Heat shock proteins (HSPs) are a family of molecular chaperones that regulate essential protein refolding and triage decisions to maintaining protein homeostasis. Numerous co-chaperone proteins directly interact and modify the function of HSPs, and these interactions impact the outcome of protein triage, impacting everything from structural proteins to cell signaling mediators. The chaperone/co-chaperone machinery protects against various stressors to ensuring cellular function in the face of stress. However, coding mutations, expression changes, and post-translational modifications of the chaperone/co-chaperone machinery can alter the cellular stress response. Importantly, these dysfunctions appear to contribute to numerous human diseases. Therapeutic targeting of chaperones is an attractive but challenging approach due to the vast functions of HSPs, likely contributing to the off-target effects of these therapies. Current efforts focus on targeting co-chaperones to develop precise treatments for numerous diseases caused by defects in protein quality control. This review focuses on the recent developments regarding selected HSP70/HSP90 co-chaperones, focusing on cardioprotection, neuroprotection, and cancer. We also discuss therapeutic approaches that highlight both the utility and challenges of targeting co-chaperones.

Background: Most prevalence surveys on nocturia have focused on older populations. This study aimed to measure the nocturia prevalence across the full spectrum of male adults living in Hong Kong, where severity and associated quality-of-life (QoL) were also explored. Methods: A cross-sectional population-based survey was conducted in men aged 18 or above using the ICIQ-NQoL Questionnaire. Results: With 1,239 respondents at age ranged 18-99, the overall nocturia prevalence were found to be 63.0% (ranged 41.6-84.6% at different age groups) and 31.2% (ranged 13.0-56.3% at different age groups), for ≥1 and ≥2 bedtime voiding episodes, respectively. The chance of nocturia was dramatically increased at age 60 or above while both prevalence and voiding frequency were increased with advancing age. About 83% of the nocturia men experienced 1-2 voiding episodes per night, but many of them had self-rated their QoL poor or very poor and indicated moderate-to-high bothersome. Younger men at age 18-39 were found to have high prevalence as 41.6% and almost 30% of them rated poor or very poor QoL. Conclusions: Nocturia was not only affecting the older populations but also caused significant bothersome and negative impacts on QoL in younger males.

The effect of COVID-19 confinement regulations on air quality in the northwestern Alps is here assessed based on measurements at five valley sites in different environmental contexts. Surface concentrations of nitrogen oxides, ozone, particle matter, together with size, chemical, and optical (light absorption) aerosol properties, complemented by observations along the vertical column are considered. The 2020 concentration anomalies relative to previous years’ average are compared with the output of a machine learning algorithm accounting for weather effects and a chemical transport model, their difference being within 10–20 %. Even in the relatively pristine environment of the Alps, the «lockdown effect» is well discernible, both in the early confinement phase and in late 2020, especially in NOx concentrations (NO decreasing by >80 % and NO2 by >50 %). While ozone shows little variation, secondary aerosols increase due to enhanced transport from the neighbouring Po basin and coarse particles decrease due to missing resuspension by traffic and, in the city, to the shutdown of a steel mill. The NO2 vertical column density decreases by >20 %, whereas the aerosol profile is mainly influenced by large-scale dynamics, except a shallow layer about 500 m thick possibly sensitive to curtailed surface emissions.

The City of Meycauayan is considered as one of the most polluted cities in the developing world on the account of industrial discharges of toxic materials to the environment. This work investigated the sources of the heavy metal pollution by analyzing soil and sediment samples for heavy metals (Cr, Hg, Ni, and Pb) together with selected environmental indicators (TN, TOM, and TP) located along the Meycauayan River. Hierarchical cluster analysis (HCA), principal components analysis (PCA), and Pearson correlation analysis (CA) were used to identify the sources of the metals. Results showed delineated locations of severe levels of heavy metal pollution downstream because of the concentration of industrial activities. Cr contributed more than any other heavy metals analyzed due to proliferation of tanneries discharging untreated wastewaters to the river. Significant inputs of Pb and Hg from Pb-acid battery recycling and gold smelting industries were also found. Risk assessments indicated severe levels of heavy metal pollution where industrial activities are concentrated. The mean Cr, Pb, Ni, and Hg in the sampling locations have mean incidences of toxicity of 91.7 %, 53.6 %, 27.7 %, and 70.0 %, respectively. Our study showed a serious need to address heavy metal pollution in Meycauayan.

This work examines the effects of two problematic trends in diesel passenger car emissions – increasing NO2/NOx ratio by conversion of NO into NO2 in catalysts and a disparity between the emission limit and the actual emissions in everyday driving – on ambient air quality in Prague. NO2 concentrations were measured by 104 membrane-closed Palmes passive samplers at 65 locations in Prague in March-April and September-October of 2019. NO2 concentrations measured by city stations during those periods were comparable with the 2016-2019. The average measured NO2 concentrations at the selected locations, after correcting for the 18.5% positive bias of samplers co-located with a monitoring station, were 36 µg/m3 (range 16-69 µg/m3, median 35.3 µg/m3), with the EU annual limit of 40 µg/m3 exceeded at 32% of locations. The NO2 concentrations have correlated well (R2=0.76) with the 2019 average daily vehicle counts, corrected for additional emissions due to uphill travel and intersections. In addition to expected “hot-spots” at busy intersections in the city center, new ones were identified, i.e. along a six-lane road V Holešovičkách. Comparison of data from six monitoring stations during March 15-April 30, 2020 travel restrictions with the same period in 2016-2019 revealed an overall reduction of NO2 and even a larger reduction of NO. The spatial analysis of data from passive samplers and time analysis of data during the travel restrictions both demonstrate a consistent positive correlation between traffic intensity and NO2 concentrations along/near the travel path. The slow pace of NO2 reductions in Prague suggests that stricter vehicle NOx emission limits, introduced in the last decade or two, have so far failed to sufficiently reduce the ambient NO2 concentrations, and there is no clear sign of remedy of Dieselgate NOx excess emissions.

Monitoring volatile organic compounds (VOCs) places a crucial role in environmental pollutants control and indoor air quality. In this study, a metal-oxide (MOx) sensor detector (used in a commercially available monitor) was employed to delineate the composition of air containing three common VOCs (ethanol, acetone and hexane) under various concentrations. Experiments with a single component and double components were conducted to investigate how the solvents interact with the metal oxide sensor. The experimental results revealed that the affinity between VOC and sensor was in the following order: acetone > ethanol > n-hexane. A mathematical model was developed, based on the experimental findings and data analysis, to convert the output resistance value of the sensor into concentration values, which in turn can be used to calculate a VOC-based air quality index. Empirical equations were established based on inferences of vapor composition versus resistance trends, and on an approach of using original and diluted air samples to generate two sets of resistance data per sample. The calibration of numerous model parameters allowed matching simulated curves to measured data. As such, the predictive mathematical model enabled quantifying not only the total concentration of sensed VOCs, but also estimating the VOC composition. This first attempt to obtain semi-quantitative data from a single MOx sensor, despite remaining selectivity challenges, is aimed at expanding the capability of mobile air pollutants monitoring devices.

Machine learning is an established and frequently used technique in industry and academia but a standard process model to improve success and efficiency of machine learning applications is still missing. Project organizations and machine learning practitioners have a need for guidance throughout the life cycle of a machine learning application to meet business expectations. We therefore propose a process model for the development of machine learning applications, that covers six phases from defining the scope to maintaining the deployed machine learning application. The first phase combines business and data understanding as data availability oftentimes affects the feasibility of the project. The sixth phase covers state-of-the-art approaches for monitoring and maintenance of a machine learning applications, as the risk of model degradation in a changing environment is eminent. With each task of the process, we propose quality assurance methodology that is suitable to address challenges in machine learning development that we identify in form of risks. The methodology is drawn from practical experience and scientific literature and has proven to be general and stable. The process model expands on CRISP-DM, a data mining process model that enjoys strong industry support but lacks to address machine learning specific tasks. Our work proposes an industry and application neutral process model tailored for machine learning applications with focus on technical tasks for quality assurance.

The Covid-19 pandemic is a tragedy for those who have been hard hit worldwide. At the same time, it is also a test of concepts and practices of what good care is and requires, and how quality of care can be accounted for. In this paper, we present our Care-Ethical Model of Quality (CEMQ) and apply it to the case of residential care for older people in the Netherlands during the Covid-19 pandemic. Instead of thinking about care in healthcare and social welfare as a set of separate care acts, we think about care as a complex practice of relational caring, crossed by other practices. Instead of thinking about professional caregivers as functionaries obeying external rules, we think about them as practically wise professionals. Instead of thinking about developing external quality criteria and systems, we think about cultivating (self-)reflective quality awareness. Instead of abstracting from societal forces that make care possible but also limit it, we acknowledge them and find ways to deal with them. Based on these critical insights, the CEMQ model can be helpful to describe, interrogate, evaluate, and improve existing care practices. It has four entries: (i) the care receiver considered from their humanness, (ii) the caregiver considered from their solicitude, (iii) the care facility considered from its habitability and (iv) the societal, institutional and scholarly context considered from the perspective of the good life, justice and decency. The crux is enabling all these different entries with all their different aspects to be taken into account. In Corona times this turns out to be more crucial than ever.

Despite recent developments in monitoring and visualizing construction progress, the data exchange between construction jobsite and office lacks automation and real-time recording. To address this issue, a near real-time construction work inspection system called iVR is proposed; this system integrates 3D scanning, extended reality, and visual programming to visualize interactive onsite inspection for indoor activities and provide numeric data. iVR comprises five modules: iVR-location finder (finding laser scanner located in the construction site) iVR-scan (capture point cloud data of jobsite indoor activity), iVR-prepare (processes and convert 3D scan data into a 3D model), iVR-inspect (conduct immersive visual reality inspection in construction office), and iVR-feedback (visualize inspection feedback from jobsite using augmented reality). An experimental lab test is conducted to validate the applicability of iVR process; it successfully exchanges required information between construction jobsite and office in a specific time. This system is expected to assist Engineers and workers in quality assessment, progress assessments, and decision-making which can realize a productive and practical communication platform, unlike conventional monitoring or data capturing, processing, and storage methods, which involve storage, compatibility, and time-consumption issues.

