content is more pronounced in the shrinkage cracks compared to the kerogen matrix pores and is particularly notable in the macropores of illite. The findings underscore the differential sensitivity of methane content to water levels across various shale pore types. These insights contribute to a deeper theoretical understanding of gas and water distribution mechanisms in deep shale reservoirs, offering valuable support for the evaluation of deep shale gas resource potential.

Adhesive-invasive E. coli have been suggested to be associated with the development of Crohn's disease (CD). It is assumed that they can provoke the onset of the inflammatory process as a result of the invasion of intestinal epithelial cells, and then, due to survival inside macrophages, stimulate chronic inflammation and the development of granuloma. In previous reports, we have shown that passage of the СD isolate ZvL2 on minimal medium M9 supplemented with sodium propionate (PA) as a carbon source stimulates, and with glucose - inhibits the adherent-invasive properties and the ability to survive in macrophages. This effect was reversible and not observed for the laboratory strain K12 MG1655. We were able to compare the isogenic strain AIEС in two phenotypes - virulent (ZvL2-PA) and non-virulent (ZvL2-GLU). We showed that, unlike ZvL2-GLU, the ZvL2-PA activates the production of ROS and cytokines when interacting with neutrophils. The laboratory strain does not cause a similar effect. Differences in neutrophil NADH-oxidase activation and ζ potential for ZvL2-GLU and ZvL2-PA are associated with changes in the abundance of membrane proteins. Using differential 2D electrophoresis and LC-MS, we identified membrane proteins that may be associated with the activation of the virulence properties of the СD isolate ZvL2.

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/Objectives: Conventional surgery gland using the naked eye remains the standard for submandibular gland resection. Owing to its excellent automatic focus and high magnification, the ORBEYE 3D system introduces precise submandibular resection with less stress. Therefore, we examined the usefulness of the exoscope in submandibular gland resection for the first time. Methods: This retrospective study enrolled 12 patients who underwent submandibular gland resection using an ORBEYE exoscope at the Department of Head and Neck Surgery and Otorhinolaryngology at Kansai Medical University from April 2021 to March 2024. Surgical outcomes were retrospectively reviewed. Results: The mean age of the 12 patients (six females and six males) was 58.5 years (23–83 years). The final histopathology showed pleomorphic adenoma in eight cases, non-sebaceous-type lymphadenoma and carcinoma ex pleomorphic adenoma in one case each, and sialolithiasis with chronic inflammation in two cases. We performed facial artery and vein sparing in all cases except one in which level I neck dissection, including the submandibular gland, was performed. In all cases, we identified the marginal mandibular branches of the facial, hypoglossal, and lingual nerves, as well as the submandibular duct. No postoperative complications occurred in any patient. The mean operative time was 104 min (80–129 min). The mean blood volume lost was 20 mL (5–43 mL). Conclusions: Using ORBEYE in submandibular gland resection will contribute to preserving the mandibular marginal branch of the facial and lingual nerves and the facial artery and vein, and visualizing the submandibular duct, which are important structures surrounding the submandibular gland.

Systemic Lupus Erythematosus (lupus) and B-cell lymphoma (lymphoma) are serious diseases. Lupus and lymphoma co-occur at higher-than-expected rates and primarily depend on B-cells for their pathology, implicating shared inflammation-related B-cell molecular mechanisms as a potential cause of co-occurrence. We consequently implemented a novel Immune Imbalance Transcriptomics (IIT) algorithm and applied IIT to lupus, lymphoma, and healthy B-cell RNA-seq data to find shared- and contrasting mechanisms potentially targetable for treatment. We observed 8,562 genes significantly dysregulated in both lupus and lymphoma. Of those genes, we found 5,335 to have a significant immune imbalance, defined as significant dysregulation by both diseases, as determined by IIT. Gene Ontology (GO) term and pathway enrichment of IIT genes yielded immune-related “Neutrophil Degranulation” and “Adaptive Immune System”, validating that the IIT algorithm isolates biologically relevant genes in immunity and inflammation. We found that 389 IIT gene products are drug-targetable with established or repurposed drugs. Among our results, we found 40 known and 349 novel lupus targets, along with 151 known and 238 novel lymphoma targets. Known disease drug targets in our IIT results further validate that IIT isolates genes with disease-relevant mechanisms. We anticipate the IIT algorithm and shared and contrasting gene mechanisms uncovered here will contribute to the development of immune-related therapeutic options for lupus and lymphoma patients.

We propose and experimentally realize a scheme of the optical nonreciprocity (ONR) using degenerate two-level atoms embedded in an optical ring cavity. For the degenerate transition Fg=4→Fe=3, we first study the cavity-transmission property in different coupling field, and verify that within the strong-coupling regime, the single-dark-state peak formed by electromagnetically induced transparency (EIT) shows ONR. Qualitative theoretical analysis shows that the stable ground-state Zeeman coherence is necessary for intracavity EIT. However, due to the frequency degeneracy, the large Rabi frequency of counter-propagating coupling field can reduce the number of effective atoms and weaken the strong-coupling of the atom-cavity, which determines that ONR based on intracavity EIT occurs only at weaker probe intensity. Furthermore, the ONR transmission with high contrast, linewidth-narrowed and broadband is experimentally demonstrated.

It is an utmost importance to characterize drug candidates as early in the development pipeline as possible. Appropriate application of the emerging high throughput analytical techniques unlocks the opportunities to obtain experimental data for in vitro absorption, distribution, metabolism and elimination (ADME) profiling of large compound libraries which is crucial for selection of lead compounds. In an usual scenario, only one drug candidate will be selected from thousands of early compounds based on several stability and screening results. A high to medium throughput screening approaches could significantly accelerates the subsequent research and production phases. Traditionally, the analysis of metabolic stability assays heavily relies on high throughput LC-MS/MS techniques to meet with the lead profiling demands. In this study presented an innovative experimental approach that can offer a refreshing alternative. Laser Assisted Rapid Evaporative Ionization Mass Spectrometry (LA-REIMS) is a quick and efficient method for characterizing complex biological samples without laborious sample preparation and chemical separation. Therefore, using an automated LA-REIMS well plate reader as fast as 8 seconds per sample, we assessed the oxidative metabolic stability of active agents using biomimetic metalloporphyrin-based oxidative model reactions at various pH for commercially available drug substances and compared stability measurements with traditional HPLC-DAD-MS results.

Objective. To test the hypothesis that a session of unilateral tSMS over the dominant primary motor cortex (M1) in healthy subjects produces a transient decrease in manual dexterity. Methods. A triple-blinded randomized control trial was conducted in 40 healthy participants who were allocated to real- or sham-tSMS group. Each participant underwent one session of tSMS and were assessed before, immediately after, 15 minutes, and 40 minutes after stimulation. Outcome measures were Finger Tapping Test (FTT), 5-seconds FTT, nine Hole Peg Test, and the hand grip assessment. Results: Significant differences were found between groups 15 minutes after stimulation in favor of the tSMS group in the FTT (2.2 ± 0.99; CI= .18-4.22; d= .84p=.034), and 5-second FTT (4.2 ± 1.98; CI= .199-8.2, d= .68; p=.04). In the intragroup analysis, a significantly lower number of taps 15 minutes after stimulation was observed in sham group (3.3 ± 1.01; CI= .47-6.13; d= .42; p=.015), but not in the real stimulation group. Conclusion: A unilateral session of tSMS in the M1 of the dominant hemisphere of healthy individuals does not reduce manual dexterity or grip strength. This technique could have benefits on the motor performance of the arm contralateral to the stimulated motor cortex

Danyore Valley area is a new prospect of copper-gold mineralization in the Gilgit-Baltistan province, Kohistan terrane, northern Pakistan. The mineralization is Cu-Au vein-type, localized within quartz veins and controlled by a fracture system mainly trending NW and NE. The host units belong to the Ladakh-Kohistan arc terrane, which covers northern Pakistan and north-western India and mainly comprises Precambrian basement units, Paleozoic to Cenozoic magmatic rocks, and sedimentary strata. The mineralized wall rocks consist of Mesozoic gabbro and diorite, which have undergone an intensive hydrothermal alteration. The study area, Danyore Valley, has yet to be explored. The geological background and mineralization type in literature are scarce. Moreover, the tectonic setting, petrogenesis, age, and magmatic evolution of the gabbro-diorite hosting unit still need to be better understood. Furthermore, the sources of metals and mineralized fluids and the types of mineralization and alteration are also unexplored. This research's contribution presents the field investigation, microscopic observations, whole rock geochemistry (major, trace, and REE), mineral analysis (EPMA), in situ LA–ICP–MS zircon U–Pb age dating, and zircon trace elements data for Danyore Valley Cu-Au prospect of Kohistan Batholith. The current research work's objectives are to (a) constrain the emplacement ages of the Danyore Valley host rocks, (b) determine the petrogenesis and tectonic environment of the gabbro-diorite wall rocks, and (c) identify the mineralization style and alteration patterns of Cu-Au occurrences. The U-Pb isotopic data of studied zircons from Danyore Valley diorite specimens yielded concordia ages from 111.60 ± 0.90 Ma to 112.18 ± 0.74 Ma. Correspondingly, the gabbro rock sample displayed a concordia age of 110.21 ± 0.99 Ma, indicating the crystallization time of the host bodies is mainly the early cretaceous period (∼110 Ma). The findings of this study reveal that the calc-alkaline affinity and arc-like geochemical characteristics of the gabbro and diorite rocks have been characterized by a significant enrichment in large-ion lithophile elements and an apparent depletion in high-field strength elements. The parent magma probably originated from a partial melting process of mantle depletion, and geochemical traits are characteristic of magmas associated with subduction zones. The Danyore Valley area of Kohistan terrane is defined by the existence of several mineralized quartz veins, which are mainly sulfide assemblages. The sulfide ore is mainly comprised of chalcopyrite, pyrite, and bornite, with a smaller amount of covellite and sphalerite and significant traces of gold, which are distributed mainly in sulfides. Copper and gold mineralization of Danyore Valley is associated with phyllic, propylitic, and carbonatization alteration assemblages. Metal-rich quartz veins exhibit a spatial correlation with diorite and gabbro rocks. The discovery of several surface Cu-Au vein-type mineralized areas accompanying outcrops of copper supergene enrichment at the Danyore Valley prospect is significant evidence (predictor patterns) of porphyry-style deposits in the Gilgit district, Kohistan terrane, northern Pakistan. This work also advocates the importance of the Danyore Valley prospect and Kohistan Batholith region for further detailed geological studies.

