bluuebunny/crossref_metadata_2025 huggingface dataset:
Valorizing Combustible and Compostable Fractions of Municipal Solid Waste to Biochar and Compost as an Alternative to Chemical Fertilizer for Improving Soil Health and Sunflower Yield
Authors: Aslam Samreen , Nazir Aisha
Published: July 2024

Reduced reliance on synthetic chemical fertilizers necessarily requires using renewable biomaterial-derived soil organic amendments (SOAs) in agriculture for sustained retention of nutrients through improvement in the soil organic matter (SOM). SOM replenishment through SOAs derived from wasted materials could help in its valorization by furthering the sustainability prospects of agronomic crop production systems. In the current study, compost (CP) and biochar (BC) were derived as SOAs from combustible and compostable fractions of municipal solid waste (MSW) for their potential valorization by adding SOAs as potential sustainable sources of nutrients as a replacement of chemical fertilizers (CF) for sunflower crops cultivated in potted soils. The experimental design included quadruplicated soil application of MSW-derived BC and CP in discrete and combined forms, each in three doses (% w:w), viz., low (L), medium (M), and high (H), i.e., BC-L, BC-M, BC-H; CP-L, CP-M, CP-H; and BC + CP-L, BC + CP-M, BC-CP-H. The results showed that, compared to the control (soil only), the sunflower growth and harvestable yield were significantly greater in BC + CF with a medium dose and were comparable to the growth and yield obtained in soils with CF. Sunflower growth in the discrete SOAs remained less than in the combined SOAs (BC + CP) and was attributed to the comprehensive soil health improvement rendered by the applied SOAs. The soil health improvement factors included SOM, CEC, and concentrations of total and available NPK. The dose-effect comparison of the SOAs showed highly variable trends, i.e., the sunflower growth did not correspond with the increase in dose of the SOAs. It is concluded that the combined application of BC + CP derived from MSW components at a medium dose could act as a potential alternative to CF. The developed approach resulted in MSW valorization, which improved soil health and yielded a better sunflower crop.
Feline Cognition and the Role of Nutrition: An Evolutionary Perspective and Historical Review
Authors: McGrath Allison P. , Horschler Daniel J. , Hancock Leslie
Published: July 2024

Research into cognition in cats and the impact of nutrition on cat cognitive health lags behind that in dogs but is receiving increased attention. In this review, we discuss the evolutionary history of the domesticated cat, describe possible drivers of domestication, and explore the interrelationships between nutrition and cat cognition. While most cat species are solitary, domesticated cats can live in social groups, engage in complex social encounters, and form strong attachments to humans. Researchers have recently started to study cat cognition using similar methods as those developed for dogs, with an initial primary focus on perception and social cognition. Similar to dogs, cats also show cognitive and behavioral changes associated with stress and aging, but these signs are often gradual and often considered a consequence of natural aging. Despite the fundamental role of nutrition in cognitive development, function, and maintenance, research into the association between nutrition and cognition in cats is only preliminary. Ultimately, additional research is needed to gain a full understanding of cat cognition and to explore the role of nutrition in the cognitive health of cats to help improve their welfare.
Buccal Swab Samples from Japanese Brown Cattle Fed with Limonite Reveal Altered Rumen Microbiome
Authors: Harakawa Kentaro , Kawarai Shinpei , Kryukov Kirill , Nakagawa So , Moriya Shigeharu , Imakawa Kazuhiko
Published: July 2024

The areas of the Mount Aso grasslands in Kumamoto, Japan, are the primary location for the breeding of the Kumamoto strain of Japanese Brown cattle (JBRK). Although Aso limonite, deposited by volcanic ash and magma, has been commonly fed to pregnant JBRK in this area, the mechanisms of its salutary effects on pregnant JBRK have not yet been elucidated. Approximately 100 days before the expected day of calf delivery, seven JBRK (four supplemented with limonite and three controls without limonite) were assigned to this study, from which a buccal swab was collected at the highest rumination every 30 days for 90 days. DNA extracted from these swabs was then analyzed using a 16S rRNA gene amplicon sequence analysis. Statistically significant differences between the two groups were discovered through beta-diversity analysis, though results from alpha-diversity analysis were inconclusive. The microbiota identified were classified into six clusters, and three of the main clusters were core-rumen bacteria, primarily cellulose digestion in cluster 1, oral bacteria in cluster 2, and non-core-rumen bacteria in cluster 3. In the limonite group, core-rumen bacteria decreased while non-core-rumen bacteria increased, suggesting that limonite feeding alters rumen microbiota, particularly activation of non-core-rumen microbiota.
Culex quinquefasciatus Mosquitoes Resist Acquisition of Methicillin-Resistant Staphylococcus aureus: Insights from Field and Laboratory Studies
Authors: Arif Waseema , Thangaraj Gowdham , Srinivasan Pushpa , Srirama Srikanth , Devaraju Panneer
Published: July 2024

