We aimed to investigate the clinical results following poor-quality embryo transfer and the parameters to foresee the prognosis. In this study, 2123 cycles that had day 3 and day 5 single-fresh embryo with a poor-quality embryo transfers and a good-quality embryo transfers were compared. The cycles according to transfer day were evaluated by conducting a subgroup analysis. The correlation between all the obtained demographic characteristics, controlled ovarian stimulation parameters and cycle results were analysed. Clinical pregnancy was established in 53 patients that underwent transfer in the poor-quality embryo group (14.9%). Of these patients, 36 had live birth (live birth rate per clinical pregnancy 67.9%). In cleavage-stage embryos, live birth rates per clinical pregnancy were higher in poor-quality blastocyst transfer. When analysing the factors affecting live births in poor-quality embryo group, as the total gonadotropin dose increases, the probability of live birth decreases, as in the probability of hCG positivity. In conclusion; although the probability of pregnant is low, when clinical pregnancy is established, there is a high chance of having a live birth after poor-quality embryo transfers. This could be regarded as an acceptable option in cycles when only poor-quality embryos were available.

Water quality assessments are crucial for human health and environmental safeguards. The utilization of a subset of artificial intelligence such as Machine Learning (ML) presents significant impacts to enhance the prediction and classification of water quality. In this research, a set of diverse ML algorithms was evaluated to handle a comprehensive dataset of water quality measurements over an extended period. The aim was to develop a robust approach for accurately forecasting water quality. This approach employed machine learning classifiers such as Logistic Regression (LR), Support Vector Machine (SVM), Stochastic Gradient Descent (SGD), K-Nearest Neighbors (KNN), Gaussian Process Classification (GPC), Gaussian Naive Bayes (GNB), Random Forest (RF), Decision Tree (DT), XGBoost, and Multilayer Perceptron (MLP). The water quality parameters assessed for pH, hardness, solids, chloramines, sulfate, conductivity, organic carbon, trihalomethanes and turbidity. The XGBoost model exhibited the highest accuracy of 89.47% among the classifiers and Stacked Ensemble Classifiers (SEC) improved the prediction further to 92.98%. The findings suggest that XGBoost and the SEC hold promise as reliable approaches for water quality assessments in contrast of artificial intelligence.

Asthma is a chronic respiratory disease that impairs breathing. Management of asthma presents a significant challenge due to its inherent variability; that is, its symptoms can substantially differ among individuals, thereby complicating the prediction and management of exacerbations. Furthermore, individuals with asthma often have unique triggers that precipitate symptoms or attacks. The identification of these triggers can often prove to be a challenging, and at times, an impractical attempt. To address this, our research proposes a practical, personalized alert system, predicated on individual lung function tests conducted under varying environmental conditions classified by air-quality sensors. To validate this concept, we conducted an observational pilot study involving healthy individuals. We recruited twelve healthy participants and monitored their responses across a broad spectrum of environments, characterized by varying air quality, temperature, and humidity conditions. The lung function for each participant, assessed using peak expiratory flow (PEF) values, was recorded in each of these environments. Our results highlighted substantial variability in pulmonary responses to different environments. Utilizing these insights, we proposed a personalized alarm system that provides real-time air-quality monitoring and issues alerts when environmental conditions may potentially become unfavorable. We also explored the feasibility of employing basic machine learning techniques to predict PEF values in the aforementioned environmental conditions. This proposed system has the potential to empower individuals in actively safeguarding their respiratory health and mitigating discomfort caused by environmental conditions, especially in cases of asthma patients. By enabling timely and personalized interventions, the system aims to provide individuals with the necessary tools to minimize exposure to asthma’s possible triggers.

This paper describes the indoor air pollution in urban (Lahore, Faisalabad, Gujranwala, Rawalpindi and Karachi) Pakistani regions while considering the outdoor air and the health and wellbeing of the occupants present indoors. It also aims to assess previous methodological approaches Such as Air Conditioning Systems, used by developed countries to improve air quality to demonstrate the improvements that can be made in air quality in Pakistani urban areas. This research also investigates the causes, concentration and effects of poor air quality in Pakistani urban areas such as particulate matter (PM2.5), carbon oxides (COx), nitrogen oxides (NOx), sulphur oxides (SOx) and volatile organic compounds (VOC’s). The average concentration of these pollutants in Pakistan’s indoor air is, particulate matter (PM): [100 – 250 µg/m3 for PM2.5, 200 – 600 µg/m3 for PM10] 1 – 20 ppm for carbon monoxide (CO), nitrogen oxides (NOx): [50 – 100 µg/m3 for NO2, 20 – 40 µg/m3 for NO], 20 – 50 µg/m3 for sulfur dioxide (SO2), volatile organic compounds (VOCs): 0.1 – 0.5 ppm for formaldehyde, 5 – 10 µg/m3 for benzene and 20 – 30 µg/m3 for toluene. It should be noted that these concentrations can differ depending on the origin of pollution, location, and time of day. The literature review is made up of a combination of descriptive research methods that are used to inform the research background of ambient and indoor air quality, thus the literature review provides a theoretical and methodological background about the air pollution and its improvement in different parts of the world. According to the World Air Quality Index, Pakistan is the third most polluted country in terms of average PM2.5 concentration which is 14.2 times the WHO annual air quality guideline value. As a result, it is suggested that a PM2.5 concentration reduction program be implemented in urban Pakistani regions' indoor air.

Despite a growing concern over sustainability in tourism, research on this domain regarding, specifically, lake destinations, is still scarce. Although perceptions on lake destinations have been studied, no study is known that analyses the impact of visitors’ perceptions on satisfaction and behavioral intentions. Thus, this paper aims to develop and test a model to analyse the effect of lake visitors’ perceptions of destination’s sustainability on both satisfaction and loyalty towards lake destinations. A questionnaire survey was conducted in the Shchuchinsk-Burabay resort area, an important lake destination in northern Kazakhstan. The results support the proposed lake destination loyalty model, tested using partial least squares structural equation modelling (PLS-SEM). Sustainability proved to be decisively influential, with water quality being the dimension with the highest impact on satisfaction with the lakes, along with a positive key impact of the absence of congestion. In addition, both water quality and lack of congestion had a significant indirect impact on satisfaction with the lake destination, and on loyalty. Based on the research findings, theoretical conclusions and practical implications are drawn.

The rural road landscape is crucial in forming rural areas' landscape character (LC). As a platform for portraying the rural landscape, the rural roads demonstrate the area's unique natural and cultural characteristics to the visitors. However, with the continuous development of rural areas, the rural LC has been severely impacted, thus impacting visitors' visual experience. In order to preserve and protect the rural landscape, this study aims to assess the visual quality of rural road landscapes based on public preference and heatmap analysis. The results indicated that most of the participants had a higher level of preference for rural landscapes with open horizontal views represented by agricultural areas such as paddy fields. It was also found that different paddy field characters based on their planting stages can also positively affect the visual quality of rural road landscapes. The study also revealed that rural LCs with roadside settlements, commercial structures, mixed agricultural crops, and vegetation received low preference ratings. These characters negatively impact the visual quality of the rural road landscape. These findings provide significant insight for planners and decision-makers regarding protecting and preserving the essential rural road landscapes for the rural tourism experience.

This qualitative research examines the quality assurance practices in private school institutions in Iligan City during the first semester of 2020-2021. The study involves interviews with 30 school administrators and document analysis to uncover key themes and sub-themes. The findings reveal the significance of clear policies, professional development for teachers, stakeholder engagement, assessment strategies, and technology utilization in quality assurance. The study also identifies challenges such as the need for standardized assessment procedures, limited resources for professional development, and the integration of technology. Moreover, it emphasizes the importance of adaptability and flexibility in the face of changing educational landscapes, particularly during the COVID-19 pandemic. Recommendations for further research include conducting a comparative analysis between private and public school institutions, investigating the long-term impacts of the pandemic on quality assurance, and exploring innovative strategies for online and blended learning environments. The paper concludes by highlighting the importance of addressing challenges and embracing new perspectives in quality assurance to improve the overall quality of education. The implications of the study emphasize the need for comprehensive quality assurance frameworks that encompass all aspects of education and the importance of ongoing evaluation and improvement. Ultimately, this qualitative research article contributes valuable insights for private school institutions and educational policymakers to enhance their quality assurance practices and provide better educational experiences for students.

The patient's satisfaction level concerning hospitalization has certain particularities, related to the geographical area, medical/non-medical assistance, the age, incomes, morbidity and mortality of the population. The objective of this study is to emphasize the degree of patients' satisfaction, depending on the specialty of the hospitalization department: surgical, medical, oncological, psychiatry, and to evidence the factors influencing the reliability and accuracy of patients' answers, such as: the patient's health condition upon admission, the duration of the admission, the level of physical pain and the emotional state. Patients and methods: The research was conducted between April and December 2021 on patients hospitalized in two public hospitals from the north-west of Romania, both of them being independent Legal Entities: the Municipal Clinical Hospital of Oradea (MCHO) and the County Clinical Emergency Hospital of Oradea (CCEHO). Results: The lowest score of PSS recorded in these two analyzed public hospitals from the north-western of Romania was appointed for the Pharmaceutical availability of patients medical treatment (2.24), attitude of the staff (2.56) and the quality of nursing care offered (2.58). Conclusions: The hospital management’s focus has been set to improve the communication skills among medical staff, to evidence their compassion, politeness, and to ensure the availability of essential drugs.

Blueberries (Vaccinium corymbosum L.) are becoming increasingly popular for their nutritional and health benefits, and their economic value is therefore increasing. Loss of quality that can occur due to softening and fungal attack is an important consideration when marketing blueberries. Despite the added value of blueberries, no studies have been carried out on how the fruit arrives at the outlets just before purchase by the consumer in terms of firmness, physico-chemical parameters, phenolic compounds and fungal growth. The aim of this work has been, therefore, to investigate possible differences in quality parameters between blueberries purchased from ten different outlets, regardless of the supplier. The results showed that all samples were of acceptable quality, although they all had a low maturity index at the point of sale. On the other hand, differences in the parameters measured were observed between samples of the same cultivar while we could not find differences between conventionally and organically grown blueberries, suggesting that preharvest and postharvest factors could influence the final quality when they reach the consumer.

Quality products are a main focus for manufacturers. Product users only determine a product is a quality product if it performs in operation to the user’s perceived standard. Product manufactures need to take a product lifecycle quality (PLQ) perspective of quality and not simply focus on manufacturing quality control, which is more accurately specification control. Manufacturing is the key phase where products take their physical form. There are increasing costs and decreasing risk of different physical quality strategies. The information provided using digital twins and virtual testing promises to be both low risk and cost and has the potential to predict what the customer will experience in operation by testing products passively with data and actively with simulation to destruction. Digital Twin Certified (DTC) is proposed as the methodology for accomplishing this. DTC will be especially important for the adoption of additive manufacturing.

Clinical trials are research studies performed on people that are aimed at evaluating a medical, surgical, or behavioural intervention. It is a primary way that researchers find out if a new treatment, like a new drug or diet, or medical device is safe and effective in people. In this paper blockchain technology is embedded in a digital twin aiming to improve the quality of clinical trials through the boost of data integrity among the quality-related activities, and to promote participants' safety. First, a blockchain-embedded quality-enabled digital twin is proposed and the interactions among the enablers and peers are highlighted. Then, a prototype of the proposed system is developed, and the data of a pilot trial is used to justify the applicability of the system. The results showed that the proposed system is efficient, and hence it is feasible to adopt into a clinical trial. With the successful development of the proposed system, it is promising to provide effective data integration and knowledge management for improving participant safety.

(Background:) Raspberry (Rubus idaeus L.) is very popular with consumers around the world for its intense flavor, attractive appearance and health benefits. In recent years, interest in healthy eating and natural products has increased, and raspberry fits perfectly into these trends, which translates into its greater importance on the consumer market. (Aim) The aim of the study was the commodity evaluation of raspberry fruits bearing fruit on 2-year-old shoots, cultivated under the conditions of varied nitrogen fertilization against the background of constant phosphorus-potassium fertilization. The first-order factor were cultivars ('Laszka' and ‘Glen Ample’), and the second-order factor was nitrogen fertilization (0, 50, 100 and 150 kg N ha-1), against the background of constant phosphorus-potassium fertilization (100 kg P2O5 and 120 kg K2O ha-1). The experiment was set up in a dependent split-plot design, in 3 repetitions. (Results) The importance of raspberry on the consumer market was shaped by: taste and quality of fruit, health benefits, naturalness and freshness, universality of use, availability and nutritional trends. (Conclusion) The tested cultivars were characterized by similar production and quality capabilities. Fertilization of the tested cultivars with a dose of 135 kg N·ha-1 turned out to be justified in terms of yield. Increasing nitrogen doses resulted in a significant increase in fresh fruit yield and 1000 fruit weight. Different doses of nitrogen increased fruit resistance to mechanical damage, firmness and improved quality indices.

In the context of market relations in agriculture in the Kyzylorda region, in order to meet the needs of animal husbandry in complete feed, it is necessary to create a solid forage base. The successful solution to the tasks of increasing the number of livestock and increasing the productivity of animal husbandry in the ecological conditions of the Aral Sea region largely depends on the timely procurement of feed and the transfer of feed production to an industrial basis. It is possible to increase the production of high-quality feeds through the introduction of high-yielding varieties, the use of new resource-saving cultivation and harvesting technologies, the optimal organization of cultivation production processes, and increasing the efficiency of the use of technical means. Of all the harvested types of feeds, alfalfa has the best effect on increasing milks yield and meat gains. The green mass of alfalfa is well-eaten by all farm animals. For example, when feeding cattle, its utilization rate is 92.6%. In terms of protein richness, alfalfa hay surpasses many other feeds, so 100 kg of alfalfa hay contains 11.6 kg of digestible protein, 1.77 kg of calcium, 0.22 kg of phosphorus, and 4.5 g of carotene. In addition, in the conditions of rice crop rotation, according to its biological characteristics, alfalfa (Medicago sativa L.) is considered indispensable in agrotechnical and reclamation relations, especially in saline soils. The economic value of alfalfa lies in its wide ecological plasticity, the ability to grow back quickly after mowing, and high productivity.