In this paper we analyze and propose new method and algorithm of selecting the optimal labor time as a function of skills following our main references Mirrlees (1971), Saez (2001) and Stancheva (2014). The optimal labor time is a situation when the utility function of individual reaches a maximum. One of the main differences with Saez (2001) is our algorithm for creation the skill distribution

HDPE (high-density polyethene) plastic waste is stronger, harder, and more resistant to high temperatures than other plastics. Using it as an additive in a concrete mixture is one solution to reduce this type of waste. We examined how HDPE-type plastics can be used as an additive material in the manufacture of concrete to improve its hardness, tensile strength and compressive strength. Using 156 samples, we aimed to identify the effect of HDPE plastic fibres on concrete of three qualities; B0, f'c10 MPa (low quality), and f'c25 MPa (medium and high quality). We added four compositions (2.5%, 5%, 10% and 20% by weight of cement) of HDPE plastic fibre to each quality of cement, with HDPE plastic fibre sizes of 1 x 1 cm, 0.5 x 2 cm or 0.25 x 4 cm. We found that the addition of 5% HDPE plastic fibre with a 0.5 x 2 cm cross-sectional shape to the f'c10 MPa concrete gives the best result, with increased tensile and compressive strength of the concrete.

Organizations can play a significant role in the advancement of Sustainable Development, and companies with Quality, Environmental and Occupational Health and Safety (QEOHS) certified management systems address the three Sustainability Dimensions (economic, environmental and social). This research aims to map the present level of engagement of those companies in contributing and reporting to the 17 Sustainable Development Goals of The United Nations 2030 Agenda. The content of companies reports (available in web sites, by 31 December 2017) of a total of 235 Portuguese organizations with QEOHS certified management systems, was analyzed. The results show a moderate reporting of SDGs by those companies, with the top five being SDG 12 - Responsible consumption and production (23.8%), SDG 13 – Climate action (22.1%), SDG 09 - Industry, innovation, and infrastructure (21.3%), SDG 08 - Decent work and economic growth (20.0%) and SDG 17 - Partnerships for the goals (19.6%). The results of the statistical tests indicate that the communication of SDGs is more prominent in organizations (QEOHS) with higher business volume, that are members of the United Nations Global Compact Network Portugal, and that disclose their sustainability reports on their web site. This study can be useful for decision-makers that aim to support organizations to contribute to the Sustainable Development Goals.

The Internet of Things (IoT) is an emerging technology that aims to enable the interconnection of a large number of smart devices and heterogeneous networks. Ad hoc networks play an important role in the designing of IoT-enabled platforms due to their efficient, flexible, low-cost, and dynamic infrastructures. These networks utilize the available resources efficiently to maintain the Quality of Service (QoS) in a multi-hop communication. However, in a multi-hop communication, the relay nodes can be malicious, thus requiring a secured and reliable data transmission. In this paper, we propose a QoS-aware secured communication scheme for IoT-based networks (QoS-IoT). In QoS-IoT, a Sybil attack detection mechanism is used for the identification of Sybil nodes and their forged identities in multi-hop communication. %by high-power and mobile nodes. After Sybil nodes detection, an optimal contention window (CW) is selected for QoS provisioning, i.e., to achieve per-flow fairness and efficient utilization of the available bandwidth. In a multi-hop communication, the MAC layer protocols do not perform well in terms of fairness and throughput, especially when the nodes generate a large amount of data. It is because the MAC layer has no capability of providing QoS to prioritized or forwarding flows. We evaluate the performance of QoS-IoT in terms of Sybil attack detection, fairness, throughput, and buffer utilization. The simulation results show that the proposed scheme outperforms the existing schemes and significantly enhances the performance of the network with a large volume of data. Moreover, the proposed scheme is resilient against Sybil attack.

Abstract This trial was realized in Yenisehir Vocational School between 2007 and 2008 on the purpose of study out the influence of lack of water in four growth periods of cabbage. In this trial, fourteen irrigation treatments was formed considering the growth periods (establishment, vegetative, yield formation and ripening) of cabbage (Brassicaceae Oleracea var. capitata L. Grandslam F1) and the results obtained from these treatments were evaluated. According to the content of the treatments, the water amount to the plants varied between 0 and 524 mm in the 2007 year, and between 0 and 536 mm in the 2008 year. Water consumption of cabbage in the 2007 year ranged between 200 and 795 mm and in the 2008 year ranged between 190 and 802 mm. Yield, head weight, diameter, height and dry matter ratio were determined statistically important. In 2007 and 2008 years, the maximal yield were found as 74.2 t ha-1 and 72.4 t ha-1 in the E100V100Y100R100 treatments, while the minimal yield were found as 2.0 t ha-1 and 4.0 ha-1 in the E0V0Y0R0 treatments, respectively. Water- yield relationship factor (ky) in 2007 and 2008 years were found as 0.96 and 0.97, respectively.

Additive manufacturing (AM) provides customization of the microstructure and mechanical properties of components. Selective laser melting (SLM) is the commonly used technique for processing high strength Aluminum alloys. Selection of SLM process parameters could control the microstructure of fabricated parts and their mechanical properties. However, process parameter limits and defects inside the as-built parts present obstacles to customized part production. This study is the second part of a comprehensive work that investigates the influence of SLM process parameters on the quality of as-built Al6061 and AlSi10Mg parts. The microstructure of both materials was characterized for different parts processed over a wide range of SLM process parameters. The optimized SLM parameters were investigated to eliminate the internal microstructure defects. Mechanical properties of the parts were illustrated by regression models generated with design of experiment (DOE) analysis. The results reported in this study were compared to previous studies, illustrating how the process parameters and powder characteristics could affect the quality of produced parts.

Power quality is a major concern in electrical power systems. The power quality disturbances such as sags, swells, harmonic distortion and other interruptions have impact on the electrical devices and machines and in severe cases can cause serious damages. Therefore it is required to recognize and compensate all types of disturbances at an earliest to ensure normal and efficient operation of the power system. To solve these problems, many types of power devices are used. At the present time, one of those devices, Dynamic Voltage Restorer (DVR) is the most efficient and effective device used in power distribution system. In this paper, design and modeling of a new structure of multifunctional DVR for voltage correction is presented. The performance of the device under different conditions such as voltage swell, voltage sag due to symmetrical and unsymmetrical short circuit, starting of motors, and voltage distortion are described. Simulation result shows the superior capability of proposed DVR to improve power quality under different operating conditions. The proposed new DVR controller is able to detect the voltage disturbances and control the converter to inject appropriate voltages independently for each phase and compensate to load voltage through three single- phase transformers.

Water quality assessment in pastoral of Tibetan Plateau, which is water sources for about 40% of world's population and the runoff-yield area of Yellow rivers, is very important. In this paper, Xiahe county which belongs to Tibetan Plateau pastoral was investigated. Six parameters(via, chloride, COD, ammonia nitrogen, nitrate, fluoride, sulfate) were selected to assess the water quality and health degree by using fuzzy comprehensive evaluation methods. The hydrochemical type in surface water was of HCO3--Mg2+-Ca2+ type. The cations and anions in surface water were mainly from weathering and dissolution of carbonate rock. Results showed that the water quality in all 69 sampling sites was all of class Ⅰ. The integrated health degree reached more than 0.85 and the health rate were 100%. Although ammonia nitrogen was regarded as the main contamination factor, but it had a little effect on the entire body of water. Overall, the surface water qualities of most samples in Xiahe County was good condition.

In the fast-evolving landscape of web services, success relies on optimizing efficiency, reliability, and user satisfaction. Decision-making in real-world applications demands a blend of quantitative (numerical values of quality of Service factors) and qualitative data of experts’ ratings of the quality of service factors. This paper proposes an optimization technique that integrates Hesitant and Intuitionistic Fuzzy Linguistic Terms with TOPSIS, leveraging Entropy Objective weights. There is limited research on Hesitant Intuitionistic Fuzzy Linguistic terms and the need to model fuzziness, haste and intuition in data precisely from experts rating. Thus, this article introduces an Entropy-based model tailored for web service optimization. Using the WS-DREAM dataset, quantitative data was extracted and objective weights were determined through the Entropy algorithm and qualitative evaluations from five experts, employing Hesitant Intuitionistic Fuzzy Linguistic Terms, were integrated. The process involved computing criteria weights and experts' assessment of Quality of Service factors for four services (S1, S2, S3, and S4) to form the Fuzzy Decision Matrix using modified Online output software. Applying the proposed technique to a web service optimization problem validated its effectiveness. The results indicated optimal selection of S1 as the best web service, supported by Coefficient Index values (0.785). This study introduces a novel approach, Entrop – Hesitationistic - Fuzz-TOPSIS, for web service optimization, integrating quantitative and qualitative data through an Entropy-based model. The effectiveness of the proposed technique, validated through application on the WS-DREAM dataset, underscores its potential in addressing real-world decision-making challenges. The optimal selection of S1 as the best web service suggests practical utility. The study encourages further exploration of this technique's applicability to diverse Multiple Criteria Decision Making (MCDM) problems, opening avenues for future research and application.

Introduction: The Fontan procedure, a palliative surgery for univentricular heart physiology, of-ten reduces exercise capacity and quality of life. This study aimed to evaluate the impact of cardiac rehabilitation (CR) on improving outcomes in Fontan patients to inform evidence-based care. Methods: Fontan patients aged 8-30 participated in a structured CR program for at least three months. The program included weekly aerobic and resistance training sessions, with educational and nutritional guidance. Baseline and post-CR assessments included cardiac function, fitness, daily activity, and health-related quality of life (HRQOL). Results: The cohort included ten Fontan patients, of whom six had a right systemic ventricle. CR significantly improved cardiorespiratory fitness, as seen in VO2 max (from 27.92 ± 5.15 to 34.69 ± 1.14 mL/kg/min, p = 0.0089) and per cent predicted VO2 (from 0.67 ± 0.18 to 0.90 ± 0.02, p = 0.005). VCO2 increased by +8.68 ± 8.59 mL/kg/min, but did not reach statistical significance (p = 0.05). Most haemodynamic and ventila-tory parameters showed no significant improvement. All the SF-36 questionnaire domains showed significant HRQOL gains (p < 0.001). High adherence (85-93%), no adverse events, and reduced NT-proBNP levels supported the program's safety. Conclusion: This study's findings have im-portant implications for the care of Fontan patients. CR significantly improved exercise capacity and HRQOL in Fontan patients across various anatomies, particularly in the right systemic ven-tricle. Integrating physical conditioning into standard care could reduce long-term morbidity and mortality; however, further research is needed to refine the protocols and confirm sustained ben-efits.

