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.

(1) Background: Childhood immunization is vital for preventing morbidities and mortalities globally. However, rural Pakistan is facing persistent challenges, particularly after recent global health crises in gauging accurate vaccination coverage estimates. This study aimed to apply a novel Lot Quality Assurance Sampling (LQAS) methodology due to its rapid and reliable estimates of the routine immunization rates among children aged 12-23 months old in Shikarpur, Sindh, and to identify priority areas for future interventions. (2) Methods: A cross-sectional household survey design was adopted for an in-depth assessment of vaccination coverage in a previously under-studied rural context. (3) Results: Data were collected from 1,402 children aged 12-23 months across 47/49 Union Councils in Shikarpur within 141 randomly identified clusters. LQAS was innovatively employed along with GIS Mapping which provided a spatial analysis of the distribution of immunization coverage and the spot map of clusters. The weighted average for fully immunized children was 42.4% after applying Direct Adjustment Method. A steep decline in coverage for each successive vaccine dose was observed, and 39 key priority areas were identified on GIS-based plotting for intensive health interventions. Multivariate Logistic Regression Model further revealed informational gaps and fear of side effects as major barriers to achieving complete immunization. (4) Conclusions: The innovative application of LQAS and GIS Mapping in this study has provided a comprehensive glimpse of its utility in future follow-ups and similar assessments. The findings stress the critical need to tackle the foundational reasons behind the vaccination gaps, with a special focus on enhancing awareness and information dissemination in the key priority areas.

As the time passes the modification in technology world lead to the evaluation in mobile application as well. With evaluation in mobile industry it is an open challenge for software quality researcher that how to enhance software quality to meet the needs of changes? Quality assurance play a key role in differentiating good application from bed application. With the continuous evaluation of mobile application developing process should be quick and efficient to comply with user requirements and satisfaction. While the listed requirement leads to bad design choices known as antipatterns, which in turn affect the reliability of the code. A tool based method PAPRIKA is used in the proposed re-search to identify and monitor these antipatterns together with a two-step assessment model for software quality assurance and object oriented software quality matrix.

Immense challenges arise in the Quality Assurance area due to contemporary development in Internet of Things (IoT) technology. Current issues are mainly related to test coverage, test diversity, IoT Stability, Use of Cellular Networks in IoTs, IoT Devices updates, Security, Data Integration, and interoperability. In this paper, we present all those issues with suggestions for tackling those issues.

IoT is a fast growing technology that has Promising potential for shaping our future. In this fast growing world of IoT, IoT systems are released without proper testing which effect its quality and does not guarantee user satisfaction. Different testing methodologies are carried out to ensure Quality assurance of IoT before releasing it to the market. In this paper we have reviewed different testing techniques using AI and different tools to ensure Quality of IoT. In this paper we have also reviewed different IoT challenges related to its quality.

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

The main moto of this study is to examine and study on behavior of Software Quality Assurance (SQA) issues of project stakeholders in a Scrum environment and their consequences. This inductive case study identifies SQA principles relevant to Meeting User Expectations. The Stakeholders in the Scrum project having lack of Concrete Guidance on Scrum’s SQA approaches, methods, and techniques. The insufficiency of concrete guidelines in Scrum needs a management squad to develop concepts that can include implementing practices from other methodologies and wisely modifying the system structure to incorporate the practices adopted, ensuring improvement in the processes, and creating a shared ownership environment. Through explaining the incompleteness of Agile approaches with special attention to the lack of concrete instructions in Scrum, the study uses techniques to customize literature and advocate for Scrum’s versatility. The study uses strategies to adapt literature and argue for Scrum’s simplicity by illustrating the incompleteness of Agile approaches with special attention to the lack of concrete instructions in Scrum methodology.

This paper discussed the concept of quality assurance (QA) in higher education and its implications to higher education institutions (HEIs) and the possible challenges. The study evaluated literature concerning QA in Zambia and elsewhere. The findings of the study show that QA is implemented through external and internal mechanisms such as accreditation, registration, institutional auditing, and the use of external examiners, self-evaluation, and peer reviews. The QA implications to HEIs in Zambia are that there is a need for accreditation of academic programmes with the Higher Education Authority (HEA) by HEIs. Further, HEIs should establish QA units to spearhead quality issues, reactive, and introduce the use of external examiners to ensure quality. The challenges identified in the implementation of QA in HEIs include inadequate funding, infrastructure, shortage of qualified academic staff, and lack of standalone QA units in some HEIs. In this regard, it has been recommended among other things, government improve funding in public HEIs, construct infrastructure, HEIs establish QA units, and recruit and retain qualified academic staff to ensure the quality of education.

Environmental policy involving citizen science (CS) is of growing interest. In support of this open data stream, validation or quality assessment of the CS data and their appropriate usage for evidence-based policy making, needs a flexible and easily adaptable data curation process ensuring transparency. Addressing these needs, this paper describes an approach for automatic quality assurance as proposed by the Citizen OBservatory WEB (COBWEB) FP7 project. This approach is based upon a workflow composition that combines different quality controls, each belonging to seven categories or ‘pillars’. Each pillar focuses on a specific dimension in the types of reasoning algorithms for CS data qualification. These pillars attribute values to a range of quality elements belonging to three complementary quality models. Additional data from various sources, such as Earth Observation (EO) data, are often included as part of the inputs of quality controls within the pillars. However, qualified CS data can also contribute to the validation of EO data. Therefore, the question of validation can be considered as ‘two sides of the same coin’. Based on an invasive species CS study, concerning Fallopia japonica (Japanese knotweed), the paper discusses the flexibility and usefulness of qualifying CS data, either when using an EO data for the validation within the quality assurance process, or validating an EO data product that describes the risk of occurrence of the plant. Both validation paths are found to be improved by quality assurance of the CS data. Addressing the reliability of CS open data, issues and limitations of the role of quality assurance for validation, due to the quality of secondary data used within the automatic workflow, are described, e.g. error propagation, paving the route to improvements in the approach.

In the last century, statistical process control has been considered a successful methodology for monitoring the variability and stability of a process over time. The analysis of variability using functional data analysis has become widespread during the early years of the 21st century. The present study proposes the implementation of a hybrid methodology called functional process control based on the functional data analysis methodology and combines its advantages with those of statistical process control, in order to provide a tool for detecting functional deviations. The phases are: (1) stabilization of processes through the identification and elimination of special causes of functional variability; (2) improvement of the process to be controlled by minimizing the common causes of functional variability; and (3) monitoring of the processes to ensure the maintenance or addition of further improvements.

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

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.

This paper proposes a novel deterministic methodology for estimating the optimal sampling frequency (SF) of water quality monitoring systems. The proposed methodology is based on employing two-dimensional contaminant transport simulation models to determine the minimum SF considering all the potential changes in the boundary conditions of a water body. A two-dimensional contaminant transport simulation model (RMA4) was implemented to estimate the distribution patterns of the total dissolved solids (TDS) within the Al-Hammar Marsh in the southern part of Iraq for 30 cases of potential boundary conditions. Using geographical information system (GIS) tools, a spatiotemporal analysis approach was applied to the results of the RMA4 model to determine the minimum SF of the monitoring stations with an accuracy level of detectable change in TDS concentration (ALC) of 5%, 10% and 15%. The proposed methodology specified a minimum and maximum SF for each monitoring station (MS) that ranged between 12 and 33 times per year, respectively. Additionally, increasing the ALC to 10% and 15% increase the minimum SF for some MSs by approximately 18% and 21%, respectively. However, the proposed methodology includes all the potential values and cases of boundary conditions, which increases the certainty of monitoring the system and the efficiency of the SF schedule. Moreover, the proposed methodology can be effectively applied to all types of surface water resources.

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.

Data from Earth Observation (EO) satellites are increasingly used to monitor the environment, understand variability and change, inform evaluations of climate model forecasts and manage natural resources. Policy makers are progressively relying on the information derived from these datasets to make decisions on mitigating and adapting to climate change. These decisions should be evidence based, which requires confidence in derived products as well as the reference measurements used to calibrate, validate or inform product development. In support of the European Union’s Earth Observation Programmes Copernicus Climate Change Service, the Quality Assurance for Essential Climate Variables (QA4ECV) project fulfilled a gap in the delivery of climate quality satellite derived datasets by prototyping a robust, generic system for the implementation and evaluation of Quality Assurance (QA) measures for satellite-derived ECV climate data record products. The project demonstrated the QA system on six new long-term, climate quality ECV data records for surface Albedo, Leaf Area Index, FAPAR, NO₂, HCHO and CO. Provision of standardized QA information provides data users with evidence-based confidence in the products and enables judgement on the fitness-for-purpose of various ECV data products their specific applications.

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.

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

Human exposure to infectious aerosols results a transmission of diseases, such as influenza, tuberculosis, and COVID-19. Most dental procedures generate a significant number of aerosolized particles, increasing transmission risk in dental settings. Since the generation of aerosols in dentistry is unavoidable, many clinics started using intervention strategies such as area-filtration units and extraoral evacuation equipment, especially under the relatively recent constraints of the pandemics. However, the effectiveness of these devices in dental operatories has not been studied. Therefore, the dental personnel's ability to position and operate such instruments efficiently is also limited. To address these challenges, we utilized a real-time sensor network for assessment of aerosol dynamics during dental restoration and cleaning producers with and without intervention. The strategies tested during the procedures were (i) local area high-efficiency particle air (HEPA) filters and (ii) extra-oral suction device (EOSD). The study was conducted at the University of Washington School of Dentistry using a network of thirteen fixed sensors positioned within the operatory and one wearable sensor worn by the dental operator. The sensor network provides time and space-resolved particulate matter (PM) data. Three-dimensional (3D) visualization informs aerosol persistence in the operatory. It was found that area filters did not improve the overall aerosol concentration in dental offices significantly. An average of 16% decrease in PM concentration was observed when EOSD equipment was used during the procedures. The combination of real-time sensors and 3D visualization can provide dental personnel and facility mangers with actionable feedback to effectively assess aerosol transmission in medical settings and develop evidence-based intervention strategies.

Nanopore raw read accuracy has improved to over 99%, making it a potential tool for metabarcoding. For broad adoption, guidelines on quality filtering are needed to ensure reliable taxonomic unit recovery. This study aims to provide those guidelines for a fungal metabarcoding context and to apply them to a case-study of ectomycorrhizae in decaying bark of Fagus sylvatica.We introduce the eNano pipeline to test two standard metabarcoding approaches: (1) reference-based mapping leveraging the UNITE’s species hypothesis system (SH-approach) and (2) constructing 98% OTUs (OTU-approach). We evaluate these approaches using a mock and natural community. Our results demonstrate that both approaches are effective with Nanopore data. When using a reference database, we recommend strict mapping criteria rather than Phred-based filtering. For 98% OTUs, filtering reads at ≥Q25 is recommended. Our case-study reveals that the decay gradient is a primary determinant of community composition, and that specific mycorrhizal fungi colonize decaying bark. Complementing our metabarcoding results with root tip morphotypification, we identify Laccaria amethystina and Tomentella sublilacina as key ectomycorrhizae of saplings on decaying logs. These findings demonstrate that Nanopore sequencing can provide valuable ecological insights and support its broader use in fungal metabarcoding as read quality continues to improve.