The emergence of antimicrobial resistance (AMR) in pathogens and their spillover into the environment have become a global public health menace. Insects can acquire these pathogens from the environment and would serve as mechanical and biological vectors. The current study assessed the ability of Culex quinquefasciatus mosquitoes to acquire methicillin-resistant Staphylococcus aureus (MRSA) through the exposure of the mosquitoes to the pathogen via rearing water, blood feed, or a feeding membrane under laboratory conditions. In addition, mosquito immatures collected from their habitat in the vicinity of hospitals, veterinary dispensaries, and butcher shops at 15 study sites in Puducherry were screened for MRSA infection. All samples were subjected to the culture-based isolation of S. aureus from the surface and homogenate. The presence of the S. aureus-specific nuc gene and the genes that confer resistance to methicillin (mecA and mecC) were screened using PCR tests. MRSA was not evident either on the external surface or in the homogenate of the mosquitoes emerging from the larvae reared in the MRSA-spiked water or those fed with MRSA through blood or smeared membranes. Furthermore, the presence of MRSA was not evident in any of the field-caught mosquitoes. Hence, we conclude that C. quinquefasciatus mosquitoes are impervious to MRSA colonization.
Hydroethanolic Extract of Lepidium apetalum Willdenow Alleviates Dextran Sulfate Sodium-Induced Colitis by Enhancing Intestinal Barrier Integrity and Inhibiting Oxidative Stress and Inflammasome Activation
Authors: Kim Kwang-Youn , Kang Yun-Mi , Lee Ami , Kim Yeon-Ji , Kim Kyung-Ho , Hwang Youn-Hwan
Published: July 2024

The prevalence of ulcerative colitis (UC) has surged in Asian nations recently. The limitations of traditional drug treatments, including biologics, have spurred interest in herbal medicines for managing UC. This study aimed to elucidate the protective mechanisms of hydroethanolic extract from Lepidium apetalum Willdenow (LWE) on intestinal integrity and inflammation in a dextran sodium sulfate (DSS)-induced colitis model of inflammatory bowel disease (IBD). Using UPLC-MS/MS analysis, eleven phytochemicals were identified in LWE, including catechin, vicenin-2, and quercetin. LWE restored transepithelial electrical resistance (TEER) and reduced paracellular permeability in IL-6-stimulated Caco-2 cells, increasing the expression of the tight junction proteins ZO-1 and occludin. LWE treatment alleviated DSS-induced colitis symptoms in mice, reducing body weight loss, disease activity index values, and spleen size, while improving colon length and reducing serum FITC-dextran levels, indicating enhanced intestinal barrier function. LWE suppressed NLRP3 inflammasome activation, reducing protein levels of pro-caspase-1, cleaved-caspase-1, ASC, and NLRP3, as well as mRNA levels of IL-1β, IL-6, and TNF-α. LWE treatment upregulated activity and mRNA levels of the antioxidant enzymes SOD1 and NQO1. Additionally, LWE modulated the Nrf2/Keap1 pathway, increasing p-Nrf2 levels and decreasing Keap1 levels. LWE also restored goblet cell numbers and reduced fibrosis in DSS-induced chronic colitis mice, increasing gene and protein expressions of ZO-1 and occludin. In summary, LWE shows promise as a therapeutic intervention for reducing tissue damage and inflammation by enhancing intestinal barrier function and inhibiting colonic oxidative stress-induced inflammasome activation.
Multi-Scale and Multi-Factor ViT Attention Model for Classification and Detection of Pest and Disease in Agriculture
Authors: Xie Mingyao , Ye Ning
Published: July 2024

Agriculture has a crucial impact on the economic, ecological, and social development of the world. More rapid and precise prevention and control work, especially for accurate classification and detection, is required due to the increasing severity of agricultural pests and diseases. However, the results of the image classification and detection are unsatisfactory because of the limitation of image data volume acquisition and the wide range of influencing factors of pests and diseases. In order to solve these problems, the vision transformer (ViT) model is improved, and a multi-scale and multi-factor ViT attention model (SFA-ViT) is proposed in this paper. Data augmentation considering multiple influencing factors is implemented in SFA-ViT to mitigate the impact of insufficient experimental data. Meanwhile, SFA-ViT optimizes the ViT model from a multi-scale perspective, and encourages the model to understand more features, from fine-grained to coarse-grained, during the classification task. Further, the detection model based on the self-attention mechanism of the multi-scale ViT is constructed to achieve the accurate localization of the pest and disease. Finally, experimental validation of the model, based on the IP102 and Plant Village dataset, is carried out. The results indicate that the various components of SFA-ViT effectively enhance the final classification and detection outcomes, and our model outperforms the current models significantly.
Finite Element Analysis of Geogrid-Incorporated Flexible Pavement with Soft Subgrade
Authors: Chhetri Sagar , Deb Plaban
Published: July 2024

