The purpose of this study is to analyse the drivers and outcomes of the brand love derived from consumption experiences in the automobile retail sector. We examine the effects of consumers’ perceptions of perceived service quality and the trust they feel towards a car dealership (cognition) on emotions and brand love (affection), and the effects of brand love on consumers´ behavioural intentions (conation). This research provides insights into customer brand love in the automobile industry.

ITRF input data which are integrated by GNSS, SLR, VLBI, DORIS combination centers are considered to be relatively high-quality and accurate solutions. However, when utilizing these inputs, one still needs to identify outliers, rescale inaccurate covariance matrix and evaluate the precision of the observed datum information. To achieve the above-mentioned objectives, we propose a terrestrial reference frame (TRF) stacking approach to establish the single technical reference frameworks for the ITRF2014 and ITRF2020 datasets of all four technologies. As a result, roughly 0.5% or less of the SLR observations are identified as outliers, while the ratio of DORIS, GNSS, and VLBI observations are below 1%, around 2%, and ranging from 1% to 1.2%, respectively. The post-rescaling covariance scale factors are 25.07, 27.25, 18.84, 6.98 for GNSS, SLR, VLBI, and DORIS in ITRF2014 datasets, and 8.95, 14.9, 16.8, 7.78 in ITRF2020 datasets, respectively. It is shown that the consistency between the SLR scale and ITRF has improved, increasing from around -5mm in ITRF2014 datasets to approximately -1mm in ITRF2020 datasets. The scale velocity derived from fitting the VLBI scale parameter series with all epochs in ITRF2020 datasets differs by approximately 0.21mm/year from the velocity obtained by fitting the data up to 2013.75 because of the scale drift of VLBI at around 2013. The decreasing standard deviations of the Polar motion parameter (XPO, YPO) offsets between Stacking TRFs and 14C04 (20C04) indicating an improvement in the precision of polar motion observations for all of the four techniques. From the perspective of the Weighted Root Mean Square in station coordinates, the measurement precision of GNSS, SLR, and DORIS techniques has improved, while VLBI shows no significant change.

The dynamic global automotive sector is characterized by an ever-evolving demand for high-quality vehicles and accessible prices. This research tackles the issue of scrap reduction in electric motor manufacturing for the automotive industry, specifically in a Chinese company, by employing the PDCA methodology. The paper delves into the company's background and current landscape, while pinpointing the problem: specific production lines segments experiencing hi-pot issues are the primary source of scrap. The overarching goal is to design and implement a strategy that, leveraging the PDCA approach, reduces scrap generated during the eight-months subassembly (armature) manufacturing process, from its current average of 2.92% to 0.7%, ultimately enabling the company to eliminate hi-pot defects.

Remote Photoplethysmography (rPPG) has emerged as a non-intrusive and promising physiological sensing capability in HCI research, gradually extending its applications in health-monitoring and clinical care contexts. With advanced machine learning models, recent datasets collected in real-world conditions have gradually enhanced the performance of rPPG methods in recovering heart-rate and heart-rate variability metrics. However, the signal quality of reference ground-truth PPG data in existing datasets is by and large neglected, while poor quality references negatively influence models. Here, this work introduces a new imaging blood volume pulse (iBVP) dataset of synchronized RGB and thermal infrared videos with PPG ground-truth signals from the ear and its high resolution signal quality labels, for the first time. Participants perform rhythmic breathing, head-movement, and stress-inducing tasks, which help reflect real-world variations in psycho-physiological states. This work conducts dense (per sample) signal quality assessment to discard noisy segments of ground-truth and corresponding video frames. We further present a novel end-to-end machine learning framework, iBVPNet that features an efficient and effective spatio-temporal feature aggregation for reliable estimation of BVP signals. Finally, this work examines the feasibility of extracting BVP signals from thermal video frames, which is underexplored. The iBVP dataset and source codes are publicly available for research use.

This study investigated the anatomical characteristics and pulp quality of tapped Styrax sumatrana wood to facilitate its further utilization. The transverse surface of the tapped S. sumatrana was light or greyish brown in the sapwood and reddish brown in the heartwood. The resin canals of the tapped wood were formed along the growth rings at the boundaries between the heartwood and sapwood. Furthermore, microscopic analyses revealed an irregular outline and rounded epithelial cells at the edges of the intercellular traumatic resin canal (TC). Approximately 8–16 epithelial cells surrounded the resin canals. The fibers in the tapped S. sumatrana were generally thin-walled, whereas those near the TC were thick-walled. Moreover, S. sumatrana were diffuse-porous and exhibited intermediately distinct or indistinct growth ring boundaries. The vessels were mainly in radial multiples and clusters of 3–5. In addition, they showed a diagonal-to-radial pattern arrangement and a few tangential bands. Deposits were observed in some vessels in the tapped part but were absent in the untapped part. The fiber length of the tapped S. sumatrana wood was classified as moderate to extensive and categorized as 2nd grade pulp quality. Finally, the cell walls were classified as thin to moderate.

Machine performance modeling and optimization have emerged as crucial steps for process enhancement and efficiency. This study explored machine learning to model and optimize the cassava grating chamber of cassava grater for the quality production of gari. This domain remains unexplored thus far. A total of 196 graters were studied. Key variables studied included tooth diameter (TD), tooth height (TH), inter-tooth spacing (ITS), drum speed (DS), clearance (C), and moisture content of cassava (MC). Geometric mean diameter (GMD) represented mash quality. Feature importance rankings emphasized TH (0.488784), C (0.243284), TD (0.112682), ITS (0.103547), DS (0.036261), and MC (0.015442) in determining particle size (GMD) of grated mash. Machine learning models efficiently interpreted these attributes, including gradient boost regressor, linear regression, neural network, and random forest. The gradient boost regressor was the best predictive model, achieving 95.34% accuracy, RMSE (0.3291), and MAE (0.2303). The study provides a GMD predictive equation and optimized parameters for specific gari size production, offering valuable insights for tailored machinery in the cassava grating activity.

With the growing awareness of entrepreneurs and consumers of the tourism market in the field of sustainable development, it seems necessary to base hotel classification systems on an integrated approach to management quality, including fulfilment of ecological and environmental criteria. The article aims to indicate how environmental standards are implemented in the European system of hotel classification- HotelstarsUnion and the one in force in Poland. With regards to these systems, the differences in the classification criteria taken into account within the systems of hotel categorization by certifying organizations in the European Union in relation to the administrative hotel categorization system in Poland were pointed out. Particular emphasis was placed on the criteria related to environmental management in the hotel industry. Criteria related to environmental management were identified through analysis of the content of criteria of eight environmental management systems that are applicable to the contemporary hotel market. The results of the research proved that even though the HotelstarsUnion system takes into account the principles of sustainable development to a much greater extent than the Polish one, its primary weakness is that most of its criteria related to environmental ones are optional. In addition, the optional ones have higher weights than the obligatory ones. In turn, the Polish classification system makes very little reference to environmental standards. Moreover, it is not detailed and the assessment criteria are not up to date. Therefore, it is recommended that a greater number of environmental criteria is included when updating the HotelstarsUnion system, which should be obligatory for hotels to meet. In addition, the sustainability criteria included in the HotelstarsUnion system should be adapted to the policy system aimed at the hotel industry in Poland and other EU countries.

In recent times, using image-based deep learning techniques has been very useful for classifying fruits. However, mango is a particular challenge because its shelf life is directly related to the degree of maturity at the time of harvest, which is determined mainly through the visual assessment of the operators when sorting them, doing it incorrectly, coupled with the blows and compressions exposed during storage and transport, trigger the deterioration in their quality, hence the importance of this operation. In this sense, the purpose of this study focuses on designing a computational model based on Deep Learning that uses a convolutional neural network (CNN) parameterized to select mangoes according to their color tone based on their maturity stage. A dataset was established from 201 labeled images, then a CNN architecture was built, obtaining a model on which 3 criteria were evaluated: the number of convolution and grouping layers, the resolution of the input images and the number of training epochs required. As a result, an input image resolution of 32 x 32 pixels was achieved, the process included a convolution layer followed by pooling that fed another layer that processed the results and ended in an output layer with 2 neurons under the One Hot Encoding representation. The model required 20 epochs to perfect its training, achieving 96.04 % accuracy in mango image selection. This study supports the potential of CNNs in quality analysis through mango color selection, even in uncertainty scenarios.

This study investigates the moderating effect of corporate governance on the associations of internal audit and quality of internal audit with quality of financial reporting among commercial banks in the Republic of Yemen. The final sample includes 210 internal auditors, heads of internal auditors, chairpersons, and members of audit committees. Using a survey-based methodology, the results of the Smart-PL4 analysis showed a positive association between internal audit and quality of internal audit and quality of financial reporting. Interestingly, the results showed an insignificant association between internal audit, quality of internal audit, and quality of financial reporting when considering the moderating effect of corporate governance. The findings of this study contributes valuable insights to the existing literature on the influence of internal audit, quality of internal audit, and corporate governance on quality of financial reporting in developing countries, specifically in Yemen.

With end-to-end encryption for video streaming services becoming more popular, network administrators face new challenges in preserving network performance and user experience. Video ads may cause traffic congestion and poor Quality of Experience. Because of the natural variation in user interests and network situations, traditional algorithms for increasing QoE may face limitations. To solve this problem, we suggest a novel method that uses user facial emotion recognition to deduce QoE and study the effect of ads. We use open-access Face Emotion Recognition (FER) datasets and extract facial emotion information from actual observers to train machine learning models. Participants were requested to watch ad videos and provide feedback, which will be used for comparison, training, testing, and validation of our suggested technique. Our tests show that our approach beats the ITU-T P.1203 standard in terms of accuracy by 37.1%. Our method provides a hopeful answer to the problem of increasing user engagement and experience in video streaming services.

Background: Exercise is an accepted intervention to improve the quality of life (QoL) of breast cancer patients. Exercise programs have been developed and all have shown satisfactory results in improving QoL. There is a lack of research comparing different prescription modalities. The aim of this study is to evaluate the effectiveness of physical exercise (in-person, home-based, prescription) on QoL in breast cancer patients actively undergoing treatment; Methods Quasi-experimental study with randomized assignment to three groups (in-person: guided and supervised in-person exercise program; home-based exercise: guided and supervised exercise program with streaming monitoring; recommendation: exercise recommendation). Quality of life was measured using the QLQ-C30 questionnaire. Baseline and 24-week analysis. Results: The total sample analyzed was n=80. QoL improved significantly at 24 weeks in the face-to-face and home-based exercise groups, but not in the advice group. Exercise in all modalities improved fatigue, nausea, vomiting, appetite, and constipation. QoL at 24 weeks depended on active chemotherapy, tumor type, and assigned exercise group (r2 = 0.503; p < 0.001). Conclusions: QoL in breast cancer patients undergoing active treatment improves after a 24-week exercise program, especially in face-to-face and home-based exercise. Home-based exercise, streaming-based recommendation is a viable option for exercise recommendation.

The aim of the study is to explore how sharing status updated and receiving Likes on Facebook, as a form of positive social feedback, correlates with current and perceived changes in Quality of Life (QoL) Sample consisted of 1577 adult Facebook users (76.3% females; 65.9% aged 18-24, 21.9% aged 25-30, 12.3% aged > 30 years old). The study employed a longitudinal approach, collecting Facebook data from adult users over a 12-month period using the Graph API. Data were divided into 12 monthly segments. Two monthly indicators were calculated: the percentage of textual status updates and the average number of Likes per post. Current and perceived changes in Quality of Life (QoL) were administered as self-report measures. The findings indicated a positive correlation between the frequency of textual Facebook posts and the average received Likes. Furthermore, receivign more Likes was positively associated with a higher current QoL, and perceived improvements in QoL correlated with an increase in Likes over time. The study suggests that online positive social feedback, measured through Likes on Facebook, is associated with both current QoL and perceived improvements in QoL among adult Facebook users. This highlights the potential impact of online social interactions on individual well-being.

Mirror Therapy (MT) and Cognitive Therapeutic Exercise (CTE) are two neurorehabilitation techniques based on neuroplasticity and designed to enhance the functionality of the upper limb. Therefore, the aim is to assess the effectiveness of the combination of CTE and MT with task-oriented training (TOT) on fine and gross motor skills of the affected hand, as well as the functionality of the affected upper limb, autonomy, independence, and quality of life (QoL) in patients with acute stroke. This longitudinal and multicenter study involved a sample of 120 participants selected randomly and consecutively. Three groups were formed, including a control group (CG) and two treatment groups, one with MT and the other with CTE. The functionality of the upper limb, fine and gross motor skills, the quantity and quality of use of the affected upper limb, autonomy, and QoL were evaluated using various scales validated in the Spanish population at the baseline, after 20 treatment sessions, and at three months of follow-up. ANCOVA analysis was conducted, revealing statistically significant differences between assessments in the CG compared to the experimental groups (GEs), indicating a notable improvement in overall functionality, fine and gross motor skills, autonomy, and QoL in the latter. However, there were no significant differences between the GEs. Therefore, the application of either of these experimental combinations is crucial for the motor recovery, functionality, and improvement of the quality of life of individuals who have suffered a stroke.