The silver fir (Abies alba Mill.) is among the most valuable conifers in Europe for ecological and economic reasons. In the course of history, primarily in the 20th century, its share in stands has been declining due to ill-suited management practices, especially clear-cut management, air pollution, and wildlife-induced damage. Based on recent knowledge of fir ecology and population dynamics, small-scale shelterwood and selection management have been introduced in fir stands, which have also stabilized them. Fir is an essential species for maintaining high stability and biodiversity, especially on planosols and in waterlogged habitats. Due to its shade tolerance and environmental flexibility, particularly at higher altitudes, it can coexist very well with many tree species in mixtures, which can increase the productive potential of stands. It can form stands of heterogeneous structure, ranging from single to multi-layer to selection. For its successful natural regeneration, it is essential to reduce cloven-hoofed game and thus prevent bud browsing damage. On the other hand, fir is a species relatively resistant to bark stripping and the spread of secondary rot compared to Norway spruce (Picea abies [L.] Karst.). During global climate change, fir is expected to shift to higher elevations with sufficient precipitation, while in the southern part of its natural range or at lower elevations, outside water-influenced habitats, it is likely to decline. This paper essentially reviews the description and distribution of the species, its ecological requirements, threats and diseases, habitat and stand conditions, and close-to-nature forest management practices with emphasis on ongoing climate change.

Small interfering RNA (siRNA) holds significant therapeutic potential by silencing target genes through RNA interference. Current clinical applications of siRNA have been primarily limited to liver diseases, while achievements in delivery methods are expanding its applications to various organs, including the lungs. Cholesterol-conjugated siRNA emerges as a promising delivery approach due to its low toxicity and high efficiency. This study focuses on developing a cholesterol-conjugated anti-Il6 siRNA and the evaluation of its potency for the potential treatment of inflammatory diseases using the example of acute lung injury (ALI). The biological activities of different Il6-targeted siRNAs containing chemical modifications were evaluated in J774 cells in vitro. The lead cholesterol-conjugated anti-Il6 siRNA after intranasal instillation demonstrated dose-dependent therapeutic effects in a mouse model of ALI induced by lipopolysaccharide (LPS). The treatment significantly reduced Il6 mRNA levels, inflammatory cell infiltration, and the severity of lung inflammation. IL6 silencing by cholesterol-conjugated siRNA proves to be a promising strategy for treating inflammatory diseases, with potential applications beyond the lungs.

Fungal infections caused by Candida spp. are responsible for high hospital morbidity and mortality rates. Therefore, there is a continuous search for new antifungal medicines, particularly ones with anti-Candida activity. This review analyzed articles published between 2002 and 2023 considering the anti-Candida activity of chemical compounds identified or isolated in plants of the Anacardiaceae family. In addition, the in-silico prediction of the isolated compounds described was performed. The analysis of 35 studies showed that extracts, essential oils, and compounds from the anti-Candida activity were frequently determined in vitro using the minimum inhibitory concentration (MIC). The most commonly tested species were Candida albicans, C. tropicalis, C. parapsilosis, C. glabrata, C. krusei, and C. guilliermondii, respectively. Essential oils were the most used form (37% of the studies). The isolated compounds with antifungal effects include cardanol, estragole, trans-anethole, β-caryophyllene, myrcene, catechin-3-o-rhamnoside, β-sitosterol-3-O-glucoside, 24Z-isomasticadienolic acid, oleanolic acid, and oleanolic aldehyde. The in-silico evaluation of those isolated compounds revealed the compounds' drug-likeness and possible antifungal activity. However, some of them showed high toxicity. In conclusion, compounds from the Anacardiaceae family show promise for developing new therapeutic antifungal drugs, especially in combination with conventional antifungals.

Neonatal mortality remains a public health concern and timely identification and prompt intervention in the delivery room could improve the outcome in neonatal morbidity and mortality. We performed a retrospective study to help us finding the profile of the high-risk newborn regarding the need for NICU admission, necessary to establish a protocol regarding the mobilization of human and material resources for the urgent management of these situations. All deliveries and neonates born in Maternity of Bihor County Emergency Clinical Hospital from Romania were reviewed, including relevant maternal, foetal and perinatal data to identify risk factors that result in birth of newborns needing resuscitation at birth between 2012-2019. The number of births showed a downward trend but around 90% of the births were on term. The incidence of neonatal emergencies is increasing, the most frequently were respiratory, sepsis and other infections, cardiovascular emergencies, and extreme prematurity. It is noted that in 2021 the incidence of these neurological emergencies increased by three times compared to previous years. The neonatal and maternal risk factors associated with admission to the NICU were mother's age over 35 years, low level of education, second/more gestation, weight under 2500 g, Apgar score under 7, premature rupture of membranes, macrosomia and mother's infectious pathology. Accurate identification of risk factors and anticipation at the birth of a high-risk neonate would result in adequate preparation and prompt resuscitation of neonates who need some level of intervention and thus, reducing neonatal morbidity and mortality.

Abstract: Lipodystrophies (LDs) are rare, complex disorders of the adipose tissue characterized by selective fat loss, altered adipokines profile and metabolic impairment. Sirtuins (SIRTs) are class III NAD+-dependent histone-deacetylases linked to fat metabolism. SIRT1 plays a critical role in metabolic health by deacetylating target proteins in tissues including liver, muscle and adipose tissue. Circulating SIRT1 levels have been found to be reduced in obesity while increased in anorexia nervosa and in patients experiencing weight loss. We evaluated circulating SIRT1 levels in relation to fat amount in 32 lipodystrophic patients affected by congenital or acquired LDs compared to non-LD subjects (24 with anorexia nervosa, 22 normal weight and 24 with obe-sity). SIRT1 serum levels were higher in LDs as compared with normal weight subjects (mean ± SEM: 4.17 ± 0.48 vs. 2.59 ± 0.20 ng/mL) or subjects with obesity (1.7 ± 0.39 ng/mL), whereas they were close to those measured in anorexia nervosa (3.44 ± 0.46 ng/mL). Our findings show that within the LD group there was no relationship between SIRT1 levels and the amount of body fat. The mechanisms responsible for secretion and regulation of SIRT1 in LD deserve further investi-gation.

Populational aging is marked by chronic non-communicable diseases, such as metabolic syndrome (MetS). IL-10 and IL-1β are pleiotropic cytokines with multiple biological effects linked to metabolic disorders. This cross-sectional study assessed 193 participants' IL-10 and IL-1β serum levels regarding their role in developing MetS, clinical characteristics, and their IL1B rs1143627 and IL10 rs1800890 variants' genotype frequencies in a population over 60. IL-10 levels correlated weakly with HDL levels and fat mass and inversely with triglycerides, glucose, glycated hemoglobin, and estimated average blood glucose levels. IL-10 levels were also indirectly influenced by the patient's T2DM duration, lean mass amount, and bone mineral content. Participants with altered HDL, elevated serum glucose, raised HbA1c levels, or those over 80 had reduced serum IL-10 levels compared to those with normal levels or other age groups, respectively. Women also had higher serum IL-10 levels than men. Dissimilarity, IL-1β levels correlated directly only with the number of total leukocytes and segmented neutrophils, showing only significant variations with self-reported alcohol consumption. Our study also found that those with the IL10 AA genotype (lower IL-10 levels) had a significantly higher risk of developing MetS. These findings may help direct future research and more targeted therapeutic approaches in older adults.

This study was designed for the first time to improve phenolic yield and antioxidant activity of ultrasonic-assisted extraction from Acer truncatum leaves (ATL) using response surface methodology, and phenolic composition in ATL extracted under the optimized condition were characterized by UPLC-QTOF-MS/MS. Solvent and extraction time were selected based on preliminary experiments, and a four-factors-three-levels central composite design was conducted to optimize solvent concentration (X₁), material-to-liquid ratio (X₂), ultrasonic temperature (X₃) and power (X₄) for an optimal total phenol yield (Y₁) and DPPH• antioxidant activity (Y₂). The results showed that the optimal combination was ethanol: water (v:v) 66.21%, material-to-liquid ratio 1:15.31 g/mL, ultrasonic temperature 60 °C, power 267.30 W, and time 30 min with three extractions, giving a maximal total phenol yield of 7593.62 mg gallic acid equivalent /100 g d.w. and a maximal DPPH• antioxidant activity of 74241.61 μmol Trolox equivalent/100 g d.w.. Furthermore, 22 phenolics were first identified in ATL extract obtained under the optimized conditions, indicating that gallates, gallotannins, quercetin, myricetin and chlorogenic acid derivatives were the main phenolic composition in ATL. What’s more, a gallotannins pathway existing in ATL from gallic acid to penta-O-galloyl-glucoside was interpreted. All these results provided practical information aiming at full utilization of phenolics in ATL, together with fundamental knowledge for further research.

Because of safety concerns associated with the use of liquid electrolytes and electrolyte solutions options of non-liquid materials like gels and polymers used as ion conducting electrolytes have been explored intensely. The low ionic conductivity of hard and soft solid materials was too low for practical applications in supercapacitors which require low internal reistance of a device and consequently highly conducting materials. Even if an additional separator may not be needed when the solid electrolyte already ensures reliable separation of the electrodes the electrolytes prepared as films or membranes as thin as practically acceptable resistance may still be too high. Recent developments with gel electrolytes sometimes approach or even surpass liquid electrolyte solutions in terms of effective conductance. Reported studies are reviewed, material combinations are sorted out, trends are identified.

