Cross-Sectoral Comparisons of Process Quality Indicators of Health Care Across Residential Regions Using Restricted Mean Survival Time.

Background: Practice guidelines recommend patient management based on scientific evidence. Quality indicators gauge adherence to such recommendations and assess health care quality. They are usually defined as adverse event rates, which may not fully capture guideline adherence over time.

Impact of oil-water emulsions on lubrication performance of ship stern bearings.

During maritime operations, extreme events such as explosions, grounding, and seal failures can cause water ingress into lubricant compartments, forming oil-water emulsions that significantly affect the lubrication performance of ship stern bearings. Existing studies mainly focus on low water content, with limited exploration of the impact of high water content on lubrication performance. To address this gap, viscosity measurements of oil-water mixtures were conducted, and an emulsification viscosity equation applicable to varying water contents was derived.

A novel development of optimized hybrid MPPT controller for fuel cell systems with high voltage transformation ratio DC-DC converter.

The world is moving towards the utilization of hydrogen vehicle technology because its advantages are uniformity in power production, more efficiency, and high durability when compared to fossil fuels. So, in this work, the Proton Exchange Membrane Fuel Stack (PEMFS) device is selected for producing the energy for the hydrogen vehicle. The merits of this fuel technology are the possibility of operating less source temperature, and more suitability for stationery and transportation applications.

Assessing the factors militating against the effective implementation of electronic health records (EHR) in Nigeria.

This study assessed the factors militating against the effective implementation of electronic health records (EHR) in Nigeria, the computerization of patients' health records with a lot of benefits including improved patients' satisfaction, improved care processes, reduction of patients' waiting time, and medication errors. Despite these benefits, healthcare organizations are slow to adopt the EHR system. Therefore, the study assessed the factors militating against the effective implementation of the EHR system, the level of awareness of EHR, and the utilization of electronic health records; it also investigated the factors militating against the effective implementation of EHR.

A novel fuzzy assisted sliding mode control approach for frequency regulation of wind-supported autonomous microgrid.

Autonomous microgrids (ATMG), with green power sources, like solar and wind, require an efficient control scheme to secure frequency stability. The weather and locationally dependent behavior of the green power sources impact the system frequency imperfectly. This paper develops an intelligent, i.

Strategic model for integrating biogas a framework for sustainable energy integration in agro-industries.

The framework of the methodology presented in this study is an effort to integrate and optimize the agro-industry sector, especially energy in biogas. In this study, the technique of the system in functional analysis is shown systematically to translate various energy requirements in the factory as criteria for performance and functional design to be integrated, optimized, and energy efficient. The case study results indicated that biogas power plants, with a capacity of 1.

Generative adversarial networks with texture recovery and physical constraints for remote sensing image dehazing.

The scattering of tiny particles in the atmosphere causes a haze effect on remote sensing images captured by satellites and similar devices, significantly disrupting subsequent image recognition and classification. A generative adversarial network named TRPC-GAN with texture recovery and physical constraints is proposed to mitigate this impact. This network not only effectively removes haze but also better preserves the texture information of the original remote sensing image, thereby enhancing the visual quality of the dehazed image.

Effect of hot isostatic pressing treatment on the thermoelectric power factors of zinc oxides.

The effect of hot isostatic pressing (HIP) on the thermoelectric power factor of zinc oxide (ZnO) has been examined. ZnO is expected to be a potential n-type oxide thermoelectric material that could enhance the thermoelectric conversion efficiency. The HIP treatment is useful for densifying the material and controlling crystal defects in the material by applying high temperatures and pressures simultaneously.

Transcriptomic and genetic profiling in a spontaneous non-human primate model of hypertrophic cardiomyopathy and sudden cardiac death.

Hypertrophic cardiomyopathy (HCM) afflicts humans, cats, pigs, and rhesus macaques. Disease sequelae include congestive heart failure, thromboembolism, and sudden cardiac death (SCD). Sarcomeric mutations explain some human and cat cases, however, the molecular basis in rhesus macaques remains unknown.

