The study aimed to know the direct effect of strategic leadership on the quality of service represented by wireless communications services, in addition to knowing the indirect effect of strategic leadership on the quality of service when using performance as an intermediary variable. This research was conducted in government institutions in the Republic of Yemen. Represented by the offices of the Ministry of Communications and Information Technology in five Yemeni cities, it targeted senior management employees, boards of directors, and middle management concerned with strategic planning and strategic leadership. To measure and evaluate the factors of strategic leadership and service quality in Offices of the Yemeni Ministry of Communications Ministry of Communications and Information Technology of the Republic of Yemen. Moreover, performance. A questionnaire was formulated and distributed to the study sample, and data was collected through questionnaires for 150 individuals in some offices of the Yemeni Ministry of Communications. This study uses structural equation model analysis from the Partial Least Squares program through the Smart Plus 4 programs. The study reached a set of results, including that all models show a direct, positive and significant effect of strategic leadership on the quality of service represented by the quality of services in the offices of the Ministry of Communications. As well as the positive relationship between them, as well as the direct and positive impact of performance on the quality of service, as well as the positive and significant relationship between them. While the results indicated a positive and significant indirect effect of strategic leadership on service quality, there is also a positive and significant indirect relationship between strategic leadership on service quality when using performance as an intermediary variable.

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.

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.

Premenstrual syndrome (PMS) continues to impact the health outcomes and emotional well-being of reproductive-age women, globally. Several studies have provided conflicting evidence concerning the role of dietary approaches in improving PMS symptoms. Accordingly, this study aimed to evaluate the possible influence of a healthy diet and motivational strategies on PMS symptoms and health-related quality of life among Omani adolescents. This open-label, randomized, prospective controlled trial was conducted in two randomly selected secondary schools, in Al Seeb Willayah, in Muscat region. Adolescents with PMS symptoms, who were at grade 10 or 11, aged 16 years or above, had regular menstrual cycles and not known to have psychiatric disorder, were included in this study. Participants in the intervention group received an individual face-to-face dietary consultation and motivational phone consultation. The health outcomes, including the PMS symptoms in both groups, and quality of life, were recorded via a daily record of severity of problems questionnaire (DRSP) and the 14-item Self-Reporting-Based Perceived Stress Scale tools, respectively. The primary outcome was the differences in the mean premenstrual symptom scores between the two groups. Secondary outcomes included the quality of life and stress levels of participants. The study period was from 1 February and ended 30 June 2021. SPSS was used to analyze the data and intention-to-treat analysis was utilized.A total of 72 adolescents with PMS were randomized to the intervention and control groups (n=36 each). Both groups were similar at baseline (P-value>0.05). No significant association was found between healthy-diet and PMS symptoms (P-value>0.05). In addition, no significant association was found between healthy-diet and quality of life at follow-up (P-value=0.216). The outcomes of this study refuted any possible relationships between healthy diet and PMS symptoms. Accordingly, dietary consultations may not facilitate the clinical management of PMS symptoms in adolescent females.

Venous leg ulcers still pose a significant medical problem worldwide. The complexity of the problem determines the need for further interdisciplinary activities that will improve the quality of life of treated patients. The study compared the quality of life of patients with venous leg ulcers who received local hyperbaric oxygen therapy or local ozone therapy procedures as a part of comprehensive treatment. The study included 129 patients (62 men and 57 women) with venous leg ulcers. Group I underwent local hyperbaric oxygen therapy (HBOT), group II - local ozone therapy (OZONE). In both groups, the patients' quality of life was assessed before the start of treatment cycle, as well as 10 weeks and 6 months after the completion of the treatment, by using the EQ-5D-5L questionnaire and the Polish shortened version of the SF-36 scale. After completing the respective therapeutic cycle, both groups showed a statistically significant (p<0.001) improvement the quality of life according to the EQ-5D-5L questionnaire and the SF-36 scale. Differences were noted between 1st examination (before treatment) and 2nd examination (10 weeks after treatment), as well as 3 examination (6 months after treatment). In the EQ-5D-5L assessment of anxiety and depression, self-care and activities of daily living 6 months after the end of treatment, better results were found in the group of patients treated with local hyperbaric oxygen therapy (p<0.001). In this group, 6 months after the end of the treatment, a statistically significantly higher result on the EQ-VAS scale was also obtained (73.09±19.8 points vs. 68.03±17.37 points, p=0.043). However, in the SF-36 assessment 6 months after the end of treatment better results - a statistically significantly lower value of the quality of life index - were recorded in the group of patients treated with local ozone therapy (103.13±15.76 points vs. 109.89±15.42 points, p<0.015). Hyperbaric oxygen therapy and local ozone therapy procedures have a beneficial effect on improving the quality of life of patients with venous leg ulcers.

Lots of efforts are made to optimize spectrum quality used for indoor farming to maximize artificial light utilization and reduce water loss. For such an improvement, green (G) light supplementation to a red-blue (RB) background was successfully employed in our previous studies to restrict both non-photochemical thermal dissipation (NPQ) and stomatal conductance (gs). At the same time, however, the downregulation of NPQ and gs influences the leaf temperature (Tleaf) in opposite ways. Thus, to elucidate which factor plays a more prominent role in Tleaf regulation and whether such response is temporal or permanent we investigated the correlation between NPQ or gs and the subsequent Tleaf. To this end, we analysed tomato plants (Solanum lycopersicum L. cv. Malinowy Ozarowski) grown solely under monochromatic LED lamps (435, 520, or 662 nm; 80 µmol m–2 s–1) or under mixed RGB spectrum (1:1:1; 180 µmol m–2 s–1), and simultaneously measured the gs and Tleaf with an infrared gas analyser and thermocouple or employed infrared thermal camera (FLIR) during thermal imaging analyses. Results documented that growth light quality significantly modified the Tleaf, and such response is not temporal. Furthermore, we found that plants' actual adaxial leaf surface temperature is more closely related to NPQ amplitude, while the temperature of the abaxial surface corresponds to gs.

The present study finds the association of board characteristics (such as gender diversity, independence, female chairperson or/and female CEO, and board size) and the quality of Corporate Social Responsibility (CSR) disclosure of the top 100 Pakistan Stock Exchange (PSX) listed companies. Unlike most earlier studies in similar contexts, we have focused on CSR disclosure ‘quality’ and not ‘quantity’. We conducted the content analysis of secondary Corporate Governance (CG) and CSR data extracted from the annual reports of PSX-listed companies across ten industrial sectors from period of 2017 and 2018. Our empirical investigation through univariate and multiple regression analysis with Ordinary least squares (OLS) techniques revealed that all the board characteristics potentially have a significant association in lessening CSR disclosure quality. We acknowledge several research limitations, including the study time period and selected board characteristics. While our study has provided some understanding of the association of board characteristics with CSR disclosure quality of PSX-listed companies, several research gaps still need to be addressed. Future investigators should examine this association through the pre-COVID-19 and post-COVID-19 connections and the inclusion of a systems theory perspective.

Power converter technologies have become increasingly vital in various applications due to their efficient management of electrical energy. With the growing prominence of renewable energy sources like solar and wind, the high penetration of power electronic converters has been justified. However, ensuring power quality has emerged as a significant challenge for grid-connected power converters. The divergence from the ideal sinusoidal waveform in terms of magnitude and frequency impacts both grid-side currents and voltages. Several studies have proposed solutions to address power quality issues at the load side. The advancement of power converters has been fueled by the development of high-performance microprocessors and the emergence of high-speed switching devices, such as SiC-MOSFETs. This paper focuses on the design of voltage source converters, particularly those based on SiC-MOSFET semiconductor devices. The article presents the design of H-Bridge cells, discusses two-level voltage source converters based on cascade H-Bridge cells in parallel configuration with experimental fault analysis, addresses the seven-level voltage source converters topology, and explores the design and experimental results of the matrix converter. The findings underscore the importance of considering the entire converter design for improved performance at high switching frequencies. The article concludes by summarizing the main outcomes and implications of this research.

Electrical power quality is one of the main elements in power generation systems. At the same time, it is one of the most significant challenges regarding stability and reliability. Due to different switching devices in this type of architecture, different kinds of power generators, and non-linear loads are used for different industrial processes. As a result of this, the need to classify and analyze Power quality disturbance (PQD) to prevent and analyze the degradation of the system reliability affected by the non-linear and non-stationary oscillatory nature. This paper presents A Novel Mul-titasking Deep Neural Network (MDL) for the Classification and Analysis of Multiple Electrical Disturbances. The characteristics are extracted with a specialized and adaptive methodology for non-stationary signals, Empirical Mode Decomposition (EMD). The methodology’s design, devel-opment, and various performance tests are carried out with 28 different difficulty levels, such as severity, disturbance duration time, and noise in the 20 dB to 60 dB signal range. MDL was devel-oped with a diverse data set in difficulty and noise, with a quantity of 4500 records of different samples of multiple electrical disturbances. The analysis and classification methodology has an average accuracy percentage of 95% with multiple disturbances. In addition, an average accuracy percentage of 90% in analyzing important signal aspects for studying electrical power quality such as crest factor, Per Unit voltage analysis, Short Term Flicker Perceptibility (Pst), and Total Harmonic Distortion (THD), among others.

Today, mobile phones are at the center of many consumers' lives and a part of people's lives. Although this tool was considered a luxury initially, it has gradually become a necessary tool with the reduction of the price and the increase of its functions. Consumers choose specific models of mobile phones according to their needs. Mobile phones have quality features that are expressed in the form of quality dimensions. These dimensions are mostly expressed by word of mouth (WOM). In this research, first; we collected the opinions of 350 students about 4 brands of mobile phones based on Garvin's quality of dimensions, finally; the students’ opinions about mobile phones were evaluated with integrated TOPSIS with interval-valued intuitionistic fuzzy numbers technique, and the priority of 4 phone brands was determined based on students' opinions.

As the first pilot ecological civilization zone in China, Fujian Province has an excellent ecological environment quality, and its ecological environment-related indices continue to be among the highest in the country. In order to investigate the causes of the excellent ecological quality in Fujian Province in the past 15 years, this paper selects MODIS images, land use data and provincial and municipal statistical yearbook data of Fujian province from 2005 to 2020 as data sources, evaluates the ecological system health of Fujian Province by remote-sensing ecological index (i.e. RSEI), constructs the land use intensity system of Fujian Province at the same time, and uses a coupled coordination model to analyze the coupling between RSEI and The coupled coordination model was used to analyze the coupling relationship between RSEI and land use intensity, and finally the spatial and temporal evolution of ecological health in Fujian Province from 2005 to 2020 was analyzed. The results show that the coupled coordination between land use intensity and ecosystem health in Fujian province showed a continuous increase between 2005 and 2020, especially in Ningde, where the increase was most significant, from 0.0993 to 0.963, this pattern of spatial distribution is lower in the south-eastern coastal region than in the north-western interior, higher in the south-western region than in the north-western region, and higher in the north-eastern region than in the south-eastern region. In terms of the type of role, the land use intensity of most cities in Fujian Province in 2005 played an obvious role in blocking the degree of ecosystem health, but as time changed, urban land use continued to be optimized and reached moderate or even high quality coordination with the quality of the ecological environment, but Xiamen City developed relatively slowly and its 2020 coupling degree value was 0.315, which was still in mild disorder. This study fills a gap in the research mechanism of the interaction between the degree of ecosystem health and land use intensity, and also provides a new perspective for the construction of ecological civilization and the assessment of the degree of ecosystem health in Fujian Province and the whole country.

The Selective Paste Intrusion (SPI) method is a layer-by-layer additive manufacturing technique that allows for the production of complex geometries in concrete elements by selectively bonding aggregates with cement paste in a particle bed. To create reinforced concrete, the Wire and Arc Additive Manufacturing (WAAM) process shall be integrated into SPI. This technique allows the production of almost free-formed reinforcement and thus complements the advantage of SPI to produce free-formed structures of almost any geometry. However, integration of WAAM into SPI poses a considerable challenge, as high temperatures are generated during the welding process. These temperatures can negatively affect the rheological properties of the cement paste, in turn the penetration behavior of the paste in the particle bed and, subsequently, the mechanical properties of the hardened concrete. A possible passive cooling strategy is to increase the protruding length of the reinforcement bars out of the particle-bed. This requires that the distance of the print nozzle to the particle bed is as well increased, since it must be possible to move it across the reinforcement. The objective was thus to investigate the effect of that distance on print quality and to quantify a maximum allowable distance for an adequate print quality (for the printer setting used) in terms of shape accuracy and concrete strength. Compressive and flexural strength tests as well as geometrical measurements using a 3D scanning method were performed on specimen, printed with varying print nozzle to particle bed distances. It can be stated that for the used SPI print-heads, nozzle-types and parameter settings, the distance between the nozzle and the particle bed should not exceed 50 mm to ensure sufficient print quality in both shape accuracy and mechanical strength.