Improving the durability of flexible pavements and constructing new roads on weak soil foundations present significant challenges, prompting designers to explore alternative methods to prolong pavement lifespan. Geosynthetics have emerged as a promising solution for soil stabilization, with various materials developed for this purpose. The current study concentrates on using the finite element (FE) method to examine the effectiveness of geogrid-incorporated flexible pavements on soft soil substrates. A three-dimensional layered pavement is constructed with an FE model, incorporating subgrade layers of varying strengths based on their California bearing ratio (CBR) values, with a geogrid layer implemented to enhance subgrade stability. Additionally, attention is also given to investigating the effect of base course thickness. The findings reveal that the geogrid layer primarily influences the formation of plastic strains in the subgrade rather than resilient strains, effectively reducing vertical compressive strain by approximately 40%. With increasing CBR values, there is a reduction in vertical strain, although the influence zone extends up to a depth of 300 mm within the subgrade. At the surface of the subgrade, vertical strain decreases by around 17%, 39%, and 49% as the CBR values increase from 1% to 3%, 5%, and 8%, respectively.
A Novel Function of a Research Process Based on a Power Internet of Things Architecture Intended for Smart Grid Demand Schemes
Authors: Al-Mashhadani Sarmad Waleed Taha , Kurnaz Sefer
Published: July 2024

The global energy sector is currently undergoing a significant transformation to address sustainability, energy efficiency, and grid resilience. Smart grids, leveraging advanced technologies like the power internet of things (PIoT), play a crucial role in this transformation. This research focuses on enhancing the efficiency, reliability, and sustainability of electricity distribution through IoT technologies. It envisions a system where interconnected devices, sensors, and data analytics optimize energy consumption, monitor grid conditions, and manage demand response scenarios. Central to this effort is the integration of PIoT into the smart grid infrastructure, particularly in implementing dynamic pricing strategies for demand response. Leveraging power line communication (PLC) techniques, this innovative approach facilitates real-time communication between grid components and consumers. The results demonstrate improved grid stability through dynamic load management, effectively responding to demand fluctuations, and minimizing disruptions. The deployment of dynamic pricing methods using PLC-driven schemes empowers customers by offering access to real-time energy use data. This access incentivizes energy-efficient behavior. leading to a 30% increase in the adoption of energy-saving techniques among consumers. A utility company pilot study claimed a 12% drop in peak demand after adopting time-of-use charges, with an accuracy rate of 98.87% in total.
Estimating Tail Probability in MMPP/D/1 Queue with Importance Sampling by Service Rate Adjustments
Authors: Anh Ngo Hai , Hung Nguyen Ngoc , Giang Pham Thanh
Published: July 2024

The Asynchronous Transfer Mode (ATM) is an efficient technology for call relays, and it transmits information from multiple services including data, video, or voice. This information is conveyed at ATM multiplexers in small fixed-size packets called cells. The acceptable cell loss probability at ATM multiplexers is about 10−12. Important Sampling (IS) is an efficient method for estimating tiny probabilities that cannot be achieved by traditional Monte Carlo (MC) methods. This research presents a novel approach for evaluating the tail probability in the MMPP/D/1 queue system utilizing importance sampling simulation in the ATM network. To generate more rare events, a virtual queue is implemented in the dequeue process by decreasing the processing rate in the queue. In this way, the tail probability can be estimated on a real-time network.
Wearable Voice Dosimetry System
Authors: Llorente Marcos , Podhorski Adam , Fernandez Secundino
Published: July 2024

The objective quantification of voice acoustic parameters is used for the diagnosis, monitoring, and treatment of voice disorders. Such assessments are carried out with specialised equipment within the doctor’s office. The controlled conditions employed are usually not those of the real environment of the patient. The results, although very informative, are specific to those measurement conditions and to the time when they were performed. A wearable voice monitoring system, based on an accelerometer to ensure the message, can overcome these limitations. We present a miniaturised, low-power, and low-cost wearable system to estimate and record voice fundamental frequency (F0), intensity and phonation time for long intervals in the everyday environment of the patient. It was tested on two subjects for up to two weeks of recording time. It was possible to identify distinct periods in vocal activity, such as normal, professional, demanding or hyperfunctional. It provided information on the workload that the vocal cords needed to cope with over time and when and to what extent that workload was concentrated. The proposed voice dosimetry system enables the extraction and recording of voice parameters for long periods of time in the everyday environment of the patient, allowing the objectification of vocal risk situations and personalised treatment and monitoring.
Location Selection Methods for Urban Terminal Co-Distribution Centers with Air–Land Collaboration
Authors: Qi Wei , Li Ang , Zhang Honghai
Published: July 2024

Urban terminal logistics and distribution enterprises face the problems of duplicated network layouts, high costs, and inefficient urban environments. Recently, collaborative distribution using unmanned aerial vehicles (UAVs) and ground vehicles has been considered as a means of reducing costs and enhancing efficiency, thus overcoming the issues created by the high-density layout of enterprises’ relatively independent networks. This essentially involves constructing an air–ground collaborative common distribution network. To optimize the economic cost and distribution time of network operations, we established a site selection planning model for air–ground cooperative urban co-distribution centers and designed a solution method based on gray wolf optimization with K-means clustering. Taking the Wangsheren area of Jinan City, China, as an example, 15 UAV co-distribution centers and 13 vehicle co-distribution centers were identified. Although the average distribution cost of the network rose by 35–50% compared to traditional terminal distribution, the time saving was 80–85%, greatly improving the high-value-added service capacity. The end-distribution efficiency and customer satisfaction were also enhanced, which fully verifies the feasibility, validity, and applicability of the proposed model. Our approach can be applied to landing sites and the planning and optimization of large-scale commercial operations using logistics UAVs in urban areas.
Inventory Prediction Using a Modified Multi-Dimensional Collaborative Wrapped Bi-Directional Long Short-Term Memory Model
Authors: Abualuroug Said , Alzubi Ahmad , Iyiola Kolawole
Published: July 2024