The aim of the present review is to investigate the role of a toothpastes containing enzymes and proteins in supplementing natural salivary defenses. A systematic review was conducted using PRISMA with PROSPERO ID code CRD42024558854. An exhaustive search of PubMed, Web Of Science, and Scopus, using the PICO format was carried out. The used MeSH were enzymes; AND proteins; AND toothpaste. In vivo studies on humans analyzing the gum effects of a toothpaste containing enzymes and proteins, in the English language, published in the last 10 years were included. The search period started on 04 June 2024 and ended on 20 July 2024. The risk of bias was evaluated according to the Revised Cochrane risk-of-bias tool for randomized trials (RoB 2.0) while non-randomized studies were evaluated with the Cochrane risk-of-bias tool in Non-Randomized Studies (ROBINS-I). From a total of 62 studies, 3 were included. Two RCTs and had low and medium risk of bias, the N-RCT had low risk of bias. With the limitations of the present study, a toothpaste containing enzymes and proteins can improve gum health after 12 week and after 12 months, the role against black stains seemed not to be confirmed.

This study investigates user behavior in urban green spaces (UGS) in downtown Shanghai prior to the COVID-19 pandemic. UGS are essential public infrastructure, contributing to urban sustainability, quality of life, and social cohesion. Although widely studied, there remains a gap in urban studies and environmental behavior research regarding UGS use from the perspective of space appropriation. This study addresses this by analyzing user demographics, frequency, and spatial activity patterns to assess how different forms of space use can be evaluated across varying levels of appropriation. Using a mixed-methods design, non-participant observation and behavior mapping were conducted across three comprehensive parks in Shanghai, divided into nine observation zones. Data were analyzed using the Pandas library in Python 3.6, descriptive statistics, and qualitative coding. Findings revealed sixty distinct activity types, predominance of elderly male users, absence of teenagers, and activity peaks in the early morning and late after-noon. Structured patterns of engagement suggest a soft to moderate level of appropriation. This research underscores the effectiveness of observational methods, validates appropriation as an analytical category, and emphasizes the importance of structured classification systems for improving understanding of UGS use and its societal role.

As the adoption of deep learning models continues to surge across various applications, the need for efficient deployment architectures becomes increasingly critical. This paper presents a novel approach to enhance the deployment of deep learning models by leveraging serverless architecture. Serverless computing has been popular for its auto-scaling, cost-effectiveness, and simplified management characteristics. However, the intense resource demands of deep learning models pose challenges in maintaining low response times and effective load balancing within serverless environments. The proposed architecture addresses these challenges by integrating principles from both deep learning model optimization and serverless computing. Through systematic experimentation and analysis, we demonstrate that by appropriately designing and tuning the deployment architecture, significant improvements in response time, performance, resource utilization, and load distribution can be achieved.

Different polyurethanes (PUs) were synthesized with polycarbonate polyols of molecular weights 500, 1000 and 2000 Da. Their self-healing abilities at 20 °C were tested and their structural, thermal, and mechanical properties were analyzed. The PUs made with polycarbonates of molecular weights 500 (YC500) and 1000 Da (YC1000) exhibited self-healing at 20 °C and the self-healing time of YC1000 was the shortest. The high mobility of the short polymeric chains, the absence of crystallinity and the low degree of micro-phase separation favored self-healing at 20 °C in YC500. However, the presence of tack and the existence of allophanate species and urethane-carbonate and urea-carbonate hydrogen bonds disfavored self-healing. Consequently, the self-healing time at 20 °C of YC500 was longer than expected. On the other hand, YC1000 exhibited an “equilibrium” between the urethane-carbonate and urea-carbonate hydrogen bonds and carbonate-carbonate interactions among the soft segments, so a particular structural order was produced which was associated to its fastest self-healing at 20 °C. The PU made with the polycarbonate of molecular weight 2000 Da did not exhibit self-healing at 20 °C because its significant micro-phase separation and the presence of semi-crystalline soft domains.

In nature and engineering applications, flexible fiber beds covering biological surfaces can play a role in reducing resistance. These fibers deform under the action of fluids, and this deformation affects the fluid flow state, forming a complex fluid-solid interaction phenomenon. To quantitatively analyze such issues, the physical model is simplified to the deformation problem of an soft hair bed caused by Stokes flow, and the deformation problem of a single fiber caused by Stokes flow is further studied. The deformation problem of an elastic single fiber in a channel caused by Stokes flow can be described by a nonlinear integral equation. We have obtained a new series solution, which has been compared with the previous perturbation method to verify the accuracy and effectiveness of the series solution. Meanwhile, we have further provided an extended form of flexible fiber deformation through experimental fitting. This fluid-solid interaction problem involves multiple fields and is very important in many natural and engineering systems. The research in this paper can not only help us better understand complex phenomena in nature but also delve into the interaction mechanism between fluids and solids, providing a theoretical basis for future scientific research and engineering applications.

Purpose of research was to determine changes in optical quality for monthly disposable soft contact lenses (SCL) wearers with new and monthly worn SCL. Retinal straylight was assessed in SCL wearers using a C-Quant straylight meter. The study included 33 participants (age 22 ± 1.4 years) who wore monthly disposable silicone hydrogel contact lenses. Measurements were taken with month-old SCL that had been worn for no more than 4 hours. Participants then replaced the old lenses with new ones. After a 15-minute adaptation period, straylight measurements were taken with the new SCL. A questionnaire was administered to all participants, inquiring about vision complaints and the type of contact lens material used. The decimal logarithm of the stray-light parameter, log(s), was notably higher with month-old SCL (log(s) = 0.97±0.17) than with brand-new SCL (log(s) = 0.86±0.15), p < 0.001. The average increase in retinal straylight after a month of SCL use was log(s) = 0.11 ± 0.08. The questionnaire revealed that 35% of participants observed a reduction in visual quality after wearing the contact lenses for a month. Results showed that monthly disposable soft contact lenses could reduce visual quality when scheduled replacement time has been reached.

The purpose of this study is to investigate the influence of heat stress on some biochemical parameters in the blood of dairy cows raised in Bulgaria. The study was conducted on a dairy farm with a capacity of 500 cows, Holstein breed, raised in free-group housing in individual resting boxes. The research was carried out over three seasons: spring, summer, and autumn, with a total of 90 blood samples collected from the cows raised on the farm - 30 blood samples for each season, including cows from the 30th to the 60th day of lactation. Temperature and humidity data were obtained from the nearest meteorological station to the farm. Based on this data, the minimum, average, and maximum values of the temperature-humidity index were calculated. The analysis of variance revealed that the month of the study significantly influenced the following blood parameters: glucose, urea, total protein, cortisol, prolactin, and Ca (P < 0.001). Analysis of the data expressed by LS mean values clearly shows that during the hot months, dairy cows experience a deficit of energy from carbohydrate sources, which they compensate for from other non-carbohydrate sources. Confirmation of this is seen in the blood glucose values, which during the summer are 1.50 mmol/l, approximately twice as low as the values measured during spring and autumn. Regarding urea concentration, a final product of protein metabolism, the values recorded during the summer are 5.3 mmol/l, 1.5 times higher compared to other study periods. As a result of the metabolic load on the liver, the values of hepatic enzymes (ASAT and ALAT) decrease during the summer months, respectively to 93.92 and 17.68 U/L. Cortisol levels in the blood during the summer were registered at 50.92 nmol/l, indicating that cows are under stress. Values for prolactin are of interest, with the highest values being recorded in spring - 1.09 mlU/I. During the summer and autumn studies, the values are 0.99 and 0.89 mlU/I, respectively. A similar trend of decreasing values from spring to autumn season is observed in total blood protein, namely 89.93; 81.99, and 74.36 g/l.

During the COVID-19 pandemic, the spread of the SARS-CoV-2 virus forced many individuals to confront their mortality and worry about losing loved ones also because social distancing policies often made it impossible to say goodbye. Those not directly experiencing loss were inundated with information about COVID-19-related deaths through various media, leading to vicarious grief. This study aims to explore the long-term effects of direct and vicarious mourning on people's mental health during the COVID-19 pandemic. A sample of 171 adults (65% female) aged 19 to 66 years (mean age = 25.8, SD = 8.57) voluntarily participated in an online survey assessing self-reported psychological measures of complicated grief, anxiety, stress, depression, dispositional neuroticism, and situational anxiety using the Fear of COVID-19 Scale. MANOVA tests revealed that individuals experiencing direct mourning had extremely severe scores for anxiety, stress, and fear of COVID-19, while those without personal losses had moderate scores. Participants reporting high media exposure had higher scores for depression and stress. In line with Terror Management Theory, the study supported that people during the COVID-19 pandemic engaged more in proximal defenses than distal ones, taking health-protective measures, experiencing increased anxiety levels toward SARS-CoV-2 infection, and feeling more distressed. Additionally, vicarious mourning was more strongly associated with depression due to emotional empathy with others. The discussion also addresses the strengths and limitations of the study.

The period of the COVID-19 pandemic resulted in a rapid development of innovative education methods, in particular using e-learning and remote work tools. The effects of this development are also post-pandemic changes in formal teaching regulations, in particular in higher education, allowing classes and lectures to be carried out with Blended Learning or Flipped Classroom methods. This paper provides information about a case study of implementing ICT technologies with elements of the mentioned methods in one of the subjects at a technical university. The implemented tools and solutions in the field of e-learning and interactivity are presented, along with information regarding their perception by students during two academic years in the post-COVID-19 period. The analysis of results of these information and student evaluations indicates their generally positive approach to such innovations in the educational path, and at the same time shows significant challenges for teachers to increase the attractiveness and effectiveness of the teaching process and the development of practical, technical skills of students.

The applicability of the distance aggregation problem has attracted the interest of many authors. Motivated by this fact, in this paper we face the modular quasi-(pseudo-)metric aggregation problem. We characterize those functions that allow merging a collection of modular quasi-(pseudo-)metrics into a single one. Specifically, a description of such functions in terms of triangle triplets is given and, in addition, the relationship between modular quasi-(pseudo-)metric aggregation functions and modular (pseudo-)metric aggregation functions is discussed. Such characterizations are illustrated with appropriate examples. A few methods to construct modular quasi-(pseudo-)metrics are yielded. Several properties of modular quasi-(pseudo-)metric aggregation functions are explored and used to develop quick tests for discarding candidate functions to aggregate modular quasi-(pseudo-)metrics. Moreover, a characterization of those modular quasi-(pseudo-)metric aggregation functions that preserve modular quasi-(pseudo-)metrics is also provided. Furthermore, the relationship between modular quasi-(pseudo-)metric aggregation functions and quasi-(pseudo-)metric aggregation functions is studied in such a way that significative differences are displayed.