Power quality problem is a hot area in power systems and drives that has drawn the attention of many researchers. This is because of the threat it poses on the health of electrical systems and the cost incurred on utility bills. The problem arises as a result of the need for reactive power to be supplied alongside active power in power transmission and distribution. Unfortunately, reactive power is consumed by almost all components of the system, leading to a shortage. To solve this problem, there is a need to compensate for the lost reactive power. Several researchers have proposed various approaches to mitigate this problem such as thyristor switched capacitor bank, series compensator, series reactor, series var compensator (SVC), Static Synchronous Compensator (STATCOM), synchronous condenser and others. In order to further draw attention in this area, this work investigates a number of research papers on power compensation techniques and draw up challenges from each work that can be considered for further investigation. To this end, each research paper reviewed is evaluated in terms of problem solved, technique used, and results obtained. It therefore offers ample opportunities for researchers to explore in improving power quality and power system safety.

The effective integration of aerial remote sensing data and ground multi-source data has always been one of the difficulties of quantitative remote sensing. A new monitoring mode is designed which installs the hyperspectral imager on the UAV and places a buoy spectrometer on the river. Water samples are collected simultaneously to obtain in situ assay data of total phosphorus, total nitrogen, COD, turbidity and chlorophyll during data collection. The cross correlogram spectral matching (CCSM) algorithm is used to match the data of the buoy spectrometer with the UAV spectral data to reduce the UAV data noise significantly. An absorption characteristics recognition algorithm (ACR) is designed to realize a new method for comparing UAV data with laboratory data. This method takes into account the spectral characteristics and the correlation characteristics of test data synchronously. It is concluded that the most accurate water quality parameters can be calculated by using the regression method under five scales after the regression tests of multiple linear regression method (MLR), support vector machine method (SVM) and neural network (NN) method. This new working mode of integrating spectral imager data with point spectrometer data will become a trend in water quality monitoring.

A correct system design can be systematically obtained from a specification model of a real-time system that integrates hybrid measurements in a realistic industrial environment, this has been carried out through complete Matlab / Simulink / Stateflow models. However, there is a widespread interest in carrying out that modeling by resorting to Machine Learning models, which can be understood as Automated Machine Learning for Real-time systems that present some degree of hybridization. An induction motor controller which must be able to maintain a constant air flow through a filter is one of these systems and it is discussed in the paper as a study case of closed-loop control system. The article discusses a practical application of ML methods that demonstrates how to replace such closed loop in industrial control systems with a Simulink block generated from neural networks to show how the proposed procedure can be applied to derive complete hybrid system designs with artificial neural networks (ANN). In the proposed ANN-based method to design a real-time hybrid system with continuous and discrete components, we use a typical design of a neural network, in which we define the usual phases: training, validation, and testing. The generated output of the model is made up of reference variables values of the cyber-physical system, which represent the functional and dynamic aspects of model. They are used to feed Simulink/Stateflow blocks in the real target system.

This study examines the spatial impact of FDI on the poverty of 44 African countries. In achieving this, the study uses the Driscoll-Kraay fixed effect instrumental variable regression, instrumental variable generalised method of moments estimator (IV-GMM), and the spatial durbin model. The empirical investigation of this study yielded four significant findings: (1) neighbouring countries’ FDI has a positive and significant impact on the incidence and intensity of host country’s poverty. (2) Improved institutional quality in neighbouring countries has a significant impact on FDI-poverty reduction nexus of the host country. (3) the empirical results lend support for a significant spatial spillover of poverty in the region. (4) the marginal effect results indicate that countries within the region are no longer in isolation or independent, i.e., the level of poverty in a particular country is influenced by its determinants in the neighbouring country. This result is robust to the alternative proximity matrix, which is the inverse distance. Since there is spatial interdependence among African countries, we recommend that African governments through the African Union (AU) should not only champion the institutional reform in the region, but also establish a binding mechanism to ensure reform implementation.

The objective was to analyze the effects of adding anthocyanin delphinidin-3-O-sambubioside and cyanidin-3-O-sambubioside of Hibiscus sabdariffa L. in animal diets. Scientific articles published before 2021 in clinics, pharmacology, nutrition, and animal production were included. The grains/concentrate, metabolic exigency, and caloric stress contribute to increasing the reactive oxygen species (ROS); the excess of ROS unbalance the oxidants and antioxidants. Cyanidin-3-O-sambubioside and delphinidin-3-O-sambubioside have antioxidant, antibacterial, antiviral, and anthelmintic activities. In the rumen, anthocyanin might show interactions and/or synergisms with substrates, microorganisms, and enzymes which could reduce the fiber degradability, but increase the potential methane (CH4) emissions; since anthocyanin interferes in the biohydrogenation of fats, they increase the fat milk and meat quality. Anthocyanins reduce plasma oxidation and deposit in tissues, increasing the milk and meat antioxidant activities. Cyanidin-3-O-sambubioside and delphinidin-3-O-sambubioside act as inhibitors of the angiotensin-converting enzyme (ACEi) and rennin expression which may improve milk yield (there is not enough evidence in ruminants, though). Polyphenols affect the reproductive potential. Sub products of HS contain as many amounts of polyphenols as calyces, and their inclusion in diets would positively affect the average daily gain and fat meat quality. Including HS in ruminant diets can improve the meat and milk quality.

Multiple social and environmental justice concerns are linked to urban form such as the distribution of socioeconomic class populations, healthcare spending, air pollution exposure, and human mobility. This study used 1m resolved LIDAR data to characterize land use in Salt Lake County, Utah and associate it with sociodemographic and air quality data at the census block group and zip code levels. We found that increasing tree cover was associated with higher per capita income and lower minority populations while increasing built cover was linked to lower per capita income and higher minority populations. Air quality showed less strong correlations, however, decreased non irrigated cover, increased built cover, and higher amounts of households living under poverty was related to higher long-term PM2.5 exposure. Several policy efforts have been undertaken to improve air quality and reduce negative health outcomes in Utah which are being informed by regulatory and research grade air quality sensors.

Depending on the characteristics of the industrial area, toxicity evaluation of human body, risk assessment and health impact assessment may directly cause cancer due to air pollution. Environmental data collection is from August 2018 to January 31, 2019, and the average, minimum, and maximum values of air pollution data respectively. According to the global data on global trends using the Big Data, high blood pressure is confirmed at 33rd place in the world, and myocardial infarction among the environmental diseases is confirmed to be lower than Korea. Disease that occurred in Jeolla province industrial complex considering the characteristics of our country was identified as representative. Air pollutants are considered to be the causes of allergic diseases in Korea. PM10 was found to be higher than the control area (28.8804348 (㎍ / ㎥), 31.7065217 (㎍ / ㎥) and 32.8532609 (㎍ / ㎥). The mean concentrations of PM2.5 in the middle and high exposure areas were lower than those of the control areas, but the highest in the intermediate exposure areas was 16.5978261 (㎍ / ㎥), 16.1086957 (㎍ / ㎥) and 17.1847826 (㎍ / ㎥) respectively. The relationship between the major variables of environmental exposure in Yeosu was confirmed to be correlated with high blood pressure, chronic obstructive pulmonary disease (COPD), bronchitis, cerebrovascular, diabetes, thyroid disease, sinus infection, anemia and pneumonia.

Reduced nutrient mineralization rates under minimum tillage are usually compensated by mineral fertilizer application. These cannot be applied in organic farming systems, however. We hypothesized that organic minimum tillage based on frequent cover cropping and application of dead mulch will improve soil fertility and can compensate for the potential negative effects of minimum tillage. Two long-term field experiments were set up in 2010 and 2011 comparing plough versus minimum tillage including application of transferred mulch. As second factor, the application of compost versus mineral potassium and phosphorus was compared. In 2019, soils were analyzed for soil pH, organic carbon, macro-, micronutrients, microbial biomass, microbial activity and total nematode abundance. In addition, performance of pea in the same soils was determined under greenhouse conditions. Across both experiments, macronutrients (+52%), micronutrients (+11%), microbial biomass (+51%), microbial activity (+86%), and bacterivorous nematodes (+112%) increased in minimum tillage compared with the plough-based system. In the greenhouse, pea biomass was 45% higher in the soil that had been subjected to minimum tillage compared to the plough. In conclusion, soil fertility can be improved in organic minimum tillage systems by intensive cover cropping and application of dead mulch to levels higher than in a plough-based system.

If genetic gains in wheat yield are to be achieved in today’s breeding, increasing genetic variability of cultivated genotypes is an essential requisite to meet. To this aim, alien gene transfer through chromosome engineering (CE) is a validated and sound strategy. Attempts to incorporate more than one alien segment into cultivated wheat have been rare, particularly for tetraploid durum wheat. Here we present the agronomic and quality performance of the first successful CE-mediated multiple introgression into the latter species. By assembling into 7AL, 3BS and 1AS arms of a single genotype homoeologous segments of Thinopyrum ponticum 7el1L, Aegilops longissima 3SlS, and Triticum aestivum 1DS arms, respectively, we have stacked several valuable alien genes, comprising Lr19+Sr25+Yp (leaf and stem rust resistance and a gene increasing semolina yellowness), Pm13 (powdery mildew resistance) and Gli-D1/Glu-D3 (genes affecting gluten properties), respectively. Advanced progenies of single, double and triple recombinants were field-tested across three years in a typical durum wheat growing area of Central Italy. The results showed that not only all recombinants had normal phenotype and fertility, but also that one of the triple recombinants had the highest yield through all seasons compared with all other recombinants and control cultivars. Moreover, the multiple introgressions enhanced quality traits, including gluten characteristics and semolina yellow index. Presence of effective disease resistance genes confers additional breeding value to the novel and functional CE products, which can greatly contribute to crop security and safety.

Research into professionalization in health and safety has recently gained in interest. Graduate training is one of the factors that determines or conditions the role of the safety professional, thus intervene in the professionalization process. This article is the result of a workshop and the discussions of nine academic directors of safety education programs about quality evaluation. This article introduces the issue with a historic overview of safety education, presents a synthesis of nine selected education programs, discusses quality evaluation of health and safety education programs, propose a quality evaluation frame and finally, proposes a process for designing a quality safety education program with an associated model of the learning objectives. The outcomes are interesting for everyone who is interested in health and safety education and quality evaluation and will give insights into how safety professionals are educated.

It is unclear which noise exposure time window and noise characteristics during nighttime are most detrimental for sleep quality in real life settings. We have conducted a field study with 105 volunteers wearing a wrist actimeter to record their sleep during seven days, together with concurrent outdoor noise measurements at their bedroom window. Actimetry recorded sleep latency increased by 5.6 minutes (95% confidence interval: 1.6 to 9.6 minutes) per 10 dB(A) increase in noise exposure during the first hour after bedtime. Actimetry assessed sleep efficiency was significantly reduced by 2-3 percent per 10 dB(A) increase in measured outdoor noise (Leq, 1h) for the last three hours of sleep. For subjectively reported sleepiness, noise exposure during the last hour prior to wake up was most crucial with an increase in the sleepiness score of 0.31 units (95% CI: 0.08 to 0.54) per 10 dB(A) Leq,1h. Associations for estimated indoor noise were not more pronounced than for outdoor noise. Considering noise events in addition to equivalent sound pressure levels (Leq) only marginally improved the statistical models. Our study provides evidence that matching the nighttime noise exposure time window to the individual’s diurnal sleep-wake pattern results in a better estimate of detrimental nighttime noise effects on sleep. We found that noise exposure at the beginning and the end of the sleep is most crucial for sleep quality.

Strip-mined land (SML) disturbed by coal-mining is the non-crop land resource that can be utilized to cultivate high-yielding energy crops such as miscanthus for bioenergy applications. However, the biomass yield potential, annual availability and environmental impacts on growing energy crops in SML are less understood. In this study, we estimated the yield potential of miscanthus (Miscanthus sinensis) in SML and its environmental impacts on local streams using the Soil and Water Assessment Tool (SWAT). After calibration and validation of the SWAT model, the results demonstrated that miscanthus yield potentials were 2.6 (0.8−5.53), 10.0 (1.3−16.0) and 16.0 (1.34−26.0) Mg ha^-1 with the fertilizer application rate of 0, 100, and 200 kg-N ha^-1 respectively. Furthermore, cultivation of miscanthus in the SML has the potential to reduce sediment (~20%) and nitrate (2.5%−10.0 %) loads reaching to water streams with a marginal increase in phosphorus load. The available SML in the United States could produce about 10 to 16 dry Tg of biomass per year without negatively impacting the water quality. In conclusion, SML can provide a unique opportunity to produce biomass for bioenergy applications, while improving stream water quality in highly dense mining area (the Appalachian region) in the United States.