Inventory prediction is concerned with the forecasting of future demand for products in order to optimize inventory levels and supply chain management. The challenges include demand volatility, data quality, multi-dimensional interactions, lead time variability, seasonal trends, and dynamic pricing. Nevertheless, these models suffer from numerous shortcomings, and in this research, we propose a new model, MMCW-BiLSTM (modified multi-dimensional collaboratively wrapped BiLSTM), for inventory prediction. The MMCW-BiLSTM model reflects a considerable leap in inventory forecasting by combining a number of components in order to consider intricate temporal dependencies and incorporate feature interactions. The MMCW-BiLSTM makes use of BiLSTM layers, collaborative attention mechanisms, and a multi-dimensional attention approach to learn from augmented datasets consisting of the original features and the extracted time series data. Moreover, adding a Taylor series transformation allows for a more precise description of the features in the model, thus improving the prediction precision. The results show that the models make the least mistakes when they use the AV demand forecasting dataset, with MAE values of 1.75, MAPE values of 2.89, MSE values of 6.76, and RMSE values of 2.6. Similarly, when utilizing the product demand dataset, the model also achieves the lowest error values for these metrics at 1.97, 3.91, 8.76, and 2.96. Likewise, when utilizing the dairy goods sales dataset, the model also achieves the lowest error values for these metrics at 2.54, 3.69, 10.39, and 3.22.
Characterization of Mesenchymal Stromal Cells after Serum Starvation for Extracellular Vesicle Production
Authors: Asti Anna Lia , Croce Stefania , Valsecchi Chiara , Lenta Elisa , Grignano Maria Antonietta , Gregorini Marilena , Carolei Adriana , Comoli Patrizia , Zecca Marco , Avanzini Maria Antonietta , Rampino Teresa
Published: July 2024

It has been demonstrated that mesenchymal stromal cells (MSCs) act by releasing bioactive molecules, among these are extracellular vesicles (EVs). The MSC-EVs are considered a convenient alternative to cell therapy, showing several functional characteristics of their origin cells. EVs can be collected from conditioned in vitro cultured MSCs. Different processes have been developed to induce in vitro EV release, and these approaches have been demonstrated to also influence MSC potentialities. This study aimed to investigate the effect of serum starvation on MSC characteristics. The morphology, phenotype, differentiation capacity, immunomodulatory ability, and metabolic state were maintained by MSCs cultured under starvation. To evaluate basic ultrastructural characteristics of cells and EVs, Transmission Electron Microscopy (TEM) analysis was performed on MSCs after 12, 24, and 48 h starvation, demonstrating that 24 h starvation was the best time for MSC structure preservation. Further studies are needed to support the hypothesis that MSCs after starvation could still be considered as therapeutic agents.
Few-Shot Steel Defect Detection Based on a Fine-Tuned Network with Serial Multi-Scale Attention
Authors: Liu Xiangpeng , Jiao Lei , Peng Yulin , An Kang , Wang Danning , Lu Wei , Han Jianjiao
Published: July 2024

Detecting defects on a steel surface is crucial for the quality enhancement of steel, but its effectiveness is impeded by the limited number of high-quality samples, diverse defect types, and the presence of interference factors such as dirt spots. Therefore, this article proposes a fine-tuned deep learning approach to overcome these obstacles in unstructured few-shot settings. Initially, to address steel surface defect complexities, we integrated a serial multi-scale attention mechanism, concatenating attention and spatial modules, to generate feature maps that contain both channel information and spatial information. Further, a pseudo-label semi-supervised learning algorithm (SSL) based on a variant of the locally linear embedding (LLE) algorithm was proposed, enhancing the generalization capability of the model through information from unlabeled data. Afterwards, the refined model was merged into a fine-tuned few-shot object detection network, which applied extensive base class samples for initial training and sparsed new class samples for fine-tuning. Finally, specialized datasets considering defect diversity and pixel scales were constructed and tested. Compared with conventional methods, our approach improved accuracy by 5.93% in 7-shot detection tasks, markedly reducing manual workload and signifying a leap forward for practical applications in steel defect detection.
Self-Diffusion in Sr-Containing Iron-Polyphosphate Glasses by Molecular Dynamics Simulations
Authors: Stoch Pawel
Published: July 2024

Among the many possible applications of iron phosphate glasses, one of them is that they are promising materials in waste vitrification, particularly for radioactive waste. In vitrified form, waste elements should be permanently immobilized in a glass network as they are susceptible to harsh environmental conditions. The self-diffusion of the vitrified material species may limit the potential usefulness of the glasses. This paper presents the possibility of using molecular dynamics simulations to study this process and the substitution of SrO into an iron phosphate glass network. It was evidenced that the self-diffusion mechanism differed significantly depending on whether the glass was in a solid or liquid state. The proposed method also offered a relatively easy prediction of glass characteristic temperatures, such as transformation and flow. We also observed, and here describe, an aggregation process of the glass elements that may drive their crystallization. The obtained results are discussed in light of the experimental and theoretical structural feature literature data.
Brainwaves in the Cloud: Cognitive Workload Monitoring Using Deep Gated Neural Network and Industrial Internet of Things
Authors: Afzal Muhammad Abrar , Gu Zhenyu , Bukhari Syed Umer , Afzal Bilal
Published: July 2024

