Browse Articles
Discover research articles across all indexed journals
Thermal performance evaluation of phase changing materials in double glazing units for office buildings in Egypt
Abstract Nowadays glass curtain walls are used widely in modern buildings as they offer a significant aesthetic appearance and provide the building with natural lighting. However, their poor thermal resistance leads to excessive usage of mechanical systems to achieve thermal comfort which in turn increases the energy consumption in buildings. The proper integration of the unique properties of the PCM could effectively enhance the thermal performance of buildings therefore, the main objective of this research is to examine and validate the effect of using phase change material (PCM) on the building thermal performance especially when integrated with double glazing unit (DGU). The research examined comprehensively the effect of using PCM with DGU by undergoing a field experiment and comparing the results with a simulation model using Design Builder (DB) -energy plus simulation tool. After validating the simulation model, DB was used to examine the effect of using PCM double glazing unit with a multi-story office building in three different climatic regions in Egypt covering humid, mild, and hot arid regions. The results showed that using petroleum jelly as a PCM with DGUs will lead to a significant effect in reducing the usage of mechanical systems in cooling the building spaces by 8.91%, 8.62%, and 8.07% in Cairo, Alexandria, and Aswan consecutively from the total yearly cooling electric consumption.
Why do people resist AI-based autonomous cars?: Analyzing the impact of the risk perception paradigm and conditional value on public acceptance of autonomous vehicles
This study examines the factors that lead to the acceptance of AI-based autonomous vehicles. Despite the considerable importance of AI-based autonomous vehicles there has been a lack of analysis based on theoretical models and analysis that considers contextual conditions. The survey was conducted between July 8 and 17, 2019. In order to increase the representativeness of the sample, a quota sampling method was adopted, based on considering gender and region. The sample size of this survey is 2,000 people. According to the response statistics, 26,231 people requested the survey, 3,973 people participated in the survey, and 2,000 people completed the survey. We adopted regression and moderation analysis as main statistical analysis methods. In modeling, we set up the variable from risk perception paradigm as independent variable and the conditional value as moderating variable in explaining the acceptance of AI-based autonomous vehicles. For this work, the analysis was conducted in two stages. Initially, a regression analysis was performed to determine the impact of the risk perception paradigm and conditional value on the acceptance of autonomous vehicles. Secondly, a moderation analysis was conducted to determine whether the perception of self-driving taxis moderates the relationship between the risk perception paradigm and the acceptance of autonomous vehicle. The study revealed that the acceptance of autonomous vehicles is influenced by a number of factors, including knowledge, image, conditional value, and perceived risks. Additionally, the relationship with perceived benefits, image and autonomous vehicle is moderated by conditional value.
Geospatial digital mapping of soil organic carbon using machine learning and geostatistical methods in different land uses
Stochastic process-based drought monitoring and assessment system: A temporal switched weights approach for accurate and precise drought determination
Drought is a recurring climate phenomenon that naturally occurs in all climate regions and leads to prolonged periods of water scarcity. The primary cause of water shortages is inadequate precipitation, which can be influenced by meteorological factors such as temperature, humidity, and precipitation patterns. Effective drought mitigation policies necessitate the monitoring and prediction of drought. To determine the severity and impacts of droughts accurately and precisely, probabilistic models have been developed. However, erroneous drought detection with probabilistic models is always possible. As a result, a novel system for meteorological, agricultural, and hydrological droughts based on the Stochastic Process (Markov chain (MC)) has been proposed to address this issue. The proposed method incorporates the Multi-Scalar Seasonally Amalgamated Regional Standardized Precipitation Evapotranspiration Index (MSARSPEI) for timescales 1–48 and employs temporal switched weights. These weights are generated from the Transition Probability Matrix (TPM) of each temporal classification of the drought type in accordance with the MC’s fundamental assumption. The developed system was implemented on nine meteorological stations in Pakistan. By leveraging historical data and information, the system enables the categorization of droughts. The resultant classifications can be incorporated into effective drought monitoring systems, which can help in devising specific policies to alleviate the effects of droughts.