Mitochondrial dysfunction is relevant mechanism in cardiac aging. Here, we investigated the effects of late-life enalapril administration at non-antihypertensive dose on mitochondrial genomic stability, oxidative damage, and mitochondrial quality control (MQC) signaling in the heart of aged rats. The protein expression of selected mediators (i.e., mitochondrial antioxidant enzymes, energy metabolism, mitochondrial biogenesis, dynamics, and autophagy) was measured in old rats randomly assigned to receive enalapril (n=8) or placebo (n=8) from 24 to 27 months of age. We also assessed mitochondrial DNA (mtDNA) content, citrate synthase activity, oxidative lesions to protein and mtDNA (i.e., carbonyls and abundance of mtDNA4834 deletion), and mitochondrial transcription factor A (TFAM) binding to specific mtDNA regions. Enalapril attenuated cardiac hypertrophy and oxidative stress-derived damage (mtDNA oxidation, mtDNA4834 deletion, and protein carbonylation), while increasing mitochondrial antioxidant defenses. TFAM binding to mtDNA regions involved in replication and deletion generation was increased following enalapril administration. Increased mitochondrial mass as well as mitochondriogenesis and autophagy signaling was found in enalapril-treated rats. Late-life enalapril administration mitigates age-dependent cardiac hypertrophy and oxidative damage, while increasing mitochondrial mass and modulating MQC signaling. Further analyses are needed to conclusively establish whether enalapril may offer cardioprotection during aging.

Alternative fuels available at low cost, friendly to natural environments and meet the energy needs and demands, have witnessed a growing demand and use today. Ethanol is an attractive renewable energy source with a high content of oxygen. Ethanol can be produced through ethanolisis, however for this work direct blending of conventional diesel, waste plastic pyrolysis oil and ethanol with commercial fuel improver CI-0808 purchased from Innospec company was attempted. The primary purpose of adding a cetane improver was to improve the combustion characteristics of the blends by at least 1- 3 ignition quality points. Five mixing ratios were chosen in the following order, 50:25:25, 60: 20:20, 70: 15:15, 80: 10:10 and 90: 5:5 for Waste Plastic Pyrolysis Oil (WPPO), ethanol and conventional diesel (CD) respectively. However, for the fuel additive mixing ratio the total volume percentage was considered and the ratio put at 0.01% of the total quantity of blended fuel. In this work WPPO, diesel blends and fuel additives improvers were used as alternative fuel. This was to evaluate their performance and emission characteristics in a stationary single cylinder water cooled experimental diesel engine. The CI-0808 was added due to its potential power to reduce emissions of CO, UHC, NO_X, PM and improved engine performance. The results obtained were compared carefully to ASTM standards and discussed using graph curves figures and tabulated values. The conclusion was that ethanol and WPPO blends can be used in diesel engines as alternative fuel without modification. Used in combination with cetane improvers the emissions reduce significantly and performance improved equalling that of conventional diesel fuel.

This paper proposes a methodology for the development and its Verification and Validation(V&amp;V) of safety-rated software. The development methodology is based on the structured analysis and structured design methodology, which has been proven in the field of safety software development during long period. The suggested the development and the V&amp;V methodology additionally focuses on the quality attributes 3C+T (completeness, Correctness, Consistency and traceability), which are important criteria in IEC international standards. The software development life cycle is compiled from IEC international standardization, which are of the requirements analysis phase, design phase, implementation phase, testing phase, installation/commissioning phase, and operation &amp; maintenance phases. The activities of the development process method were defined from requirements analysis to implementation, and the activities of the verification and validation were defined to include the scope of the developer's activities and then to include the test phase, installation/commissioning phase, and operation phases additionally. In other words, testing phase performed by the developer was defined as informal testing, and testing performed by the verifier according to test criteria, test plans, and test procedures was defined as formal testing. According to proposed methodology, the requirements phase defines the sequence of Entity Relationship Diagram (ERD)-Context Diagram-Data Flow Diagram (DFD), functional decomposition process and defines operational scenario. In the design phase, module design such as task analysis and task allocation were defined. In the implementation phase, we listed the coding guidelines that must be followed for safety-related system. The test phase defined the test criteria, test plan, test procedure, and test result report activities. In the installation/commissioning and operation phases, recommendations for improving reliability, quality, and safety were proposed for deliverables such as user documentation and technical documentation.

Probiotics in cosmetics is a new and burgeoning area of research attracting attention from cosmetic manufacturers and customers looking for natural or additional alternatives in their skincare regimens. Probiotics not only promote beneficial microbiomes to improve skin health but can also modulate the visual, topographical, and mechanical attributes to improve skin quality. This study was conducted in healthy adults to determine the effect of a topical serum formulation containing the live probiotic Micrococcus luteus Q24 on several key cosmetic skin quality parameters and its beneficial impact on the modulation of the skin microbiome. Quantitative changes in various skin parameters were measured using a skin analyzer device and skin swabs were analysed using whole genome sequencing to monitor microbial diversity and levels of probiotic colonisation. Compared to the baseline, a significant reduction in the pore, spots, wrinkles, and impurities scores; and an increase of 101% in the hydration scores were observed. Additionally, 45-80% of participants showed a decrease in pores, spots, wrinkles, and impurities and 90% of participants showed an increase in hydration after 25 days of probiotic serum application. The WGS analysis of the skin swab samples showed a significant increase in the relative abundance of M. luteus Q24. The results from this study indicated that topical application of serum-containing probiotic M. luteus Q24 offers the benefit of improving skin health quality.

Background: Gluten and casein-containing foods could aggravate the symptoms of children and adolescents with autism spectrum disorder (ASD), and subsequently impact their quality of life. However, there is a mixed opinion among researchers concerning the impact of alternative diet on reducing ASD symptoms. Objective: This scoping review aimed at examining the impact of the ‘’gluten-free, casein-free’’ (GFCF) diet on health outcomes and the quality of life among autistic children and adolescents. Methods: A scoping review of the literature was performed following the Joanna Briggs Institute (JBI) guidelines. Four databases including EbscoHost, Medline, CINAHL and ProQuest were used to obtain subject-specific studies relevant to the research question and published between July 2013 and March 2024. A comprehensive search using keywords such as “autism spectrum disorder”, “gluten-free diet”, and “casein-free diet” was conducted to obtain articles related to the research focus area. Only full-text, peer-reviewed, written in English articles were selected. Data extraction and data analysis were performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses- extension to Scoping Review (PRISMA-ScR) protocol. Results: From the initial 586 studies a total of 27 articles were included in the final analysis of the review. The thematic analysis included ‘GFCF diet and improvement of the core autistic symptoms’’, “the gut-brain link’’, ‘’dietary interventions and autism’’, ‘’possible side effects due to the GCFC diet’’, and ‘’ inconclusive studies and mixed opinions’’. Majority of the studies showed positive effect of the GFCF diet on a variety of autistic symptoms including positive changes in cognitive skills, behaviour, and gastrointestinal symptoms while some showed conflicting evidence. Conclusion: The currently available evidence on the impact of ‘GFCF’’ diet on the quality of life of autistic children and adolescents may warrant potentially effective interventions for alleviating symptoms of autism spectrum disorders. However, this scoping review highlighted the need for more research to provide more reliable evidence on the health outcomes and quality of life of ASD sufferers to guide practice.

In order to cope with the limited supply of feed for global animal production, there is a pressing need to explore alternative feed resources. Orange pulp, a by-product of agriculture and industry, has shown potential to positively or neutrally impact pig productive performance when included in their diet. However, there is a lack of research on the effects of fermented navel orange pulp (FNOP) on pig growth and productive performance. This study aimed to investigate the effects of FNOP as a dry matter substitute on pig’s growth performance, carcass characteristics, meat quality, meat nutrition, and serum biochemical indicators. The experiment involved 128 finishing Tibetan pigs, divided into four feed treatment groups, with varying levels (0%, 5%, 10% and 15%) of FNOP replacing dry matter in the basal diet. The results indicated that substituting 5% to 15% FNOP had no adverse effects on pig growth performance. However, at a 15% substitution rate, there was a decrease in serum growth hormone and IGF-1 levels, along with an increase in feed-to-gain ratio. A 10% FNOP replacement notably increased the eye muscle area of pigs. Additionally, 5% and 10% FNOP substitutions reduced the drip loss of pork. The study also found that substituting 5% to 15% FNOP increased unsaturated fatty acids and umami nucleotide contents in pork, as well as raised serum total protein and uric acid (nucleotide metabolism related-product) levels. These findings suggest that moderate FNOP substitution might enhance meat quality and maintain growth and productive performance in Tibetan pigs by improving protein synthesis and nucleotide metabolism, while also reducing feed costs. The optimal substitution ratio identified was 10%.

INTRODUCTION: Breast sensibility following reconstruction surgery, though often overlooked, holds significant importance due to its widespread occurrence and profound effects on patients’ well-being and safety. Our objective is to compare the sensory outcomes between DIEP flap microsurgery reconstruction and implant-based reconstruction. Additionally, we explored the potential influence of sociodemographic and clinical factors on sensory recovery, along with assessing temperature discrimination abilities and evaluating quality of life. MATERIAL AND METHODS: We conducted an ambispective descriptive-analytical study, involving women who underwent mastectomy with reconstruction using either DIEP flap and implants at our hospital between 1990 and 2021. Data were collected from medical records, patient histories, physical examination, and validated quality of life questionnaires (BREAST-Q). RESULTS: A total of 99 women with breast reconstruction were included, 47 with DIEP flap and 52 with implants. Sensory recovery in implant-based reconstruction was found to be superior to DIEP flap reconstruction (5.03 and 5.18 respectively, p-value &lt;0.005). A direct correlation was observed between sensory improvement and thermal discrimination (Spearman coefficient 0.9, p-value &lt;0.001). Factors such as radiotherapy, delayed reconstruction with DIEP flap, and height with implants were associated with poorer sensory recovery in the breast. Women experiencing better breast sensibility reported higher satisfaction with their surgeon, medical team, and psychosocial quality of life. CONCLUSION: Women reconstructed with implants or DIEP abdominal flap exhibit suboptimal overall sensory recovery of the reconstructed breast, with slightly better outcomes observed in women reconstructed with implants.

Abstract: Peptide pools composed of short amino acid sequences have proven to be versatile tools in various research areas and clinical applications. They are powerful tools for epitope mapping, immunotherapy, and vaccine development. Their importance lies in their ability to map complex protein structures, enabling a comprehensive understanding of immune responses and facilitating the identification of potential therapeutic agents. The application of peptide pools also extends to the field of personalized medicine, offering tailored solutions for diseases such as cancer and infectious diseases. Peptide pools are complex mixtures of immunostimulatory antigens primarily intended for T-cell stimulation. They are commercially available in many different compositions and variants. However, unlike other reagents that consist of only one or a few compounds, peptide pools are highly complex products with limited stability. This makes their quality control a major challenge. Quantitative peptide analysis usually requires sophisticated methods, in most cases isotope-labeled standards and reference materials. None of these are routinely available for these products. Synthesis and purification of all labeled peptides might be required. Usually, this approach would be prohibitively laborious and expensive. Therefore, an approach is needed to provide a practical and feasible method for quality control of peptide pools. With insufficient quality control, the use of such products could lead to incorrect experimental results, which would worsen the well-known reproducibility crisis in the biomedical sciences. Here we propose the use of ultra-high performance liquid chromatography (UHPLC) with two detectors, a standard UV detector (at 214 nm) for quantitative analysis and a high-resolution mass spectrometer (HRMS) for identity confirmation. To be cost-efficient and fast, quantification and identification are performed in one chromatographic run. An optimized protocol is shown, and different peak integration methods are compared and discussed. This work was performed using a peptide pool known as CEF, which consists of 32 peptides derived from cytomegalovirus (CMV), Epstein-Barr virus (EBV) and influenza virus, ranging from 8 to 12 amino acids in length.

