bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluating the Prediction Performance of the WRF-CUACE Model in Xinjiang, China
Authors: Wulayin Yisilamu , Li Huoqing , Zhang Lei , Mamtimin Ali , Liu Junjian , Huo Wen , Liu Hongli
Published: October 2024

Dust and air pollution events are increasingly occurring around the Taklimakan Desert in southern Xinjiang and in the urban areas of northern Xinjiang. Predicting such events is crucial for the advancement, growth, and prosperity of communities. This study evaluated a dust and air pollution forecasting system based on the Weather Research and Forecasting model coupled with the China Meteorological Administration Chemistry Environment (WRF-CUACE) model using ground and satellite observations. The results showed that the forecasting system accurately predicted the formation, development, and termination of dust events. It demonstrated good capability for predicting the evolution and spatial distribution of dust storms, although it overestimated dust intensity. Specifically, the correlation coefficient (R) between simulated and observed PM10 was up to 0.85 with a mean absolute error (MAE) of 721.36 µg·m−3 during dust storm periods. During air pollution events, the forecasting system displayed notable variations in predictive accuracy across various urban areas. The simulated trends of PM2.5 and the Air Quality Index (AQI) closely aligned with the actual observations in Ürümqi. The R for simulated and observed PM2.5 concentrations at 24 and 48 h intervals were 0.60 and 0.54, respectively, with MAEs of 28.92 µg·m−3 and 29.10 µg·m−3, respectively. The correlation coefficients for simulated and observed AQIs at 24 and 48 h intervals were 0.79 and 0.70, respectively, with MAEs of 24.21 and 27.56, respectively. The evolution of the simulated PM10 was consistent with observations despite relatively high concentrations. The simulated PM2.5 concentrations in Changji and Shihezi were notably lower than those observed, resulting in a lower AQI. For PM10, the simulation–observation error was relatively small; however, the trends were inconsistent. Future research should focus on optimizing model parameterization schemes and emission source data.
Melt Pond Evolution along the MOSAiC Drift: Insights from Remote Sensing and Modeling
Authors: Wang Mingfeng , Linhardt Felix , Lion Victor , Oppelt Natascha
Published: October 2024

Melt ponds play a crucial role in the melting of Arctic sea ice. Studying the evolution of melt ponds is essential for understanding changes in Arctic sea ice. In this study, we used a revised sea ice model to simulate the evolution of melt ponds along the MOSAiC drift at a resolution of 10 m. A novel melt pond parameterization scheme simulates the movement of meltwater under the influence of gravity over a realistic sea ice topography. We evaluated different melt pond parameterization schemes based on remote sensing observations. The absolute deviation of the maximum pond coverage simulated by the new scheme is within 3%, while differences among parameterization schemes exceed 50%. Errors were found to be primarily due to the calculation of macroscopic meltwater loss, which is related to sea ice surface topography. Previous studies have indicated that sea ice with a lower surface roughness has a larger catchment area, resulting in larger pond coverage during the melt season. This study has identified an opposing mechanism: sea ice with lower surface roughness has a larger catchment area connected to the macroscopic flaws of the sea ice surface, which leads to more macroscopic drainage into the ocean and thereby a decrease in melt pond coverage. Experimental simulations showed that sea ice with 46% higher surface roughness, resulting in 12% less macroscopic drainage, exhibited a 38% higher maximum pond fraction. The presence of macroscopic flaws is related to the fragmentation of sea ice cover. As Arctic sea ice cover becomes increasingly fragmented and mobile, this mechanism will become more significant.
Comparison of the Morrison and WDM6 Microphysics Schemes in the WRF Model for a Convective Precipitation Event in Guangdong, China, Through the Analysis of Polarimetric Radar Data
Authors: Chen Xiaolong , Liu Xiaoli
Published: October 2024

Numerical weather prediction (NWP) models are indispensable for studying severe convective weather events. Research demonstrates that the outcomes of convective precipitation simulations are profoundly influenced by the choice between single or double-moment schemes for ice precipitation particles and the categorization of rimed ice. The advancement of dual-polarization radar has enriched the comparative validation of these simulations. This study simulated a convective event in Guangdong, China, from May 7 to 8, 2017, employing two bulk microphysical schemes (Morrison and WDM6) in the WRF v4.2 model. Each scheme was divided into two versions: one representing rimed ice particles as graupel (Mor_G, WDM6_G) and the other as hail (Mor_H, WDM6_H). The simulation results indicated negligible differences between the rimed ice set as graupel or hail particles, for both schemes. However, the Morrison schemes (Mor_G, Mor_H) depicted a more accurate raindrop size distribution below the 0 °C height level. A further analysis suggested that disparities between the Morrison and WDM6 schemes could be attributed to the intercept parameter (N0) setting for snow and graupel/hail in WDM6 scheme. The prescribed snow and graupel/hail N0 of WDM6 scheme might influence the melting processes, leading to a higher number concentration but a reduced mass-weighted diameter of raindrops. Reducing the intercept parameter for snow and graupel/hail in the WDM6 scheme could potentially enhance the simulation of convective precipitation. Conversely, the increase in N0 might deteriorate the precipitation simulation performance of the WDM6_G scheme, whereas the WDM6_H scheme exhibits minimal sensitivity to such changes.
Gridless DOA Estimation Method for Arbitrary Array Geometries Based on Complex-Valued Deep Neural Networks
Authors: Cao Yuan , Zhou Tianjun , Zhang Qunfei
Published: October 2024