Background: According to EWGSOP2, the diagnosis of sarcopenia is confirmed when in addition to low muscle strength, low muscle quantity or quality is present. Echo intensity (EI) determined by muscle ultrasound (US) has been proposed as an efficient method for the assessment of muscle quality. The effect of changing various US parameter settings on EI remains unclear. Therefore, the aim of this study was to assess the differences between EI values obtained by adjusting parameter settings over their entire range in a sample of middle-aged healthy subjects. Methods: Thirty-two repeated US scans of rectus femoris (RF) and rectus abdominis (RA) muscles were taken in eight men and three women with a portable Mindray M7 premium US machine, working in an Extended field-of-view, B-Mode setup, equipped with a linear 5.0-10.0 MHz transducer. The following US parameters and settings were fixed: gain 60dB, depth 6.5cm, and frequency 10 MHz. Readily adjustable parameters were dynamic range (DR), gray map (GM), line density, persistence, and IClear. A default setting DR65 was chosen as the reference setting. For each of the parameters, the settings of one single parameter of interest was changed over its entire range following a standardized protocol. The EI values were calculated using the open-source software ImageJ. Repeated measures analyses were performed to evaluate the effect of parameter settings on EI. Linear interpolation was used to determine non-significant ranges across a given parameter. Results: For the RF muscle, the EI values were significantly different across DR (p<0.001), GM (p<0.001), and IClear (p<0.001). Post hoc analysis confirmed the differences within these three settings. Echo intensity values within the range of DR55 to DR80 were not significantly different. For the RA muscle, the EI values were significantly different across DR (p=0.004) and GM (p=0.030). Post hoc pairwise comparisons revealed no significant difference with the default setting, except for DR150 (p=0.042). Conclusion: We showed that EI values differ across the DR and GM range, especially in the RF. We suggest using a DR setting within its midrange to minimize the effect of machine setting-dependent factors on EI values. These findings reconfirm the need for standardization of ultrasound echo intensity settings when applied for diagnostic purposes of muscle quality.

The primary sources of particulate matter are linked to human activity. Certain particulate emissions, particularly those of a finer nature, can significantly impact human health, making them one of the most concerning pollutants. Ultrafine particles (UFP), which have a diameter of less than 100 nm, are of particular concern due to their impact on human health and the difficulty in controlling them. The concentration of ultrafine particles (UFP) in the workplace is a growing concern and is classified as an emerging risk. Workers may be exposed to UFP through inhalation, skin absorption, ingestion, or a combination of these routes. This study aims to determine the levels of UFP exposure among workers in environments with varying direct particle emission patterns. Measurements were conducted to compare the results with the levels recommended by the WHO. The study monitored industrial workplaces with direct particulate matter emissions, such as a carpentry and a bakery, as well as social sector sites without or almost without direct particle emissions, such as a school and a health clinic. One conclusion drawn from this study is that all tasks and occupations are susceptible to high levels of UFP, exceeding WHO recommended values in virtually all monitored environments. Therefore, monitoring and controlling UFP is crucial. Further in-depth studies on this subject are also necessary..

Chrysanthemum tea, a typical health tea with the same origin as medicine and food, is famous for its unique health benefits and flavor. To clarify the influence of metabolites of different varieties of chrysanthemum tea on the formation of taste and quality differences, nontargeted metabolomics combined with electronic tongue analysis were used to characterize the correlation between metabolites profiles and taste characteristics of different quality chrysanthemum tea. Thirteen metabolites were identified as the key metabolites of the sensory quality difference between Huangju and Jinsi Huangju tea. Kaempferol, luteolin, genistein, and some quinic acid derivatives were correlated with the ‘astringent’ and taste attributes. In contrast, l-(-)-3 phenyllactic acid and L-malic acid were found to be the ‘bitterness’ and ‘umami’ in chrysanthemum tea. KEGG pathway enrichment analysis showed that the flavonoid and flavonol biosynthesis pathway had important effects on the sensory quality of chrysanthemum tea.

Inland waters pose a unique challenge for water quality monitoring by remote sensing techniques due to their complicated spectral features and small-scale variability. At the same time, collecting the high-quality reference data needed to calibrate remote sensing data products is both time consuming and expensive. In this study, we present the further development of a robotic team composed of an uncrewed surface vessel (USV) providing in situ reference measurements and an unmanned aerial vehicle (UAV) equipped with a hyperspectral imager. Together, this team is able to address the limitations of existing approaches by enabling the simultaneous collection of comprehensive in situ data together with high-resolution hyperspectral imagery. We showcase the capabilities of this team using data collected in a north Texas pond during three collections in the fall of 2020. Machine learning models for 13 variables are trained using the data set of paired in situ measurements and coincident reflectance spectra. These models can successfully estimate physical variables, including temperature, conductivity, pH, and turbidity, as well as the concentrations of blue-green algae, colored dissolved organic matter (CDOM), chlorophyll-a, crude oil, optical brighteners and the ions Ca2+, Cl−, and Na+. We extend the training procedure to utilize conformal prediction to estimate 90% confidence intervals for the output of each trained model. The maps generated by applying each trained model to the collected images reveal the small-scale spatial variability within the pond. Additionally, the permutation importance computed for each feature of the trained models highlights the spectral features relevant to each water quality variable.

The high-quality development of urban-rural integration is a vital component of China's economy, serving as a strategic response to the in-depth deployment of new urbanization and rural revitalization strategies. This integration is underscored by the promotion of entrepreneurship in agriculture, rural areas, and among farmers, which acts as a driver for fostering high-quality development in urban-rural areas through market competition. The resulting influx of resources and commodities with similar characteristics plays a crucial role in bridging the urban-rural divide. To maintain objectivity, it is important to adopt a balanced approach and refrain from using biased language. This study delves into the connotation and internal mechanism of the high-quality development of urban-rural integration, centering on the principle of 'quality'. Specifically, it examines the role of entrepreneurship in agriculture, rural areas, and among farmers, and evaluates its direct impact and transmission mechanism. The research employs balanced panel data from 41 cities in the Yangtze River Delta region spanning from 2003 to 2021. The findings reveal that entrepreneurship in agriculture, rural areas, and among farmers serves as a catalyst for promoting high-quality urban-rural development through the construction of a virtuous cycle, whereby resource factors and commodity services are exchanged. Moreover, this deep integration yields diverse effects across economic, spatial, demographic, social, and ecological domains, underscoring the necessity of continued support for entrepreneurship in agriculture, rural areas, and among farmers to facilitate a seamless urban-rural economic cycle and fully realize the benefits of high-quality development.

1) Background: Patients with neurological disorders are particularly at risk of falling and requiret functional rehabilitation. HUBER® is a motorised rotating platform that allows simultaneous work on balance, stability and strength with continuous adaptation and immediate feedback. This study aimed to measure the impact of rehabilitation with the HUBER® on the physical performance and quality of life of patients with neurological diseases requiring functional rehabilitation. 2) Methods: 32 subjects were enrolled in CHU Liège CNRF and randomly divided into 2 groups. The first group received classical rehabilitation combined with two training sessions per week on the HUBER® for 8 weeks. The second group received their usual treatment. This randomized control trial has been registered on clinicaltrials.gov under the number NCT04687293. Physical performance and quality of life were evaluated at different time. 3) Results: There was no significant difference between the 2 groups after enrolment. In terms of physical performance, an improvement in SPPB chair stand test (p=0.021) and total SPPB (p=0.003) was observed in the HUBER® group. In terms of quality of life, a higher improvement was observed overall in the HUBER® group (p&lt;0.05 between groups). 4) Conclusion: The HUBER® showed promising results in functional rehabilitation of patients with neurological pathologies, as a complement to classical rehabilitation management by physiotherapy.

Summer annual species are the most widely grown crops in the Upper Midwest, but reliance on a summer annual system has led to excessive soil and nutrient loss when crops are not present. Integrating winter rye (Secale cereale L.), known for its hardiness and environmental benefits, into the rotation can address these issues. However, there's limited understanding of the phenotypic diversity in winter rye during key growth stages that overlap with the typical planting dates for corn (Zea mays L.), soybean [Glycine max (L.) Merr], and late-planted crops like dry bean (Phaseolus vulgaris L.). Thus, the objectives of this study were to evaluate changes in biomass accumulation and quality of winter rye and triticale (x Triticosecale Wittmack) cultivars at three growth stages. Twenty cultivars were assessed over the 2014-2015 and 2015-2016 growing seasons across three environments in Minnesota. Winter rye and triticale were harvested for biomass at the tillering, booting, and soft dough growth stages and rye biomass yield and quality [i.e., crude protein, neutral detergent fiber (NDF), and 48-hour digestibility (NDFD)] were determined following harvest. Overall, there was little variation in each parameter among the cultivars within a location and growth stage. NDFD had some variation at the soft dough stage where digestibility ranged from 273 to 324 g kg-1 at the Crookston site and 332 to 406 g kg-1 at the St. Paul site. The lack of difference between cultivars indicates a wide range of choice when selecting a winter rye cultivar.

Keywords: early childhood; education; quality; measurement; monitoring; majority world; Item Response Theory; psychometrics

Recent technological advancements such as IoT and Big Data have granted industries extensive access to data, opening up new opportunities for integrating Artificial Intelligence (AI) across various applications to enhance production processes. We can cite two critical areas where AI can play a key role in industry such as product quality control and predictive maintenance. This paper presents a survey of AI applications in the domain of Industry 4.0, with a specific focus on product quality control and predictive maintenance. Experiments were conducted using two datasets, incorporating different machine learning and deep learning models from the literature. Furthermore, this paper provides an overview of the AI solution development approach for product quality control and predictive maintenance. This approach includes several key steps, such as data collection, data analysis, model development, model explanation, and model deployment.

Mozambique is one of the poorest countries of the world. However, it has natural resources and if they are managed under sustainable development principles, Mozambique can overcome the current problems. In the present socio-economic status, soil is one of its most important resources and must be protected from pollution and from degradation. This review focuses on the identification and discussion of the main soil quality stressors, namely: soil fertility; deforestation and its sources: agriculture, timber harvesting, charcoal production and uncontrolled fires; mining activities, manly gold artisanal explorations and industrial open-pit coal mining. The sustainable use of the natural resources is mandatory to allow future generations to continue profiting for this nature-based wealth.

The treatment of cancer and associated healthcare procedures often impose a detrimental effect on patients’ quality of life. Symptoms stemming from treatment often hinder patients’ social interactions, emphasizing the crucial role of social support in preserving quality of life and alleviating stress. Moreover, patient resilience serves as a valuable asset in mitigating stress levels and upholding an optimal quality of life amidst the challenges posed by the illness. This study aims to explore the correlation between diverse sources and forms of social support, resilience, and their impact on the quality of life and stress levels among patients undergoing cancer immunotherapy. This study involved thirty patients undergoing immunotherapy at Costa del Sol Hospital in Marbella. Resilience correlated with improved cognitive functioning and diminished symptoms. Informational support from healthcare providers and emotional support from friends were linked to symptom alleviation, such as reduced appetite and insomnia. Moreover, emotional support from friends emerged as a predictor for decreased perceived stress. Interventions targeting the improvement of quality of life and reduction of stress among cancer patients should prioritize assessing support needs and involving the patient's social network, especially during the treatment phase.

Litchi (Litchi chinensis Sonn.) is considered as one of the most important sub-tropical fruits of the World. Under western part of Odisha, India, the litchi growers are facing problem of unstable and lower marketable yield and inferior quality due to higher incidence of fruit cracking, fruit drop, low sugar content and higher fruit acidity. Keeping in mind the positive effects of nutrients and bioregulators, the current study was conducted to elucidate their impact on fruit yield, and quality in the farmers field of Jamankira block in Sambalpur district of Odisha under Odisha University of Agriculture and Technology, India. For the studies, eight years old litchi trees were selected. With 12 treatments, the experiment was set up in a randomized block design replicated thrice viz, T₁: Spray treatment of Borax @ 0.5%; T₂: Spray treatment of Borax @ 0.3%; T₃: Spray treatment of ZnSO₄ @ 0.75% ; T₄: Spray treatment of ZnSO₄ @ 0.5%; T₅: Spray treatment of CaCl₂ @ 0.5%; T₆: Spray treatment of CaCl₂ @ 0.1%; T₇: Spray treatment of Humic acid @ 1.5%; T₈: Spray treatment of Humic acid @ 1%; T₉: Spray treatment of Seaweed extract @ 0.5%; T₁₀: Spray treatment of Seaweed extract @ 0.1 %; T₁₁: Foliar spray of NAA @ 20 ppm and T₁₂ : Control (water spray).The current study compared foliar feeding of different nutrient and bioregulators treatments, which were applied during the first week of December, just after completion of new leaf formation and untreated control. The total number of fruits per plant was recorded highest in plants sprayed with ZnSO4 @ 0.5% (T₄) followed by those treated with humic acid @ 1% (T₈). The highest total fruit yield was recorded in plants with foliar feeding of 0.3% Borax (T₂) which was found to be statistically similar to plants treated with seaweed extract @ 0.1% (T₁₀)and seaweed extract @ 0.5% (T₉).Among the treatments better response for higher number of marketable fruits and marketable yield was recorded in plants treated with both 0.3% Borax (T₂) followed by 0.5% Zinc sulphate (T₄), 1% Humic acid (T₈) and 0.1% CaCl₂ (T₆) in litchi. Application of 1% Humic acid (T₈) followed by 1.5% Humic acid (T₉) enhanced the fruit set (%) and fruit retention (%) along with reduction in fruit drop (%). The enhanced fruit size (fruit length and fruit breadth) and higher fruit weight was obtained in plants treated with 0.3% Borax in litchi. The foliar application of 0.3% Borax (T₂) had also resulted in higher TSS, total sugars, reducing sugar, lower acidity, highest aril weight and lower seed weight in litchi cv. Bombai.

This study has two main focuses: the first focus is to explore the design and the behavior of a locally built solar dryer during processing henna leaves. This was performed through the determination of the most important parameters that have effect on the drying process. Appropriately, it was found that the outlet air temperature of the solar collector depends entirely on the solar radiation, Moreover, the inlet temperature of the air to the drying chamber has also an important impact on the moisture content of the product. It was found that most of the studies dealing with solar drying do not take into consideration the quality of the final product. Accordingly, the second objective of this study is to present the effect of drying process on the quality of the drier samples. For this purpose, the bioactivity of the samples, in terms of determination of the total phenol content, total flavonoid content, and antioxidant activities was performed. Three different samples: fresh sample, samples dried with the presented solar dryer and open solar dried samples are tested. It was found that samples dried with the solar dryer presented the best results.

