bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Room Layout on Natural Gas Explosion in Kitchen
Authors: Yang Kai , Wu Hao , Chen Ye
Published: July 2024

In order to elucidate the overpressure and fire hazard effects of gas explosion in a congested room, the effects of gas concentration and room layout on a gas explosion in a kitchen were studied by CFD. The results showed that the flow field parameters in a kitchen exhibited an initial increase followed by a decrease as the gas concentration increased. The maximum gas flow rate recorded within the chamber was 390 m/s, while the corresponding maximum flame propagation rate and peak pressure reached 289.86 m/s and 30.95 kPa, respectively. The difference in the flow field induced by the concentration was further enhanced by the presence of congested materials. Additionally, the room layout influenced the gas congestion’s blowout effect due to variations in turbulence intensity and flammable gas volume caused by significant changes in the congestion within the room. Specifically, when the gas concentration was 10%, the order of indoor gas flow rate and flame combustion rate were II > U > L > I, while the turbulent kinetic energy and explosive overpressure followed the order I > II > L > U. The results are of great significance for the disaster assessment and accident prevention of natural gas explosion in civil kitchens.
Morphometric Analysis of Two Shell Color Strains of the Bay Scallop Argopecten irradians
Authors: Huang Xianpeng , Hao Zhenlin , Mao Junxia , Wang Luo , Wang Xubo , Tian Ying
Published: July 2024

In this study, we employed geometric morphometrics (GMs) to analyze the shell shape differences among two mass-selected strains of bay scallops (red shell strain (RS) and black shell strain (BS)) and a control group (CG). The results revealed distinct shell shape differences corresponding to shell coloration, with the black shell strain displaying a more elliptical shell compared to the red shell strain. Additionally, the umbonal angle of the red shell strain was smaller than that of the black shell strain, indicating that the black shell strain had a more favorable jet direction that could enhance swimming capabilities. To evaluate the model’s performance in practical applications, leave-one-out cross-validation was carried out on the two shell strains and one control group. The results demonstrated discrimination accuracy rates of 67.44%, 47.62%, and 68.18% for the BS strain, RS strain, and CG, respectively. Similarly, for the right valves, the discrimination accuracy rates were 62.79%, 50.00%, and 75.00% for the BS strain, RS strain, and CG, respectively.
Split-Step Galerkin FE Method for Two-Dimensional Space-Fractional CNLS
Authors: Zhu Xiaogang , Zhang Yaping , Nie Yufeng
Published: July 2024

In this paper, we study a split-step Galerkin finite element (FE) method for the two-dimensional Riesz space-fractional coupled nonlinear Schrödinger equations (CNLSs). The proposed method adopts a second-order split-step technique to handle the nonlinearity and FE approximation to discretize the fractional derivatives in space, which avoids iteration at each time layer. The analysis of mass conservative and convergent properties for this split-step FE scheme is performed. To test its capability, some numerical tests and the simulation of the double solitons intersection and plane wave are carried out. The results and comparisons with the algorithm combined with Newton’s iteration illustrate its effectiveness and advantages in computational efficiency.
Selective Sheet Extrusion: A Novel Manufacturing Process for Large-Format Material Extrusion
Authors: Parrott Brian , Coronado Preciado Angelica , Feron Eric
Published: July 2024

The trade-off between resolution and speed represents a significant challenge when extrusion-based additive manufacturing (AM) is used for large-format additive manufacturing (LFAM). This paper presents an analysis of a new material extrusion process, named selective sheet extrusion (SSE), that aims to decouple these parameters. Unlike traditional single-nozzle material extrusion processes, SSE utilizes a single, very wide nozzle through which extrusion is controlled by an array of dynamically actuated teeth at the nozzle outlet. This allows the system to deposit a selectively structured sheet of material with each pass, potentially enabling the deposition of an entire layer of a part in a single pass. An analysis of the theoretical performance of the SSE technology, in terms of speed and material efficiency in comparison with single-nozzle extrusion systems, predicted speed increases of 2–3 times for the geometries that were explored. The analysis was then validated through experimental work that indicated a normalized improvement in print speed of between 2.3 and 2.5 times using a proof-of-concept SSE prototype. The SSE concept expands the opportunity frontier of LFAM technologies by enabling enhanced print speeds, while maintaining higher resolutions at scale. This enhancement in speed and/or resolution could have significant benefits, especially in large-scale prints that benefit from enhanced internal resolution.
Systematic Review of Preclinical Studies on the Efficacy and Mechanisms of Herbal Medicines in Post-Myocardial Infarction Heart Failure with Reduced Ejection Fraction
Authors: Yun Soyeong , Oh Jieun , Chu Hongmin , Park Dasol , Leem Jungtae
Published: July 2024