With the rise of Internet of Things (IoT) devices and Cyber-Physical Systems, the demand for more functional and high-quality software has increased tremendously. To meet this need, we must reengineer and reuse existing software, as well as develop new software formal verification methods. One such method is based on physical quantities defined by the System International, which have physical dimensions. The homogeneity of physical dimensions in software code enables us to check the software code in the space of base units, making it the first basis of the new software verification method. However, this method cannot check expressions with angles, angle speed, and other similar features. To address this, a transformation for physical value orientation introduced by Siano allows us to check software code for orientational, stabilization, and other related branches. This makes the orientational homogeneity the second basis of the new software verification method. To assess the effectiveness of the proposed method, we developed special software defect models based on the statistical characteristics of software code. We used a special statistical analysis tool to define the statistical characteristics of modern software and analyzed over 2 GB of C++ GITHUB code for drones. Based on the actual distribution of software characteristics, the proposed method can detect over 60% of latent software defects. Implementing this method can significantly reduce testing time, improve reliability, and enhance overall software quality.

Grasslands are at risk of degradation due to unsustainable management practices and climate change. Sustainable grassland soil management can promote ecosystem service delivery and improve the resilience of the entire grassland ecosystem to anthropogenic change. Here, we re-view the principal soil quality indicators (SQIs) and how they have been used to evaluate the sustainability of different grassland management practices globally. We then discuss sustainable grazing management practices, before reviewing some novel grassland species which may im-prove grassland resilience with relevance for grassland management in Europe and the UK. We also give an overview of current sustainable grassland management methods and their assessment at field scale. From this, we suggest that sustainable Grazing Management Plans (GMPs), together with the testing of drought-resistant grass species and appropriate SQIs monitoring, is key to increasing resilience of grassland ecosystems to anthropogenic change.

An out-of-hospital cardiac arrest (OHCA) is one of the leading causes of death in the world. The survival rate can be influenced by the Chain of Survival. The school is the institution that has the opportunity to promote the education of citizens in Basic Life Support (BLS), increasing the number of trained bystanders. This study aimed to identify the theoretical and practical knowledge and self-reported skills in BLS, in order to characterise the motivation to intervene in an emergency situation. A quantitative, descriptive, cross-sectional, and analytical study of the survey type was developed with a sample of 1215 students enrolled in 10th grade of secondary education in 2019-2020 in Portugal. The results point to a fragile appropriation of theoretical and practical knowledge in the field of BLS. Self-declared competences tend to rank below the theoretical knowledge manifested. Motivation to intervene is high: students are sensitive to the topic, willing to learn and highlight the importance and social relevance of the topic. We conclude that students do not feel nor are able to intervene in an OHCA episode. It seems necessary to develop didactic proposals that align the teaching of BLS with the Essential Learning at the end of compulsory education in Portugal.

The purpose of this study is to characterize atmospheric pollution and its sources in two West African urban sites during the dry season (January 2009 in Bamako, Mali, and December 2009 in Dakar, Senegal). Particulate Matter (PM) source apportionment was performed using Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF). Carbonaceous components, water-soluble inorganic compounds, and trace elements were analyzed from PM (TSP, PM10, and PM2.5) samples. The measured PM2.5 and PM10 concentrations were 5 to 10 times and 3 to 8 times higher than the 2005 WHO 24-hour standards, respectively. PCA and PMF analyses identify five sources in both cities. The sources contributing to aerosol concentrations (PM2.5 - PM10) in Bamako are motor vehicles (20-13%), solid fuel combustion (16-13%), crustal dust (24-30%), resuspended road dust (26-30%) and secondary aerosols (10-16%). During the sampling period in Bamako, dust was the most prevalent source, accounting for 63% of the total PM10 mass. In Dakar, the main identified sources were motor vehicles (28-19%), mineral dust (16-25%), industries and oil burn-ing (11-10%), sea salts (15-20%), and resuspended road particles (21-29%). The findings also indicate that anthropogenic emissions contribute significantly to the PM2.5 fraction, implying that populations are highly exposed to fine particles.

Chronic pain is a source of major alterations in quality of life. It represents significant costs for health systems, and reduces the competitiveness of the working population. Vulnerability can drive the incidence of chronic pain, through its influence on modifiable risk factors, and reduced utilization of health care systems. But vulnerability can also be the consequence of a chronic pain: illness can push people into precariousness. We analysed the factors associated with pain intensity among vulnerable persons with a chronic condition, in five European countries (N=1,364). Pain was, among the whole set of variables, the main predictor of sleep problems, fatigue, depression, self-perceived health, physical and mental quality of life. This is in line with other studies showing the major impact of pain on an individual’s health and life. Multivariable analyses, adjusting for the whole set of variables, showed that women had more intense pain, as well as participants with a lower education level. These results confirm the social component in the complex etiology of pain and clearly plaid in favor of integrated care, taking into account individual characteristics and environment.

There is immense variability in the postharvest quality of Hass avocados. However, there is a lack of knowledge to guaranteeing the robustness of fruit with consistent quality. The aims of this work were to develop a multivariate methodology for evaluating the postharvest quality of avocado and to determine predictive quality markers to manage fruit quality. Fruit samples produced under different nutrient management, elevation, date-to-harvest, and growing-cycle conditions were analyzed. The results highlighted soil and weather differences among orchards. Nutrient management practices based on index balancing in some samples increased both productivity and the fruit size. High variability was observed in the dry matter related to the age of the fruit at harvest. Ripening heterogeneity was very large in low-elevation orchards where the fruit was picked relatively early. High flesh mineral contents delayed fruit ripening. At low growing temperatures, more oleic and linoleic acids were present in fruits. The sensory texture and taste descriptors were affected by the fruit age and related to the flesh composition. Logistic, PLS-DA, and biplot models effectively represented the variabilities in the ripening pattern, composition, and sensory profile of avocado fruits and allowed the samples to be grouped according to the internal fruit quality.

In the process of image feature extraction, noise in the image will greatly affect the accuracy of edge detection. In this paper, the image is filtered to remove noise before edge detection by using the algorithm of wavelet transformation. Different wavelet functions are used to decompose image. Based on the experimental results, the best denoising wavelet function is selected. Canny algorithm is used to detect the edge of the denoised image, and the result of edge detection is evaluated according to the Pratt quality factor. It is proved that wavelet transform can improve the edge detection results.

Microbial-based biostimulants containing arbuscular mycorrhizal fungi (AMF), Trichoderma fungi and plant growth-promoting rhizobacteria (PGPR) have been applied in an open-field tomato cultivation. A two-years field experiment (2020-2021) was performed in Southern Italy on “Heinz 1534” processing tomato hybrid, using three commercial formulations characterized by different microbial consortia (MIC: Glomus spp., Rhizophagus spp., Bacillus spp., Streptomyces spp., Pichia spp., Trichoderma spp.; EKO: Glomus spp., Bacillus spp., Streptomyces spp., Pseudomonas spp., Arthrobotrys spp., Monacrosporium spp., Paecilomyces spp., Myrothecium spp., Trichoderma spp.; FID: Glomus spp., Bacillus spp., Trichoderma spp.) and comparing them to untreated control (CTRL). The effect of growing season and microorganism-based treatments on yield, technological traits and functional quality of tomato fruits was assessed. The year of cultivation (Y) affected yield (with lower fruit weight, higher marketable to total yield ratio and higher % of total defected fruits in 2020), and technological components (higher dry matter, total acidity, total soluble solids in 2020). During the first year of the trial, all evaluated treatments (MIC, EKO and FID) enhanced soluble solids content by 10%, on average, compared to CTRL. Sucrose and lycopene contents were influenced both by the microbial-based treatments and the growing season (greater values found in 2021 with respect to the first year). Y factor also significantly affected all evaluated metabolites contents, except for tyrosine, essential (EAA) and branched-chain (BCAAs) amino acids. Over two years of field trial, FID biostimulant enhanced the contents of proteins (+53.71%), alanine (+16.55%), aspartic acid (+31.13%), γ-aminobutyric acid (+76.51%), glutamine (+55.17%), glycine (+28.13%), monoethano-lamine (+19.57%), total amino acids (+33.55), essential amino acids (+32.56%) and branched-chain amino acids (+45.10%) compared to the untreated control. Our findings highlighted the valuable effect of FID microbial inoculant in boosting several primary metabolites (proteins and amino acids) in the fruits of processing tomato crop grown under Southern Italy environmental condi-tions, although no effect on yield and its components was appreciated.

COVID-19 is a well-known respiratory disease spreading worldwide since January 2020, causing many deaths and massive pressure on health systems. This pandemic’s appearance compromised the health services’ sustainability and quality as many procedures were postponed or even canceled out, with an expected increase of adverse events like nosocomial infections, in-hospital deaths, and the worsening of the patients’ clinical status. Therefore, assessing whether the healthcare providers’ performance has changed is paramount. In this case, we evaluated the public hospitals in Portugal as the leading secondary health care providers in the country, which in turn has been highly affected by the pandemic. To this end, we developed a network Data Envelopment Analysis model serially relating efficiency and effectiveness. Using 2,795 observations from public hospitals and 18 variables, we observed consistent drops in efficiency when the pandemic started, followed by a recovery to levels above the pre-pandemic ones. Regarding effectiveness, we observed a positive trend during the evaluated period. In short, these results allow us to conclude that, apart from the great resilience of public healthcare providers, the Portuguese State was not prepared for a pandemic like COVID-19, but still the actions taken (including massive vaccination) were beneficial.

Background. The European Centre for Disease Prevention and Control describes the community pharmacist as gatekeeper to the quality of antibiotic use. The pharmacist has the responsibility to guard safe and effective antibiotic use; however, little is known about how this is implemented in practice. Aims. To assess the feasibility of a method to audit the quality of antibiotic dispensing in community pharmacy practice and to explore antibiotic dispensing practices in Greece, Lithuania, Poland, and Spain. Methods. The Audit Project Odense methodology to audit antibiotic dispensing practice was adapted for use in community pharmacy practice. Community pharmacists registered antibiotic dispensing on a specifically developed registration chart and were asked to provide feedback on the registration method. Results. Altogether twenty pharmacists were recruited in four countries. They registered a total of 409 dispenses of oral antibiotics. Generally, pharmacists were positive about the feasibility of implementing the registration chart in practice. The frequency of checking for allergies, contraindications and interactions differed largely between the four countries. Pharmacists provided little advice to patients. The pharmacists rarely contacted prescribers. Conclusion. This tool seems to make it possible to get a useful picture of antibiotic dispensing patterns in community pharmacies. Dispensing practice does not seem to correspond with EU guidelines according to these preliminary results.

Prediction of protein-ligand binding affinities is crucial for computational drug discovery. A number of deep learning approaches have been developed in recent years to improve the accuracy of such affinity prediction. While the predicting power of these systems have advanced to some degrees depending on the dataset used for model training and testing, the effects of the quality and quantity of the underlying data have not been thoroughly examined. In this study, we employed erroneous datasets and data subsets of different sizes, created from one of the largest databases of experimental binding affinities, to train and evaluate a deep learning system based on convolutional neural networks. Our results show that data quality and quantity do have significant impacts on the prediction performance of trained models. Depending on the variations in data quality and quantity, the performance discrepancies could be comparable to or even larger than those observed among different deep learning approaches. In particular, the presence of proteins during model training leads to a dramatic increase in prediction accuracy. This implies that continued accumulation of high-quality affinity data, especially for new protein targets, is indispensable for improving deep learning models to better predict protein-ligand binding affinities.

This study aims to identify factors associated with anxiety levels of adults living in Singapore before the pandemic and during the COVID-19 outbreak. Data were collected using a cross-sectional web-based survey conducted from July to November 2020 accruing 264 eligible participants. Ordered logistic regression was used to assess Generalized Anxiety Disorder-7 (GAD-7), ranked as minimal (0-4), mild (5-9), moderate (10-14), and severe (15-21) before the pandemic and during the pandemic. About 74% of participants were female, 50% were aged 25-34, and 50% were married. The GAD-7 level went up from pre-pandemic for both moderate (from 12.5% to 16%) and severe GAD (from 2% to 11%). Alcohol consumption (AOR 1.79, 95% CI 1.04-3.06), loneliness (AOR 1.28, 95% CI 1.05-1.54), and difficulty in switching off social media (AOR 2.21, 95% CI 1.29-3.79) predicted increased GAD-7 levels. The quality of life (AOR 0.84, 95% CI 0.79-0.90) was significantly associated with decreased GAD-7 levels. The results heighten the awareness that early initiation of mental health support is crucial for the population in addition to the various financial support measures provided by the government as they are adapting to live with the COVID-19 pandemic.

Gender parity, is an important standard to be achieved by a society in which men and women are treated equally. The distinctions in the treatment may arise from psychology, biology, or cultural norms constructed by society. Studies show the different experiences of genders across many areas including health, education, personality, life expectancy, sports, interests, political empowerment, and careers. However, we are still far from reaching the objective, because there are conducts such as gender discrimination and expressions such as the purplewashing. In relation to feminism, purplewashing is used to define a diversity of marketing and political strategies intended at promoting people, companies, associations, and other organizations through an appeal to gender equality: they use only some of the feminist values at their convenience and in its actions, they are not really supportive of gender equality. In this opinion we aimed to address some of the reasons for inequality of opportunities based on gender; purplewashing is described as an expression that takes away the visibility of women's struggle. Additionally, we touch on some actions that promote gender equality in the family, educational, and work environments. Global leaders have an unprecedented opportunity to build gender-sensitive societies and economies. The challenges facing women today are essentially the same as they were a long time ago. It is time to break the bias.