Gridless direction of arrival (DOA) estimation methods have garnered significant attention due to their ability to avoid grid mismatch errors, which can adversely affect the performance of high-resolution DOA estimation algorithms. However, most existing gridless methods are primarily restricted to applications involving uniform linear arrays or sparse linear arrays. In this paper, we derive the relationship between the element-domain covariance matrix and the angular-domain covariance matrix for arbitrary array geometries by expanding the steering vector using a Fourier series. Then, a deep neural network is designed to reconstruct the angular-domain covariance matrix from the sample covariance matrix and the gridless DOA estimation can be obtained by Root-MUSIC. Simulation results on arbitrary array geometries demonstrate that the proposed method outperforms existing methods like MUSIC, SPICE, and SBL in terms of resolution probability and DOA estimation accuracy, especially when the angular separation between targets is small. Additionally, the proposed method does not require any hyperparameter tuning, is robust to varying snapshot numbers, and has a lower computational complexity. Finally, real hydrophone data from the SWellEx-96 ocean experiment validates the effectiveness of the proposed method in practical underwater acoustic environments.
The Effect of Tai Chi (Bafa Wubu) Training and Artificial Intelligence-Based Movement-Precision Feedback on the Mental and Physical Outcomes of Elderly
Authors: Zhang Yuze , Li Haojie , Huang Rui
Published: October 2024

(1) Background: This study aims to compare the effects of AI-based exercise feedback and standard training on the physical and mental health outcomes of older adults participating in a 4-week tai chi training program. (2) Methods: Participants were divided into three groups: an AI feedback group received real-time movement accuracy feedback based on AI and inertial measurement units (IMUs), a conventional feedback group received verbal feedback from supervisors, and a control group received no feedback. All groups trained three times per week for 8 weeks. Outcome measures, including movement accuracy, balance, grip strength, quality of life, and depression, were assessed before and after the training period. (3) Results: Compared to pre-training, all three groups showed significant improvements in movement accuracy, grip strength, quality of life, and depression. Only the AI feedback group showed significant improvements in balance. In terms of movement accuracy and balance, the AI feedback group showed significantly greater improvement compared to the conventional feedback group and the control group. (4) Conclusions: Providing real-time AI-based movement feedback during tai chi training offers greater health benefits for older adults compared to standard training without feedback.
Technologies and Solutions for Cattle Tracking: A Review of the State of the Art
Authors: Montalván Saúl , Arcos Pablo , Sarzosa Pablo , Rocha Richard Alejandro , Yoo Sang Guun , Kim Youbean
Published: October 2024

This article presents a systematic literature review of technologies and solutions for cattle tracking and monitoring based on a comprehensive analysis of scientific articles published since 2017. The main objective of this review is to identify the current state of the art and the trends in this field, as well as to provide a guide for selecting the most suitable solution according to the user’s needs and preferences. This review covers various aspects of cattle tracking, such as the devices, sensors, power supply, wireless communication protocols, and software used to collect, process, and visualize the data. The review also compares the advantages and disadvantages of different solutions, such as collars, cameras, and drones, in terms of cost, scalability, precision, and invasiveness. The results show that there is a growing interest and innovation in livestock localization and tracking, with a focus on integrating and adapting various technologies for effective and reliable monitoring in real-world environments.
Zigbee-Based Wireless Sensor Network of MEMS Accelerometers for Pavement Monitoring
Authors: Prabatama Nicky Andre , Nguyen Mai Lan , Hornych Pierre , Mariani Stefano , Laheurte Jean-Marc
Published: October 2024

In this paper, we propose a wireless sensor network for pavement health monitoring exploiting the Zigbee technology. Accelerometers are adopted to measure local accelerations linked to pavement vibrations, which are then converted into displacements by a signal processing algorithm. Each device consists of an on-board unit buried in the roadway and a roadside unit. The on-board unit comprises a microcontroller, an accelerometer and a Zigbee module that transfers acceleration data wirelessly to the roadside unit. The roadside unit consists of a Raspberry Pi, a Zigbee module and a USB Zigbee adapter. Laboratory tests were conducted using a vibration table and with three different accelerometers, to assess the system capability. A typical displacement signal from a five-axle truck was applied to the vibration table with two different displacement peaks, allowing for two different vehicle speeds. The prototyped system was then encapsulated in PVC packaging, deployed and tested in a real-life road situation with a fatigue carousel featuring rotating truck axles. The laboratory and on-road measurements show that displacements can be estimated with an accuracy equivalent to that of a reference sensor.
Fluorescence and Hyperspectral Sensors for Nondestructive Analysis and Prediction of Biophysical Compounds in the Green and Purple Leaves of Tradescantia Plants
Authors: Falcioni Renan , Oliveira Roney Berti de , Chicati Marcelo Luiz , Antunes Werner Camargos , Demattê José Alexandre M. , Nanni Marcos Rafael
Published: October 2024