Background and Objectives: Heart failure with reduced ejection fraction (HFrEF) remains a significant burden. Traditional herbal medicines have shown cardioprotective effects in treating HFrEF. However, the implications of herbal formulation considering the dynamic immunohistological changes in the myocardium following acute ischemic injury have been insufficiently discussed. This review investigated the efficacy and mechanisms reported in studies using rat or mouse models of HFrEF induced by left descending coronary artery ligation. Materials and Methods: A systematic search was conducted using PubMed, Embase, AMED, CINAHL, and CENTRAL databases. Information was extracted regarding study characteristics, disease model induction protocols, intervention characteristics, treatment protocols, outcomes, and suggested mechanisms. Hierarchical cluster analysis of test drugs was performed based on constituent herb similarities. The risk of bias (RoB) was assessed using the Systematic Review Center for Laboratory animal Experimentation RoB tool. Results: Overall, 26 studies met the eligibility criteria. HF model induction periods after LADCA ligation ranged from 1 day to 12 weeks. Most studies administered the test drug for four weeks. Commonly used herbs included Panax ginseng, Astragalus membranaceus, Salvia miltiorrhiza, Carthamus tinctorius, and Lepidium apetalum, which demonstrated anti-fibrotic, anti-inflammatory, and anti-apoptotic effects through various signaling pathways. The overall RoB was relatively high. No significant association was found between model induction periods and herbal formulations or examined mechanisms. Conclusions: Future research should consider the time-dependent immunohistological features of the myocardium during HF treatment.
Elucidating the Phytochemical Landscape of Leaves, Stems, and Tubers of Codonopsis convolvulacea through Integrated Metabolomics
Authors: Yuan Fang , Yan Shiying , Zhao Jian
Published: July 2024

Codonopsis convolvulacea is a highly valued Chinese medicinal plant containing diverse bioactive compounds. While roots/tubers have been the main medicinal parts used in practice, leaves and stems may also harbor valuable phytochemicals. However, research comparing volatiles across tissues is lacking. This study performed metabolomic profiling of leaves, stems, and tubers of C. convolvulacea to elucidate tissue-specific accumulation patterns of volatile metabolites. Ultra-high performance liquid chromatography–tandem mass spectrometry identified 302 compounds, belonging to 14 classes. Multivariate analysis clearly differentiated the metabolic profiles of the three tissues. Numerous differentially accumulated metabolites (DAMs) were detected, especially terpenoids and esters. The leaves contained more terpenoids, ester, and alcohol. The stems accumulated higher levels of terpenoids, heterocyclics, and alkaloids with pharmaceutical potential. The tubers were enriched with carbohydrates like sugars and starch, befitting their storage role, but still retained reasonable amounts of valuable volatiles. The characterization of tissue-specific metabolic signatures provides a foundation for the selective utilization of C. convolvulacea parts. Key metabolites identified include niacinamide, p-cymene, tridecanal, benzeneacetic acid, benzene, and carveol. Leaves, stems, and tubers could be targeted for antioxidants, drug development, and tonics/nutraceuticals, respectively. The metabolomic insights can also guide breeding strategies to enhance the bioactive compound content in specific tissues. This study demonstrates the value of tissue-specific metabolite profiling for informing the phytochemical exploitation and genetic improvement of medicinal plants.
Thermal Decomposition of Bio-Based Plastic Materials
Authors: Oliver Inés , Conesa Juan A. , Fullana Andres
Published: July 2024

This research delves into a detailed exploration of the thermal decomposition behavior of bio-based polymers, specifically thermoplastic starch (TPS) and polylactic acid (PLA), under varying heating rates in a nitrogen atmosphere. This study employs thermogravimetry (TG) to investigate, providing comprehensive insights into the thermal stability of these eco-friendly polymers. In particular, the TPS kinetic model is examined, encompassing the decomposition of three distinct fractions. In contrast, PLA exhibits a simplified kinetic behavior requiring only a fraction described by a zero-order model. The kinetic study involves a systematic investigation into the individual contributions of key components within TPS, including starch, glycerin, and polyvinyl alcohol (PVA). This detailed analysis contributes to a comprehensive understanding of the thermal degradation process of TPS and PLA, enabling the optimization of processing conditions and the prediction of material behavior across varying thermal environments. Furthermore, the incorporation of different starch sources and calcium carbonate additives in TPS enhances our understanding of the polymer’s thermal stability, offering insights into potential applications in diverse industries.
The Significance of Lignocellulosic Raw Materials on the Pore Structure of Activated Carbons Prepared by Steam Activation
Authors: Zhang Li , Zuo Songlin
Published: July 2024

Five different lignocellulosic raw materials (coconut shells, Moso bamboo, sawtooth oak, Chinese fir, and Masson pine) were used to prepare activated carbons by steam activation at 850 °C to evaluate the effects of their structures on physical activation. The chemical compositions, botanic forms, and pore structures of the lignocellulose-based charcoal samples were systematically characterized by proximate and ultimate analyses, scanning electron microscopy, and mercury injection porosimetry. It was found that the rate of the activation reaction between charcoal and steam is determined by the porosity of the precursor. Pore structure results show that the steam activation of coconut shell and bamboo charcoals primarily produced micropores, thus yielding microporous activated carbon materials with just a few mesopores, even following a high burn-off of >66%. The steam activation of sawtooth oak charcoals produced mainly micropores at a low burn-off of <50% and both micropores and mesopores at a high burn-off of >50%. The steam activation of Chinese fir and Masson pine charcoals produced mainly mesopores at a burn-off of 0–80%. These mesopores were remarkably broadened to >20 nm on extending the activation time, resulting in a high vitamin B12 (VB12) adsorption capacity of ~530 mg/g. In conclusion, the raw lignocellulosic materials used as precursors have a decisive effect on the development of pore structures in activated carbon materials obtained through physical activation.
Serine/Threonine Protein Kinases as Attractive Targets for Anti-Cancer Drugs—An Innovative Approach to Ligand Tuning Using Combined Quantum Chemical Calculations, Molecular Docking, Molecular Dynamic Simulations, and Network-like Similarity Graphs
Authors: Latosińska Magdalena , Latosińska Jolanta Natalia
Published: July 2024