The intelligent elderly care model places new demands on the skills of aging caregivers. The identification and development of forward-thinking, high-potential nursing talent is essential for advancing the intelligent elderly care sector. Multi-benchmarking selection and competitive analysis is used to evaluate and identify nursing personnel in the rehabilitation treatment center of a hospital in Hefei City. Using proxy evaluation and democratic evaluation model, three types of benchmarks such as single item benchmark, individual benchmark and group benchmark were identified and selected, and the professional nursing team was constructed based on the evaluation results. Different from the traditional other-directed evaluation, multi-benchmarking selection and competitive analysis is self-directed evaluation, this method is more conducive to the identification of high-potential and digital nursing talents by intelligent elderly service organizations, and facilitates the formation of professional nursing teams with complementary strengths and cross-fertilization, so as to satisfy the diversified and multi-level needs of the elderly for intelligent elderly services.

Dipole antennas, fundamental components in wireless communication systems, have garnered significant attention due to their versatility and efficiency across various applications. This literature review explores the performance analysis of dipole antennas, focusing on recent advancements and methodologies from 2019 to 2024. Employing a systematic approach, the review synthesizes findings from multiple databases, emphasizing peer-reviewed studies that delve into dipole antenna designs and applications. Through meticulous data extraction, key parameters influencing dipole antenna performance, such as material properties and operating frequency, are identified and analyzed. Results highlight the widespread utilization of dipole antennas in wireless communication systems, including indoor positioning, mobile communication, and antenna calibration, among others. Discussions underscore the evolution of dipole antennas in base station environments and their role in filtering applications. The review concludes by emphasizing the continued relevance and evolution of dipole antennas, showcasing their adaptability and potential across diverse wireless communication contexts.

Urbanization-induced land use transition results in a decline in ecosystem services, which has implications for regional ecological security. In order to explore the relationship between ecosystem services and land use transition, this paper utilizes the InVEST model, geographically weighted regression model to examine the impact of land use transition on ecosystem services in the Dongting Lake area (DLA). The results showed that (1) During the period 2000-2020, the intensity and motivation of land-use transition showed obvious spatial and temporal heterogeneity with the variation of urbanization development. (2) Habitat quality and Carbon sequestrations showed a downward trend. In contrast, food supply followed an upward trend; soil conservation and water yield services initially increased and dropped later. The overall spatial changes in habitat quality and Carbon sequestration appear to be insignificant. Food supply shows significant differences in the plains compared to other areas; while soil conservation and water yield service shows significant changes in places other than the DLA. (3) From 2000 to 2020, land use transition dynamics, population density, GDP density, night lighting and transition intensity had mainly negative effects on ecosystem services. Only the Normalized Vegetation Index (NDVI) showed a positive effect on ecosystem services. The results of the research will provide valuable references for the development and implementation of spatial ecological restoration planning and land use policies in the national territory.

Amid escalating urbanization, devising rational commercial space layouts is a critical challenge. Leveraging machine learning, this study uses a Back-propagation (BP) neural network to optimize commercial spaces in Weinan City's central urban area. The results indicate an increased number of commercial facilities with a trend of multi-centered agglomeration and outward expansion. Based on these findings, we propose a strategic framework for rational commercial space development emphasizing aggregation centers, development axes, and spatial guidelines. This strategy provides valuable insights for urban planners in small and medium-sized cities in the Yellow River Basin and metropolitan areas, ultimately showcasing the power of machine learning in enhancing urban planning.

Day by day, the share of renewable energy-based power plants such as offshore wind farms and photovoltaic power plants, in the present-day power systems is escalating. Nevertheless, most of these power-producing facilities have been located quite far away from the load centers. At this stage, HVDC power systems provide satisfactory options due to qualities such as reduced line losses, substantial controllability, and environmental advantages. Nevertheless, unique converter designs are required to combine asynchronous HVDC networks with each other and with already existing high voltage alternating current (HVAC) networks. In this study, based on the above special cases, a unique DC-DC modular multilevel converter (MMC) architecture is presented that provides an excellent solution for both integrating modern asynchronous HVDC networks and integrating these modern HVDC power systems with existing asynchronous HVAC power systems. The mathematical analysis of the recommended DC-DC MMC design has been examined in detail and the power transfer between two asynchronous power grids has been realized in a simulation environment. Efficient bilateral power transmission has been made achievable by the control system. The recommended DC-DC MMC topology has shown to be a highly successful approach, in the interconnection of HVDC power systems, according to the simulation results.

Two polyurethanes (PUs) were similarly synthesized by reacting a cycloaliphatic isocyanate with 1,4 butanediol and two polyols of different nature (polyester, polycarbonate diol) with molecular weights of 1000 Da. The PU made with polycarbonate diol polyol (YCD) was the only showing intrinsic self-healing at 20 °C. For assessing the mechanism of intrinsic self-healing of YCD, a structural characterization by molecular weights determination, infrared and X-ray photoelectronic spectroscopies, differential scanning calorimetry, X-ray diffraction, thermal gravimetric analysis and dynamic mechanical thermal analysis was carried out. It was concluded that the self-healing at 20 °C of YCD was due to non-covalent dynamic exchange interactions among the carbonate groups of the soft segments. Therefore, the chemical nature of the polyol played a key role in developing PUs with intrinsic self-healing at 20 °C.

Circulating tumor cells (CTCs) are cells released from the primary tumor and intravasate into the blood or lymphatic vessels, where they are transported to distant sites and act as seeds that initiate cancer metastases. Recent advances in CTC research have shown their relevance as prognostic markers for early and metastatic disease detection, predictive biomarkers for relapse, and response to medical intervention or therapy. The rapidly evolving landscape of CTC biology has opened new avenues for understanding cancer progression, metastasis, and treatment response. Additionally, translating these findings into clinical applications holds promise for improving cancer diagnostics, prognosis, and personalized therapeutic strategies. This review discusses the significance of CTCs in cancer research and their associated challenges. We explore recent developments in the detection and characterization of CTCs and their implications in cancer research and clinical practice.

Background: The increasing prevalence of Mycoplasma genitalium infections with macrolide resistance causing high azithromycin failure rates is a major concern internationally. In response to this challenge, diagnostics that simultaneously detect M. genitalium and genetic markers for macrolide resistance enable the therapy to be individually tailored, i.e. to implement resistance-guided therapy (RGT). Objectives: This study aimed to evaluate patient treatment outcomes of M. genitalium therapy guided by a macrolide-resistance assay in Bulgaria; Methods: Consecutively referred M. genitalium infection cases (n=17) were analyzed for macrolide-resistance mutations (MRMs) and specific antimicrobial treatment was recommended accordingly (MRMs-negative infections received azithromycin and MRMs-positive received moxifloxacin). Treatment outcome based on test-of-cure was recorded and treatment failure rates and time to microbiological cure were compared with treatment outcomes in patients treated before the implementation of RGT; Results: Among patients given RGT (n=17), the overall treatment failure rate was 1/17 (5.9%). This was significantly lower than the rate (47.6%) observed in patients treated pre-RGT (p=0.002). The time to microbiological cure was 29.4 days (CI 24.5 – 34.3) compared to 45.2 days (CI 36.5 – 53.7) pre-RGT (p=0.001); Conclusions: Implementation of M. genitalium diagnostics with macrolide-resistance detection improved treatment outcomes in Bulgaria with significantly lower treatment failure rates and reduced time to microbiological cure. In light of limited treatment options and concerns about their decreasing efficacy in response to misuse and overuse, diagnostic macrolide-resistance assay is critical to direct appropriate first-line treatment, to maintain the efficacy of antimicrobial treatment (antibiotic stewardship) and to minimize the spread of antimicrobial resistance.

The capability of the complex fuzzy sets plays a valuable role to resolve many real life problems. In this paper, we present the compositions of complex fuzzy relations by using the idea of implication operators and max-product compositions of complex fuzzy relations and illustrate these compositions with concrete examples. The converse of these newly invented triangular compositions in terms of compositions of the converse relations are also defined. We also study the interactions with union and intersection. The main goal of this article to present a new technique to enhance medical diagnostic model that can assist to increase the features of healthcare systems. We utilize these compositions to determine the diseases of patients on the basis of intensity of symptoms.

Low-density parity-check (LDPC) codes form part of the IRIG-106 standard and have been successfully deployed for the Telemetry Group version of shaped-offset quadrature phase shift keying (SOQPSK-TG) modulation. Recently, LDPC code solutions have been proposed and optimized for continuous phase modulations (CPMs), including pulse code modulation/frequency modulation (PCM/FM) and the multi-h CPM developed by the Advanced Range TeleMetry program (ARTM CPM). These codes were shown to perform around one dB from the respective channel capacities of these modulations. In this paper, we consider the effect of random puncturing and shortening of these LDPC codes to further improve spectrum efficiency. We perform asymptotic analyses of the ARTM0 code ensembles and present numerical simulation results that affirm the robust decoding performance promised by LDPC codes designed for ARTM CPM.