Monitoring and classifying cognitive workload in real time is vital for optimizing human–machine interactions and enhancing performance while ensuring safety, particularly in industrial scenarios. Considering this significance, the authors aim to formulate a cognitive workload monitoring system (CWMS) by leveraging the deep gated neural network (DGNN), a hybrid model integrating bi-directional long short-term memory (Bi-LSTM) and gated recurrent unit (GRU) networks. In our experimental setup, each of the four virtual users is equipped with a Raspberry Pi Zero W module to ensure efficient data transmission, thereby enhancing the reliability and efficacy of the monitoring process. This seamless monitoring framework utilizes the constrained application protocol (CoAP) and the Things Board platform to evaluate cognitive workload in real time. The most popular EEG benchmark dataset, the STEW is utilized for workload classification in this study. We employ the short-time Fourier transformation (STFT) to extract frequency bands corresponding to users in both high and low cognitive workload modes. The proposed DGNN models achieve a perfect accuracy of 99.45%, outperforming every previous state-of-the-art model. We meticulously monitored critical parameters, including latency, classification processing time, and cognitive workload levels. This research demonstrates the importance of continuous monitoring for increasing productivity and safety in industries by introducing a novel method of real-time cognitive workload monitoring. The implementation codes for each experiment are documented and made available for reproducibility.
Impact of Transcranial Direct Current Stimulation on the Capacity to Perform Burpees: A Randomized Controlled Trial
Authors: Chen Tai-Chih , García de Frutos José Manuel , Colomer-Poveda David , Márquez Gonzalo , Kaushalya Fernando Shyamali , Orquín-Castrillón Francisco Javier , Romero-Arenas Salvador
Published: July 2024

Transcranial direct current stimulation (tDCS) has emerged as a potential intervention to improve physical performance. This study investigates the effects of tDCS applied to the primary motor cortex (M1) and dorsolateral prefrontal cortex (DLPFC) on performance in a maximal effort task, specifically the No-Jump Burpee exercise. Twenty healthy male subjects (26.0 ± 4.91 years) completed three experimental conditions (a-DLPFC, a-M1, and SHAM) in a double-blind crossover design. Prior to the performance of burpees to exhaustion, tDCS (2 mA, 20 min) was administered. The total number of repetitions, vastus lateralis muscle oxygen saturation, heart rate, and subjective perception of exertion (RPE) during exercise were measured. Repeated ANOVAs showed a significant effect of condition on the number of repetitions (p < 0.001). Subjects performed more repetitions under the M1 condition (68 ± 19.5) compared to DLPFC (63 ± 17.9) and SHAM (58 ± 18.0), with significant differences between all conditions. This study demonstrates that tDCS can improve performance in a physical endurance task such as the No-Jump Burpee. The findings suggest that tDCS may be a viable ergogenic tool for improving athletic performance. Future research should explore the underlying mechanisms and the practical application of these results in long-term physical training programs (NCT06472882).
Monocular Depth Estimation Based on Dilated Convolutions and Feature Fusion
Authors: Li Hang , Liu Shuai , Wang Bin , Wu Yuanhao
Published: July 2024

Depth estimation represents a prevalent research focus within the realm of computer vision. Existing depth estimation methodologies utilizing LiDAR (Light Detection and Ranging) technology typically obtain sparse depth data and are associated with elevated hardware expenses. Multi-view image-matching techniques necessitate prior knowledge of camera intrinsic parameters and frequently encounter challenges such as depth inconsistency, loss of details, and the blurring of edges. To tackle these challenges, the present study introduces a monocular depth estimation approach based on an end-to-end convolutional neural network. Specifically, a DNET backbone has been developed, incorporating dilated convolution and feature fusion mechanisms within the network architecture. By integrating semantic information from various receptive fields and levels, the model’s capacity for feature extraction is augmented, thereby enhancing its sensitivity to nuanced depth variations within the image. Furthermore, we introduce a loss function optimization algorithm specifically designed to address class imbalance, thereby enhancing the overall predictive accuracy of the model. Training and validation conducted on the NYU Depth-v2 (New York University Depth Dataset Version 2) and KITTI (Karlsruhe Institute of Technology and Toyota Technological Institute) datasets demonstrate that our approach outperforms other algorithms in terms of various evaluation metrics.
Analysis of a Mechanism Used to Operate an Oscillating Separator
Authors: Mosnegutu Emilian , Bibire Luminița , Chitimuș Dana , Panainte-Lehăduș Mirela , Jasiński Marcin , Przydatek Grzegorz , Sporea Nicoleta
Published: July 2024