Serine/threonine protein kinases (CK2, PIM-1, RIO1) are constitutively active, highly conserved, pleiotropic, and multifunctional kinases, which control several signaling pathways and regulate many cellular functions, such as cell activity, survival, proliferation, and apoptosis. Over the past decades, they have gained increasing attention as potential therapeutic targets, ranging from various cancers and neurological, inflammation, and autoimmune disorders to viral diseases, including COVID-19. Despite the accumulation of a vast amount of experimental data, there is still no “recipe” that would facilitate the search for new effective kinase inhibitors. The aim of our study was to develop an effective screening method that would be useful for this purpose. A combination of Density Functional Theory calculations and molecular docking, supplemented with newly developed quantitative methods for the comparison of the binding modes, provided deep insight into the set of desirable properties responsible for their inhibition. The mathematical metrics helped assess the distance between the binding modes, while heatmaps revealed the locations in the ligand that should be modified according to binding site requirements. The Structure-Binding Affinity Index and Structural-Binding Affinity Landscape proposed in this paper helped to measure the extent to which binding affinity is gained or lost in response to a relatively small change in the ligand’s structure. The combination of the physico-chemical profile with the aforementioned factors enabled the identification of both “dead” and “promising” search directions. Tests carried out on experimental data have validated and demonstrated the high efficiency of the proposed innovative approach. Our method for quantifying differences between the ligands and their binding capabilities holds promise for guiding future research on new anti-cancer agents.
Polysaccharides as Quality Marker to Rapid Profile for Ophiocordyceps sinensis by PXRD
Authors: Wang Weien
Published: July 2024

Background: Ophiocordyceps sinensis has long been recognized as a mysterious and valuable traditional Chinese medicine but there has been little research on quality markers for O. sinensis. Purpose: This study looked into the potential of using powder X-ray diffractometry (PXRD) to analyze polysaccharides as a quality marker for O. sinensis. Study design: There were 16 different habitats of O. sinensis collected in Qinghai, Gansu, Sichuan, Yunnan, and Tibet. In addition, five different types of Cordyceps species were collected. The characteristic diffraction peaks of O. sinensis were determined and then matched with the characteristic diffraction peaks of intracellular polysaccharides obtained from O. sinensis to determine the attribution relationship of the characteristic diffraction peaks. Methods: O. sinensis powder’s X-ray diffraction pattern is determined by its composition, microcrystalline crystal structure, intramolecular bonding mechanism, and molecular configuration. After fractionation and alcohol precipitation of crude intracellular polysaccharide, mycelium crude intracellular polysaccharide (MCP) and fruiting body crude intracellular polysaccharide (FCP) were obtained and the fingerprint of O. sinensis was identified by the specific characteristic peaks of the X-ray diffraction pattern from intracellular polysaccharide. Results: The results indicated that the PXRD patterns of different populations of O. sinensis were overlaid well with 18 characteristic diffraction peaks obtained by microcrystalline diffraction. Moreover, the powder diffractograms as a fingerprint provided a practical identification of O. sinensis from other Cordyceps species. In addition, we detected that the powder diffractograms of intracellular polysaccharide MCP and MCP75 could be coupled with the PXRD of O. sinensis. Specifically, 18 characteristic diffraction peaks were identified as coming from MCP and MCP75 according to those interplanar crystal spacing, which matched well with those of PXRD of O. sinensis. Conclusions: PXRD spectra combined with an updated multivariable discriminant model were found to be an efficient and sensitive method for O. sinensis quality control. According to the findings of this study, PXRD should be further investigated for quality control assessments and plant extract selection trials.
Surface Functionalization of Bamboo via Photo-Grafting Tannic Acid for Enhanced Silver Ion Loading Properties
Authors: Xu Juan , Liu Lanxiang , Ma Jinju , Tang Baoshan , Shi Zhengjun , Zhang Hong
Published: July 2024