Background: Observational health data has the potential to be a rich resource to inform clinical practice and regulatory decision making. However, the lack of standard data quality processes makes it difficult to know if these data are research ready. The EHDEN COVID-19 Rapid Col-laboration Call presented the opportunity to assess how the newly developed open-source tool Data Quality Dashboard (DQD) informs the quality of data in a federated network. Methods: 15 Data Partners (DPs) from 10 different countries worked with the EHDEN taskforce to map their data to the OMOP CDM. Throughout the process at least two DQD results were collected and compared for each DP. Results: All DPs showed an improvement in their data quality between the first and last run of the DQD. The DQD excelled at helping DPs identify and fix conformance is-sues but showed less of an impact on completeness and plausibility checks. Conclusions: This is the first study to apply the DQD on multiple, disparate databases across a network. While study-specific checks should still be run, we recommend that all data holders converting their data to the OMOP CDM use the DQD as it ensures conformance to the model specifications and that a database meets a baseline level of completeness and plausibility for use in research.

Abstract: Commercialization of extra virgin olive oil (EVOO) requires a best before date recom-mended at up to 24 months after bottling, stored under specific conditions. Thus, it is expected that the product retains its chemical properties and preserves its ‘extra virgin’ category. However, in-adequate storage conditions could alter the properties of EVOO. In this study, Arbequina EVOO was exposed to five storage conditions for up to one year to study the effects on the quality of the oil and the compounds responsible for flavor. Every 15 or 30 days, samples from each storage condition were analyzed determining physicochemical parameters, the profiles of phenols, volatile compounds, α-tocopherol and antioxidant capacity. Principal component analysis was utilized to better elucidate the relationships between composition of EVOOs and the storage conditions. EVOOs stored at -23 and 23 °C in darkness and 23 °C with light, differed from the oils stored at 30 and 40 °C in darkness. The former were associated with higher quantity of non-oxidized phenolic compounds and the latter with higher elenolic acid, oxidized oleuropein and ligstroside derivatives, which also increased with storage time. E-2-Nonenal (detected at trace levels in fresh oil) was selected as a marker of the degradation of Arbequina EVOO quality over time, with significant linear regressions identified for the storage conditions at 30 and 40 °C. Therefore, early oxidation in EVOO could be monitored by measuring E2-Nonenal levels.

Among the agricultural practices promoted by the Common Agricultural Policy to increase soil functions, the use of cover crops is a recommended tool to improve the sustainability of Mediter-ranean woody crops such as olive orchards. However, there is a broad range of cover crop ty-pologies in relation to its implementation, control and species composition. In that sense, the in-fluence of different plant species on soil quality indicators in olive orchards remains unknown yet. This study describes the effects of four treatments based on the implementation of different ground covers (CC-NAT, CC-GRA and CC-MIX) and conventional tillage (TILL) on soil erosion, soil physicochemical and biological properties, and soil microbial communities after 8 years of cover crop establishment. Our results have demonstrated that the presence of a temporary cover crop (CC), compared to a soil under tillage (TILL), can reduce soil losses and maintain good soil physicochemical properties and modify greatly the structure and diversity of soil bacterial com-munities and its functioning. The presence of a homogeneous CC of gramineous (Lolium rigidum or Lolilum multiflorum) (CC-GR) for 8 years significantly increased the functional properties of the soil as compared to TILL; although the most significant change was a modification on the bacte-rial community composition that was clearly different from the rest of treatments. On the other hand, the use of a mixture of plant species (CC-MIX) as a CC for only two years although did not modify greatly the structure and diversity of soil bacterial communities compared to the TILL soil, induced significant changes on the functional properties of the soil, and reverted those properties to a level similar to that of an undisturbed soil that had maintained a natural cover of spontaneous vegetation for decades (CC-NAT).

A complete halt on all anthropogenic activities and human movement due to COVID-19 lockdown has provided a great opportunity to assess the impact of human activities on coastal marine ecosystems. The current study assessed the concentration of the metals in water samples of the largest brackish water lagoon of Asia; the Chilika lagoon in the state of Odisha, India between pre-COVID-19 and post-COVID-19 lockdown scenarios. Monthly water samples (n=30 stations) from 0.3 m depth were collected from three sectors of the lagoon seasonally; pre-monsoon, monsoon, and post-monsoon. In addition to various physical parameters [pH, salinity, alkalinity, (DO) dissolved oxygen, (TDS) total dissolved solids, and (EC) electrical conductivity] the collected water samples were analysed for 18 trace metals (Al, As, Ba, Be, Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb, Sr, Th, Tl, U, V). Most of the physical parameters showed a significant variation between pre-and post-COVID-19 scenarios, except for pH and DO. The concentration of five metals (Be, Cd, Co, Ni, and Pb) remained below detection limits in all water samples. The impact of COVID-19 lockdown on the concentration of the metal in the water samples was noticed along with the three sectors of the lagoon. However, eight metals (Al, As, Cr, Fe, Mn, Th, U, and V) were significantly different between the COVID-19 scenarios and the remaining five metals were not statistically significant. The mean concentration of Al, As, Fe, Th, and V were higher in the pre-COVID-19 scenarios, whereas only Cr and Mn were higher in the post-COVID-19 scenarios. The mean concentration of U was similar among both COVID-19 scenarios, even though there were seasonal and sectoral differences. The seasonal influence of riverine influx was more evident on metal concentration during the monsoon season, whereas the difference between sectors was more prominent during the post-monsoon season. An increased number of correlations between physical parameters and metal concentration were observed in the post-monsoon season and post-COVID-19 scenario. This study provides evidence that the imposition of COVID-19 lockdown reduced metal influx in the water column and improved the water quality of the Chilika lagoon. Our results can be used as baseline for metal concentration in surface waters of the lagoon.

Abstract This article examines the implementation of the Swedish national environmental quality objectives and discusses what can be learnt for the equivalent process for the set of global UN 2030 goals (SDGs), established in 2015. The empirical basis is a study on 50 large companies in Sweden and their use of these objectives in their policy formulation. The SDGs are crafted with a broader approach than the Swedish national environmental quality objectives. Therefore, the SDGs probably better reflect the agenda of the business community since they have a global character, cover the whole spectrum of important sustainability issues and provide a mutual agenda for the business community world-wide. More than 90 percent of the large companies in the study have explicitly committed themselves to the SDGs, only 1-2 years after they were published, whereas similar commitments hardly exist for the national environmental quality objectives, even 20 years after its establishment. A large majority of the large companies in this study know about the SDGs, have actively endorsed them, and started to adjust their activities accordingly. At the end, the results of these endorsements remain to be seen.

The control of air quality in museums or storages is of fundamental interest for the conservation of historic artifacts. The present work reports an example of application of RFID sensors developed in the European project SensMat and dedicated to this issue. The sensors are based on the varia-tion of property of an RFID tag coupled to a sensitive silver thin film exposed to the environment. As it will be described in the paper, such low cost sensors are interrogated by a commercial reader and provide the environmental corrosivity index and thus the presence of pollutants. The selected case study concerns the monitoring of pollution by H2S in a building dedicated to conservation and restoration of archeological and historical woods. The ability of sensors to map spatially the corrosivity within buildings is highlighted.

Recently, there has been a trend towards healthy food. Consumers are looking for products that have health-promoting properties in addition to their taste. Actinidia fruit, apart from being tasty, contains valuable nutrients. They are high in vitamin C, polyphenols, and pectins and low in calories. These pro-health properties allow kiwiberry fruit to qualify in the group of so-called superfoods. All tested cultivars belong to two species of Actinidia, well tolerating conditions of moderate climate with negative temperatures in winter. The cultivars differed significantly in mineral content, color, firmness, weight and content of antioxidant substances. Summer pruning (lightening) increased the content of N, P, K, extract, and NO3 and resulted in darker fruit color. However, it slightly decreased the content of polyphenols. 'Sientiabrskaja' can be recommended for consumption as the cultivar richest in polyphenols and with the highest health-promoting values.

The CARA program has been developed since 2008 by the French reference laboratory for air quality monitoring (LCSQA) and the regional monitoring networks to gain a better knowledge at the national level on the particulate matter (PM) chemistry and its diverse origins in urban environments. It results of strong collaborations with international-level academic partners, allowing to bring state-of-the-art, straightforward and robust results and methodologies within operational air quality stakeholders (and subsequently, decision makers). Here, we illustrate some of the main outputs obtained over the last decade thanks to this program, regarding methodological aspects (both in terms of measurement techniques and data treatment procedures) as well as acquired knowledge on the predominant PM sources. Offline and online methods are used following well-suited quality assurance and quality control procedures, notably including inter-laboratory comparison exercises. Source apportionment studies are conducted using various receptor modeling approaches. Overall, the results presented herewith underline the major influences of residential wood burning (during the cold period) and road transport emissions (exhaust and non-exhaust ones, all along the year), as well as substantial contributions of mineral dust and primary biogenic particles (mostly during the warm period). Long-range transport phenomena, e.g., advection of secondary inorganic aerosols from the European continental sector and of Saharan dust into the French West Indies, are also discussed in this paper. Finally, we briefly address the use of stable isotope measurements (δ15N) and of various organic molecular markers for a better understanding of the origins of ammonium and of the different organic aerosol fractions, respectively.

Studies have found critical software malfunctions responsible for some of the worst accidents in recent times. These malfunctions are often only minor defects that snowball into large problems; a few lines of code is all it takes. Complexity, safety, quality, and resilience are among the key attributes defining a software’s operational success. There are many leading factors for complexity, such as increases in the product size, the rate of requirement changes, and the number and type of stakeholders, and failure to manage these issues efficiently always has the same consequence, i.e., massive failure and sometimes technological catastrophe. This work analyzes some of the architecture, design, and implementation guidelines used as detection and mitigation techniques. It also discusses the safety considerations, as considering how the steam industry has handled safety issues could offer some guidance for ensuring safety. Complexity in such systems also causes some of the worst side effects from the quality auditor's perspective. While failures in the software are hard to predict, one of the most significant ways of showing preparedness is practicing software resilience. New mitigation areas, such as the fragility spectrum and failure obviation, and their usage for building a safer system are analyzed. Also discussed are various architecture styles in practice and the dramatic effect human factors can have on the success of the software being developed.

The rural communities are affected by gaseous emissions from intensive livestock production. Practical mitigation technologies are needed to minimize emissions from stored manure and improve air quality inside barns. In our previous research, the one-time surficial application of biochar to swine manure significantly reduced emissions of NH3 and phenol. We observed that the mitigation effect decreased with time during the 30-day trials. In this research, we hypothe-sized that bi-weekly reapplication of biochar could improve the mitigation effect on a wider range of odorous compounds using larger scale and longer trials. The objective was to evaluate the effectiveness of biochar dose and reapplication on mitigation of targeted gases (NH3, odor-ous VOCs, odor, GHGs) from stored swine manure on a pilot-scale setup over 8-weeks. The bi-weekly reapplication of the lower biochar dose (2 kg/m2) showed much higher significant percent reductions of emissions for NH3 (33% without & 53% with reapplication) and skatole (42% without & 80% with reapplication), respectively. In addition, the reapplication resulted in the emergence of statistical significance to the mitigation effect for all other targeted VOCs. Spe-cifically, for indole, the % reduction improved from 38% (p=0.47, without reapplication) to 78% (p=0.018, with reapplication). For phenol, the % reduction improved from 28% (p=0.71, without reapplication) to 89% (p=0.005, with reapplication). For p-cresol, the % reduction improved from 31% (p=0.86, without reapplication) to 74% (p=0.028, with reapplication). For 4-ethyl phenol, the percent emissions reduction improved from 66% (p=0.44, without reapplication) to 87% (p=0.007, with reapplication). The one-time 2 kg/m2 and 4 kg/m2 treatments showed similar effectiveness in mitigating all targeted gases, and no statistical difference was found between the dosages. The one-time treatments showed significant % reductions of 33% & 42% and 25% & 48% for NH3 and skatole, respectively. The practical significance is that the higher (one-time) biochar dose may not necessarily result in improved performance over the 8-week manure storage, but the bi-weekly reapplication showed significant improvement in mitigating NH3 and odorous VOCs. The lower dosages and the frequency of reapplication on the larger-scale should be explored to optimize biochar treatment and bring it closer to on-farm trials.

An adaptive control technique has been implemented for DSTATCOM for power quality enhancement in three phase four wires(3P4W) distribution system. The reference source currents are extracted from active components of load current for each phase by using this technique. It has also been used for load balancing, harmonic suppression, power factor improvement and reactive power compensation in distribution system. The adaptive control technique has been tested at varying load in steady state and dynamic conditions. This technique is developed using MATLAB/Simulink and source side harmonics are mitigated under different load conditions which are acceptable in accordance with IEEE standard.

In the search for more efficient production systems, many changes have occurred in the strawberry production sector. Planting density is one of the management techniques that most interferes with the quality of fruits and production aspects. This study aimed to evaluate the effect of different planting densities on the photosynthetic characteristics, fruit quality, and production of the strawberry cultivar Pircinque. The study was conducted in the 2018/2019 and 2019/2020 harvests in Lages, Santa Catarina, Brazil. The treatments consisted of plant spacing of 5, 10, 15, 20, 25, and 30 cm. The experimental design was in randomized blocks, with four blocks and plots of 20 plants. Plant spacing interfered with fruit quality, photosynthetic efficiency, production, productivity, and economic return. Due to the fruits of 'Pircinque' with higher quality than other cultivars, the planting spacing between 5 and 15 cm allows meeting the fruit's main production and quality requirements. However, it is up to the producer to adapt the management if opting for higher planting densities, which allow greater economic viability of the business.