The application of non-imaging hyperspectral sensors has significantly enhanced the study of leaf optical properties across different plant species. In this study, chlorophyll fluorescence (ChlF) and hyperspectral non-imaging sensors using ultraviolet-visible-near-infrared shortwave infrared (UV-VIS-NIR-SWIR) bands were used to evaluate leaf biophysical parameters. For analyses, principal component analysis (PCA) and partial least squares regression (PLSR) were used to predict eight structural and ultrastructural (biophysical) traits in green and purple Tradescantia leaves. The main results demonstrate that specific hyperspectral vegetation indices (HVIs) markedly improve the precision of partial least squares regression (PLSR) models, enabling reliable and nondestructive evaluations of plant biophysical attributes. PCA revealed unique spectral signatures, with the first principal component accounting for more than 90% of the variation in sensor data. High predictive accuracy was achieved for variables such as the thickness of the adaxial and abaxial hypodermis layers (R2 = 0.94) and total leaf thickness, although challenges remain in predicting parameters such as the thickness of the parenchyma and granum layers within the thylakoid membrane. The effectiveness of integrating ChlF and hyperspectral technologies, along with spectroradiometers and fluorescence sensors, in advancing plant physiological research and improving optical spectroscopy for environmental monitoring and assessment. These methods offer a good strategy for promoting sustainability in future agricultural practices across a broad range of plant species, supporting cell biology and material analyses.
Improving Non-Line-of-Sight Identification in Cellular Positioning Systems Using a Deep Autoencoding and Generative Adversarial Network Model
Authors: Gao Yanbiao , Deng Zhongliang , Huo Yuqi , Chen Wenyan
Published: October 2024

Positioning service is a critical technology that bridges the physical world with digital information, significantly enhancing efficiency and convenience in life and work. The evolution of 5G technology has proven that positioning services are integral components of current and future cellular networks. However, positioning accuracy is hindered by non-line-of-sight (NLoS) propagation, which severely affects the measurements of angles and delays. In this study, we introduced a deep autoencoding channel transform-generative adversarial network model that utilizes line-of-sight (LoS) samples as a singular category training set to fully extract the latent features of LoS, ultimately employing a discriminator as an NLoS identifier. We validated the proposed model in 5G indoor and indoor factory (dense clutter, low base station) scenarios by assessing its generalization capability across different scenarios. The results indicate that, compared to the state-of-the-art method, the proposed model markedly diminished the utilization of device resources and achieved a 2.15% higher area under the curve while reducing computing time by 12.6%. This approach holds promise for deployment in future positioning terminals to achieve superior localization precision, catering to commercial and industrial Internet of Things applications.
Discrepancies between Promised and Actual AI Capabilities in the Continuous Vital Sign Monitoring of In-Hospital Patients: A Review of the Current Evidence
Authors: Aagaard Nikolaj , Aasvang Eske K. , Meyhoff Christian S.
Published: October 2024

Continuous vital sign monitoring (CVSM) with wireless sensors in general hospital wards can enhance patient care. An artificial intelligence (AI) layer is crucial to allow sensor data to be managed by clinical staff without over alerting from the sensors. With the aim of summarizing peer-reviewed evidence for AI support in CVSM sensors, we searched PubMed and Embase for studies on adult patients monitored with CVSM sensors in general wards. Peer-reviewed evidence and white papers on the official websites of CVSM solutions were also included. AI classification was based on standard definitions of simple AI, as systems with no memory or learning capabilities, and advanced AI, as systems with the ability to learn from past data to make decisions. Only studies evaluating CVSM algorithms for improving or predicting clinical outcomes (e.g., adverse events, intensive care unit admission, mortality) or optimizing alarm thresholds were included. We assessed the promised level of AI for each CVSM solution based on statements from the official product websites. In total, 467 studies were assessed; 113 were retrieved for full-text review, and 26 studies on four different CVSM solutions were included. Advanced AI levels were indicated on the websites of all four CVSM solutions. Five studies assessed algorithms with potential for applications as advanced AI algorithms in two of the CVSM solutions (50%), while 21 studies assessed algorithms with potential as simple AI in all four CVSM solutions (100%). Evidence on algorithms for advanced AI in CVSM is limited, revealing a discrepancy between promised AI levels and current algorithm capabilities.
HSP-UNet: An Accuracy and Efficient Segmentation Method for Carbon Traces of Surface Discharge in the Oil-Immersed Transformer
Authors: Ji Hongxin , Liu Xinghua , Han Peilin , Liu Liqing , He Chun
Published: October 2024