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

Urban air quality is increasingly becoming a cause for concern for the health of the human population. The poor air quality is already wreaking havoc in major cities of the world, where serious health issues and reduction of average human life by a factor of years are reported. The air quality in developing countries can become worse as they undergo development. The urban air quality varies non-linearly depending upon the various factors such as land use, industrialization, waste disposal, traffic volume, etc. To address this problem, it is necessary to look at the plethora of available literature from multiple perspectives such as types and sources of pollutants, meteorology, urban mobility, urban planning and development, health care, economics, etc. In this paper, we provide a comprehensive survey of the state-of-the-art in urban air quality. We first review the fundamental background on air quality and present the emerging landscape of urban air quality. We then explore the available literature from multiple urban air quality measurement projects and provides the insights uncovered in them. We then take a look at the sources that are significantly contributing to polluting the air quality. Finally, we highlight open issues and research challenges in dealing with urban air pollution.

This study investigates the evolving corporate governance mechanisms within the context of an emerging economy. Addressing a literature gap, we analyse the influence of corporate governance and earnings quality on idiosyncratic risk in an emerging economy. In particular, this research explores the impact of corporate governance practices and earnings quality on idiosyncratic risk. For this purpose, we utilise a sample of 75 non-financial firms listed on the Pakistani equity market over nine years from 2010 to 2018. Employing the generalised method of moments, the findings of our empirical analysis reveal that firms with robust governance mechanisms and higher earnings quality experience minimal idiosyncratic risk. These outcomes provide valuable insights for standard setters, regulatory authorities, policymakers, and other stakeholders, emphasising the importance of governance mechanisms and earnings management in mitigating idiosyncratic return volatility.

Air pollution knows no boundaries, which means for a city or a region to attain clean air standards, must not only look at the emission sources within its own administrative boundary, but also at sources in the immediate vicinity and those originating from long-range transport. And there is a limit to how much area can be explored to evaluate, govern, and manage as designated airsheds for cities and larger regions. This paper discusses the need from an official airshed framework for India’s air quality management, urban airsheds designated for India’s 131 non-attainment cities under the national clean air programme, and proposes climatically and geographically appropriate regional airsheds to support long-term planning. Between 28 states, eight union territories, 36 meteorological sub-regional divisions, and six regional meteorological departments, establishing the proposed 15 regional airsheds for integrated and collaborative air quality management across India is a unique opportunity.

Image fusion is a useful tool for producing a high-resolution multispectral image to be used for land use and land cover mapping. In this study, we use nine pansharpening algorithms namely Color Normalized (CN), Gram-Schmidt (GS), Hyperspherical Color Space (HCS), High Pass Filter (HPF), Nearest-Neighbor Diffusion (NND), Principal Component Analysis (PCA), Resolution Merge (RM), Stationary Wavelet Transform (SWT), and Wavelet Resolution Merge (WRM) to fusion Worldview-3 multispectral Bands and panchromatic band. In spectral and spatial fidelity, several image quality metrics are used to evaluate the performance of pansharpening algorithms. The SWT and PCA algorithms showed better results compared to other pansharpening algorithms while GS and CN algorithms showed the worst results for the original image fusion. The effect of fusion on each band was separately investigated and according to the calculations, we found that the CoastalBlue band and the Blue band showed the best result and the NIR-1 band and NIR-2 band show the worst result for the original image fusion. In the end, we conclude that the choice of fusion method depends on the requirement of remote sensing application.

The key goal of the current study was to determine suitable areas of water pumping for drinking and agricultural harvest in Tabriz aquifer, located in East Azerbaijan province, northwest Iran. In the study area, groundwater is the key foundation of water for drinking and farming requirements. Groundwater compatibility study was conducted by analyzing Electrical conductivity (EC), Total dissolved solids (TDS), Chloride (Cl), Calcium (Ca), Magnesium (Mg), Sodium (Na), Potassium (K), Sulfate (SO4), Total hardness (TH), Bicarbonate (HCO3), pH, carbonate (CO3) and Sodium Adsorption Ratio (SAR) obtained from 39 wells in the period of 2003 to 2014. For this purpose, the Water Quality Index (WQI) and irrigation water quality (IWQ) index were utilized. The WQI index zoning exposed that the groundwater of the study area for drinking purposes is categorized as excellent, good and poor water. Most drinking water harvested for urban and rural areas are in the class of 'excellent water'. The results revealed that about 37 percent (296 km2) of groundwater has high compatibility, and 63 percent of the study area (495 km2) has average compatibility for agricultural purposes. The trend of IWQ and WQI indexes demonstrates that the groundwater is getting worse over the time.

The article "Ensuring Quality Medicine is Not a Single Event but a Combined Effort of a Pharmaceutical Company" explores the multifaceted approach required to maintain high standards in pharmaceutical manufacturing. It emphasizes that quality assurance in medicine production is not an isolated event but a continuous, integrated process involving multiple departments and stages. The article highlights the roles of research and development, rigorous clinical trials, regulatory compliance, and robust manufacturing practices in ensuring the efficacy and safety of medicines. It also discusses the importance of quality control measures, such as stringent testing protocols and regular audits, to detect and mitigate potential issues early. The collaboration between different teams within a pharmaceutical company, including scientists, engineers, and quality assurance professionals, is crucial for sustaining quality throughout the product lifecycle. Moreover, the article addresses the necessity of adhering to global standards and guidelines, such as Good Manufacturing Practices (GMP), to ensure consistency and reliability in drug production. By fostering a culture of continuous improvement and vigilance, pharmaceutical companies can effectively safeguard public health and maintain trust in their products. This holistic approach underscores that delivering quality medicine is an ongoing commitment requiring coordinated efforts across the entire organization.

With an increased interest in applications that require a clean background image, such as video surveillance, object tracking, street view imaging and location-based services on web-based maps, multiple algorithms have been developed to reconstruct a background image from cluttered scenes. Traditionally, statistical measures and existing image quality techniques have been applied for evaluating the quality of the reconstructed background images. Though these quality assessment methods have been widely used in the past, their performance in evaluating the perceived quality of the reconstructed background image has not been verified. In this work, we discuss the shortcomings in existing metrics and propose a full reference Reconstructed Background image Quality Index (RBQI) that combines color and structural information at multiple scales using a probability summation model to predict the perceived quality in the reconstructed background image given a reference image. To compare the performance of the proposed quality index with existing image quality assessment measures, we construct two different datasets consisting of reconstructed background images and corresponding subjective scores. The quality assessment measures are evaluated by correlating their objective scores with human subjective ratings. The correlation results show that the proposed RBQI outperforms all the existing approaches. Additionally, the constructed datasets and the corresponding subjective scores provide a benchmark to evaluate the performance of future metrics that are developed to evaluate the perceived quality of reconstructed background images.

Nowadays, determining the socioeconomic factors' influence on environmental quality is a crucial issue for policymakers. We aim to explore the impact of socioeconomic factors i.e., ethnic conflicts inform ethnic fragmentation, institutions quality effectiveness, and energy consumption on environmental quality by testing the various hypotheses (Pollution Halo Hypothesis, IPAT, and EKC) in 40 selected Asian countries throughout 1993-2019. We also use a set of control variables which are gross domestic product per capita, foreign direct investment inflows, and population growth to determine their impact on environmental quality. We use the Panel Quintile Regression Method of 0.25, 0.5, and 0.75 to analyze the results. We find ethnic conflict negatively affects the environmental quality at all quantiles. The institution's variables regulatory quality and rule of law negatively influence the environmental quality. Our result supports Porter's hypothesis because the effect of direct foreign investment on the amount of CO2 emissions is negative and significant at 0.25, 0.5, and 0.75 quantiles which states that foreign direct investment in the host country supports environmental quality. Furthermore, our results support the IPAT hypothesis in selected Asian countries.

The success of a software product depends on several factors. Given that different organizations and institutions use software products, the need to have a quality and desirable software according to the goals and needs of the organization makes measuring the quality of software products an important issue for most organizations and institutions. To be sure of having the right software. It is necessary to use a standard quality model to examine the features and sub-features for a detailed and principled study in the quality discussion. In this study, the quality of Word software was measured. Considering the importance of software quality and to have a good and usable software in terms of quality and measuring the quality of software during the study, experts and skilled in this field were used and the impact of each factor and quality characteristics. It was applied at different levels according to their opinion to make the result of measuring the quality of Word software more accurate and closer to reality. In this research, the quality of the software product is measured based on the fuzzy inference system in ISO standard. According to the results obtained in this study, it is understood that quality is a continuous and hierarchical concept and the quality of each part of the software at any stage of production can lead to high quality products.

A global approach towards quality management highlights the need for constructing a new body of knowledge that views the field of global quality from a systems perspective. Based on the results of field experiments, and in light of the need to develop new global quality management terminology, the current article presents several key concepts in this field, with emphasis on a systems-oriented rationale and perspective. As such, the article is an important stage in building this body of knowledge, and towards the conceptualization of key variables used in global quality management, from a systems approach that interacts with the fields of international management and strategic management.

Background Main treatment modality for spinal meningiomas (SM) is gross total resection (GTR). However, optimal timing of surgery, especially in cases with absent or mild neurological symptoms remains unclear. The aim of this study is to assess the impact of early-stage resection on neurological outcome, quality of life (QoL) and quality of care. The primary objective was a favorable neurological outcome (McCormick scale 1); Methods: We retrospectively analyzed data from patients operated on SM between 2011 and 2021. Patients with mild neurological symptoms preoperatively (McCormick scale 1 and 2) were compared to those with more severe neurological symptoms (McCormick scale 3-5). Disabilities and QoL were assessed according to validated questionnaires (SF36, ODI, NDI). Results: Age, spinal cord edema, thoracic localization, and spinal canal occupancy ratio were associated with more severe neurological symptoms (all p<.05). Patients presented with mild symptoms were associated with favorable neurological outcome (OR: 14.778 (95%CI 3.918-55.746, p<.001), which is associated with shorter hospitalization, better QoL and less disabilities (p<.05). Quality of care was comparable in both cohorts; Conclusions: Early surgical intervention of SM, before the development of severe neurological deficits, should be considered as it is associated with a favorable neurological outcome and quality of life.

Maize silage is produced to alleviate forage shortage on dairy animals, particularly during the dry season. Microorganisms play a significant role in silage fermentation and thus determine the silage quality. Therefore, modulation of microorganisms in silage may help prohibit undesired bacteria and improve silage quality. Hence, this study evaluated the effects of tannin extract as an additive on fermentative quality, aerobic stability and microbial composition of maize silage. Therefore, a mini-silo experiment of maize with five treatments was conducted for 75 days. The results showed that additives modulate silage microorganisms. In addition, tannin extract reduced certain silage bacteria while promoting others. However, this is without affecting the silage’s fermentative quality and aerobic stability. All silage fermented well with a pH below 4.2. Tannin extract improved dry matter recovery of silage while reducing silage weight loss. Furthermore, tannin extract suppressed the establishment of undesired bacteria, such as genera Dysgonomonas, Gluconacetobacter and Clostridium, while promoting desirable bacteria, such as genera Lactobacillus and Weissella, which attributed to silage quality. Therefore, it is concluded that tannins can be strategically used as silage additives to modulate microbial composition of silage and improve silage quality by promoting the dominance of desirable bacteria in silage.