We investigate the impact of air quality and weather on the equity returns of the Shenzhen Exchange. To capture the air quality and weather effects, we use dummy variables created by employing a moving average and moving standard deviation. The important results are as follows. First, in the whole sample period (2005–2019), we find that high air pollution and extremely high temperature have significant and negative influence on the equity returns. In the sub-period I (2005–2012), the 11-day model and 31-day model show that high air pollution have significant and negative impacts on the Shenzhen stock returns. Second, the results of the quantile regression show that high air pollution have significant and negative effects during bullish market phase, and extremely high temperature have significant and negative effects during bearish market phase. This implies that the air quality and weather effects are asymmetric. Third, the weather effect of the abnormal temperature on the stock returns is greater in severe bearish market. Whereas the effect of the air pollution on the stock returns is greater in the bullish market. Fourth, the least squares method underestimates the air quality and weather effects compared to the quantile regression method, suggesting that the quantile regression method is more suitable in analyzing these effects in a very volatile emerging market such as the Shenzhen stock market.

The influence of a high inclusion level of Chlorella vulgaris, individually and supplemented with two carbohydrase mixtures, in finishing pig diets was assessed on zootechnical performance, carcass characteristics, pork quality traits and nutritional value of pork fat. Forty crossbred entire male pigs, sons of Large White × Landrace sows crossed with Pietrain boars, with an initial live weight of 59.1 ± 5.69 kg were used in this trial. Swines were randomly assigned to one of four dietary treatments (n=10): cereal and soybean meal-based diet (control), control diet with 5% C. vulgaris (CV), CV diet supplemented with 0.005% Rovabio® Excel AP (CV+R) and CV diet supplemented with 0.01% of a four-CAZyme mixture (CV+M). Animals were slaughtered, after the finishing period, with a BW of 101 ± 1.9 kg. Growth performance, carcass characteristics and meat quality traits were not influenced (p > 0.05) by the incorporation of C. vulgaris in the diets. However, the inclusion of the microalga in finishing pig diets increased some lipid-soluble antioxidant pigments and n-3 PUFA, and decreased the n-6:n-3 ratio of fatty acids, thus ameliorating the nutritional value of pork fat. Moreover, the supplementation of diets with the carbohydrase mixtures did not change (p > 0.05) neither animal performance nor meat quality traits, indicating their inefficacy in the increase of digestive utilization of C. vulgaris by pigs under these experimental conditions. It is concluded that the use of C. vulgaris in finishing pig diets, at this high incorporation level, improves the nutritional value of pork fat without compromising pig performance.

The present study investigated the effect of different ambient temperature and relative humidity (RH) but equal temperature-humidity index (THI) on laying performance, egg quality, heterophil to lymphocyte ratio (H/L ratio), corticosterone (CORT) concentration in blood, yolk and albumen, and plasma biochemical parameters in laying hens. One hundred and twenty commercial hens (Hy-Line Brown) aged 60 weeks were allocated into 2 environmental chambers. Laying hens were subjected to either one of two thermal treatments, i.e., 26ºC and 70% RH (LH75) and 30ºC and 30% RH (HL75) for 28 days. Both thermal treatments had equal THI being 75. Neither LH75 nor HL75 affected (P > 0.05) laying performance including egg production, egg weight, egg mass, feed intake, and feed conversion ratio. Plasma biochemical parameters such as total cholesterol, high-density lipoprotein cholesterol, triglyceride, calcium, magnesium, and phosphorus was not altered (P > 0.05) by thermal treatments. As to the stress indicators, both environment regimes failed (P > 0.05) to affect blood H/L ratio and CORT levels in plasma, yolk and albumen although albumen CORT levels were elevated (P < 0.05) in LH75 vs. HL75 at days 3, 7, and 28. In conclusion, our study suggests that laying hens performed and responded equally when they were exposed to equal THI environment conditioned from either 26ºC and 70% RH or 30ºC and 30% RH. The results of this study will be served as a scientific basis for management decisions and handling under thermally challenging conditions.

We investigate the impact of air quality and weather on the stock market returns of the Shenzhen Exchange. To capture the air quality and weather effects, we apply dummy variables generated by applying a moving average and moving standard deviation. Our study provides several interesting results. First, in the whole sample period (2005–2019), we find that high air pollution and extremely high temperature have significant and negative effects on the Shenzhen stock returns. In the sub-period I (2005–2012), the 11-day model and 31-day model show that high air pollution have significant and negative effects on the Shenzhen stock returns. Second, the results of the quantile regression show that high air pollution have significant and negative effects during bullish market phase, and extremely high temperature have significant and negative effects during bearish market phase. This implies that the air quality and weather effects are asymmetric. Third, the more the Shenzhen stock returns drop, the greater the effect of the abnormal temperature is. Whereas, the more the Shenzhen stock returns increase, the greater the effect of the abnormal air quality is. Fourth, the least squares method underestimates the air quality and weather effects compared to the quantile regression method, suggesting that the quantile regression method is more suitable in analysing these effects in a very volatile emerging market such as the Shenzhen stock market.

The consumption of dairy products and the dairy industry is one of the main global agro-food sectors for size, economic importance and level of technology. Microbiological quality of pasteurized milk or other milk products is dependent on microbiological quality of raw milk. A variety of microbiological count methods is available for monitoring the hygienic quality of raw milk. Among them, the pour plate method is the official essay for counting the number of colony forming units in milk samples according to ISO 4833-1:2013. The aim of the present study is the validation of the Micro Biological Survey (MBS) method, against the reference plate count method, for the assessment of the microbiological quality of raw milk. This comparative study, performed in collaboration with the “Istituto Zooprofilattico Sperimentale del Lazio e della Toscana M. Aleandri” (IZSLT), demonstrates the accuracy of this alternative method for the determination of total viable bacterial count in cow’s raw milk. The results obtained with the MBS method highlighting its potential as a valid tool for reliable microbiological analysis in dairy industries.

In this research, an attempt was made to reduce the dimension of wavelet-ANFIS/ANN (artificial neural network/adaptive neuro-fuzzy inference system) models toward reliable forecasts as well as to decrease computational cost. In this regard, the principal component analysis was performed on the input time series decomposed by a discrete wavelet transform to feed the ANN/ANFIS models. The models were applied for dissolved oxygen (DO) forecasting in rivers which is an important variable affecting aquatic life and water quality. The current values of DO, water surface temperature, salinity, and turbidity have been considered as the input variable to forecast DO in a three-time step further. The results of the study revealed that PCA can be employed as a powerful for dimension reduction of input variables and also to detect inter-correlation of input variables. Results of the PCA-Wavelet-ANN models are compared with those obtained from Wavelet-ANN models while the earlier one has the advantage of less computational time than the later models. Dealing with ANFIS models, PCA is more beneficial to avoid Wavelet-ANFIS models creating too many rules which deteriorate the efficiency of the ANFIS models. Moreover, manipulating the Wavelet-ANFIS models utilizing PCA leads to a significant decreasing in computational time. Finally, it was found that the PCA-Wavelet-ANN/ANFIS models can provide reliable forecasts of dissolved oxygen as an important water quality indicators in rivers.

This study was conducted to determine whether overcrowding in the emergency department (ED) affects the occurrence of a return visit (RV) within 72 hours. The crowding indicator of index visit was the average number of total patients, patients under observation, and boarding patients during the first 1 and 4 hours from ED arrival time and the last 1 hour before ED departure. Logistic regression analysis was conducted to determine whether each indicator affects the occurrence of RV and post-RV admission. Of the 87,360 discharged patients, 3,743 (4.3%) returned to the ED within 72 hours. Of the crowding indicators pertaining to total patients, the last 1 hour significantly affected decrease in RV (p=0.0046). Boarding patients were found to increase RV occurrence during the first 1 hour (p=0.0146) and 4 hours (p=0.0326). Crowding indicators that increased the likelihood of admission post-RV were total number of patients during the first 1 hour (p=0.0166) and 4 hours (p=0.0335) and evaluationg patients during the first 1 hour (p=0.0059). Overcrowding in the ED increased the incidence of RV and likelihood of post-RV admission. However, overcrowding at the time of ED departure was related to reduced RV.

Background: Besides anemia, iron deficiency may cause more subtle symptoms including those of the restless legs syndrome (RLS), the chronic fatigue syndrome (CFS) or sleeping disorders. Objective: The aim of this pre-planned secondary analysis was to compare the frequency and severity of symptoms associated with iron deficiency before and after (intravenous or oral) iron supplementation in iron deficient blood donors. Methods/Design: Prospective, randomized, controlled, single centre trial. (ClinicalTrials.gov: NCT01787526). Setting: Tertiary care center in Graz, Austria Participants: 138 female and 38 male whole blood and platelet apheresis donors aged ≥18 and ≤65 years with iron deficiency (ferritin ≤30ng/ml at the time of blood donation). Interventions: Intravenous iron (1 g ferric carboxymaltose, n=86) or oral iron supplementation (10 g iron fumarate, 100 capsules, n=90). Measurements: Clinical symptoms were evaluated by a survey before iron therapy (visit 0, V0) and after 8-12 weeks (visit 1, V1) including questions about symptoms of RLS, CFS, sleeping disorders, quality of life and symptoms like headaches, dyspnoea, dizziness, palpitations, pica and trophic changes of fingernails or hair. Results: We found a significant improvement in the severity of symptoms for RLS, fatigue and sleep quality (p<0.001). Furthermore, a significant decrease of headaches, dyspnoea, dizziness and palpitations was reported (p<0.05). There was no difference between the type of iron supplementation (intravenous versus oral) and clinical outcome data. Conclusion: Iron supplementation in iron deficient blood donors may be an effective strategy to improve symptoms related to iron deficiency and the wellbeing of blood donors.

This article discuss the effects of heat treatment and lubrication modes on the machinability of an A356 alloy (Al-Si-Mg); the alloy is studied as-received, with solution heat-treated alloy (SHT) as well as with an alloy that is solution heat-treated and then aged at 155, 180 and 220 °C. In the course of machinability evaluation, several criteria including cutting force, surface roughness, tool wears and burr analysis (chip) were studied. The results and analysis in this work indicated that the selected machinability criteria are important and necessary to effectively evaluate the machinability of A356 alloys. The machinability of both materials and tools were estimated in terms of cutting force, chip thickness ratio and burr formation, flank wear and roughness. The effects of different cutting parameters (cutting speed and feed rate) and lubrication modes (dry, mist and wet) on the machinability of the A356 cast alloy were also examined. The influence of heat treatments on the burr formation and surface quality was clearly revealed by the experimental results. Experimental work revealed that cutting forces were influenced significantly by aging and cutting speed. However, the different aging at 155, 180, and 220 °C and the cutting speed significantly affected the machinability of the A356 cast alloy. The results obtained show that a better drilling performance in terms of surface quality occurs at a high feed rate, with dry drilling and artificial aging at T6.

Particle size can pose a challenge to random embankment compaction control methods, where practical techniques have hardly been developed and procedural control is used instead. In order to develop new quality control procedures for slate random fill, the necessary fieldwork and laboratory tests were carried out. This involved the revision of certain methods such as the wheel-tracking or topographic settlement tests. More than six hundred in-situ density and moisture content measurements were carried out for this research. In addition, more three hundred topographic settlements and three hundred wheel-tracking carriage tests were performed. The quality control processes were completed with more than thirty plate bearing tests. Possible evidence of statistical correlations between compaction control tests were identified. An analysis of variance (ANOVA) was performed. When testing proved relationships between them, the replacement of one of them by the other was assessed by deduction. Finally, the study suggests new procedures for compaction quality control of random slate fill used in crown area.

The semi-enclosed estuary is very susceptible to changes in the physical and environmental characteristics of the inflow from the land and the coastal sea weather and so the continuous and comprehensive monitoring is necessary for managing the estuary. Nevertheless, the standard procedure or schematic framework has not been proposed appropriately to determine how many instruments are necessary and where they need to be deployed to detect critical changes. Therefore, the present work proposes a systematical strategy for the deployments of the monitoring array by using the combination of the graphical optimization with the objective mapping technique. In order to reflect the spatiotemporal characteristics of the bay, the representative variables and eigenvectors are determined by the Empirical Orthogonal Function (EOF), and the cosine angle among them are calculated for a design index of optimization. At the recommended locations, the sampled representative variables are interpolated to reconstruct their spatiotemporal distribution and compared with the distributions of the true values. Analysis confirms that the selected locations, even with a small number of points, can be used for on-site monitoring. Also, the present framework suggests how to determine installable regions for real-time monitoring stations, which reflect the global and local characteristics of the semi-enclosed estuary.

Pit lakes can represent significant liabilities at mine closure. However, pit lakes also present opportunities to provide significant regional benefit and address residual closure risks of both their own and overall project closure, and even offset the environmental costs of mining by creating new end uses. Unfortunately, many pit lakes have continued to be abandoned without repurposing for an end use. We reviewed published pit lake repurposing case studies of abandoned mine pit lakes. We found beneficial end use type and outcome varied dependent upon climate and commodity; but equally important social and political dynamics that manifest as mining company commitments or regulatory requirements. Many end uses have been realized: passive and active recreation, nature conservation, fishery and aquaculture, drinking and industrial water storage, greenhouse carbon fixation, flood protection and waterway remediation, disposal of mine and other waste, mine water treatment and containment, and education and research. Common attributes and reasons that led to successful repurposing of abandoned pit lakes as beneficial end uses are discussed. Recommendations are given for all stages of mine closure planning to prevent pit lake abandonment and to achieve successful pit lake closure with beneficial end uses.

Faecal sludge (FS) contains a significant amount of plant nutrients. After drying and composting, FS has been used as soil ameliorant in several countries. Use of FS-based compost on lettuce may meet reservations due to possible microbiological contamination. The objectives of this research are: (l) to determine the fertilizer value of different formulations of sawdust and faecal sludge compost (SDFS) pellets, (2) to compare the effect of these SDFS formulations with poultry manure, commercial compost, mineral fertilizer and non-fertilization on lettuce cultivation. The SDFS products were made by enriching and pelletized with ammonium sulphate, mineral-NPK or ammonium sulphate + muriate of potash + triple super phosphate. Lettuce was cultivated in a greenhouse and in an open field. The result showed that the fresh weight obtained from all SDFS pellets with/without enrichments were higher than those obtained from commercial compost, poultry manure, mineral fertilizer or no fertilizer. Cultivation in the open field gave higher yields than those in the greenhouse. No helminth eggs were detected in composts or lettuces. Some faecal coliforms were detected in lettuces despite fertilization treatments. A properly treated fecal sludge-based fertilizer can be a sustainable solution for lettuce production which helps urban and peri-urban agriculture.