The central aim of this paper is to present the Green Web Meter software which is designed to support the measurement of digital sustainability performance of websites and web apps, as well as providing sound based analytic tools for improving their overall quality. We analyzed scientific literature and specifically selected three quality assessment models (E-S Qual, Sitequal, Webqual 4.0) which we used as a starting point for identifying the most crucial aspects for the monitoring activities. A consistent set of Key Performance Indicators (KPIs) suitable for automated tracking has been provided. We finally developed model-based software able to deliver solutions for real-time website performance analysis and reports. We structured the model to offer accurate references for digital sustainability reporting by aggregating the KPIs into an Environmental, Social, and Governance (ESG) framework and computing a comprehensive score for its pillars.

Some preterm and sick neonates have altered biochemical profiles and follow-up newborn screening (NBS) collections are recommended. The Victorian NBS program historically recommended recollections for babies with birth weight &lt;1500g (managed by the maternity service provider) and 3 weeks post-transfusion (managed by the laboratory). We aimed to determine adherence to current guidelines and review the guidelines to improve NBS performance. To do this we audited data from 348,584 babies between January 2018 and June 2022. Babies with a recorded birth weight of &lt;1500g were filtered for inclusion. For the overall review and visualization of the protocol, we sourced information from the literature, our professional society and tertiary hospital services. A total of 2647 babies had a birth weight recorded between 200 and 1499g. Of these 2036 (77%) had a second sample collected, indicating that &gt;1 in 5 babies were not receiving a follow-up collection. Our timing of recollections for transfused babies, requiring a 3-week follow-up collection, was longer than in other Australasian jurisdictions. A new combined “sick-prem-protocol” was launched to support recollections and after a one-year review achieve 95% compliance. We recommend NBS laboratories audit preterm and sick neonate recollections to ensure appropriate follow-up. This should be supported with a visual process map to aid education and compliance.

Objective: This study aimed to assess the impact of artificial intelligence (AI)-driven noise reduction algorithms on metal artifacts and image quality parameters in cone-beam computed tomography (CBCT) images of the oral cavity. Materials and Methods: This retrospective study included 70 patients, 61 of whom were analyzed after excluding those with severe motion artifacts. CBCT scans, performed using a Hyperion X9 PRO 13 × 10 CBCT machine, included images with dental implants, amalgam fillings, orthodontic appliances, root canal fillings, and crowns. Images were processed with ClariCT. AI deep learning model (DLM) for noise reduction. Objective image quality was assessed using metrics such as the differentiation between voxel values (ΔVVs), the artifact index (AIx), and the contrast-to-noise ratio (CNR). Subjective assessments were performed by two experienced readers, who rated overall image quality and artifact intensity on predefined scales. Results: Compared with native images, DLM reconstructions significantly reduced the AIx and increased the CNR (p<0.001), indicating improved image clarity and artifact reduction. Subjective assessments also favored DLM images, with higher ratings for overall image quality and lower artifact intensity (p<0.001). However, the ΔVV values were similar between the native and DLM images, indicating that while the DLM reduced noise, it maintained the overall density distribution. Orthodontic appliances produced the most pronounced artifacts, while implants generated the least. Conclusion: AI-based noise reduction using ClariCT. AI significantly enhances CBCT image quality by reducing noise and metal artifacts, thereby improving diagnostic accuracy and treatment planning. Further research with larger, multicenter cohorts is recommended to validate these findings.

Salinity, resulting from climate change and excessive mineral fertilization, burdens farmers and negatively impacts soil and water ecosystems in the Northeastern Nile Delta. Organic and biological approaches are crucial for addressing these issues. This study examined the effects of individual and combined inoculations with cyanobacteria, yeast, and Arbuscular Mycorrhizal Fungi (AMF), with or without K-humate, on enhancing salinity tolerance, increasing yield, and improving crop quality of wheat and faba bean. The aim was to reduce NPK mineral fertilizer application rates to 25% of recommended doses. An economic evaluation was also conducted. In a preliminary laboratory experiment, the interactive effects of these microbiomes on the production of plant antioxidant enzymes and soil enzymes were investigated under salinity stress. Results showed that co-inoculation, especially with K-humate, yielded superior outcomes compared to individual inoculations. The laboratory experiment findings were confirmed by a field trial conducted in saline-alkaline soil in the Northeastern Nile Delta region. The study found that the integrated inoculation of cyanobacteria, yeast, and mycorrhizae with K-humate, along with 25% mineral NPK fertilization enhanced microbial activity, including AMF colonization, spore density, and total bacteria, cyanobacteria, and yeast counts in the plant rhizosphere. It also increased soil enzyme activity, improving soil fertility compared to individual or mineral control treatments. This integration resulted in wheat yields of 2.77 tons/ha and faba bean yields of 4.75 tons/ha. Crop quality improved, with higher levels of nitrogen, potassium, phosphorus, and protein in wheat grains and faba bean seeds. Microbiomes inoculation increased potassium uptake over sodium, enhancing the potassium/sodium ratio and salt stress tolerance. This approach reduces reliance on costly mineral fertilizers by up to 75%, enabling economically viable cultivation in marginal lands. These sustainable practices optimize resource utilization, maximize economic efficiency, and preserve natural resources.

In air quality management, at urban and regional levels, road transport remains the cornerstone of residential, commercial, and industrial activities, and the vehicle exhaust emissions maintain the position of one of the key contributing sources. In Indian cities, big and small, vehicle exhaust emissions and dust from vehicle movement on the roads, contribute to as much as 50% of particulate matter pollution in a year. So, having access to a vehicle exhaust emissions inventory that is reliable and replicable is critical for air quality management and this exercise starts with access to vehicle stock numbers. These numbers are typically obtained from vehicle registration databases, traffic surveys, and other governmental records, and often require time consuming data cleaning protocols before they can used for emissions and pollution baseline analysis. This paper provides a cleaned and open-access vehicle stock database, as registered and in-use fleet, for the period covering 1993 and 2018, for all India and states, along with an estimate of age-mix of the vehicles using survival functions.

The paper describes the new method for image compression based on coordinated group signal transformation. The algorithm is a type of difference coding. Coordinated processing significantly simplifies the difference signal conversion scheme using a single group codec for all signals. The described method considers color channels as correlated signals of a multi-channel communication system. The specifics of the processed data required modification of the coordinated group processing algorithm. First, we changed how to calculate the difference signals to prevent data loss. Secondly, the group codec was supplemented with a neural network to improve the quality of reconstructed images. We considered the following types of neural networks: fully connected, recurrent, convolution, and convolution in the Fourier space. Based on the simulation results, it is best to use fully connected neural networks if the goal is to minimize processing delay time. These networks have a response time of 13 ms. On the other hand, if the priority is to improve quality in cases where delays are not critical, then convolution neural networks in the Fourier space should be used. These networks have a response time of 140 ms and are of significant interest.

The prevalence of diagnosed cases of autism has increased rapidly, which raise interest in studying the variables related to the well-being of these families. The purpose of this paper is to review recent literature on other variables related to family well-being such a parenting styles. We conducted a systematic review using PRISMA check list and bias assessment ESTROBE with the aim of analyzing if the concepts of autism, well-being and parenting style are related. We screened 753 references, 16 full text articles and abstracts were read. It was identified that authoritative parenting style, those based on warmth, establishing relationships and emotional bonding, and low expressed emotion were positively related to family well-being. On the other hand, authoritarian, permissive and overprotective styles, as well as critical, punishing and training-based were negatively associated with well-being and quality of family life.

Objective: The COVID-19 pandemic inferred on neuro-oncological patients (PTS) and the caregivers regarding tumor care and emotional functioning. This study aimed to understand how COVID-19 affects their psychological state and relations between PTS and health personnel in neuro-oncology. Methods: A cross-sectional study on neuro-oncological PTS and their caregivers. Results: A total of 162 PTS and 66 caregivers completed the questionnaire. The 37.5% of PTS perceived greater risk of contracting the COVID-19 compared to the general population. On the 0-10 scale, PTS tumor-related anxiety score was 5.8 and COVID-related 4.6. The caregivers reported 7.7 and 5.5 respectively. The QoL was described at least as good in 75% of both PTS and caregivers; the caregivers’ care burden increased in 22.7% during the pandemic, with no correlation with QoL. Future perception often changed both in PTS and in the caregivers. Cancer treatment schedule was changed in 18.5%, including for PTS decision. However, the 93.5% of PTS was satisfied with the overall care. Conclusion: A considerable proportion of PTS and caregivers still perceived the tumor disease as more burdensome than the pandemic, and perceived their future as more uncertain. Such data rinforce the need to build a proficient alliance between PTS and health personnel.

In the current complex and uncertain macroeconomic situation, improving the inherent resilience of the new energy vehicle industry chain is the key to effectively addressing various risks and challenges, and achieving dynamic balance between high-quality industrial development and industrial chain security. Based on the basic concept of resilience and the actual situation of new energy vehicle industry chain development, this study constructs a comprehensive evaluation index system for the resilience of the new energy vehicle industry chain, which includes four dimensional first-level indicators of coping resistance, adaptive resilience, autonomous control and leading competitiveness. In addition, it is measured by combining the data related to the new energy vehicle industry chain in Changzhou City. Our study shows that the situation on the new energy vehicle industry chain is complicated, and the comprehensive evaluation index system is more favorable for evaluating its resilience level.

There are several challenges on how to attain energy efficiency while maintaining balance among factors affecting energy consumption such as power rating and temperature setpoints of cooling units, room temperature and humidity, and indoor air quality (IAQ). A real-time energy and IAQ monitoring system were installed in an educational building to profile the operational power consumption of inverter-based air condition unit (ACU) installed in each room. Polynomial curve and neural fitting regression analysis were applied to the real-time power consumption, indoor temperature and humidity, and carbon dioxide (CO2) level data. The derived models were able to provide the stabilizing indoor thermal and air conditions of the room to reach steady state ACU power consumption. These collected data and calculated parameters can be used to define rules in automating control of cooling appliances for an efficient energy utilization. The regression approaches, using real-time data, have determined the influence of indoor heat conditions and carbon dioxide levels on ACU power consumption. These parameters were utilized to establish consistent values for temperature, humidity, and carbon dioxide levels under stable settings of inverter-based air conditioning units.