Photo-grafting is a gentle, simple, and precise approach to incorporating specific functional molecules for the surface functionalization of substrates. In this work, ultraviolet (UV)-induced tannic acid (TA) grafting onto the surface of bamboo was proposed as a viable strategy for functionalizing bamboo. X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared spectroscopy (FTIR) clearly indicated that TA was successfully introduced to the bamboo’s surface. The optimal conditions for the grafting reaction were determined to be 15 mM Methyl-2-benzoylbenzoate (BB), 30 mM TA, 20 min, and a pH = 8. Under these conditions, the amount of TA grafted onto the bamboo’s surface was measured to be 19.98 μg/cm2. Results from Inductively Coupled Plasma (ICP) and Energy Dispersive Spectrometer (EDS) analyses showed that the silver ion loading capacity of tannic acid-grafted bamboo was significantly improved compared to that of raw bamboo and tannic acid-impregnated bamboo. Furthermore, the presence of TA grafted on the bamboo’s surface exhibited a positive correlation with the loading of silver ions, indicating that grafted TA plays an important role in the surface functionalization of bamboo. We believe that photo-grafted TA may help generate multifunctional bamboo with diverse properties.
Enhancing Sustainable Analytical Chemistry in Liquid Chromatography: Guideline for Transferring Classical High-Performance Liquid Chromatography and Ultra-High-Pressure Liquid Chromatography Methods into Greener, Bluer, and Whiter Methods
Authors: El Deeb Sami
Published: July 2024

This review is dedicated to sustainable practices in liquid chromatography. HPLC and UHPLC methods contribute significantly to routine analytical techniques. Therefore, the transfer of classical liquid chromatographic methods into sustainable ones is of utmost importance in moving toward sustainable development goals. Among other principles to render a liquid chromatographic method green, the substitution of the organic solvent component in the mobile phase with a greener one received great attention. This review concentrates on choosing the best alternative green organic solvent to replace the classical solvent in the mobile phase for easy, rapid transfer to a more sustainable normal phase or reversed-phase liquid chromatography. The main focus of this review will be on describing the transfer of non-green to green and white chromatographic methods in an effort to elevate sustainability best practices in analytical chemistry. The greenness properties and greenness ranking, in addition to the chromatographic suitability of seventeen organic solvents for liquid chromatography, are mentioned to have a clear insight into the issue of rapidly choosing the appropriate solvent to transfer a classical HPLC or UHPLC method into a more sustainable one. A simple guide is proposed for making the liquid chromatographic method more sustainable.
Artificial Intelligence-Based Microfluidic Platform for Detecting Contaminants in Water: A Review
Authors: Zhang Yihao , Li Jiaxuan , Zhou Yu , Zhang Xu , Liu Xianhua
Published: July 2024

Water pollution greatly impacts humans and ecosystems, so a series of policies have been enacted to control it. The first step in performing pollution control is to detect contaminants in the water. Various methods have been proposed for water quality testing, such as spectroscopy, chromatography, and electrochemical techniques. However, traditional testing methods require the utilization of laboratory equipment, which is large and not suitable for real-time testing in the field. Microfluidic devices can overcome the limitations of traditional testing instruments and have become an efficient and convenient tool for water quality analysis. At the same time, artificial intelligence is an ideal means of recognizing, classifying, and predicting data obtained from microfluidic systems. Microfluidic devices based on artificial intelligence and machine learning are being developed with great significance for the next generation of water quality monitoring systems. This review begins with a brief introduction to the algorithms involved in artificial intelligence and the materials used in the fabrication and detection techniques of microfluidic platforms. Then, the latest research development of combining the two for pollutant detection in water bodies, including heavy metals, pesticides, micro- and nanoplastics, and microalgae, is mainly introduced. Finally, the challenges encountered and the future directions of detection methods based on industrial intelligence and microfluidic chips are discussed.
Redefining Accuracy: Underwater Depth Estimation for Irregular Illumination Scenes
Authors: Liu Tong , Zhang Sainan , Yu Zhibin
Published: July 2024

Acquiring underwater depth maps is essential as they provide indispensable three-dimensional spatial information for visualizing the underwater environment. These depth maps serve various purposes, including underwater navigation, environmental monitoring, and resource exploration. While most of the current depth estimation methods can work well in ideal underwater environments with homogeneous illumination, few consider the risk caused by irregular illumination, which is common in practical underwater environments. On the one hand, underwater environments with low-light conditions can reduce image contrast. The reduction brings challenges to depth estimation models in accurately differentiating among objects. On the other hand, overexposure caused by reflection or artificial illumination can degrade the textures of underwater objects, which is crucial to geometric constraints between frames. To address the above issues, we propose an underwater self-supervised monocular depth estimation network integrating image enhancement and auxiliary depth information. We use the Monte Carlo image enhancement module (MC-IEM) to tackle the inherent uncertainty in low-light underwater images through probabilistic estimation. When pixel values are enhanced, object recognition becomes more accessible, allowing for a more precise acquisition of distance information and thus resulting in more accurate depth estimation. Next, we extract additional geometric features through transfer learning, infusing prior knowledge from a supervised large-scale model into a self-supervised depth estimation network to refine loss functions and a depth network to address the overexposure issue. We conduct experiments with two public datasets, which exhibited superior performance compared to existing approaches in underwater depth estimation.
A 64 × 128 3D-Stacked SPAD Image Sensor for Low-Light Imaging
Authors: Wang Zhe , Yang Xu , Tian Na , Liu Min , Cai Ziteng , Feng Peng , Dou Runjiang , Yu Shuangming , Wu Nanjian , Liu Jian , Liu Liyuan
Published: July 2024