The maintenance of high quality standards for prolonging shelf life of fruit and maintaining sensory and nutritional quality is a priority the horticultural products. The aim of this work was to test the effectiveness of a single treatment of edible coating based on Aloe arborescens and a combined treatment of 1-Methylcycyclopropene and edible coating to prolong the shelf-life of "Settembrina" white flesh peach fruit. White flesh peach fruit were harvested at the commercial ripening stage and treated with edible coating (EC) or 1-MCP +EC and stored for 28 days at 1°C. After 7, 14, 21 and 28 days fruits were removed from cold storage, transferred at 20°C and then analyzed immediately (cold out) and after 6 days (shelf life) to evaluate the combined effect of cold storage and room temperature. Weight loss, physical, chemical and sensory parameters were measured. Fruit treated with EC and 1-MCP +EC kept their marketing values better than CTR after 14 days of storage and 6 days of simulated shelf life, in terms of flesh firmness, total soluble solids and titratable acidity as well as sensory parameters. After 21 days of storage, all treatments showed a deterioration of the quality parameters. The single and combined application of Aloe-based coating (with 1-MCP) slowed down the maturation processes of the fruit, limited the weight loss and preserved its organoleptic characteristics.

The present study investigates the reliability and validity of the Positive-Negative Relationship Quality (PN-RQ) scale in Turkey. In order to determine the validity and reliability of the scale, two studies were performed. The first was carried out with emerging adults (university students) who were in a romantic relationship (148 females, 43 males, and 2 unkown) and had the main purpose to examine the structure validity of the measurement tool in the Turkish sample with an exploratory analysis. Study 2 was performed online with 513 married adults (359 females, 149 males, and 5 unknown); confirmatory findings and criterion validity studies were added. Exploratory factor analyses revealed that relationship quality had a two-factor structure and that there was also a negative relationship between the factors. Confirmatory factor analyses on the married sample showed that the bi-factor model provided evidence for the multidimensional nature of the scale. Both studies demonstrated high internal consistency.

Socioeconomically disadvantaged people are disproportionally more likely to develop obesity and obesity-related diseases. However, it remains unclear to what extent diet quality contributes to socioeconomic inequalities in obesity. We aimed to assess the role of diet quality in the association between socioeconomic status (SES) and obesity. Data originated from the national nutrition survey, a cross-sectional sample of the adult Swiss population (N=1860). We used education and income as proxies for SES; calculated the Alternate Healthy Eating Index (AHEI) as measure of diet quality; and used body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR) as obesity markers. We applied counterfactual mediation modelling to generate odds ratios, 95% confidence intervals, and the proportion mediated by diet quality. Individuals with less than a tertiary education were two to three times more likely to be obese, regardless of the marker (OR; 95% CI: 3.36 (2.01, 5.66) using BMI; 2.44 (1.58, 3.75) using WC; 2.48 (1.63, 3.78) using WHR; and 2.04 (1.43, 2.96) using WHtR). The proportion of the association between educational level and obesity that was mediated by diet quality was 22.1% using BMI, 26.6% using WC, 31.4% using WHtR, and 35.8% using WHR. Similar findings were observed for income. Our findings suggest that diet quality substantially contributes to socioeconomic inequalities in obesity while it does not fully explain them. Focusing efforts on improving the diet quality of disadvantaged groups could help reduce social inequalities in obesity.

Shenzhen is China’s top ten clean air city and the cleanest air megacity. Even so, epidemiologic studies have shown ambient air pollution had significant adverse impacts on human health in this less polluted city. In this study, the concentrations of six criteria air pollutants (PM2.5, PM10, O3, NO2, SO2, and CO) from 2014 to 2017 were analyzed and compared to thresholds of both national and international air quality standards. The results showed concentrations of all air pollutants were below target values of current national air quality standard, but levels of particulate matter (PM) and O3 were still much higher than the recommended levels by the World Health Organization. Within national air quality standards, the number of over-limit days was rare with few variations between highly polluted and low pollution areas. The air quality improvement was slowing down recently. Our results suggest annual and daily thresholds for PM are too loose for air quality improvement in Shenzhen. Hence, we call for evaluation and establishment of tougher air quality standard.

The present study was carried out at the north-eastern part of Bangladesh to investigate organochlorine pesticide (OCP) residues and microbiological quality of dried barb (Puntius sophore). Samples were collected from both producers and retailers from December 2016 to April 2017. A control sample was also prepared with the same raw fish used by the producers in the laboratory to compare the result. Gas Chromatography with Electron Capture Detector (GC-ECD) was used to detect and quantify OCP residues. Around 22 % (6) samples out of 27 were found contaminated with OCP residues. Among these six adulterated samples, four were from retailers and two from producers. Only Aldrin was detected in four samples and rest two samples were detected with both Aldrin + Dieldrin and Aldrin + Endrin. Aldrin was found between 0.332 to 0.967 ppm, Dieldrin 0.762 ppm, and Endrin 0.828 ppm. All these values were much higher than the Maximum Residual Limit (MRL) 0.1 ppm. Aerobic Plate Count (APC) of producer samples were ranged between log5.3 ± 0.02 to log5.4 ± 0.03, log6.2 ± 0.02 to log6.4 ± 0.02 for retailer samples and log5.0 ± 0.03 to log5.2 ± 0.04 for control samples. While fungal count was ranged between log3.2 ± 0.04 to log3.5 ± 0.04, log3.4 ± 0.04 to log3.6 ± 0.03 and log2.2 ± 0.05 to log2.5 ± 0.03 for producer, retailer and control samples respectively. All the producer and retailer samples and one-third of the control samples were found contaminated with Escherichia coli. Whereas, Salmonella sp. was detected as 13.3% in producer samples, 20% in retailer samples except for the control. In case of Vibrio sp., maximum count was found for retailer samples (13.3%), whereas, producer and control samples showed no detection. The finding of the present study revealed the presence of pesticides and poor microbiological quality of dried barb are alarming for the consumers of Bangladesh and which may cause chronic disease and potential long-term risk for human health.

Quality control (QC) may be a lengthy and tedious process. As a result, most data users use data from meteorological services without performing data quality checks. The South African Weather Service (SAWS) re-established the national solar radiometric network comprising of 13 new stations within the six climatic zones of the country. This study reports on the performance results of the Baseline Surface Radiation Network (BSRN) QC procedures applied to the solar radiation data within the SAWS radiometric network. The overall percentage performance of the SAWS solar radiation network based on BSRN QC methodology is 97.79%, 93.64%, 91.6% and 92.23% for Long Wave Downward Irradiance (LWD), Global Horizontal Irradiance (GHI), Diffuse Horizontal Irradiance (DHI) and Direct Normal Irradiance (DNI) respectively with operational problems largely dominating the percentage of bad data. The overall average performance of the Surface Solar Radiation Dataset – Heliosat (SARAH) data records for the GHI estimation for all the stations showed a Mean Bias Deviation (MBD) of -8.28 Wm^-2, a Mean Absolute Deviation (MAD) of 9.06 Wm^-2 and the Root Mean Square Deviation (RMSD) of 11.02 Wm^-2. The correlation (quantified by R²) between ground-based and SARAH-derived GHI time series was ~ 0.98. The established network has the potential of providing high quality minute solar radiation data sets (GHI, DHI, DNI and LWD) and auxiliary hourly meteorological parameters vital for scientific and practical applications in renewable energy technologies in South Africa.

Water, soil/sediment, and 36 fish samples were collected at three major sites along Flint Creek in 2015-2016 and analyzed for total organic carbon (TOC), dissolved organic carbon (DOC), total mercury (tHg), and other water quality indicators. This study was a follow-up to a 2012 study that revealed elevated tHg levels in fish, resulting in a public health advisory. This study revealed tHg concentrations in water below the detection limit (0.0002 ppm); while, tHG in soil/sediment ranged from < 0.0133 ppm to 0.0682 ppm dry weight. No temporal trends existed, but tHG tended to increase with TOC. Mercury levels in sediment were below the threshold effects level suggested as a preliminary screening level by the National Oceanic and Atmospheric Administration (acute = 1.4, chronic = 0.77 ppb). In summary, tHg levels were low; posing little risk to drinking water. Soil/sediment levels were generally higher and could pose risk to aquatic species.

The sustainability of irrigated agriculture depends on the quality of irrigation water used. The electrolyte concentration (EC) of irrigation water may lead to the accumulation of salts in the root zone layers and affect the physiological functions of the crop by osmotic and ion toxicity effects. Further, the cationic and anionic composition of the water may alter the exchangeable cation composition of the soil and as well as its pH. Because of the dominance of sodium salts in many sources of irrigation water, parameters related to sodium such as exchangeable sodium percentage (ESP) of soils and sodium adsorption ratio (SAR) of soil solutions have been commonly used to study the effects of sodium in irrigation water on soil structural stability. Quirk and Schofield concept of ‘threshold electrolyte concentration’ (TEC) has shown the importance of electrolytes in preventing the effects of sodium on soil structure. Based on this concept, several models have been proposed to relate ESP or SAR with EC to predict the possible impacts of irrigation water on soil structural stability. However, many research reports indicate that this relationship varies with soils and a given model is not suitable for all types of soils. Further, the effects of potassium and magnesium in the processes leading to clay dispersion are disregarded in these models. This essay analyses all the factors involved in the structural failure of soils with different cationic composition, identify the defects in these TEC models and re-defines TEC on the basis of new insights on dispersive and flocculating charges of soils. This review does not deal with EC effects on crops and also the role of contaminant ions not involved with soil structural stability.

Grading of rice grains has gain attentions due its requirement of quality assessment during import or export. Rice grain quality depends on milling operation, where rice hull is removed with a huller system followed by whitening operation. In such process, adjustment of rollers, control, and operation is important in terms of quality of milled rice. Especially, the basmati rice needed more quality assurance as it is not parboiled rice and exported globally with a high product value. In this present work, the basic problem of quality assessment in rice industry is addressed with digital image processing based technique. Machine vision and digital image processing provide an alternative with the automated, nondestructive, cost-effective, and fast approach as compared with traditional method which is done manually by human inspectors. A model of quality grade testing and identification is built based on morphological features using digital image processing and knowledge based adaptive neuro-fuzzy inference system (ANFIS). The qualities of rice kernels are determined with the help of shape descriptors and geometric features using the sample images of milled rice. The adopted technique has been tested on a sufficient number of training images of basmati rice grain. The proposed method gives a promising result in an evaluation of rice quality with 100% classification accuracy for broken and whole grain. The milling efficiency is also assessed using the ratio between head rice and broken rice percentage and it is 77.27% for the test sample. The overall results of the adopted methodology are promising in terms of classification accuracy and efficiency.

Electronic-health applications rely on large computer networks to facilitate patients' information access and to communicate various types of medical data. To examine the effectiveness of these networks, the traffic parameters need to be analysed. Due to quantity of the information carrying packets, examining each packet's transmission parameters individually is not practical, especially when a real time operation is needed. Sampling allows a subset of packets that accurately represents the original traffic to be formed. In this study an adaptive sampling method based on regression and fuzzy inference system was developed. It dynamically updates the number of packets sampled by responding to the traffic variations. Its performance was found to be superior to the conventional non-adaptive sampling methods.

This study investigated the effect of protein bread fortification with 2, 4 and 6% of cumin (Cuminum cyminum) and caraway (Carum carvi) whole seeds and by-products flour, respectively. Fortified protein bread samples were compared to control protein bread and evaluated for their sensory, color, moisture, hardness properties as well as their nutritional values. Total phenolic contents and Trolox equivalent antioxidant capacity were also analyzed. Results indicated that bread fortification shows significant effects on bread properties depending on fortification level. A higher acceptability was observed specially for bread fortified with by-products flour. Increased tendencies of color darkness, moisture content, bread hardness, nutritional values as well as total phenolic content and radical scavenging activity compared to control bread were observed as the percentage of fortification increased in both cases. The overall results showed that addition of cumin and caraway seeds and by-products flour can improve the antioxidant potential and overall quality of protein bread.

For decades, the Ébrié Lagoon in Côte d'Ivoire has been the receptacle of wastewater effluent and household waste transported by runoff water. This work assesses the spatio-temporal variability of the Ébrié lagoon water quality at the city of Abidjan. The methodological approach used in this study is summarized in three stages: the choice and standardization of the parameters for assessing water quality for uses such as aquaculture, irrigation, watering, and sports and recreation; the weighting of these parameters using the Hierarchical Analysis Process (AHP) of Saaty; and finally, the aggregation of the weighted parameters or factors. Physicochemical and microbiological analysis data on the waters of the Ébrié lagoon for June and December of 2014 and 2015 were provided by the Ivorian Center for Anti-Pollution (Centre Ivoirien Anti-Pollution, CIAPOL) and the concentrations of trace elements in sediments (As, Cd, Cr, Pb, Zn) were used. The aggregation of standardized and weighted parameters allowed the determination of the Water Quality Indices (WQI) by usage for each bays of the lagoon. The results show that in both 2014 and 2015, the waters of the Ébrié lagoon were generally of poor quality for the different uses examined in this study (aquaculture, irrigation, watering and sport and recreation) with an accentuation in 2015. However, some bays of the lagoon have waters of dubious to satisfactory quality. This study contributes an improved evaluation of the Ébrié lagoon waters.