Sachet water (SW) is a major source of drinking water in most Nigerian homes, thus making it a possible conveyance medium for health risks due to contamination rather than for replenishment of the body. This study collected SW from three busy neighborhoods and investigated for the presence of indicator bacteria – Escherichia coli (E. coli), Total Coliform (TC), Total Heterophilic Bacteria (THB), and Staphylococcus – and some physio-chemical parameters – total dissolved solids (TDS), pH, electrical conductivity (EC), and salinity. Multi-variable and exploratory statistical methods were applied to the results to determine correlations between bacterial contamination levels and perceived brand reputation. Bacteriological test with raw SW samples appeared too numerous to count (TNC) and thus required serial dilutions. After seven dilutions, results obtained revealed that SW brands with good reputation had no TC and E. coli and was statistically significant with groupings of other SW brands (χ2 = 12.28; p < 0.05 and χ2 = 37.96; p < 0.05) respectively. Additionally, SW brands with poor reputation had mean values of TC (19.7X10^8 cfu/ml;14X10^8 cfu/ml1.15X10^8 cfu/ml) and E.coli (18.2X10^8 cfu/ml;38.7X10^8 cfu/ml,32.4X10^8 cfu/ml) exceeding threshold value of zero set by the World Health Organization (WHO). Only one sample from poor reputation brand tested positive for Staphylococcus and was not statistically significant (χ2 =5.2191; p = 0.074). Principal Component Analysis (PCA)/ Factor Analysis (FA) revealed that most of the SW had fecal contamination in an alarming magnitude. Therefore, this study suggests that periodic cleaning of distribution lines, location specific treatment, QC and QA measures should be taken to reduce water security risk for SW consumption in the region.

Resistance spot welding is an established joining process in the production of safety-relevant components in the automotive industry. Therefore, a consecutive process monitoring is essential to meet the high-quality requirements. Artificial neural networks can be used to evaluate the process parameters and signals to ensure the individual spot weld quality. The predictive accuracy of such algorithms depends on the provided training data set and the prediction of untrained data is challenging. The aim of this paper is to investigate the extrapolation capability of the multi-layer perceptron model. That means, that the predictive performance of the model will be tested with data that clearly differs from the training data in terms of material and coating composition. Therefore, three multi-layer perceptron regression models were implemented to predict the nugget diameter from process data. The three models were able to predict the trained datasets very well. The models, which were provided with features from the dynamic resistance curve predicted the new dataset better than the model with only process parameters. This study shows the beneficial influence of the process signals on the predictive accuracy and robustness of artificial neural network algorithms. Especially, when predicting a data set from outside of the training space.

Asphalt binder requires more investigation to be accurately and precisely extracted since it is a significant procedure for quality control quality assurance (QC/QA) and subsequent binder characterization. In this research, the authors provided a hands-on experience with binder extraction to deliver recommendations concerning the sensitive steps that may affect the outcomes (extracted binder content, P_be%). Based on the extraction by the centrifuge method, two mineral matter determination methods (ashing and centrifuge) were addressed. Field cores were investigated with comparing the P_be% to the actual binder content, P_ba%. Analysis of variance (ANOVA) and Tukey Post-Hoc statistical analyses, in addition to linear least square regression analysis, were used to show the significance of difference according to 38 variant cores randomly obtained from the field segments (in-service roads) via the first two weeks from the construction date. Such cores involved reclaimed asphalt pavement (RAP), reclaimed asphalt shingles (RAS), and a wide range of additives. The two extraction methods were compared with concluding that the centrifuge method was highly recommended based on a quantitative evaluation, which delivered the same average P_ba% based on the 38 cores. Furthermore, the centrifuge method provided much saving in the experimental time (almost half the time required for the ashing method). It was found that the ashing outcomes were equal to the centrifuge outcomes with disregarding the ammonium carbonate addition. Thus, it could be recommended to reassess the ammonium carbonate addition as it might excessively compensate for fake minerals that have not been lost by the ignition oven.

: Following the phenomenal growth of and competition among coffee chain retailers, the coffee chain market has expanded substantially thanks to rising income levels, the increasing young population, and rapidly changing lifestyles. Attracting consumers’ attention and enhancing their loyalty behaviors have become very difficult for coffee chain retailers. This study seeks to understand the mechanisms through which emotions and the dedication-constraint model lead to brand loyalty and willingness to pay more to certain coffee chain retailers. Emotions and the dedication-constraint model are major factors in the research, but few studies have combined them to examine the formation of loyalty behaviors. This study synthesizes emotional responses and the dedication-constraint model to develop a theoretical model. Based on the ambivalent view of emotions, it also examines how positive and negative emotions affect the combination of brand loyalty and willingness to pay more to certain coffee chain retailers. Moreover, it identifies the antecedents of affective and calculative commitments in the context of coffee chain retailers. Our findings indicate that loyalty behaviors (dedication- and constraint-based mechanisms from brand loyalty and willingness to pay more to certain coffee chain retailers), emotional responses, and affective and calculative commitments significantly affect brand loyalty directly and indirectly through both positive and negative emotions. Furthermore, service quality, physical environment quality, and price fairness significantly affect affective commitments, while price fairness significantly affects both affective and calculative commitments. Finally, affective and calculative commitments significantly affect willingness to pay more, both directly and indirectly, through positive emotions and affect it directly through negative emotions. The results’ theoretical and managerial implications and possible future research directions are discussed.

The last decade has seen a significant growth in low-cost air quality monitoring systems (LCAQMS) adoption, mostly driven by the spatial density limitations of traditional regulatory grade networks which restrict their effectiveness in several settings. The EU's regulatory framework advise for deploying one air quality monitoring unit per roughly 170,000 people or 15 square kilometers which is insufficient for capturing high spatio-temporal variance in complex urban scenarios. Often these settings are characterized by distributed emissions in small roads subjected to intense cars traffic, house heating driven emissions and frequently subjected to canyon effects. The Air Heritage project in Portici, funded by the EU's Urban Innovative Actions (UIA) program, addressed these challenges by integrating low-cost sensors with traditional monitoring systems and engaging the community in pervasive measurement strategies. The project highlights the importance of individualized sensor calibration and frequent recalibrations to maintain accuracy. It also showcases the benefits of citizen science approaches, IoT infrastructures, AI components, and geostatistical sensor fusion algorithms for mobile and opportunistic air quality measurements. This paper reports on the lessons learned and experiences from the Air Heritage project, aiming to guide future implementations in similar contexts. By sharing these insights along with the gathered datalake, we aim to inform stakeholders, including researchers, public authorities, and citizens, about effective strategies for deploying and utilizing LCAQMS to enhance air quality monitoring and public awareness.

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

An increasingly frail population in nursing homes accentuates the need for high quality care at the end of life and better access to palliative care in this context. Implementation of palliative care and its outcomes can be monitored by using quality indicators. Therefore, we developed a quality indicator set for palliative care in nursing homes and a tailored measurement procedure using a mixed-methods design. We developed the instrument in three phases: 1) literature search, 2) interviews with experts and 3) indicator and measurement selection by expert consensus (RAND/UCLA). Second, we pilot tested and evaluated the instrument in nine nursing homes in Flanders, Belgium. After identifying 26 indicators in the literature and expert interviews, 19 of them were selected through expert consensus. Setting-specific themes were advance care planning, autonomy and communication with family. The quantitative and qualitative analyses showed the indicators were measurable, had good preliminary face validity and discriminative power and were considered useful in terms of quality monitoring according to the caregivers. The quality indicators can be used in a large implementation study and process evaluation in order to achieve continuous monitoring of the access to palliative care for all residents in nursing homes.

In addition to the traditional QoS metrics of delay, delay jitter, and packet loss probability (PLP), Quality of Experience (QoE) is now widely accepted as a numerical proxy for actual user experience. The literature has reported many mathematical mappings between QoE and QoS. These QoS parameters are measured by the network providers using sampling. There are some papers studying sampling errors in QoS measurements; however there is no account of propagation of these sampling errors to QoE evaluation. In this paper, we used industrially acquired measurements of PLP and jitter to evaluate the sampling errors and correlation in measurements. Focussing on Video-on-demand (VoD) applications, we use subjective testing and regression to map QoE metrics onto PLP and jitter. The resulting mathematical functions of QoE and theory of error propagation was used to evaluate the propagated error in QoE, and this error was represented as confidence interval. Using the guidelines of UK government for sampling, our results indicate that confidence intervals around estimated QoE in a busy hour can be between MOS=1 to MOS=5 at targeted operating point of QoS parameters. These results are a new perspective on QoE evaluation, and are of great significance to all organisations that need to estimate the QoE VoD applications precisely.

Live-streaming commerce (LSC) is a new shopping method that combines the characteristics of social commerce and e-commerce. Since the global coronavirus disease 2019 (COVID-19) outbreak, the number of branded platforms is growing rapidly, and their competition is fiercer than ever. Understanding consumer needs and improving service quality become the key issue for survival. This study aims to develop and empirically validate a multi-dimensional hierarchical model for measuring service quality on LSC platforms. A hierarchical reflective construct was proposed to capture dimensions based on literature on e-retail and social commerce service quality. The pro-posed model was rigorously tested using two waves of survey data through the partial least squares method. Results showed that the service quality of LSC is a third-order, reflective con-struct and includes five primary dimensions (the streamer’s interaction quality, physical envi-ronment, website quality, outcome quality and ordering process) and twelve sub-dimensions (trustworthiness, expertise, responsiveness, telepresence, consumption scenarios, information quality, system operation quality, fulfillment and refund/compensation, privacy/security, contact and ease of use). Findings also supported the hypothesis that service quality has a significant impact on customers’ satisfaction and their behavioral intentions. Furthermore, we tested an al-ternative model, and the results showed that the relationship between dimensions and overall assessment is reflective rather than formative. We offered directions for further research on LSC service quality and discussed managerial implications stemming from the empirical findings.

Groundwater represents a pivotal asset in conserving natural water reservoirs for potable consumption, irrigation, and diverse industrial uses. Nevertheless, human activities intertwined with industry and agriculture contribute significantly to groundwater contamination, highlighting the critical necessity to appraise water quality for safe drinking and effective irrigation. This research primarily focused on employing the Water Quality Index (WQI) to gauge water's appropriateness for these purposes. However, the generation of an accurate WQI can prove time-intensive owing to potential errors in sub-index calculations. In response to this challenge, an artificial intelligence (AI) forecasting model was devised, aiming to streamline the process while mitigating errors. The study collected 422 data samples from Mirpurkash, a city nestled in the province of Sindh, for a comprehensive exploration of the region's WQI attributes. Furthermore, the study probed into unraveling the interdependencies amidst variables in the physiochemical analysis of water. Diverse machine learning classifiers were employed for WQI prediction, with findings revealing that random forest and gradient boosting eclipsed other algorithms, achieving an accuracy rate of 99%. In close pursuit were SVM and XGBoost, registering accuracy scores of approximately 95% and 93%, respectively, while KNN and Decision Trees garnered accuracy rates of 88% and 87%, respectively. In addition to WQI prediction, the study conducted an uncertainty analysis of the models using the R-factor, providing insights into the reliability and consistency of predictions. This dual approach, combining accurate WQI prediction with uncertainty assessment, contributes to a more comprehensive understanding of water quality in Mirpurkash and enhances the reliability of decision-making processes related to groundwater utilization

Study Objectives: To (1) investigate the prevalence of sleep disorder symptoms in caregivers of children with autism spectrum disorder (ASD) and (2) the relationships between caregiver sleep problems and their health-related quality of life and family quality of life. Methods: Descriptive cross-sectional study of caregivers (N=62) of children ages 6 to 11 years old diagnosed with ASD receiving care at a regional autism research and resource center. Measurements and Results: Participants completed the Sleep Habits Questionnaire (SHQ), the Medical Outcomes Study (MOS) SF-12, and the Beach Center Family Quality of Life Scale (FQOL). Caregivers with longer sleep duration reported better mental health and better family quality of life. Caregivers who reported insomnia symptoms, non-restorative sleep, and insufficient sleep were more likely to report poorer mental health than caregivers who did not report these sleep disorder symptoms. Caregivers with obstructive sleep apnea and restless legs syndrome experienced worse physical quality of life. Conclusions: The physical and mental health of the primary caregiver is essential to the support of the child with ASD and to the functioning of the family. The study findings point to the importance of future research and interventions to enhance sleep health in order to improve quality of life for caregivers of children with ASD.