Currently, one of the main focuses of attention in academia is microgrids (MGs) and their ability to maintain stable, resilient, reliable and high–power quality operations. A crucial component in MGs is power converters (PC), which facilitate the decentralization of power generation. This decentralization, however, poses challenges in terms of power quality. This paper presents a microgrid model based on the IEEE 14–bus distribution system and aims to investigate the power quality when the MG operates while connected to the conventional power grid. The MG model has been developed using MATLAB–Simulink®, a specialized tool for electrical engineering simulations. The results obtained are subjected to rigorous analysis and compared with the compatibility levels established by the IEEE–519 standard. This approach allows an accurate assessment of the MGs’ ability to maintain power quality at acceptable levels while interconnected to the conventional power grid. Finally, this study provides a valuable contribution to the MGs’ field of microgrids by providing a detailed and quantitative assessment of power quality, which will aid in the design and optimization of MGs’ for effective implementation in real electric power systems.

In precision grinding of hard and brittle materials, coarse-grained diamond grinding wheels are increasingly favored for their efficiency and contour accuracy. However, challenges in dressing these grinding wheels have hindered their widespread adoption. In this paper, the effects of dressing parameters on the surface profile and morphological characteristics of electroplated coarse-grained diamond were studied, thereby optimizing the dressing accuracy and dressing efficiency of the coarse-grained diamond grinding wheel. Models for the surface morphology of the large-grained diamond grinding wheel and its grinding surface were established. With a focus on optimizing dressing accuracy, we explored how the grain’s protruding height post-dressing affects the surface morphology of both the diamond grinding wheel and the grinding surface. The model’s accuracy was verified by electroplated coarse-grained diamond grinding wheel grinding experiments with different grain protrusion heights, and the causes of surface morphology formation were analyzed based on morphological characteristic parameters such as surface roughness and surface height difference. The results showed that compared with the undressed grinding wheel, the surface roughness Sa and Sq of the workpiece by the dressing wheel are reduced by 97.75%−99.77% and 97.57%−99.73%, respectively. Precision dressing enables the surface roughness of the electroplated coarse-grained diamond grinding wheel to reach nanometer levels, enhancing its feasibility and application potential.

Emotional intelligence can contribute to quality of life and as a health predictor. The aim of this study is to analyze emotional intelligence, quality of life and the correlation factors associated in patients undergoing chronic hemodialysis. A quantitative, observational, cross-sectional design was performed, and one hundred and thirty-eight multi-centers hemodialysis patients were recruited. A battery of questionnaires, including Trait Meta-Mood Scale (TMMS-24), Kidney Disease Quality of Life-Short Form (KDQOL-SF), and an ad-hoc sociodemographic questionnaire, were answered. Sex differences existed when assessing the three dimensions of emotional intelligence: ranked by order, the highest scores in males were in clarity, repair, and attention. However, in females were in repair, clarity, and attention. Males had higher scores than females in emotional role (p=0.045). Younger participants had better scores in all physical functions (p=0.001) and vitality (p=0.038) than older. Moreover, those who had a higher level of education presented better physical function (p=0.027) and higher scores in emotional wellbeing (p=0.036). Finally, in females, emotional attention (p=0.046) and repair (p<0.001) were strongly associated with general health perception. The assessment of emotional intelligence considering sex differences in patients undergoing chronic hemodialysis can be an indicator of quality of life including the use in health interventions.

One of the challenges of deploying Wireless Sensor Networks (WSN) at large scale is to operate for prolonged periods of time relying on the limited amounts of energy stored in its nodes. Generally, data communication is the main factor of draining energy. Consequently, reducing the amount of transmitted data by the nodes is of great interest. At the same time, reducing data to be transmitted should not decrease the quality of the deduced information. Solving this problematic is what we call in this article "Ensuring the Quality of Information Service (QoIS)". This document provides a state-of-the-art for the QoIS regarding WSNs. At first, we give a quick overview of the Internet of Things (IoT) paradigm and the WSN technologies in order to understand how data is gathered and used in these networks. Also, we introduce a novel concept: QoIS, in contrast with classic QoS. Then, it is expected a summary of criteria that asses the QoIS in WSNs plus some techniques to improve it. In this article, we will focus on data management techniques. These techniques can improve raw data, information and/or knowledge quality in energy-constrained WSNs. Finally, we give some conclusions and a glimpse about our future work.

Software defect prediction models enable test managers to predict defect-prone modules and assist with delivering quality products. A test manager would be willing to identify the attributes that can influence defect prediction and should be able to trust the model outcomes. The objective of this research is to create software defect prediction models with a focus on interpretability. Additionally, it aims to investigate the impact of size, complexity, and other source code metrics on the prediction of software defects. This research will also assess the reliability of cross-project defect prediction. Well-known machine learning techniques such as support vector machines, k-nearest neighbors, random forest classifiers, and artificial neural networks were applied to publicly available PROMISE datasets. The interpretability of this approach has been demonstrated by SHapley Additive exPlanations (SHAP) and local interpretable model-agnostic explanations (LIME) techniques. The developed interpretable software defect prediction models showed reliability on independent and cross-project data. Finally, the results demonstrate that static code metrics can contribute to the defect prediction models, and the inclusion of explainability assists in establishing trust in the developed models.

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

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

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

Agricultural crops productivity is heavily influenced by the strength of their seeds. Current methods for testing seed vigor, such as the germination rate and tetrazolium test, rely on time-consuming human visual inspections. Computer Vision, a crucial technology in smart production processes, offers an automated alternative and is increasingly applied in digital agriculture processes. Here we propose a method that combines YOLOv8 and morphological analysis of seeds using X-ray images to aid seed quality analysts in classifying seed lots based on their physiological potential. We examined the internal morphology of three seed lots and generated X-ray images to train a YOLOv8-based model with a post-segmentation module. This model assessed various parameters such as the total seed area, area filled by the embryo and endosperm, length, width, and calculated the percentage occupied by the embryo and endosperm in relation to the total seed area. Subsequently, seeds were classified into four categories based on the internal area occupied by the endosperm and embryo. Our findings reveal the robust performance of the YOLOv8 model in segmenting and classifying despite the challenges posed by a relatively small dataset. Notably, the proposed model achieved an impressive accuracy of up to 95.6% in identifying and segmenting the endosperm over 1,500 epochs with just 15 training images. The endosperm/seed area ratio, particularly within the 50-60% range covering over 50% of the samples, emerged as a significant metric for evaluating the viability of seed batches.

Weather has significant impact on growth and plants development. It is important to analyze the influence of changing climate conditions on expression of plants agronomical characters. Two flax varieties were grown from 1987 to 2018 in the North-West of Russia. Whether conditions and their influence on flax agronomic characters were analyzed using variance and correlations analyses. Significant influence of year conditions on the manifestation of all evaluated characters was revealed. Starting from June high temperatures accelerate the development of plants at all stages. Prolongation of germination - flowering period is the most important for fiber productivity improvement. Oppositely, for formation of high quality fiber fast ripening in hot weather after flowering is preferable. Such data give possibility to predict the amount and quality of yield. Usage of weather conditions data also permits to compare results obtained in different years. Suggested method of year’s meteorological conditions classification can be used in other genebanks for systematization and analyses of crops field evaluation results. Correlation analyses reviled 3 correlated pleiades: (1) pleiade of productivity, (2) pleiade of fiber quality and yield, (3) pleiade of the growing season phases duration, the sums of active temperatures and precipitation during each period. Great influence of growing conditions on economically valuable traits indicates the necessity of searching for genotypes with stable characters manifestation for breeding new varieties, which will give stable yield and fiber of good quality.

Metabolic Syndrome (MetS) is a serious condition that significantly increases the risk of cardiovascular diseases and the severity of type 2 diabetes, also impacting on the development and evolution of other chronic diseases. Predicting metabolic syndrome is a complex task due to the multifactorial nature of this condition, which involves a combination of various risk factors such as abdominal obesity, insulin resistance, dyslipidemia, and hypertension. The complex interplay of these factors makes it challenging to predict the syndrome. Both genetic predisposition and environmental factors also contribute to the development of metabolic syndrome. Metabolic syndrome affects diverse populations with different ethnicities, lifestyles, and socioeconomic backgrounds. Prediction models, in addition, need to account for population heterogeneity and consider variations in risk factors across different groups. The present study analyzed data from participants in a cohort from Mexico City to identify key risk factors in men and women, addressing the presence of unbalanced data. In order to tackle the issues posed by data imbalance data, SMOTE and ADASYN were applied to assess significant differences in the selection of risk factors for MetS prediction. Random Forest and RPART models using ADASYN and SMOTE demonstrated better performance, achieving a balanced accuracy of approximately 87%. In women, they highlighted sleep quality, anxiety factors, tobacco consumption, and nutritional components. In the case of men, stronger associations were identified with the social development index and factors related to gout in parents.

Sleep is a fundamental human need: sleep disruption, in fact, causes an increase in the activity of the sympathetic nervous system and the hypothalamic-pituitary-adrenal axis, metabolic effects, changes in circadian rhythms and pro-inflammatory responses. Sci-entific literature is finally starting to pay attention to the central role of sleep-wake rhythm alterations for patients health. Oxaliplatin is used extensively for the treatment of gastrointestinal cancer and other malignancies, with increased frequency of use in recent years. This study aims to understand the effects of sleep-wake rhythm alterations on health and quality of life on cancer patients treated with oxaliplatin. Study has been conducted through the creation and distribution of questionnaires to patients to inves-tigate the potential alteration of the sleep-wake quality. Evaluating the influence of the collected variables on sleep quality, only liver and biliary tract and pancreas tumor lo-calization, in males, and previous difficulty sleeping, and anxiety, worries and stress, in females, resulted statistically significant. The results obtained may serve as foundation for designing awareness campaigns and updating of patients, healthcare personnel and caregivers, to improve health and quality of patients life.

Globally, weeds interfere with agricultural production activities and have a very serious impact on agriculture and animal husbandry. Identifying a safe and reliable weed control strategy might increase yield, production net income, and improve crop quality. A field experiment was carried out to explore the effects of weeds interference frequency on the yield and quality of Glycyrrhiza uralensis Fisch in an arid and semi-arid area of northwest China. The experiment consisted of seven treatments and were (1) no weeding, marked as WF0; (2)-(7) artificial weeding by hoe once every 1, 2, 4, 6, 8, 10 weeks after emergence, marked as WF1, WF2, WF4, WF6, WF8 and WF10, respectively. We found that the higher weeding frequency had a higher the plant height, photosynthesis, yield and quality. The highest yield was obtained in the WF1 treatment, while the cost of weeding was the highest among all treatments. The concentration of liquiritin and glycyrrhizic acid were increased by 53.24% and 36.57%, with the highest nitrogen metabolism enzymatic activities and quality in WF4 treatment. WF4 treatment exhibited the largest increases in the net income among all treatments in both growing seasons, with respective increases up to 71.39 % and 78.81%. These findings suggested that weeding once every 4 weeks would be an effective and sustainable measure to control weeds in an arid and semi-arid area.

Tea infusions are the most consumed beverages in the world after water, their pleasant yet peculiar flavor profile drives consumer choice and acceptance and becomes a fundamental benchmark for industry. Any qualification method capable of objectifying the product's sensory features effectively supports industrial quality control laboratories guaranteeing high sample throughputs even without the human panel intervention. The current study presents an integrated analytical strategy acting as an Artificial Intelligence decision tool for black tea infusion aroma and taste blueprinting. Key markers validated by sensomics are accurately quantified in a wide dynamic range of concentrations. Thirteen key aromas are quantitatively assessed by standard addition with in-solution solid-phase microextraction sampling followed by GC-MS. On the other hand, nineteen key taste and quality markers are quantified by external standard calibration and LV-UV/DAD. The large dynamic range of concentration for sensory markers is reflected in the selection of seven high-quality teas from different geographical areas (Ceylon, Darjeeling Testa Valley and Castleton, Assam, Yunnan, Azores, and Kenya). The strategy acts as an AI smelling and taste machine predicting teas sensory features without the human panel intervention.

In this study, alfalfa silage with different packing densities (500 kg/m3, 600 kg/m3 and 700 kg/m3) were set up under outdoor high temperature and indoor normal temperature. The chemical composition, fermentation quality and microbial community of alfalfa silage were analyzed. The results showed that DM and WAC content decreased with the increase of density. When the density is 600kg/m3, CP content reaches the maximum and ADF content is the lowest. Temperature has a certain effect on alfalfa silage. The content of Lactobacillus plantarum fermented at high temperature is lower than that fermented at normal temperature. At the same time, the content of Lactobacillus plantarum decreased with the increase of packing density. However, the content of Lactobacillus plantarum was the lowest when the packing density was 600 kg/m3 at high temperature. In summary, this study explained the effects of different temperature and density on alfalfa fermentation quality and microbial community, and clarified that the density should be reasonably controlled within 600 kg/m3 during alfalfa silage, providing theoretical support for production practice.

This study addresses the influence of working conditions on Work-Related Quality of Life (WRQOL) among Spanish healthcare professionals. The research seeks to elucidate the mediating roles of job engagement and burnout, and the moderating effects of resilience and self-efficacy, in this relationship. Methods: The study included 374 healthcare workers from Spain, encompassing physicians, nurses, and nursing assistants. It employed a methodological approach using validated instruments to assess psychosocial risks, work-life quality, job engagement, burnout, and resilience. Data were gathered through self-reported questionnaires. Results: Key findings indicate a negative association between working conditions and WRQOL. Job engagement and burnout significantly mediated this relationship, accounting for 19% to 33% of the variance in WRQOL. Notably, lack of support emerged as a strong negative factor for work-related quality of life. Additionally, resilience moderated the relationship between lack of support and burnout. Conclusions: The study concludes that improving working conditions could increase WRQOL. Interventions aimed at enhancing engagement and addressing burnout may be effective. The moderating role of resilience suggests that strategies to enhance resilience could also be beneficial. These findings hold significant implications for policy formulation and human resources planning in healthcare, emphasizing the need for enhanced workplace support and the development of resilience among health workers.