The fish supply chain (FSC) industry faces a significant challenge in terms of maintaining fish quality and authenticity throughout the chain. The main goal of modern FSC systems is tracking and tracing the fish product at each stage, from harvester to end customer, as well as assessing its quality and authenticity. Integrating FSC with new technologies, such as Blockchain (BC), Big Data, Artificial intelligence (AI), and Internet of Things (IoT), enhances fish product traceability, authenticity, visibility, and security. We propose a BC-based FSC framework that follows a layered architecture consisting of a SC layer, an IoT layer, and a BC layer. We integrate a new AI-based hand-held device, a Quality, Adulteration & Traceability (QAT) device, that can identify fish species and assess fish quality. We leverage the key features of BC and smart contracts, deployed over the Ethereum platform for the proposed framework integrated with QAT technology. Extensive validation of smart contracts is conducted to prove its practical feasibility.

Conventional cancer clinical trials can be time-consuming and expensive, often yielding results with limited applicability to real-world scenarios and presenting challenges for patient participation. Real-world data (RWD) studies offer a promising solution to address evidence gaps and provide essential information about the effects of cancer treatments in real-world settings. Defining RWD based on its original intent, which is the collection of data at the point of care for clinical purposes, can distinguish it from conventional clinical trial data. RWD can be generated using experimental designs that resemble those used in conventional clinical trials, but with several advantages, such as improved efficiency and a better balance between internal and external validity. RWD can support pharmacovigilance, insights into disease progression, and the development of external control groups. Prospective RWD collection enables evidence generation based on pragmatic clinical trials (PCTs) that support randomized study designs and expand clinical research to the point of care. To ensure the quality of real-world studies, it is crucial to implement auditable data abstraction methods and develop new incentives to capture clinically relevant data electronically at the point of care. The treatment landscape is constantly evolving, with the integration of front-line immune checkpoint inhibitors (ICIs), either alone or in combination with chemotherapy, affecting subsequent treatment lines. Real-world effectiveness and safety in underrepresented populations, such as the elderly, patients with poor performance status (PS), hepatitis, or human immunodeficiency virus-infected patients, are still largely unexplored. Similarly, the cost-effectiveness and sustainability of these innovative agents are important considerations in the real world.

Background:Caregiving for individuals with neurological disease involves providing physical, emotional, and social support, which can be a challenging and stressful experience. This study aims to compare the caregivers' burden, including the impact on mental and physical health, social support, and quality of life, in different neurodegenerative disorders. Methods:Fifty-five primary caregivers (F=41;mean age=53.07±12.29) of patients with Parkinson's Disease (PD=26), Multiple System Atrophy (MSA=16), and Amyotrophic Lateral Sclerosis (ALS=13), took part in the study. Standardized screening scales for the quality of life (EQ-5D/EQ-VAS and PQoL), levels of the caregiving burden (CBI and FSQ), and the assessment of the anxiety-depressive axis (HADS) were administered. Results: The mean CBI score was higher for caregivers of MSA patients (28.81±21.90) and ALS (25.15±16.23) than for caregivers of PD patients (16.08±10.34; p=0.036). Critical burden (cut-off>36) was present in the caregivers of MSA (31.3%), ALS (23.1%), and PD (19.2%) patients. Caregivers of patients with ALS had a worse perception of quality of life (EQ-5D total score) than caregivers of patients with MSA and PD (p

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.

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.

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.

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.

Laportea bulbifera (Sieb. et Zucc.) Wedd. (L. bulbifera) is a significant plant belonging to the Laportea genus. It has been traditionally used in ethnomedicine to treat various conditions such as rheumatic arthralgia, fractures, falling injuries, nephritis dropsy, limb numbness, pruritus, fatigue-induced internal imbalances, and irregular menstruation. Modern pharmacological studies have confirmed its therapeutic potential, as it exhibits anti-inflammatory, immunosuppressive, analgesic, and anti-rheumatoid arthritis properties. In order to gather in-depth information on L. bulbifera, a comprehensive literature search was conducted using databases such as Web of Science, PubMed, ProQuest, and CNKI. This review aims to provide a comprehensive understanding of L. bulbifera by covering various aspects, including ethnomedicinal uses, geographical distribution, botanical description, phytochemistry, pharmacology, and quality control. By doing so, this review intends to lay a strong foundation and propose new research avenues for the exploration and development of potential applications of L. bulbifera. Thus far, a total of 189 compounds have been isolated and identified from L. bulbifera. These compounds include flavonoids, phenolics, nitrogen compounds, steroids, terpenoids, coumarins, phenylpropanoids, fatty acids and their derivatives, and other compounds. Notably, flavonoids and fatty acids in L. bulbifera have demonstrated remarkable antioxidant and anti-inflammatory properties. Furthermore, these compounds show promising potential in activities such as analgesia, hypoglycemia, and hypolipidemia, as well as toxicity. Despite the extensive fundamental studies conducted on L. bulbifera, further research is still needed to enhance our understanding of its credible mechanism of action and improve its quality control. This necessitates more comprehensive investigations to explore the specific material basis, uncover new mechanisms of action, and refine the quality control methods related to L. bulbifera. By doing so, we could contribute to the further development and utilization of this plant.

Cloud Manufacturing (CMfg) has attracted lots of attention from scholars and practitioners. The purpose of quality of service (QoS)-aware manufacturing cloud service composition (MCSC), as one of the key issues in CMfg, is to combine different available manufacturing cloud services(MCSs) to generate an optimized MCSC that can meet diverse requirements of customers. However, many available MCS, deployed in the CMfg platform, have same function but different QoS attributes. It is a great challenge to achieve optimal MCSC with high QoS. In order to obtain better optimization results efficiently for the QoS-MCSC problems, a whale optimization algorithm(WOA) with adaptive weight, Lévy flight, and adaptive crossover strategies (ASWOA) is proposed. In the proposed ASWOA, the adaptive crossover inspired by the genetic algorithm is developed to balance the exploration and exploitation. The Lévy flight is designed to expand the search space of WOA and accelerate the convergence of WOA with adaptive crossover. The adaptive weight is developed to extend the search scale of the exploitation. Simulation and comparison experiments are conducted on different scale QoS-MCSC problems. The experimental results demonstrate that the proposed ASWOA outperforms other compared cutting-edge algorithms.

Alcohol use disorder (AUD) is a chronic and relapsing biopsychosocial condition that leads to a wide range of medical, psychological, social, economic, and personal issues. The study investigated the predictors of quality of life (QoL) among male patients seeking treatment for AUD based on attention, cognitive instability, motor impulsiveness, perseverance, and self-control dimensions of trait impulsivity. The study also investigated the potential mediating effect of anxiety and alcohol use severity in this relationship. After an initial assessment, participants underwent comprehensive evaluations, including sociodemographic data, clinical history, and QoL domains. Evaluations also covered AUD severity, impulsivity dimensions, cognitive functions, craving intensity, depression, anxiety and self-efficacy. Multiple linear regressions were employed to identify associations between independent variables and QoL. Attention dimension of impulsivity and anxiety symptoms significantly predicted physical health QoL. Self-control dimension and severity of alcohol use disorder predicted psychological QoL. Indirect effect of attention dimension on physical health was significant [effect =-1.082,95% CI (-2.008, -0.3598)].The significance of impulsivity in influencing QoL for individuals with AUD has profound clinical implications. These findings underscore the importance of addressing anxiety and impulsivity in managing AUD, given their considerable impact, particularly on QoL, ultimately shaping treatment outcomes.

Besides the increase in global energy demand, access to clean energy, reduction in greenhouse gas emissions caused by conventional power generation sources, energy security, and availability of electricity in remote villages in emerging nations are some of the factors that foster the use of renewable energy sources (RESs) in generating electricity. One of the aims of initiating microgrids (MGs) is to maximize the benefits of RES and alleviate the associated grid integration issues. Microgrids are made up of RES connected to electrical loads within clearly delineated electrical limits that operate as individual controllable units on the electrical network. It can operate in-dependently as well as in connection with the grid. The paper presents an overview of microgrids and investigates the system's performance when connected to and disconnected from the grid. Furthermore, in both modes of operation, the functioning and behavior of system components such as the bidirectional DC-DC converter and energy storage system (ESS) were evaluated. The architecture of the proposed microgrid consists of a small hydropower plant, a wind farm, and a battery energy storage system (BESS). The microgrid under investigation is modeled and simu-lated using MATLAB and Simulink.

(1) Background: Human-generated greenhouse gas (GHG) emissions are the largest contributor to climate change worldwide. Climate change negatively impacts human and planetary health threatening the existence of life on earth. The healthcare industry is responsible for approximately 8.5% of carbon emissions in the United States. Measuring baseline GHG emissions is the first step in emissions reduction. However, very few models of measurement exist for health care organizations. This project aimed to develop and implement a program to measure and track GHG emissions at a Midwestern Academic Medical Center (MAMC) and to educate staff to manage the process. (2) Methods: A Plan, Do, Study, Act (PDSA) cycle and Quality Improvement methodology was used to develop, implement, and assess a standardized GHG emission inventory process to measure Scope 1 and Scope 2 baseline emissions, and provide virtual training and education to the accountable staff. A pre- and post-survey design was used to measure the knowledge and readiness of the staff after the implementation of the GHG inventory training. (3) Results: The GHG inventory process was validated through an external verification process and the measurement of Scope 1 and Scope 2 baseline GHG emissions was completed and verified for accuracy through a data comparison review. The pre-post-training survey showed an increase in the knowledge and readiness of staff in maintaining a GHG inventory. (4) Conclusions: This work shows the feasibility of obtaining baseline GHG emissions data at large medical centers. It represents the initial phase of the overarching goal to develop site-wide and system-wide carbon reduction strategies and a climate action plan within this health system.

The high demand for SARS-CoV-2 tests but limited supply to South African laboratories early in the COVID19 pandemic, resulted in a heterogenous diagnostic footprint of open and closed molecular testing platforms. Novel approaches were required to monitor test quality especially during the introduction of newly circulating variants. The National Health Laboratory Service centrally collected cycle threshold (Ct) values from 1,497,669 test results reported from six commonly used PCR assays in 36 months, and visually monitored changes in their median Ct within a 28-day centered moving average for each assays’ gene targets. This continuous quality monitoring rapidly identified delayed hybridization of RdRp in the Allplex™ SARS-CoV-2 assay due to the Delta (B.1.617.2) variant; S-gene target failure in the TaqPath™ COVID-19 assay due to B.1.1.7 (Alpha) and the B.1.1.529 (Omicron); and recently E-gene delayed hybridization in the Xpert® Xpress SARS-CoV-2 due to XBB.1.5. This near “real-time” monitoring helped inform the need for sequencing and the importance of multiplex molecular nucleic acid amplification technology designs used in diagnostics for patient care. This continuous quality monitoring approach at the granularity of Ct values should be included in ongoing surveillance and with application to other disease use cases that rely on molecular diagnostics.

Plums are primarily marketed for fresh consumption, canning, freezing, jam and jelly. Unfortunately, plum consumption has remained steady or declined. Consumers complain about a lack of flavor quality but are willing to pay for higher quality. Thus, lack of flavor and cold storage disorders are the main barriers to consumption. Plum cultivars are susceptible to gel breakdown, flesh browning and ‘off flavors’. Consumer acceptance and postharvest life are highly dependent on genotype, quality attributes, harvest date and proper postharvest handling. A consumer quality index (CQI) based on soluble solids concentration (SSC) and minimum firmness is proposed to maximize flavor and postharvest life. In most cases, late harvest increases quality attributes. Our work and industry experience demonstrated that using critical bruising thresholds (CBT) based on minimum firmness measured at harvest acts as a reliable predictor of how late to harvest safely for maximum visual and sensory quality. Plums are well adapted to late harvest because of their low susceptibility to bruising damage, but proper postharvest temperature management and marketing within the potential market life are necessary to maintain flavor and avoid the onset of storage disorders. Thus, to maximize flavor and postharvest life, a CQI based on SSC and minimum firmness measured at consumption is proposed. This article provides guidance on using this CQI, combined with proper postharvest handling techniques such as correct harvest date determination and temperature management, to maintain quality and increase consumption.