This study examined the use of high dosages of ultraviolet germicidal irradiation (UVGI) (253.7 nm) to deal with various concentrations of air pollutants, such as formaldehyde (HCHO), total volatile organic compounds (TVOC), under various conditions of humidity. We also estimated the emission of ozone as a secondary pollutant of UVGI as treatment. A number of irradiation methods were applied for various durations in field studies to examine the efficiency of removing HCHO, TVOC, bacteria, and fungi. The removal efficiency of air pollutants (HCHO and bacteria) through long-term exposure to UVGI appears to increase with time. The effects on TVOC and fungi concentration were insignificant in the first week; however, improvements were observed in the second week. No differences were observed among the various irradiation methods in this study regarding the removal of HCHO and TVOC; however significant differences were observed in the removal of bacteria and fungi.

Indoor air quality and public health have always been an area of prime interest across the globe. The significance of low-cost air quality sensing and indoor public health practices spikes during the time of pandemic and epidemics when indoor air pollution becomes a threat to living beings especially human beings. Indoor diseases are hard to diagnose if they are due to the indoor environmental conditions. A major challenge was observed in establishing a baseline between the indoor air quality sensors and associated diseases. In this work, 10,000+ articles from top literature databases were reviewed using bibliometric analysis to formulate indoor air quality sensors and diseases correlation rubrics to critically review 500+ articles. A set of 200+ articles were selected based on for detailed study based on seven bibliometric indices for publications that used WHO, NIH, US EPA, CDC, and FDA defined principles. This review has been conducted to assist end-users, public health facilities, state agencies, researchers, scientists and air quality protection agencies.

The main purpose of this study was to develop a model for predicting the quality of holes drilled in the root part of a spar of helicopter main rotor blades made of the Glass Fiber Reinforced Plastic (GFRP)-Ti multilayer polymer composite. As the main quality criterion, delaminations at the entry and exit of the drill from the hole were taken. In the experimental study a conventional drill and two modified geometry drills: a double-point angle drill and a dagger drill were used. Preliminary experiments showed the best hole quality when using modified drills, which allowed further detailed study only with both modified drills at different drilling speeds and feed rates. Its results in the form of training sets were used to build the Artificial Neural Networks (ANNs) to predict delamination at the entry and exit of drilled holes. The analysis of the fitted response functions, presented as 3D surfaces plots and superimposed contour plots, made it possible to choose the better tool - a double-point angle drill and determine the optimal area for drilling speed and feed rates, confirming that the prediction of the quality and productivity of machining composites based on ANN is an effective tool to search and quantify the quality criteria of such technologies.

Satellite-derived high-resolution soil moisture and precipitation data have become widely adopted in natural hazard and climate change research. Landslide susceptibility mapping, which often relies on static predisposing factors, faces challenges in accounting for temporal changes, limiting its efficacy in accurately identifying potential locations for landslide occurrences. A key challenge is the lack of sufficient ground-based monitoring networks for soil moisture and precipitation, especially in remote areas with limited access to rain gauge data. This study addresses these limitations by integrating static landslide conditioning factors—such as topography, geology, and landscape features—with high-resolution dynamic satellite data, including soil moisture and precipitation. Using machine learning techniques, particularly the Random Forest (RF) algorithm, the approach enables the generation of dynamic landslide susceptibility maps that incorporate both spatial and temporal variations. The work validates the method by analyzing two major landslide events and their relationship to hydrological factors, occurred during two rainfall events in 2019 in Italy. The results successfully identified high-probability landslide areas by accounting for multiple hydrogeological factors and capturing the unique patterns of rainfall and soil moisture distribution and intensity. The findings emphasize the need for further research to refine the use of high-resolution satellite precipitation and soil moisture data, particularly in identifying the optimal temporal and spatial resolutions for landslide susceptibility mapping.

This paper investigates the flexural behavior of unfired and fired one-way slabs constructed from reinforced ferronickel slag-based alkali-activated concrete. The study aims to expand the limited knowledge of large-scale testing of alkali-activated concrete structural elements, with a particular emphasis on their post-fire performance. Four slabs, each measuring 2.1 × 0.9 × 0.18 m³, were produced—two made of alkali-activated concrete and two of conventional concrete incorporating ordinary Portland cement. Both types of concrete exhibited similar compressive strengths. In each group, one slab served as a reference (control specimen—tested under monotonic four-point bending in its original state), while the other was subjected to a standard fire curve on the tensioned side before mechanical testing. The fired slabs were then tested in a cooled condition under ambient conditions. The effect of fire on the alkali-activated concrete was further examined using mercury intrusion porosity and scanning electron microscopy. The results reveal that the load capacity of structural members cast with alkali-activated concrete is only slightly lower than that of their conventional concrete counterparts (6% lower). However, the alkaliactivated slabs retain more of their stiffness and ductility after fire exposure.

Bandsaw blades are typical band-shaped cutting tools characterized by low stiffness and micro-level cutting depth, resulting in distinct wear mechanisms compared to rigid cutting tools. In this study, the wear curve and wear mechanisms of bandsaw tooth during the bandsawing of Cr12MoV cold-working steel was investigated. The tool life was divided into two stages: a rapid wear stage (Stage I) and a homogeneous wear stage (Stage II). In Stage I, the wear was dominated by chipping although multiple wear mechanisms were found due to the relatively poor manufacturing accuracy compared to rigid cutting tools, which results in remarkable differences among the cutting depths of individual teeth. In Stage II, abrasive and adhesive wear were the primary wear mechanisms instead of chipping, which was related to the microstructure of Cr12MoV. Furthermore, methods for increasing the bandsaw performance were proposed based on the tooth wear mechanisms.

BACKGROUND: Qu-aroma is a critical quality indicator for medium-high temperature Daqu (MT-Daqu), significantly influencing the aroma profile of strong-aroma Baijiu (SAB). SAB is produced across various regions in China, each with unique environmental conditions and production techniques. These regional differences are likely to cause variations in the Qu-aroma of MT-Daqu. Despite this, comprehensive research on the variations in Qu-aroma across different regions has been lacking. This study aims to address this gap by utilizing Gas Chromatography-Olfactometry-Mass Spectrometry (GC-O-MS) and electronic nose (E-nose) technology, combined with sensory evaluation, to analyze the differences in Qu-aroma characteristics and volatile compound profiles of MT-Daqu from seven distinct production areas.RESULTS: Sensory analysis identified seven broad aroma categories and 25 specific aromas characterizing the Qu-aroma of MT-Daqu samples. Chen aroma and roasted aroma were notably more prevalent in MT-Daqu samples from Sichuan compared to those from other regions (P < 0.05), while the fermentation aroma was less prominent in Sichuan samples. In total, 123 volatile compounds were detected in MT-Daqu, with 46 classified as aroma-active compounds. Among these, 21 aroma-active compounds were identified as markers distinguishing Sichuan MT-Daqu from those produced in non-Sichuan regions, showing significant differences in their concentrations (P < 0.05). Additionally, six major aroma-active compounds-ethyl isovalerate, ethyl heptanoate, hexanal, 1-nonanal, (E)-2,4-decadienal, and 2,3-dimethyl-5-ethylpyrazine-were found to significantly contribute to the aroma differences between Sichuan and non-Sichuan MT-Daqu.CONCLUSION: This study delineates the distinct Qu-aroma characteristics of MT-Daqu from various SAB production areas and identifies the aroma-active compounds responsible for these differences. The insights gained from this research offer valuable guidance for optimizing flavor profiles in MT-Daqu production, potentially enhancing the overall quality and regional distinctiveness of the product.

In this paper, we demonstrate a method of measuring the flexural elastic modulus of ceramics at an intermediate (~millimeter) scale, at high temperatures. We used a picosecond laser to precisely cut micro-beams from the location of interest in a bulk ceramic. They had a cross-section of approximately 100 μm × 300 μm, and a length of ~1 cm. They were then tested in a thermal-mechanical analyzer at room temperature, 500°C, 800°C, and 1100°C using the four-point flexural testing method. We compared the elastic moduli of high-purity Al2O3 and AlN measured by our method with the reported values in the literature and found that the difference was less than 5% for both materials. This paper provides a new and accurate method of characterizing the high-temperature elastic modulus of miniature samples extracted from representative/selected areas of bulk materials.

Land subsidence is an environmental hazard occurring gradually over time, potentially posing significant threats to the structural stability of civilian buildings and essential infrastructures. This study presented a workflow using the SBAS-PSInSAR approach to analyze surface deformation in the Choushui River fluvial plain (CRFP) based on Sentinel-1 SAR images and validated against precise leveling. Integrating InSAR results with hydrogeological data, such as groundwater levels, multilayer compactions, and borehole loggings, a straightforward model was proposed to estimate appropriate groundwater level drops to minimize further subsidence. The results showed a huge subsidence bowl centered in Yunlin, with maximal sinking at an average 60 mm/year rate. High-resolution subsidence maps enable the quantitative analyses of the safety issues for Taiwan High Speed Rail (THSR) across the considerable subsidence areas. In addition, the analysis of hydrogeological data revealed that half of the major compaction in the study area occurred at shallow depths. Based on a maximal subsidence control rate of 40 mm/year specified in the CRFP, the model results indicated that the groundwater level drops from wet to dry seasons needed to be maintained from 3-5 m for the shallowest aquifer and 4 – 6 m for aquifers 3 and 4. The workflow demonstrated the compatibility of InSAR with traditional geodetic methods and the effectiveness of integrating multiple data sources to assess the complex nature of land subsidence in the CRFP.

This study investigated the aerodynamic performances of various trains with different nose shapes, using as design variables two angles α,β for the heads shape and the bluntness angle γ, without crosswind. The effect on aerodynamic performances, such as the train drag coefficient, pressure distribution along the train surface, flow structures around the train and the wake, head pressure pulse, were analyzed. The results indicate that the increase of the train nose length for flat shapes decreases the CD values by 21.47% and 19.11%, decreasing the high-pressure region in the leading head. The duck-nose configuration emerges as a compromise between drag reduction and nose length. Increasing the angle γ a further drag reduction of 8.5% is featured. Drag formation along the train is also analyzed. The steeper the variation of the geometry, the higher the peak intensity and the slope of the curve. Regarding the flow features around the train, two-main counter-rotating vortices are captured in the wake. Moreover, the higher the nose length and the higher the bluntness angle γ, the weaker and narrower the wake. Again, a longer nose shape yields to a softer jump in terms of pressure difference, crucial for train homologation and safety.

The purpose of this study was to establish the association between total and segmental body composition (BC) variables and anaerobic performance and to create optimal models that best predict such performance in CrossFit® (CF) athletes. Fifty athletes, 25 males and 25 females (age: 33.26 ± 6.81 years; body mass: 72.57 ± 12.17 kg; height: 169.55 ± 8.71 cm; BMI: 25.06 ± 2.31 kg·m−2) were recruited to participate and underwent BC analysis using dual-energy X-ray absorptiometry (DXA) and an all-out laboratory test on a cycle ergometer (Wingate) to determine their anaerobic performance. The results show a significant correlation between BC values and performance, ranging from moderate (r = -0.34, p = 0.015) to near-perfect (r = 0.96, p &lt; 0.01). Furthermore, the created performance prediction models exhibited predictive capacities ranging from 19% (p = 0.017) to 93% (p &lt; 0.001). All prediction models were created using total or segmental lean mass variables, excluding others. BC and performance variables found significant differences between males and females. The findings demonstrate that BC variables are crucial indicators of anaerobic performance in CF athletes. Professionals responsible for athlete performance should use this information to monitor athletes and design training programs.

Diffusion magnetic resonance imaging (dMRI) is an imaging technique that provides information on the microstructural organization of biological tissue. dMRI allows for non-invasive visualization and quantitative assessment of white matter architecture in the brain by characterizing restrictions on the random motion of water molecules. Ultra-high field MRI scanners, such as those operating at 7 Tesla (7T) or higher, can boost signal-to-noise ratio (SNR) to improve dMRI compared with what is attainable at conventional field strengths such as 3T or 1.5T. However, at 7T wavelength effects cause lower transmit magnetic field efficiency in the human brain, mainly in the posterior fossa region, manifesting as signal dropouts in this region. Recently, we reported a simple approach of using a wireless radiofrequency (RF) surface array to improve transmit efficiency and signal sensitivity at 7T. Here we demonstrate the feasibility and effectiveness of using this RF enhancer for in-vivo dMRI at 7T. The use of the RF enhancer can effectively recover signal dropouts in the regions with intrinsically lower SNR such as cerebellum, leading to a better depiction of principal fiber orientations and enhanced visualization of extended tracts to the brainstem and pons enabling more comprehensive delineation of the full white matter architecture.

In the realm of high-pressure vessel simulation, conventional finite element method (FEM) approaches, as per ASME standards, may inadequately predict the behavior of flat surfaces under elevated temperatures. This study challenges the efficacy of shell-type mesh modeling for high-temperature flat plates, demonstrating that the thermal conditions within such high-pressure vessels can induce thermal instability and buckling, not accounted for by traditional FEM methods recommended by ASME. Through comprehensive analytical investigations, we reveal that traditional shell-type meshing techniques, while suitable for certain applications, fail to capture the intricate thermal stresses and deformation patterns inherent in high-temperature flat plate configurations. Our analysis delineates distinct stability regimes governed by key design parameters—including plate thickness, operating temperature, and geometric dimensions—profoundly impacting the structural integrity of heating plates under thermal loading. By elucidating these stability boundaries, this research provides engineers with critical insights necessary for optimizing the design and performance of high-temperature equipment. This includes the design of high-pressure vessels with flat surfaces for heating materials, flanges in high-temperature environments, and fins in heat exchangers across various industries such as oil and gas, pyrolysis, and power plants. The findings presented herein serve as a valuable reference for engineers seeking to comprehend and mitigate instability phenomena in solid mechanics, offering practical guidance for developing robust and reliable high-temperature structures in demanding industrial environments.