Transdermal drug delivery systems (TDDS) are designed to administer a consistent and effective dose of medication through the patient's skin. These pharmaceutical preparations are self-contained, discrete dosage forms designed to be placed topically on intact skin to release the active component at a controlled rate by penetrating the skin barriers. This medication provides a continuous and prolonged administration of a substance at a consistent rate. TDDS, or transdermal drug delivery system, has gained significant attention as a non-invasive method of administering drugs to vulnerable patient populations, such as pediatric and geriatric patients. This approach is considered easy to administer and helps overcome bioavailability issues associated with conventional drug delivery, which can be hindered by poor absorption and metabolism. TDDS has various advantages compared to conventional methods of drug administration. It is less intrusive, more patient-friendly, and can circumvent first-pass metabolism and the corrosive acidic environment of the stomach that happens when medications are taken orally. Multiple methodologies have been devised to augment the transdermal permeability of diverse pharmaceutical substances. Recent advancements in transdermal drug delivery systems have facilitated the precise delivery of medications to the intended site of action by improving the penetration of drugs through the outermost layer of the skin, known as the stratum corneum, resulting in enhanced drug availability throughout the body. This review seeks to provide a concise overview of the several methods employed in the production of TDDS, as well as their evaluation, therapeutic uses, clinical considerations, and current advancements. These advancements have resulted in the development of intelligent, biodegradable, and highly efficient transdermal drug delivery systems.

This study aimed to use spatiotemporal tensor data to measure the level of employment quality in China's provinces and analyzed the magnitude and direction of its influencing factors in the spatiotemporal dimension. Taked 30 provinces, autonomous regions and municipalities directly under the central government in China from 2011 to 2020 as the research object, the employment quality evaluation system was constructed from six dimensions of employment environment, employment status, employability, labor remuneration, social security, and labor relations. The employment quality index data was expressed as a three-order high-dimensional tensor spatio-temporal data form, and the employment quality of China's provinces was measured from the spatio-temporal perspective by using principal tensor analysis, and the visual analysis of the development and change process of employment quality was carried out. The spatial autocorrelation analysis of employment quality was carried out, and the time-space dual fixed effect model of the spatial Dubin model was selected to analyze the direction and magnitude of the influence factors of employment quality on itself and its neighboring provinces. The research showed that: (1) The overall level of employment quality in China was not high and the employment quality varies greatly among provinces, and the employment quality development gap among provinces showed a trend of widening. (2) The development of employment quality in western China was relatively fast, while the development of employment quality in central China showed insufficient stamina. (3) Sichuan Province had a strong radiation effect on the development of employment quality in neighboring provinces, and Beijing and Tianjin had a strong siphon effect on the development of employment quality in neighboring provinces. (4) The level of industrialization and informatization promoted the development of employment quality in China's provinces, while the industrial structure had a significant negative effect on the development of employment quality.

Background: Given the extensive translation of the Prolapse Quality of Life Questionnaire (P-QoL) into many languages, it is imperative to develop an Arabic version to facilitate study on Pelvic organ health within the Arabian culture. Objective: To investigate, cross culturally adapt and validate Arabic version of the P-QoL. Study Design: Cross-cultural adaptation and psychometric testing. Methods: A total of 90 participants were included in the study. This cross-sectional study went through two phases; during phase I, the P-QoL was translated and adapted from English into Arabic. The Arabic version was psychometrically validated during phase II using the test-retest reliability internal consistency with Cronbach’s alpha coefficient, convergent construct validity (CC) among the four study tools using Spearman’s coefficient (r) and discriminative validity using Mann-Whitney test to find differences between the means of the two samples. Results: A satisfactory level of semantic, conceptual, idiomatic, and content comparability was reached in the cross-cultural adaptation of the Arabic version of the P-QoL questionnaire. The internal consistency was high in terms of psychometric validation, with a Cronbach’s alpha coefficient of 0.971 for the P-QoL questionnaire. The test-retest results showed a high reliability with interclass correlation coefficient (ICC) of P-QoL = 0.987. The convergent construct validity was highly accepted (moderately strong), reflecting a positive correlation between the Arabic version of the P-QoL and the Australian Pelvic Floor Dysfunction Questionnaire (APFD) r = 0.68 (p &lt; 0.001). Similarly, a significant convergent validity of P-QoL Arabic version and Visual Analogue Scale (VAS) r = 0.47 (p &lt; 0.001) was found, as well as the correlation between the APFD and the VAS r = 0.46 (p &lt; 0.001). However, there were no significant correlation between the SF-12, the P-QoL, the APFD, and the VAS. Conclusion: Based on a significant correlation between the Arabic APFD and the VAS, the results reveal good reliability, internal consistency, and construct validity. It is recommended that Arabic-speaking females with pelvic organ prolapse use the Arabic version of the P-QoL. More research is needed to assess the responsiveness of the P-QoL.

This study was conducted to compare the fertility and hatchability performance of the indigenous helmeted guinea fowls and exotic birds of the French strain, and predict egg weight from egg indices in Nigeria. A total of 300 randomly selected 8-month old guinea fowls comprising 150 indigenous (30 males and 120 females) and 150 French strain (30 males and 120 females) were utilized in the study. From these, a total of 240 randomly selected eggs (120 per genetic group) were used separately for the reproductive and egg quality assessment. The fertility and hatchability parameters were subjected to descriptive statistics, while the seventeen egg quality parameters were analysed using T-test, phenotypic correlation, principal component analysis, multiple linear regression and CHAID decision tree. Percentage fertility (90.0 versus 73.3%) and hatchability (66.7 versus 56.8%) were higher in the French strain compared to their indigenous counterparts. The egg quality parameters of the French strain were higher (P<0.05) than those of their indigenous counterparts with the exception of egg shell index (18.88±0.79 versus 16.41±0.69) and haugh unit (92.37±3.13 versus 91.09±3.22). However, the mean yolk/albumen ratio was similar (P>0.05). The phenotypic correlation coefficients between egg weight and egg quality indices in both genetic groups ranged from low to high values [-0.05-0.95 (indigenous); -0.19-0.96 (French strain)]. Three principal components sufficiently accounted for the variations in the egg quality traits of both genetic groups. The CHAID algorithm was more consistent in egg weight prediction with egg width as the primary explanatory variable. The present information may guide breeding and management strategies geared towards the improvement of the reproductive and egg quality traits of the helmeted guinea fowls.

Since the integration of electronic devices and intelligent electronic devices into the power grid, power quality (PQ) has consistently remained a significant concern for system operators and experts. Maintaining high standards of power quality is crucial to prevent malfunctions and faults in electric assets and in connected loads. Recently, PQ studies have shifted their focus to a specific frequency range, previously not considered problematic, the supraharmonic 2kHz–150kHz range. This range is not populated by the harmonic components of the 50-60 Hz mains fundamental, but a combination of intentional emissions, switching and non-linearity by-products and various types of resonances. This paper aims to provide a detailed analysis of the impact of SH on power network operation and assets, focusing on the most relevant documented negative effects, namely power loss and heating of grid elements, aging of dielectric materials, failure of medium voltage (MV) cable terminations, and interference to equipment and to power line communication (PLC) technology in particular. Under some shareable assumptions limits are derived and compared to existing ones for harmonic phenomena, providing a clear identification of the primary issues associated with supraharmonics and suggestions for the standardization process. Strictly related is the problem of grid monitoring and assessment of SH distortion, discussing the suitability of normative requirements for instrument transformers (ITs) with specific focus on their accuracy.

This study aimed at investigating the quality statuses of graduates’ sustainable core competences development and the causes behind the identified competence statuses by applying the core competencies’ model. The study employed case study design with thematic analysis involving seven interviewees. This study used tracer study findings and national exit exam results as exhibits. The study revealed “very good” and “excellent” quality statuses for the graduates’ core competence development of College of medicine and Health Sciences (CMHS). Similarly, this study identified “Good +” statuses for the quality of graduates’ core competence development in College of Agriculture and Environmental Sciences ( CAES) and College of Science (CS). Furthermore, the study identified "good" - and +” statuses for the quality of graduates’ competence development at the Faculty of Social Sciences (FSS) and Faculty of Humanities (FH). Improved instruction with a balance of theory and practice, task-oriented deans’ leadership behavior with fairness and shared vision- mission identity, handling internal conflicts, and external ethnic-based war influences were the major reasons for the identified higher competence quality statuses in CMHS, CAES, and CS, whereas the opposite direction decline of these factors were the causes for the low statuses of FSS and FH. Sustainable graduates’ core competence development leads to sustainable employability, labor force, and individual to nation-wide holistic sustainable development

Due to combined climate and biodiversity crisis, the sustainable utilization of phytogenetic resources stands as one-way alternative while nutrient management strategies gain an increasing role in agriculture. Building on previous studies regarding the Endangered local endemic of Crete (Greece) Carlina diae (Asteraceae) with medicinal and ornamental value, this investigation focused on its pilot cultivation and fertilization (foliar or root application). Foliar application included chemical fertilizer (conventional) or integrated nutrient management (INM). Root application consisted of chemical fertilizer, biostimulant, or INM with biostimulant. Above-ground biomass content of nutrients, together with leaf chlorophyll fluorescence and colour parameters (SPAD meter, DA meter, Chroma Meter) were determined. The leaf content of chlorophyll, three key antioxidant compounds and minerals’ titers were also assessed. The fertilization scheme did not influence plant growth and visually perceived quality (leaf color and shape). Notably, foliar INM fertilization increased biomass partitioning to inflorescences (harvestable organ for either medicinal or ornamental purposes), and decreased tissue water content (facilitating processing). Considering all three antioxidants together, INM with biostimulant appeared the optimum scheme, being associated with the highest (carotenoids, phenolics) or the second highest (flavonoid) content. In C. diae, therefore, INM fertilization was optimal for upgrading yield (foliar) and herbal quality in terms of antioxidant profile (INM with biostimulant), which might be embraced as an eco-friendly approach for high quality yields.

Little information is available in the literature on the use of cactus pear meal in poultry diets being important to evaluate diets that provide excellent performance and lower production costs. Our objective was to study the use of cactus pear meal in diets of laying hens. In the first study, two diets for male and female chicks were used - 1: 80% reference diet + 20% Miúda cactus pear meal (CPM) and 2: 80% reference diet + 20% Gigante cactus pear meal. The variety Miúda provid-ed better use of metabolizable energy, digestibility coefficient of dry matter, protein, and min-eral matter. In the second study, a control diet was compared to three diets with different levels of CPM for laying hens, in the proportions of 3%, 6% and 9%. No significant differences were found in productive performance. However, there were significant differences in egg quality, texture and color profile of the cooked yolk, egg composition, fatty acids and cholesterol in the yolk. It is possible to use 9% of CPM in the diet of laying hens in semi-intensive system not compromising performance and egg quality, and using 3% of CPM provides higher economic return.

This narrative review delves into the evolving landscape of fertility preservation techniques with a particular focus on their use in patients undergoing oncology treatment that carries a risk of ovarian insufficiency. Advances in established methods such as cryopreservation of oocytes and embryos are highlighted and the increasing use of gonadotropin-releasing hormone (GnRH) agonists is discussed. The review also addresses the complexities and controversies associated with these approaches, such as the 'flare-up' effect associated with GnRH agonists and the potential of GnRH antagonists to reduce the risk of ovarian hyperstimulation syndrome. Despite advances in fertility preservation, the report highlights the challenges we face, including the need for personalized treatment protocols and management of associated risks. It calls for continued research and collaboration between healthcare professionals to refine these techniques and ultimately improve reproductive outcomes for patients facing the prospect of fertility-impairing treatment.

The agricultural sector faces challenges due to climate change and the growing global population. Alkaline stress could adversely impact plant growth and crop production. This stressor diminishes water quality essential for crop cultivation, consequently impairing plant growth and overall productivity. Gamma-aminobutyric acid (GABA), a non-protein amino acid, may exhibit multifaceted roles in plant responses to adverse environmental conditions. Optimization of crop production in controlled environmental agriculture under artificial light attracted much attention. In the present study, we investigated the effects of different light spectra and GABA concentrations on Lollo Rosso lettuce plants under alkaline stress. Seedlings were placed under different light spectra [red (R), blue (B), white (W), 3R:1B, and 2R:1B:1far-red (FR)] and treated by GABA (0 and 50 µmol). Alkaline conditions were instituted by applying NaHCO3 at a concentration of 40 mM. The experiment incorporated a control treatment without NaHCO3. In general, R light exposure caused the highest growth performance of lettuce plants. GABA augmented biomass production in control and alkaline-treated plants across all light spectra. Additionally, it increased the concentrations of photosynthetic and protective pigments under alkaline conditions. GABA also improved the photosynthetic performance under all light spectra. Non-photochemical quenching and pigmentation were enhanced by exposure to B light, especially in plants treated with GABA. Alkaline stress induced an increase in soluble carbohydrate content in the lettuce leaves. These findings highlight the support of GABA application in facilitating coping plants to alkaline stress.