Computer systems are involved in many critical human applications today, so that a small error can lead to serious and dangerous problems. These errors can be from an error in the incorrect design of the user interface to an error in the program code. The success of a software product depends on several factors. Given that different organizations and institutions use software products, the need to have a quality and desirable Software according to the goals and needs of the organization makes measuring the quality of software products. an important issue for most organizations and institutions, To be sure of having the right software. It is necessary to use a standard quality model to examine the features and sub-features for a detailed and principled study in the quality discussion. In this study, the quality of Word software was measured by Adaptive Neural Fuzzy Inference System. In recent years, powerful systems called fuzzy inference systems on The basis of adaptive neural network (ANFIS) has been used in various sciences. Using the power of neural network training and the linguistic advantage of fuzzy systems, these types of systems have been able to realize the advantages of the two in terms of analyzing very powerful complex processes. Considering the importance of software quality and to have a good and usable software in terms of quality and measuring the quality of software during the study. It was applied at different levels to make the result of measuring the quality of Word software more accurate and closer to reality. In this research, the quality of the software product is measured based on the adaptive neural-fuzzy inference system in ISO standard. According to the results obtained in this study, it is understood that quality is a continuous and hierarchical concept and the quality of each part of the software at any stage of production can lead to high quality products.

The tiered laboratory framework for HIV viral load monitoring accommodates a range of HIV viral load testing platforms, with quality assessment critical to ensure quality patient testing. HIV plasma viral load testing is challenged by the instability of viral RNA. An approach using an RNA stabilizing buffer is described for the Xpert® HIV-1 Viral Load (Cepheid) assay and was tested in remote laboratories in South Africa. EDTA-plasma panels with known HIV viral titres were prepared in PrimeStore molecular transport medium for per-module verification and per-instrument external quality assessment. The panels were transported at ambient temperatures to 13 testing laboratories during 2017 and 2018, tested according to standard procedures and uploaded to a web portal for analysis. A total of 275 quality assessment specimens (57 verification panels and two EQA cycles) were tested. All participating laboratories met study verification criteria (n=171 specimens) with an overall concordance correlation coefficient (ρ_c) of 0.997 (95% confidence interval [CI]: 0.996 to 0.998) and a mean bias of -0.019 log cp/mL (95% CI: -0.044 to 0.063). The overall EQA ρ_c (n=104 specimens) was 0.999 (95% CI: 0.998 to 0.999), with a mean bias of 0.03 log cp/mL (95% CI: 0.02 to 0.05). These panels are suitable for use in quality monitoring of Xpert® HIV-1 VL and are applicable to laboratories in remote settings.

Groundwater is a vital resource for human welfare. However, due to various factors, groundwater pollution is one of the main environmental concerns facing. Yet, it is challenging to simulate groundwater quality dynamics due to the insufficient representation of nutrient percolation processes in the soil and Water Assessment Tool model. The objectives of this study were extending the SWAT module to predict groundwater quality. The results proved a linear relationship between observed and calculated groundwater quality considering No3 and TDS with R2, NSE and PBIAS values in the satisfied ranges, albeit underestimation and overestimation were observed due to limited data availability. These results highlight that nitrate and TDS concentrations and variability in groundwater may used as a tool in surface water quality that have to be assumed for designing adaptive management scenarios. Hence, extended SWAT model could be a powerful tool for future regional to global scale modelling of nutrient loads supporting effective surface and groundwater management.

In this article, the quality of water in the reservoirs of Lake Arpi, Lake Yerevan, Akhuryan, Azat, Aparan and Kechut was estimated with usage of the Armenian Water Quality Index. It was established that in the waters of reservoirs the the maximum permissible concentration of copper, vanadium, aluminum, chromium, manganese, iron, NH4+ and NO2- regularly increases. The following computational algorithm was used for determination of the Armenian Water Quality Index values: to determine the number of cases of MPC excess of i-substance or indicator of water –n; to estimate the total amount of cases of the maximum permissible concentration (N) – N = ∑n; to computes log2N, nlog2n and ∑nlog2n; to determine geoecological syntropy (I) and entropy (H): I = ∑ nlog2n/N and H = log2N – I. Then, Geo-Ecological Evolving Organized index index was determined: G = H/I. Further, the total amount multiplicity of MAC exceedances was estimated: (M) - M=∑m and log2M was computed. Finally, Armenian Water Quality Index was obtained: AWQI = G + 0.1log2M. It was established that the Armenian Water Qquality Index showed a linear dependence on the Water Contamination Index, the Specific Combinatory Water Quality Index, the Geo-Ecological Evolving Organized index and an inverse dependence on the Canadian Water Quality Index.

Summary Genome assembly projects have grown exponentially due to breakthroughs in sequencing technologies and assembly algorithms. Evaluating the quality of genome assemblies is critical to ensure the reliability of downstream analysis and interpretation. To fulfil this task, we have developed the AssemblyQC pipeline that performs file-format validation, contaminant checking, contiguity measurement, gene- and repeat-space completeness quantification, telomere inspection, taxonomic assignment, synteny alignment, scaffold examination through Hi-C contact-map visualisation, and assessments of completeness, consensus quality and phasing through K-mer analysis. It produces a comprehensive HTML report with method descriptions, tables, and visualisations. Availability and Implementation The pipeline uses NextFlow for workflow orchestration and adheres to the best-practice established by the nf-core community. This pipeline offers a reproducible, scalable, and portable method to assess the quality of genome assemblies – the code is available online.GitHub: https://github.com/Plant-Food-Research-Open/assemblyqc Supplementary information Pipeline usage documentation, parameter descriptions and example outputs are available on GitHub: https://github.com/Plant-Food-Research-Open/assemblyqc/tree/main/docs. A preview report is also hosted online: https://plant-food-research-open.github.io/assemblyqc

In light of growing concerns over water contamination, particularly in regions like Sindh, Pakistan, this research aimed to evaluate and map the groundwater quality in Taluka Larkana for both drinking and irrigation applications, addressing the expressed worries of the local community. A total of forty groundwater samples were collected from various sources such as hand pumps, taps, and tube wells. These samples underwent comprehensive analysis encompassing parameters including color, odor, taste, turbidity, pH, total hardness (TH), electrical conductivity (EC), and total dissolved solids (TDS), with comparisons drawn against WHO guidelines.Results indicated that taste, color, odor, and turbidity of the groundwater samples generally fell within acceptable ranges. However, EC levels varied from moderately elevated to excessively high. Notably, a significant proportion of samples (84% EC, 21% Cl, 30% Ca, 37% Mg, 22% TH, and 84% TDS) exceeded WHO-recommended thresholds.Assessment via the SPI model classified approximately 16% of samples as moderately contaminated, while 65% were deemed highly contaminated, and 19% were found unsuitable for drinking purposes. These findings underscore the pressing need for concerted efforts to address water quality issues in the region.

The objective of this work was to evaluate the blending and grinding influence over the nutritional, sensorial and sustainable aspects of coffee. To do so, a systematic review of the literature was accomplished. The database for the selection of relevant papers was the Portal de Periódicos da Capes, with remote access via CAFe. For the elaboration of the research, a chronological criterion with period restriction was used, considering the period between 2008-2022, to access all possible works related to the theme of this work. The following terms were used: blending; grinding; coffee; nutrition-al; sensorial; sustainability. To filter the searches, the association of these terms was also used by means of links and word associations. In the terminology, the Boolean operator AND was used to interconnect the terms used. Roasting degree, grinding, and amount of each coffee species impacts the nutritional and sensorial aspects of coffee. And the determination of each blending influences the sustainability of the environment, economic and social aspects of the coffee chain.

The purpose of this research is to determine if the tradeoffs that Kissick proposed among cost containment, quality, and access remain as rigidly interconnected as originally conceived in the contemporary health care context. Although many have relied on the Kissick model to advocate for health policy decisions, to our knowledge, the model has never been empirically tested. Some have called for policy makers to come to terms with the premise of the Kissick model tradeoffs, others have questioned the model given the proliferation of quality enhancing initiatives, automation, and information technology in the health care industry. One wonders whether these evolutionary changes alter or disrupt the originality of the Kissick paradigms themselves. Methods: Structural Equation Modeling (SEM) was used to evaluate the Kissick hypothetical relationships among the unobserved constructs of cost, quality, and access in hospitals for the year 2018. Hospital data were obtained from Definitive Healthcare a subscription site which contains Medicare data as well as non-Medicare data for networks, hospitals, and clinics (final n= 2,766). Results: Reporting significant net effects as defined by our chosen study variables, we find that as quality increases costs increase, as access increases quality increases, and as access increases, costs increase. Policy and Practice Implications: Our findings lend continued relevance to a balanced approach to health care policy reform efforts. Simultaneously bending the health care cost curve, increasing access to care, and advancing quality of care is as challenging now as it was when the Kissick model was originally conceived.

The Delaware River has made a marked recovery in the half-century since the adoption of the Delaware River Basin Commission (DRBC) Compact in 1961 and passage of the Federal Clean Water Act amendments during the 1970s. During the 1960s, the DRBC set a 3.5 mg/l dissolved oxygen criteria for the river based on an economic analysis that concluded a waste load abatement program designed to meet fishable water quality goals would generate significant recreation and environmental benefits. Scientists with the Delaware Estuary Program have recently called for raising the 1960s DO criteria along the Delaware River from 3.5 mg/l to 5.0 mg/l to protect anadromous American shad and Atlantic sturgeon and address the prospect of rising temperatures, sea levels, and salinity in the estuary. This research concludes through a marginal abatement cost (MAC) analysis that it would be cost effective to raise DO levels to meet a more stringent standard by prioritizing agricultural conservation and wastewater treatment investments in the Delaware River watershed to reduce 90% of the pollutant load 13.6 million kg/year of nitrogen (30 million lb/year) for $160 million at 35% of the $449 million annual cost. The annual least cost to reduce nitrogen loads and raise dissolved oxygen levels to meet more stringent water quality standards in the Delaware River totals $45 million for atmospheric NOX reduction, $130 million for wastewater treatment, $132 million for agriculture conservation, and $141 million for urban stormwater retrofitting. This 21st century least cost analysis estimates that $50 million/year is needed to reduce pollutant loads in the Delaware River to raise dissolved oxygen levels to 4.0 mg/l, $150 million/year is needed to reach 4.5 mg/l, and $449 million/year is needed to reach 5.0 mg/l.

Background: The patients with head and neck cancer often experience impaired sleep. Moreover, the treatment may negatively affect sleep quality. The aim of this observational study was to evaluate the sleep quality after treatment for head and neck cancer, and its relationship with quality of life and psychological distress. Methods: One hundred fifty-one patients who underwent treatment for head and neck cancer at our department were included in the study. Quality of life, sleep quality, risk of sleep apnea, sleepiness, pain and psychological distress were assessed by means of specific questionnaires. Results: The median follow-up was 30 months. A poor sleep quality was observed in 55.6% of cases. An association between PSQI global sleep quality and EORTC global health status was found. The DT, the HADS anxiety and the HADS depression scores were associated to PSQI global score, sleep quality, sleep latency, sleep disturbances, daytime dysfunction. Conclusions: Sleep disturbances, particularly OSA and insomnia, are frequent in HNC patients, and significantly impact their quality of life and psychological well-being. Given the effect of sleep on overall well-being, addressing sleep disorders should be a priority in the care of HNC patients.