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

In recent years, online review system attracts attention to assess seller-customer relations in the world of e-commerce. To address the quality concern of online review, especially incentivized ones, this study evaluates credibility and consistency based on reviews’ volume, length, and content to distinguish the impact of incentives on customer review behavior, improving review quality, and purchase decision-making. Software product reviews collected from software review websites, including Capterra, Software Advice, and GetApp undergo Exploratory Data Analysis (EDA) to reveal critical features such as cost, support, usability, and product features. The indirect impact of companies’ size, direct impact of users’ experience, and different impacts of changing situations during years on the incentive reviews’ volume are major findings of sentiment analysis. A/B testing results show a minimal to no impact of such reviews on purchasing decisions, highlighting discrepancies in credibility and consistency in volume, length, and content. Employing advanced techniques like Sentence-BERT (SBERT) and TF-IDF, the study explores semantic differences in reviews to improve recommendation systems for a more customized shopping experience. This approach seeks to establish a framework that discerns between review types and their effect on customer behavior. The findings contribute to developing more sophisticated and consistent e-commerce solutions, emphasizing the importance of authentic and reliable online reviews in influencing consumer choices.

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

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

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

Ultralight power generation equipment has high requirements for the power density, continuous operation, and transient stability of the whole machine, and there is a direct conflict between high power density design and substantial stability control in the power unit design. In order to meet the power density requirements of ultra-light power stations, three main problems need to be solved, namely engine speed oscillation and flameout in the process of load power mutation, matching of the generator and engine torque, and stabilizing the voltage waveform of the AC output end. In this paper, we proposed an exquisite control strategy for ultralight power generation systems in engines, generators, and inverters. The effectiveness and practicability of the proposed strategy are verified by both simulation and experiment. The results show that the proposed control strategy can effectively solve the instability problem of the ultralights generator set and improve the stability of the system, where the response recovery can be achieved within 0.9 seconds under the condition of total load increase or decrease, and the mismatching degree of the generator following the engine is reduced by 90%. The strategy could also guarantee long-term stable operation with high-quality electrical energy output.

Artificial intelligence (AI)-based conversational models, such as ChatGPT, Microsoft Bing, and Google Bard, emerged as valuable sources of health information for the lay individuals. However, the accuracy of information provided by these AI models remains a significant concern. This pilot study aimed to test a new tool referred to as “CLEAR”, designed to assess the quality of health information delivered by AI-based models. Tool development involved a literature review on health information quality, followed by initial establishment of the CLEAR tool comprising five items that aimed to assess the following: completeness of content in response to the prompt, lack of false information, evidence support, appropriateness, and relevance of the generated content. Each item was scored on a 5-point Likert scale from excellent to poor. Content validity was checked by expert review of the initial items. Pilot testing involved 32 healthcare professionals using the CLEAR tool to assess content on eight different health topics deliberately designed with varying qualities. The internal consistency was checked using the Cronbach α. Feedback through the pilot test resulted in language modifications to improve the clarity of the items. The final CLEAR tool was used to assess health information quality generated through four different AI-based models in five different, yet common health topics. The AI models were ChatGPT 3.5, ChatGPT 4, Bing, and Bard, and the content generated was scored by two independent raters with Cohen κ to assess the inter-rater agreement. The final five CLEAR items were: (1) Is the content sufficient? (2) Is the content accurate? (3) Is the content evidence-based? (4) Is the content clear, concise, and easy to understand? and (5) Is the content free from irrelevant information? Pilot testing using the eight different health topics revealed an acceptable internal consistency with a Cronbach α range of 0.669–0.981. The use of the final CLEAR tool yielded the following average scores: Bing (mean=24.4±0.42), ChatGPT-4 (mean=23.6±0.96), Bard (mean=21.2±1.79), and ChatGPT-3.5 (mean=20.6±5.20). The inter-rater agreement revealed the following Cohen κ values: for ChatGPT-3.5 (κ=0.875, P<.001), ChatGPT-4 (κ=0.780, P<.001), Bing (κ=0.348, P=.037), and Bard (κ=.749, P<.001). The CLEAR tool is a brief yet helpful tool that can aid to standardize testing of the quality of health information generated by the AI-based conversational models. Future studies are recommended to validate the utility of the CLEAR tool to assess the quality of the AI-generated health-related content using a larger sample across various complex health topics.

Objective: The objective of our study was to explore the potential benefits of combining moderate alcohol consumption with regular vigorous physical activity on HDL-cholesterol levels and its potential positive impact on cardiovascular health. Material and method: The study comprised two groups: group A (102 patients) who consumed 1 gram of alcohol per day, specifically red wine, and increased their exercise levels in addition to their standard medical treatment, and group B (108 patients) who adhered only to their standard medical treatment. The patients were monitored for a year, during which various clinical parameters were observed. Results:Our study showed that moderate alcohol consumption, particularly red wine, along with increased physical activity levels, was associated with enhancements in exercise tolerance and elevated levels of HDL-cholesterol. Our findings suggest the efficacy of the intervention in improving lipid profiles, with the group that consumed alcohol as part of their treatment scheme, generally experiencing more pronounced positive effects. Statistically significant differences between groups in terms of angina evolution, AMI recurrence, or arrhythmias evolution were not found. However, there were important differences in terms of EF improvement and quality of life, with the alcohol consuming group displaying greater improvements in both aspects. Conclusions:In conclusion, our study emphasizes the potential benefits of combining moderate alcohol consumption, specifically red wine, with increased physical activity levels for improving exercise tolerance and enhancing HDL-cholesterol levels. However, further research and clinical trials are essential to fully understand the mechanisms and optimize the integration of these lifestyle elements for improved cardiovascular health outcomes.

Objective: The objective of our study was to explore the potential benefits of combining moderate alcohol consumption with regular vigorous physical activity on HDL-cholesterol levels and its potential positive impact on cardiovascular health. Material and method: The study comprised two groups: group A (102 patients) who consumed 1 gram of alcohol per day, specifically red wine, and increased their exercise levels in addition to their standard medical treatment, and group B (108 patients) who adhered only to their standard medical treatment. The patients were monitored for a year, during which various clinical parameters were observed. Results:Our study showed that moderate alcohol consumption, particularly red wine, along with increased physical activity levels, was associated with enhancements in exercise tolerance and elevated levels of HDL-cholesterol. Our findings suggest the efficacy of the intervention in improving lipid profiles, with the group that consumed alcohol as part of their treatment scheme, generally experiencing more pronounced positive effects. Statistically significant differences between groups in terms of angina evolution, AMI recurrence, or arrhythmias evolution were not found. However, there were important differences in terms of EF improvement and quality of life, with the alcohol consuming group displaying greater improvements in both aspects. Conclusions:In conclusion, our study emphasizes the potential benefits of combining moderate alcohol consumption, specifically red wine, with increased physical activity levels for improving exercise tolerance and enhancing HDL-cholesterol levels. However, further research and clinical trials are essential to fully understand the mechanisms and optimize the integration of these lifestyle elements for improved cardiovascular health outcomes.

The aim of this study was to evaluate the effect of dietary supplementation with Olea europaea L. extract on the animal welfare and milk quality of lactating Italian Holstein-Friesian dairy cows at different calving orders. Cows in mid lactation phase received, for 60 days, the natural olive extract Phenofeed Dry® (500 mg/cow/day) with high antioxidant power. Hormonal and metabolic parameters were determined through ELISA assays, the milk fatty acid profile through gas chromatography, chemical-nutritional and hygienic-sanitary parameters through ultrasonic analyses. The milk lysozyme content was measured through a specific ELISA assay. The administration of the enriched feed did not alter the hormonal balance. Primiparous cows were more sensitive to the treatment and showed a better general health status compared to other calving orders. The enriched feed resulted in a reduction of saturated fatty acids (SFAs) and an increase of monounsaturated fatty acids (MUFAs) and polyunsaturated fatty acids (PUFAs), ensuring an adequate nutritional content and, above all, a significantly higher content of the antibacterial protein, lysozyme. Overall, our study demonstrate that the inclusion of natural bioactive molecules such as Olea europaea L. polyphenols contributes to improving the welfare status of dairy cows and ensuring high nutritional and functional quality of animal productions.

In the future, the pursuit of high-quality economic development and a focus on ecological environmental protection in China will inevitably result in significant conflicts between land use and ecological land use. The challenge lies in achieving sustainable high-quality development while simultaneously protecting the ecological environment, optimizing the land use structure, and promoting a harmonious relationship between humans and the land. These challenges are faced by all regions. Land use conflicts primarily occur in peri-urban areas characterized by prominent economic development and urban agglomeration. Previous studies have mainly focused on analyzing the effects of land use on habitat quality during intense urbanization. However, it is important to recognize that land pressure encompasses economic, ecological, and social aspects. To gain a comprehensive understanding of the spatial conflict of land use and the impact on habitat quality in Ankang, a city that has been advocating ecological protection for the past two decades, this study aims to objectively analyze the spatial trends in land use changes in such cities. Additionally, it aims to provide insights for the harmonious development of land use in eco-region-oriented cities. Using the SSP-RCP scenarios provided by CMIP6, this paper employs a system analysis method, PLUS model, InVEST model, and land use conflict measurement model to dynamically simulate the future habitat quality and spatial conflict patterns of land use in Ankang City. The study explores the spatial coupling effect of both factors under different scenarios. The results indicate the following:(1) Under different future shared socio-economic path scenarios, land use intensity and land conflict levels follow the order of SSP585 (high forcing scenario), SSP370 (medium to high forcing scenario), SSP245 (medium forcing scenario), and SSP126 (low forcing scenario), with intensity and conflict decreasing accordingly. (2) The overall development trend in Ankang City reveals an intensification of land use conflicts and a decrease in habitat quality. The expansion rate of construction land is increasing and exhibiting aggregation, while agricultural land area is expanding and forest land area is continuously decreasing. (3) Land use intensity exhibits a significant positive correlation with land conflict levels, while land conflict levels demonstrate a significant negative correlation with habitat quality. These findings suggest that land use has had some impact on the ecological environment, with indications of habitat degradation. Even in Ankang, where ecological development is highly valued, the city will gradually face conflicts between ecological protection and economic development in future scenarios. The study highlights that Ankang's future development space will be constrained within the context of environmental protection, leading to greater land use conflicts in urban and surrounding areas. Consequently, the quality of habitats will inevitably decline. Therefore, it is crucial to allocate sufficient space for economic development while simultaneously prioritizing ecological protection. This approach will ensure a healthy economic development trajectory and foster a harmonious relationship between humans and the land.