This article presents a comparative study of two different kinds of processes that produce oscillatory motion on a work surface during the mechanical separation process. The investigation began with determining the trajectory produced by the oscillating separator’s active component of the classical drive mechanism. Based on this, a second mechanism—the six-bar mechanism—was created using the WATT program, and a mathematical analysis was conducted. The comparative examination of the two mechanisms was carried out using OriginPro, Mathcad, and Roberts software. This study’s findings all point to the same conclusion: the newly developed mechanism produces the same trajectory as the classical mechanism when viewed through the lens of the reference element, or the element that causes the oscillatory movement. However, when looking at the operating parameters, there was a noticeable difference in the movement’s speed and the angle of the crank when producing its maximum speed. Theoretically, this new mechanism increases the speed at which solid particles move across a work surface. However, this difference cannot be characterized as positive or negative because further research is required to determine how the nature of solid particles and the work surface’s inclination affect this process, in addition to this mechanism. The identification of the mathematical equations of motion for the constituent parts of the mechanism under study is the novelty produced of this paper.
Varying Drivers of 2013–2017 Trends in PM2.5 Pollution over Different Regions in China
Authors: Tao Yanan , Liu Guangjin , Sun Bowen , Dong Yawei , Cao Lei , Zhao Bei , Li Mei , Fan Zeman , Zhou Yaqing , Wang Qiaoqiao
Published: July 2024

A significant decrease in surface PM2.5 concentrations has been reported since the implementation of the Air Pollution Prevention and Control Action Plan in 2013. In this study, we use the GEOS-Chem model to simulate the trend in surface PM2.5 pollution in China from 2013 to 2017, as well as the relative contributions of emission reduction and meteorology. The simulated decline rate averaged over monitoring sites in China is around −4.7 μg m−3 yr−1 in comparison with the value of −6.4 μg m−3 yr−1 from observations. The model also captures the variations over different regions, with r in the range of 0.85–0.95. Based on the sensitivity tests against emissions and meteorology, the study finds that the decline in PM2.5 concentrations is mainly driven by the reduction in anthropogenic emissions. The variation in open biomass burning (OBB) is not significant, except in Northeast China (NEC) and Pearl River Delta (PRD), where the changes originated from OBB are 40% and 30% of those associated with anthropogenic emission reductions. Changes in meteorology from 2013 to 2017 led to significant increases in PM2.5 concentrations in most areas in China, except in NEC. The increase attributed to meteorology, to a large extent, could be explained by the significant decrease in surface wind speed (WS) and planetary boundary layer height (PBLH) between 2013 and 2017, combined with their negative correlation with PM2.5. The decrease in PM2.5 concentrations in NEC, on the other hand, could be explained by the significant decrease in relative humidity (RH) there combined with the positive correlation of RH with PM2.5, while the changes in WS and PBLH there are relatively small compared with other areas. The change in meteorology, therefore, hinders the improvement of air quality via emission controls in most of China. In Sichuan Basin (SCB), the increase due to meteorology almost compensates for the decrease associated with emission reduction, leading to the least change in PM2.5 concentrations, although the decrease due to emission controls is the largest compared with other areas.
Low-Cost Sensor Monitoring of Air Quality Indicators during Outdoor Renovation Activities around a Dwelling House
Authors: Bencs László
Published: July 2024

A couple of air quality (AQ) parameters were monitored with two types of low-cost sensors (LCSs) before, during and after the garden fence rebuilding of a dwelling house, located at the junction of a main road and a side street in a suburban area of Budapest, Hungary. The AQ variables, recorded concurrently indoors and outdoors, were particulate matter (PM1, PM2.5, PM10) and some gaseous trace pollutants, such as CO2, formaldehyde (HCHO) and volatile organic compounds (VOCs). Medium-size aerosol (PM2.5-1), coarse particulate (PM10-2.5) and indoor-to-outdoor (I/O) ratios were calculated. The I/O ratios showed that indoor fine and medium-size PM was mostly of outdoor origin; its increased levels were observed during the renovation. The related pollution events were characterized by peaks as high as 100, 95 and 37 µg/m3 for PM1, PM2.5-1 and PM10-2.5, respectively. Besides the renovation, some indoor sources (e.g., gas-stove cooking) also contributed to the in-house PM1, PM2.5-1 and PM10-2.5 levels, which peaked as high as 160, 255 and 220 µg/m3, respectively. In addition, these sources enhanced the indoor levels of CO2, HCHO and, rarely, VOCs. Increased and highly fluctuating VOC levels were observed in the outdoor air (average: 0.012 mg/m3), mainly due to the use of paints and thinners during the reconstruction, though the use of a nearby wood stove for heating was an occasional contributing factor. The acquired results show the influence of the fence renovation-related activities on the indoor air quality in terms of aerosols and gaseous components, though to a low extent. The utilization of high-resolution LCS-assisted monitoring of gases and PMx helped to reveal the changes in several AQ parameters and to assign some dominant emission sources.
Analyzing the Improvement Effect of the k-Distribution Method on the Radiation Parameterization for WRF Model
Authors: Choi Sung-Jin , Jee Joon-Bum , Lee Kyu-Tae , Zo Il-Sung
Published: July 2024