Effects of life history strategy on the diversity and composition of the coral holobiont communities of Sabah, Malaysia
Evaluating the impacts of microplastics on agricultural soil physical, chemical properties, and toxic metal availability: An emerging concern for sustainable agriculture
Microplastics (MPs) are an emerging environmental issue that might endanger the health of agricultural soil. Even though several research on the particular toxicity of MPs to species have been carried out, there is little information on MPs’ impacts on soil physicochemical properties and heavy metals (HMs) availability of HMs contaminated and without contaminated soils. This study examined the changes in soil characteristics for both HMs contaminated and without contaminated soils by five distinct MPs, including Polyethylene (PE), Polyethylene terephthalate (PET), Polystyrene Foam (PS), Polyamide (PA), and a combination of these four types of MPs (Mixed MPs), at two different concentrations (0.2% and 1%; w/w), where soil incubation experiments were setup for this studies and the standard analytical techniques employed to measure soil characteristics and toxic metal availability. After the ending of soil incubation studies (90 days), significant changes have been observed for physicochemical properties [bulk density, porosity, water holding capacity, pH, electrical conductivity (EC), organic carbon (OC), and organic matter (OM)]. The soil nutrients change in descending order was found as NH4+ -N> PO43+ > Na > Ca > NO3- > Mg for lower concentrations of MPs compared to higher concentrations. The HMs availability is reducing with increasing MPs concentration and the descending order for metal availability was as follows Pb > Zn > Cd > Cr > Cu > Ni. Based on MP type, the following descending order of MPs PS > Mix (MPs) > PA > PET > PE, respectively act as a soil properties influencer. Usually, effects were reliant on MPs’ category and concentrations. Finally, this study concludes that MPs may modify metal movements, and soil quality; consequently, a possible threat will be created for soil health.
MCU expression in hippocampal CA2 neurons modulates dendritic mitochondrial morphology and synaptic plasticity
Abstract Neuronal mitochondria are diverse across cell types and subcellular compartments in order to meet unique energy demands. While mitochondria are essential for synaptic transmission and synaptic plasticity, the mechanisms regulating mitochondria to support normal synapse function are incompletely understood. The mitochondrial calcium uniporter (MCU) is proposed to couple neuronal activity to mitochondrial ATP production, which would allow neurons to rapidly adapt to changing energy demands. MCU is uniquely enriched in hippocampal CA2 distal dendrites compared to proximal dendrites, however, the functional significance of this layer-specific enrichment is not clear. Synapses onto CA2 distal dendrites readily express plasticity, unlike the plasticity-resistant synapses onto CA2 proximal dendrites, but the mechanisms underlying these different plasticity profiles are unknown. Using a CA2-specific MCU knockout (cKO) mouse, we found that MCU deletion impairs plasticity at distal dendrite synapses. However, mitochondria were more fragmented and spine head area was diminished throughout the dendritic layers of MCU cKO mice versus control mice. Fragmented mitochondria might have functional changes, such as altered ATP production, that could explain the structural and functional deficits at cKO synapses. Differences in MCU expression across cell types and circuits might be a general mechanism to tune mitochondrial function to meet distinct synaptic demands.
Digital economy, green finance, and economic resilience
With the rapid development of digital technology, the digital economy has become an important force to promote economic growth and drive innovation, and to enhance economic quality and ecological efficiency through green finance. Additionally, green finance, as an important means to achieve resource and environmental sustainability, has received increasing attention and importance from the international community. This study explores how the digital economy and green finance contribute to economic resilience using panel data from 30 provinces and cities in China from to 2011–2023. The development of the digital economy can effectively promote economic resilience, and green finance plays a significant mediating role between the digital economy and economic resilience. In this regard, China’s economic resilience must be enhanced by strengthening the construction of digital infrastructure, promoting innovation and the development of green finance, and formulating a policy environment conducive to the development of green finance.
Author Correction: Induced hepatocyte-like cells derived from adipose-derived stem cells alleviates liver injury in mice infected with Echinococcus Multilocularis
Induction of systemic resistance through calcium signaling in Arabidopsis exposed to air plasma-generated dinitrogen pentoxide
Plasma technology, which can instantaneously transform air molecules into reactive species stimulating plants, potentially contributes to developing a sustainable agricultural system with high productivity and low environmental impact. In fact, plant immunity activation by exposure to a reactive gas mainly consisting of dinitrogen pentoxide (N2O5) was recently discovered, while physiological responses to N2O5 are rarely known. Here, we demonstrate early (within 10 min) physiological responses to N2O5 gas in Arabidopsis. Exposure to N2O5 gas induced an increase in cytosolic Ca2+ concentration within seconds in directly exposed leaves, followed by systemic long-distance Ca2+-based signaling within tens of seconds. In addition, jasmonic acid (JA)-related gene expression was induced within 10 minutes, and a significant upregulation of the defense-related gene PDF1.2 was observed after 1 day of exposure to N2O5 gas. These systemic resistant responses to N2O5 were found unique among air-plasma-generated species such as ozone (O3) and nitric oxide (NO)/nitrogen dioxide (NO2). Our results provide new insights into understanding of plant physiological responses to air-derived reactive species, in addition to facilitating the development of plasma applications in agriculture.