Existing research lacks studies that explore the impact of government fiscal support on the high-quality development of regional economy and society from the perspective of livelihood-based infrastructure construction. The investigation in this paper explores the economic and social effects of government fiscal support behavior from the perspective of livelihood infrastructure construction. On the basis of the TOPSIS-Entropy Method, this paper constructs an evaluation indicator that closely conforms to the denotation and requirements of high-quality development and then carries out empirical regressions in combination with government expenditure on people's livelihood to verify the theoretical hypothesis, whose transmission mechanism and moderating effect are further empirically tested. The results reveal that increasing government expenditure on people's livelihoods can effectively improve regional high-quality development, but the marginal improvement degree varies with different periods and locations. The mechanism test proves that the regional consumption level plays a significant part in the mediating effect, accounting for 24.27% of the total effect. Urbanization is also the critical impetus for regional high-quality development and positively moderates the promotion effect of people's livelihood fiscal expenditure. Our study presents a theoretical basis and policy inspiration for improving residents' quality of life and welfare level and improving people's livelihood in the midst of high-quality economic development.

It is well-established that plants are sessile and photoautotrophic organisms that rely on light throughout their entire life cycle. Light quality (spectral composition) is especially important as it provides energy for photosynthesis and influences signaling pathways that regulate plant devel-opment in the complex process of photomorphogenesis. During past years, significant progress has been made in the physiological and biochemical effects of light quality on crops. However, understanding how light quality modulates plant growth and development remains a complex challenge. In this review, we provide an overview of the role of light quality in regulating early development of plants, encompassing processes such as seed germination, seedling de-etiolation, and seedling establishment. These insights can be harnessed to improve production planning and crop quality by producing high-quality seedlings in plant factories and improving the theoretical framework for modern agriculture.

Natural image matting is an essential technique for image processing that enables various applications, such as image synthesis, video editing, and target tracking. However, the existing image matting methods may fail to produce satisfactory results when computing resources are limited. Sampling-based methods can reduce the dimensionality of the decision space and therefore reduce computational resources by employing different sampling strategies. While these approaches reduce computational consumption, they may miss an optimal pixel pair when the number of available high-quality pixel pairs is limited. To address this shortcoming, we propose a novel multi-criterion sampling strategy that avoids missing high-quality pixel pairs by incorporating multi-range pixel pair sampling and high-quality samples selection method. This strategy is employed to develop a multi-criterion matting algorithm via Gaussian process, which searches for the optimal pixel pair by using the Gaussian process fitting model instead of solving the original pixel pair objective function. Experimental results demonstrate that our proposed algorithm outperforms other methods even with 1% computing resources, and achieves alpha matte results comparable to those yielded by the state-of-the-art optimization algorithms.

Dental healthcare providers, staff and patients are constantly exposed to the risk of infection or cross-infection in the dental office, particularly due to the formation of biofilms within Dental Unit Waterlines (DUWLs). Good water quality, achieved with environmentally friendly means, is essential in ensuring the safe operation of the clinic. The aim of this study was to evaluate the practices and protocols used in dental offices of Metropolitan Athens in Greece with regards to water quality in DUWLs. The questionnaire about water quality was distributed to dental practitioners in 2022 and was completed by 206 dentists. Water supplied to dental units was mainly from the public network (65.0%), with 55.8% using in-office filtration. Most dentists (71.8%) do not know the active substance of the antiseptic used for the DUWLs, while 96.1% reported having an antiseptic reservoir embedded in the dental unit. Daily flushing with a small and a large amount of fluid was practiced in approximately 83% and 61% of dental offices, respectively. Dental associations should raise awareness regarding water quality and maintenance of DUWLs in dental offices, investing in lifelong learning, while implementing protocols and green strategies.

In commercial terms, Virgin Olive Oil (VOO) is considered an exceptional food of excellent sensory and nutritional quality, for its taste and genuine odour and, as well as for its bioactive compounds, of a great interest for the health. This quality can be affected by oxidative degradation, chemical as well as enzymatic (activity of oxidative endogenous enzymes from polyphenol oxidase and peroxidase olive fruit type), of essential components during extraction and conservation of VOO. In the bibliography, the reduction of oxygen during the malaxation process and the storage of the oil has been studied in different ways. However, research about the reduction of oxygen in the crushing of olive fruit, malaxation of the paste and/or both at the same time in “real extraction condition” is scarce. The reduction of oxygen has been compared to control conditions (concentration of atmospheric oxygen of 21%). Batches of 200 kg of olive fruit, Picual cultivar, were used and the following treatments were applied: Control (21% O2 Mill - 21% O2 Mixer), “IM-NM”: Inerted milling -Normal malaxation (6.5% O2 Mill-21% O2 Mixer), “NM-IM”: Normal milling-Inerted malaxation (21% O2 Mill-4 % O2 Mixer) and “IM-IM”: Inerted milling-Inerted malaxation (5.5% O2 Mill-10% O2 Mixer). The parameters of commercial quality covered by Regulation: free acidity, peroxide value and absorbency in ultra-violet (k 232 and k270) did not suffer any change in relationship to the control, the oils belong to the comercial category of “Extra virgin olive oil”. The phenolic compounds are involved in the distinctive bitter and purgent taste and, their healthy properties and their oxidative stability, increased with the downsizing amounts of oxygen regarding control and the IM-NM, NM-IM and IM-IM treatments with an average of 4, 10 and 20 %, respectively. By contrast, total volatile compounds decrease between a 10-20 % in all oxygen reduction treatments. The volatile compounds arising from lipoxygenase pathway, which are responsable for the green and fruity notes of VOO, also decreased their concentration with the treatments, between 15-20%. The results show how the reduction of oxygen in the milling and malaxation stages of olive fruit can modulate the content of phenols, volatile compounds, carotenoids and chlorophyll pigments of the VOO avoiding the degradation of compound with sensorial and nutritional interest.

Low pasture biomass production and fodder scarcity are among the major challenges affecting productivity of dairy cattle farms in Sri Lanka. As a potential solution to this, two Napier hybrid cultivars CO-5 and Sampoorna were recently introduced and a field experiment was conducted to evaluate their growth, dry matter production and nutritional composition during May to September 2020. Plant measurements and samples were collected at five harvest intervals (4, 6, 8, 10 and 12 weeks after planting), with the plant samples subjected to biomass and nutritional assessments. The number of tillers and leaf length differed (P=0.01) between the two cultivars at 4 weeks harvesting interval (HI) whilst number of leaves differed at 12 HI respectively. Dry matter yield increased (P=0.16) almost linearly whilst crude protein declined exponentially with CO-5 greater than Sampoorna (P=0.057; 9.3% vs 8.7%), with increasing harvesting intervals respectively. In-vitro Organic Matter Digestibility and In-vitro Metabolizable Energy contents were similar across weeks 4, 6 and 8 but then decreased. This study demonstrates that higher dry matter yields (12.54 t/ha) can be obtained by harvesting both cultivars at 12 HI, but from a nutritional perspective harvesting at 6 HI during Yala season of the year would be optimum for farmers.

Environmental monitoring is an important topic and serves a vibrant scientific role by revealing long-term trends that can lead to new knowledge and understanding. Globally, there is active development of photonic sensors incorporating multidisciplinary research. The ultimate objective is to develop small, low-cost, sensitive, selective, quick, durable, remote-controllable sensors that are resistant to electromagnetic interference. Different photonic sensor designs and advances in photonic frameworks have shown the possibility to realize these capabilities. In this review paper, the latest developments in the field of optical waveguide and fiber-based sensors which can serve for environmental monitoring are discussed. Several important topics such as toxic gas, water quality, indoor environment, and natural disaster monitoring are reviewed.

Rationale: The 14-3-3 protein family is known to interact with many proteins in non-cardiac cell types to regulate multiple signaling pathways, particularly those relating to energy and protein homeostasis; and the 14-3-3 network is a therapeutic target of critical metabolic and proteostatic signaling in cancer and neurological diseases. Although the heart is critically sensitive to nutrient and energy alterations, and multiple signaling pathways coordinate to maintain the cardiac cell homeostasis, neither the structure of cardiac 14-3-3 protein interactome, nor potential functional roles of 14-3-3 protein-protein interactions (PPIs) in heart has been explored. Objective: To establish the comprehensive landscape and characterize the functional role of cardiac 14-3-3 PPIs. Methods and Results: We evaluated both RNA expression and protein abundance of 14-3-3 isoforms in mouse heart, followed by co-immunoprecipitation of 14-3-3 proteins and mass spectrometry in left ventricle. We identified 52 proteins comprising the cardiac 14-3-3 interactome. Multiple bioinformatic analyses indicated that more than half of the proteins bound to 14-3-3 are related to mitochondria; and the deduced functions of the mitochondrial 14-3-3 network are to regulate cardiac ATP production via interactions with mitochondrial inner membrane proteins, especially those in mitochondrial complex I. Binding to ribosomal proteins, 14-3-3 proteins likely coordinate protein synthesis and protein quality control. Localizations of 14-3-3 proteins to mitochondria and ribosome were validated via immunofluorescence assays. The deduced function of cardiac 14-3-3 PPIs is to regulate cardiac metabolic homeostasis and proteostasis. Conclusions: Thus, the cardiac 14-3-3 interactome may be a potential therapeutic target in cardiovascular metabolic and proteostatic disease states, as it already is in cancer therapy.

A discharge mixing zone (DMZ) is a defined geographical area or volume of water in the receiving environment of a discharge where initial dilution of the effluent occurs and where exceedance of water quality criteria may be permitted. DMZs are essential to inform determination of discharge consent conditions and an important element of risk management frameworks to reduce any effects of the discharges on the environment and human health. In this review, we describe the principles and technical application of DMZs. We present an overview of the physical processes that govern the dispersion and dilution of wastewater discharges and the fate of contaminants in coastal environments and define key criteria for determining the size of DMZs. We summarize DMZ requirements in international legislation and guidance and exemplify their application to different types of discharges by means of case studies. The selected case studies illustrate different modelling tools for defining DMZs and different monitoring approaches to assess their effectiveness in achieving ecological and human health objectives.