Overconsumption of an unbalanced diet and overweight, leading to insulin resistance, dyslipidemia, hepatic steatosis, cardiovascular diseases and obesity, is nowadays a worldwide health issue, with different patterns of metabolic disturbances in the young and adult popula-tions, in both gender. Preclinical models that closely mimic the gradual weight gain that occurs in humans upon consumption of a “western-type” diet (WD) are of great interest. In particular, the diet-induced obesity (DIO) model in the C57BL/6J mouse sub-strain is often used in biomed-ical research, considering that it is prone to metabolic disorders and obesity, and is widely used to generate genetically modified mice. This study aimed to phenotypically characterize the C57BL/6J mouse strain fed a WD-like diet, using high-frequency ultrasound imaging (HFUS) as a complementary tool to longitudinally monitor morphofunctional changes in the liver, heart and kidney associated with DIO. Long term WD feeding increased mice body weight (BW), liver/BW ratio and body condition score (BCS), serum transaminases, glucose and insulin, as well as Homeostasis model assessment (HOMA) indexes, and caused dyslipidemia and insulin resistance. According to the 3Rs, ultrasound imaging has enabled a comprehensive study of metabolic syndrome in mice, in vivo and non-invasive, improving the identification of early stages of diseases.

There are few results about the internal damping ratio of normal and high strength concretes. Hence, this paper presents the expansion of the investigation about internal damping ratio under undamaged and damaged conditions, for usual concretes (NSC) and high strength concretes (HSC). In this way, the study cover a strength range of 42 to 83 MPa. Cyclic load was employed by a servo-controlled hydraulic testing machine and for each cyclic step the dynamic elastic modulus (Ed) and internal damping ratio (ξ) were determinate by acoustic tests. Normal strength concretes (fc = 42MPa) presented undamaged internal damping ratio ξ = 0.5% and achieved the maximum value of ξ = 2.5 for a damage index equal to 0.8. High strength concretes mixtures (fc = 83MPa) presented an undamaged internal damping of ξ=0.29% and maximum internal damping equal to ξ=0.93% (under damage index of 0.32). Porosity and the transition zones were the responsible to the initial internal damping values and how the material behavior under each cyclic load. The progressive damage generates the increase of coulomb damping. There are few studies allowing the quantification and comprehension of internal damping ratio under damage cyclic loading and this approach will lead to improve the understanding of NSC and HSC under dynamical excitation subject to damage evolution, mainly in impact situations.

The major challenge in the current context of a rising world’s energy demand is to limit the global temperature increase for mitigating climate change. This goal requires a large reduction of CO2 emissions, mainly produced by power generation and industrial processes using fossil fuels. In this study, a novel methodology for K2CO3-doped Li4SiO4 sorbents production for CO2 capture at high temperature was adopted based on the Design of Experiments (DoE). Different synthesis (temperature and K2CO3 content) and adsorption conditions (sorption temperature and CO2 concentration) were systematically tested by Response Surface Methodology (RSM) to obtain predictive models of CO2 uptake and Li4SiO4 conversion. The results of RSM analysis evidenced a maximum adsorption capacity of 196.4 mg/g for a sorbent produced at 600 °C and with 36.9 wt% of K2CO3, tested at 500 °C and 4 vol% of CO2. Whereas at 50 vol% of CO2, the best uptake of 295.6 mg/g was obtained with a sorbent synthesized at 600 °C, containing less K2CO3 (17.1 wt%) and tested at higher temperature (662 °C). The obtained results highlight that K2CO3-doped Li4SiO4 sorbents can be tailored for maximizing CO2 capture at different operating conditions, making them suitable for use in industrial processes.

Increased activity of transforming growth factor-beta (TGF-β) is a key factor mediating kidney impairment in diabetes. Glomerular podocytes, the crucial component of the renal filter, are a direct target of TGF-β action, resulting in irreversible cell loss and progression of chronic kidney disease (CKD). Urolithin A (UA) is a member of the family of polyphenol metabolites produced by gut microbiota from ellagitannins and ellagic acid-rich foods. The broad spectrum of biological ac-tivities of UA makes it a promising candidate for the treatment of podocyte disorders. In this in vitro study, we investigated whether UA influences the changes exerted in podocytes by TGF-β and high glucose. Following a 7-day incubation in normal (NG, 5.5 mM) or high (HG, 25 mM) glucose the cells were treated with UA and/or TGF-β1 for 24 hours. HG and TGF-β1, each independent and in concert reduced expression of nephrin, increased podocyte motility and up-regulated expression of b3 integrin and fibronectin. These typical for epithelial-to-mesenchymal transition (EMT) effects were inhibited by UA in both HG and NG conditions. UA also reduced the typically elevated in HG expression of TGF-β receptors and activation of TGF-β signal transducer Smad2. Our results indicate that in podocytes cultured in conditions mimicking diabetic milieu, UA inhibits and reverses changes underlying podocytopenia in diabetic kidneys. Hence, UA should be considered as a po-tential therapeutic agent in podocytopathies.

The higher education sector in Africa has experienced remarkable growth over the past decades, enrolling and graduating millions of students annually. Despite this progress, high unemployment rates among graduates and pervasive underdevelopment have raised questions about the relevance of higher education in Africa. Critics have intensely scrutinized the quality of curricula, highlighting a significant mismatch between the skills offered and the demands of the job market. This disconnect is often due to curricula that are unresponsive to both job requirements and students' needs. Enhanced pedagogical approaches are essential to address this issue. Community engagement and service learning (CE&SL) offer promising solutions by bridging the gap between theoretical knowledge and practical application. Recognizing the potential benefits, higher education institutions across the continent are gradually integrating CE and SL into their teaching and research frameworks. However, the adoption of these approaches has been slow. This paper explores the opportunities and challenges hindering the effective and widespread implementation of CE and SL in African higher education institutions and proposes practical strategies to overcome these obstacles. By embracing these innovative approaches, African universities can better prepare graduates for the dynamic job market and contribute more effectively to the continent's development.

Coastal environments are complex systems that are influenced by a combination of natural processes and human activities. Scientific interest in the effects of coastal erosion/accretion and climatic change-related processes greatly increased in recent decades due to the growing human development along coastal areas. This paper investigates the state and evolution of beach-dune systems for the 1977-2001 and 2001-2019 periods of the Mediterranean coast of Andalusia (Spain) using two different proxies: the dune toe line, which was used to track foredunes evolution, and the high-water line, which was used to assess shoreline evolution. Results showed a general erosional behavior of the studied beach-dune systems and identified cases where the main trend was altered through human interventions. In the 1977-2001 period, 54% of foredunes showed erosion, 24% accretion and 22% stability while and 34% of shorelines showed erosion, 40% accretion and 34% stability. In the 2001-2019 period, 42% of foredunes showed erosion, 28% accretion and 30% stability, and 40% of shorelines showed erosion, 34% accretion and 26% stability. Combining the evolution classes of each proxy (dune toe/shoreline) allows the behavior of both shoreline proxies to be assed together and provides insights additional to those derive from the use of a single proxy. In this regard, Erosion/Erosion (EE) was the most frequent behavior, with 25% and 27% in the first and second periods respectively, and Accretion/Accretion (AA), with 17% in both periods. Erosion of foredunes combined with stability or accretion of the shoreline (ES and EA) were the most common pairings in the first period, while stability of dunes combined with accretion of the shoreline (SA) and Stability/Stability (SS) dominated in the second period. The results obtained provide additional insights on the nature and drivers of coastal change that aid local coastal managers and administrations in understanding erosion processes. The method can be applied at other areas around the world where a similar data base is available.

Abstract Purpose: This study aims to evaluate the potential of multimodal ultrasound techniques in improving the visibility of liver lesions that are indistinct under conventional ultrasound. Specifically, we will explore the application of fusion imaging, contrast-enhanced ultrasound (CEUS), and high-frequency ultrasound in enhancing the visibility of liver masses. These techniques will be utilized to assist in visualizing liver lesions and to accurately localize them for the purpose of performing percutaneous tissue biopsy. Lastly, we will compare the biopsy results with the final diagnosis to assess whether multimodal techniques can enhance the success rate of percutaneous biopsy for liver masses that are not clearly visible under conventional ultrasound. Furthermore, the potential impact of these techniques on the development of personalized treatment strategies for patients was also discussed. Materials and Results: A retrospective analysis was conducted on 144 patients with liver masses who underwent conventional ultrasound examinations at our hospital from October 2018 to January 2024. These patients had poor visibility on conventional ultrasound, but the tumor location was visible on abdominal computerized tomography (CT) or magnetic resonance imaging (MRI) scans. We excluded 71 patients who did not undergo percutaneous liver tumor biopsy and 8 patients who remained non-visualized under multimodal ultrasound. Finally, 95 patients met the inclusion criteria and their clinical and radiological data were selected for analysis. Computerized tomography or magnetic resonance imaging-ultrasound (CT/MR-US) fusion imaging was performed in 55 patients, CEUS was conducted in 95 patients, and high-frequency ultrasound examination was performed in 21 patients. The visibility of the lesions using these three techniques was evaluated, and the consistency between the biopsy pathology and the final diagnosis was analyzed. Results: In the study, a total of 39 cases were identified as solitary liver lesions, 34 cases as multiple lesions, and an additional 23 cases as diffuse hepatocellular carcinoma. Among them, there were 13 cases (13.7%) of lesions located in the left lobe, 73 cases (76.8%) in the right lobe, and 9 cases (9.4%) at the junction of the left and right lobes. The average maximum diameter of the lesions was 2.7 cm (ranging from 0.7 cm to 10.0 cm). The detection rates of lesions using CT/MR-US fusion imaging, contrast-enhanced ultrasound (CEUS), and high-frequency ultrasound examination were 49.1%, 96.8%, and 76.2%, respectively. All patients in the entire cohort underwent percutaneous ultrasound-guided biopsy after confirming the target location of the lesions, including 9 patients underwent percutaneous microwave ablation. No severe complications were observed. The accuracy rate of the biopsies was 91.6%, and the positive concordance rate was 91.1%. The biopsy pathology included 39 cases of hepatocellular carcinoma (HCC), 16 cases of intrahepatic cholangiocarcinoma (ICC), 22 cases of metastatic adenocarcinoma, 3 cases of hepatic adenoma (HA), 1 case of vascular sarcoma, and 1 case of mixed HCC-ICC. Among the 13 patients with negative pathology findings after biopsy, 8 cases were considered false negatives (based on follow-up laboratory tests and imaging results consistent with malignant tumor characteristics), resulting in a false negative rate of 8.9%. Conclusions: The application of multimodal ultrasound technology can significantly improve the success rate of liver lesion biopsies that are difficult to visualize using conventional ultrasound. Furthermore, it will facilitate the guidance of microwave ablation therapy for lesions using multimodal ultrasound imaging, enabling collaborative precision treatment planning for patients with clinical physicians.

An analysis of the processes of plastic deformation and acoustic relaxation in a high-entropy alloy Al0.5CoCrCuFeNi was carried out. The following have been established: dominant dislocation defects; types of barriers that prevent the movement of dislocations; mechanisms of thermally activated movement of various elements of dislocation lines through barriers at room and low temperatures. Based on modern dislocation theory, quantitative estimates have been obtained for the most important characteristics of dislocations and their interaction with barriers.

The challenge of missing data in scientific research prompts researchers to decide between imputing incomplete data or discarding observations, where discarding can lead to information loss. Various methods exist, from simple deletion to sophisticated approaches like Multiple Imputation (MI). However, these methods often fall short with high-dimensional datasets. Multiple Imputation by Chained Equations (MICE) and Random Forest (RF) proximity imputation offer promising alternatives. Therefore, in this paper, we propose integrating MICE with Bayesian random forest (BRF) to enhance imputation accuracy and predictive power, particularly in high-dimensional analyses. Our approach combines MICE’s efficiency with BRF’s robustness, offering a comprehensive solution to missing data challenges. By way of example, we provide empirical evaluations to validate its effectiveness using synthetic data of various missing data scenarios. The results from the simulations showed that the combination of BRF and MICE offered a promising strategy for high-dimensional analysis in the presence of missing data.

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.

Oral cancer represents a significant global public health challenge, contributing substantially to cancer incidence and mortality. Despite established risk factors such as tobacco use and alcohol consumption, early detection remains crucial for effective treatment. This study introduces a novel approach using a transistor-based biosensor system for detecting the P90 (CIP2A) protein. We have tested the presence of CIP2A in human leukoplakia samples that can rise into oral squamous cell carcinoma. The method employs commercially available glucose test strips functionalized with P90 antibodies, providing high sensitivity and a low limit of detection, which is five orders lower than commercial ELISA kits. A specially designed printed circuit board (PCB) facilitates accurate measurements, and the device's performance is optimized through characteristic tests. Human sample testing validates the biosensor's effectiveness in distinguishing samples after cell lysis. This study contributes to advancing accurate and cost-effective diagnostic approaches for oral pre-cancer and cancer tissues.

The objective of this study was to investigate the relationship between high-performance work systems and a company’s social performance, taking into account the organizational climate as a situational variable. Specifically, this study aimed to analyze the impact of perceptions of a high-performance work system on the perception of a company’s social responsibility (CSR) among employees of Jordanian companies with an organizational size of 300 or more. This study used 175 valid questionnaires, and SPSS and AMOS 24 were used to test the hypotheses. The results showed that there was a positive relationship between the perception of a high-performance work system and the perception of a company’s CSR. Furthermore, this study found that a positive diversity climate could enhance the positive relationship between the two. These findings suggest that high-performance work systems can contribute to the development of sustainable human resource management systems and that a positive diversity climate is essential in shaping these systems. Based on these results, it is recommended that companies implement HPWSs and encourage workforce diversity to maximize the value of CSR activities and ensure their sustainability.