People wore clothes for warmth, survival and necessity in modern life as well but in modern era, eco-friendliness, shorten production time, design, and intelligence also matters. The seamless bonding technology strengthen the bond between fabrics in textiles, while Grey relational analysis (GRA) can be applied to fabrics to measure the relationship between data series and determine the closeness of each data series. In this study, polyurethane prepolymer, 2-Hydroxyethyl acrylate (2-HEA) as an end-capping agent, and n-octyl acrylate (ODA) as a photo-initiator were used to synthesize dual-curing polyurethane hot-melt adhesive. The Taguchi quality engineering and grey relational analysis used to discuss the influence of different mole ratio of NCO:OH, and the effect of the molar ratio of addition of octyl decyl acrylate on the mechanical strength. The Fourier transform infrared spectroscopy (FTIR) results showed the termination of prepolymer's polymerization reaction and the C=O peak intensity at 1730 cm-1 indicating the efficient bonding to main chain. The high molecular weight polymer (20,000-30,000) described by advanced polymer chromatography (APC) confirmed the polyurethane polymer bonded with octyl decyl acrylate to achieve the photo-thermosetting effect. The thermogravimetric analysis (TGA) results showed the thermal decomposition temperature of polyurethane hot melt adhesive also increased and highest pyrolysis temperature (349.89℃) for the polyhydric alcohols. The high value of shear strength (34.94 kg/cm2) as well as peel strength (1.68 kg/cm) were also observed in dual-cure photo-thermosetting polyurethane hot melt adhesive. The signal-to-noise ratio also used to generate the grey relational degree. It was observed that the best parameter ration of NCO: OH was 4:1 with 5 moles of monomer. The Taguchi quality engineering method was used to find the parameters of single quality optimization, and then the grey relation calculation was used to obtain the parameter combination of multi-quality optimization for thermosetting polyurethane hot melt adhesive. The study aims to meet the requirements of seamless bonding in textile factories and optimized experimental parameter design by setting target values can effectively increase production speed, reduce processing time and costs as well.

Given the context of global climate change, a worldwide increase in land surface temperature (LST) is anticipated, leading to the exacerbation and broadening of its impacts. This could jeopardize the environmental conditions in countries with a predominantly hot and harsh climate, such as Bahrain, one of the Cooperation Countries (GCC) nations. Conversely, Bahrain is currently experiencing significant population growth, leading to a surge in demand for land to accommodate the construction of additional residential developments. This circumstance allows investigation of the potential impact of land use and land cover alterations on the variation in Land Surface Temperature (LST). In order to accomplish this objective, a residential development project was executed within the timeframe spanning from 2013 to 2023. Four sets of Landsat 8 OLI/TIRS remote sensing datasets were selected, with each set corresponding to one of the four climate seasons. Each set consisted of two images: one capturing the study area before the commencement of the development process and the other depicting the study area after the completion of the development. The study area was analyzed by extracting the land surface temperature (LST), normalized difference vegetation index (NDVI), and normalized difference built-up index (NDBI) on various dates. Subsequently, correlation and regression analysis were employed to examine the interrelationships among these three variables. The findings demonstrated a notable rise in the mean land surface temperature throughout the spring and autumn seasons following the conclusion of land development activities. The findings indicate a positive and robust association between LST and NDBI across all seasons. Moreover, this relationship strengthened following the completion of development activities in the area. Conversely, there was a negative correlation between LST and NDVI prior to the region's development, which transformed into a positive relationship post-development. These results provide empirical support for the notion that small-scale residential developments contribute to a notable increase in LST, primarily driven by the expansion of impervious surfaces in built-up areas. The findings can potentially contribute to the formulation of localized adaptation strategies for small-scale residential development projects.

Indoor comfort is a critical determinant of the holistic educational experience, significantly influencing the well-being, concentration, and performance of students within the confines of school environments. Despite the widespread implementation of heating, ventilation, and air conditioning (HVAC) systems in educational institutions, achieving satisfactory thermal conditions, acceptable acoustics, and optimal daylight levels for occupants continues to pose a considerable challenge. In this review, we specifically delves into the parameters characterizing Italian school environments, recognizing their direct impact on students’learning and concentration. The primary objectives of this review are conducting a thorough examination of the current acustic conditions in Italian schools. The initial phase of our search strategy involved retrieving data from key databases, namely, Scopus, Web of Science, ScienceDirect, PubMed, and Google Scholar. Following the elimination of duplicate articles (n = 289), a total of 135 distinct papers remained for analysis. A critical review of the existing literature is presented based on these criteria, offering guidelines and recommendations for forthcoming studies. The critical review underscores various shortcomings in the current design, deployment, and documentation of multi-domain studies, signaling the need for enhanced quality in future research efforts.

Origanum dictamnus L. (Lamiaceae), a local endemic plant of Crete (Greece), creates polysaccharide-containing subcuticular compartments presenting biological activity against phytopathogenic fungi, and, among others, significantly affecting the fungal cell wall polysaccharides. This field study introduces a fertilization scheme for O. dictamnus, which was developed and refined to optimize yield as well as critical herbal quality aspects. Five fertilization schemes were investigated, based on a polysaccharide-based Integrated Nutrient Management (INM), a mixture of chemical fertilizers and two biostimulants (not algae) via foliar and soil application. Plant growth, together with leaf chlorophyll fluorescence and colour (SPAD meter, DA meter, Chroma Meter) were determined. The leaf content of chlorophyll, three critical antioxidant compounds (carotenoids, flavonoids, phenols) and minerals were also assessed. Considering all three antioxidants together, the enhanced efficiency, non-toxic, water-soluble, polysaccharide-based INM by foliar application was the most stimulatory scheme, playing an important role in plant growth and development. The present field study provides for the first time baseline fertilization data improving key herbal quality features in O. dictamnus and unravels the attainment of high antioxidant properties. The latter may be exploited in favor of its further utilization as raw material for tea preparation, medicinal purposes, natural food flavoring and/or food preservative.

While current video quality assessment research predominantly revolves around resolutions of 4K and beyond, targeted at Ultra High-Definition (UHD) displays, effective video quality for mobile video streaming remains primarily within the range of 480p to 1080p. In this study, we conducted a comparative analysis of the Quality of Experience (QoE) for widely implemented video codecs on mobile devices, specifically Advanced Video Coding (AVC), its successor High-Efficiency Video Coding (HEVC), and Google's VP9. Our choice of 720p video sequences from a newly developed database, all with identical bitrates, aimed to maintain a manageable subjective assessment duration, capped at 35-40 minutes. To mimic real-time network conditions, we generated stimuli by streaming original video clips over a controlled emulated setup, subjecting them to eight different packet loss scenarios. We evaluated the quality and structural similarity of the distorted video clips using objective metrics, including Video Quality Metric (VQM), Peak Signal-to-Noise Ratio (PSNR), Video Multi-Method Assessment Fusion (VMAF), and Multi-Scale Structural Similarity Index (MS-SSIM). Subsequently, we collected subjective ratings through a custom mobile application developed for Android devices. Our findings revealed that VMAF accurately represents the degradation in video quality compared to other metrics. Moreover, in most cases, HEVC exhibits an advantage over both AVC and VP9 under low packet loss scenarios. However, it is noteworthy that in our test cases, AVC outperformed HEVC and VP9 in scenarios with high packet loss, based on both subjective and objective assessments. Our observations further indicate that user preferences for the presented content contribute to video quality ratings, emphasizing the importance of additional factors that influence the perceived video quality of end-users.

The pharmaceutical industry is undergoing a shift in processing methods for small-scale production (250-1000 kg/a), leading to an increased focus on continuous production research. Various concepts were developed to overcome challenges in small-scale crystallization for the production of high-quality products. However, further optimization is needed to enhance the industrial applicability of these concepts. This study aims to demonstrate the practical applicability of the Slug Flow Crystallizer (SFC) in the pharmaceutical industry by extending its use to a wider range of substance systems for small-scale API production. Employing an experimental strategy, the research seeks to rapidly assess the SFC's potential for achieving uniform, high-purity product yields, emphasizing the importance of factors such as slug flow stability, residence time distribution, and substance-specific crystallization criteria. This, coupled with our previously published model-based strategy, forms a comprehensive methodology to explore crystallization behavior and modeling for a variety of substance systems within the SFC. The ultimate goal of this study is to showcase the practicality of the SFC in the pharmaceutical industry, enabling the way for its reliable use in long-term, small-scale continuous crystallization and the production of high-quality pharmaceutical products.

To improve the adaptability of aerial reflective opto-mechanical structures to low-temperature environments, an optimized thermal control design is proposed. Firstly, the relationship be-tween conventional heating methods and axial/radial temperature differences of mirrors with different shapes is analyzed. Based on heat transfer analyses, it is pointed out that optimized thermal control design is necessary to ensure the temperature uniformity of the fused silica mirror and take into account the temperature level when working in low temperature environ-ments. A thermal control scheme based on temperature negative feedback variable power zone heating is proposed for the characteristics of aerial electro-optics systems. Using the thermal control scheme at low temperatures ensures that the average temperature of the mirror fluctu-ates slowly and slightly around 20℃. At the same time, the temperature differences within a mirror and between the primary mirror and the secondary mirror can be controlled within 5℃. Thereby, satisfactory image quality is obtained.

Background: Quality of life (QoL) in IC/BPS patients is an evidence gap in guidelines, because studies are limited and outdated. Therefore, guidelines might not reflect the current situation accurately, and no possible improvements in QoL of these patients. Secondly, guidelines suggest multimodal approach in therapy, however unknown is how the efficacy of these therapies are perceived by the patient themselves. The aim of this study is to investigate the perception of IC/BPS patients on their QoL and to determine which treatments they received and how they evaluate the efficacy of these various (alternative) therapies.Methods: Quantitative retrospective database study in IC/BPS patients, compiled of existing patient survey data (n=217) from July 2021. Results: The QoL of patients is affected significantly by IC/BPS. This is evident from the substantial self-reported impact by patients, the various affected domains on EQ-5D 5L. The QoL was not negatively affected by delayed diagnosis, but there were differences between female and males. Secondly, there was the wide array of (alternative) treatments utilized, although some have doubtful results and high dropout rates. Conclusion: QoL is considerably impaired in IC/BPS patients. Coagulation therapy and intravesical GAG therapy were most appreciated treatments. The diverse responses and adherence to various treatments warrant a personalized approach (phenotype-oriented therapy). To achieve improvement in the QoL, it is important to incorporate the patient’s perspective in treatment guidelines.

Fractal analysis of time series aims to extract the hidden or complex structures issued from the associated real data, such as scaling laws, non-stationary, dynamics, and so on. In the present work, the air quality index and its components are considered as time series owing fractal structures. To understand their underlying dynamics, wavelet multifractal approach is applied starting with a wavelet multifractal spectrum test to confirm the multifractality of the underlying data. Next, a new model is introduced improving the classical minmax one, provided with a statistical measure for the adequacy of the new model. The theoretical findings are applied to the north west Tabuk region of Saudi Arabia for environmental and climate data related to pollutants and factors involved in the estimation of the air quality index.

There are several forms of maintenance high-efficiency hemodialysis (HD) including hemodiafiltrations (HDF) in different technic modes and expanded HD using dialyzers with medium cut-off membranes. The aim of the study was to assess the intradialytic tolerance and length of dialysis recovery time (DRT) in these modalities. This is an exploratory, cross-over study in maintenance HD patients with low comorbidity and no clinical indications for the use of high-efficiency HD, who were exposed to five intermittent dialysis in random order: high flux hemodialysis (S-HD), expanded HD (HDx), pre-dilution HDF (PRE-HDF), mix-dilution HDF (MIX-HDF) and post-dilution HDF (POST-HDF). 24 dialysis sessions of each method were included in the analysis. Dialysis parameters including blood flow rate, dialysis fluid flow rate and temperature, and pharmacological treatment were constant. Average total convection volume for post-HDF, pre-HDF and mix-HDF were 25.6 (3.8), 61.5 (7.2) and 47.1 (11.4) l, respectively. During all therapies, patients had similar hydration status monitored using bioimpedance spectroscopy and similar variability over time in systemic blood pressure, cardiac output, and peripheral resistance monitored using impedance cardiography. The lowest frequency of all intradialytic adverse events were observed during HDx. Delayed DRT was the shortest during PRE-HDF. Patients were also more likely to report immediate recovery while receiving PRE-HDF. These differences did not reach statistical significance, however the study results suggest that, intradialytic tolerance and DRT may depend on the dialysis method used. This support the need of taking into account patient preferences and quality of life while individualizing high efficiency therapy in HD patients.

The overuse of chemical fertilisers degrades the soil ecosystem and restricts the natural development of plants. Within the coffee industry, various by-products are produced throughout the process of coffee production and consumption, which are significant in terms of environmental waste. SCG (spent coffee grounds) contain a variety of bioactive compounds that have demonstrated potential applications in various fields. These compounds can enhance soil quality by improving its chemical, physicochemical, physical properties, and biological fertility, ultimately leading to improved plant growth. This study examines the impact of SCG, vermicompost, and chemical fertilisers on the growth of organic red radish (Ravanello Cherry Belle) and soil quality. The experiment, conducted in a greenhouse, tested various concentrations and applications of SCG. Results showed that the SCGT 0.5 gm treatment yielded the highest mean plant length (18.47 cm) and fresh weight (27.54 grammes), while the SCG 10% treatment resulted in the lowest mean plant length (4.54 cm) and fresh weight (0.07 grammes). Vermicompost at 50% concentration produced the highest mean leaf surface area (58.32). These findings suggest the potential of SCG as a sustainable fertiliser alternative, contributing to improved plant growth and soil quality, thus supporting sustainable agricultural practices and a circular economy.

In this study, the effects of food waste (FW) compost, vermicompost, and chemical fertilizers on the growth of organic red radish and soil quality are investigated to promote sustainable agriculture. Utilizing a comparative approach, it assesses the impacts of these fertilizers on various plant growth metrics and soil characteristics, highlighting the potential of converting FW into nutrient-rich amendments as a sustainable alternative to chemical fertilizers. The results indicate a significant variation in fresh weight among different treatments. For example, the FV 25% treatment demonstrated a relatively high mean fresh weight of 7.9664, while the CO 50% treatment yielded a much lower mean fresh weight of 0.2589. These numbers underscore the potential efficacy of specific FW treatments in enhancing plant growth, with VC 50% and FV 25% showing considerable promise in increasing crop yield. The study concludes that FW compost and vermicompost significantly enhance plant growth and soil quality, advocating for their use as sustainable and environmentally friendly alternatives to chemical fertilizers. The findings emphasize the importance of selecting appropriate fertilizer types and concentrations to optimize agricultural productivity and environmental sustainability, supporting the incorporation of FW into agricultural systems as a beneficial resource.