In recent years, the High Dynamic Range (HDR) image has gained widespread popularity 1 across various domains such as security, multimedia, and biomedical fields, owing to its ability 2 to deliver an authentic visual experience. However, the extensive dynamic range and rich detail 3 in HDR images present challenges in assessing their quality. Therefore, current efforts involve 4 constructing subjective databases and proposing objective quality assessment metrics to achieve 5 efficient HDR Image Quality Assessment (IQA). Recognizing the absence of a systematic overview 6 of these approaches, this paper provides a comprehensive survey of existing HDR IQA methods. 7 Furthermore, this paper aims to serve as a valuable resource for researchers by discussing the 8 limitations of current methodologies and potential research directions in the future.

The quality of life (QOL) is an important indicator of human satisfaction and wellbeing. QOL is significantly and persistently affected for patients after a cancer diagnosis. Despite some evidence suggesting that psycho-oncologic interventions can provide lasting benefits, the inclusion of such interventions in cancer therapy is not universal. This article overviews known approaches to the evaluation of QOL in cancer patients and various interventions for improving patients’ outcomes with a focus on the Eastern European regional and specific Romanian context. With a mortality rate above and cancer care performance below the EU average and unequally distributed, Roma-nia urgently needs a national coordination program which is discussed in our review highlighting the main psychological tools needed for the assessment and its challenges towards implementing the program. In the end, we suggest some directions for future development of the psycho-oncologic approach in the context of social, policy and unexpected financial challenges the nation provides

Abstract: In Australia adoption of reduced tillage and stubble retention cropping systems to conserve soil moisture by growers has seen an increase in the prevalence of the disease Fusarium crown rot (FCR) caused by the stubble-borne fungal pathogen Fusarium pseudograminearum. Durum wheat is particularly susceptible to FCR expressing significant yield and quality losses in the presence of infection. Increasing rates of nitrogen (N) application at sowing exacerbates FCR. However, to achieve the desired grain protein and quality suited to pasta manufacture, N application is necessary and this creates a dilemma for growers. The purpose of this study was to investigate the effects of FCR infection in the presence of different N fertiliser application rates in durum wheat varieties on yield and technological quality. Two durum varieties were evaluated at the same location over two seasons (2020 and 2021). These seasons were characterised by being wetter than normal and showed different responses to FCR and N application. In general, the 2021 season showed better responses to applied N with no impact of FCR. The FCR inoculation while it resulted in significant infection, it had no impacts on yield or grain quality in 2021 while in 2020 yield was reduced and only gluten index was reduced. Jandaroi was found to hold its kernel vitreosity at all protein levels obtaining the premium grade while DBA Lillaroi did not and would suffer downgrade if N application was insufficient. However, higher N application rates needed to achieve 12% + protein saw a reduction in dough strength with Jandaroi holding its dough strength much better than DBA Lillaroi. This was related to the lower glutenin/gliadin (Gli/Glu) ratio in response to applied N at sowing in Jandaroi which helped retain kernels with high vitreousness. This suggests genetics plays an important role in a genotype response to N fertilisation and should be considered when selecting a variety where higher premium grades are desirable.

Soil quality is related to food security and human survival and development. In recent years, due to the acceleration of urbanization and the increase of abandoned land, land degradation occurs, poor topsoil quality. In this study, the minimum data set (MDS) was constructed through principal component analysis (PCA) to determine the indicator data set for evaluating topsoil quality in Tieling County, China. In addition, the soil quality index (SQI) was calculated to analyze the spatial distribution characteristics and influencing reasons of topsoil quality in Tieling County. The re-sults showed that MDS included total potassium (TK), Clay, zinc (Zn), soil organic matter (SOM), soil water content (SWC), cation exchange capacity (CEC), pH, and copper (Cu). The MDS indicators can well replace all indicators to evaluate the topsoil quality in the study area. The overall soil quality of Tieling County showed a trend of low in the east and high in the west, and gradually increased from the hilly area to the plain area. The evaluation results are consistent with field research, which can provide reference for other topsoil quality evaluation, and it also provide a basis for the formulation of soil quality improvement measures.

The coronavirus disease 2019 (COVID-19) pandemic has led to wastewater surveillance becoming an important tool for monitoring the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within communities. As a result, molecular methods, in particular reverse transcription-quantitative PCR (RT-qPCR), have been employed to generate large data sets aimed at the detection and quantification of SARS-CoV-2 in wastewater. Although RT-qPCR is rapid and sensitive, there is no standard method that fits all use cases, there are no certified quantification standards and experiments are carried out using numerous different assays, reagents, instruments, and data analysis protocols. These variations can lead to the reporting of erroneous quantitative data resulting in potentially misleading interpretations and conclusions. We have reviewed the SARS-CoV-2 wastewater surveillance literature focusing on the variability of RT-qPCR data as revealed by inconsistent standard curves and associated parameters. We find that variation in these parameters and deviations from best practices as described in The Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines suggest a lack of reproducibility and reliability in quantitative measurements of SARS-CoV-2 RNA in wastewater.

CAMx-LPiG (Comprehensive Air Quality Model with Extensions – Linear Plume in Grid) is an online hybrid model, based on the Chemistry and Transport Model (CTM) CAMx, that includes a sub-grid scale module to simulate the dispersion of linear road traffic emissions, called LPiG. LPiG is a plume in grid module specifically developed by extending the capabilities of the Lagrangian puff sub-grid model available in CAMx. The online integration of the local scale model within the Eulerian CTM allows for a multiscale simulation of air quality from the regional scale to the urban scale, preserving a coherent description of the chemical state of the atmosphere at all spatial scales and avoiding any double counting of the emissions simulated by the sub-grid module. In this work the model is presented and evaluated against measured NO2 concentrations for the city of Milan for the month of January 2017. The model is able to introduce road traffic induced gradient in NO2 concentration at sub-grid resolution. Moreover, CAMx-LPiG is shown to reduce the bias compared to CAMx stand-alone simulations.

This research addresses a gap in the literature by conducting a comprehensive analysis of patients’ level of satisfaction with dental care. Methods: By combining quantitative and qualitative survey methods with the PSQ questionnaire this study aims to augment ongoing initiatives to enhance dental patients’ experiences by painting a more comprehensive depiction of patients' level of satisfaction; Results: When asked about their overall level of satisfaction 77,1% of the patients said they received excellent services from the office personnel and 72,2% said they trust their doctors; Conclusions: Assessing patient satisfaction in the realm of dental services quality is crucial for enhancing service quality and accuracy, benefiting both patients and dentists, and ultimately improving public health.

Aiming at the problem of low pollutant concentration in the sewage treatment plant due to external water intrusion into the sewage collection system, which in turn leads to low pollutant reduction efficiency. A sewage system in Zhenjiang City is taken as an example. Analyze the situation of external water intrusion in the sewage pipe network, and determine the external water intrusion proportion based on the water quality and quantity method. First, the dry season flow rate of the sewage pipe is obtained according to the monitoring data of the flowmeter. Then, the key research areas are screened out based on the changes in the concentration of water quality characteristic factors. Furthermore, chemical oxygen demand and electrical conductivity are used as the water quality characteristic indicators to characterize shallow groundwater and river water. In addition, the proportions of groundwater and river water intrusion in the sewage pipe network are quantitatively analyzed based on the chemical mass balance equation. At the same time, the dredging detection method is used to assist in the investigation, and finally the engineering rectification of the problems found in the drainage is carried out. The results show that the water quality and quantity method can effectively identify the types of external water and analyze the proportion of external water intrusion, which is of exemplary significance for the evaluation of sewage collection systems.

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

Remote sensing methods have the potential to improve lake water quality monitoring and deci-sion-making in water management. This reviews introduces novel findings in the field of opti-cally active water quality parameters using remote sensing. It summarizes existing retrieval methods (analytical, semi-analytical, empirical, semi-empirical, and artificial intelli-gence/machine learning (AI/ML)), examines measurement methods used to determine concen-tration of specific water quality parameters, summarizes satellite systems that enable temporal data for understanding the state of the lake with focus on water quality parameters, and pro-poses enhancements for future research of lake water quality using remote sensing. As part of this review, eight optically active biological and physical water quality parameters were ana-lyzed, including chlorophyll-α (chl-α), transparency (Secchi disk depth (SDD)), colored dis-solved organic matters (CDOM), turbidity (TUR), electrical conductivity (EC), surface salinity (SS), total suspended matter (TSM), and water temperature (WT). The research proposes a shift from point-based data representation to a more reliable raster representation and encourages optimizing grid selection for in situ measurements by combining hydrodynamic model with re-mote sensing methods. This review presents a comprehensive summary of the bands, band combinations, and band equations per sensor for eight optically active water quality parameters as listed in Tables A1-A8. The review’s findings indicate that use of remotely sensed data is an effective method for estimating water quality parameters in lakes, with a significant increase in global utilization. The review highlights potential solutions and limitations to the challenges of remote sensing water quality determination in lakes.

Abstract: Self-regulated Learning has become one of educational psychology's most critical research areas. Contemporary research indicates that student creativity is crucial to the success of arts education. However, there is limited research on creativity in arts education in Self-regulated Learning. Therefore, this study aims to define the creativity characteristics that determine the quality of students’ work. This study implemented a creative competition in painting and composition for first-year undergraduates. It evaluated the characteristics of creativity during the three main phases of the task: planning, execution, and completion. We discovered through semi-open questionnaires (n=178)，and using the content analysis method. According to the competition results, the students with the highest scores in Flow, Inspiration, and Idea Generation in the Performance phase had the best quality work. In the Forethought phase, Analogical Thinking and Idea Generation worked best for most students, while in the Performance phase, Flow Sense, Idea Generation, and Idea Manipulation worked best.Data on creativity characteristics at different work phases and final quality might adequately guide and organize educational procedures. These findings can serve as a theoretical foundation for quantifying the creativity phase in Self-regulated Learning and offer arts educators a reference for creativity instruction.

Senegal central regions face rainfall deficit combined with scarcity of surface water and poor quality. Populations use groundwater for drinking and irrigation. A Groundwater assessment studiebased on 42 samples aims to determine their quality. Several parameters (TDS, TH, WQI, SAR, RSC, %N, PI, KR and MR) and ion chemistry determined . Samples exhibit an alcaline pH (7.6) and hydrochemical facies mainly Ca-Na-Mg-HCO3. The ionic dominance is Na+ ˃ Ca2+ ˃ Mg2+ ˃ K+ and HCO3- ˃ Cl- ˃ SO42- ˃ NO3- ˃ F-. From TDS and WQI index most of the groundwaters are suitable for drinking. Irrigation quality (based on SAR, %N, RSC, KR, MR) varie from excellent to good water type. Plotting chemical data (USSL salinity & Wilcox diagrams) reveals that the majority of the groundwater samples belong to the fields excellent to good and from good to permissible . Natural processes (rock weathering, mineral dissolution, evaporation and ion exchange) control groundwater quality. As the region faced a persistent rainfall deficit combine with fragile groundwater quality should alert the stakeholders. A sustainable development of the region can be faced if strong measures are planned to follow water quality evolution and quantity available for human purposes

One of the main technological and economic challenges for an engineer is designing high-quality products in manufacturing processes. Most of these processes involve a large number of variables included the setting of controllable (design) and uncontrollable (noise) variables. Robust Design (RD) method uses a collection of mathematical and statistical tools to study a large number of variables in the process with a minimum value of computational cost. Robust design method tries to make high-quality products according to customers’ viewpoints with an acceptable profit margin. This paper aims to provide a brief up-to-date review of the latest development of RD method particularly applied in manufacturing systems. The basic concepts of the quality loss function, orthogonal array, and crossed array design are explained. According to robust design approach, two classifications are presented, first for different types of factors, and second for different types of data. This classification plays an important role in determining the number of necessity replications for experiments and choose the best method for analyzing data. In addition, the combination of RD method with some other optimization methods applied in designing and optimizing of processes are discussed.