To address the need for the accurate parameterization of radiative absorption by gasses (for predicting atmospheric warming), Chou et al. developed a new k-distribution method. In this study, we compared the improved k-distribution method (hereinafter referred to as the NEW method) with the New Goddard radiation schemes (hereinafter referred to as the OLD method) for the WRF (the weather research and forecasting) model. The results of radiative flux calculations by the NEW and OLD methods of k-distribution using the New Goddard Radiation Scheme were compared with the results of the line-by-line (LBL) method, and the results showed that the radiative flux calculated by the NEW was accurate to within 1.00 Wm−2 with respect to the LBL, while the OLD showed large differences at altitudes above the upper troposphere and near the surface. Therefore, in this study, we selected clear-sky and cloudy-day conditions and compared the weather elements prediction results of WRF using the NEW and OLD methods. For the clear-sky days, the downward shortwave radiation at the surface and the temperature at 2 m above the surface (hereinafter referred to as T2) over land and ocean were reversed in sign due to the highly sensitive absorption coefficients of gasses. For cloudy days, the absorption effect by gasses harmonized with the scattering effect induced by cloud droplets; the differences in the shortwave and longwave radiations and radiative heating rate between the NEW and OLD methods were obvious. Thus, it was analyzed that the proposed NEW method could lead to significant improvements in forecasting weather elements.
Uncertainty Degradation Model for Initiating Explosive Devices Based on Uncertain Differential Equations
Authors: Ma Changli , Jia Li , Wen Meilin
Published: July 2024

The performance degradation of initiating explosive devices is influenced by various internal and external factors, leading to uncertainties in their reliability and lifetime predictions. This paper proposes an uncertain degradation model based on uncertain differential equations, utilizing the Liu process to characterize the volatility in degradation rates. The ignition delay time is selected as the primary performance parameter, and the uncertain distributions, expected values and confidence intervals are derived for the model. Moment estimation techniques are employed to estimate the unknown parameters within the model. A real data analysis of ignition delay times under accelerated storage conditions demonstrates the practical applicability of the proposed method.
Estimates of Eigenvalues and Approximation Numbers for a Class of Degenerate Third-Order Partial Differential Operators
Authors: Muratbekov Mussakan , Suleimbekova Ainash , Baizhumanov Mukhtar
Published: July 2024

In this paper, we study the spectral properties of a class of degenerate third-order partial differential operators with variable coefficients presented in a rectangle. Conditions are found to ensure the existence and compactness of the inverse operator. A theorem on estimates of approximation numbers is proven. Here, we note that finding estimates of approximation numbers, as well as extremal subspaces, for a set of solutions to the equation is a task that is certainly important from both a theoretical and a practical point of view. The paper also obtained an upper bound for the eigenvalues. Note that, in this paper, estimates of eigenvalues and approximation numbers for the degenerate third-order partial differential operators are obtained for the first time.
A Roadmap for the Rational Use of Biomarkers in Oral Disease Screening
Authors: Cirillo Nicola
Published: July 2024

Oral health has witnessed a significant transformation with the integration of biomarkers in early-diagnostic processes. This article briefly reviews the types of biomarkers used in the screening and early detection of oral diseases, particularly oral cancer, periodontal diseases, and dental caries, with an emphasis on molecular biomarkers. While the advent of these biomarkers may represent a leap forward in oral healthcare, it also opens the door to potential overtesting, overdiagnosis, and overtreatment. To inform the selection of novel biomarkers and ensure their rational use in screening tests, it is imperative to consider some key characteristics, which are specific to the biomarker (e.g., surrogate biomarkers should reliably reflect the primary health outcome), to the test (e.g., sensitivity and specificity must be balanced based on the disease of interest), and to the disease (e.g., the efficacy of treatment should improve when the condition is diagnosed earlier). For systemic conditions associated with oral diseases, researchers should be extremely cautious when determining who is “at risk”, particularly when such risk is small, non-existent, or inconsequent. This framework aims to ensure that advancements in oral health diagnostics translate into genuine improvements in patient care and well-being.
Molecular Analysis of Volatile Metabolites Synthesized by Candida albicans and Staphylococcus aureus in In Vitro Cultures and Bronchoalveolar Lavage Specimens Reflecting Single- or Duo-Factor Pneumonia
Authors: Filipiak Wojciech , Wenzel Matthias , Ager Clemens , Mayhew Chris A. , Bogiel Tomasz , Włodarski Robert , Nagl Markus
Published: July 2024