The nursing home (NH) population becomes increasingly frail, suffering several chronic ill-nesses, high symptom severity, and short remaining lifespan after admission; all this requires skilled, well-organized professional care. Little is known about how NH managers influence the caring and learning environment (CLE) to ensure competencies in meeting NH patients’ needs. The aim of this study is to explore how NH managers influence the CLE to provide basic nursing education for students and apprentices, in order to improve it. This study applies a qualitative design, using multiple methods and focusing on NHs as a context involving complex adaptive systems and on basic nursing as a complex issue. NH managers express a constant struggle to keep workloads manageable, and NHs come across as exhausted organizations with little surplus. Both managers and staff look for ways to execute the work with as little effort as pos-sible and mainly stick to well-established routines. Not participating directly in either daily caring or placement learning, NH managers influence the CLE indirectly through taming and coping strategies, largely using taming strategies that lead to serious unintended outcomes. Coping strategies involve leading collaborative processes in holding environments that are feasible with their workload and roles as managers.

The TeNDER project aims to improve the Quality of Life (QoL) of chronic patients through an integrated care ecosystem. This study evaluates the Health Recommender System (HRS) developed for the project, which offers personalized recommendations based on data collected from a set of monitoring devices. The list of notifications covered different areas of daily-life such as physical activity, nutrition, and sleep. We conducted this case of study to evaluate the effectiveness and usability of the HRS in providing accurate and relevant recommendations to users. Evaluation process consisted on survey administration for QoL assessment, and the satisfaction and usability of the HRS. The four-week pilot study involved several patients and caregivers, and demonstrated that the HRS was perceived as user-friendly, consistent, and helpful, with a positive impact on patients’ QoL. However, the study highlights the need for improvement in terms of personalization of recommendations.

This study was to determine the effects of different irrigation, fertigation and mulching applications on the yield and quality parameters of strawberries. The study was conducted at the Bursa Uludağ University Yenişehir Ibrahim Orhan Vocational School Agricultural Research Field in 2019-2020. In the research, four different irrigation topics, three different fertigation and three different mulching topics were selected The maximum and minimum yield values of the study years were calculated as 5.05-18.70 t ha-1 and 1.20-8.7 t ha-1, respectively, from I100F100M1 and I25F50M0 treatments. As a result, a three-factor study determined that irrigation, fertigation, and mulching had a significant effect on the yield and quality characteristics of strawberries. However, when the reductions in yield and quality losses are evaluated together, despite the reductions in irrigation water and fertigation levels, I75 and F75 topics can be recommended. Also, in mulching treatments, black mulch material (M1) should be chosen over clear mulch material (M1) and no mulch (M0).

(1) Background: Rational use of medicines (RUM) and their assessment is important to ensure optimal use of resources and patient care in hospitals. These assessments are essential to identifying practice gaps for quality improvement. (2) Methods: Assessment of adherence to WHO/ International Network for Rational Use of Drugs core prescribing indicators among out-patients in 2021 was conducted at the University Hospital of the Kwame Nkrumah University of Science and Technology in the Ashanti region of Ghana. We reviewed electronic medical records (EMR) of 110,280 patient encounters in the year which resulted in 336,087 medicines prescribed. (3) Results: The average number of medicines prescribed per encounter was 3 with generics being prescribed in 76% of prescriptions. Injections were prescribed in 7% of encounters while 90% of medicines were from Ghana’s Essential Medicines List 2017. (4) Conclusions: With the exception of patient encounters with injections, all prescribing indicators assessed in this study did not meet WHO optimum levels providing targets for quality improvement in RUM. Implementing prescribing guides and policies, regular audits and feedback as well as continuous professional development training may help to improve prescribing practices in the hospital.

While L-PBF offers advantages in terms of geometrical freedom or lightweight construction, its use is often limited by economic constraints or currently achievable part costs. With an anticipated increase of L-PBF machine productivity during the next years, an increase of the share of material costs and the share of non-productive time for powder layer application process is to be expected. This results in a demand for less expensive powder materials and advanced processing strategies for the short-and medium-term advancement of L-PBF. As one possible approach, the processing of gas- and water atomized stainless steel (316L) powders with different morphology and particle size distribution as well as their impact on L-PBF productivity is investigated. The actual powder applicability in L-PBF systems and the L-PBF processability determines the minimum necessary powder quality. The main focus of the presented work is put on the interaction between powder quality, powder layer properties, part quality and cost-effectiveness of the L-PBF process. To this end, the influence of the gas and water-atomized powder properties (particle size and morphology) during the powder layer application process at highest possible powder recoater speeds and the resulting powder bed properties (powder layer density, powder bed density, powder demixing) and part properties (part density and tensile strength) is investigated.

Background: Low-level physical activity (PA) among Chronic Low Back Pain (cLBP) is associated with various biopsychosocial factors. This research aimed to study the predictors of PA behavior among cLBP patients. Methods: In the present study 300 eligible patients with cLBP who referred to comprehensive health service centers in the Shahid Beheshti University of Medical Sciences (SBUMS) in Tehran, Iran were random selected.To diagnose the predictors of PA behavior, all the Theory of Reasoned Action (TRA) constructs were examined as risk factors to see if they influence on the probability of PA behavior occurrence and were interpreted through odds ratio (OR). SPSS version 19 was used to analyze the data. Results: Totally 280 cLBP patients with mean age of 57.07 ±13.09 years old participated in the study. This study showed that motivation to comply significant predictor the cLBP patients for subjective norm OR (%95CI): 2.095(0.116-2.792), p-value<0.001), intention was significant predictor for perform the PA behavior OR (%95CI): 1.431(0.138-1.538), p-value <0.001), behavior beliefs could predictor for attitude OR (%95CI): 1.276(0.106-1.355), p-value= 0.002). attitude, normative beliefs, subjective norm ,and evaluation outcome behavior could predictors the cLBP patients for intention to perform the PA behavior OR (%95CI): 1.188(0.032-1.312), p-value<0.001)., OR (%95CI): 1.158(0.076-2.208), p-value=0.003) ., OR (%95CI): 1.104(0.076-1.128), p-value<0.001) ., OR (%95CI): 0.814(0.301-1.440), p-value=0.007). Conclusions: This study showed that the cLBP patients who were normative beliefs and evaluation regarding PA behavior could effect on the intention to engage in greater PA than those via other constructs (attitude and subjective norm). This study showed that the cLBP patients who were normative beliefs and evaluation regarding PA behavior could effect on the intention to engage in greater PA than those via other constructs (attitude and subjective norm). This study showed that the cLBP patients who were normative beliefs and evaluation regarding PA behavior could effect on the intention to engage in greater PA than those via other constructs (attitude and subjective norm).

One of the rapidly developing research areas is the creation of systems. which are commonly referred to as cyberphysical complexes. In such systems, devices and complexes interact with a completely different physical nature. The role of a person in such systems usually consists in the formation of final tasks for “artificial intelligence” and executive mechanisms. The functioning of actuators is controlled by accurate information systems.

There are numerous hazards found on the farms. Most of them are ignored, which might cause the farmer to pay later in terms of his ill health, potential injuries or death. The current article discusses some of the common issues such as dust and air quality concerns; environmental (weather) stressors and psychological stressors; noise and hearing protection; and tractor safety and seatbelt use. And finally, the recommendations to overcome the hazards are discussed.

Chronic myeloid leukemia (CML) is a myeloproliferative neoplasm constituting approximately 15% of newly diagnosed leukemia in adult patients. Development of tyrosine kinase inhibitors (TKIs) have dramatically improved outcomes in patients with chronic CML in chronic phase. However, adverse drug events (ADEs) associated with TKI therapy have influenced drug adherence, resulting in adverse clinical outcomes and a decline in the quality of life (QoL). In this study, we carried out a unique questionnaire survey to evaluate ADEs, which comprised 14 adverse events. We compared drug adherence rates between patients using imatinib and those who switched from imatinib to nilotinib, a second-generation TKI. Following the switch, the total number of ADEs decreased considerably in most cases. Simultaneously, better QoL was observed in the nilotinib group than in the imatinib group. Drug adherence was measured using Morisky’s 9-item Medication Adherence Scale (MMAS). MMAS increased significantly after switching to nilotinib in all cases. Drug adherence is a critical factor for achieving molecular response in patients with CML. In fact, our results showed a strong inverse correlation between clinical outcome [international scale (IS)] and adherence (MMAS), with a stronger tendency in the nilotinib group than in the imatinib group. In conclusion, low occurrence of ADEs induced a high level of QoL and a good clinical response with second-generation TKI nilotinib treatment.

Water supply is a mandatory service for Tanzanians from respective legal public water utilities, and their sustainability reflects implementations of best management strategies at a local level. The objective of this study was to assess current approaches used in water quality and quantity management in Tanzania. This was achieved through secondary water data tends, on-site water quality assessments, visits of respective water supply and sanitation authorities, and assessment of their performances. It was observed that water supplied in rural-based authorities was quite different from that supplied in an urban setting as far as quality and quantity is concerned, urban-based supplies being of assistance to users over rural ones. A new strategy on water management is presented for sustainable water supply in Tanzania; it is based on controlling groundwater abstractions and preference of surface water in public water supplies. Rural water supply management must learn several practices realized at urban supplies for the betterment of respective majority water users.

A study of the water quality of the Adolfo López Mateos Reservoir (ALMD) was developed through different indicators from a spatial and seasonal perspective. Variables related to the general characteristics of water quality, trophic level and ecological risk were assessed through the water Quality Index (WQI_NSF-BROWN), Trophic State Index (TSI_CARLSON) and the Ecological Risk Index (RI_HAKANSON). Using data from physical, chemical and biological parameters obtained from four sampling points in the ALMD, the water quality was assessed in each model used. The results indicated that the reservoir presents a water quality classified as “medium” (WQI_NSF-BROWN = 70), where significant variations in the concentrations of some parameters are observed. The reservoir showed a general trophic state classified as “Mesotrophic” (TSI_{GENERAL-AVERAGE} = 43.04). The ecological risk analysis achieved the best classification of the methodology, discarding contamination by heavy metals in surface waters. Through this type of applied methodologies will help as decision making tools in the dam, as well as for application in other dams in the region.

Estimating ground surface PM2.5 with fine spatiotemporal resolution is a critical technique for exposure assessments in epidemiological studies of its health risks. Previous studies have utilized monitoring, satellite remote sensing or air quality modeling data to evaluate the spatiotemporal variations of PM2.5 concentrations, but such studies rarely combined these data simultaneously. We develop a three-stage model to fuse PM2.5 monitoring data, satellite-derived aerosol optical depth (AOD) and community multi-scale air quality (CMAQ) simulations together and apply it to estimate daily PM2.5 at a spatial resolution of 0.1˚ over China. Performance of the three-stage model is evaluated using a cross-validation (CV) method step by step. CV results show that the finally fused estimator of PM2.5 is in good agreement with the observational data (RMSE = 23.00 μg/m^3 and R2 = 0.72) and outperforms either AOD-retrieved PM2.5 (R2 = 0.62) or CMAQ simulations (R2 = 0.51). According to step-specific CVs, in data fusion, AOD-retrieved PM2.5 plays a key role to reduce mean bias, whereas CMAQ provides all-spacetime-covered predictions, which avoids sampling bias caused by non-random incompleteness in satellite-derived AOD. Our fused products are more capable than either CMAQ simulations or AOD-based estimates in characterizing the polluting procedure during haze episodes and thus can support both chronic and acute exposure assessments of ambient PM2.5. Based on the products, averaged concentration of annual exposure to PM2.5 was 55.75 μg/m3, while averaged count of polluted days (PM2.5 > 75 μg/m3) was 81, across China during 2014. Fused estimates will be publicly available for future health-related studies.

Acute myeloid leukemias (AMLs) are heterogeneous hematologic cancers that occur prevalently in older patients as the result of a complex pathobiology. The clinical outcomes of older patients with AML, often unsuitable for intensive chemotherapy and allogeneic stem cell transplantation, are generally disappointing. However, recent advances in understanding molecular pathogenesis and other biological mechanisms recognized in AML development and progression have changed the treatment approach, especially for this particularly vulnerable category of patients. Indeed, non-intensive biologically tailored approaches, such as combining venetoclax with hypomethylating agents, have changed the therapeutic paradigm in this field. Moreover, other promising compounds and treatment strategies are currently under advanced clinical development. This article delves into the latest biological understanding and therapeutic advances in the clinical management of older AML patients into new conceptual frameworks that progressively transform the clinical practice in this challenging setting.