Restricted by a metal-enclosed structure, the internal defects of large transformers are difficult to visually detect. In this paper, a micro-robot is used to visually inspect the interior of a transformer. For the micro-robot to successfully detect the discharge level and insulation degradation trend in the transformer, it is essential to segment the carbon trace accurately and rapidly from the complex background. However, the complex edge features and significant size differences of carbon traces pose a serious challenge for accurate segmentation. To this end, we propose the Hadamard production-Spatial coordinate attention-PixelShuffle UNet (HSP-UNet), an innovative architecture specifically designed for carbon trace segmentation. To address the pixel over-concentration and weak contrast of carbon trace image, the Adaptive Histogram Equalization (AHE) algorithm is used for image enhancement. To realize the effective fusion of carbon trace features with different scales and reduce model complexity, the novel grouped Hadamard Product Attention (HPA) module is designed to replace the original convolution module of the UNet. Meanwhile, to improve the activation intensity and segmentation completeness of carbon traces, the Spatial Coordinate Attention (SCA) mechanism is designed to replace the original jump connection. Furthermore, the PixelShuffle up-sampling module is used to improve the parsing ability of complex boundaries. Compared with UNet, UNet++, UNeXt, MALUNet, and EGE-UNet, HSP-UNet outperformed all the state-of-the-art methods on both carbon trace datasets. For dendritic carbon traces, HSP-UNet improved the Mean Intersection over Union (MIoU), Pixel Accuracy (PA), and Class Pixel Accuracy (CPA) of the benchmark UNet by 2.13, 1.24, and 4.68 percentage points, respectively. For clustered carbon traces, HSP-UNet improved MIoU, PA, and CPA by 0.98, 0.65, and 0.83 percentage points, respectively. At the same time, the validation results showed that the HSP-UNet has a good model lightweighting advantage, with the number of parameters and GFLOPs of 0.061 M and 0.066, respectively. This study could contribute to the accurate segmentation of discharge carbon traces and the assessment of the insulation condition of the oil-immersed transformer.
A Calculation Method of Bearing Balls Rotational Vectors Based on Binocular Vision Three-Dimensional Coordinates Measurement
Authors: Lu Wenbo , Xue Junpeng , Pu Wei , Chen Hongyang , Wang Kelei , Jia Ran
Published: October 2024

The rotational speed vectors of the bearing balls affect their service life and running performance. Observing the actual rotational speed of the ball is a prerequisite for revealing its true motion law and conducting sliding behavior simulation analysis. To address the need for accuracy and real-time measurement of spin angular velocity, which is also under high-frequency and high-speed ball motion conditions, a new measurement method of ball rotation vectors based on a binocular vision system is proposed. Firstly, marker points are laid on the balls, and their three-dimensional (3D) coordinates in the camera coordinate system are calculated in real time using the triangulation principle. Secondly, based on the 3D coordinates before and after the movement of the marker point and the trajectory of the ball, the mathematical model of the spin motion of the ball was established. Finally, based on the ball spin motion model, the three-dimensional vision measurement technology was first applied to the measurement of the bearing ball rotation vector through formula derivation, achieving the analysis of bearing ball rolling and sliding characteristics. Experimental results demonstrate that the visual measurement system with the frame rate of 100 FPS (frames per second) yields a measurement error within ±0.2% over a speed range from 5 to 50 RPM (revolutions per minute), and the maximum measurement errors of spin angular velocity and linear velocity are 0.25 °/s and 0.028 mm/s, respectively. The experimental results show that this method has good accuracy and stability in measuring the rotation vector of the ball, providing a reference for bearing balls’ rotational speed monitoring and the analysis of the sliding behavior of bearing balls.
Role of the Regulation Framework in Occupational Safety in Construction Excavation Works—A Survey Analysis in Turkey
Authors: Baykuş Nurdan , Chadee Aaron Anil , Yalçın Nurgül , Azamathulla Hazi Mohammad
Published: October 2024

The construction sector is known to have the highest risks of occupational accidents. A rationale for this high occurrence of occupational risks can be related to legislative requirements to enforce safe construction practices within this sector. Within the context of excavation works in Turkey, this study investigates the leading risks for any compliance shortfalls and ultimately presents recommendations to mitigate occupational accidents’ occurrences during excavation works in the construction sector. Based on a quantitative methodology, a closed-ended survey consisting of 35 questions and based on legislative requirements was applied to project managers in the construction industry, such as site supervisors, occupational safety experts, auditors, and control personnel. A sample size of 277 responses was found to have stability and validity through a reliability analysis and an exploratory factor analysis, and was used for testing statistical significance via cross-tabulation analysis and chi-square tests. The findings revealed that the major deviation of safety in excavation works from legislative requirements is executing works during adverse weather conditions. Moreover, it was also noteworthy that protective curtains did not surround the excavation sites, and most of the employees encountered ground slippage during excavation work. Therefore, the findings revealed preliminary research that will contribute positively to providing incentives for a focus on and development of relevant security and technical measures. It also provided information to protect the safety and welfare of the workers involved in excavation works. Finally, though these findings may be considered context-specific, this research can be used for comparative purposes for similar studies into the safety practices of excavation works in different countries, where generalized findings can be later derived to inform academia and practice.
The Spatial Spillover Effects of Transportation Infrastructure on Regional Economic Growth—An Empirical Study at the Provincial Level in China
Authors: Yin Fan , Qian Yongsheng , Zeng Junwei , Wei Xu
Published: October 2024

