Quality Of Guarantees Research Articles

Occurrence of metals, phthalate esters, and perfluoroalkyl substances in cellar water and their relationship with bacterial community in rural areas of China

Water cellars are traditional rainwater harvesting facilities that have been widely used in rural areas of northwest China. However, there are few reports about the water quality and health risk caused by the cellar water, especially phthalate esters (PAEs) and perfluoroalkyl substances (PFASs). This study investigated and assessed the health risks caused by the metals, PAEs, PFASs and bacterial communities in cellar water. The results showed that the turbidity and total number of bacterial colonies ranged from 4.7 to 58.5 NTU and 5–557 CFU/mL, respectively. The turbidity and total number of bacterial colonies were the main water quality problems. Due to high concentration of Tl (0.005–0.171 μg/L), the samples reached a high level of metal pollution. PAEs showed no non-carcinogenic and carcinogenic risk. The perfluorobutanoic acid (PFBA), perfluorobutanesulfonic acid (PFBS), perfluorooctanoic acid (PFOA), and perfluorooctane sulfonate (PFOS) were the main components of PFASs. PFOA and PFOS reached a moderate risk level in many cellar water samples. Moreover, Tl, Pb, As, PFBA and PFBS could change the bacterial community composition and induce the enrichment of bacterial functions related to human diseases. Besides these parameters, dissolved oxygen (DO) also affected the bacterial functions related to human diseases. Therefore, more attention should be paid to turbidity, DO, Tl, Pb, As, PFOA, PFOS, PFBA and PFBS in the cellar water. These results are meaningful for the water quality guarantee and health protection in rural areas of China.

Natural hazards international rescue response mechanism and development trends under UN framework.

The international rescue response to natural hazards, which has frequently drawn the attention of the international community, is a very important part of the international humanitarian assistance system. This paper focuses on the international rescue response mechanism, which is under the United Nations (UN) framework, and trends in its devel-opment. Referencing the international rescue response mechanism, this paper analyzes the overall characteristics of the humanitarian response mechanism under the UN framework, and its main components, basic procedures, quality guarantee, and support of the international rescue response mechanism. In view of the international rescue develop-ment, this paper reviews the development history and the strategic plan from 2021 to 2026. From the authors' point of view, in the next development period, the international rescue community should pay more attention on building Urban Search and Rescue team's capacity at different levels and standards, ready to respond to different kinds of disasters with flexible modules, establishing deeper and more extensive partnerships during the preparedness phase. We hope to provide a foundation for broader and deeper discussions in this field.

A Carrying Method for 5G Network Slicing in Smart Grid Communication Services Based on Neural Network

When applying 5G network slicing technology, the operator’s network resources in the form of mutually isolated logical network slices provide specific service requirements and quality of service guarantees for smart grid communication services. In the face of the new situation of 5G, which comprises the surge in demand for smart grid communication services and service types, as well as the digital and intelligent development of communication networks, it is even more important to provide a self-intelligent resource allocation and carrying method when slicing resources are allocated. To this end, a carrying method based on a neural network is proposed. The objective is to establish a hierarchical scheduling system for smart grid communication services at the power smart gate-way at the edge, where intelligent classification matching of smart grid communication services to (i) adapt to the characteristics of 5G network slicing and (ii) dynamic prediction of traffic in the slicing network are both realized. This hierarchical scheduling system extracts the data features of the services and encodes the data through a one-dimensional Convolutional Neural Network (1D CNN) in order to achieve intelligent classification and matching of smart grid communication services. This system also combines with Bidirectional Long Short-Term Memory Neural Network (BILSTM) in order to achieve a dynamic prediction of time-series based traffic in the slicing network. The simulation results validate the feasibility of a service classification model based on a 1D CNN and a traffic prediction model based on BILSTM for smart grid communication services.