In this study, the hybrid biological ion exchange (BIEX) resin and gravity-driven membrane (GDM) process was employed for the treatment of coloured and turbid river water. The primary objective was to investigate the impact of both physical and chemical cleaning methods on ceramic and polymeric membranes in terms of stabilised flux, flux recovery after physical/chemical cleaning, and permeate quality. To address these objectives, two types of MF and UF membranes were utilised (M1 = polymeric MF, M2 = polymeric UF, M3 = ceramic UF, and M4 = lab-made ceramic MF).Throughout extended operation, the resin functioned initially in the primary ion exchange (IEX) region (NOM displacement with pre-charged chloride) and progressed to a secondary IEX stage (NOM displacement with bicarbonate and sulphate), while membrane flux remained stable. Subsequently, physical cleaning involved air/water backwash with two different flows and pressures, and chemical cleaning utilised NaOH at concentrations of 20 and 40 mM, as well as NaOCl at concentrations of 250 and 500 mg Cl2/L. These processes were carried out to assess flux recovery and identify fouling reversibility. The results indicated an endpoint of 1,728 bed volumes (BV) for the primary IEX region, while the secondary IEX continued up to 6,528 BV. At the end of the operation, DOC and UVA254 removal in the effluent of the BIEX columns were 68% and 81%, respectively, compared to influent water. This was followed by 30% and 57% DOC and UVA254 removal by M4 (ceramic MF). The stabilised flux remained approximately 3.8 – 5.2 LMH both before and after the cleaning process, suggesting that membrane materials do not play a pivotal role. The mean stabilised flux of polymeric membranes increased after cleaning, whereas that of ceramics decreased. Enhanced air–water backwash flow and pressure resulted in increased removal of hydraulic reversible fouling, which was identified as the dominant fouling type. Ceramic membranes exhibited higher removal of reversible hydraulic fouling than polymeric membranes. Chemical cleaning had a low impact on flux recovery; therefore, we recommend solely employing physical cleaning.

The paper aims to develop and test an algorithm for classifying Russian-language text reviews of patients’ experiences with medical facilities and physicians, extracted from social media. This is motivated by the limitations of conventional methods of surveying consumers to assess their satisfaction with the quality of services, which are being replaced by automatic processing of text data from social media. This approach enables to get more objective results due to the increased representativeness and independence of the sample of service consumers. The authors have tested machine learning methods using various neural network architectures. A hybrid method was developed to classify text reviews of medical facilities posted by patients on the two most popular physician review websites in Russia. Overall, more than 60,000 reviews were analysed. The main results are as follows: 1) the classification algorithm developed by the authors has a high efficiency, the best result being achieved by the GRU-based architecture (val_accuracy = 0.9271); 2) applying the named entity search method to text messages following their partitioning improved the classification efficiency for each of the classifiers based on artificial neural networks. To further enhance the classification quality, reviews need to be semantically partitioned by target and sentiment and the resulting fragments need to be analysed separately.

One of the main challenges in geodetic deformation analysis is to infer whether the geometry of some engineering structures or zones of natural hazards has changed from their initial state or not. The pillar that supports such an analysis is tightly based on the fundamentals of statistical hypothesis testing. The null hypothesis model indicates that no displacement has occurred. It is tested against a class of alternative models, which stipulate different displacement patterns. In this contribution, we present an innovative geodetic displacement detection which integrates combinatorial analysis and likelihood ratio tests into a sequential procedure for the case where the differences between observations of two epochs are in play. This framework is applied and investigated to two test scenarios: a synthetic and a real simulated trilateration network. From a statistical point of view, our approach is rigorous, because the alternative model can identify simultaneously more than one unstable point. In addition, the relationship between the unknown parameters and the observations is always linear, even if the problem manifests itself as non-linear. Consequently, we avoid a potential loss of statistical test power due to the model linearization. In addition, the proposed method controls the false positive rate efficiently. One of the problems that arise here is also related to the selection of the maximum number of points to be considered in the test procedure ( ). Here, we provide an innovative methodology based on rank computation of the design matrices to define , which can even be extended to the problem of outlier detection. Determining avoids the problem of having non-separable models in identifying unstable points. The algorithms and data are available in the repository.

Serine is widely involved in antioxidant synthesis, immune response, and fat metabolism. However, it remains unclear whether dietary serine supplementation affects fat deposition in the skeletal muscles of pigs. Thus, we explored the effects of dietary serine supplementation on growth performance, meat quality, and composition of gut microbes and their metabolites in growing-finishing pigs. Forty-eight boars weighing approximately 20 kg were fed either a basal diet or a basal diet supplemented with 0.15% serine. The results showed that dietary serine increased the daily weight gain and improved the antioxidant ability of pigs, as indicated by the decreased malondialdehyde content and increased glutathione and superoxide dismutase content. Pigs supplemented with serine had better meat quality, as shown by the lower drip loss and higher IMF content. Furthermore, dietary serine increased the relative abundance of Streptococcus and Lactobacillus and decreased the relative abundance of Clostridium_sensu_stricto_1 and Terrisporobacter. Differential microbial metabolites were mostly enriched in metabolic pathways related to lipid synthesis, such as alpha-linolenic acid metabolism and steroid hormone biosynthesis. Correlation analysis showed that the altered metabolites were closely related to the intestinal microbiota. In conclusion, our results suggested that serine serves as a potential additive for improving meat quality in growing-finishing pigs.

The quality assurance of malaria microscopy unit was established by National Malaria Control Program, Ministry of Health (MoH) in 2009 to respond to the internal malaria microscopy validation process, in microscopy training for malaria diagnosis in the country, monitoring and supervision, and other relevant activities regarding laboratory diagnosis of malaria in Timor-Leste is described. Trained laboratory technicians who are working in the relevant unit. There are two ways of malaria microscopy validation process such as onsite validation and monthly validation after received malaria blood smear from senior analyst at the municipality level. The aim of this work is to describe the quality assurance of malaria microscopy system in Timor-Leste. The management of quality assurance service support, the importance of quality assurance of malaria microscopy, the role of quality assurance of malaria microscopy, challenge and opportunities encountered by quality assurance microscopy unit, National Health Laboratory are highlighted. Key words: Quality assurance of malaria microscopy, system, Timor-Leste.

The study analyzed Ecuador's presence in the Web of Science (WoS) post-pandemic from a multivariate dynamic, highlighting a significant transformation in scientific communication towards open access (OA). The methodology integrated multivariate statistical techniques, using R and specialized tools, to process 9,085 relevant articles, 52% of the Ecuadorian publications in WoS between 2019 and 2021 were open access. This movement reflects a commitment to quality research and accessibility, showing an increase in publications and citations under OA. The research underscores the importance of establishing robust national OA policies in Ecuador to promote scientific collaboration and an equitable distribution of knowledge. Despite funding challenges and the lack of specific regulations, educational institutions in Ecuador have maintained a constant scientific output, adapting to the global environment and the demand for transparent information. The study concludes that there is an urgent need for a holistic approach to OA in the country, recognizing the progress made despite the difficulties.

The assessment of Health-Related Quality of Life (HRQoL) in Thalassemia offers a holistic approach to the disease and facilitates better communication between physicians and patients. This study aimed to evaluate the HRQoL of Transfusion-Dependent Thalassemia (TDT) patients in Greece. This was a multicentre, cross-sectional study conducted in 2017, involving 283 adult TDT patients. All participants completed a set of two QoL questionnaires, the generic SF-36v2 and the disease-specific TranQol. Demographic and clinical characteristics were used to predefine patient subgroups. Significant factors identified in univariate analysis were entered into a multivariate analysis to assess their effect on HRQoL. The SF-36 scores of TDT patients were consistently lower, compared to the general population in Greece. The mean summary score of TranQol was relatively high (71±14%), exceeding levels observed in national surveys in other countries. Employment emerged as the most significant independent factor associated with better HRQoL, whereas age had the most significant negative effect. This study represents the first comprehensive QoL assessment in a representative sample of the TDT population in Greece. The implementation of TranQol allowed for the quantification of HRQoL in Greece, establishing a baseline for future follow-up, and identifying more vulnerable patient subgroups.

Background: Catheter ablation (CA) benefits atrial fibrillation (AF) patients with heart failure (HF). Brain natriuretic peptide (BNP), a marker of left-ventricular pressure load, may serve as a potential surrogate for predicting quality of life (QOL) in broader range of patients. Methods: Within the multicenter KiCS-AF registry, 491 AF patients underwent CA without clinical HF (e.g. documented history of HF, left ventricular ejection fraction ≤40%, or BNP levels ≥100 pg/mL). Participants, aged 61±10 years, were categorized by baseline BNP quartiles. Atrial Fibrillation Effect on QualiTy-of-Life (AFEQT) questionnaire assessments were assessed at baseline and 1 year. Results: Lower baseline BNP correlated with reduced AFEQT scores. Post-CA, all groups showed significant AFEQT score improvements. Lower BNP group displayed notable enhancements (18.2±1.2, 15.0±1.1, 12.6±1.2, 13.6±1.2, p<0.005), especially in symptom and treatment concern areas. Even those with normal BNP levels (≤18.4 pg/ml) exhibited significant QOL improvements. Comparing PAF and non-PAF groups, the PAF group, especially with higher BNP levels, showed greater AFEQT score improvements. Conclusion: This study establishes BNP as a predictive marker for QOL enhancement in non-HF patients undergoing CA for AF. BNP levels represent AF stages, with individuals in earlier stages, especially within normal BNP levels, experiencing greater QOL improvement.

Multiple sources influence air quality and regional climate in complicated atmospheric emission situations like urban agglomerations. To resolve pollution plumes and source influences in polluted areas, a comprehensive chemical fingerprinting of sources utilizing non-methane hydrocarbons (NMHCs) and the identification of acceptable tracer molecules and emission ratios is required, in contrast to pristine locations, where reliance on a single or a few chemical tracers is frequently sufficient. We have characterized the prevalence of NMHCs fingerprints in the urban areas and quantified the correlation of windspeed with the concentration of these pollutants. eNose sensors and Air quality management stations provide the data to identify the emission sources of such pollutants. Based on our analysis, the average NMHC concentration in 2021 has been recorded 0.424 ppm at point 1 AQMS whereas at point 2 AQMS it was 0.256 ppm. Such outcomes could be attributed to the proximity of emissions sources, the direction and speed of the wind, or both. Moreover, traffic can be a major contributor to pollution levels in any urban area. More research based on a larger dataset is required before definitive conclusions can be drawn, and viable solutions can be proposed.

The phytoplankton community in 66 reservoirs ubicated at the hydrographic basin of the Ebro River (Spain) was analyzed. Samples were collected in the summer season during the period 2010-2015, with the main purpose of evaluate the Trophic State and Ecological Potential according to the Water Framework Directive of the European Union. In this work we presented a representative overview of several consecutive years of the state of the reservoirs and their associated trophic status; methodology was to obtain statistically significant relationships between the phytoplankton community and main physicochemical water quality variables (water transparency, pH, chlorophyll a, total and soluble phosphorus, anoxic zone depth, nitrite, nitrate and ammonium concentrations). We provide data for retrospective comparative of the state of the reservoirs with previous and current studies in order to improve the management of these reservoirs, and to serve as data reference for future works in a context of global change (climate and pollution).

The lengthy maturation period is the key cause of the reduced hot pepper market value. An experiment was performed to assess the effects of R/B/W light qualities on reducing the maturation period. The maturation period was shortened by 16 days under 4R:1B:5W compared to the control. The appearance of the first flower is a limiting factor affecting the maturation period. It exhibited a dark purple color and an abnormal petal under 4R:1B:5W compared to the control, which was associated with increased contents of flavonoids, total organic acids, and phenolics and decreased total amino acid and carbohydrate contents. Plant hormone, flavonoid, ABC transporters, key metabolites (such as amino acid, carbohydrate, organic acid) was associated with first flower development. Ethylene response factors (ERFs) mediated by light, especially ERF021, were identified as potential hub regulators during the development of the first flower due to their involvement in all the associated metabolic pathways.

Fresh-cut apple is commonly known as minimally processed agriculture products because of their convenience and ease of consumption. However, during storage, the quality of the apple rapidly changes after the cutting process due to enzymatic and non-enzymatic processes. This study aimed to monitor the quality changes of fresh-cut apples at various temperatures and different types of products in the application of a cold chain system during distribution and storage. The results showed that the total viable count in fresh-cut apples initially differed between apple only and mixed products (apple, orange, and tomato) during storage (p &lt; 0.05). Moreover, there are no significant differences (p &gt; 0.05) in physicochemicals except firmness, titratable acidity, and pH, which are highly correlated to microbial growth (total viable count and total coliform number). Furthermore, the optimal temperature for extending the shelf-life of fresh-cut apples was at 4°C.

This study explores the interplay between web-based professional development, teachers' self-efficacy, resilience, and work values in the context of the Davao Region. The investigation reveals significant findings in three key areas: web-based professional development, teachers' resilience, and teachers' work values. The survey indicates that web-based professional development significantly impacts teachers' self-efficacy, with interaction self-efficacy registering the highest mean score. Moreover, teachers' resilience is manifested across emotional, motivational, and social dimensions, with emotional resilience scoring the highest mean. Teachers' work values, encompassing physical facilities, social environment, job security, new challenges, professional growth, personal growth, and interpersonal relationships, all demonstrate high descriptive equivalents. The study establishes a significant positive correlation between web-based professional development and teachers' self-efficacy, as well as a significant relationship between teachers' resilience and their work values. Furthermore, both web-based professional development and teachers' resilience exert a significant influence on teachers' work values.The conclusions drawn from the study highlight the prominence of web-based professional development, teachers' resilience, and work values in the educational landscape of the Davao Region. The findings underscore the interconnectedness of these factors and their crucial role in shaping the teaching profession. In light of these results, recommendations are made to inform policy decisions and enhance professional development programs for teachers in the region. The study encourages a holistic understanding of the relationships between web-based professional development, self-efficacy, resilience, and work values, aiming to contribute to the continuous improvement of education quality in the Davao Region. Additionally, future research is suggested to delve deeper into specific aspects of teachers' general self-efficacy, social resilience, and interpersonal relationships for a more comprehensive understanding.