Low-light imaging capabilities are in urgent demand in many fields, such as security surveillance, night-time autonomous driving, wilderness rescue, and environmental monitoring. The excellent performance of SPAD devices gives them significant potential for applications in low-light imaging. This article presents a 64 (rows) × 128 (columns) SPAD image sensor designed for low-light imaging. The chip utilizes a three-dimensional stacking architecture and microlens technology, combined with compact gated pixel circuits designed with thick-gate MOS transistors, which further enhance the SPAD’s photosensitivity. The configurable digital control circuit allows for the adjustment of exposure time, enabling the sensor to adapt to different lighting conditions. The chip exhibits very low dark noise levels, with an average DCR of 41.5 cps at 2.4 V excess bias voltage. Additionally, it employs a denoising algorithm specifically developed for the SPAD image sensor, achieving two-dimensional grayscale imaging under 6 × 10−4 lux illumination conditions, demonstrating excellent low-light imaging capabilities. The chip designed in this paper fully leverages the performance advantages of SPAD image sensors and holds promise for applications in various fields requiring low-light imaging capabilities.
Piezoelectric Transducers: Complete Electromechanical Model with Parameter Extraction
Authors: Isaf Michael L. , Rincón-Mora Gabriel A.
Published: July 2024

This paper presents a complete electromechanical (EM) model of piezoelectric transducers (PTs) independent of high or low coupling assumptions, vibration conditions, and geometry. The PT’s spring stiffness is modeled as part of the domain coupling transformer, and the piezoelectric EM coupling coefficient is modeled explicitly as a split inductor transformer. This separates the coupling coefficient from the coefficient used for conversion between mechanical and electrical domains, providing a more insightful understanding of the energy transfers occurring within a PT and allowing for analysis not previously possible. This also illustrates the role the PT’s spring plays in EM energy conversion. The model is analyzed and discussed from a circuits and energy harvesting perspective. Coupling between domains and how loading affects coupled energy are examined. Moreover, simple methods for experimentally extracting model parameters, including the coupling coefficient, are provided to empower engineers to quickly and easily integrate PTs in SPICE simulations for the rapid and improved development of PT interface circuits. The model and parameter extractions are validated by comparing them to the measured response of a physical cantilever-style PT excited by regular and irregular vibrations. In most cases, less than a 5–10% error between measured and simulated responses is observed.
A Dynamic Multi-Scale Convolution Model for Face Recognition Using Event-Related Potentials
Authors: Li Shengkai , Zhang Tonglin , Yang Fangmei , Li Xian , Wang Ziyang , Zhao Dongjie
Published: July 2024

With the development of data mining technology, the analysis of event-related potential (ERP) data has evolved from statistical analysis of time-domain features to data-driven techniques based on supervised and unsupervised learning. However, there are still many challenges in understanding the relationship between ERP components and the representation of familiar and unfamiliar faces. To address this, this paper proposes a model based on Dynamic Multi-Scale Convolution for group recognition of familiar and unfamiliar faces. This approach uses generated weight masks for cross-subject familiar/unfamiliar face recognition using a multi-scale model. The model employs a variable-length filter generator to dynamically determine the optimal filter length for time-series samples, thereby capturing features at different time scales. Comparative experiments are conducted to evaluate the model’s performance against SOTA models. The results demonstrate that our model achieves impressive outcomes, with a balanced accuracy rate of 93.20% and an F1 score of 88.54%, outperforming the methods used for comparison. The ERP data extracted from different time regions in the model can also provide data-driven technical support for research based on the representation of different ERP components.
An Improved Instance Segmentation Method for Fast Assessment of Damaged Buildings Based on Post-Earthquake UAV Images
Authors: Zou Ran , Liu Jun , Pan Haiyan , Tang Delong , Zhou Ruyan
Published: July 2024

Quickly and accurately assessing the damage level of buildings is a challenging task for post-disaster emergency response. Most of the existing research mainly adopts semantic segmentation and object detection methods, which have yielded good results. However, for high-resolution Unmanned Aerial Vehicle (UAV) imagery, these methods may result in the problem of various damage categories within a building and fail to accurately extract building edges, thus hindering post-disaster rescue and fine-grained assessment. To address this issue, we proposed an improved instance segmentation model that enhances classification accuracy by incorporating a Mixed Local Channel Attention (MLCA) mechanism in the backbone and improving small object segmentation accuracy by refining the Neck part. The method was tested on the Yangbi earthquake UVA images. The experimental results indicated that the modified model outperformed the original model by 1.07% and 1.11% in the two mean Average Precision (mAP) evaluation metrics, mAPbbox50 and mAPseg50, respectively. Importantly, the classification accuracy of the intact category was improved by 2.73% and 2.73%, respectively, while the collapse category saw an improvement of 2.58% and 2.14%. In addition, the proposed method was also compared with state-of-the-art instance segmentation models, e.g., Mask-R-CNN and YOLO V9-Seg. The results demonstrated that the proposed model exhibits advantages in both accuracy and efficiency. Specifically, the efficiency of the proposed model is three times faster than other models with similar accuracy. The proposed method can provide a valuable solution for fine-grained building damage evaluation.
Suggestions and Comparisons of Two Algorithms for the Simplification of Bluetooth Sensor Data in Traffic Cordons
Authors: Özlü Beylun , Yardım Mustafa Sinan
Published: July 2024