A comprehensive research on wear resistance of GH4169 superalloy in longitudinal-torsional ultrasonic vibration side milling with tool wear and surface quality

To improve the service and machining performance of the workpiece, the tool wear mechanisms, surface machining quality, and wear resistance in conventional side milling (CSM) and longitudinal-torsional ultrasonic vibration side milling (LTUVSM) of GH4169 superalloy at different cutting lengths are investigated systematically. Tool wear mechanisms are revealed and the correlation between machined surface quality with tool wear is analyzed correspondingly. Tool wear patterns mainly include adhesive wear, diffusion wear, abrasive wear, and chipping sticking. Better surface quality is achieved in LTUVSM due to a maximum reduction of flank wear bandwidth and wear rate by 71.9% and 71.5%, respectively, compared to CSM. The friction coefficient, initial wear stage time, and wear volume of dry sliding wear were measured to evaluate the workpiece wear resistance. The maximum reductions in friction coefficient and wear volume in LTUVSM are 18.2% and 15.8% compared to CSM. The regular ultrasonic vibration textures suppress the friction and the growth of contact nodes in the contact area, decreasing the degree of surface wear, which is demonstrated by a 38.8% increase in initial wear stage time compared to CSM. In conclusion, the workpiece in LTUVSM exhibits higher wear resistance because of the improvement of tool wear and the guarantee of surface quality.

Reverse Maximum Inner Product Search: Formulation, Algorithms, and Analysis

The maximum inner product search (MIPS), which finds the item with the highest inner product with a given query user, is an essential problem in the recommendation field. Usually e-commerce companies face situations where they want to promote and sell new or discounted items. In these situations, we have to consider the following questions: Who is interested in the items, and how do we find them? This article answers this question by addressing a new problem called reverse maximum inner product search (reverse MIPS). Given a query vector and two sets of vectors (user vectors and item vectors), the problem of reverse MIPS finds a set of user vectors whose inner product with the query vector is the maximum among the query and item vectors. Although the importance of this problem is clear, its straightforward implementation incurs a computationally expensive cost. We therefore propose Simpfer, a simple, fast, and exact algorithm for reverse MIPS. In an offline phase, Simpfer builds a simple index that maintains a lower bound of the maximum inner product. By exploiting this index, Simpfer judges whether the query vector can have the maximum inner product or not, for a given user vector, in a constant time. Our index enables filtering user vectors, which cannot have the maximum inner product with the query vector, in a batch. We theoretically demonstrate that Simpfer outperforms baselines employing state-of-the-art MIPS techniques. In addition, we answer two new research questions. Can approximation algorithms further improve reverse MIPS processing? Is there an exact algorithm that is faster than Simpfer? For the former, we show that approximation with quality guarantee provides a little speed-up. For the latter, we propose Simpfer++, a theoretically and practically faster algorithm than Simpfer. Our extensive experiments on real datasets show that Simpfer is at least two orders of magnitude faster than the baselines, and Simpfer++ further improves the online processing time.

Physics-informed hierarchical data-driven predictive control for building HVAC systems to achieve energy and health nexus

Buildings consume 74% of US electricity and 40% of primary energy use. However, 15% of the energy was wasted due to bad controls. Many research studies have demonstrated that model predictive control strategies could provide significant energy savings, but the lack of a scalable building dynamic model impeded the large-scale implementation of predictive control strategies. Moreover, many predictive control strategies lacked the consideration of indoor air quality. Therefore, in this research study, we proposed a novel physics-informed input convex neural network (PINN) to predict indoor environmental dynamics with 6 h ahead. The model sanity check results showed that the proposed PINN had physically consistent behavior to different control inputs. Then, the PINN is used to design a hierarchical data-driven predictive control (HDDPC) strategy to minimize both the space cooling load and airside coil load. Three different case studies were simulated to evaluate the proposed control strategy comprehensively: a) maintaining a similar indoor temperature profile as the measurement to evaluate energy reduction potential by the HDDPC; b) evaluating the impact of the proposed weather forecast models on the HDDPC performance by comparing the case with perfectly accurate weather information and the case with forecasted weather information. Results indicated that the hierarchical data-driven predictive control strategy with weather forecasting had a similar performance with measured weather inputs. On average, the HDDPC strategy could reduce more than 35% of total cooling energy and 70% of total airside coil energy with the guarantee of indoor thermal comfort and air quality.