Author Correction: Relationship between METS-IR and ABSI index and the prevalence of nocturia: a cross-sectional analysis from the 2005–2020 NHANES data
Immediate and short-term effects of neurodynamic techniques on hamstring flexibility: A systematic review with meta-analysis
Background Good hamstring flexibility(HF) is crucial for sports performance and health, with injuries having an economic impact on healthcare and sports teams. Therefore, our objectives were to estimate the effect of neurodynamic techniques on HF and to compare the effect of these techniques with static stretching. Methods We systematically searched the Cochrane, MEDLINE(via PubMed), Scopus, Web of Science and Sportdiscus databases for RCTs comparing neurodynamic interventions with control intervention or with static stretching exercises for HF in adults with limited HF. We conducted a random-effects meta-analysis with subgroup analyses according to the type of comparison group(control group or static stretching exercises) and total number of sessions. Furthermore, to reflect the variation in genuine therapy effects in different scenarios, including future patients, we calculated a 95% prediction interval(prI). Results Thirteen trials were included, involving 624 participants. Pooled results showed a significant improvement in HF for immediate (SMD = 1.01, 95% CI: 0.44 to 1.59) and short-term effects (SMD = 1.21, 95% CI: 0.90 to 1.52). Subgroup analyses by type of comparison group showed that these techniques are more effective than the control group in the immediate and short term and than static stretching in the short term. Analyses by total sessions showed a significant increase in HF with a treatment of 1, 3, 10 and 12 sessions. Conclusion Neurodynamic techniques improve HF immediately and in the short term. Subgroup analyses by type of comparison group showed that these techniques are more effective than static stretching in the short term.
Design and modeling of a highly compact negative index floral shape metamaterial for flight navigation applications
Abstract The collision avoidance system (CAS) is a mandatory monitoring apparatus equipped in all aircraft to safeguard flight safety. The CAS scans the predefined regions in a systematic manner for a certain length of time to detect any approaching aircraft that could potentially pose a threat. Thus, CAS requires a focused multi-element radiator which can encompass the complete azimuth region. Recent years have seen a growing emphasis on enhancing the efficiency of CAS antennas because of several constraints, such as low gain (3.6 dB), larger dimensions, substantial side-lobe amplitude (− 7 dB), and challenges with beam adaptation. The current research strives to enhance the gain of a CAS antenna by incorporating the basic idea of metamaterials (MTMs). Therefore, a compact floral-shaped double negative (DNG) MTM design is proposed. The CAS antenna routes the signal throughout the complete azimuth region, so the designed MTM must be proficient to withstand its DNG characteristics for different incident angles. Hence, the proposed design is tested at various incident angles spanning between to along the azimuth region, at a deviation. The results indicate that the proposed structure retains its DNG behavior in the desired frequency range, regardless of the incident angles. The computed effective medium ratio of the structure is 13.47 at the CAS central frequency (1.06 GHz), highlighting its compactness and efficacy. Furthermore, to analyze the function of the structure on the antenna, the unit-element (UE) is expanded to a 5 × 4 array and deployed as an additional layer on the radiator at a predetermined distance. The addition of MTM to the radiator outperformed the conventional radiator by enhancing the antenna gain, by 2.6 dB, respectively. Additionally, to confirm the experimental findings, the UE and array designs are fabricated, and the fabrication results align closely with the simulation results.