Bluetooth sensors in intelligent transportation systems possess extensive coverage and access to a large number of identity (ID) data, but they cannot distinguish between vehicles and persons. This study aims to classify and differentiate raw data collected from Bluetooth sensors positioned between various origin–destination (i–j) points into vehicles and persons and to determine their distribution ratios. To reduce data noise, two different filtering algorithms are proposed. The first algorithm employs time series simplification based on Simple Moving Average (SMA) and threshold models, which are tools of statistical analysis. The second algorithm is rule-based, using speed data of Bluetooth devices derived from sensor data to provide a simplification algorithm. The study area was the Historic Peninsula Traffic Cord Region of Istanbul, utilizing data from 39 sensors in the region. As a result of time-based filtering, the ratio of person ID addresses for Bluetooth devices participating in circulation in the region was found to be 65.57% (397,799 person IDs), while the ratio of vehicle ID addresses was 34.43% (208,941 vehicle IDs). In contrast, the rule-based algorithm based on speed data found that the ratio of vehicle ID addresses was 35.82% (389,392 vehicle IDs), while the ratio of person ID addresses was 64.17% (217,348 person IDs). The Jaccard similarity coefficient was utilized to identify similarities in the data obtained from the applied filtering approaches, yielding a coefficient (J) of 0.628. The identity addresses of the vehicles common throughout the two date sets which are obtained represent the sampling size for traffic measurements.
A Novel Instruction Driven 1-D CNN Processor for ECG Classification
Authors: Deng Jiawen , Yang Jie , Wang Xin’an , Zhang Xing
Published: July 2024

Electrocardiography (ECG) has emerged as a ubiquitous diagnostic tool for the identification and characterization of diverse cardiovascular pathologies. Wearable health monitoring devices, equipped with on-device biomedical artificial intelligence (AI) processors, have revolutionized the acquisition, analysis, and interpretation of ECG data. However, these systems necessitate AI processors that exhibit flexible configuration, facilitate portability, and demonstrate optimal performance in terms of power consumption and latency for the realization of various functionalities. To address these challenges, this study proposes an instruction-driven convolutional neural network (CNN) processor. This processor incorporates three key features: (1) An instruction-driven CNN processor to support versatile ECG-based application. (2) A Processing element (PE) array design that simultaneously considers parallelism and data reuse. (3) An activation unit based on the CORDIC algorithm, supporting both Tanh and Sigmoid computations. The design has been implemented using 110 nm CMOS process technology, occupying a die area of 1.35 mm2 with 12.94 µW power consumption. It has been demonstrated with two typical ECG AI applications, including two-class (i.e., normal/abnormal) classification and five-class classification. The proposed 1-D CNN algorithm performs with a 97.95% accuracy for the two-class classification and 97.9% for the five-class classification, respectively.
Glove-Net: Enhancing Grasp Classification with Multisensory Data and Deep Learning Approach
Authors: Pratap Subhash , Narayan Jyotindra , Hatta Yoshiyuki , Ito Kazuaki , Hazarika Shyamanta M.
Published: July 2024

Grasp classification is pivotal for understanding human interactions with objects, with wide-ranging applications in robotics, prosthetics, and rehabilitation. This study introduces a novel methodology utilizing a multisensory data glove to capture intricate grasp dynamics, including finger posture bending angles and fingertip forces. Our dataset comprises data collected from 10 participants engaging in grasp trials with 24 objects using the YCB object set. We evaluate classification performance under three scenarios: utilizing grasp posture alone, utilizing grasp force alone, and combining both modalities. We propose Glove-Net, a hybrid CNN-BiLSTM architecture for classifying grasp patterns within our dataset, aiming to harness the unique advantages offered by both CNNs and BiLSTM networks. This model seamlessly integrates CNNs’ spatial feature extraction capabilities with the temporal sequence learning strengths inherent in BiLSTM networks, effectively addressing the intricate dependencies present within our grasping data. Our study includes findings from an extensive ablation study aimed at optimizing model configurations and hyperparameters. We quantify and compare the classification accuracy across these scenarios: CNN achieved 88.09%, 69.38%, and 93.51% testing accuracies for posture-only, force-only, and combined data, respectively. LSTM exhibited accuracies of 86.02%, 70.52%, and 92.19% for the same scenarios. Notably, the hybrid CNN-BiLSTM proposed model demonstrated superior performance with accuracies of 90.83%, 73.12%, and 98.75% across the respective scenarios. Through rigorous numerical experimentation, our results underscore the significance of multimodal grasp classification and highlight the efficacy of the proposed hybrid Glove-Net architectures in leveraging multisensory data for precise grasp recognition. These insights advance understanding of human–machine interaction and hold promise for diverse real-world applications.
ZIF-8-Based Surface Plasmon Resonance and Fabry–Pérot Sensors for Volatile Organic Compounds
Authors: Estany-Macià Anna , Fort-Grandas Ignasi , Joshi Nirav , Svendsen Winnie E. , Dimaki Maria , Romano-Rodríguez Albert , Moreno-Sereno Mauricio
Published: July 2024