Method for Continuous Integration and Deployment Using a Pipeline Generator for Agile Software Projects

Lately, the software development industry is going through a slow but real transformation. Software is increasingly a part of everything, and, software developers, are trying to cope with this exploding demand through more automation. The pipelining technique of continuous integration (CI) and continuous delivery (CD) has developed considerably due to the overwhelming demand for the deployment and deliverability of new features and applications. As a result, DevOps approaches and Agile principles have been developed, in which developers collaborate closely with infrastructure engineers to guarantee that their applications are deployed quickly and reliably. Thanks to pipeline approach thinking, the efficiency of projects has greatly improved. Agile practices represent the introduction to the system of new features in each sprint delivery. Those practices may contain well-developed features or can contain bugs or failures which impact the delivery. The pipeline approach, depicted in this paper, overcomes the problems of delivery, improving the delivery timeline, the test load steps, and the benchmarking tasks. It decreases system interruption by integrating multiple test steps and adds stability and deliverability to the entire process. It provides standardization which means having an established, time-tested process to use, and can also decrease ambiguity and guesswork, guarantee quality and boost productivity

The Purchase Decision to ABC Sauce in Kebumen Regency

This analysis on purchasing decisions for ABC sauce in Kebumen Regency has the aim of knowing the effect of brand image, characteristic products, and cost on purchasing decisions for ABC sauces. This study was conducted on consumers who consume ABC brand sauce products, are domiciled in Kebumen Regency, and have a minimum age of 20 years. The respondent of this study is 100 people and was collected by using purposive sampling. Data were obtained through in-depth interviews and observation in the existing sub-districts. The analytical method used is SEM-PLS. The output of this analysis regarding the purchase decision of ABC sauce illustrates that the purchase decision of ABC sauce is not influenced by the brand image variable, but the purchase decision of ABC sauce in Kebumen Regency is influenced by the product quality and product price. ABC sauce producers must pay attention to the factors that influence consumer purchasing decisions such as product quality and price. Indicators of product quality are the suitability of benefits with needs, a guarantee of safety, product features, and quality. Indicators of price are affordable prices, prices according to product quality, chili prices can compete with similar products, and according to the needs and abilities of consumers.

Research on the purification enhancement of ecological ponds: Integrating water cycle optimization and plants layout

The hydrodynamic conditions of ponds are generally poor, which seriously affects the long–term water quality guarantee. In this research, the numerical simulation method was used to establish an integrated model of hydrodynamics and water quality for the simulation of the plant purification effect in ponds. Based on the flushing time using the tracer method, the purification rate of plants was introduced to consider the purification effect of plants on water quality. In–situ monitoring was carried out at the Luxihe pond in Chengdu, and the model parameters such as the purification rate of typical plants were calibrated. The degradation coefficient of NH3–N in the non–vegetated area was 0.014 d−1 in August and 0.010 d−1 in November. In areas with vegetation, the purification rate of NH3–N was 0.10–0.20 g/(m2·d) in August and 0.06–0.12 g/(m2·d) in November. The comparison of the results in August and November showed that due to the higher temperature in August, the plant growth effect was better, and the degradation rate of pollutants and the purification rate of pollutants by plants were higher.The flushing time distribution of the proposed Baihedao pond under the conditions of terrain reconstruction, water replenishment, and plant layout was simulated, and the frequency distribution curve of flushing time was used to evaluate the results. Terrain reconstruction and water replenishment can significantly improve the water exchange capacity of ponds. The reasonable planting of plants can reduce the variability of the water exchange capacity. Based on this combined with the purification effect of plants on NH3–N, the layout plan of Canna, Cattails, and Thalia in ponds was proposed.

Analysis Factor Performance Nurse with Satisfaction Patient in Public Health Center Mejobo Kudus

Quality service health Good If performance nurse give guarantee quality service given health _ to patient good sick _ nor healthy . Performance nurse Good Good to patient , then patient so feel like And want to return Again as well as can recommend to family or his friend . This type of correlational research by using a cross sectional approach with a total sample of 4 5 people using a purposive sampling technique . The results of the study showed that most of the nurse's performance was good, as many as 29 respondents (64.4%) and the lowest nurse performance was less, as many as 5 respondents (11.1%) , patient satisfaction was partly 36 respondents (80.0%) were satisfied and 9 respondents (20.0%) were dissatisfied. There is a relationship between Nurse Performance and Patient Satisfaction at the Mejobo Kudus Health Center with a p value of 0.000. There is a relationship between Nurse Performance and Patient Satisfaction at the Mejobo Kudus Health Center with a p value of 0.000. expected nurse more increase performance so that treated patients _ feel more satisfied with services provided.