Ethnogenetic analysis reveals the Bronze Age genetic affiliation of Yashkuns with West Eurasians.

Focusing on the Yashkun population of Gilgit-Baltistan, an administrative territory in northern Pakistan, our study investigated mtDNA haplotypes as indicators of ancient gene flow and genetic diversity. Genomic DNA was extracted and evaluated for quality using agarose gel electrophoresis. The complete control region of mtDNA (nt 16024-576) was amplified via PCR, and sequencing was performed using the Big Dye Terminator Kit on an Applied Biosystems Genetic Analyzer.

Dynamic reconfiguration of multiobjective distribution networks considering the variation of load and DG using a novel LDEDBO algorithm.

To address the challenges related to active power dissipation and node voltage fluctuation in the practical transformation of power grids in the field of new energy such as wind and photovoltaic power generation, an improved Dung Beetle Optimization Algorithm Based on a Hybrid Strategy of Levy Flight and Differential Evolution (LDEDBO) is proposed. This paper systematically addresses this issue from three aspects: firstly, optimizing the DBO algorithm using Chebyshev chaotic mapping, Levy flight strategy, and differential evolution algorithm; secondly, validating the algorithm's feasibility through real-time network reconfiguration at random time points within a 24-h period; and finally, applying the LDEDBO to address the dynamic reconfiguration problems of the IEEE-33 and IEEE-69 node bus. The simulation indicates that the power dissipation of the IEEE-33 node bus is decreased by 28.

Occurrence and ecological risks of antibiotics and antiparasitics in surface water in urban lakes in Hanoi city, Vietnam.

The presence of antibiotics in the environment is of significant concern due to their adverse effects on aquatic ecosystems. This study provides an assessment of potential ecological risks (RQ) associated with the concentrations of eight antibiotics and antiparasitics (amoxicillin-AMO, azithromycin-AZI, ciprofloxacine-CIP, ofloxacine-OFL, oxfendazole-OXF, lincomycin-LIN, sulfacetamide-SCE and sulfamethoxazole-SME) in the surface water of 13 urban lakes in Hanoi city, Vietnam during the period 2021-2023. The findings revealed considerable variations in the total concentrations of these 8 substances (T), ranging from below the method detection limit (< MDL) to 2240 ng L with an average of 330.

Evaluation of emissions and performance of a diesel engine running on graphene nanopowder and diesel-biodiesel-ethanol blends.

Today, there are environmental problems all over the world due to the emission of greenhouse gasses caused by the combustion of diesel fuel. The excessive consumption and drastic reduction of fossil fuels have prompted the leaders of various countries, including Iran, to put the use of alternative and clean energy sources on the agenda. In recent years, the use of biofuels and the addition of nanoparticles to diesel fuel have reduced pollutant emissions, improved the environment, and enhanced the physicochemical properties of the fuel.

Vehicle re-identification with multiple discriminative features based on non-local-attention block.

Vehicle re-identification (re-id) technology refers to a vehicle matching under a non-overlapping domain, that is, to confirm whether the vehicle target taken by cameras in different positions at different times is the same vehicle. Different identities of the same type of vehicles are one of the most challenging factors in the field of vehicle re-identification. The key to solve this difficulty is to make full use of the multiple discriminative features of vehicles.

Impact of EV interfacing on peak-shelving and frequency regulation in a microgrid.

A vehicle-to-grid (V2G) technology enables bidirectional power exchange between electric vehicles (EVs) and the power grid, presenting enhanced grid stability and load management opportunities. This study investigates a comprehensive microgrid system integrating EVs with solar (8 MW), wind (4.5 MW), and diesel generation sources, focusing on peak load reduction and frequency regulation capabilities.

Developmental validation of a novel all-in one assay of X chromosomal multi-insertion/deletion loci for forensic genetics.

Multi-insertion/deletion polymorphisms (Multi-InDels), as the novel genetic markers, show great potential in forensic research. Whereas, forensic researchers mainly focus on the multi-InDels on the autosomes, which can provide relatively limited information in some complex paternity cases. In this study, a novel X chromosomal multi-InDel multiplex amplification system was designed, containing 22 multi-InDels and one STR locus on the X chromosome.