This study examines the spatial spillover effects of transportation infrastructure on regional economic growth, utilizing panel data from 31 provincial-level administrative divisions in China from 2003 to 2022. Using the spatial Durbin model (SDM) and three distinct spatial weight matrices—0–1 adjacency, spatial economic–geographical nested, and GDP-based economic distance matrices—this study comprehensively analyzes the multifaceted impacts of transportation infrastructure. The results show that transportation infrastructure significantly promotes economic growth in both local and neighboring regions across all spatial weight matrices. The total effect is most pronounced in geographically proximate regions, with a coefficient of 7.845 (p < 0.01). Regions with similar economic development levels also show strong collaborative effects, with a coefficient of 2.074 (p < 0.01), although the marginal effect of transportation infrastructure diminishes. Furthermore, adjustments in industrial structure and innovation inputs demonstrate a short-term inhibitory effect on economic growth, highlighting the need for synchronized development of transportation infrastructure alongside industrial and innovation policies. This study incorporates multi-dimensional spatial weight matrices to systematically reveal the direct and indirect impacts of transportation infrastructure on regional economies, providing essential empirical support for regional coordination and infrastructure investment policies. The findings offer valuable insights for infrastructure planning in other regions, particularly in formulating policies that promote cross-regional economic cooperation and optimize resource allocation.
Regional Economic Development, Climate Change, and Work Force in a Gender Perspective in Chile: Insights from the Input–Output Matrix
Authors: Soza-Amigo Sergio , Doussoulin Jean Pierre
Published: October 2024

Most nations fulfilled the commitment to reduce their emissions after the Paris Climate Agreement, and as a result, each nation has produced suitable plans to reach those goals. In this sense, Chile is hardly an exception. The emission multiplier product matrix (eMPM) and labor multiplier product matrix (lMPM), which are associated with the gender differences in the labor market, a state-of-the-art technique that integrates CO2 emissions with multi-region input–output table (MRIO) databases and elasticity to estimate the pollution caused by inter-industrial activity in the nation’s various north, center, and south regions, are used in this article to analyze the emissions of Chilean industries. This approach, by studying the economic territorial consistency (ETC) issue, is expected to establish a connection between each region’s production structure and interregional relationships between gender and the main industries that produce emissions. Indeed, the study aims to determine which regions foster economic development from an equitable perspective through the ETC study. The ETC in Chile depends on some variables, such as labor force, gender and CO2 emissions. The improvement in terms of emissions reduction will depend on the use of technology and the proper state regulation in line with the promises gained by Chile following the convening of COP25.
A Novel Model for Sustainable Supplier Selection in the Paint and Coating Industry
Authors: Dewi Alina Cynthia , Zagloel Teuku Yuri M. , Ardi Romadhani
Published: October 2024

Given the significance of sustainability in the current global market, doing a comprehensive and current assessment of a supplier’s sustainability might be beneficial for improving a firm’s competitiveness. This study aims to develop sustainable supplier selection criteria, examine their interrelationships, and determine the critical criteria in the paint and coating industry. This study employed a focus group discussion (FGD), the Delphi method, a decision-making trial and evaluation laboratory-based analytical network process (DANP), and a measurement of alternatives and ranking according to compromise solution (MARCOS). The findings indicated that most sub–criteria experts agreed that 11 economic sub–criteria, five environmental sub–criteria, and three social sub–criteria should be considered when selecting a sustainable supplier. The results show that the most influential criteria are environmental criteria, while the critical criteria are social criteria. In addition, “Service” (E4), “Green Material” (L3), and “Health and Safety” (S1) sub–criteria should be considered to assess the supplier because they have high relation and prominence. Globally, the top five highest weighted sub–criteria are “Respect for the Law” (S2), “Health and Safety” (S1), “Worker’s Social Rights” (S3), “Waste Management” (L5), and “Environment Management System” (L1). We practically selected 12 providers from the paint and coating sector to assess the scheme’s practicality. This work introduced a novel model for selecting a sustainable supplier that helps industries understand their core criteria and sub–criteria. This will enhance the industry’s competitiveness and sustainability by evaluating suppliers based on economic, environmental, and social criteria.
Comprehensive Review of Microbial Inoculants: Agricultural Applications, Technology Trends in Patents, and Regulatory Frameworks
Authors: dos Reis Guilherme Anacleto , Martínez-Burgos Walter Jose , Pozzan Roberta , Pastrana Puche Yenis , Ocán-Torres Diego , de Queiroz Fonseca Mota Pedro , Rodrigues Cristine , Lima Serra Josilene , Scapini Thamarys , Karp Susan Grace , Soccol Carlos Ricardo
Published: October 2024