Processing of alumina grinding media using scandia as a sintering aid

AbstractWear resistance is one of the essential properties of grinding media. Good wear resistance is the quality guarantee of preparing high‐purity ultrafine powder. This paper mainly studied the influence rule and enhanced mechanism of Sc2O3 on the wear resistance of Al2O3 ceramics. The relationship between Sc2O3 content and sintering properties, wear resistance, and microstructure of ceramics was studied. According to research findings, Sc2O3 could promote the densification of ceramics, improve the morphology of grain boundaries, enhance the binding force of grains, and increase the mechanical property of alumina grain.

Approx-RM: Reducing Energy on Heterogeneous Multicore processors under Accuracy and Timing Constraints

Reducing energy consumption while providing performance and quality guarantees is crucial for computing systems ranging from battery-powered embedded systems to data centers. This paper considers approximate iterative applications executing on heterogeneous multi-core platforms under user-specified performance and quality targets. We note that allowing a slight yet bounded relaxation in solution quality can considerably reduce the required iteration count and thereby can save significant amounts of energy. To this end, this paper proposes Approx-RM , a resource management scheme that reduces energy expenditure while guaranteeing a specified performance as well as accuracy target. Approx-RM predicts the number of iterations required to meet the relaxed accuracy target at run-time. The time saved generates execution-time slack, which allows Approx-RM to allocate fewer resources on a heterogeneous multi-core platform in terms of DVFS, core type, and core count to save energy while meeting the performance target. Approx-RM contributes with lightweight methods for predicting the iteration count needed to meet the accuracy target and the resources needed to meet the performance target. Approx-RM uses the aforementioned predictions to allocate just enough resources to comply with quality of service constraints to save energy. Our evaluation shows energy savings of 31.6%, on average, compared to Race-to-idle when the accuracy is only relaxed by 1%. Approx-RM incurs timing and energy overheads of less than 0.1%.

NATIONAL IDENTITY OF THE SPECIALIST BASED ON MUSIC PEDAGOGICS OF O. P. RUDNYTSKA

The review article analyzes the peculiarities of the national identity of Oksana Petrivna Rudnytska, a specialist in music pedagogy. The logic of the scientific content of the terms related to the topic of the submitted article (identity, national identity; professional and artistic competence; scientific school) is revealed. The article considers national identity as a sphere of ideas, values, and meanings of culture, perceived and articulated by the majority of the country's citizens. It has its own principles in the individual's construction of his identity, belonging to a definite nation and state. Certain issues regarding the effectiveness of the scientific schools of Ivan Zyazyun Institute of Pedagogical and Adult Education of the National Academy of Sciences of Ukraine, in particular the Ukrainian scientist, Doctor of Pedagogical Sciences, Professor O. P. Rudnytska, are highlighted. A conclusion is made regarding the results of the scientist's activity in relation to her national identity as a specialist in music pedagogy, which is based on the values of pedagogical mentoring, intellectual leadership, empathy, and national ethical and aesthetic worldview guidelines.
 Based on the vast experience of a teacher-artist, we can help increase the level of formation of the professional competence of music teachers and guarantee quality training of future music teachers for pedagogical and artistic activities.

Benzophenoxazine-based colorimetric and fluorescent probe for highly sensitive detection of amines and food freshness

In this work, we reported a chromogenic and near infrared (NIR) region fluorogenic dual-channel probe NRB, which could visually detect gaseous amines with high sensitivity (eg. 50 and 17 ppt for methylamine (MeNH2) via naked eyes and fluorescence spectrometer respectively). It exhibited a wide fluorescent emission band extending to the NIR region with a peak at 615 nm when stimulated by the MeNH2 solution. The plausible sensing mechanism was proved by mass spectrometry, where the reaction process was based on a nucleophilic substitution between the probe and amines rather than the ester group hydrolysis. Furthermore, NRB was successfully applied to monitor the food freshness (seafood and meat food), because of its low cytotoxicity and excellent photophysical properties. It was worth mentioning that real time monitoring for food quality can be realized visually by using a 365 nm UV lamp. In addition, the probe was stable during the quality guarantee period for perishable packaged food. It was believed that the applied experiments have demonstrated the value of this probe in the practical applications for food safety.