Objectives: The aim of this study was to compare the performance of the EQ-5D-Y-3L (Y-3L) and the expanded five level version, the EQ-5D-Y-5L (Y-5L). Methods: Children/adolescents with an acute or chronic health condition and from the general population completed the Y-5L and Y-3L self-report questionnaires. Performance of the Y-5L and Y-3L was determined by comparing feasibility, redistribution of dimension responses, discriminatory power, validity, and test-retest reliability. Results. Five hundred and fifty children/adolescents completed baseline measures and 173 completed repeat measures. The ceiling effect decreased by 15% from the Y-3L to Y-5L. Informativity of dimensions improved by 0.094 on the Y-5L. There was a range of 4-9% inconsistent responses moving from the Y-3L to Y-5L. Convergent validity of the Visual Analogue Scale (VAS) and Y-3L, Y-5L dimensions was similar, weak to moderate (r_s range: 0.18 – 0.38) but similar and strong on paired Y-3L and Y-5L dimensions: Kendall Tau B (range 0.69 – 0.80) and Gamma (range 0.92 – 0.98). The Y-5L and Y-3L showed moderate to substantial agreement for test-retest reliability across dimensions and VAS scores in stable chronic health conditions and fair agreement for the general population. Conclusion: The EQ-5D-Y-5L is a valid, reliable extension of the Y-3L for children/adolescents across health conditions and healthy children/adolescents. The expanded levels reduced the ceiling effect. The relative informativity of report across dimensions increased on the Y-5L compared to the Y-3L with retention of the evenness of reporting. The convergent validity and test-retest reliability of the Y-5L was comparable to the Y-3L.

In a changing climate, extreme weather events such as heat waves will be more frequent and could affect grain weight and the quality of crops such as wheat, one of the most significant crops in terms of global food security. In this work, we characterized the response of Triticum turgidum spp. durum wheat to a short-term heat-stress (HS) treatment at transcriptomic and physiological levels during early grain filling in glasshouse experiments. We found a significant reduction in grain weight and size from HS treatment. Grain quality was also affected, showing a decrease in starch content in addition to increments in grain protein levels. Moreover, an RNA-seq analysis of durum wheat grains allowed us to identify 1590 differentially expressed genes related to photosynthesis, response to heat, and carbohydrate metabolic process. A gene regulatory network analysis of HS-responsive genes uncovered novel transcription factors (TFs) controlling the expression of genes involved in abiotic stress response and grain quality, such as a member of the DOF family predicted to regulate glycogen and starch biosynthetic processes in response to HS in grains. In summary, our results provide new insights into the extensive transcriptome reprogramming that occurs during short-term HS in durum wheat grains.

Currently, most middleware application developers have two choices when designing or implementing API services: They can either stick with REST or explore the emerging GraphQL technology. Although REST is widely considered the standard method for API development, GraphQL is believed to overcome the main drawbacks of REST, especially data fetching issues. Yet, doubts remain as there are no experimental studies with convincing results to evaluate the performance of the two services. In this paper, we propose a research methodology to evaluate the performance of REST and GraphQL API services, which includes two main contributions. The first contribution is that the performance evaluation of the two services is conducted in the real operation of a massive and intensively accessible management information system. The second contribution is the fair and independent performance evaluation results obtained for both API services. The performance evaluation was studied using basic measures of QoS, including response time, throughput, CPU load, and memory usage. The results show that REST is still faster in response time and throughput, while GraphQL is very efficient in resource utilization, i.e., CPU load and memory utilization. Therefore, GraphQL is the right choice when data requirements change frequently and resource utilization is the most important consideration. REST is used when some data is frequently accessed called by multiple requests.

The bivalve mollusk, Anadara tuberculosa (Black Shell, in Spanish Concha prieta, "CP"), is found on America's Pacific coast, where it is harvested for subsistence and commercial markets. This paper aims to diagnose the performance of the black shell's value chain. We also identify several challenges that must be addressed to improve the sustainability of the black shell fishery in Ecuador. The descriptive methodology was quantitative, with a non-experimental, field, cross-sectional, and ex post facto design. Similar questionnaires were designed, validated, and applied to each link in the production chain to collect information. The performance of the value chain was diagnosed in the dimensions of productivity, competitiveness, and quality of life, reaching a 75.1% index, a result that indicates that the value chain has a moderate to good performance level. However, the value chain can be improved if the following challenges are met: 1) Restoration of the mangrove ecosystem, 2) Promotion of low-intensity shellfish aquaculture, 3) Good sanitary management and purification, 4) Promotion of value-focused ventures, 5) Strengthening of organizations and agreements for the use and custody of mangroves, and 6) Strengthening of institutions that contribute to the advancement of these challenges.

The work addresses the problem of Power Quality (PQ) metrics (or indexes) suitable for DC grids, encompassing Low and Medium Voltage applications, including electric transports, all-electric ships and aircrafts, electric vehicles, distributed generation and microgrids, modern data centers, etc. The two main pillars on which such PQ indexes are discussed and built are: i) the physical justification, so the electric phenomena affecting DC grids and components (PV panels, fuel cells, capacitors, batteries, etc.), causing e.g. stress of materials, ageing, distortion, grid instability; ii) the existing standardization framework, pointing out desirable coverage and extension, similarity with AC grids standards, but also inconsistencies. The first point is made more clear and usable by a graphical overview of the discussed phenomena. On this basis PQ is interpreted beyond the usual low-frequency range, including thus supraharmonics and common-mode disturbance, and filling the gap with the Electromagnetic Compatibility domain. However, phenomena typical of EMC and electrical safety (such as various types of overvoltages and fast transients) are excluded. Suitable PQ indexes are then reviewed, suggesting integrations and modifications, to cover the relevant phenomena and technological progress, and to better follow the normative exigencies.

In this work, we investigate the ability of a data assimilation technique and space-borne observations to quantify and monitor changes in nitrogen oxides (NOx) emissions over North-Western Greece for the summers of 2018 and 2019. In this region, four lignite-burning power plants are located. The data assimilation technique, based on the Ensemble Kalman Filter method, is employed to combine space-borne atmospheric observations from the high spatial resolution Sentinel-5 Precursor (S5P) Tropospheric Monitoring Instrument (TROPOMI) and simulations using the LOTOS-EUROS Chemical Transport model. The Copernicus Atmosphere Monitoring Service-Regional European emissions (CAMS-REG, version 4.2) inventory based on year 2015 is used as the a priori in the simulations. Surface measurements of nitrogen dioxide (NO2) from air quality stations operating in the region are compared with the model surface NO2 output using either the a priori (base run) or the a posteriori (assimilated run) NOx emissions. The high biases found between the in situ NO2 measurements and the base run surface NO2 decrease in the assimilated run in most cases. The bias in the station near the largest power plant decreases to 2.0 μg/m3 (2.83 μg/m3) from 10.5 μg/m3 (8.46 μg/m3) in 2019 (2018 respectively). Concerning the estimated annual a posteriori NOx emissions it was found that, for the pixels hosting the two largest power plants, the assimilated run results in emissions decreased by ~40-50% for 2018 compared to 2015, whereas a larger decrease, of ~70% for both power plants, was found for 2019, after assimilating the space-born observations. For the same power plants, the European Pollutant Release and Transfer Register (E-PRTR) reports decreased emissions in 2018 and 2019 compared to 2015 (-35% and -38% in 2018, -62% and -72% in 2019), in good agreement with the estimated emissions. We further compare the a posteriori emissions to the reported energy production of the power plants during the summer of 2018 and 2019. Mean decreases of about -35% and-63% in NOx emissions are estimated for the two larger power plants in summer of 2018 and 2019, respectively, which are supported by similar decreases in the reported energy production of the power plants (~-30% and -70%, respectively).

When it comes to air pollution complaints, odours are often the most significant contributor. Sources of odour emissions range from natural to anthropogenic. Mitigation of odour can be challenging, multifaceted, site-specific, and is often confounded by its complexity—defined by existing (or non-existing) environmental laws, public ordinances, and socio-economic considerations. The objective of this paper is to review and summarize odour legislation in selected European countries (France, Germany, Austria, Hungary, United Kingdom, Spain, The Netherlands, Italy, Belgium), North America (USA and Canada), South America (Chile and Colombia), as well as Oceania (Australia and New Zealand) and Asia (Japan, China). Many countries have incorporated odour controls into their legislation. However, odour-related assessment criteria tend to be highly variable between countries, individual states, provinces and even counties and towns. Legislation ranges from (1) no specific mention in environmental legislation that regulates pollutants which are known to have an odour impact to (2) extensive details about odour source testing, odour dispersion modeling, ambient odour monitoring, (3) setback distances, (4) process operations, and (5) odour control technologies and procedures. Agricultural operations are one specific source of odour emissions in rural and suburban areas and a model example of such complexities. Management of agricultural odour emissions is important because of the dense consolidation of animal feeding operations and the advance of housing development into rural areas. Overall, there is a need for continued survey, review, development, and adjustment of odour legislation that considers sustainable development, environmental stewardship, and socio-economic realities, all of which are amenable to a just, site-specific, and sector-specific application.

A workplace sleep health promotion program was implemented in an Italian police unit from 2016 to 2017. Of the 242 police officers in the unit, 218 (90%) agreed to take part in the program. A crossover trial was made in which the police officers were divided into two groups that performed sleep health promotion activities in the first and second year, respectively. The first group of officers showed significant sleep improvements at the end of the first year, while the second group had similar or worse parameters than at baseline. At follow-up, a significant improvement in the quantity and quality of sleep was reported in both groups. Sleep improvements at follow-up were associated with a marked reduction in the frequency of accidents at work and near-misses. All sleep parameters showed a significant association with injuries and near-misses in univariate logistic regression analyses. Before the intervention, sleepiness was the best predictor of injuries (aOR 1.220; CI95% 1.044-1.426) and near-misses (aOR 1.382; CI95% 1.182-1.615). At follow-up, when sleep conditions had improved, insomnia symptoms were the most significant predictors of work accidents (aOR 13.358; CI95% 2.353-75.818). Sleep health promotion can be useful in police officers.

This work aimed to assess and characterize the air quality in what concerns particulate pollution in urban-industrial environments. The main objectives were to study the spatial variability of the deposition flux of particulate pollution identifying areas with higher deposition, associate the variability with climatological variables and with possible surrounding emitting sources. The method for collecting the deposited particles was based on the standard NF X 43-007. Sampling for particulate pollution took place between April 2015 and February 2016, through seven sampling campaigns. Maps of the spatial dispersion for the particulate pollution were obtained through statistics and geostatistics techniques. Elemental identification by scanning electron microscopy (SEM) was also used but only in two sampling campaigns. The results show that the sampling campaigns that took place during hot and dry periods, 2nd and 3rd, present higher deposition flux: 2.04 g/(m2 x month) and 1.72 g/(m2 x month), respectively. Lower deposition fluxes were registered in the 6th and 7th campaigns: 0.23 g/(m2 x month) and 0.24 g/(m2 x month), respectively. It was also observed a recurrent high deposition at specific sampling points which may be due to both the nearby road traffic and the presence of chimneys. SEM analysis allowed to associate repetitive element deposition, at the same sampling point, to the same emitting source.