Two-phase evaporative spray cooling technology can significantly reduce power consumption in data centre cooling applications. However, the literature lacks an established methodology for assessing the overall performance of such evaporation systems. The current study develops a Lagrangian-Eulerian computational fluid dynamics modelling approach to examine the functionality of these two-phase evaporative spray cooling systems. To replicate a modular system, a hollow spray cone nozzle with Rosin-Rammler droplet size distribution is simulated in a turbulent convective natural-air environment. The model was validated against the available experimental data from the literature. A new formulation for the coefficient of performance (COP) is derived to assess the performance of the system. Parametric studies of geometric, flow and climate parameters, namely, domain length, droplet size, water mass flow rate, temperature, and humidity were performed with a specific focus on the climatic conditions in Dublin, Ireland. The findings indicate that at elevated temperatures and low humidity, evaporation results in a bulk temperature reduction of up to 12℃. The efficiency of the evaporation system showed a systematic improvement with a reduction in the droplet size and the mass flow rate. A close to 100 % evaporation rate was achieved in comparison to only a 1 % evaporation rate when the spray Sauter mean diameter (SMD) is reduced to 8-15 μm from 292 μm. It was concluded that the utilization of a fine droplet spray nozzle provides an effective solution for the reduction in water consumption (97 % in our case) for data centres, whilst concomitantly augmenting the proportion of evaporation.

Physical literacy (PL) is increasingly recognised as essential to fostering lifelong physical activity (PA) engagement, particularly when nurtured in early childhood. However, there remains limited understanding of how key stakeholders in early years (EY) education perceive, value, and implement a PL informed approach. This exploratory study aimed to investigate a variety of EY stakeholders' knowledge and beliefs regarding PL and PA in relation to 3-5-year-olds. A concurrent mixed-methods approach was used, incorporating semi-structured expert interviews (n=11), focus groups (n=22), and a survey (n=210) to gather both qualitative and quantitative data. Thematic analysis was applied to identify key themes, and survey data was analysed to complement and triangulate qualitative findings. Findings revealed variation in stakeholders' awareness of PA recommendations, confusion over terminology, and the influence of environmental and policy constraints on practice. Stakeholders acknowledged the importance of PL but expressed uncertainty about the connection between academic theory and practical application. Resource limitations, conflicting priorities, and lack of training and policy support emerged as key barriers. Feedback on an educational PL-EY model was generally positive, emphasising its potential educational value while underscoring the need for clearer guidance and support. Given the pivotal role of EY education in shaping children’s behaviours, health, and well-being, this study highlights the necessity of a holistic approach to interventions, strong stakeholder involvement, and evidence-based practices to foster PL in EY children and raises critical questions about what effective interventions to develop PL in this age group should consider and look like.

Post-exercise recovery is fundamental to optimizing athletic performance, focusing on muscle repair, glycogen replenishment, rehydration, and reducing exercise-induced inflammation. This review examines the evolving landscape of recovery nutrition, highlighting the transition from conventional supplements—such as protein, carbohydrates, creatine, and branched-chain amino acids (BCAAs)—to functional foods rich in bioactive compounds. Emerging evidence supports the efficacy of functional foods like tart cherry juice, turmeric, and omega-3 fatty acids in mitigating oxidative stress and inflammation, thus accelerating recovery. Additionally, probiotics and prebiotic-rich foods are gaining recognition for enhancing gut health, promoting nutrient absorption, and strengthening immune function, which are crucial in recovery processes. The concept of personalized nutrition, guided by genetic and metabolic profiling, is explored as a promising approach to tailor recovery strategies to individual physiological needs. Continued research into the long-term effects of supplements, the role of functional foods, and nutrient interactions is essential for developing more comprehensive and individualized recovery protocols. Integrating functional foods with personalized nutrition offers a holistic strategy to enhance recovery, optimize performance, and promote long-term health in athletes.

Cardiac ischemia-reperfusion injury (IRI) occurs when blood flow is restored to the myocardium after a period of ischemia, leading to oxidative stress and subsequent myocardial cell damage, primarily due to the accumulation of reactive oxygen species (ROS). In our previous research, we identified that miR-25 is significantly overexpressed in pressure overload-induced heart failure, and its inhibition improves cardiac function by restoring the expression of SERCA2a, a key protein involved in calcium regulation. In this study, we aimed to investigate the role of miR-25 in the context of ischemia-reperfusion injury. We found that miR-25 was markedly upregulated under hypoxic conditions in both in vitro and in vivo models. Through in silico analysis, we identified Sestrin3 (SESN3), an antioxidant protein known for its protective effects against oxidative stress, as a novel target of miR-25. Based on these findings, we hypothesized that inhibiting miR-25 would restore Sestrin3 expression, thereby reducing ROS-induced myocardial cell damage and improving cardiac function. To test this hypothesis, we employed two model systems: a hypoxia/reoxygenation (H/R) stress model using H9c2 myoblasts and a surgically induced ischemia-reperfusion injury mouse model. Our results demonstrated that the use of miR-25 inhibitors significantly improved cardiac function and reduced myocardial damage in both models through the restoration of SESN3 expression. In conclusion, our findings suggest that targeting miR-25 may serve as a novel therapeutic modality to alleviate oxidative damage in the heart.

Mergers and acquisitions (M&A) represent pivotal moments for businesses, with the potential to unlock growth, synergies, and market power. However, the success of such transactions is heavily dependent on the robustness of the contractual agreements that define them. Poorly designed contracts introduce numerous risks that can derail the benefits of the deal, leading to financial losses, legal disputes, or operational inefficiencies. This work examines the core risks associated with inadequate contract design in M&A, supported by academic research.

Single crystal nickel-based superalloys are extensively used in turbine blade applications 1 due to their superior creep resistance compared to their polycrystalline counterparts. With the high 2 creep resistance, High Cycle Fatigue (HCF) and Low Cycle Fatigue (Single crystal nickel-based 3 superalloys are extensively used in turbine blade applications due to their superior creep resistance 4 compared to polycrystalline counterparts. As a result, fatigue becomes the primary failure mechanism 5 in such applications. Specifically, High Cycle Fatigue (HCF) and Low Cycle Fatigue (LCF) are of 6 significant concern under these conditions. This study investigates the fatigue life prediction of 7 CMSX-4 using a combined crystal plasticity and lifetime assessment model. The constitutive crystal 8 plasticity model simulates the anisotropic, rate-dependent deformation behavior of CMSX-4, while 9 a modified Chaboche damage model is used for lifetime assessment, incorporating anisotropy by 10 focusing on cleavage stresses on active slip planes. Both qualitative and quantitative data obtained 11 from HCF experiments on single crystal superalloys with notched geometry were used to validate 12 the model. Furthermore, artificial neural networks (ANNs) were employed to enhance the accuracy 13 of lifetime predictions across varying temperatures by analyzing the stress-strain data obtained from 14 simulations. The integration of crystal plasticity, damage mechanics, and ANNs resulted in accurate 15 predictions of fatigue life and crack initiation points under complex loading conditions of single 16 crystal superalloys.

Biofilm-associated infections caused by Candida species represent a significant clinical challenge due to their inherent resistance to antifungal therapies. This study evaluates the antifungal efficacy of trans-Cinnamaldehyde, a natural compound derived from Cinnamomum cassia, in comparison to the widely used antifungal agent Nystatin, against both planktonic and biofilm forms of Candida albicans, Candida glabrata, and Candida tropicalis. Biofilms were established in 96-well polystyrene plates and treated with various concentrations of trans-Cinnamaldehyde and Nystatin. The Minimum Biofilm Inhibitory Concentration (MBIC) and planktonic minimum inhibitory concentration (PMIC) were determined using the MTT assay and Scanning Electron Microscopy (SEM) was employed to assess structural changes in biofilms. The results demonstrated that Nystatin exhibited superior antifungal efficacy across all tested species, particularly in biofilm inhibition, with MBIC50 values as low as 0.0015 mg/mL for C. albicans and C. glabrata. In contrast, trans-Cinnamaldehyde showed moderate antifungal activity with MBIC50 values of 0.16 mg/mL for C. albicans and C. glabrata and higher resistance observed in C. tropicalis (MBIC50 of 0.32 mg/mL). SEM analysis revealed significant biofilm disruption in C. albicans following exposure to trans-Cinnamaldehyde, but C. tropicalis exhibited more resilient biofilm structures. Overall, while Nystatin remains the gold standard for antifungal treatment, trans-Cinnamaldehyde presents potential as an adjunctive treatment, particularly for biofilm-related infections in C. albicans and C. glabrata. Further research is required to explore synergistic effects between trans-Cinnamaldehyde and conventional antifungal agents and to optimize its therapeutic application in clinical settings. This study reused measurement results data from our previous publication to include in tables and charts.

Wearing masks to protect against communicable diseases is an effective tool used in many countries affected by the COVID-19 pandemic. Antibacterial activity, antibacterial efficiency, microbial purity and breathability properties of medical disposable masks are very important. Ag is most commonly applied to antimicrobial textiles, but several studies are known about Ag nano-particles. In this work three antimicrobial additives were used. One of them Rudolf GmBH's RUCO-BAC AGP with silver chloride (AgCl) active ingredient also has antimicrobial activity. Four compositions of the binders with antimicrobial additives were prepared and applied to one-layer nonwoven PP material using screen printing, knife over roll coating and laminating machine methods. The influence of the binder antimicrobial polymer coating on the breathability and antibacterial activity of the nonwoven PP material was evaluated. Results had showed that the composition of the polyacrylic acid binder Tubicoat Thickener LP had the least effect on their breathability and samples with the RUCO-BAC AGP formulation had showed the best antimicrobial response. Therefore, further studies of the antimicrobial coating composition were performed using the binder Tubicoat Thickener LP and antimicrobial additives of different chemical nature and concentration - RUCO-BAC AGP, BI-OME AM10 and Nano Ag aqueous dispersion. Based on the microbiological and air permeability results of the samples of the one-layer nonwoven material with coating, the samples of two-layers and three-layers of medical mask model were prepared. Microbiological studies have shown that three-layered medical mask model with RUCO-BAC AGP composition in the middle layer, in both sides of the model has antibacterial efficiency against three pathogens (E. Coli, K. Pneumoniae, an S. Aureus). The performance of this medical mask model has been found to meet requirements for type I medical masks according to the EN 14863 standard. Study have shown that the microbial purity of the mask model is CFU/g <3.