Enhancing low‐priority traffic reconfiguration designs in mixed‐critical avionics networks

AbstractIn avionics system networking, mixed‐critical networks are commonly used to integrate system applications with different levels of guarantees for various traffic classes on a shared resource platform, effectively addressing issues such as cabling, cost, weight, volume, power consumption, etc. However, current fault recovery and reconfiguration techniques mainly focus on high‐priority time‐triggered (TT) traffic, often neglecting the impact of TT traffic reconfiguration on low‐priority traffic. This paper proposes an avionics mixed‐critical networking approach based on the IEEE 802.1CB protocol, which is shown to be more effective for the post‐failure recovery of Rate‐Constrained (RC) traffic (a typical type of low‐priority traffic in TT networks). Furthermore, an elastic reconfiguration algorithm is presented to ensure quality of service for RC traffic during and after reconfiguration, preventing arbitrary application and traffic shutdown triggered by TT traffic reconfiguration. Simulations demonstrate that the proposed approach and algorithm can significantly improve the post‐failure recovery ratio of RC traffic, as well as guarantee quality of service and network throughput of RC traffic during and after reconfiguration to a certain extent.

Tracing the Volatilomic Fingerprint of the Most Popular Italian Fortified Wines.

The aim of the current study was to provide a useful platform to identify characteristic molecular markers related to the authenticity of Italian fortified wines. For this purpose, the volatilomic fingerprint of the most popular Italian fortified wines was established using headspace solid-phase microextraction combined with gas chromatography-mass spectrometry (HS-SPME/GC-MS). Several volatile organic compounds (VOCs), belonging with distinct chemical groups, were identified, ten of which are common to all the analyzed fortified Italian wines. Terpenoids were the most abundant chemical group in Campari bitter wines due to limonene's high contribution to the total volatilomic fingerprint, whereas for Marsala wines, alcohols and esters were the most predominant chemical groups. The fortified Italian wines VOCs network demonstrated that the furanic compounds 2-furfural, ethyl furoate, and 5-methyl-2-furfural, constitute potential molecular markers of Marsala wines, while the terpenoids nerol, α-terpeniol, limonene, and menthone isomers, are characteristic of Vermouth wines. In addition, butanediol was detected only in Barolo wines, and β-phellandrene and β-myrcene only in Campari wines. The obtained data reveal an adequate tool to establish the authenticity and genuineness of Italian fortified wines, and at the same time constitute a valuable contribution to identify potential cases of fraud or adulteration to which they are subject, due to the high commercial value associated with these wines. In addition, they contribute to the deepening of scientific knowledge that supports its valorization and guarantee of quality and safety for consumers.

Redispensing of expensive oral anticancer medicines: A practical application.

Increasing use of expensive oral anticancer medicines comes with the downside of a financial and environmental burden, partially caused by unused medication. Returned oral anticancer medicine to the pharmacy could be considered for redispensing providing guaranteed quality. This study aimed to identify and implement quality aspects and criteria for redispensing oral anticancer medicine in daily pharmacy practice. A systematic analysis was conducted to determine the eligibility of oral anticancer medicine for redispensing. Over a one-year period, the number of returned oral anticancer medicine accepted for redispensing was quantified, and the reduction in financial waste and environmental burden calculated based on this assessment. Four categories of quality aspects were identified for determining the eligibility of oral anticancer medicine for redispensing: Product presentation suitability (stability characteristics, storage requirements), physical condition (unopened or opened secondary or primary packaging, visual appearance), authentication (Falsified Medicines Directive, confirmation of initial dispense, recall), and additional aspects (remaining shelf life, period of storage in uncontrolled conditions). A standardized procedure for redispensing was implemented in daily pharmacy practice. During the study period, 10,415 oral anticancer medicine dose units out of 13,210 returns (79%) were accepted for redispensing. The total value of oral anticancer medicine accepted for redispensing was €483,301, accounting for 0.9% of the total value dispensed during this period. Furthermore, the potential reduction in environmental burden was estimated at 1132.1 g of potent active pharmaceutical ingredient. By implementing strict procedures considering all relevant quality aspects, redispensing of oral anticancer medicine can be successfully implemented into daily pharmacy practice, resulting in a significant reduction in financial waste and environmental burden.