An iterative outlier elimination procedure based on hypothesis testing, commonly known as Iterative Data Snooping (IDS) among geodesists, is often used for the quality control of the modern measurement systems in geodesy and surveying. The test statistic associated with IDS is the extreme normalised least-squares residual. It is well-known in the literature that critical values (quantile values) of such a test statistic cannot be derived from well-known test distributions, but must be computed numerically by means of Monte Carlo. This paper provides the first results about Monte Carlo-based critical value inserted to different scenarios of correlation between the outlier statistics. From the Monte Carlo evaluation, we compute the probabilities of correct identification, missed detection, wrong exclusion, overidentifications and statistical overlap associated with IDS in the presence of a single outlier. Based on such probability levels we obtain the Minimal Detectable Bias (MDB) and Minimal Identifiable Bias (MIB) for the case where IDS is in play. MDB and MIB are sensitivity indicators for outlier detection and identification, respectively. The results show that there are circumstances that the larger the Type I decision error (smaller critical value), the higher the rates of outlier detection, but the lower the rates of outlier identification. For that case, the larger the Type I Error, the larger the ratio between MIB and MDB. We also highlight that an outlier becomes identifiable when the contribution of the measures to the wrong exclusion rate decline simultaneously. In that case, we verify that the effect of the correlation between the outlier statistics on the wrong exclusion rates becomes insignificant from a certain outlier magnitude, which increases the probability of identification.

Real data obtained from ship in operation are processed and analyzed in this paper. The intention was to provide software which would predict ship’s fuel consumption in some future time instant. It is showed that it is possible to develop such software based on numeric fitting of known data. In order to check how well the prediction of future fuel consumption is, we used only the first half of data for obtaining prediction curve. The second part of data was used to compare different prediction curves goodness. Hence, the presented research used actually a “real future data” and forecasted future data, which are used to numerically evaluate goodness of prediction. The research is of interest for companies logistics, to provide adequate fuel for fleet when and where actually needed. It is concluded that there are several prediction functions which satisfy used statistical quality measures.

Objective: The private healthcare providers (PHCP) are believed to improve access to healthcare services in Public-Private Mix (PPM) projects, as they are considered first point of contact for healthcare. The purpose of this study was to know the satisfaction level of TB patients. Design: A questionnaire-based, cross-sectional study was carried out during November and December 2017 for 572 under-treatment patients registered with PHCPs in the PPM project. Lot quality assurance sampling technique was used to randomly select 19 districts from sample frame of 75 districts. In each selected district, data collector retrieved TB register of 8 months (Jan – Aug 2017) and systematically selected patients by fixed periodic interval. SPSS (version 24.0) was used to analyze the data. Results: Study included 53% (n=301) of males and 47% (n=271) of females, with mean age of 38 years (SD, ±18). Almost half of the participants were illiterate (51%, n=289) and 64% (n=365) were non-earning members of the family. In practice, most of the participants visit private providers (71%, n=407), including private hospital/clinic (44%) and traditional practitioners (27%; n=153). 55% of participants visited the current doctor because of clinic’s proximity to residence. 82% of the participants (n=469) were satisfied with the TB care services and 85% (n=488) said that they would recommend this clinic to others. Conclusion: PHCPs are preferred providers for individuals, which is consistent with findings of other studies. Though they are satisfied with TB care and services, interventions should be introduced to reduce the financial burden on the patient. Partnering PHCP is a way forward to ensure universal health coverage, health system strengthening and better health outcomes of the population.

For many years, the programmable positioners have been widely applied in structures of modern electro-pneumatic final control elements. The positioner consists of an electro-pneumatic transducer, embedded controller and measuring instrumentation. Electro-pneumatic transducers that are used in positioners are characterized by a relatively short mean time-to-failure. The practical and economical method of a reasonable prolongation of this time is proposed in this paper. It is principally based on assessment and minimizing the effort of the embedded controller. For this purpose, were introduced: the control value variability, mean-time and the cumulative controller's effort. The diminishing of controller effort has significant practical repercussions, because it reduces the intensity of mechanical wear of the final control element components. On the other hand, the reduction of the cumulative effort is important in the context of process economy due to limitation of the consumption of energy of compressed air supplying the final control element. Therefore, the minimization of introduced effort factors has an impact on increasing the functional safety and economics of the controlled process. As a result of the performed simulations, the recommendations regarding the selection of the structure and tuning of positioner controller were elaborated. The simulations were performed in the Matlab-Simulink environment with the use of the liquid level control system in which a phenomenological model of a final control element was deployed. It has been proven that under appropriate conditions, it is possible to extend significantly the lifetime of the final control element and simultaneously enhance the control quality factors.

For centuries, crop plants have represented the basis of the daily human diet. Among them, cereals and legumes, accumulating oils, proteins and carbohydrates in their seeds, distinctly dominate modern agronomic practice. Indeed, these plants play an essential role in the food industry and fuel production. Therefore, the seeds of crop plants are intensively studied by food chemists, biologists, biochemists, and nutritional physiologists. Accordingly, not only seed development and germination, but also age- and stress-related alterations in seed vigor, longevity, nutritional value and safety can be addressed by a broad panel of analytical, biochemical and physiological methods. Currently, functional genomics is one of the most powerful tools, giving direct access to characteristic metabolic changes, accompanying plant development, senescence and response to biotic or environmental stress. Among individual methodological platforms, proteomics represents one of the most effective ones, giving access to cellular metabolism at the level of proteins. Here we discuss the main methodological approaches employed by seed proteomics in the context of physiological changes related to seed development, ageing and response to environmental stress.

Additive manufacturing (AM) offers customization of microstructure and mechanical properties of fabricated components according to the material selected, and process parameters applied. Selective laser melting (SLM) is the commonly used technique for processing high strength aluminum alloys. Selection of SLM process parameters could control the microstructure of parts and their mechanical properties. However, the process parameters limit and defects obtained inside the as-built parts present obstacles to customized part production. This study investigates the influence of SLM process parameters on the quality of as-built Al6061 and AlSi10Mg parts according to the mutual connection between the microstructure characteristics and mechanical properties. The microstructure of both materials was characterized for different parts processed over a wide range of SLM process parameters. The optimized SLM parameters were investigated to eliminate the internal microstructure defects. The behaviour of mechanical properties of parts was presented through regression models generated from the design of experiment (DOE) analysis for the results of hardness, ultimate tensile strength, and yield strength. A comparison between the results obtained and that reported in the literature is presented to illustrate the influence of process parameters, build environment, and powder characteristics on the quality of parts produced. The results obtained from this study could help to customize the part’s quality by satisfying their design requirements in addition to reducing the as-built defects which in turn reduce the amount of the post-processing needed.

Parmigiano Reggiano cheese is one of the most appreciated and consumed food worldwide, especially in Italy, for its high content of nutrients and for its taste. However, these characteristics make this product subject to counterfeiting in different forms. In this study, a novel method based on an electronic nose has been developed in order to investigate the potentiality of this tool to distinguish rind percentage in grated Parmigiano Reggiano packages that should be lower than 18%. Different samples in terms of percentage, seasoning and rind working process were considered to tackle the problem at 360°. In parallel, GC-MS technique was used to give a name to the compounds that characterize Parmigiano and to relate them with sensors responses. Data analysis consisted of two stages: multivariate analysis (PLS) and classification made in a hierarchical way with PLS-DA ad ANNs. Results are promising in terms of correct classification of the samples. The classification rate is higher for ANNs than PLS-DA, reaching also 100% values.

The residential built form, including open space, provides the physical environment for social interaction. Understanding urban open space, including semi-public and public domains, through the lens of physical accessibility and visual permeability can potentially facilitate the building of a sense of community contributing to a better quality of life. Using an inner-city suburb in Perth, Western Australia as a case study, this research explores the importance of physical accessibility patterns and visual permeability for socialising in semi-public and public domains, such as the front yard and the residential streets. It argues that maintaining a balance between public and private inter-relationship in inner city residential neighbourhoods is important for creating and maintaining a sense of community.

Speckle noise reduction is an important area of research in the field of ultrasound image processing. Several algorithms for speckle noise characterization and analysis have been recently proposed in the area. Synthetic ultrasound images can play a key role in noise evaluation methods as they can be used to generate a variety of speckle noise models under different interpolation and sampling schemes, and can also provide valuable ground truth data for estimating the accuracy of the chosen methods. However, not much work has been done in the area of modelling synthetic ultrasound images, and in simulating speckle noise generation to get images that are as close as possible to real ultrasound images. An important aspect of simulated synthetic ultrasound images is the requirement for extensive quality assessment for ensuring that they have the texture characteristics and gray-tone features of real images. This paper presents texture feature analysis of synthetic ultrasound images using local binary patterns (LBP) and demonstrates the usefulness of a set of LBP features for image quality assessment. Experimental results presented in the paper clearly show how these features could provide an accurate quality metric that correlates very well with subjective evaluations performed by clinical experts.

'Xinomavro' (V. vinifera L.) is an important native red wine grape variety in Northern Greece, particularly in PDO (Protected Designation of Origin) regions. Despite its significance, there is limited research on the effects of pruning type and severity on 'Xinomavro' vine physiology, yield, and berry quality across diverse environmental conditions. This study aimed to address this knowledge gap and provide growers with crucial information for optimizing vineyard management practices. The study was conducted over two consecutive years (2016 and 2017) in a vineyard in Thessaloniki, Northern Greece. Four treatments ( B12:12 buds on 6 spurs; B24:24 buds on 12 spurs; M12:12 buds on 2 canes; M24:24 buds on 4 canes) combining two bud load levels (12 or 24 count nodes) and two pruning types (short spurs or long canes) were applied to 'Xinomavro' vines in complete block randomized design. The vine water status, gas exchange, canopy characteristics, yield components, and berry composition were measured. Bud load and pruning type significantly influenced vine canopy development, microclimate, and yield components. Short pruning with high bud load (B24) resulted in denser canopies and higher yields, whereas cane pruning (M12 and M24) led to more open canopies and improved berry quality indicators. Treatment effects on berry composition were inconsistent across years, but showed a tendency for higher anthocyanin and total phenol content in cane-pruned vines. This study demonstrated that pruning type (short or long fruiting units) may have a greater impact on vine growth, yield, and berry composition than bud load alone in 'Xinomavro' vines. Cane pruning appears to be a more effective strategy for achieving vine balance and potentially improving grape quality under given experimental conditions.