Agriculture is essential for nutrition and the global economy, becoming increasingly important due to population growth and higher food demand. This situation boosts interest in creating bioproducts that enhance productivity sustainably while reducing environmental issues and strain on natural resources. Bioinoculants are important innovations that use beneficial microorganisms to boost crop growth and resilience. They enhance the interaction between soil and plants by solubilizing essential nutrients and producing phytohormones. This not only boosts agricultural productivity but also promotes environmentally sustainable practices by decreasing reliance on chemical fertilizers. Considering the relevance of this subject to advances in agro-industrial biotechnology, this review analyzes recent studies and patent advances on the production and use of bioinoculants, as well as their integration into agricultural practices and plant development. It also explores the dynamics of production and downstream processes on an industrial scale, regulations in different countries, and growing market demands, which is an important feature of this review. Furthermore, future perspectives for the application of bioinoculants in agro-industrial biotechnology are discussed, emphasizing the critical role that these biological agents play in advancing agricultural sustainability.
Free Speech, Green Power: The Impact of Freedom of Expression on Renewable Energy
Authors: Uzar Umut
Published: October 2024

Although there has been a growing interest in identifying the key drivers of renewable energy over the last few decades, theoretical connections and empirical evidence on the impact of freedom of expression still need to be made. Within the framework of this gap in the literature, this study tries to solve the mystery by focusing on the impact of freedom of expression on renewable energy in 20 high-income countries from 1990 to 2022. The effects of economic growth, carbon dioxide emissions, trade openness, and foreign direct investment were also examined. The evidence-based on second-generation econometric estimators such as AMG and CCEMG are consistent. Findings show that freedom of expression indicates increased renewable energy consumption. In addition, while economic growth and foreign direct investments increase renewable energy, CO2 emissions reduce renewable energy. Trade has no significant impact. The positive link between freedom of expression and renewable energy is promising for the countries involved and presents a significant win–win opportunity. Therefore, countries need to establish democratic principles.
Study of the Micro-Vibration Response and Related Vibration Isolation of Complex Traffic Load-Induced Experimental Buildings
Authors: Feng Feifan , Lu Yunjun , Chen Weiwei
Published: October 2024

In view of the high-sensitivity vibration effect of precision instrument laboratory buildings under the influence of surrounding traffic loads, field micro-vibration tests under various working conditions were carried out based on actual projects. Combined with numerical simulation, measured data served as input loads to simulate the vibration effect of various traffic loads on the floor of a building structure, and the structural vibration laws under the comprehensive action of various loads were analyzed. The vibration isolation effect of the isolation ditch on the oblique orthogonal load was investigated according to the corresponding safety index. The results show that the main frequency components of the site vibration frequency caused by various traffic loads are approximately 25 Hz and that the root-mean-square speed value is stable below VC-E, which meets the design requirements. Under the comprehensive action of multiple loads, the site structure will produce a vibration amplification effect, which is obvious when all types of loads are distributed symmetrically and the curve distribution is controlled by load factors with large amplitudes. The isolation effect of a small isolation ditch is best when it is located close to the source and the building. The depth of the isolation ditch must be greater than the maximum depth of the source to achieve better results, and the width has little influence. The effect of a small isolation trench on vertical vibration is poor, and the oblique orthogonal triaxial load has a counteracting effect on the vertical component. Thus, additional structural vibration isolation measures are needed. The research results provide a reference for engineering vibration isolation, damping measures, and structural design.
RETRACTED: ELrokh et al. On Cubic Roots Cordial Labeling for Some Graphs. Symmetry 2023, 15, 990
Authors: ELrokh Ashraf , Ismail Rashad , Abd El-hay Atef , Elmshtaye Yasser
Published: October 2024

The journal Symmetry retracts the article titled “On Cubic Roots Cordial Labeling for Some Graphs” [...]
Determination of Initial Data in the Time-Fractional Pseudo-Hyperbolic Equation
Authors: Serikbaev Daurenbek , Tokmagambetov Niyaz
Published: October 2024

We examine a time-fractional pseudo-hyperbolic equation involving positive operators. We explore the determination of initial velocity and perturbation. It is demonstrated that these initial inverse problems are ill posed. Additionally, we prove that under certain conditions, the inverse problems exhibit well-posedness properties. Our focus is on developing a theoretical framework for these initial inverse problems associated with time-fractional pseudo-hyperbolic equations, laying the groundwork for future studies on numerical algorithms to solve these problems. This investigation is crucial for understanding the fundamental behavior of the equations under various initial conditions and perturbations. By establishing a rigorous theoretical framework, we pave the way for future research to focus on practical numerical methods and simulations. Our results provide a deeper insight into the mathematical structure of time-fractional pseudo-hyperbolic equations, ensuring that future computational approaches are built on a solid theoretical foundation.
On Modular b-Metrics
Authors: Romaguera Salvador
Published: October 2024