PENINGKATAN KUALITAS TAS KAIN PERCA MITRA COLLECTION DENGAN MENGGUNAKAN METODE QUALITY FUNCTION DEPLOYMENT(QFD)

The craft of batik patchwork bags was initially less desirable, but now it has become one of the most admired and demanded handicrafts by many Indonesians, even throughout the world. However, increased market development is not matched by a guarantee of product quality. Manufacturers still ignore the importance of the quality of a product. Meanwhile, on the other hand, consumers want quality in the products they consume/use. This study aims to determine the desires and satisfaction of patchwork bag consumers and to find out how to improve the quality of Mitra Collection patchwork bag products. In this study the Quality Function Deployment (QFD) method was used because QFD aims to fulfill as many consumer desires as possible so that it is hoped that it will be superior to competing products and will be more customer focused. So that it can be seen how the realization is between consumer expectations and actual product conditions. This study uses a field research approach with a quantitative model and the research design used is an explorative design. The population in this study were all consumers of patchwork bag collection partners. The sampling method used purposive sampling with a sample of 100 respondents, Yogyakarta collection partner patchwork consumers. The results showed that the three priorities of consumers' desire to improve the quality of patchwork partner collection bags from the perspective of consumers' wishes were the uniqueness of the product being an important point in purchasing, the artistic value of the product, the artistic value derived from patchwork batik, the combination of attractive patchwork colors, and the combination appropriate patchwork shape.

Retrospective study of influencing factors on the outcomes of luteal phase stimulation in patients with dual stimulation.

Dual/double stimulation (DS) is an ovarian stimulation strategy that has emerged in recent years; it is characterized by two rounds of ovarian stimulation and oocyte retrieval in the same menstrual cycle. DS can greatly shorten the time required to obtain valid embryos in assisted reproduction. For fertility preservation, DS can speed up oocyte storage process. However, factors influencing luteal phase ovarian stimulation (LPS) outcomes in DS have not been elucidated. A total of 156 cycles from 78 cases were studied. Patients were grouped and analyzed according to their follicular phase ovarian stimulation (FPS) types. Female ages, ovarian stimulation protocols, number of oocytes retrieved, embryo quality were recorded. Comparisons of outcomes were conducted between different groups. Our study found that LPS obtained similar outcomes to follicular phase stimulation (FPS), and that the choice of FPS protocol affected the efficiency of LPS, the antagonist protocol and progestin-primed ovarian stimulation (PPOS) protocol resulted in better embryo outcomes in LPS. In LPS of DS, sufficient stimulation duration was the guarantee of embryo quality (number of available embryos: β = 0.145, 95% CI [0.078-0.211], P = 0.000; number of high-quality embryos: β = 0.114, 95% CI [0.057-0.171], P = 0.000). This study provided ideas for the precise use of DS. We suggest to further expand the sample size of DS in the future, conduct prospective controlled studies, unify the sample size of each subgroup, include the ovarian reserve of patients in the grouping basis, and exclude the influence of male factors. We hope that this study will help further refinement of DS so as to maximize patient benefits from it. When the DS strategy is considered in the follicular phase, the antagonist protocol and PPOS protocol are more recommended for better embryo outcomes in LPS. During LPS, adequate ovarian stimulation duration is the most important guarantee for LPS efficiency.

Efficient data-centric pest images identification method based on Mahalanobis entropy for intelligent agriculture

The frequent outbreak of crop pests is one of the main factors affecting crop yield. The accurate identification of pests is significant for effective pest control, which is the basis for the safe growth of crops and is also an important guarantee for high crop quality and crop yield. Computer vision based on supervised deep learning enables intelligent identification of pests, whose success is still inseparable from a large amount of labeled data, causing a large number of resource consumption due to data labeling. Therefore, an in-depth study on maximizing the value of data is essential when lacking labeled data. A new data evaluation method based on Mahalanobis distance and entropy is proposed to address the problem of lacking labeled data in intelligent pest identification. This method enables filtering high-value data, thus achieving effective pest identification performance with a small data volume. The experiment is conducted on a dataset we collected called PD-20, which shows the proposed method achieves baseline accuracy of 100% using only about 60% of the original data. Moreover, the proposed method can save at least 10% of the data volume compared with three comparison methods. To facilitate the deep integration of smart agriculture with artificial intelligence (AI), we designed an interactive framework of active learning for pest identification based on the proposed method, which lays the foundation for the application of AI in direction of agriculture.