This work explores the use of ZIF-8, a metal–organic framework (MOF) material, for its use in the optical detection of volatile organic compounds (VOCs) in Fabry–Pérot and surface plasmon resonance (SPR)-based sensors. The experiments have been carried out with ethanol (EtOH) and show response times as low as 30 s under VOC-saturated atmospheres, and the estimated limit of detection is below 4000 ppm for both sensor types. The selectivity towards other VOCs is relatively poor, although the dynamics of adsorption/desorption differ for each VOC and could be used for selectivity purposes. Furthermore, the hydrophobicity of ZIF-8 has been confirmed and the fabricated sensors are insensitive to this compound, which is a very attractive result for its practical use in gas sensing devices.
Effect of Data-Processing Methods on Acceleration Summary Metrics of GNSS Devices in Elite Australian Football
Authors: Ellens Susanne , Carey David L. , Gastin Paul B. , Varley Matthew C.
Published: July 2024

This study aimed to measure the differences in commonly used summary acceleration metrics during elite Australian football games under three different data processing protocols (raw, custom-processed, manufacturer-processed). Estimates of distance, speed and acceleration were collected with a 10-Hz GNSS tracking technology device from fourteen matches of 38 elite Australian football players from one team. Raw and manufacturer-processed data were exported from respective proprietary software and two common summary acceleration metrics (number of efforts and distance within medium/high-intensity zone) were calculated for the three processing methods. To estimate the effect of the three different data processing methods on the summary metrics, linear mixed models were used. The main findings demonstrated that there were substantial differences between the three processing methods; the manufacturer-processed acceleration data had the lowest reported distance (up to 184 times lower) and efforts (up to 89 times lower), followed by the custom-processed distance (up to 3.3 times lower) and efforts (up to 4.3 times lower), where raw data had the highest reported distance and efforts. The results indicated that different processing methods changed the metric output and in turn alters the quantification of the demands of a sport (volume, intensity and frequency of the metrics). Coaches, practitioners and researchers need to understand that various processing methods alter the summary metrics of acceleration data. By being informed about how these metrics are affected by processing methods, they can better interpret the data available and effectively tailor their training programs to match the demands of competition.
Consumer Culture and Its Relationship to Saudi Family Financial Planning
Authors: Bahrawi Salwa Abdel Hafeez , Aldossry Theeb Mohammed
Published: July 2024

Family financial planning involves the family understanding future needs within a specific time frame and estimating the financial resources required. Also, potential opportunities and challenges must be considered in order to address them. Consumer culture also plays a fundamental role in shaping family financial behaviors and decisions. Therefore, this study aimed to study the relationship between consumer culture and financial planning for the Saudi family. This study relied on descriptive-analytical methods to achieve its aim. The study focuses on consumer culture and its relationship with family financial planning by studying economic, personal, social, and media factors. The study sample consisted of 457 individuals from Saudi families. Among the findings of this study is that social factors play the most significant role in determining and directing consumer culture. In addition, there is a significant role in directing the consumer towards purchasing a specific product. Finally, the researchers found the effective role of financial planning by setting a comprehensive budget for all the family’s needs, which contributes to ensuring the family’s financial well-being. This study recommends the necessity of holding meetings, seminars, and programs to introduce consumer influences and priorities, how to properly deal with them, and how to benefit from them. There is also a need to increase awareness campaigns in various media regarding the necessity of rationalizing consumption and the necessity of financial planning.
Effect of pH, Temperature, and Salinity Levels on Heavy Metal Fraction in Lake Sediments
Authors: Zhao Shengnan , Zhao Yunxi , Cui Zhimou , Zhang Hui , Zhang Jinda
Published: July 2024

Heavy metals (HMs) in aquatic environments are characterized by high toxicity, a propensity for bioaccumulation, and non-degradability, and pose significant risks to biological communities. Previous studies of HMs in lakes have shown that the physical and chemical characteristics of the lake water may control both the migration of HMs in the sediments and the concentration of heavy metals in the lake water. In fact, the change in aquatic environments changes the heavy metal fraction in the sediment, which controls the release of HMs. In this paper, we investigated the effects of the pH, temperature, and salinity levels of overlying water on the chemical fraction of Cu and Zn in Wuliangsuhai Lake surface sediments. The results show that lower water pH and higher water salinity and temperature could increase Cu and Zn release from the sediment. An increase in pH led to changes in the speciation of solid fractions of Zn, namely increases in the residual fraction and decreases in the organic matter and sulfide, whereas acid-extractable and Fe-Mn oxide fractions remained largely the same. Increases in temperature and salinity led to opposite changes in the speciation of solid fractions, namely decreases in the residual fraction and increases in the organic matter and sulfide and Fe-Mn oxide fractions, whereas acid-extractable fractions remained largely the same. The effect of pH, temperature, and salinity on Cu fractions in the solids was much smaller. According to the ratio of the secondary phase to the primary phase (RSP), acidic, high-temperature, and high-salt conditions increase the release risks of Zn. Changes in water temperature have the greatest influence on the risk of Zn and Cu release from sediments, followed by the influence of salinity changes.
Observations of Tide- and Wave-Driven Groundwater Dynamics in Meso-Tidal Sandy Beach
Authors: Woussen Emilie , Sous Damien , Sénéchal Nadia
Published: July 2024