As digitalization expands across all sectors, the economic toll of software defects on the U.S. economy reaches up to $2.41 trillion annually. High-profile incidents like the Boeing 787-Max 8 crash have shown the devastating potential of these defects, highlighting the critical importance of software testing within quality assurance frameworks. However, due to its complexity and resource intensity, the exhaustive nature of comprehensive testing often surpasses budget constraints. This research utilizes a machine learning (ML) model to enhance software testing decisions by pinpointing areas most susceptible to defects and optimizing scarce resource allocation. Previous studies have shown promising results using cost-sensitive training to refine ML models, improving predictive accuracy by reducing false negatives through addressing class imbalances in defect prediction datasets. This approach facilitates more targeted and effective testing efforts. Nevertheless, the generalizability of these models across different projects (cross-project) and programming languages (cross-language) remained untested. This study validates the model's applicability across diverse development environments by integrating various datasets from distinct projects into a unified, using a more interpretable ML approach. The results demonstrate that ML can support software testing decisions, enabling teams to identify up to seven times more defective modules with the same testing effort as a benchmark.

In the dynamic interplay between people and their physical environments, the Global South stands as a mosaic undergoing a multitude of transformative influences in architecture and urbanism where examining social sustainability becomes imperative. While prevailing attention remains on environmental and economic sustainability, this study addresses a persistent gap in the urban literature by focusing on the dynamic and manifold nature of social sustainability. Positioning itself within the context of sustainable development, the study links the pursuit of social aspects of sustainability with selected unique urban contexts from the Global South. Five cases that include Alexandria (Egypt), Tripoli (Libya), Basra (Iraq), Lilongwe (Malawi), and Accra (Ghana) are discussed through multi-layered investigations that involve attitude surveys, interviews, focus groups, participatory systematic observations, and behavioral mapping, engaging directly with inhabitants and stakeholders. Uncovering people-place narratives in the identified contexts, the cases are developed into five knowledge typologies that serve as practical tools for planning and design decision-making, policy formulation, and academic discourse. Discussions are conceived to demonstrate the transformative role people-place narratives play in fostering a more sustainable and equitable urban future. Conclusions are drawn to offer practical insights for stakeholders involved in various capacities in shaping the urban landscape of the Global South.

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.

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: Carers (or care partners) of adults in LTC contribute substantially to the health and well-being of their loved ones by providing physical care, emotional support, and companionship. Despite their critical role, little is known about how caregivers have been impacted by the pandemic. The purpose of this study was to explore the lived experiences of caregivers of people living in long-term care (LTC) homes during the initial phases of the COVID-19 pandemic and potential supports and resources needed to improve caregivers’ quality of life.Design: An interpretive descriptive approach that incorporated photovoice method was used. Methods: Using purposive sampling strategy, six family carers in Ontario, Canada were recruited between September and December 2021. Over a four-week period, caregivers took pictures depicting their experience of the pandemic that were shared in a virtual focus group. Visual and text data were analyzed using thematic analysis with an inductive approach.Findings: Caregivers expressed feelings of frustration, confusion, and joy. Emerging themes included: (i) feeling like a “criminal” amidst visitor restrictions and rules; (ii) experiencing uncertainty and disappointment in the quality of care of long-term care homes; (iii) going through burnout; and (iv) focusing on small joys and cherished memories.Conclusions: The combination of visual and textual methods provided unique insight into the mental distress, isolation, and intense emotional burdens experienced by caregivers during the pandemic. Impact: Our findings underscore the need for LTC organizations to work in unison with caregivers to optimize the care of residents and support mental health of caregivers.

Abstract: The internationally accepted goals of eliminating climate gas emissions implies substantial investments in renewable energy (RE) facilities. This will inevitably lead to major impacts on landscapes. Landscape concerns linked to RE facilities are already leading to controversies in many local communities. In this article, we focus on the question of landscape democracy related to the establishment of RE facilities. Based on recommendations from the European Landscape Convention, an analytical framework is presented identifying three main dimensions of landscape democracy, followed by an overview of arrangements, procedures and methods that are or may be used to encourage democracy. The procedures and methods are analysed based on examples from Denmark and Norway. This is followed by an analysis of decision levels with a special focus on the principle of subsidiarity. Finally, recommendations are presented to strengthen landscape democracy in relation to the installation of RE-facilities.

Air pollution is a leading cause of death worldwide, and has a profound impact on the planet's climate and ecosystems. A substantial portion of air pollution is attributable to Ocean Going Vessels (OGVs). In light of this, international regulations have been put in place to mitigate air pollutant emissions from OGVs. While studies have indicated that these regulations can create significant health, environmental, and economic benefits, there remains a research gap regarding their specific impact on enhancing air quality. The aim of this study is to investigate how the implemented regulations have affected air quality in the Southern North Sea. The study found that the international regulations on ship emissions have successfully led to a decline in SO2 emissions from OGVs in the Southern North Sea, which resulted in a reduction of ambient SO2 concentrations inland, leading to positive effects on public health and the environment. However, it was projected that their proportion is tend to increase in the following years. Moreover, the study revealed that Exhaust Gas Cleaning Systems (EGCS) present significant concerns. They were significantly more frequently found to be non-compliant, and more alarmingly, they emit notably higher average levels of SO2. It also turned out that international regulations in the southern North Sea have less effect on the reduction of NOx emissions from OGVs than expected. The NOx emissions from OGVs will even account for an alarming 40% of the total domestic NOx emissions for the Belgian Region by 2030.

Knowing, with reasonable accuracy, the dry matter (DM) content of Hass avocado fruit will help determine when the fruit must be harvested. The reliability of predictive models based on near infrared spectra for DM quantification depends on the ability of the spectra to be representative of the DM gradient within a whole fruit. The aim of this work was to develop a methodology to determine the optimum number of spectra to develop a robust model for DM content quantification. Three spectra were recorded for each zone of the intact fruit: peduncle, equator, and base. Each scanning point was sampled, and the DM content was determined using oven drying. Two-way ANOVA confirmed the DM gradient within the whole fruit. This gradient was observed within spectra using the RMS (root mean square) criterion and PCA. The PLS models showed that at least one spectrum per zone could be enough to construct an efficient and robust model for dry matter quantification.

Traditional dry fermented meat products are obtained artisanally in many countries, where they represent a gastronomic heritage well distinguished from industrial counterparts. This food category is most often obtained from red meat, a food commodity that is under attack because of evidences of increased risk of cancer and degenerative diseases with high consumption. However, traditional fermented meat products are intended for moderate consumption and gastronomic experience and, as such, their production must be continued also to safeguard culture and economy of the geographical areas of origin. In this review, the main risks attributed to these products are considered and how these risks are minimized by following precise production norms, respectful of the ancient manufacturing processes is described. Moreover, results obtained in studies reporting use of autochthonous microbial cultures of lactic acid bacteria (LAB), coagulase negative staphylococci (CNS), Debaryomyces hansenii and Penicillium nalgiovense to improve safety and quality of traditional fermented meats are summarized. The role of these products as a source of microorganisms that can be beneficial to the host are also considered. From the results of the studies reviewed here it appears that the development of autochthonous cultures for these foods ensure safety and stabilize sensory characteristics with possibility to be extended to the large variety of traditional productions.

Artificial Intelligence (AI) play an important role in many fields, including medical education, practice, and research. Many medical educators started using ChatGPT at the end of 2022 for many purposes. The aim of this article was to explore the potential uses, benefits and risks of using ChatGPT in integrated pharmacotherapy of infectious disease module education. This study was an experimental study with content analysis of the potential applications of the ChatGPT model for integrated pharmacotherapy of infectious diseases module education was performed. The findings of this study shows that there are many potential uses, benefits and risks associated with the use ChatGPT. In conclusion, medical and health sciences educators can use ChatGPT as a guide in many aspects related to the integrated pharmacotherapy of infectious disease curriculum development, syllabus design, lecture notes preparation and exam preparation with caution.

The World Health Organization estimates that every year air pollution kills seven million people worldwide. As it is expected that climate change will affect future air quality patterns, the full understanding of the links between air pollution and climate change, and how they affect human health, are challenges of future research. In this scope, a methodology to assess the air quality impacts on health was developed. The WRF-CAMx modelling framework was applied for the medium-term future climate (considering the SSP24.5 scenario) and for the recent past (considered as baseline). Following the WHO recommendations, mortality health indicators were used to estimate health impacts of long-term exposures. For that, the Aveiro Region, in Portugal, was considered as a case study. Future climate results indicate the occurrence of higher temperatures, and lower total precipitation. Despite that, improvements in the main pollutants’ concentrations, and consequently in the reduction of the related premature deaths are foreseen, mainly due to the reduction of pollutants emissions imposed by the European legislation for the upcoming years. The applied approach constitutes an added value in this research field, being crucial to anticipate the effects of climate change on air quality and evaluate their impacts on human health.

Among the components of a healthy life, sexuality is an essential part, contributing not only to psychophysical well-being, but also to the social well-being of women and, consequently to their quality of life. A poorly investigated standpoint is the acceptability of a contraceptive method, not only in terms of tolerability and metabolic neutrality, but also concerning the impact that it can have on sexual life. In this context, we will provide an overview of the different methods of contraception and their effects on female sexuality from the biological changes, to organic, social, and psychological factors, which can all shape sexuality.A MEDLINE/PUBMED review of the literature between 2010 and 2021 was conducted using the following key words/phrases: hormonal contraception, contraceptives, female sexual function, libido, sexual arousal and desire, and sexual pain. Recent studies have supported the effects of contraceptives on women’s sexuality, describing a variety of positive and negative events on several domains of the sexual function (desire, arous-al, orgasm, pain, enjoyment). However, satisfaction with sexual activity depends on factors that extend beyond sexual functioning alone. A more holistic approach is needed to better under-stand the multitude of factors linked to women’s sexuality and contraception. Contraceptive counselling must necessarily consider these important elements since they are closely related to good compliance.

The demand for efficient processes through a comprehensive understanding and optimization of welding conditions continues to grow in the manufacturing industry. This study involves heat-resistant 2.25 Cr-1 Mo V-groove steel welding using the square-waveform alternating cur-rent. Experiments were conducted to build the relationship between input variables—such as current, frequency, electrode negativity ratio, and welding speed—and process performance, such as penetration, bay area, deposition rate, melting efficiency, percentage dilution, flux–wire ratio, and heat input. The process was analyzed in light of the defect-free high-deposition weld groove weld, the sensitivity to process parameters, and the optimization and development of the process map. The study proposes an innovative approach to reducing the cost and time of optimizing the one-pass-each-layer V-groove welding process using bead-on-plate welds. Square waveform welding creates a metallurgical notch in the form of a bay at the fusion boundary that can be minimized by selecting appropriate welding conditions. The square waveform submerged arc welding is more sensitive towards changes in current and welding speed than the frequency and electrode negativity ratio; however, the electrode negativity ratio and frequency are minor but helpful parameters to achieve optimal results. The proximity of the planned and experimental results to within 3% confirms the validity of the proposed approach. The investigation shows that 90% of the maximum deposition rate is possible for one-pass-each-layer V-groove welds within heat input and weld width constraints.

This article proposes a measurement solution designed to monitor instantaneous frequency in power systems. It uses a data acquisition module and a GPS receiver for time stamping. A program in Python takes care of receiving the data, calculating the frequency, and finally transferring the measurement results to a database. The frequency is calculated with two different methods, which are compared in the article. The stored data is visualized using the Grafana platform, thus demonstrating its potential for comparing scientific data. The system as a whole constitutes an efficient low cost solution as a data acquisition system.

Software is playing the most important role in recent vehicle innovation, and consequently the amount of software has been rapidly growing last decades. Safety-critical nature of ships, one sort of vehicles, makes Software Quality Assurance (SQA) has gotten to be a fundamental prerequisite. Just-In-Time Software Defect Prediction (JIT-SDP) aims to conduct software defect prediction (SDP) on commit-level code changes to achieve effective SQA resource allocation. The first case study of SDP in maritime domain reported feasible prediction performance. However, we still consider that the prediction model has still rooms for improvement since the parameters of the model are not optimized yet. Harmony Search (HS) is a widely used music-inspired meta-heuristic optimization algorithm. In this article, we demonstrated that JIT-SDP can produce the better performance of prediction by applying HS-based parameter optimization with balanced fitness value. Using two real-world datasets from the maritime software project, we obtained an optimized model that meets the performance criterion beyond baseline of previous case study throughout various defect to non-defect class imbalance ratio of datasets. Experiments with open source software also showed better recall for all datasets despite we considered balance as performance index. HS-based parameter optimized JIT-SDP can be applied to the maritime domain software with high class imbalance ratio. Finally, we expect that our research can be extended to improve performance of JIT-SDP not only in maritime domain software but also in open source software.