Application of artificial intelligence based on state grid ESG platform in clean energy scheduling optimization.

The randomness and volatility of existing clean energy sources have increased the complexity of grid scheduling. To address this issue, this work proposes an artificial intelligence (AI) empowered method based on the Environmental, Social, and Governance (ESG) big data platform, focusing on multi-objective scheduling optimization for clean energy. This work employs a combination of Particle Swarm Optimization (PSO) and Deep Q-Network (DQN) to enhance grid scheduling efficiency and clean energy utilization.

Optimization of microwave components using machine learning and rapid sensitivity analysis.

Recent years have witnessed a tremendous popularity growth of optimization methods in high-frequency electronics, including microwave design. With the increasing complexity of passive microwave components, meticulous tuning of their geometry parameters has become imperative to fulfill demands imposed by the diverse application areas. More and more often, achieving the best possible performance requires global optimization.

Numerical optimization of anti resonant hollow core fiber for high sensitivity methane detection.

This study presents an innovative methane gas sensor design based on anti-resonant hollow-core fiber (AR-HCF) technology, optimized for high-precision detection at 3.3[Formula: see text]. Our numerical analysis explores the geometric optimization of the AR-HCF's structural parameters, incorporating real-world component specifications.

Temperature alters bacterial community structure in sediment of mountain stream.

Temperature and nutrients are known as crucial drivers for the variations of bacterial community structure and functions in oceans and lakes. However, their significance and mechanisms in influencing the bacterial community structure and function in mountain stream remain unclear. In this study, we investigated the spatiotemporal patterns of the bacterial communities and the main environmental factors in the Taizicheng River, a high-latitude mountainous stream, to reveal the main driving factors for sedimental bacterial communities.

A ridge-loaded staggered double-vane slow wave structure for terahertz radiation sources.

A ridge-loaded staggered double-vane slow-wave structure is proposed for terahertz radiation sources employing a sheet electron beam. This slow-wave structure has the advantages of enhanced electric field and energy density distribution and improved interaction impedance in the beam-wave interaction region. High-frequency characteristics are investigated for the proposed slow wave structure and compared with those of the staggered double-vane slow wave structure.

An efficient method for identifying surface damage in hydraulic concrete buildings.

Traditional hydraulic structures rely on manual visual inspection for apparent integrity, which is not only time-consuming and labour-intensive but also inefficient. The efficacy of deep learning models is frequently constrained by the size of available data, resulting in limited scalability and flexibility. Furthermore, the paucity of data diversity leads to a singular function of the model that cannot provide comprehensive decision support for improving maintenance measures.

An interpretable fault diagnosis method for aeroengine bearings based on belief rule based with a dynamic power set.

Accurately identifying bearing faults in aeroengines is crucial for maintaining their lifespan and cost. However, most current models are black-box models, such as deep learning models such as deep neural networks. The decision-making process of these models is more complex and lacks interpretability, which results in insufficient credibility of the results.

Non-catalytic glycerol dehydrogenation to dihydroxyacetone using needle-in-tube dielectric barrier discharge plasma.

Glycerol, a by-product of biodiesel production, could be converted into various value-added products. This work focuses on its dehydrogenation to dihydroxyacetone (DHA), which is mainly used in the cosmetics industry. While several methods have been employed for DHA production, some necessitate catalysts and involve harsh reaction conditions as well as long reaction times.

Spatiotemporal dynamics and spatial correlation patterns of urban ecological resilience across the Yellow River Basin in China.

Addressing the need to harmonize environment conservation and sustainable economic development within the Yellow River Basin (YRB) requires a profound comprehension of the spatiotemporal dynamics of urban ecosystem resilience. This study developed an index system utilizing the resistance-adaptability-recovery framework to measure these dynamics. By applying the advanced multi-attribute boundary area comparison method and a spatial autocorrelation model, we investigated the spatiotemporal variations and spatial correlation patterns of urban ecological resilience across the YRB.