The notions of modular b-metric and modular b-metric space were introduced by Ege and Alaca as natural generalizations of the well-known and featured concepts of modular metric and modular metric space presented and discussed by Chistyakov. In particular, they stated generalized forms of Banach’s contraction principle for this new class of spaces thus initiating the study of the fixed point theory for these structures, where other authors have also made extensive contributions. In this paper we endow the modular b-metrics with a metrizable topology that supplies a firm endorsement of the idea of convergence proposed by Ege and Alaca in their article. Moreover, for a large class of modular b-metric spaces, we formulate this topology in terms of an explicitly defined b-metric, which extends both an important metrization theorem due to Chistyakov as well as the so-called topology of metric convergence. This approach allows us to characterize the completeness for this class of modular b-metric spaces that may be viewed as an offsetting of the celebrated Caristi–Kirk theorem to our context. We also include some examples that endorse our results.
Epidemiology, Detection and Treatment of Malaria
Authors: Lee Wenn-Chyau , Lau Yee-Ling
Published: October 2024

Malaria, one of the oldest infections to affect humans, incurs significant healthcare burdens across various parts of the world [...]
MiR-181a Negatively Regulates Claudin-3 to Facilitate Lateolabrax maculatus Iridovirus Replication in Lateolabrax maculatus Astroglia Cells
Authors: Ma Yanping , Xu Jingjing , Hao Le , Wang Gang , Huang Wen , Liu Zhenxing
Published: October 2024

Lateolabrax maculatus iridovirus (LMIV) is a variant strain of red sea bream iridovirus (RSIV), causing serious economic losses in aquaculture. Claudins (CLDNs) are major components of tight junctions (TJs) forming an important line of defense against pathogens. Our pilot miRNA-mRNA joint analysis indicated the degradation of CLDN3, as well as its interaction with miR-181a during LMIV infection. To elucidate the miR-181a/CLDN3/LMIV interactions, in vitro assays were carried out on LMB-L cells. We first confirmed that LMIV infection could decrease the expression of CLDN3, accompanied by the enhancement of permeability, suggesting the dysfunction of TJs. Contrary to the inhibition of CLDN3, the activation of miR-181a was proved, presenting a negative correlation between miR-181a and CLDN3 (Pearson r = −0.773 and p < 0.01). In addition, the influence of CLDN3 on LMIV replication was analyzed by knockdown and over-expression of CLDN3. When CLDN3 was silenced in LMB-L cells with siCLDN3-623 at 9 days post transfection (dpt), LMIV copies and titers were significantly up-regulated by 1.59-fold and 13.87-fold, respectively. By contrast, LMIV replication in LMB-L cells was reduced by 60% and 71%, post transfection with pcDNA3.1-CLDN3 over-expressed plasmid at 6 dpt and 9 dpt, respectively. Ultimately, the regulatory relationship between miR-181a and CLDN3 was further validated by dual luciferase reporter assays. Taking into account the above-described results, we proposed a “miR-181a/CLDN3/LMIV” regulatory relationship. This study provides a new insight for understanding the mechanism of LMIV replication.
Shared Accountability Shaping the Destinies of Individual and Groups of Nonhuman Primates
Authors: Pomerantz Ori , Timmel Gregory Brion
Published: October 2024

At the California National Primate Research Center (CNPRC), the preferred housing for rhesus macaques involves maintaining them in complex social groups outdoors, primarily for breeding purposes. This functionally appropriate environment promotes effective coping through the expression of species-typical behaviors and important aspects of species-typical social structure, thus enabling normal animal development, higher reproductive success, and the production of high-quality biological models. Despite the benefits, social housing introduces challenges like trauma from aggressive interactions. These challenges necessitate a delicate balance between tolerating some aggression and preventing repeated targeting of individuals. Therefore, the CNPRC has established a multidisciplinary working group of behavioral management experts, veterinarians, animal care, and researchers that meets regularly to review cases of animals that may need to be removed from their social group. We discuss the criteria and decision-making processes employed to manage and mitigate aggression. We describe the systematic approach to identifying at-risk individuals and the comprehensive evaluation process that guides whether to relocate an animal from their groups or not. Considerations include the welfare of the individual and the group’s social stability. This paper provides case studies demonstrating how the working group applies these criteria and processes in practical scenarios, highlighting the complexities and challenges of such decisions.
Effects of Polyvinyl Chloride Microplastics on the Reproductive System, Intestinal Structure, and Microflora in Male and Female Mice
Authors: Yang Yang-Kai-Xin , Ge Shu-Jun , Su Qi-Ling , Chen Jin-Jun , Wu Jiang , Kang Kai
Published: October 2024