Industrial products e-commerce refers to the specific application of the e-commerce concept in the field of industrial products transactions. It enables industrial enterprises to conduct transactions via Internet platforms and reduce circulation and operating costs. Industry literature such as policies, reports and standards related to industrial products e-commerce contains abundant and crucial information. Through systematical analysis of the literature information, it is beneficial to explore and grasp the development characteristics and trends of the industrial products e-commerce. To study the characteristics and development status of industrial products e-commerce in China, literature comprising 18 policy documents, 10 industrial reports and 5 standards is deeply analyzed by employing text mining methods. Firstly, natural language processing (NLP) technology is utilized to pre-process the text data related to industrial products commerce. Then, word frequency statistics and TF-IDF keyword extraction are performed, and the results of word frequency statistics are visually displayed. Subsequently, the feature set is obtained by combining the manual screening method. The original text corpus is used as the training set by employing the skip-gram model in word2vec, and the feature words are transformed into word vectors in the multi-dimensional space. The k-means algorithm is used to cluster the feature words into groups. Moreover, the latent dirichlet allocation (LDA) method is also utilized to further group and discover the features. The research results based on text mining provide supportive decisions for uncovering the development characteristics and trends of industrial products e-commerce in China.

Indoleamine 2,3-dioxygenase 1 (IDO1) and IDO2, originated from gene duplication before vertebrate diver-gence. While IDO1 has a well-defined role in immune regulation, the biological role of IDO2 remains unclear. Discovered in 2007, IDO2 is located near the IDO1 gene. Because of their high sequence similarity, IDO2 was initially thought to be a tryptophan (Trp)-degrading enzyme like IDO1. Differently from what expected, IDO2 displays extremely low catalytic activity toward Trp. Nevertheless, many studies, often contradictory, tried to demonstrate that IDO2 modulates immune responses by catabolizing Trp into kynurenine, a hypothesis un-convincing and, let’s say, linked to the first life of IDO2. Here, we review its “new life”, the one in which IDO2 has a functional role beyond Trp metabolism. The IDO2’s evolutionary persistence across species, despite be-ing almost inactive as an enzyme, suggests it has some relevant biological importance. IDO2 expression in human normal cells is poor, but significant in various cancers, with two prevalent SNPs. Overall, the com-parison of IDO2 to IDO1 as a Trp-degrading enzyme may have led to misunderstandings about IDO2’s true physiological and pathological roles. New insights suggest that IDO2 might function more as a signaling molecule, particularly in cancer contexts, and further studies could reveal its potential as a target for cancer therapy.

With the rising awareness of environmental issues, concerns about pollution and global warming have gained importance, and electricity generation costs continue to increase. As a result, research on energy recovery using thermoelectric modules has attracted attention in recent years. Given the lack of significant breakthroughs in thermoelectric materials, improving the structure of thermoelectric modules has become a key direction for enhancing efficiency. Common thermoelectric module types include flat plate (Flat Plate TEG), annular (Annular TEG), flexible (Flexibility TEG), segmented, and cascaded designs. Factors influencing thermoelectric performance include the number, shape, height, contact area of thermoelectric elements, temperature difference, copper plate length, contact resistance, and the geometric arrangement of the elements. This study is based on the commercially available TGM1-127-1.0-0.8 thermoelectric module. By simulating the output performance of both flat plate and annular thermoelectric module structures under identical conditions—such as total volume of thermoelectric material, shape, and height of the thermoelectric legs, the total contact area with the heat source, temperature differential, and total volume of the connecting copper plate—we observed that the number of thermoelectric elements not only determines the open-circuit voltage but also influences the output power. The trend of output power remains consistent under varying temperature differences, regardless of changes in the load resistance.

The gut microbiome known as the “hidden organ” in humans has received wide attention due to its pivotal role in human health, influencing various physiological functions and metabolic processes. Multiple factors influence the gut microbiome and diet emerging as a prominent determinant. Increasing evidence verifies different dietary patterns modulate gut microbial composition and its functionality. Asia, home to the world's largest population, showcases immense diversity, reflected in its complex dietary patterns influenced by tradition and modernization. A plethora of research evidence proves Asian diet confers beneficial effects on maintaining and improving health through favorable alteration of gut microbiome. Yet up to date, no comprehensive review exists on the influence of the Asian diet on gut microbiome. This review critically examines published data on dietary components from Eastern, Southeastern, Southern, Western and Central Asian diet and their interaction with the human gut microbiome across healthy and diseased states. It identifies strengths and limitations in Asian gut microbiome research. Asia experiences rapid dietary transitions demanding further investigation into their effects on the gut microbiota. However, evidence proves traditional Asian diets hold promise for developing personalized dietary interventions and therapeutics to promote gut health and prevent chronic diseases by modulating gut microbiome.

Antimicrobial resistance (AMR) is a worsening global health crisis that has arisen due to antibiotic overuse and misuse. Antibiotic resistance renders standard treatments less effective, making it difficult to control some infections, thereby increasing morbidity and mortality. Medicinal plants are sustainable treatment options that are becoming increasingly important as antibiotics lose their efficacies. The present study evaluates the antibacterial activity of aqueous, methanolic and ethyl acetate extracts prepared using Terminalia bellirica and Terminalia chebula fruit against six bacterial pathogens using disc diffusion and broth microdilution assays. The aqueous and methanol extracts of T. bellirica and T. chebula showed substantial zones of inhibition (ZOIs) against S. aureus and MRSA. The activity against those bacteria was determined to be strong, with minimum inhibitory concentrations (MIC) ranging from 94 µg/mL to 392 µg/mL. Additionally, the T. bellirica methanolic extract showed noteworthy antibacterial activity against E. coli and an ESBL E. coli strain (MIC values of 755 µg/mL for both). The aqueous T. bellirica and T. chebula extracts also inhibited K. pneumoniae growth (MIC values of 784 µg/mL and 556 µg/mL respectively), whilst the methanolic extracts of these plants also inhibited ESBL K. pneumoniae growth (MIC values of 755 µg/mL and 1509 µg/mL respectively). Eighteen additive interactions were observed when extracts were combined with reference antibiotics. Notably, strong antagonistic interactions occurred when any of the extracts were mixed with polymyxin B. All extracts were subjected to LC-MS analysis, revealing several interesting flavonoids and tannins, including 6-galloylglucose, 1,2,6-trigalloyl-β-D-glucopyranose, 6-O-[(2E)-3-phenyl-2-propenoyl]-1-O-(3,4,5-trihydroxybenzoyl)-β-D-glucopyranose, propyl gallate, methyl gallate, sanguiin H4, hamamelitannin, pyrogallol, gallic acid, ellagic acid, chebulic acid, and chebuloside II. All extracts were nontoxic when tested in brine shrimp assays. This lack of toxicity, combined with their antibacterial activities suggests that these plant species may be promising sources of antibacterial compound(s) that warrant further study.

Groundwater pollution in intensive horticultural areas is becoming an increasingly important problem. Therefore, this study evaluates nitrogen (N) fertilization in open field processing pepper crop in Extremadura, Spain. Previous research on the effect of N on sweet peppers grown in greenhouses is abundant, but data on outdoor cultivation, especially considering variety and site influences, are lacking. Field trials were conducted in 2020, 2021 and 2022 to determine the opti-mum N fertilizer rate for processing peppers, with the aim of reducing environmental impacts such as nitrate leaching while maintaining crop yields. Different N rates were applied in the trials, ranging from no N fertilizer to 300 kg N/ha. Meas-urements included crop yield, biomass, intercepted photosynthetically active radiation (PAR), and canopy cover. The study also developed a critical nitrogen curve (CNC) to determine the minimum N concentration required for optimal growth. The results showed that applying more than 200 kg N/ha did not significantly increase yield. Nitrogen-free treatments resulted in earlier fruit maturity, concentrating the harvest and reducing waste. In addition, excessive N application led to envi-ronmental problems such as groundwater contamination due to nitrate leaching. The study concludes that outdoor pepper crops in this region can achieve optimal yields with lower N rates (around 120 kg N/ha) compared to current practices, thereby reducing environmental risks and fertilizer costs. It also established relationships between biomass, canopy cover, and N uptake to improve fertilization strategies. These data support future crop modelling and sustainable fertili-zation practices.

The Electric Fish Optimization (EFO) Algorithm is inspired by the predation behavior and communication of weak electric fish. It is a novel meta-heuristic algorithm that attracts researchers because it has few tunable parameters,high robustness,and strong global search capabilities. Nevertheless, when operating in complex environments, the EFO algorithm encounters several challenges including premature convergence, susceptibility to local optimum, and issues related to passive electric field localization stagnation. To address these challenges, this study introduces an Adaptive Electric Fish Optimization Algorithm Based on Standstill Label and Level Flight (SLLF-EFO). This hybrid approach incorporates the Golden Sine Algorithm and Good Point Set Theory to augment the EFO algorithm’s capabilities, employs a variable step size Levy flight strategy to efficiently address passive electric field localization stagnation problems, and utilizes a standstill label strategy to mitigate the algorithm’s tendency to fall into local optimum during the iterative process. By leveraging multiple solutions to optimize the EFO algorithm, this framework enhances its adaptability in complex environments. Experimental results from benchmark functions reveal that the proposed SLLF-EFO algorithm exhibits improved performance in complex settings, demonstrating enhanced search speed and optimization accuracy This comprehensive optimization not only enhances the robustness and reliability of the EFO algorithm but also provides valuable insights for its future applications.

FER zeolites has a unique framework structure and acid distribution, and is widely studied as a catalyst for reactions such as n-butene skeletal isomerization and dimethyl ether carbonylation. The BAS located in the 10-MR of FER zeolites serves as the active site for the isomerization reaction of n-butene skeletal to produce isobutene. In contrast, the acid site found in the 8-MR is prone to side reactions, such as polymerization and cracking, which can adversely affect the selectivity of isobutene. This study prepared five types of FER zeolites using different method, inducing Na-form or H-form crystal seeds without organic structure directing agents (OSDAS), using pyridine alone as a template, and combining the seeds with pyridine. The differences in the structure and acid distribution of the five zeolites were investigated, as well as their catalytic performance for the the skeletal isomerization of n-Butene. Experiments and characterization results showed that under hydrothermal synthesis conditions, the FER-PY+SH zeolites synthesized by using both H-form zeolites seeds and pyridine exhibited the highest aluminum concentrations at T1 and T3 positions, along with the greatest BAS of 10-MR. This unique composition contributed to the highest selectivity of isobutene. The FER-PY+SH catalyst was continuously used for 720 hours at 350 ℃, 0.1 MPa, and n-butene mass space velocity of 2.0 h^-1 for three recycles on 2160 h. During this period, the conversion of n-butene over 39%, while the selectivity of isobutene exceeded 95%.The catalyst exhibited excellent stability and activity.