Urination on carpet and subflooring can develop into persistent and challenging to mitigate odor. Very little or no information is published on how these VOCs change over time when urine is deposited on the carpet covering a plywood-type subflooring. This research has investigated the VOCs emitted from carpet+subflooring (control), carpet+subflooring sprayed with water (control with moisture), and cat urine-contaminated carpet+subflooring (treatment) over time (day 0 and 15). In addition, the effect of popular cleaning products on VOCs emitted and evaluated their efficacy in eliminating those indoor odors over time (day 0 and 15). Carpet-subflooring with all treatments were also contaminated with Micrococcus luteus, nonmotile obligate aerobe commonly found in household dust, to observe the impact of the aerobe on carpet-subflooring VOCs emission. VOCs emitted from carpet+subflooring receiving different treatments were collected from headspace using solid-phase microextraction (SPME). The VOCs were analyzed using a multidimensional gas chromatography-mass spectrometer attached to an olfactometry (GC-MS-O). Many common VOCs were released from the carpet on day one and day fifteen, specifically from urine contamination. Cleaning products were effective in masking several potent odors of cat urine contaminated carpet VOCs on day one but unable to remove the odor appeared on day 15 in most cases.

The complexity of software is increasing day by day due to the increase in the size of the projects being developed. For better planning and management of large software projects, estimation of software quality is important. During the development processes, complexity metrics are used for the indication of the attributes/characteristics of the quality software. There are many studies about the effect of the complexity of the software on the cost and quality. In this study, we discussed the effects of software complexity on the quality attributes of the software for open source and closed source software. Though, the quality metrics for open and closed source software are not distinct from each other. In this paper, we comparatively analyzed the impact of complexity metrics on open source and private software. We also presented various models for the management of the project complexity such as William’s Model, Stacey’s Agreement and Certainty matrix, Kahane’s Approach and UCP Model. Quality metrics here refer to the standards for the measurement of the quality of software which contains certain attributes or characteristics of the software that are related to the quality of the software. Certain quality attributes addressed in this study are Usability, Reliability, Security, Portability, Maintainability, Efficiency, Cost, Standards and Availability, etc. Both Open source and Closed source software are evaluated on the basis of these quality attributes. This study also recommended future approaches to manage the quality of project Open source and Closed source software and specify which one of them is mostly used in the industry.

The slate aggregate has long been perceived as a substandard, low quality waste material with its physical and chemical properties not being competitive with those of the primary aggregates. It is assumed that the slate aggregate particles are not strong, that is not durable and will not compact. This research aims to address those claims and review the available literature on the performance of the slate aggregate. The review inaugurates by analysing the physical, chemical and mechanical properties of slate, before expanding into a literature review of laboratory testing’s on the effect of moisture content on density, compaction and layer thickness of slate aggregate.The paper reviews case studies of construction projects in North Wales, where the slate aggregate has been used for general fill and road building for many years. Some of the case studies include the A55 coastal road and duelling of the A5 in Anglesey (WRAP, 2004), where slate aggregate was successfully used as sub-base. The paper also investigates why many civil engineers are reluctant to use the slate aggregate and regard the material as sub-standard, flaky aggregate. The research paper reviews the potential usages and various products the slate aggregate is suitable for and satisfies the requested standards. The final topic reviewed is the cost of transporting slate aggregate compared with the cost of transport for primary aggregate and the introduction of the Primary Aggregates Tax (Parliament of the United Kingdom, 2011). The last topic includes a critical analyses of the claims that the slate aggregate a commercially viable construction material despite its remote location (Woodward et al, 2004). The transportation cost and the supply chain complexities must be evaluated prior to considering the long-term sustainability of the product (Radanliev et al^1-6, 2014, 2015, 2016).

We examine how observations can be used to evaluate an air quality analysis by verifying against passive observations (i.e. cross-validation) that are not used to create the analysis and we compare these verifications to those made against the same set of (active) observations that were used to generate the analysis. The results show that both active and passive observations can be used to evaluate of first moment metrics (e.g. bias) but only passive observations are useful to evaluate second moment metrics such as variance of observed-minus-analysis and correlation between observations and analysis. We derive a set of diagnostics based on passive observation–minus-analysis residuals and we show that the true analysis error variance can be estimated, without relying on any statistical optimality assumption. This diagnostic is used to obtain near optimal analyses that are then used to evaluate the analysis error using several different methods. We compare the estimates according to the method of Hollingsworth Lonnberg, Desroziers, a diagnostic we introduce, and the perceived analysis error computed from the analysis scheme, to conclude that as long as the analysis is optimal, all estimates agrees within a certain error margin. The analysis error variance at passive observation sites is also obtained.

A simple approach to enable water-management agencies employing free data to achieve the goal of using a single set of predictive equations for water-quality retrievals with satisfactory accuracy is proposed. Multiple regression-derived equations based on surface reflectance, band ratios, and environmental factors as predictor variables for concentrations of Total Suspended Solids (TSS), Total Nitrogen (TN), and Total Phosphorus (TP) were derived using a hybrid forward-selection method that considers Variance Inflation Factor (VIF) in the forward-selection process. Landsat TM, ETM+, and OLI/TIRS images were jointly utilized with environmental factors, such as wind speed and water surface temperature, to derive the single set of equations. The coefficients of determination of the best-fitting resultant equations varied from 0.62 to 0.79. Among all chosen predictor variables, ratio of reflectance of visible red (Band 3 for Landsat TM and ETM+, or Band 4 for Landsat OLI/TIRS) to visible blue (Band 1 for Landsat TM and ETM+, or Band 2 for Landsat OLI/TIRS) has a strong influence on the predictive power for TSS retrieval. Environmental factors including wind speed, remote sensing-derived water surface temperature, solar altitude, and time difference (in days) between the image acquisition and water sampling were found important in water-quality parameter estimation.

The evaluation of Eco-Environmental Quality (EEQ) is important to maintain the quality of ecology and is crucial for the protection of the environment and promote sustainable development. In the past 30 years, Rupandehi district has gone into rapid urbanization and population growth due to the migration of people causing drastic changes in Land use. This study takes Rupandehi district as a study area and analyses the land use change dynamics and its impact on the ecological environment from 1993 to 2023. The study utilizes the cloud computing capability of Google Earth Engine (GEE) to extract multiple indices using Landsat remote sensing data. We also applied the Thresholding approach to various spectral indices to extract land use information in GEE. The Remote Sensing Ecological Indices (RSEI) was constructed using Principal Component Analysis (PCA) to monitor the ecological quality and the effect of Land Use Land Cover (LULC) change on the quality of ecology was analysed. The result shows that the overall ecological quality of the Rupandehi district is good ranging from 0.59 in 1993 to 0.67 in 2023 with a significant impact of land use change. The eco-environmental quality of the study area is deteriorating because of a sharp increase in built-up areas and deforestation as well as the loss of agricultural land. Meanwhile, the spatial and temporal distribution of land use change collides with the change in the ecological quality of the study area. This study provides an accurate and rapid assessment of ecological quality and monitors the impact of land use change on it providing a scientific basis for researchers, government, and others to preserve the ecology and promote sustainable and eco-friendly development.

Background: Current management of COPD is predominantly focused on respiratory aspects. A multidimensional assessment including nutritional assessment, quality of life and disability provides a more reliable perspective of the true complexity of COPD patients. Methods: Prospective observational study of 120 elderly COPD patients at high risk of acute exacerbations. The Mini-Nutritional Assessment (MNA) was administered in addition to the usual respiratory assessment. The primary outcome was a composite of moderate or severe acute exacerbations during 52 weeks of follow-up. Results: The median MNA Short Form (SF) score was 11 (8-12), 39 participants (32.50%) had normal nutritional status, 57 (47.5%) were at risk of malnutrition and 24 (20%) were malnourished. Our multivariate linear logistic models showed that the MNA score was associated with dyspnea and respiratory symptoms severity assessed by the Modified British Medical Research Council (mMRC) and the COPD Assessment Test (CAT) score, with spirometric variables, in particular with the severity of airflow limitation based on the value of FEV1 and with poorer QoL as assessed by the EQ-5D-3 questionnaire. Cox regression analysis according to nutritional status based on the MNA score showed that COPD participants "at risk of malnutrition" and "malnourished" had a higher risk of moderate to severe acute exacerbations with a hazard ratio (HR) of 3.54 (p=0.002) and 8.20 (p=0.0001), respectively. Conclusion: Our study confirms the importance of assessing nutritional status in elderly COPD patients and its prognostic value.

In today's world, the significance of reducing energy consumption globally is increasing, making it imperative to prioritize energy efficiency in the 5th Generation (5G) networks. However, it is crucial to ensure that these energy-saving measures do not compromise the Key Performance Indicators (KPIs) such as user experience, quality of service (QoS), or other important aspects of the network. To address this challenge, advanced wireless technologies have been incorporated into the design of 5G networks across various network layers. Given the rapid advancements in Artificial Intelligence (AI) and emerging technology trends such as Machine Learning (ML), which is considered a subset of AI, the integration of such trends into 5G networks has become a significant area of research. The primary objective of this survey is to analyze AI integration into 5G networks for enhanced energy efficiency. By exploring this intersection between AI and 5G, we aim to identify potential strategies and techniques for optimizing energy consumption while maintaining the desired network performance and user experience.

To enhance pomegranate production on marginal gravelly lands, our study evaluated standardized planting techniques in an 8-year-old orchard. We employed trenching, wider pit excavation, pit digging, and auger digs with dimensions of 1 and 2 meters. Utilizing native soil from barren land, with or without spent wash, and mixing it with black soil up to 1 meter deep, we assessed growth parameters, leaf nutrients, and fruit yield. The trench and wider pit methods outperformed others, yielding greater above-ground biomass (>7.03 t tree-1), root biomass (2.5 t tree-1), and cross-sectional area (3.3 m² tree-1). Additionally, trench planting enhanced leaf phosphorus (0.28%) and potassium (1.8%) levels, fruit juice content (48.5%), total soluble solids (16.05°), and fruit yield (>9.3 t ha-1). The trench method also fostered longer roots at 90–150 cm radial distance and deeper roots at 40–60 cm depth. In summary, the trench and wider pit methods, combined with a soil mixture, are recommended for sustainable, high-quality fruit production in shallow gravelly terrains, thereby improving food security and the livelihoods of farmers in arid regions.

The paper delineates the developed vision system of the UR5 cobot and the operating algorithm of the robotic quality control station. The hardware-software architecture of the developed robotic station was shown, consisting of a UR5 cobot equipped with a web camera and a stationary industrial camera with a lighting system. Image processing and analysis algorithms were described, the method of control and communication between the station components was discussed, and two operating scenarios were presented as a single robotic station and a robotic line. Based on the results obtained, the level of measurement noise, accuracy, and repeatability of the developed vision system were estimated.

Assessment of health-related quality of life (HRQoL) after pediatric traumatic brain injury (TBI) has been limited in children and adolescents due to a lack of disease-specific instruments. To fill this gap, the Quality of Life after Traumatic Brain Injury for Children and Adolescents (QOLIBRI-KID/ADO) was developed for the German-speaking population. Reference values from a comparable general population are essential for comprehending the impact of TBI on health and well-being. This study examines the validity of the German QOLIBRI-KID/ADO in a general pediatric population in Germany and provides reference values for use in clinical practice. Overall, 1997 children and adolescents aged 8-17 years from the general population and 300 from the TBI population participated in the study. The questionnaire was tested for reliability and validity. A measurement invariance (MI) approach was used to assess the comparability of the HRQoL construct between both samples. Reference values were determined by percentile-based stratification according to factors that significantly influenced HRQoL in regression analyses. The QOLIBRI-KID/ADO demonstrated strong psychometric properties. The HRQoL construct was measured largely equivalently in both samples, and reference values could be provided. The QOLIBRI-KID/ADO was considered reliable and valid for assessing HRQoL in a general German-speaking pediatric population, allowing for clinically meaningful comparisons between general and TBI populations.

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.

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

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.

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.