Air pollution is responsible for any adverse effects on human beings. Thermal discomfort, on the other hand, is able to overload the human body and eventually provoke health implications due to the heat imbalance. Methods: The aim of the present work is to study the behavior of two bio-climatic indexes and statistical characteristics of the air quality index for Sofia city - the capital of Bulgaria for the period 2008 - 2014. The study is based on WRF-CMAQ model system simula-tions with a spatial resolution of 1 kilometer. The air quality is estimated by the air quality index, taking into account the influence of different pollutants and the thermal conditions by two indi-ces, respectively, for hot and cold weather. Results: It was found that half of the heat and cold index categories are present in the simulations. Their distribution has some spatial features. All air quality categories are present in the domain, with dominance only of the O3 and PM10. Conclu-sions: It was found that Sofia is not so hot and air polluted place, but in some situations, people have to have some concerns when intend to be outdoors for a prolonged time.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex, multisystem, and profoundly debilitating condition, probably of multifactorial etiology. No effective approved drugs are currently available for its treatment. Several studies have proposed symptomatic treatment with melatonin and zinc supplementation in chronic illnesses; however, little is known about the synergistic effect of this treatment on fatigue-related symptoms in ME/CFS. The primary endpoint of the study was to assess the effect of oral melatonin plus zinc supplementation on fatigue in ME/CFS. Secondary measures included participants’ sleep disturbances, anxiety/depression, and health-related quality of life. A proof-of-concept, 16-week, randomized, placebo-controlled, double-blind trial was conducted in 50 ME/CFS patients assigned to receive either oral melatonin (1 mg) plus zinc (10 mg) supplementation (n = 24) or matching placebo (n = 26) once daily. Endpoint outcomes were evaluated at baseline and then reassessed at 8 and 16 weeks of treatment and 4 weeks after treatment cessation, using self-reported outcome measures. Treatment was safe and well-tolerated. The most relevant results were the significant reduction in the perception of physical fatigue in the active group at the final follow-up versus placebo (p < 0.05), and the significant improvement in the physical component summary at all follow-up visits in the experimental group. Our findings suggest that oral melatonin plus zinc supplementation for 16 weeks is safe and potentially effective in reducing fatigue and improving the quality of life in ME/CFS. This clinical study was registered on ClinicalTrials.gov (NCT03000777).

Objective Image Quality Assessment (IQA) measures are playing an increasingly important role in the evaluation of digital image quality. New IQA indices are expected to be strongly correlated with subjective observer evaluations expressed by MOS/DMOS scores. One such recently proposed index is the SuperPixel-based SIMilarity (SPSIM) index, which uses superpixel patches instead of the rectangular pixel grid.The authors in this paper have been proposed three modifications of SPSIM index. For this purpose, the color space used by SPSIM was changed and the way SPSIM determines similarity maps was modified using methods derived from the algorithm for computing the MDSI index. The third modification was a combination of the first two. These three new quality indices were used in the assessment process. The experimental results obtained on many color images from five image databases demonstrated the advantages of the proposed SPSIM modifications.

Analytical methodologies were developed based on the near infrared spectroscopy (NIR) associated with chemometric tools to predict the content of macronutrients (total carbohydrate, total protein, and total lipids) in medical food. We prepared the samples employed in this study according to a mixture design with percentual variations from 25% to +25% of macronutrients. Partial least squares (PLS) regression models were built with 70 and 30 samples as calibration and validation sets, respectively. We chose the best processing techniques and results based on the parameters of the ASTM 1655 standard. The models were used to determine these macronutrients in marketed enteral nutrition products, of three different batches, that have quality certification. The average errors in the determination of total carbohydrate, total protein, and total lipids were 1.8, 4.3, and 2.3 %, respectively. The percentages of errors found in this study suggest that the developed model may be useful for the quality control laboratory routine.

The maturation process of Arabica coffee fruits is influenced by plant endogenous and external factors. The maturation stage of the fruits affects the bean's chemical composition, which is related to coffee beverage quality. During fruit maturation, the colour of the peel changes from green to red (cherry), which indicates the harvest time and supposedly that the fruits have high quality. However, many tones of red may define fruit maturity. This work aimed to study the dynamics of soluble sugar accumulation related to fruit redness in coffee fruit tissues. We classified the ripe fruits into six ripeness classes based on the intensity of the red colour of the epicarp using a colourimeter. Total soluble sugar, sucrose and starch were analyzed in the coat (exocarp+mesocarp), coat juice (obtained by squeezing the coat), and beans. We showed that endosperm sugar dynamics do not follow changes in the coat, indicating a separate control of sugar accumulation, mainly related to sucrose, an essential component of coffee quality. Our data show that there is no transfer of sucrose and reducing sugars from the red coat to the bean.

Photoplethysmography (PPG) is widely utilized in wearable healthcare devices due to its convenient measurement capabilities. However, the unrestricted behavior of users often introduces artifacts into the PPG signal. As a result, signal processing and quality assessment play a crucial role in ensuring that the information contained in the signal can be effectively acquired and analyzed. Traditionally, researchers have discussed signal quality and processing algorithms separately, with individual algorithms developed to address specific artifacts. In this paper, we propose a quality-aware signal processing mechanism that evaluates incoming PPG signals using signal quality index (SQI) and selects the appropriate processing method based on the SQI. Unlike conventional processing approaches, our proposed mechanism recommends processing algorithms based on the quality of each signal, offering an alternative option for designing signal processing flows. Furthermore, our mechanism achieves a favorable trade-off between accuracy and energy consumption, which are the key considerations in long-term heart rate monitoring.

The objective of this work was to evaluate the roast time, weight loss and quality of coffee grain at four different roasting degrees, aiming to recognize and develop sustainable patterns to industrialize specialty coffees. Coffee (Coffea arabica L.), from eight producers, with scores between 80 and 83 from SCA classification, were used. Samples of 300 g were roasted in a cylindric rotative roaster, until the grains reached four different roasting profiles (Agtron scale 22.36, #33.64, #40.05, #59.92). Afterwards, analysis of roasting time, gas pressure, weight loss, and sensorial grades were accomplished. It was observed that samples roasted at #22.36 led to significant differences, regarding roasting time and weight loss. Furthermore, there is a significant difference at the sensorial grades of the coffee beverage. Comparing the roast degree #40.05 (standard used for specialty coffee) with the roast degree #22.36 (most used for commodities coffee), the first one has a gas consumption of 0.34 kg per coffee kg, whilst the second presented a gas consumption of 0.41 kg per coffee kg. Thus, from gas consumption, roast degree # 40.05 is the more sustainable option, along with the remaining parameters analyzed.

Cotton is the most important natural fiber cash crop, which has high commodity economic benefits and provides an important material foundation for China's construction. With the improvement of textile technology and living standard, higher requirements are put forward for raw cotton quality. Traditional cotton breeding methods need typing and selection. With the development of biotechnology and the research of genomics, genomic selection has been widely used in cotton breeding. Genomic selection is a new breeding method, which can be selected and bred by constructing a prediction model and using high-density molecular markers covering the whole genome. In this study, the application of various genomic selection models in cotton fiber quality was explored, which provided more reliable information for genetic breeding improvement in the future, thus helping to improve the efficiency of actual cotton breeding.

In the pursuit of energy efficiency and reduced environmental impact, adequate ventilation in enclosed spaces is essential. This study presents a hybrid neural network model designed for real-time monitoring and prediction of environmental variables. The system comprises two phases: An IoT hardware-software platform for data acquisition and decision-making, and a hybrid model combining short-term memory and convolutional recurrent structures. The results are promising and hold potential for integration into parallel processing AI architectures.

Pediatric interventional cardiology procedures are essential in diagnosing and treating congenital heart disease in children; however, they raise concerns about potential radiation exposure. Managing radiation doses and assessing image quality in angiographs becomes imperative for safe and effective interventions. This systematic review aims to comprehensively analyze the current understanding of physical image quality metrics relevant for characterizing X-ray systems used in fluoroscopy-guided pediatric cardiac interventional procedures, considering the main factors reported in the literature that influence this outcome. A search in Scopus and Web of Science, using relevant keywords and inclusion/exclusion criteria, yielded fourteen relevant articles published between 2000 and 2022. The physical image quality metrics reported were noise, signal-to-noise ratio, contrast, contrast-to-noise ratio, and high contrast spatial resolution. Various factors influencing image quality were investigated, such as polymethyl methacrylate thickness (often used to simulate water equivalent tissue thickness), operation mode, anti-scatter grid presence and tube voltage. Objective evaluations using these metrics ensure impartial assessments for main factors affecting image quality, improving in the characterization fluoroscopic X-ray systems, and aiding informed decisions to safeguard pediatric patients during procedures.

Asthma, like other chronic diseases, affects children prone to transitions of various aspects of their lives. The purpose of this thesis is to investigate the level quality of life of children with bronchial asthma and to what extent the disease affects them their everyday life. The literature search was conducted a review of the articles was done in Greek and English, through electronic databases PubMed, Google Scholar and Scopus. The terms and conditions their combinations used for the search were: “kids”, “children”, "pediatric asthma", "quality of life (QOL)", "health", "adolescents". The search was limited to the last five years (2015 – 2020) and finally 12 were selected articles. The most important areas negatively affected by quality of life of children with asthma are physical activity, their emotional state, school performance and sleep quality when it is connected to other factors. Important role in quality of life of these children has asthma management, disease severity and other environmental factors. Medical and nursing staff need to guide them asthmatic children and their families to have a good everyday life. Having the necessary knowledge needed for the quality-of-life health professionals should include in their medical nursing caring methods of achieving and maintaining a lifestyle that is no different than that of healthy children.

Hospital bed shortage is a worldwide concern. Beds unavailability has caused elective surgery cancellations, at our hospital peaking in spring 2016 at over 50%. This is often due to difficult patient step-down from intensive care (ICU) and high-dependency units (HDU). In our general/digestive surgery service admitting approximately 1000 patients yearly, ward rounds were run on a consultant firm basis. We report a quality improvement (ISRCTN13976096) introducing in our service a structured daily multi-disciplinary board round framework (SAFER Surgery R2G) adapted from the “SAFER patient flow bundle” and the "Red to Green days” approaches to enhance flow, comparing the previous year to 2017, when our framework was applied for 12 months.We used a Plan-Do-Study-Act (PDSA) methodology. Our intervention consisted in 1) systematic communication of the key care plan after the afternoon ward rounds to the nurse in charge; 2) 30’ 10AM Monday-to-Friday multidisciplinary board rounds, attended daily by the senior-team and weekly by hospital and site managers, revising the key care plan aiming at safe, early discharges, assessing the appropriateness of each inpatient day and tackling any cause of delay. We measured patient flow by average length of stay (LOS), ICU/HDU step-downs and operation cancellations count, monitoring safety through early 30-day readmissions. Compliance was assessed by board round attendance and staff satisfaction rate surveys.After 12 months (PDSA 2, N=1032), LOS significantly decreased from 7.2(±8.9) to 6.3(±7.4) days (p=0.003); ICU/HDU bed step-down flow increased by 9.3% from 345 to 375 (p=0.197), surgery cancellations dropped from 38 to 15 (p=0.100). 30-day re-admissions increased from 0.9% (N=9) to 1.3% (N=14)(p=0.390). Average cross-specialty attendance was 80%. Satisfaction rates were >75%, regarding enhanced teamwork and faster decisions.The SAFER Surgery R2G framework has shown an increase in patient flow in the context of an enhanced multidisciplinary approach, requiring senior staff commitment to remain sustainable.