Background: Caring for individuals with mental disorders poses significant challenges for caregivers, often leading to compromised quality of life and mental health issues such as stress, anxiety, and depression. This study aims to assess the extent of these challenges among caregivers in Greece, identifying which demographic factors influence their well-being. Method: A total of 157 caregivers were surveyed using the SF-12 Health Survey for quality of life assessment and the DASS-21 questionnaire for evaluating stress, anxiety, and depression symptoms. T-tests, Kruskal-Wallis tests, Pearson correlation coefficients, and regression analyses were applied to understand the associations between demographics, quality of life, and mental health outcomes. Results: The study found that caregivers, especially women and younger individuals, faced high levels of mental health challenges. Marital status, educational level, and employment status also significantly influenced caregivers' well-being. Depression was the most significant factor negatively correlating with the mental component of quality of life. The magnitude of burden experienced by caregivers highlighted the urgency for targeted social and financial support, as well as strategic treatment programs that consider caregiver well-being. Conclusions: Caregivers of individuals with mental disorders endure significant stress, anxiety, and depression, influencing their quality of life. Demographic factors such as age, gender, marital status, education, and employment status have notable impacts. Findings emphasize the need for society-wide recognition of caregivers' roles and the creation of comprehensive support and intervention programs to alleviate their burden, particularly in the context of the COVID-19 pandemic.

Abstract: Background: Bangladesh has achieved remarkable progress in reducing maternal mortality, yet postpartum deaths remain a significant issue. Emphasis on quality postnatal care (qPNC) is crucial, as increased coverage alone has not sufficiently reduced maternal morbidity and mortality. Methods: This study included data from the Bangladesh Maternal Mortality Survey of 32,106 mothers who delivered within three years prior to the survey. Descriptive statistics were used to report coverage and components of postnatal care stratified by covariates. Log-linear regression models were used to assess the determinants of quality postnatal care among facility and home births. Results: From 2010 to 2016, postnatal care coverage within 48 hours of delivery by a qualified provider rose from 23% to 47%. 94% of facility births received timely PNC, contrasted with only 6% for home births. Despite the increased coverage, quality of care remained as low as 1% for home births and 13% for facility births. Key factors affecting qPNC utilization included socio-demographic factors, pregnancy complications, delivery method, financial readiness, and mobile ownership. Conclusion: Importantly, deliveries assisted by skilled birth attendants correlated with higher quality postnatal care. The study reveals a significant gap between the coverage and quality of postnatal care in rural Bangladesh, especially for home births. It underscores the need for targeted interventions to enhance qPNC.

Oceans cover about 70% of the Earth's surface, and about 95% remain unexplored for various reasons. Underwater wireless communication has been revolutionised with the help of Internet of Things networks. Recently, applications such as collecting marine data, marine monitoring, disaster prevention, historical exploration, oil and gas exploration, shipwreck exploration, maritime security, and monitoring of aquatic species and water pollution, and several applications have become possible. However, the problem of routing, information transfer, and resource preservation in the fluid underwater environment remains unsolved. In this research, we were looking for a solution to make routing more efficient, considering the various and practical criteria for the quality of service of the underwater IoT network. One of the outstanding features of this research is the possibility of dynamically weighing the parameters involved in routing and taking optimal and distributed decisions between network components. The proposed method has achieved acceptable results in terms of quality of service compared to recent methods.

Accounting studies neglected to link corporate social responsibility to accounting information, the theoretical background revealed the study gap and the paper referred to it in the question: Do the corporate social responsibility CSR dimensions affect the accounting information quality? as the study aimed to reveal the effect of corporate social responsibility dimensions (economic, ethical, legal, and philanthropic) on accounting information quality (relevance and reliability) in banks in the Riyadh Governorate in Saudi Arabia. The researcher used a questionnaire to collect data from the study sample, and the data analysis was done using SPSS and smart partial least squares (pls), and its reliability and validity have been confirmed. Result revealed a positive effect of CSR (economic, ethical) dimension on the relevance of accounting information, a negative effect of CSR Legal dimension on the relevance of accounting information, and no effect of CSR philanthropic dimension on the relevance of accounting information, a positive effect of CSR (ethical, philanthropic) dimension on the reliability of accounting information and no effect of CSR economic and legal dimension on the reliability of accounting information.

The application of chitosan and alginate coatings for Ready-to-Eat (RTE) baked fish product were studied. An experimental design was used to investigate the effect of coating polysaccharide concentration and glycerol addition on the safety (microbial growth), and quality (water loss and lipid oxidation) of RTE seafood product under optimal, and abused storage conditions. The results showed that a chitosan coating with 1% (w/v) chitosan in 1% (v/v) acetic acid, and 15% (w/w chitosan) glycerol, or 1% (w/v) alginate coating with no glycerol, and no crosslinking showed the best performance in controlling the tested safety and quality parameters. Desirability method was used to identify the shelf life of chitosan, alginate and double coated RTE products. Whereby, chitosan coated samples showed the best performance with a third fold shelf life extension compared to uncoated products.

Saudi Arabia is a prominent producers of dates, with 1.6 million tons annually. There is a need to evaluate physical properties and quality of fruits non-destructively and then be modeled and predicted throughout the storage period. The aim of the current study was to generate a quality index (Qi) and Near-infrared spectra (NIR) models non-destructively to predict properties of Barhi dates fruits including objective and sensory evaluations. The engineering properties of Barhi dates were measured and modeled with quality index (Qi) based on NIR of fresh Barhi fruits (hardness, color, TSS, pH, and sensory evaluations) and during storage in cold, ambient, and controlled at-mosphere (CA) for up to four months. The prediction of Qi is non- destructively based on NIR utilizing PLSR and ANN data analysis. The results showed that the Qi generated corresponds with high precision to the characteristics of the examined fruits through the duration of the storage period with R2 of 0.96. The NIR spectrum proves to be an efficient method to evaluate the Barhi fruits' quality index. where ANN was found to be more suitable than PLSR analysis. Thus, NIR can be utilized to accurately predict the Qi of fruits quality effectively throughout the handling, processing, transporting, storage, and retail sector supply chain.

A milk drink flavored with dates syrup produced at a lab scale level was evaluated. The production process of date syrup involves a sequence of essential unit operations, commencing with the extraction, filtration, and concentration processes from two cultivars: Sukkary and Khlass. Date syrup was then mixed with cow’s and camel’s milk at four percentages to form a nutritious, natural, sweet, and energy milk drink. Sensory, physical, and chemical characteristics of the milk drinks flavored with date syrup were examined. The objective of this work was to measure physiochemical properties of dates fruits and milk drinks flavored with dates syrup, then to evaluate the physical properties of milk drinks utilizing a non-destructive NIR spectra. The study assessed the characteristics of the milk drink enhanced with date syrup by employing near-infrared spectra (NIR) spectra and analyzed utilizing partial least-square regression (PLSR) and artificial neural network (ANN) analysis. The NIR spectrum proved to be highly effective in estimating the physiochemical attributes of the flavored milk drink. The ANN model outperformed the PLSR model in this context. RMSECV is considered a more reliable indicator of a model's future predictive performance compared to RMSEC, R2 ranged between 0.946 and 0.989. Consequently, non-destructive NIR technology demonstrates significant promise for accurately predicting and contributing to the entire production process of the product's properties examined.

Although hydrogen gas (H2) treated soil improves crop biomass, this approach appears difficult for the field application due to the flammability of H2 gas. In this report, we investigated whether and how H2 applied in hydrogen nanobubble water (HNW) improves the yield and quality of cherry tomato (Lycopersicon esculentum var. cerasiforme) with/without fertilizers. Two-year field trials showed that compared to corresponding controls, HNW without/with fertilizers improved cherry tomato yield per plant by 39.7% and 26.5% in 2021 (Shanghai), and 39.4% and 28.2% in 2023 (Nanjing). Compared to surface water (SW), HNW increased soil available nitrogen (N), phosphorus (P), and potassium (K) consumption regardless of fertilizer application, which may be attributed to the increased NPK transport related genes in roots (LeAMT2, LePT2, LePT5, and SlHKT1,1). Also, HNW-irrigated cherry tomato displayed higher sugar-acid ratio (8.6%) and lycopene content (22.3%) than SW-irrigated plants without fertilizers. Importantly, the beneficial effects of HNW without fertilizers on yield per plant (9.1%), sugar-acid ratio (31.1%), volatiles (20.0%) and lycopene contents (54.3%) were stronger than those achieved by fertilizers alone. In short, this study clearly indicated that HNW-supplied H2 not only exhibited fertilization effect on enhancing tomato yield, but also improved fruit quality with a lower carbon footprint.

The quality of cellular products used in biological research can directly impact the ability to ob-tain accurate results. Epstein-Barr virus (EBV) is a latent virus that spreads extensively world-wide, and cell lines used in experiments may carry EBV and pose an infection risk. The presence of EBV in a single cell line can contaminate other cell lines used in the same laboratory, affecting experimental results. We developed three EBV detection systems: (1) a polymerase chain reac-tion (PCR)-based detection system, (2) a recombinase polymerase amplification (RPA)-based de-tection system, and (3) a combined RPA-lateral flow assay (LFA) detection system. The mini-mum EBV detection limits were 1×103 copy numbers for the RPA-based and RPA-LFA systems and 1×104 copy numbers for the PCR-based system. Both the PCR and RPA detection systems were applied to 192 cell lines, and the results were consistent with those obtained by the EBV assay methods specified in the pharma-ceutical industry standards of the People's Republic of China. 10 EBV-positive cell lines were identified. The combined RPA-LFA system is simple to operate, allowing for rapid results visualization. This system can be implemented in laborato-ries and cell banks as part of a daily quality control strategy to ensure cell quality and experi-mental safety and may represent a potential new technique for the rapid detection of EBV in clinical samples.

The variability of the material properties of steel from different suppliers causes problems in achieving the required surface quality after turning. Therefore, the manufacturer needs to be able to estimate the resulting quality before starting production, especially if it is an expensive, small-batch production from stainless steel. Predictive models will make it possible to estimate the surface roughness from the mechanical properties of steel in the Mill Test Certificate (MTC) and thus support decision-making about the supplier selection or the acceptance of a material supply. Multivariate second-order polynomial model and feedforward back-propagation Artificial Neural Network (ANN) model were used to enhance the methodological robustness in formulating the decision if the predicted surface roughness is outside the required range, even before accepting the delivery. Both models can accurately predict surface roughness, while the ANN model is more accurate than the polynomial model; however, the predictive model is sensitive to the accuracy of the input data, and the model’s prediction is valid only under precisely defined conditions. The prediction model is used in a step-by-step decision-making procedure, which enables the trained staff to make a quick decision.

Background: Health management is gaining importance as a business resource to enhance employee well-being. The rise of remote work during COVID-19 impacted lifestyle habits. This study explores the impact of tele-exercise intervention on remote workers' lifestyle habits, aiming to improve health and productivity. Methods: This study divided into remote (G1) and face-to-face (G2) groups. Over three months, G1 followed a 30-minute weekly exercise program. Measurements and questionnaires were collected at three time points covering areas like presenteeism, weight, sleep, stress, job satisfaction, and happiness. Data underwent Two-way repeated measures ANOVA, Autocorrelation, Correlation Analysis, and Correspondence Analysis to assess differences and relationships between G1 and G2. Results: ANOVA showed that a significant difference was observed in Daily Stress (DS) between G1 and G2, with G1 exhibiting higher DS. Autocorrelation Analyses showed for G1 that strong relationships each of BMI, Presenteeism (PST), Daily Stress (DS), Stress Relief (SR), Sleep Quality (SQ), Purpose of Work (PW), and Satisfaction of Life (SL) in the time frame. Correlation Analysis showed for G1 that the pairs of PRS and SQ, and DS and SL had strong positive relationships, and the pairs of BMI and PRS, and BMI and SQ had strong negative relationships. Autocorrelation Analyses showed for G2 that strong relationships each of SR, Stress due to Remote Work (SRW), ST, SQ, and PW in the time frame. Correspondence Analysis showed that that G1 was encompassed in a job and life satisfaction area, and G2 was encompassed in a sleep and stress for weight control area.

This work introduces a novel facial image capture system that utilizes computer vision technology and artificial intelligence for real-time detecting, tracking, and capturing of human faces. The objective of this study is to address the challenges posed by poor-quality facial images in biometric authentication, especially in passport photo acquisition and recognition. By combining face-aware capture technology with AES encryption for secure image storage, we present a completely open-source hardware solution that consists of a Jetson processor, a 16MP autofocus RGB camera, a custom enclosure, and a touch sensor LCD for user interaction. Pilot data collection demonstrates the system's ability to capture high-quality images, achieving a 98.98% accuracy in storing images of acceptable quality. The integration of AES encryption ensures data security, making the proposed system suitable for real-time applications in other domains beyond identity verification in passport applications, such as security systems, video conferencing, etc

To follow the growth and development of each tree (N = 1200) Pinus sylvestris L., var. Negorelskaya starting from the seed and continuing at the juvenile (or even generative) stage is the goal of an ambitious project to create a plant passport if possible. Five datasets of replenished empirical (tab-ular and file) and systematic data reflect the early results of a unique ongoing experiment conducted with families moved along a climatic gradient from the collection area (1731 degree days, 722 mm) to the experimental area (2326 degree days; 786 mm). Datasets of morphometric, VIS-spectrometric, and germination seed data, combined with the first results of biometric data (including the Dickson quality index) of seedlings produced from these seeds, will allow scientists in the future to conduct correlation and other statistical analysis, or train a neural network to determine the presence of connections between a seed and a plant. These data contribute to the early non-destructive diag-nosis and grading of seeds according to VIS-spectrometric properties. This dataset structure can complement the FLR-Library. In the future, by tracing seedlings in their early growth (for example, over three growing seasons at the site being restored), it will be possible to determine the degree of intensification of FRM production depending on the initial properties of the seed.