This paper proposes an experimental design to publish on the Internet the measurements resulting from the use of four sensors: a sensor inside a cistern to measure the level of drinking water, a sensor inside a water tank to measure the water level, a sensor to measure the water flow or pressure brought by the pipes, and another sensor to measure the water quality. Using these sensors, data was collected and published in real-time on the Internet, and at the same time, it was recorded in a database. Several tests of filling and emptying the cistern were performed. A system analyzes, makes decisions, and acts on the data collected by the sensors. Finally, experimental results demonstrated that if the cistern perceived that there was no water in the tank, it turned on the water pump to fill the tank to 100\% of its storage capacity; while this was happening, the water level in the cistern and tank, the flow of water from the piped water, and the quality of the water could be visualized on a dashboard. In short, this proposal monitors water levels and flows through the Internet of Things.

The incremental sheet forming is born as an excellent alternative to other material forming pro-cedures to deform incrementally flat metal sheets into the preferred complex three-dimensional profile. The main characteristics of this process are its versatility and cost-effectiveness; in addition, it allows for reaching greater formability, compared to conventional sheet forming processes. Re-cently, its use has been extended to polymers and composites. The following review aims to present the current state of the art of the incremental sheet forming of polycarbonate, an outstanding en-gineering plastic, starting from the first studies on the feasibility of this process applied to polymers. Attention is given to the advantages, drawbacks and main applications of the incrementally formed polycarbonate sheets, as well as the influence of the process parameters and the toolpath strategies on features like formability, forming forces, deformation and failure mechanisms, geometric accu-racy, surface quality, etc. Moreover, new hybrid forming methods for process optimization are presented. Finally, a discussion is provided on the technical challenges and research directions for incremental sheet forming of polycarbonate, and more generally thermoplastics, in the future. Therefore, this review aims to offer an extensive overview of the incremental forming of polycar-bonate sheets, useful to academic and industrial researchers who work on this topic.

This narrative review examines the crucial role of physical activity in managing long COVID, characterized by persistent symptoms such as fatigue, breathlessness, and cognitive impairments following SARS-CoV-2 infection. The methodology involved a comprehensive literature search across PubMed, EBSCO (EDS), and Google Scholar, selecting peer-reviewed articles from December 2019 focusing on long-term COVID physical activity interventions. The review highlights that tailored exercise programs, adjusted to individual health status and abilities, significantly alleviate symptoms and enhance psychological well-being. Key findings emphasize the importance of personalized exercise prescriptions due to the variability in patient responses and the need for a multidisciplinary approach in developing and monitoring interventions. Despite promising outcomes, the review identifies research gaps, including the need for long-term studies, randomized controlled trials, and deeper mechanistic insights. It suggests that standardized reporting, templates like CERT, and integrating digital health tools are essential for optimizing interventions. Overall, the review advocates including personalized physical activity programs in standard care for long COVID to improve patient outcomes and quality of life.

During 2021 and 2022 summers, we measured the total and dissolved (&lt; 0.45 mm) concentration of 25 elements in Utah Lake using Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES). Utah regulates twelve of these elements. ICP-OES sensitivity is at the ppb-level but is not the approved regulatory method. All regulations are for dissolved concentrations; except aluminum (Al) and phosphorus (P) which are for total recovery. We found total Al concentrations above allowable, but dissolved concentrations were well below allowable concentrations. We attribute high total concentrations to suspended clays. Dissolved copper (Cu) concentrations were below regulatory levels in 2021, but some samples were above regulatory levels in 2022. This could be related to the use of Cu-based algaecide treatments, or from other sources. Lead (Pb) data were inconclusive; dissolved Pb concentrations were well below the acute (1-hour average) limit, but the chronic concentration limit (4-hour average) is below the ICP-OES minimal detection limit. Arsenic (As) concentrations exhibit a seasonal trend that we attribute to groundwater inflows. This ppb-level study provides insight into regulated elements in Utah Lake previously not available due to the high sensitivity of the method and measurements of both total and dissolved concentrations.

The problem of energy poverty, when energy becomes unaffordable for some population group, is not only a problem for developing countries, but this phenomenon is appearing more and more often in European countries as well. In Europe, it is estimated that 50 to 125 million people are at risk of energy poverty. We hear more and more about energy poverty in connection with the current energy crisis and rising energy prices, but also as a result of insufficient use of renewable energy sources. Due to rising energy prices, we are increasingly hearing about deepening energy poverty in Slovakia as well. The aim of the contribution is to examine the development of energy poverty in Slovakia compared to other EU countries. The situation is studied from the view of the number of days of heating and cooling, the percentage of the population that cannot maintain adequate heat at home, the percentage of the population that has a lack of heat and the percentage of residents without enough heat. During the research, we used distribution analysis, trend analysis, analysis of variance and one-way analysis. The main results show that HDD index recorded decrease, CDD index recorded increase, and Energy poverty is most obvious in low-income group of inhabitants, having shortage of heat, when RES use contribute to mitigation of energy poverty. Solving the unfavorable situation with energy poverty is possible by increasing the share of Renewable energy sources in the gross final energy consumption for heating and cooling, primarily in residential buildings. The results provide information for policy makers in area of economic, social and environmental decision-making.

Urban air pollution is a critical global environmental issue, necessitating an understanding of the spatiotemporal characteristics and driving factors for effective environmental protection and urban planning. This study introduced an advanced air quality assessment system that integrates environmental, socio-economic, and urban layout factors, addressing gaps in traditional models that often overlook the impact of urban spatial structures. Analyzing air quality data from Beijing's main urban area (2016-2020) alongside multi-source geographic data, the research develops a comprehensive evaluation system, incorporating 14 key driving factors. Employing Geographically Weighted Regression (GWR) and Multi-scale Geographically Weighted Regression (MGWR), the study quantitatively assessed the influence and spatial heterogeneity of these factors. Findings revealed an annual improvement in air quality, with a U-shaped seasonal pattern and significant spatial clustering (Global Moran’s I = 0.922). The MGWR model, in particular, provided a superior fit over GWR, effectively capturing the spatial variability of factors. Variables such as NDVI), economic output (GDP), and humidity space adjustment capability (HSAC) showed significant positive spatial impacts on air quality, while population density (POP), temperature (TEMP), and road density (RD) exhibited negative effects. These insights enhance the understanding of air pollution dynamics and aid in refining urban planning strategies.

Power quality (PQ) plays an important role in ensuring the smooth operation of power systems. PQ disturbances may cause significant consequences, impacting the reliability and efficiency of power networks. This paper presents a comprehensive review of PQ within smart grids and the integration of renewable energy sources. Methods of detecting, classifying, optimizing, and mitigating PQ events are reviewed with providing a brief theoretical explanation for each technique. Related work done in the past two decades, was conducted, presenting a clear view of the development of research in a chronological order serving as a guide for future investigations in this field of study.

Advanced air treatment systems have the potential to reduce airborne infection risk, improve indoor air quality (IAQ) and reduce energy consumption, but few studies reported practical implementation and performance. PlasmaShield®, an advanced multi-modal HVAC-integrated system was directly compared with a standard MERV-13 system in a post-surgical pediatric healthcare setting. The evaluation entailed monitoring of multi-size airborne particles, bioaerosols and key IAQ parameters. Measurements were made of outside air, recovery room supply air and air in the occupied space for 3 days prior to, and after, installation of the PlasmaShield system. Compared with the existing arrangement, very significant reductions in particle number concentrations were observed in the occupied space, especially with virus-like submicron particles. Significant reductions in airborne culturable bacteria and fungi were observed in the supply air, with more modest reductions in the occupied space. In the case of virus-like particles, there was an 8-fold improvement in equivalent clean air, suggesting a 5-fold infection risk reduction for long range exposure. The data suggest multiple benefits of airborne particle and biaerosol reduction, with applications beyond healthcare. Long term studies are recommended to confirm the combined IAQ, health and energy benefits.

Dealing with and maintaining high-quality standards in the design and construction phases is challenging, especially for on-site construction. Issues like improper implementation of building components and poor communication can widen the gap between design specifications and actual conditions. To prevent this, particularly for energy-efficient buildings, it's vital to develop resilient, sustainable strategies. These should optimize resource use, minimize environmental impact, and enhance livability, contributing to carbon neutrality by 2050 and climate change mitigation. Traditional post-occupancy evaluations, which identify defects after construction, are impractical for addressing energy performance gaps. A new, real-time inspection approach is necessary throughout the construction process. This paper suggests an innovative guideline for prefabricated buildings, emphasizing digital 'self-instruction' and 'self-inspection'. These procedures ensure activities impacting quality adhere to specific instructions, drawings, and 3D models, incorporating relevant acceptance criteria to verify completion. This methodology, promoting alignment with planned energy-efficient features, is supported by BIM-based software and Augmented Reality (AR) tools, embodying Industry 4.0 principles. BIM and AR bridge the gap between virtual design and actual construction, improving stakeholder communication and enabling real-time monitoring and adjustments. This integration fosters accuracy and efficiency, key for energy-efficient and Nearly Zero-Energy Buildings, marking a shift towards a more precise, collaborative, and environmentally sensible construction industry.

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.

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.

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.

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.

The article discusses the formation of local electric energy systems (LEES) based on renewable energy sources (RSE) as balancing groups in the electric power system (EPS). These systems can function autonomously, providing electricity even in extreme conditions. LEES incorporate small hydroelectric, photovoltaic, and wind power plants, whose output is unstable due to varying natural conditions. To address this, energy storage systems are included to ensure stability and balance. LEES may vary significantly in terms of reliability, power losses, and quality, making it essential to choose the optimal configuration. Optimizing power supply by focusing on individual indicators is discouraged, as it may negatively affect others. To evaluate LEES performance, an integral indicator has been developed, combining the theory of Markov processes and similarity. This indicator compares actual performance with an "ideal" standard, simplifying the assessment of complex systems. It allows comparison of different transmission and distribution options without needing to evaluate all technical and economic details. The proposed integral indicator effectively reflects real operating conditions and assesses the efficiency, quality, and optimality of power supply, while remaining adaptable to partial indicators.