Degradable thermosets via orthogonal polymerizations of a single monomer
Quality of information in gestational diabetes mellitus videos on TikTok: Cross-sectional study
Background TikTok is an important channel for consumers to obtain and adopt health information. However, misinformation on TikTok could potentially impact public health. Currently, the quality of content related to GDM on TikTok has not been thoroughly reviewed. Objective This study aims to explore the information quality of GDM videos on TikTok. Methods A comprehensive cross-sectional study was conducted on TikTok videos related to GDM. The quality of the videos was assessed using three standardized evaluation tools: DISCERN, the Journal of the American Medical Association (JAMA) benchmarks, and the Global Quality Scale (GQS). The comprehensiveness of the content was evaluated through six questions covering definitions, signs/symptoms, risk factors, evaluation, management, and outcomes. Additionally, a correlational analysis was conducted between video quality and the characteristics of the uploaders and the videos themselves. Results A total of 216 videos were included in the final analysis, with 162 uploaded by health professionals, 40 by general users, and the remaining videos contributed by individual science communicators, for-profit organizations, and news agencies. The average DISCERN, JAMA, and GQS scores for all videos were 48.87, 1.86, and 2.06, respectively. The videos uploaded by health professionals scored the highest in DISCERN, while the videos uploaded by individual science communicators scored significantly higher in JAMA and GQS than those from other sources. Correlation analysis between video quality and video features showed DISCERN scores, JAMA scores and GQS scores were positively correlated with video duration (P<0.001). Content scores were positively correlated with the number of comments (P<0.05), the number of shares (P<0.001), and video duration (P<0.001). Conclusion We found that the quality of GDM video on TikTok is poor and lack of relevant information, highlighting the potential risks of using TikTok as a source of health information. Patients should pay attention to identifying health-related information on TikTok.
LeaData a novel reference data of leather images for automatic species identification
Abstract In the leather industry, the mammalian skins of buffalo, cow, goat, and sheep are the permissible materials for leather-making. They serve the trade of quality leather products; hence, the knowledge of animal species in leather is inevitable. The traditional identification techniques are prone to ambiguous predictions due to insufficient reference studies. Indeed, leather image analysis with big data can pave the way for automatic and objective analysis with accurate prediction. This study focuses on creating novel and unique leather image data, LeaData. The objective is to automatically determine species from grain surface analysis. Hence, it employs a simple, cheaper, handheld digital microscope for leather image acquisition. The magnifying parameter 47 $$\times$$ captures the species-unique grain patterns distributed over the leather surface. In total, the LeaData encloses 38,172 images of four species from 137 leather samples. This big data spans leather images with theoretically ideal and practically non-ideal grain patterns. It also includes images of grain patterns varying over different body parts. Thus, the novel LeaData is an adequately larger pool of leather images with diverse behavior. The motive is to establish a smart leather species identification technique that can be easily accessible by leather specialists, customs officials, and leather product manufacturers. Hence, this paper solely creates the bigger LeaData and presents its different versions to the digital image processing and computer vision research community. This digitized source of permissible leather species helps enable digitization in leather technology for species identification. In turn, in maintaining biodiversity preservation and consumer protection.
Correction: Microtubules and Gαo-signaling modulate the preferential secretion of young insulin secretory granules in islet β cells via independent pathways
Author Correction: Assessment of energy management and power quality improvement of hydrogen based microgrid system through novel PSO-MWWO technique
Bioaccumulation, sources and health risk assessment of polycyclic aromatic hydrocarbons in Lilium davidii var. unicolor
Dietary uptake is the main pathway of exposure to polycyclic aromatic hydrocarbons (PAHs). However, there is no data regarding the pollution and health risks posed by PAHs in Lilium davidii var. unicolor. We measured the concentrations of 16 PAHs in lily bulbs from Lanzhou; analyzed the bioaccumulation, sources, and pollution pathways of PAHs; assessed the influence of baking on PAH pollution in the bulb; and assessed the cancer risks associated with PAH exposure via lily consumption. The total PAH concentrations in raw bulbs were 30.39–206.55 μg kg-1. The bioconcentration factors of total PAHs ranged widely from 0.92 to 5.71, with a median value of 2.25. Pearson correlation analysis revealed that the octanol-water partition coefficients and water solubility values played important roles in the bioaccumulation of naphthalene, fluorene, phenanthrene, pyrene, and fluoranthene in the raw bulb by influencing PAH availability in soil. Correlation analysis and principal component analysis with multivariate linear regression indicated that biomass and wood burning, coal combustion, diesel combustion, and petroleum leakage were the major sources of PAHs in the raw bulbs. The paired t-test showed that the PAH concentrations in the baked bulbs were higher than those in the raw bulbs. PAH compositions in lily bulb changed during the baking process. Baked bulbs exhibited a higher cancer risk than raw bulbs. Local adults had low carcinogenic risks from consuming lily bulbs. This study fills the knowledge gap about PAH pollution and the related health risks of PAHs in the Lanzhou lily.