Today, numerous studies have shown that the physical environment in hospitals can significantly influence patients' well-being, comfort, and recovery. However, this is currently neglected in hospitals in the Global South. Therefore, there is an urgent need to increase the awareness to make it more applicable worldwide. Thus, this study focuses on improving the healing environment standards, by exploring the impact of evidence-based design and patient-centred care in hospitals for cancer patients; particularly the architectural space quality, on patient health outcomes as well as hospital staff health and wellbeing. In Global North countries, such as the UK, the Achieving Excellence Design Evaluation Toolkit (AEDET), is used by its National Health Services, to assess the effectiveness of various environmental attributes. However, these toolkits have not been designed for and do not work well within Global South countries, such as Northern Cyprus. To examine and compare the effectiveness of different physical environmental attributes and to evaluate user responses, the Post-Occupancy Evaluation Method and the AEDET toolkit have been used in the study. These were applied to both public and private hospitals in Northern Cyprus, involving cancer patients, staff, and professionals (n=220). The findings reveal the strength and weaknesses in terms of environmental comfort based on the aspects of evidence-based design of the hospitals such as natural light, air quality, noise, view, infection control, etc., to create a more optimal physical environment for better psychological outcomes. This is the first study to propose an adaptation of the AEDET toolkit to assist architects in designing healthcare facilities that are responsive to the requirements of hospital patients and staff; and to promote the quality of healing environment for improved health and well-being outcomes.

Objective: Determine the feasibility of utilizing longitudinal electronic dental record (EDR) data to track change over time in patient periodontal disease (PD) and to generate three patient cohorts: 1) patients whose disease did not change over time, 2) patients whose PD progressed, and 3) patients whose disease improved over time using informatics approaches. Methods: We conducted a retrospective study of 28,908 patients who received a comprehensive oral evaluation between January 1, 2009, and December 31, 2014, at the Indiana University School of Dentistry (IUSD) clinics. We developed and tested three automated computer applications to: 1) diagnose periodontitis cases from periodontal charting, 2) retrieve clinician-documented diagnoses from clinical notes, and 3) track disease change over time. We also evaluated the density of longi-tudinal EDR data for the following follow-up times: 1) none, 2) up to 5 years, 3) >5 and <=10 years, and 4) >10 and <=15 years Results: Thirty-four percent (n=9,954) of the study cohort had up to five years of follow-up visits with an average of 2.78 visits with periodontal charting information. An average of three patient visits per year that contained periodontal charts (63,552) were utilized to obtain a diagnosis, which is considered excellent. For clinician-documented diagnoses from clinical notes, 42% of patients (n=5,562) had at least two PD diagnoses to determine their disease change. In this cohort with cli-nician-documented diagnoses, 72% percent of patients (n=3,919) did not have a disease status change between their first and last visits, 669 (13%) patients' disease status progressed, and 589 (11%) patients’ disease improved. Conclusions: This study demonstrated the feasibility of utilizing longitudinal EDR data to track disease changes over 15 years during the observation study period. We found excellent longitudinal data when diagnoses generated from periodontal charting were considered (three visits per pa-tient). This information can be now utilized for studying the clinical course of periodontitis.

Optical networks offer a wide range of benefits to the telecommunication sector world- wide with its provision of higher bandwidth which leads to faster data speed, longer transmission distance, and improved latency. Currently, the complexity associated with advancements in optical networks poses problems to network flexibility, reliability, and quality of service. Over the years, many reviews and proposals have been implemented by several literatures to provide solutions for optical networks using software-defined networks and network service orchestrators. This paper reviews the significant challenges in current optical network applications, the various solutions rendered by software-defined networks as well as network service orchestration, the impediments, and gaps in these software – defined networks. This paper will go a step further to look into the various improvements and implementations of software-defined networks tailored to solve specific optical network problems. This paper further proposes a flexible orchestration architecture for software-defined networks for solving flexibility and scalability problems in optical networks. This proposal uses Open Network System (ONOS) SDN controller, leveraging on dockerisation as well as kubernetes clusterisation and orchestration. This solution presents a more flexible, reliable, customable, and higher quality of service which is an improvement upon current solutions in literature.

The ISO 2859 and ISO 3951 series provide acceptance sampling procedures for lot inspection, allowing both sample size and acceptance rule to be determined, starting from a specific value either for the consumer or producer risk. However, insufficient resources often make it difficult to implement “ISO sampling plans.” In cases where the sample size is determined by external constraints, the focus shifts from determining sample size to determining consumer and producer risks. Moreover, if the sample size is very low (e.g. one single item), prior information should be included in the statistical analysis. For this reason, it makes sense to work within a Bayesian theoretical framework, such as that described in JCGM 106. Accordingly, the approach from JCGM 106 is adopted and broadened so as to allow application to lot inspection. The discussion is based on a “real-life” example of lot inspection on the basis of a single item. Starting from simple assumptions, expressions for both the prior and posterior distributions are worked out, and it is shown how the concepts from JCGM 106 can be reinterpreted in the context of lot inspection. Conceptual differences regarding the definition of consumer and producer risks in JCGM 106 and in the ISO acceptance sampling standards are elucidated and a numerical example is provided.

Persistent Spinal Pain Syndrome Type 2 (PSPS-T2), (Failed Back Surgery Syndrome), dramatically impacts on patient quality of life, as evidenced by Health-Related Quality of Life (HRQoL) assessment tools. However, the importance of functioning, pain perception and psychological status in HRQoL can substantially vary between subjects. Our goal was to extract patient profiles based on HRQoL dimensions in a sample of PSPS-T2 patients and to identify factors associated with these profiles. Two classes were clearly identified using a mixture of mixed effect models from a clinical data set of 200 patients enrolled in “PREDIBACK”, a multicenter observational prospective study including PSPS-T2 patients with 1-year follow-up. We observed that HRQoL was more impacted by functional disability for first class patients (n=136) and by pain perception for second class patients (n=62). Males that perceive their work as physical were more impacted by disability than pain intensity. Lower education level, lack of adaptive coping strategies and higher pain intensity were significantly associated with HRQoL being more impacted by pain perception. The identification of such classes allows for a better understanding of HRQoL dimensions and opens the gate towards optimized health-related quality of life evaluation and personalized pain management.

In recent years, data providers are generating and streaming a large number of images. More particularly, processing images that contain faces have received great attention due to its numerous applications, such as entertainment and social media apps. The enormous amount of images shared on these applications presents serious challenges and requires massive computing resources to ensure efficient data processing. However, images are subject to a wide range of distortions in real application scenarios during the processing, transmission, sharing, or combination of many factors. So, there is a need to guarantee acceptable delivery content, even though some distorted images do not have access to their original version. In this paper, we present a framework developed to estimate the images' quality while processing a large number of images in real-time. Our quality evaluation is measured using an integration of a deep network with random forests. In addition, a face alignment metric is used to assess the facial features. Experimental results have been conducted on two artificially distorted benchmark datasets, LIVE and TID2013. We show that our proposed approach outperforms the state-of-art methods, having a Pearson Correlation Coefficient (PCC) and Spearman Rank Order Correlation Correlation Coefficient (SROCC) with subjective human scores of almost 0.942 and 0.931 while minimizing the processing time from 4.8ms to 1.8ms.

In this paper, we present the results of the research concerning extraction of informative gene expression profiles from high-dimensional array of gene expressions considering the state of patients' health using clustering method, ensemble of binary classifiers and fuzzy inference system. Applying of the proposed stepwise procedure can allow us to extract the most informative genes taking into account both the subtypes of disease or state of the patient's health for further reconstruction of gene regulatory networks based on the allocated genes and following simulation of the reconstructed models. We used the publicly available gene expressions data as the experimental ones which were obtained using DNA microarray experiments and contained two types of patients' gene expression profiles: the patients with lung cancer tumor and healthy patients. The stepwise procedure of the data processing assumes the following steps: in beginning, we reduce the number of genes by removing non-informative genes in terms of statistical criteria and Shannon entropy; then, we perform the stepwise hierarchical clustering of gene expression profiles at hierarchical levels from 1 to 10 using SOTA clustering algorithm with correlation distance metric. The quality of the obtained clustering was evaluated using complex clustering quality criterion which is considered both the gene expression profiles distribution relative to center of the clusters were these gene expression profiles are allocated and the centers of the clusters distribution. The result of this stage execution was selection of the optimal cluster at each of the hierarchical levels which corresponded to minimum value of the quality criterion. At the next step, we have implemented classification procedure of the examined objects using four well known binary classifiers: logistic regression, support-vector machine, decision trees and random forest classifier. The effectiveness of the appropriate technique was evaluated based on the use of ROC analysis using criteria included as the components the errors of both the first and the second kinds. The final decision concerning extraction of the most informative subset of gene expression profiles was taken based on the use of fuzzy inference system, the inputs of which are the results of the appropriate single classifiers operation and output is the final solution concerning state of the patient's health. To our mind, the implementation of the proposed stepwise procedure of the informative gene expression profiles extraction create the conditions for increasing effectiveness of the further procedure of gene regulatory networks reconstruction and the following simulation of the reconstructed models considering the subtypes of the disease and/or state of the patient’s health.

Mitochondrial functions are essential for life, critical for development, maintenance of stem cells, adaptation to physiological changes, responses to stress and aging. The complexity of mitochondrial biogenesis requires coordinated nuclear and mitochondrial gene expression, owing to the need of stoichiometrically assemble the OXPHOS system for ATP production. It requires, in addition, the import of thousands of proteins from the cytosol to keep optimal mitochondrial function and metabolism. Moreover, mitochondria require lipid supply for membrane biogenesis, while it is itself essential for the synthesis of membrane lipids. To achieve mitochondrial homeostasis, multiple mechanisms of quality control have evolved to ensure that mitochondrial function meets cell, tissue and organismal demands. Herein, we give an overview of mitochondrial mechanisms that are activated in response to stress, including mitochondrial dynamics, mitophagy and the mitochondrial unfolded protein response (UPR^mt). We then discuss the role of these stress responses in aging, with particular focus on Caenorhabditis elegans. Finally, we review observations that point to the mitochondrial PHB (prohibitin) complex as a key player in mitochondrial homeostasis, being essential for mitochondrial biogenesis and degradation, and responding to mitochondrial stress. Understanding how mitochondria responds to stress and how such responses are regulated is pivotal to combat aging and disease.

Traditionally, palliative care (PC) systems focused on the needs of advanced cancer patients. But, most patients needing PC have end-stage organ diseases. Similarly, PC models focused on the needs of patients in hospice or at home; however, in most cases PC is provided in acute hospitals. Indeed, the symptom burden that these patients experience in the last year of life frequently forces them to seek care in Emergency Department. The majority of them are admitted to the hospital and many die. This issue poses important concerns. Despite the efforts of attending healthcare professionals, inhospital patients do not receive optimal care near the end-of-life. Also, evidence is emerging that delay in identifying patients needing PC have a detrimental impact on their quality of life (QoL). Therefore, there is an urgent need to early and properly identify these patients among those hospitalized. Several trials reported the efficacy of PC in improving the QoL in these patients. Each hospital should ensure that a multidisciplinary PC team is available to support attending physicians to achieve the best QoL for both PC patients and their families. This review discusses the role and the impact of inhospital PC in patients with end-stage disease or advanced cancer.

Hydroponic farming systems play an increasingly important role in the sustainable production of nutrient-rich foods. The contamination of surfaces in hydroponic fresh produce production poses risks to the food safety of crops, potentially endangering public health and causing economic losses in the industry. While sanitizers are widely used in commercial hydroponic farms, their effectiveness against human pathogens on surfaces, and their impact on plant health and quality are not known. In this study, we evaluated the efficacy of chemical sanitizers in eliminating Salmonella Typhimurium from inanimate surfaces in commercial hydroponic Nutrient Film Technique (NFT) systems. Further, we assessed the impact of sanitizers on the yield, quality, and nutritional value of lettuce and basil. Sanitizers (Virkon, LanXess; Sanitate 12.0, Bi-oSafe Systems; Kleen Grow, Pace Chemical Ltd.; Green Shield, United Labs Inc.; Zerotol, BioSafe Systems; Bleach, Pure Bright), were tested against Salmonella Typhimurium inoculated on NFT surfaces (nutrient reservoirs, growing channels, top covers, drain lines). The effective treatments were then tested for their impact on lettuce and basil in a split-plot experiment conducted in commercial NFT units. Crop yield, color, and nutrient content were measured throughout the crop life cycle. While all quaternary ammonium compounds (QAC), SaniDate 12.0 (200ppm), Zorotol (5%), and Virkon (1%) eliminated Salmonella Typhimurium from commercial NFT surfaces, chlorine-based sanitizer treatments were statistically similar to water treatments on most surfaces. All chemical sanitizers impacted the yield, color, and nutritional value of lettuce and basil. SaniDate 12.0 (200ppm) was the least detrimental to crops and was identified as a potential candidate for further validation in commercial hydroponic settings. The findings of this study will be translated into recommendations for the industry and will contribute to the development of future food safety guidelines and policies.