In the present research, it has been tried to use the applied research bases in the field of business management with marketing orientation. Since there were wide and diverse spectrums in the field of economic activities in Isfahan province and Isfahan city, the model of economic sectors was used to categorize these activities. In this regard, the specific goals of the research in all five sectors of the model of economic sectors, drawing and prioritizing the components (indices) of the 7P marketing mix model in each of these economic sectors by the related individuals and members of subgroups of guilds and non-governmental organizations in Isfahan province, have been formed, specified and determined. Collecting data for processing and answer the question of this research, after designing a questionnaire in accordance with the AHP model standard, by spending a period of 2 months from September 2022 and ended in November 2022 , from the statistical population has been done.

Dead reckoning is a promising yet often overlooked smartphone-based indoor localization technology that relies on phone-mounted sensors for counting steps and estimating walking directions, without the need for extensive sensor or landmark deployment. However, misalignment between the phone’s direction and the user’s actual movement direction can lead to unreliable direction estimates and inaccurate location tracking. To address this issue, this paper introduces SWiLoc, an enhanced direction correction system that integrates passive WiFi sensing with smartphone-based sensing to form Correction Zones. Our two-phase approach accurately measures the user’s walking directions when passing through a Correction Zone and further refines successive direction estimates outside the zones, enabling continuous and reliable tracking. In addition to direction correction, SWiLoc extends its capabilities by incorporating a localization technique that leverages corrected directions to achieve precise user localization. This extension significantly enhances the system’s applicability for high-accuracy localization tasks. Additionally, our innovative Fresnel zone-based approach, which utilizes unique hardware configurations and a fundamental geometric model, ensures accurate and robust direction estimation, even in scenarios with unreliable walking directions. We evaluate SWiLoc across two real-world environments, assessing its performance under varying conditions such as environmental changes, phone orientations, walking directions, and distances. Our comprehensive experiments demonstrate that SWiLoc achieves an average 75th percentile error of 8.89 degrees in walking direction estimation and an 80th percentile error of 1.12 meters in location estimation. These figures represent reductions of 64% and 49%, respectively for direction and location estimation error, over existing state-of-the-art approaches.

Against the backdrop of the European Union's commitment to achieve climate neutrality by 2050, efforts to improve energy efficiency are being intensified. The manufacturing industry is a key focal point of these endeavors due to its high final electrical energy demand, while simultaneously facing a growing shortage of skilled workers crucial for meeting established goals. Expert systems (ESs) offer the chance to overcome this challenge by automatically identifying potential energy efficiency improvements and thereby playing a significant role in reducing electricity consumption. This paper systematically reviews state-of-the-art approaches of ESs aimed at improving energy efficiency in industry, with a focus on manufacturing. The literature search yields 1668 results, of which 62 articles published between 1987 and 2024 are analyzed in depth. These publications are classified according to the system boundary, manufacturing type, application perspective, application purpose, ES type, and industry. Furthermore, we examine the structure, implementation, utilization, and development of ESs in this context. Through this analysis, the review reveals research gaps, pointing toward promising topics for future research.

Predicting the thermophysical properties of designed materials at the nanoscale is crucial. However, this remains a significant challenge despite numerous efforts by researchers and scientists. This paper presents a unified thermodynamic model to study the size and shape-dependent cohesive energy, as well as the melting temperature of semiconductor nanosolids, including InSb, ZnSe, CdS, and CdSe. The model provides insight into the thermal stability of nanosolid materials by considering the combined impact of size, shape, and packing density. The finding indicates that smaller nanoparticles exhibit a lower cohesive energy compared to larger ones. Our unified thermodynamic model yields results consistent with experimental values and demonstrates a closer agreement than those from the universal liquid drop model of size-dependent cohesive energy, which includes a shape factor of α = 2/3 for nanowires. According to the results, the melting temperature of nanoparticles drops as their size decreases. Below a diameter of 5 nm, this trend becomes more noticeable. In the nano-scale domain, the nanoparticle's shape also matters greatly. In particular, compared to tetrahedral nanoparticles, nanowires show a lesser reduction in melting temperature. Also, up to a diameter of roughly 10 nm, the melting temperatures of these nanoparticles rise with particle size. The search results show that, especially in the < 5 nm size range, the size and shape of nanoparticles significantly affect their melting point. The models accurately predict the relationship between particle size and melting point for various semiconductor nanomaterials, aligning with experimental findings. Interestingly, the information points to a potential preference for these nanomaterials to form nanowire structures in the < 5 nm size range. Our research offers helpful insights into the thermophysical properties of these semiconducting materials, which may have significant implications for their use in a diversity of technological applications.

This study explores how the Household Dietary Diversity Score (HDDS) and spatial visualization can inform food governance in Chile, focusing on socio-demographic and geographical determinants affecting food consumption patterns. A national household database (n=4,407) provided by the “Family Support Program of Food Self-Sufficiency” (FSPFS) of the Ministry of Social Development and Family was analyzed. The findings revealed that Chilean vulnerable households were led mostly by women (86.6%), with an age average of 55.9 15.6 years old, versus 68.9 12.9 years in the case of men. The intake frequency analysis showed that dairy, fruits, and vegetables were below the recommended values in at least half of the households, and that fats and sugars were above recommended levels. Regarding the HDDS [0-189], the national average was of 91.4 ± 20.6 and was significantly influenced by the number of minors in the households, water access, food access issues, and residing in the Zona Sur. Finally, the spatial visualization showed that the Zona Central had higher consumption of fruits and vegetables, while the extreme zones Norte Grande and Zona Austral showed higher intakes of fats and sugars. These findings emphasize the importance of leveraging data insights like HDDS and spatial visualization to enhance food security and inform food governance strategies.

Sustainable water resource management in Bangladesh's Gumti River Basin faces challenges from climate change, urbanization, and population growth. This study aimed to calibrate and validate the HEC-HMS model for the Gumti River to enhance flood prediction and water resource planning. The model was set up using precipitation, temperature, and discharge data from 2019-2021, with SRTM elevation data for catchment delineation. Manual calibration was performed for 2019-2020, followed by validation for 2021, using parameters such as Muskingum routing and SCS Curve Number. Model performance was evaluated using R², Nash-Sutcliffe efficiency (NSE), RSR, and PBIAS metrics. Results showed satisfactory to good performance, with R² values of 0.64 and 0.68 for calibration and validation, respectively. NSE values were within the satisfactory range, while PBIAS indicated very good performance with slight underestimation. The study concludes that the calibrated HEC-HMS model provides a reliable tool for simulating the Gumti River's hydrology, though there's room for improvement. Integration with flood frequency analysis, water quality monitoring, and climate change projections is recommended for comprehensive water resource management, alongside the implementation of Sustainable Water Resource Management principles and community engagement strategies.

The Sustainable Development Center of the University of Brasilia is one of the modernist buildings that make up the Darcy Ribeiro campus. The architectural project contains several recommendations for the execution of the flat roof waterproofing system, as well as details for rainwater runoff and drainage, which reveals a certain concern with watertightness. The research seeks to identify the relationship between the pathological manifestations recognized on the roof and the semicircular shape of the building, assessing the state of conservation through the use of damage maps as an analysis tool. The article is based on a field survey using aerophotogrammetry with a drone, the application of vector drawing software for graphic representation and discussion of the possible causes, agents and mechanisms of degradation at work. The results show the importance of mechanical protection for the good performance of the waterproofing system, as well as the need for correct sizing of expansion joints in order to absorb and relieve the stresses caused by hygrothermal variations. The methodology incorporated proved to be effective and economical in diagnosing and monitoring pathological manifestations, making it possible to plan maintenance actions that extend the useful life and preserve the intrinsic characteristics of building systems.

A simple protocol for preparation of O-acylated enol form - (R/S)-ethyl-2-acetoxy-4-phenyl-4H-chromene-3-carboxylate 5 was presented. The compound was characterized by 1H-, 13C-and DEPT135 NMR spectra, including {1H,1H} COSY, {1H,13C} HSQC, {1H,13C} HMBC and 2D-NOESY spectra. The preferred regioselectivity for O-acylation of 3,4-dihydrocoumarin 5 in the presence of substituent in 4-th position in the chroman ring and accounting the steric hindrance of the ester group in 3-th place was confirmed.

The increasing demand for large-scale, high-frequency environmental monitoring has driven the adoption of satellite-based technologies for effective forest management, especially in the context of climate change. This study explores the potential of SAR for estimating the mass of harvesting residues, a significant component of forest ecosystems that impacts nutrient cycling, fire risk, and bioenergy production. The research hypothesizes that while the spatial distribution of residues remains stable, changes in moisture content—reflected in variations in the dielectric properties of the woody material—can be detected through SAR techniques. Two models, generalized linear model (GLM) and random forest (RF), were used to predict the mass of residues using interfer-ometric variables (phase, amplitude and coherence) as well as the backscatter signal from several acquisition pairs. The models provided encouraging results (R2 of 0.48 for GLM and 0.13 for RF), with acceptable bias and RMSE. We concluded that SAR data are feasible to predict the mass of harvesting residues and the findings could lead to improved monitoring and management of forest residues, contributing to sustainable forestry practices and enhanced bioenergy resource utilization.