The pervasive use of plastics in numerous industrial sectors has resulted in the circulation of microplastics across diverse ecosystems and food chains, giving rise to mounting concerns regarding their potential adverse impacts on biological systems and the environment. The objective of this experiment was to investigate the distinct effects of microplastic-polyvinyl chloride (PVC) exposure on the reproductive system, intestinal tissue structure, and intestinal microbial flora of both male and female mice. A total of 24 4-week-old Kunming mice were randomly assigned to one of four groups: male control group (CM), female control group (CF), male PVC test group (PVCM), and female PVC test group (PVCF) (n = 6). The findings revealed that in terms of the reproductive system, the PVCM group exhibited an impaired testicular structure with an irregular arrangement and a significant reduction in spermatogonia, spermatocytes, and spermatozoa within the seminiferous tubules (p < 0.01). The PVCF group exhibited a notable decrease in ovarian follicles (p < 0.01), accompanied by a reduction in uterus volume, fallopian tube volume, and muscle layer thickness, all of which also decreased significantly (p < 0.01). In comparison to the control groups, exposure to PVC resulted in a reduction in the width and height of the intestinal villi, accompanied by an increase in crypt depth. This led to a significant alteration in the ratio of villus height to crypt depth (V/C) (p < 0.01). Moreover, a reduction in microbial species diversity was observed within both the PVCM and PVCF groups; additionally, it was accompanied by contrasting changes in relative abundance and functional gene profiles among the major intestinal flora constituents. In summary, the findings indicate that PVC induces damage to both male and female mice reproductive and digestive systems, further exhibiting notable sex-dependent effects on mouse intestinal microflora composition, which correlates significantly with its impact on reproductive organs.
Trabajo decente y nuevas formas de trabajo. Reflexiones y análisis para América Latina y el Caribe
Authors: Riaño Casallas Martha Isabel
Published: October 2024

Trabajo decente y crecimiento económico es uno de los Objetivos de Desarrollo Sostenible (ODS) que se espera sean alcanzados para el 2030. Y es que el trabajo ha estado en constante transformación gracias a los avances tecnológicos. En este escenario han surgido nuevas formas de trabajo en las que la tecnología tiene un rol clave al modificar las relaciones laborales y la forma en donde y como se desarrollan las tareas. Por tal razón, el objetivo de este documento es presentar reflexiones y análisis, a partir de la evidencia disponible en la literatura y utilizando datos de los indicadores de los ODS, de cómo en esa transformación del trabajo se pueden cumplir y desarrollar los principios y los elementos de la agenda de trabajo decente de la Organización Internacional del Trabajo (OIT). El documento está dividido en seis secciones. La primera, introductoria a la problemática y al contexto actual del trabajo. En el siguiente apartado, por medio de un análisis bibliométrico, se presentan los antecedentes, evolución e indicadores del trabajo decente. La tercera sección presenta el estado del trabajo decente en América Latina y el Caribe a partir de los indicadores estandarizados por la OIT. Posteriormente, se presenta el marco en el que se unifican los conceptos y tipologías de las nuevas formas de trabajo. Con estos insumos, en la quinta sección se exponen los resultados de una revisión de alcance o scoping review, en la que se identifican los estudios empíricos más relevantes que han analizado la relación entre el trabajo decente y las nuevas formas de trabajo. Finalmente, el último apartado contiene las conclusiones y recomendaciones para incorporar los principios del trabajo decente en las nuevas formas de trabajo, y que permitan cumplir con el objetivo de un trabajo decente productivo para todos.
Automatic estimation of the wind turbine noise with recurrent neural networks
Authors: RKHISS ABDELAZYZ , FINEZ Arthur , GLOAGUEN Jean Rémy , MAILLARD Julien , VASILE Gabriel
Published: October 2024

There is growing interest in the development of renewable energies, particularly wind power. However, wind turbines generate noise that can affect the sound environment of nearby residents. This study focuses on the isolation of wind farm noise (WFN) from the surrounding ambient noise.
Our method is based on a Recurrent Neural Network (RNN) Architecture that captures temporal dependencies in the acoustic signal. This proposal is compared to Non-Negative Matrix Factorization (NMF) that has shown first promising results on a previous study on simulated sound scenes. Our approach
relies on Long Short Term Memory (LSTM) RNN, conducted using an end-to-end trained model and a Gated Recurrent Unit (GRU). The training and testing dataset is constructed by superimposing measured background noise with synthesized wind turbine noise, effectively simulating realistic environmental
conditions. This study aims to reduce the acoustic impact of wind turbines on communities and attempt to control turbine operation using advanced machine learning techniques.
Numerical study of shell-side flow-induced noise characteristics of staggered straight tube bundle heat exchanger under different inflow conditions
Authors: HAN Wang , CAO Yipeng , LIU Chen , XU Pan , SUN Kailang
Published: October 2024

This paper presents a numerical study on the shell-side flow noise characteristics of staggered straight tube bundle heat exchangers under varying inflow conditions. A three-dimensional numerical model of a compactly arranged staggered straight tube bundle heat exchanger was established.
To validate the numerical model, a feasibility study using a cylindrical flow model was conducted. Subsequently, the large eddy simulation (LES) method was employed to investigate the unsteady shell-side flow field characteristics, and the vortex characteristics of the flow field were obtained
based on the Q-criterion. Finally, the acoustic finite element method (FEM) was utilized to calculate and analyze the noise characteristics at the inlet and outlet positions of the heat exchanger shell side. The results show that the inflow angle has an influence on both the flow field and
the acoustic field of the heat exchanger shell side. As the inflow angle increases, the flow stability decreases, horseshoe vortices replace boundary layer vortices, and the decrease in fluctuating pressure leads to a reduction in flow noise. Analysis of the sound pressure level spectrum indicates
a line spectral characteristic at low frequencies, with high-frequency components experiencing rapid attenuation.