Current microbiological methods for pneumonia diagnosis require invasive specimen collection and time-consuming analytical procedures. There is a need for less invasive and faster methods to detect lower respiratory tract infections. The analysis of volatile metabolites excreted by pathogenic microorganisms provides the basis for developing such a method. Given the synergistic role of Candida albicans in increasing the virulence of pathogenic bacteria causing pneumonia and the cross-kingdom metabolic interactions between microorganisms, we compare the emission of volatiles from Candida albicans yeasts and the bacteria Staphylococcus aureus using single and mixed co-cultures and apply that knowledge to human in vivo investigations. Gas chromatography–mass spectrometry (GC-MS) analysis resulted in the identification of sixty-eight volatiles that were found to have significantly different levels in cultures compared to reference medium samples. Certain volatiles were found in co-cultures that mainly originated from C. albicans metabolism (e.g., isobutyl acetate), whereas other volatiles primarily came from S. aureus (e.g., ethyl 2-methylbutyrate). Isopentyl valerate reflects synergic interactions of both microbes, as its level in co-cultures was found to be approximately three times higher than the sum of its amounts in monocultures. Hydrophilic–lipophilic-balanced (HLB) coated meshes for thin-film microextraction (TFME) were used to preconcentrate volatiles directly from bronchoalveolar lavage (BAL) specimens collected from patients suffering from ventilation-associated pneumonia (VAP), which was caused explicitly by C. albicans and S. aureus. GC-MS analyses confirmed the existence of in vitro-elucidated microbial VOCs in human specimens. Significant differences in BAL-extracted amounts respective to the pathogen-causing pneumonia were found. The model in vitro experiments provided evidence that cross-kingdom interactions between pathogenic microorganisms affect the synthesis of volatile compounds. The TFME meshes coated with HLB particles proved to be suitable for extracting VOCs from human material, enabling the translation of in vitro experiments on the microbial volatilome to the in vivo situation involving infected patients. This indicates the direction that should be taken for further clinical studies on VAP diagnosis based on volatile analysis.
Placement Principles of Islamic Calligraphy in Architecture: Insights from the Al-Hambra and Al-Azem Palaces
Authors: Baydoun Ziad , Norishah Tengku , Baydoun Reham , Adam Mastura
Published: July 2024

This paper addresses a critical gap in the study of Islamic architecture by exploring the interconnected relationship between Arabic calligraphy and architectural design. Specifically, it examines the principles guiding the placement of Islamic calligraphy within the interior and exterior spaces of Islamic public buildings through a qualitative analysis of two notable case studies, the Al-Hambra Palace in Granada, Spain, and the Al-Azem Palace in Hama, Syria. This research elucidates fundamental principles that underpin the integration of calligraphy in Islamic architectural contexts. To enhance the robustness of the findings, interviews were conducted with three expert master calligraphers, providing skillful insights that enrich the understanding of calligraphy placement. This study reveals significant implications for the decoration of walls and ceilings in Islamic buildings. However, the findings are limited by the scope of the case studies and the subjective interpretations of the interviewed experts. This research contributes valuable knowledge to the field, informing contemporary architectural practices and the preservation of cultural heritage.
Racial/Ethnic Disparities and Immunotherapeutic Advances in the Treatment of Hepatocellular Carcinoma
Authors: Garcia Alexsis , Mathew Stephen O.
Published: July 2024

Hepatocellular carcinoma (HCC) remains one of the leading causes of death among many associated liver diseases. Various conventional strategies have been utilized for treatment, ranging from invasive surgeries and liver transplants to radiation therapy, but fail due to advanced disease progression, late screening/staging, and the various etiologies of HCC. This is especially evident within racially distinct populations, where incidence rates are higher and treatment outcomes are worse for racial/ethnic minorities than their Caucasian counterparts. However, with the rapid development of genetic engineering and molecular and synthetic biology, many novel strategies have presented promising results and have provided potential treatment options. In this review, we summarize past treatments, how they have shaped current treatments, and potential treatment strategies for HCC that may prove more effective in the future.
Identification and Characterization of ATOH7-Regulated Target Genes and Pathways in Human Neuroretinal Development
Authors: Atac David , Maggi Kevin , Feil Silke , Maggi Jordi , Cuevas Elisa , Sowden Jane C. , Koller Samuel , Berger Wolfgang
Published: July 2024

The proneural transcription factor atonal basic helix–loop–helix transcription factor 7 (ATOH7) is expressed in early progenitors in the developing neuroretina. In vertebrates, this is crucial for the development of retinal ganglion cells (RGCs), as mutant animals show an almost complete absence of RGCs, underdeveloped optic nerves, and aberrations in retinal vessel development. Human mutations are rare and result in autosomal recessive optic nerve hypoplasia (ONH) or severe vascular changes, diagnosed as autosomal recessive persistent hyperplasia of the primary vitreous (PHPVAR). To better understand the role of ATOH7 in neuroretinal development, we created ATOH7 knockout and eGFP-expressing ATOH7 reporter human induced pluripotent stem cells (hiPSCs), which were differentiated into early-stage retinal organoids. Target loci regulated by ATOH7 were identified by Cleavage Under Targets and Release Using Nuclease with sequencing (CUT&RUN-seq) and differential expression by RNA sequencing (RNA-seq) of wildtype and mutant organoid-derived reporter cells. Additionally, single-cell RNA sequencing (scRNA-seq) was performed on whole organoids to identify cell type-specific genes. Mutant organoids displayed substantial deficiency in axon sprouting, reduction in RGCs, and an increase in other cell types. We identified 469 differentially expressed target genes, with an overrepresentation of genes belonging to axon development/guidance and Notch signaling. Taken together, we consolidate the function of human ATOH7 in guiding progenitor competence by inducing RGC-specific genes while inhibiting other cell fates. Furthermore, we highlight candidate genes responsible for ATOH7-associated optic nerve and retinovascular anomalies, which sheds light to potential future therapy targets for related disorders.