Children with epilepsy are affected by several factors, including clinical and social variables, which can lead to reductions in quality of life (QOL). Among these variables, factors relating to seizure severity such as frequent seizures and status epilepticus (SE) have been identified as important predictors of QOL. In addition, frequency of interictal epileptiform discharges (IEDs) on the electroencephalogram (EEG) may also lead to cognitive declines and behavioral disturbances. Moreover, frequent seizures and/or IEDs may play a role in emotional mediators such as stigma and fatigue in childhood epilepsy. Seizure severity and/or IEDs are thus important QOL-related factors in childhood epilepsy. Frontal lobe dysfunctions such as cognitive decline and behavioral disturbances can result in reduced QOL for both the child and their family. Frontal and prefrontal lobe growth disturbances can be present during active-phase epilepsy in some children with neuropsychological impairments. Recovery from prefrontal lobe growth disturbance may depend on the active seizure period. Disturbance of prefrontal lobe growth can recover more rapidly in children with a shorter active seizure period. In contrast, recovery may be delayed in children with a longer active seizure period. Accordingly, severe seizures can lead to neuropsychological impairments in association with prefrontal lobe growth disturbance in children with epilepsy. Moreover, frequent seizures can lead to having seizure-associated headache, perception of self-stigma and parental stigma, and fatigue. In addition, IEDs on EEG, representing persistent pathological neuronal discharges, may be associated with several pathological aspects. Frontal IEDs can be a risk factor for recurrent seizures, cognitive decline, and behavioral disturbances and may also play a role as an emotional mediator similar to stigma. In addition, behavioral disturbances may result in the presence of secondary bilateral synchrony (SBS) on EEG. Behavioral disturbances can be improved in association with reduction of IEDs in children with frontal IED and SBS. Seizure severity and IEDs on EEG may thus be associated with neuropsychological impairments, leading to QOL reduction. Therapeutic management may be desirable to remit seizures and EEG abnormalities such as frontal IED and SBS as soon as possible to improve QOL in children with epilepsy.

We aimed to determine whether A-mode ultrasound (US) can provide accurate and reliable measurements comparable to those obtained through B-mode US, under diverse conditions. Thirty healthy participants (15 female, 15 male) underwent measurements of subcutaneous fat thickness (SFT), muscle thickness (MT), and muscle quality (MQ) in the trapezius and biceps brachii muscle with both US modes after and before exercises designed to stimulate the respec-tive muscles. In three key indices, the results demonstrated high validity of A-mode, with min-imal mean differences between the two devices less than 0.91mm and intraclass correlation coef-ficients exceeding 0.95 at all measures. Also, Correlation coefficients between error scores and average scores for the trapezius and biceps brachii muscles suggested no evidence of systematic error. The trapezius MT and MQ significantly increased, and biceps brachii MT significantly in-creased after exercise (p<0.05). Notably, both A-mode and B-mode exhibited the same tendency in these post-exercise changes in muscle. This study suggests that low-cost and low-resolution A-mode US provides measurements of SFT, MT, and MQ similar to more expensive, high-resolution B-mode imaging. A-mode US can serve as an affordable and portable alternative for muscle assessment.

Milkfish (Chanos chanos) locally called Bangus in the Philippines, is a popular food fish in terms of production and consumption in the Philippines, Indonesia and Taiwan. This study characterized a typical grow-out milkfish farm in the Davao region in terms of socioeconomic profile, farming practices, and simple costs and returns. Three sites were chosen to conduct this study, mainly in Mati, Pantukan and Panabo in Davao region where N=43 farm workers provided information on their daily farming practices. Farms are commonly stocked with 16,000 fingerlings, harvesting occurs after every 6 months with six feeding times in a day. Moreover, workers were paid an average of Php 10,000 per month while the company had a gross income of Php 930,000 per cropping cycle. The feed cost shares 76% of the overall operational cost with a 27% return on investment for the first year of operation. Climate change impacts (e.g. higher sea surface temperature, unpredictable weather and flooding) and deteriorating water quality conditions were seen as bigger threats. Other results showed a positive relationship between stocking density and volume harvested (df=1, MS=0.0907, F=40.13, P=0.000) and income (df=1, MS=0.048, F=21.22, P=0.000). The study also showed the need for cheaper feed substitute and better benefits to farm workers.

Better understanding of the quality of life among nursing home residents with dementia is im-portant for developing interventions. The objectives of this cross-sectional study were to examine factors associated with poor health-related quality of life in older adults with dementia living in nursing homes in Hanoi, Vietnam. In-person interviews were conducted with 140 adults 60 years and older with dementia and information about their quality of life was obtained using the Quality of Life in Alzheimer’s Disease scale (QOL-AD). A number of sociodemographic and clinical factors associated with poor health-related quality of life (lowest tertile) were assessed through the results of physical tests, interviews with nursing home staff, and review of medical records. The average age of the study sample was 78.3 years, 65% were women, and their av-erage QOL-AD total score was 27.3 (SD = 4.4). Malnutrition, total dependence in activities of daily living, and urinary incontinence were associated with poor quality of life after controlling for multiple potentially confounding factors. Our findings show that Vietnamese nursing home residents with dementia have a moderate quality of life and interventions based on comprehen-sive geriatric assessment remain needed to modify risk factors associated with poor health-related quality of life.

: Kentucky is one of the largest coal producing states and surface coal mining has led to changes in natural land cover, soil loss, and water quality. This study explored relationships between actively mined and reclaimed areas and vegetation change and water quality parameters. The study site evaluated 58 watersheds with Landsat-derived variables (reclamation age, mining percentage, reclaimed forest percentage, and reclaimed woods percentage) as well as topographic variables (such as elevation, slope, drainage density, and infiltration). Water samples were collected in spring (n=9), summer (n=14), and fall (n=58) 2017 to study changes in water quality variables (SO42-, alkalinity, conductivity, Ca2+, Mg2+, Mn2+, Al3+, and Fe2+,Fe3+) in response to changes in land cover. Pearson correlation analyses indicated conductivity has strong to very strong relationships with other variables of water quality variables related to coal mining (except Al3+, Fe2+,Fe3+, Mn2+, elevation, slope, and drainage density) and land cover variables. In addition, separate multivariate regression analyses were performed with conductivity values based on samples collected in the fall. First, conductivity response to mining percentage, reclamation age and topographic variables were examined (adjusted R2=0.818, p &lt; 0.01). Next, vegetation cover change parameters were added to the same model, which yielded slightly improved R2 (adjusted R2 = 0.826, p &lt; 0.01). Finally, reclamation age and mining percentage were used to explain the quantity of reclaimed forested areas as a percentage of watersheds. The model was significant (p &lt; 0.01) with an adjusted R2 value of 0.641. Results suggest that the quantity (area as a percentage) of reclaimed forests may be a predictor of mining percentage and reclamation age. This study indicated that conductivity is a predictable water quality indicator that is highly associated with Coal Mine Related Stream Chemistry in areas where agriculture and urban development are limited. These findings may help the scientific community and key state and federal agencies improve their understanding of water quality attributes in watersheds affected by coal mining as well as refining land reclamation practices.

Currently, active and intelligent packaging have been developed to solve the spoilage problem for rich protein foods during storage, especially by adding anthocyanin extracts. In such film system, the antioxidant and antibacterial properties were dramatically increased by adding anthocyanins. The physicochemical properties were enhanced through interactions between active groups in anthocyanins and reactive groups in polymer chains. Additionally, active and intelligent film could monitor the spoilage of rich protein foods in response to pH change. Therefore, this film could monitor the sensory acceptance, and extending the shelf life of rich protein foods simultaneously. In this paper, the structure and functional properties of anthocyanins, the composite actions of anthocyanin extracts and biomass materials, and their reinforced properties of active and intelligent film were discussed. Also, the applications of this film in quality maintenance, shelf-life extension and quality monitoring for fresh meat, aquatic product and milk were summarized. The film that achieves high stability and continuous release of anthocyanins on demand will become an underlying trend in packaging applications for rich protein foods.

Traditional olive orchards have been grown for thousands of years and still occupy most of the world’s olive cultivation area. To compete with olive oil produced in the higher-yielding intensive orchards, the oil from traditional orchards must be of high quality. We evaluated oil quali-ty—potential and actual (under commercial conditions)—and identified the stages in the pro-duction chain that reduce oil quality in the traditional sector in the Middle East region. Our findings show a clear negative impact of growers' traditional practices on both chemical and sensorial characteristics of the olive oil. The oil originating from the commercial process had higher free fatty acid and lower polyphenol and carotenoid contents, lower stability, lower pungency, fruitiness and bitterness, and a higher prevalence of organoleptic defects than oil originating from fruit picked from the same trees in the experimental procedure. The current, commonly harvesting technique of pole beating significantly increased fruit injury and fruit with mold, leading to a reduction in oil polyphenols and an increase in free fatty acid level compared to manual picking. After harvest, storing the fruit for more than 48 h in plastic bags reduced oil quality dramatically. The traditional olive orchard could potentially be a source of high-quality Extra Virgin Olive Oil. However, handling of the fruit—from the trees until the end of the oil-extraction process—is done incorrectly, adversely affecting oil quality.

For two-dimensional forward-looking sonar imaging, high sidelobes significantly degrade the quality of sonar images. The cosine window function weighting method is often applied to suppress the sidelobe levels in the angular and range dimensions at the expense of the main lobe resolutions. Therefore, the improved spatially variant apodization imaging method for forward-looking sonar is proposed to reduce the sidelobes without degrading the main lobe resolution in angular-range dimensions. The proposed method is a nonlinear post-processing operation in which the raw complex-valued sonar image produced by a conventional beamformer and matched filter is weighted by a spatially variant coefficient. To enhance the robustness of the spatially variant apodization approach, the array magnitude and phase errors are calibrated to prevent beam sidelobe heightening from occurring prior to beamforming operations. The analyzed results of numerical simulations and a lake experiment demonstrate that the proposed method can greatly reduce the sidelobes to approximately -40 dB, while the main lobe width remains unchanged. Moreover, this method has an extremely simple computational process.

Different coffee drying technologies face complex task in ensuring an acceptable final seed moisture content. Drying technology of agricultural commodities aims to maintain and improve the quality of the agricultural products themselves. In addition to maintaining quality, especially from other bacterial attacks, it can last for a long time before further processing. Coffee commodities are promising for the welfare of coffee farmers. Drying technology plays a major role in determining the quality of coffee. Various drying models are applied including the traditional model that until now is still applied, direct drying under solar radiation. However, this drying process is less hygienic and requires a large area. Thus, one of the drying technologies that can accelerate drying time is to vary the air flow in the drying chamber so that the coffee can be determined to reduce the water content with a certain temperature. In this study, it was found that the moisture content of coffee beans dried using a dryer on air flow with variations of velocity in solar collector 1 (DB1) air velocity of 1.0m/s obtained the final mass = 732.249 gr, solar collector 2 (DB2) with air velocity 1.5 m/s obtained the final mass = 774.70 gr, solar collector 3 (DB3) with air velocity 2.0 m/s obtained the final mass = 855.10 gr, solar collector 4 (DB4) with air velocity 2.5 m/s obtained the final mass = 745.79 gr, and solar collector 5 (DB5) with air velocity 3.0 m/s obtained the final mass = 786.40 gr. Water Content DB1=12.0%, DB2=13.6%, DB3=18.5%, DB4=12.9% and DB5=15.2%. The time required for 25 hours with a maximum radiation of 586.9 w/m2, total heat utilized from solar radiation in 3 days =16.663128 MJ/m2. from the initial weight of 1500gr coffee bean samples and dried in five solar collectors with parallel simultaneously. The evaporated water content DB1=51.18%, DB2=48.35%, DB3=42.96%, DB4=50.28% and DB5=47.57%. Based on this research, it was found that the most optimum quality of coffee was by using solar collector 2 (DB2), namely with air flow of 1.5 m/s with average temperature in the drying box DB2=43.68°C, with the quality content of the coffee, Protein content=12.2%, Carbohydrate=22.8% and Free Fatty Acid (ALB) content=0.05%.

Use of fingerprints found at a crime scene is a common practice for identifying suspects in criminal investigations. Over the past two decades, attempts have been made to obtain additional information from fingerprints, beyond locating suspects as part of an investigation. This includes gender, age and nationality. Researchers demonstrated 75%-90% accuracy in gender classification based on fingerprint images. Nonetheless, despite promising results, these studies have several significant shortcomings with respect to their practical feasibility. First, they ignore the low quality and quantity of fingerprints collected from the crime scene since typically the scene of a crime has only one fingerprint collected, and the fingerprint might be partially or of poor quality as well. Second, as most results are based on a single database, public or private, it is difficult to generalize the most suitable method. Third, studies miss the untapped potential of Data-Centric AI (DCAI) approaches for improving results. The aim of this study was to compare, for the first time, the gender classification from a fingerprint using several datasets and with varying fingerprint image quality. The results from four databases are compared, three public and one internal private database. In addition, we utilize the latest Data-Centric AI (DCAI) approaches for improving classification results. The results demonstrate that a conservative Convolutional Neural Networks (CNN) such as VGG is sufficient for this task. Classification accuracy ranges from 80% to 95% depending on the quality of the fingerprint, with DCAI approaches adding 1%-4% improvement. For partially or low-quality fingerprint images, the periphery of a fingerprint is the most significant area for determining gender. The source code is also provided here for practical application.