This study focuses on the non-hydrostatic groundwater dynamics of a meso-tidal sandy beach under the influence of tides and waves. A field campaign was conducted at Lacanau Beach, France, during four consecutive tide cycles in March 2022. Groundwater dynamics was monitored based on a network of buried pressure sensors. The data analysis revealed the combined influences of waves and tides on the groundwater circulation. Tidal-scale groundwater flows are predominantly seaward, primarily controlled by the head gradient resulting from a high coastal aquifer. A circulation cell develops under the swash zone and moves across the beachface following the tidal oscillations. On a daily scale per alongshore and vertical units, the observed flow is 2.5 m3.m−2.day−1, i.e., 912.5 m3.m−2.year−1. Extrapolating the present dataset, it may be expected that combined events, such as drought-induced aquifer depletion with high tides, could lead to beach-scale gradient reversal, potentially causing salinisation of the continental aquifer.
Research on the engineering calculation method of acoustic radiation of open-frame multi-cabin structure
Authors: Zhao Tengrui , Sun Hongling , Wu Xianjun
Published: July 2024

The open-frame multi-cabin structure is a common structure for deep-sea underwater vehicles. The numerical method on the vibration and acoustic radiation characteristics of the open-frame multi-cabin structure is of great significance for the prediction and control of underwater vehicles
noise radiation. In this work, an engineering calculation method based on dynamic load identification in frequency domain was proposed for the acoustic radiation of structures excited by complex vibration sources. The dynamic model of the open-frame multi-cabin structure was established by
using the finite element method (FEM). The vibration source was replaced by an equivalent load model, and the equivalent load was identified through the vibration response and the dynamic model of the structure. The key to the equivalent load identification is the selection of vibration measurement
point. A method for selection of vibration measurement point in load identification process is proposed by predicting vibration response of the accelerometer validation channel. The identified load was loaded on the structural finite element model as an input to calculate the structural dynamic
vibration and acoustic radiation. The equivalent load model was proposed for eccentric motors, and the load identification was verified on the stiffened plate structure. Using this method, the acoustic radiation of the open-frame multi-cabin structure was calculated and compared with experimental
results. The results show that the sound pressure level at the excitation frequency of the vibration source and the overall sound pressure level are in good agreement with the experimental results. This research provides a practical engineering calculation method for radiation noise prediction
of underwater vehicles.
ONOMATOPOEIA USAGE IN "AO NO HAKO" MANGA
Authors: Ibrahim Archi Maulana , Ali Mohammad
Published: July 2024

This study aims to describe the types of onomatopoeia based on the theory stated by Kindaichi (1989) and the meaning of onomatopoeia based on the theory stated by Ono (2016). The data source of this research is a manga titled "Ao no Hako" by Kōji Miura chapter 1. The method used in this research is qualitative method with descriptive analysis approach. The result of this research is the discovery of 27 data on the use of onomatopoeia which in terms of types, the most appearing type is giongo as much as 14 data, followed by giyougo 8 data, then gitaigo 4 data and the last is giseigo. Then in the meaning section that appears, there are meanings related to humans, namely 13 data Followed by 13 data related to objects.
PATIENT RIGHTS OF SOCIAL BADAN PENYELENGGARA JAMINAN SOSIAL (BPJS) PARTICIPANTS REGARDING THE FULFILLMENT OF MEDICATION NEEDS BY HOSPITALS
Authors: Situmeang Sahat Maruli Tua ,   Universitas Komputer Indonesia, Bandung, Indonesia, Mile Tiara ,   Universitas Komputer Indonesia, Bandung, Indonesia
Published: July 2024

The government provides health services through the BPJS social security program. However, complaints often arise regarding the lack of availability of medicines for BPJS patients in hospitals so that they require out-of-pocket costs. This research aims to determine the rights to provide health services and treatment for BPJS patients, as well as legal protection against fraud in hospitals. Using normative juridical methodology, this research uses descriptive analysis to describe secondary and primary facts. Data sourced from regulations, publications and websites, through literature studies. The research results show that drug services to BPJS patients are influenced by state budget limitations in administering health insurance. Based on this, it is important to confirm the availability of drugs between pharmacists and prescribing doctors and establish protocols for providing drugs, and offer profitable alternatives for patients in an effort to improve health services.
POSTER AS A PROMOTIONAL MEDIA FOR COMPUTER COURSE PROGRAM OF LKP SCTC MRANGGEN DEMAK
Authors: Kusumaningrum Dyah Ayu , Maulina Rini
Published: July 2024

Communication is one of the means of conveying information. LKP SCTC Mranggen Demak is a course and training institution that has been established since 2009. So far, the promotion carried out still relies on brochures. This research aims to analyze whether poster media is effective in increasing public interest and attention to computer courses at LKP SCTC Mranggen Demak, analyzing through poster visualization LKP SCTC Mranggen Demak, as a promotional media for computer courses. Data collection methods using literature and observation to find out what things are contained in the visual poster. The results showed that the poster still did not fulfill the elements of promotional objectives both verbal and non-verbal. The benefits of this research can be used by LKP SCTC in improving its promotional posters