The increasing need for effective analytical tools to evaluate beef quality has prompted the development of new procedures to improve the animal sector’s performance. In this study, three beef breeds—Thai native (TN), crossbred Brahman x Thai native (BT), and crossbred Charolais x Brahman (CB)—were compared in terms of their physicochemical and metabolic profiles. The findings demonstrated that TN beef was lighter and tougher than other beef. Beef odor was stronger in BT. In addition, CB beef was the most tender and the highest intramuscular fat content. Twenty-one different metabolites were found overall through NMR and chemometric approaches. High levels of lactate and creatine were found in all species. The primary factors contributing to the difference in OPLS-DA loading plots were acetylcholine, valine, adenine, leucine, and phosphocreatine, β-hydroxypyruvate, ethanol, adenosine diphosphate, creatine, acetylcholine, and lactate. The multivariate analysis indicated that these metabolites in beef cattle breeds could be distinguished using NMR spectroscopy. The results of this study provide valuable information on the quality and meat metabolites in different breeds. This could help in the development of a more accurate assessment of the quality of beef in future research.

IT auditing quality has been defined by results obtained in the process. Meanwhile, multiple studies have been done to enhance it therefore, it continues to be a topic interest and research so it is worth mentioning that its quality relies on trained competent auditors and experts able to develop a process correctly, adapting to clients and to manage auditing inherent risks According to results from the IT audit, low quality and security levels have been identified in terms of the human, technical and contextual factors, affecting audit quality. The objective of this investigation is to identify metrics and to determine their own corresponding factor applying an exploratory type of research. In order to achieve such aim, a targeted survey was designed and implemented at the Institute of Internal Auditors of Ecuador since they have the knowledge and expertise in the field. A factor analysis statistics technique was applied to data gathered to verify that it relates to the identified factors as dimensions are reduced, thus the most impacting metrics may assess the quality of IT audits. Analysis results yielded a mean score for each one of the assessed metrics, concluding that the technical factor is the most significative since it relates roles and task performance during the auditing process as well as control proce-dures. Finally, most auditing quality-related issues are mainly the outcome of an inferior management auditing process, therefore it is crucial that collegiate groups and professionals in the field validate the auditing process.

While maintenance dredging of port access channels is often required to maintain navigability, it can result in increased turbidity, sediment plumes, and associated reductions in water quality. Unoccupied aircraft systems (UAS, or drones) are increasingly applied to study water quality due to their high spatial and temporal resolutions. In this study, we investigated the use of drone imagery to monitor turbidity in the Morehead City Harbor, North Carolina, USA, during channel maintenance by hopper dredge. Drone flights were conducted concurrently with in-situ sampling during active dredging and post-dredging. Multispectral drone images were radiometrically calibrated, converted to reflectance and then turbidity using two separate processing methods and a single-band (red; 620nm-700nm) generic turbidity retrieval algorithm, and then compared to in-situ measurements. The method of using average reflectance to retrieve a single turbidity measurement per drone image produced agreeable results when compared to the in-situ measurements (R² = 0.84). This method was then used to generate turbidity maps and extract surface plumes. While this could be considered a limited validation, the results indicate that realistic values can be obtained from drone imagery for low and high turbidity concentrations (1-72 FNU), making drones a viable option for monitoring surface turbidity associated with dredging.

Interest in organic foods is increasing at a moment when humanity is facing a range of health challenges including the concern that some conventionally produced foods may pose possible adverse effects on human and livestock health. With the increasing human population, intensive production is increasingly trending towards high-input systems that aim to close yield gaps, increase crop yields, and develop new crop varieties with higher yield potential and tolerance to biotic and abiotic stresses, all within the context of incorporating specific traits to satisfy consumer demand. Potato (Solanum tuberosum L.) is one of the most consumed foods under different cultural diets, however its production faces some challenges related to soilborne diseases, marketable yield and quality, sugars and dry matter content of the produced tubers, tuber content in terms of nitrate, minerals, vitamins, bioactive compounds and antioxidants, and consumer appreciation regarding the sensory characteristics of tubers and processed products. Different studies have been investigating some of these challenges, with sometimes straightforward and sometimes connflicting results. This variability in research results indicates the general non-transferability of the results from one location to another under the same management practices in addition to differences in plant material. This review compares some characteristics of raw or boiled potato and processed products from potato tubers grown organically and conventionally. Ideally, such information may be of benefit in decision making by consumers in their dietary choices, by potato growers in their selection of crop management practices, and by scientists looking at potential areas for future research on potatoes.

Client or patient satisfaction is a very important indicator in determining service quality, patient satisfaction with various factors, but the main determining factor for patient satisfaction is the nurse, because nurses are medical personnel who are always near the patient and almost approaching the treatment that the client receives always involves the nurse. In it, therefore, nursing services, namely in the form of nursing care, are important to penetrate patient satisfaction. The purpose of this paper is to determine the effect of the quality of nursing services in increasing patient satisfaction. The method used in this research was a literature study which is analyzed from 25 articles searched through Google Scholar and Pubmed and selected based on indexes, namely Scopus, Sinta 1, and 2 and the topics discussed. The results showed that if the quality of service of nursing or nursing care can significantly increase patient satisfaction.

Background: There is an upsurge in the consumption of chicken meat leading to a high influx of imported frozen chicken parts into the Ghanaian markets with little information on their microbial qualities. This study examined the microbial quality of imported frozen chicken parts from three major import countries (USA, the Netherlands and Brazil) into the Kumasi Metropolis. Methods: A total of 45 chicken meat parts of 15 thighs, wings and backs from wholesale cold stores market in the Kumasi Metropolis were randomly sampled for laboratory examinations. A ten-fold serial dilution was performed on each homogenized chicken parts to determine microbiological quality using Plate Count Agar [1], MacConkey Agar (MCA), Mannitol Salt Agar (MSA) and Desoxycholate Citrate Agar (DCA) for the total viable count (TVC), total coliform count (TCC), Staphylococcus and Salmonella spp counts respectively incubated at 37oC for 48 hours. Sabouraud Dextrose Agar (SDA) was used for fungal counts. We identified bacterial and fungal isolates using appropriate laboratory and biochemical tests. Descriptive data analysis was carried using SPSS-IBM version 16. Results: Mean TVCs of 5.93, 5.98 and 6.14 log10cfu/g were recorded for frozen chicken meats from the USA, the Netherlands and Brazil respectively. Means TCCs of 6.14, 5.93 and 5.98 log10cfu/g were obtained for chicken meats from Brazil, USA and the Netherlands respectively. Staphylococcus spp. (35.4%), E. coli (26.2%), Salmonella spp. (24.6%), and Klebsiella spp. (13.8%) were isolated with Aspergillus spp (33.3%), Rhizopus spp (27.3%), Penicillin spp (24.2%), and Cladosporium spp (15.2%). Chicken thighs, backs and wings recorded 46.2%, 29.2% and 24.6% bacterial contaminants in this order. Bacterial isolates of 49.2%, 28.8% and 22.0% were recorded in frozen chicken meat products from Brazil, the Netherlands USA respectively. Conclusion: The results suggest that imported frozen chicken meats into the Ghanaian market have moderate quality with potential pathogens such as E. coli and Salmonella spp.

The PACS (Picture Archiving and Communication System) market is heterogenous with dozens of PACS providers having deployed installations in healthcare facilities. The DICOM query and retrieve interfaces provided by PACS have multiple variations, related to the implemented SOP (Service Object Pair) Class UID (Unique Identifier), transfer syntaxes, extended negotiations, matching attributes and matching types. These variations make any integration of a new DICOM consumer with a PACS complex and time consuming. As there is no collective information describing the various PACS query and retrieve capabilities, application developers and healthcare facilities lack a method to evaluate the PACS capabilities and classify its functionalities. GE designed a method to evaluate the PACS capabilities in terms of query retrieve functionalities. Our aim is to analyze several PACS in test and production environments, using our method to provide the DICOM object consumers a macroscopic knowledge of query/retrieve capabilities of PACS functionalities and its different variations. Our evaluation can also be used by PACS and VNA (Vendor Neutral Archive) developers to evaluate their query/retrieve capabilities, for quality improvement purpose.

Background: Accreditation is a qualitative assessment aimed at technical-professional quality, but above all, at organizational and measurable aspects through process and outcome checks. Method: There are few references in the literature relating to the accreditation and improvement of the quality and safety of care and treatment in the field of primary care. Clinical Governance must also be applied and certified in the field of primary care. Results: An accreditation system for general medicine is proposed based on a new dynamic model and implement that meets different requirements and assessed on the basis of indicators. Discussion: In the current Italian health system, accreditation of health structures is addressed only to public hospitals and private structures and to providers of services and services, however primary care. GPs / PLS do not have quality and safety guarantee systems or models or systems or public or private accreditation certifications with the SSR and SSN. Conclusion: Given the fundamental importance in the NHS of primary care of MG / PLS as the main and fundamental provider of services to the patient in all his socio-welfare and clinical needs, it is considered essential to think and implement an accreditation system extended to the territorial general practice as already present and in place for all affiliated and provider structures on behalf of the NHS.

Despite the fact that Wikipedia is often criticized for its poor quality, it continues to be one of the most popular knowledge base in the world. Articles in this free encyclopedia on various topics can be created and edited in about 300 different language versions independently. Our research showed that in language sensitive topics quality of information can be relatively better in the relevant language versions. However, in most cases it is difficult for the Wikipedia readers to determine the language affiliation of the described subject. Additionally, each language edition of Wikipedia can have own rules in manual assessing of the content quality. This makes automatic quality comparison of articles between various languages a challenging task. The paper presents results of relative quality and popularity assessment of over 28 million articles in 44 selected language versions. In addition, a comparative analysis of the quality and popularity of articles in some topics was conducted. The proposed method allows to find articles with information of better quality that can be used to automatically enrich other language editions of Wikipedia.

Models come in different forms: visual, arithmetic, mental, physical. The most common type of model is arguably the mental model, which people use to view and interpret the world. A model can be described as a representation of a problem or a situation – a simplified representation. The process of building or developing a model is called modeling. A model once developed by the modeller, can be ‘owned’ by a manager or decision maker. The ideal is to make the model an extension of the user’s ability to think about and analyse problems or situations. When used properly – taking into consideration its limitations – an economic model for a project can provide insight for decision makers, when making the crucial decision to approve a project. An economic model for a liquefied natural gas (LNG) project is shown as an example.

Introduction : In today’s competitive business landscape, organizations strive to maintain a highly committed workforce to enhance productivity, reduce turnover, and achieve long-term success. Organizational commitment, defined as the psychological attachment of employees to their organization, is crucial in fostering employee loyalty and engagement (Meyer & Allen, 1991). However, identifying the factors that influence organizational commitment requires a deep understanding of employee attitudes and behaviors.

The digital transformation in Industry 4.0 has revolutionized quality control paradigms, integrating advanced technologies such as augmented reality, deep learning, and computer vision systems into a new era called "Quality 4.0". This study systematically reviews how these technologies are shaping new practices in continuous quality supervision and improvement, adapting to increasingly automated and connected production environments. Through a comprehensive analysis of the literature, practical applications in various industrial sectors, from manufacturing and agriculture to the production of sweets and snacks, are highlighted. Additionally, the conceptual and detailed design of a quality control system using artificial intelligence tools is presented, focusing on the inspection of dimensions, color, weight, and labeling of MDF boxes. The proposed system demonstrates an effective integration of sensors, high-definition cameras, and deep learning algorithms, validated through tests with boxes of different sizes. The results suggest that the adoption of these technologies not only improves the accuracy and efficiency of inspections but is also essential to maintaining high-quality standards in a dynamic and competitive industrial environment.