Background: During the pandemic, Emergency departments were overcrowded with critically ill patients and confronted ethical dilemmas to assign respiratory support to them due to scarce resources. Quick tools to evaluate patients at admission were needed; many scores were used but inaccurate to predict outcomes. The Rox Index is an easy and fast score that reflects the respiratory status in acute respiratory failure patients, this score could predict the outcome of covid 19 patients. Hypothesis: The 24-hour difference in the Rox Index discriminate accurately the mortality and needs for mechanical ventilation of patients with covid-19. Methods: Study design: Prospective analytic study. Population: 204 Patients admitted to the emergency department from May to August 2020. Data were collected from the clinical records. The Rox Index was calculated at admission and 24h later, the difference was used to establish the outcome, a logistic regression model adjusting for age, sex, presence of comorbidities and disease severity to build and perform ROC analysis. Results: Difference in respiratory ROX Index between admission and 24h is a good predictor for death AUC 0.92 and for mechanic ventilation AUC: 0.75. Each decrease in one unit of the difference at 24h had an Odds Ratio for death risk: 1.48 (95%CI: 1.31-1.67) and for mechanic ventilation: 1.16 (95%IC: 1.1-1.23). Conclusion: The 24-hour variation of Rox Index has good predictive value and allows healthcare professionals to identify which patients will benefit from invasive treatment, especially in low resource settings where emergency physicians deal with survival.

Energy distance is used to eigenvalue distributions in this new Wishart distribution study, providing a new perspective on high-dimensional data. Multivariate statistics relies on Wishart distribution to explain covariance matrices. This analysis shows how degrees of freedom and covariance matrix configurations affect eigenvalue dispersion. We use energy distance based on eigenvalue distributions to assess Wishart distribution differences without the "curse of dimensionality" via extensive simulation simulations. This approach improves measurement accuracy and processing efficiency in distribution comparisons and enables new analytical pathways in scientific fields that need data covariance comprehension. Our results show that degrees of freedom and matrix structure considerably affect energy distances, expanding the theoretical framework and practical applications of statistical models.

The structural, elastic, and electronic properties of orthorhombic Cd2SiO4 and Hg2GeO4 were examined under varying pressure conditions using first-principles calculations based on densi-ty-functional theory employing the projector augmented wave method. The obtained cell pa-rameters at 0 GPa were found to align well with existing experimental data. We delved into the pressure-dependence of normalized lattice parameters and elastic constants. In Cd2SiO4, all lat-tice constants decreased as pressure increased, whereas in Hg2GeO4, parameters a and b de-creased while parameter c increased under pressure. Employing the Hill average method, we calculated the elastic moduli and Poisson’s ratio up to 10 GPa, noting an increase with pressure. Evaluation of ductility/brittleness under pressure indicated both compounds remained ductile throughout. We also estimated elastic anisotropy and Debye temperature under varying pres-sures. Cd2SiO4 and Hg2GeO4 were identified as indirect band gap insulators, with estimated band gaps of 3.34 eV and 2.09 eV, respectively. Interestingly, Cd2SiO4 exhibited a significant increase in band gap with increasing pressure, whereas the band gap of Hg2GeO4 decreased under pres-sure, revealing distinct structural and electronic responses despite their similar structures.

In the digital era, enhancing the heritage resources of a tourist route means describing and networking them to promote their visibility and attractiveness. Prior studies mainly assess mountainous region’s natural resources through multi-indicator descriptive evaluation. This study aims to develop a comprehensive measurement of indicator’s value while assessing the tourism development potential of mountainous rural area. It concerns the main tourist route of the UNESCO M'Goun Geopark, located in the central High Atlas of Morocco. It also involves analyzing the criteria for choosing this destination by segmenting tourists' consumption experiences. Statistical analysis of the collected data reveals five dimensions of destination choice and four visitor groups. This article proposes to discuss findings and their applicability in terms of tourism destination management and decision-making, which can help local governments to rationally allocate tourism resources and land use.

To facilitate the computation of the uniaxial compressive strength value of the cemented paste backfill under the condition of high sand-cement ratio, and to analyze the size effect of the cemented paste backfill with high sand-cement ratio under varied aspect ratios, the cemented paste backfill specimens with sand-cement ratios of 8:1-24:1 and aspect ratios of 0.5, 1, and 2 were prepared. Through response surface experiments and finite element analysis, the influence of three aspect ratios on the cemented paste backfill strength was explored, and the failure characteristics and size effect mechanisms of cemented paste backfill with various aspect ratios were analyzed. The model of strength conversion between cemented paste backfill with different aspect ratios was established. The results show that the compressive strength of the cemented paste backfill decreases with the increase of the aspect ratio under the same mass concentration and sand-cement ratio. When the aspect ratio is 0.5 and 1, the splitting failure is the main factor; when the aspect ratio is 2, the shearing failure is the main factor. The three-dimensional stress caused by the end effect of the cemented paste backfill is the main reason for the high strength when the aspect ratio is 0.5. Due to the one-dimensional stress zone generated in the middle of the cemented paste backfill with an aspect ratio of 2 in the laboratory, its strength value is closer to the actual uniaxial compressive strength value of the cemented paste backfill. The strength values of the cemented paste backfill with aspect ratios of 0.5 and 1 were higher than the actual uniaxial compressive strength values in the laboratory. The rationality of the theoretical analysis was verified by the ABAQUS analysis results. According to the experimental results, a strength conversion model between different aspect ratios is established, which can provide a reference for the design of the uniaxial compressive strength of the cemented paste backfill.

Purposes: Engaging in regular physical activity has been consistently linked to improved physical health and academic performance. Despite its known benefits, there is a concerning trend of decreased physical activity among children globally. The study primarily aims to investigate the level of physical activity among junior high school students in Taiyuan and analyze the main affecting factors from a socio-ecological perspective. Methods: A cross-sectional study was conducted, involving 650 junior high school students from 7 schools in Taiyuan, and 648 valid questionnaires were collected. Physical activity levels were assessed using the Children’s Leisure Activities Study Survey Questionnaire. Factors influencing physical activity were evaluated through the Student Perceived Factors Affecting Physical Activity Questionnaire. Results: In this study, students from the 7th, 8th, and 9th grades participated in physical activities, averaging 214.5 minutes per week in moderate-intensity and 25 minutes in high-intensity activities, cumulatively averaging 280 minutes weekly. Notably, a significant disparity (p<0.05) was observed in the combined duration of moderate and high-intensity activities, with male students engaging more time compared to their female counterparts (307.500 vs 255.000 minutes). This variance extended across different grades, particularly evident in 8th graders who recorded the highest weekly high-intensity activity duration (31.000 minutes) and overall physical activity time (320.500 minutes), surpassing the 7th graders. Furthermore, an exploratory factor analysis of a 32-item questionnaire, designed to identify determinants of physical activity, revealed six principal components. These components were found to positively correlate with both moderate and high-intensity physical activities. Conclusion: This study emphasizes the necessity for educational institutions and community programmes to provide engaging physical activities, especially during weekends. It highlights the importance of tailoring physical education curricula to address gender and grade differences and investing in quality sports equipment and facilities by schools and local governments.

Experimental investigations were conducted to uncover the impact of cavitation control - through the use of riblets (mesoscale surface structuring) - on cavitating flows around a circular cylinder. First, the dynamics of cavitation in the flow behind a finite cylinder (without riblets) was unveiled by visualizing the cavitation clouds and measuring the lift force fluctuations acting on the cylinder. Second, as a significant step forward, a comprehensive explanation was provided for the mechanism of cavitation control using two bio-inspired riblet morphologies positioned in different orientations and locations on the cylinder. For the first time, the effects of these tiny structures on the flow dynamics and the associated cavitation process were scrutinized. This showed that scalloped riblets, with their curved design, induced secondary vortices near their tips and distorted primary streamwise vortices, and that high velocity gradients near the jagged pattern peaks of sawtooth riblets delayed flow separation, which affected cavitation.

Genetic engineering and directed evolution are effective methods to address the low yield and poor industrialization level of microbial target products. The current research focus is on how to efficiently and rapidly screen beneficial mutants from constructed large-scale mutation libraries. Traditional screening methods such as plate screening and well plate screening are severely limited in their development and application due to their low efficiency and high costs. In the past decade, microfluidic technology has become an important high-throughput screening technology due to its fast speed, low cost, high automation, and high screening throughput, and it has developed rapidly. Droplet-based microfluidic high-throughput screening has been widely used in various fields such as strain/enzyme activity screening, pathogen detection, single-cell analysis, drug discovery, and chemical synthesis, and has been widely applied in industries such as materials, food, chemicals, textiles, and biomedicine. In particular, in the field of enzyme research, droplet-based microfluidic high-throughput screening has shown excellent performance in discovering enzymes with new functions, improved catalytic efficiency or stability, acid-base tolerance, etc. Currently, droplet-based microfluidic high-throughput screening technology has achieved high-throughput screening of enzymes such as glycosidase, lipase, peroxidase, protease, amylase, oxidase, and transaminase, as well as high-throughput detection of products such as riboflavin, coumarin, 3-dehydroquinate, lactic acid, and ethanol. This article reviews the application of droplet-based microfluidics in high-throughput screening, with a focus on high-throughput screening strategies based on UV, visible, and fluorescence spectroscopy, including labeled optical signal detection screening, as well as label-free electrochemical detection, mass spectrometry, Raman spectroscopy, nuclear magnetic resonance, etc. Furthermore, the research progress and development trends of droplet-based microfluidic technology in enzyme modification and strain screening are also introduced.

Cavitation resulting from underwater explosions in compressible multiphase or multicomp-onent flows presents significant challenges due to the dynamic nature of shock-cavitation-structure interactions, as well as the complex and discontinuous nature of the involved interfaces. Achieving accurate resolution of interfaces between different phases or components, in the presence of shocks, cavitating regions, and structural interactions, is crucial for modeling such problems. Furthermore, pressure convergence in simulations involving shock-cavitation-structure interactions requires accurate algorithms. In this research paper, we employ the diffuse interface method, also known as the interface capturing scheme, to investigate cavitation in various underwater explosion test cases near different surfaces; free surface and a rigid surface. The simulations are conducted using the Unstructured Compressible Navier-Stokes (UCNS3D) finite volume framework employing central-weighted essentially non-oscillatory (CWENO) reconstruction schemes, utilising the five-equation diffuse interface family of methods. Quantitative comparisons are made between the performance of both models. Additionally, we examine the effects of cavitation as a secondary loading source on structures, and evaluate the ability of the CWENO schemes to accurately capture and resolve material interfaces between fluids with minimal numerical dissipation or smearing. The results are compared with existing high-order methods and experimental data, where possible, to demonstrate the robustness of the CWENO schemes in simulating cavitation bubble dynamics, as well as their limitations within the current implementation of interface capturing.

The superficial quality of the strip is a very important issue in steel production; the profile, flat-ness, and geometry of strip are indicators of supreme quality. Considering the dimensions, the thickness is one of the most important variables in the production of strip. In the present study the elastic curve of Back Up Rolls (BUR) is analyzed, considering them as simply supported beams as well as the effect of rolls on the profile of the strip, specifically in the strip edge pro-ducing edge drop. The analysis is simulated with a model in 3D using a Finite Element Method (FEM) considering +0.039mm crown on Back Up Roll and +0.101mm crown on Work Roll (WR). The results showed that there is an instability zone of 76mm in the strip edge, this geometry is symmetrical in both ends of the strip, it was validated with the results of compact X-ray thick-ness gauge from a 4-high cold mill. This study not only provides a theoretical basis for the edge drop, but also provides the basis for the understanding of deformation on rolls used in rolling mill processes and their effect on the thickness, profile, shape, and dimensional quality of strips.

Abstract: Objectives: To establish the expression profile of N6-methyladenosine(m6A) modifications in the hippocampus of mice with diabetic cognitive impairment (DCI) and elucidate the potential regulatory mechanism. Methods: A DCI model was established by feeding a high-fat diet to C57BL/6J mice. m6A and RNA sequencing was conducted to profile the m6A-tagged transcripts in the hippocampus. Results: Methylated RNA immunoprecipitation with next-generation sequencing and RNA sequencing analyses yielded differentially m6A-modified and expressed genes in the hippocampus of DCI mice, which were enriched in pathways involving synaptic transmission and axonal guidance. Mechanistic analyses revealed a remarkable change in m6A modification levels through alteration of the mRNA expression of m6A methyltransferases (METTL3 and METTL14) and demethylase (FTO) in the hippocampus of DCI mice. Conclusions: We identified a co-mediated specific RNA regulatory strategy that broadens the epigenetic regulatory mechanism of RNA-induced neurodegenerative disorders associated with metabolic and endocrine diseases.

In order to utilize high-alumina coal gangue (HACG) as auxiliary cementitious admixture, it is of fundamental significance to thermally activating Al2O3 effectively in HACG and promoting formation of hydratable products containing Al2O3. In this paper, a new preparation technology is developed to make HACG auxiliary cementitious admixture by thermal activation of HACG-Ca(OH)2 (CH) mixture. HACG powders mixed with 20wt.% CH were calcined within a temperature range of 600-900oC, the thermal transformation and mineral phase formation were analyzed by thermogavimetric analyzer (TGA), X-ray diffractometer (XRD), scanning electron microscope (SEM) and energy dispersive X-ray spectrometer (EDS). The hydration reaction between activated HACG-CH mixture and cement was also investigated. HACG experienced a conventional transformation from kaolinite to metakaolin at 600oC and finally to mullite at 900oC. However, CH underwent an unexpected transformation process from CH to CaO, then to CaCO3, and finally to CaO again with increasing calcining temperature. These substances states were associated with dehydroxylation of CH, chemical reaction between CaO and CO2 generating from combustion of carbon in HACG, and decomposition of CaCO3, respectively. It is the formation of a large amount of CaO above 800oC that favors the formation of hydratable products containing Al2O3 in the calcining process and C-A-H gel in hydration process. The mechanical properties of HACG-cement mortar specimens were measured, from which the optimal calcination temperature for preparing HACG auxiliary cementitious admixture was determined to be 850oC. As compared with pure cement mortar specimens, the maximum 28-d flexural and compressive strength of HACG-cement mortar specimens increased by 5.4% and 38.2%, respectively.