To address the issue of intelligent optimization algorithms being prone to local optima, resulting in insufficient feature extraction and low fault type recognition rates when optimizing Variational Mode Decomposition (VMD) and Support Vector Machine (SVM) parameters, this paper proposes a fault diagnosis method based on an improved Artificial Gorilla Troops Optimization (GTO) algorithm. The GTO algorithm is enhanced using Logistic chaotic mapping, a linear decreasing weight factor, the global exploration strategy of the Osprey Optimization Algorithm, and the Levy flight strategy, improving its ability to escape local optima, adaptability, and convergence accuracy. This algorithm is used to optimize the parameters of VMD and SVM for fault diagnosis. Experiments on fault diagnosis with two datasets of different sample sizes show that the proposed method achieves a diagnostic accuracy of no less than 98% for samples of varying sizes, with stable and reliable results.

The extensive use of polypropylene (PP) in various industries has heightened interest in devel-oping efficient methods for recycling and optimising its mixtures. This study focuses on formu-lating predictive models for the Melt Flow Rate (MFR) and shear viscosity of PP blends. The in-vestigation involved characterising various grades, including virgin homopolymers, copolymers, and post-consumer recyclates, in accordance with ISO 1133 standards. The research examined both binary and ternary blends, utilising traditional mixing rules and symbolic regression to predict rheological properties. High accuracy was achieved with the Arrhenius and Cragoe models, at-taining R² values over 0.99. Symbolic regression further enhanced these models, offering signif-icant improvements. To mitigate overfitting, empirical noise and variable swapping were in-troduced, increasing the models' robustness and generalisability. The results demonstrated that the developed models could reliably predict MFR and shear viscosity, providing a valuable tool for improving the quality and consistency of PP mixtures. These advancements support the de-velopment of recycling technologies and sustainable practices in the polymer industry by opti-mising processing and enhancing the use of recycled materials.

The microbial communities are closely related to the overall health and quality of soil, but studies on microbial ecology in apple-pear orchard soils are limited. In the current study, 28 soil samples were collected from three apple-pear orchards in northeastern China, and the composition and structure of fungal and bacterial communities were investigated by high-throughput sequencing. Molecular ecological network showed that the keystone taxa of bacterial communities were Actinobacteria, Proteobacteria, Gemmatimonadetes, Acidobacteria, Nitrospirae, and Chloroflexi, and the keystone taxa of fungal communities was Ascomycota. Mantel tests showed that soil texture and pH were important factors shaping soil bacterial and fungal communities, and soil water soluble organic carbon (WSOC) and nitrate nitrogen (NO3--N) were also closely related to soil bacterial communities. Canonical correspondence analysis (CCA) and variation partition analysis (VPA) analysis revealed that geographic distance, soil texture, pH, and other soil properties could explain 10.55%, 13.5%, and 19.03% of the overall variation of bacterial communities, and they explained 11.61%, 13.03%, and 20.26% of the overall variation of fungal communities, respectively. The key stone taxa of bacterial and fungal communities in apple-pear orchard soils and their strong correlation with soil properties could provide useful clues toward sustainable management of orchards.

Microalgae are photosynthetic microorganism able to receive light from sunlight and external light sources for their growth. Despite the simplicity of cultivation and their widespread presence, the growth of microalgae is affected by several factors, light intensity being a crucial one as it is linked to external environmental conditions. On the other hand, microalgae cultivation in wastewater with high nitrogen content has become a promising alternative as a low cost nutrients substrate method. However, effluents may contain many compounds, making therefore difficult the assessment of light intensity on cells growth profile and especially on nutrients assimilation rate. The aim of this study was the examination of the effect of intensity of light source on the growth and nutrient uptake rates by a freshwater microalgae, Chlorella sorokiniana in the effluent from an anaerobic digestion plant, with nitrogen content reaching up to 5 g/L. Microalgae were cultivated using three light intensities (1,500, 5,000 and 12,000 lx) in 10% digestate mixtures in water. Samples were collected and analyzed for the presence of microalgae cells, while aqueous phase samples were subjected to the analysis of nitrogen and phosphorous content. Biomass productivity followed the light intensity pattern: the highest the light the highest the cells growth. A similar pattern was observed in the reduction rate of nitrogen and phosphorous concentrations; however, nutrients reduction rate per gram of microalgae were mainly associated to biomass growth rate, indicating that the effect of light intensity was significant for biomass growth, without however changing the main nutrients assimilation pathway. In addition, results indicated that under high light intensity, microalgae might change their metabolism towards formation of lipids against nitrogenous compounds.

Access to reliable water supply is critical for sustainable development and public health, yet many peri-urban and rural communities in the developing world face challenges such as poor maintenance, faulty infrastructure, and inadequate governance of water services, hindering the UN’s Sustainable Development Goals (SDG). In Emina-Boadi, a small town in Kumasi, Ghana, residents increasingly rely on boreholes due to substandard service from the Ghana Water Company Limited (GWCL). This shift highlights concerns about water reliability, quality, and affordability, impacting public health and hindering progress toward SDG 6. This case study assesses water service levels using key performance indicators (KPIs) such as quantity, quality, affordability, accessibility, and reliability, focusing on sources like boreholes, hand pumps, piped water, hand-dug wells, rainwater, and surface waters. The study aims to delineate the roles of different water providers, understand community dynamics, and evaluate contributions to rural development and SDG 6 through stakeholder interviews and questionnaires. Leveraging the WASHCost framework, which aims to improve planning methods and provision of water and sanitation services by addressing the lack of cost information in rural and peri-urban areas, and the Joint Monitoring Programme (JMP) framework, which monitors progress toward global targets related to water, sanitation, and hygiene, the study categorizes indicators and draws connections among them. Findings reveal a significant preference for borehole services, with 87% usage and an 83% reliability rate compared to 13% for GWCL. Daily water consumption averages 60.75 liters per person, with on-premises access improving water collection efficiency to 7 minutes. Dissatisfaction with GWCL services highlights the need for improved delivery aligned with community needs and SDG targets. Adopting sustainable management practices, enhancing infrastructure, and improving governance are crucial for ensuring safe and affordable water access for all residents of Emina-Boadi and similar communities.

This study presents an advanced defect detection approach for solar cells using the YOLOv10 deep learning model. Leveraging a comprehensive dataset of 10,500 solar cell images, annotated with 12 distinct defect types, our model integrates Compact Inverted Blocks (CIB) and Partial Self-Attention (PSA) modules to enhance feature extraction and classification accuracy. Training on the Viking cluster with state-of-the-art GPUs, our model achieved remarkable results, including a mean Average Precision (mAP@0.5) of 98.5%. Detailed analysis of the model's performance revealed exceptional precision and recall rates for most defect classes, notably achieving 100% accuracy in detecting black core, corner, fragment, scratch, and short circuit defects. Even for challenging defect types such as thick line and star crack, the model maintained high performance with accuracies of 94% and 96%, respectively. The recall-confidence and precision-recall curves further demonstrate the model's robustness and reliability across varying confidence thresholds. This research not only advances the state of automated defect detection in photovoltaic manufacturing but also underscores the potential of YOLOv10 for real-time applications. Our findings suggest significant implications for improving the quality control process in solar cell production.

Stage IV grade C localized periodontitis (pre-puberal localized aggressive periodontitis/LPP), an extremely rare form of periodontal disease, occurs in otherwise healthy individuals (no signs of dental plaque/calculus) due a hyper-aggressive auto-immune response to high periodontopathic bacteria levels. Methods: A 4-year-old Caucasian girl with unusual high mobility of temporary lower left canine and localized gingival inflammation was misrecognized by multiple clinicians (initially diagnosed with hypophosphatasia, genetic and metabolic disorders, all turning negative), over a period of 4-6 month, despite initial radiographs showing clear pathognomonic signs. LPP diagnostic was made by the last clinician, but by now the tooth was lost. Similar inflammation signs appeared around the lower temporary right canine. X-ray examination showed similar bone and periodontal loss as previously seen, while periodontopathic bacteria tested highly positive. The patient received both mechanical cleaning and ten days systemic antibiotic treatment (Augmentin and Metronidazole). Results: Two months after, inflammation signs disappeared, with periodontal regeneration radiologically present, and only small periodontopathic bacteria precursors concentrations. Conclusions: Despite initial periodontal loss, an adequate treatment can keep under control an LPP disease. Moreover, bone and periodontal regeneration appears if periodontopathic bacteria scores are kept lower, showing the importance of fast adequate diagnostic and treatment.

Single-cell RNA sequencing (scRNA-seq) technique has enabled detailed analysis of gene expression at the single cell level, enhancing the understanding of subtle mechanisms that underly pathologies and drug resistance. To derive such biological meaning from sequencing data in oncology, some critical processing must be performed, including identification of the tumor cells by markers and algorithms that infer copy number variations (CNVs). We compared the performance of sciCNV, InferCNV, CopyKAT and SCEVAN tools that identify tumour cells by inferring CNVs from scRNA-seq data. Sequencing data from Pancreatic Ductal Adenocarcinoma (PDAC) patients, adjacent and healthy tissues were analysed, and the predicted tumor cells were compared to those identified by well-assessed PDAC markers. Results from InferCNV, CopyKAT and SCEVAN overlapped by less than 30% with InferCNV showing the highest sensitivity (0.72) and SCEVAN the highest specificity (0.75). We show that the predictions are highly dependent on the sample and the software used, and that they return so many false positives hence are of little use in verifying or filtering predictions made via tumor biomarkers. We highlight how critical this processing can be, warn against the blind use of these software and point out the great need for more reliable algorithms.

In order to study the effect of explosion load on the flexural performance of RC beams, two RC beams of the same size were carried out explosion test and bearing capacity test successively. Piezoelectric intelligent aggregate was embedded in the beams in advance to monitor the damage state of the beams, which realized the whole process of damage monitoring of the concrete inside the structure from explosion damage to compression damage.Based on wavelet packet analysis and residual bearing capacity damage evaluation criteria, the beam damage was quantitatively evaluated, and the bending bearing capacity of RC beam after explosion damage was compared and analyzed.The results show that the change of concrete strain gauge signal, the phenomenon of crack development and the increase of internal crack development index indicate that the RC beam is damaged by explosion load.After explosion damage, the damage index of the beam increases and the residual bending capacity decreases, which proves that the piezoelectric intelligent aggregate sensor can effectively monitor the bending capacity change of the component after explosion damage.