(1) Introduction: The COVID-19 pandemic presented unique challenges for patients and healthcare providers, especially for those working with obesity and related health problems. E-health has emerged as a crucial tool for the follow-up of users undergoing bariatric surgery during this period, allowing remote monitoring of users' health status and providing access to virtual consultation with health professionals. This study aims to analyze the impact of the use of telemedicine during the COVID-19 pandemic on the results of bariatric surgery and user satisfac-tion with this follow-up. (2) Method: Observational study with retrospective data collection. The variables were divided into several groups: health data, associated comorbidities, quality of life, quality of sleep and satisfaction with telemedicine monitoring. (3) Results: Surgery significantly affected weight loss, in general more than 75% loss of excess weight. Comorbidities, like the qual-ity of life, were reversed over time, with 50% of subjects maintaining excellent levels. Although most users were satisfied with the monitoring, the variables had no relationship. (4) Conclusions: The follow-up assured by telemedicine did not alter the results of bariatric surgery, which may allow us to infer that it may be an option to consider for regular monitoring of the post-bariatric surgery process.

The water quality index (WQI) and irrigational index for groundwater were studied in the northeastern section of the Manipur Valley in northeast India. Water samples were collected in 2022 during the pre-monsoon season. To compute the water quality index for drinking water, the basic chemical parameters of total hardness, pH, electrical conductivity, total dissolved solids, Ca2+, Na+, Fe, Mg2+, Mn, Cl-, and HCO3, were used. The assessment of bacteriological quality is also done, which is crucial for overall water quality evaluation, alongside physical and chemical analyze. For determining irrigation suitability, irrigational indices such as sodium absorption ratio, sodium percentage, and magnesium hazard were calculated. WQI, %Na+, SAR, magnesium hazard, permeability Index and total hardness indicate that most water samples are harmless for irrigation and drinking purpose. They have affirmative relationships indicating that these characteristics are interdependent. Approximately 25% of the Piedmont zone groundwater is found to be unfit for agricultural and drinking usage. The encrustation of gypsum, halite, and evaporation into the Disang shares accelerate the dissolution of ions in Piedmont water, resulting in quality degradation. According to Gibbs plots, Durov Scatter Plot, and Hill Piper Trilinear Diagram of water dominated the rock-weathering process, while hydro chemical facies progressed from the beginning to the intermediate stage of Chadha's graphical representation illustrates the progression of hydro chemical processes in surface water. Therefore, proper integrated water resource management and development are required for effective water resource utilization, particularly around the Piedmont zone. To prevent a water crisis, groundwater resources must be managed sustainably. The current study also concentrated on a bibliometric examination of groundwater management and access to gauge the state of the field.

This research analyzed the impact of quality of service as perceived by Hapkido students on their exercise continuation and recommendation intentions. It also identified the measures to reduce the rate of student dropout, strengthen competitiveness, and create more efficient marketing strategies for consumer patterns that are rapidly diversifying Hapkido. A questionnaire survey method was conducted with 300 middle and high school students aged 14–19 years having Hapkido training of three months to two years in Incheon and Bucheon during March–April 2019. Frequency, factor, reliability, correlation, and standard multiple regression analyses were conducted on the surveyed data. The conclusions are as follows. First, considering the impact of service quality on exercise continuation intention, service quality positively affects reliability, personification, and perceptual openness; in terms of possibility, it positively affects typicality, personification, and perceptual openness; and in terms of reinforcement, it positively affects reliability and perceptual openness. Second, examining the impact of service quality on recommendation intention positively affects reliability, personification, and perceptual openness. Third, exercise continuation intention positively affects recommendation intention.

Resveratrol is one of the most investigated natural polyphenolic compounds and is contained in more than 70 types of plants and in red wine. The widespread interest in this polyphenol derives from its antioxidant, anti-inflammatory and anti-aging properties. Several studies have established that resveratrol regulates animal reproduction. However, the mechanisms of action and the potential therapeutic effects are still unclear. This review aims to clarify the role of resveratrol in the male and female reproductive functions, with a focus on animals of veterinary interest. In the female, resveratrol has been considered a phytoestrogen due to its capacity to modulate ovarian function and steroidogenesis via sirtuins, SIRT1, in particular. Resveratrol has also been used to enhance aged oocyte quality, and as a gametes cryo-protectant with mainly antioxidant, and anti-apoptotic effects. In the male, resveratrol enhanced testes function and spermatogenesis through activation of AMPK pathway. Furthermore, resveratrol has been supplemented to semen extenders improving the preservation of sperm quality. In conclusion, resveratrol has potentially beneficial effects for ameliorating ovarian and testes function. However, due to unclear data, further studies are necessary to consolidate these findings.

Background Increasingly, healthcare organizations are using technology for the efficient management of data. The aim of this study was to compare the data quality of digital records with the quality of the corresponding paper-based records by using data quality assessment framework. Methodology We conducted a desk review of paper-based and digital records over the study duration from April 2016 to July 2016 at six enrolled TB clinics. We input all data fields of the patient treatment (TB01) card into a spreadsheet-based template to undertake a field-to-field comparison of the shared fields between TB01 and digital data. Findings A total of 117 TB01 cards were prepared at six enrolled sites, whereas just 50% of the records (n=59; 59 out of 117 TB01 cards) were digitized. There were 1,239 comparable data fields, out of which 65% (n=803) were correctly matched between paper based and digital records. However, 35% of the data fields (n=436) had anomalies, either in paper-based records or in digital records. 1.9 data quality issues were calculated per digital patient record, whereas it was 2.1 issues per record for paper-based record. Based on the analysis of valid data quality issues, it was found that there were more data quality issues in paper-based records (n=123) than in digital records (n=110). Conclusion There were fewer data quality issues in digital records as compared to the corresponding paper-based records. Greater use of mobile data capture and continued use of the data quality assessment framework can deliver more meaningful information for decision making.

Adults’ with Intellectual Disabilities (ID) experiences on occupational participation were explored through the prism of Occupational Justice model (MOJ) aiming to shape and develop an occupation-centered model of Quality of Life (QoL). In this qualitative study participated thirteen adults with ID (N=13). A semi-structured interview based on MOJ was constructed and administered to explore perspectives on QoL, as well as injustices regarding occupational participation. The interviews were processed with QSR NVivo8 following content analysis research methodology. An Occupational – Quality of Life (O-QoL) model with an everyday occupations core component has been formed. This model includes three core O-QoL domains: (i) social well-being, (ii) emotional – physical well-being and (iii) material adequacy. Main indicators of O-QoL were the recreational occupations and social activities, while socio-environmental factors such as occupational deprivation have been identified as aggravating. In addition, specific occupations such as leisure activities, physical exercise / sports, art, video games and vocational training could also be beneficial for O-QoL. Moreover, the importance of promoting and supporting the rights of people with ID for employment, independent living and sexual expression was highlighted. The O-QoL could be a valuable conceptual framework in the field of ID, however further research for developing specialized assessment tools and Occupational Therapy interventions to promote O-QoL is needed.

With this article, impact of effluent mixed water with the quality of the Mansagar Lake has been established by evaluating the physico-chemical parameters and the heavy-metal contents experimentally. The process of calculating water quality and the metal pollution quality indices is also explained in brief with respect to selected sample locations and varied environmental conditions (Pre- and Post-Monsoon season). Distribution trends of Pearson‘s correlation factor have also been discussed to establish their relation among the physico-chemical parameters and the heavy-metal contents for varied environmental conditions. In the end, detailed discussion on observations made during this study and useful recommendations are also elaborated in details. With this article, we intend to present a document for better understanding of the water quality of this lake in view of futuristic management strategies to be adopted to maintain it heritage values.

Objectives: This study aimed to investigate and compare sleep quality between patients with chronic temporomandibular disorder and healthy controls, and to analyze the association of sleep quality with disease characteristics, obstructive sleep apnea risk factors, and excessive daytime sleepiness. Methods: Chronic temporomandibular disorder patients (n=503) and 180 age- and sex-matched healthy controls were included, who completed well-organized clinical report and answered questions on sleep quality (Pittsburgh Sleep Quality Index), sleep apnea risk factors (STOP-Bang questionnaire), and excessive daytime sleepiness (Epworth sleepiness scale). Results: Mean global Pittsburgh Sleep Quality Index scores were significantly higher in the patients (6.25±2.77) than in healthy controls (6.25±2.77) (p&lt;0.001). Poor sleep was significantly more prevalent in the patient group (56.9%) than in healthy controls (22.2%) (p&lt;0.001). Compared with healthy controls, chronic temporomandibular disorder patients had a higher likelihood of obstructive sleep apnea. (STOP-Bang total score ≥3; 7.2% vs. 16.1%; p&lt;0.01) and higher excessive daytime sleepiness (Epworth sleepiness scale score ≥10; 12.8% vs. 19.7%; p&lt;0.05). Age (odds ratio=2.551; p&lt;0.001), female sex (odds ratio=1.885; p=0.007), total Epworth sleepiness scale score (odds ratio=1.839; p=0.014), and headache attributed to temporomandibular disorder (odds ratio=1.519; p=0.049) were the most powerful predictors of poor sleep (global Pittsburgh Sleep Quality Index score ≥5) in chronic temporomandibular disorder patients. Conclusion: Chronic temporomandibular disorder patients had sleep quality impairment. Various factors, including peripheral and central factors, affect the patient's sleep quality. Therefore, in addition to sleep quality and sleep-related problems, the underlying central mechanism for poor sleep quality should be assessed when treating chronic temporomandibular disorder patients.

Most people living in Europe's cities are still exposed to levels of air pollution deemed harmful by the World Health Organization. In the modern world, air pollution is the foremost concern because of its impact in human health and economy. This strong connection appears gaining a lot of concern, driven by new installed low-cost electrochemical sensors monitoring systems. Highly accuracy, real-time monitoring, daily and yearly statistics, data access from experts or simple users, low-cost equipment and forecasting needs, enforce the market to develop new air quality monitoring systems using advanced technologies and protocols. In this study, a comparison via low-cost electrochemical sensors and of static, fixed site measurement monitoring station, is taking place in Athens, Greece, along with the data quality and Air Quality Index (AQI) including data accuracy and quality of data concerning adverse health effects due to air pollution. The findings presented in this work, relate to different flexible and affordable alternatives adopted during the evaluation and calibration of low-cost gas sensors for the monitoring. The significance of the positive results is particularly useful, especially considering the founding for interference, environmental conditions affections and air quality information including indexes and health recommendations for a specific location.

Quality of Service (QoS) metrics deal with network quantities, e.g. latency and loss, whereas Quality of Experience (QoE) provides a proxy metric for end-user experience. Many papers in the literature have proposed mappings between various QoS metrics and QoE. This paper goes further in providing analysis for QoE versus bandwidth cost. We measure QoE using the widely accepted Mean Opinion Score (MOS) rating. Our results naturally show that increasing bandwidth increases MOS. However, we extend this understanding by providing analysis for internet access scenarios, using TCP, and varying the number of TCP sources multiplexed together. For these target scenarios our analysis indicates what MOS increase you get by further expenditure on bandwidth. We anticipate that this will be of considerable value to commercial organizations responsible for bandwidth purchase and allocation.