bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparison of Agonist Activity between CB1 and CB2 Receptors with Orthosteric Site Mutations
Authors: Brust Christina A. , Swanson Matthew A. , Tsoutsouvas Christos Iliopoulos , Dimova Snezana T. , Dang Vuong Q. , Stahl Edward L. , Ho Jo-Hao , Nikas Spyros P. , Makriyannis Alexandros , Bohn Laura M.
Published: August 2024

Human endocannabinoid signaling is primarily mediated by the cannabinoid receptors, CB1 and CB2, which are G protein-coupled receptors (GPCRs). These receptors have been linked to a variety of physiological processes and are being pursued as prospective drug targets due to their potential in treating pain and inflammation. However, because of their homology and shared signaling mechanisms, investigating the individual physiological roles of these receptors and designing subtype-selective ligands has been challenging. Using active-state CB1 and CB2 structures as guides, homologous residues within the orthosteric pocket of each receptor were mutated to alanine to test whether they equally impair CB1 and CB2 activity in response to two high-affinity, nonselective agonists (CP55,940 and AM12033). Interestingly, mutating the Y5.39 position impairs CB1 but not CB2 function. Conversely, mutating residue C6.47 improves CB1 but impairs CB2 signaling. The F7.35A mutation leads to a decrease in CP55,940 potency at CB1 and impairs internalization; however, AM12033 gains potency and promotes CB1 internalization. In CB2, mutation of F7.35A decreases the potency of CP55,940 and neither agonist induces internalization. These observations provide some insight into functional sensitivity of CB1 and CB2 to different agonists when conserved residues are mutated in the orthosteric pocket.
Predicting Particle Size and Soil Organic Carbon of Soil Profiles Using VIS-NIR-SWIR Hyperspectral Imaging and Machine Learning Models
Authors: Oliveira Karym Mayara de , Gonçalves João Vitor Ferreira , Furlanetto Renato Herrig , Oliveira Caio Almeida de , Mendonça Weslei Augusto , Haubert Daiane de Fatima da Silva , Crusiol Luís Guilherme Teixeira , Falcioni Renan , Oliveira Roney Berti de , Reis Amanda Silveira , Ecker Arney Eduardo do Amaral , Nanni Marcos Rafael
Published: August 2024

Modeling spectral reflectance data using machine learning algorithms presents a promising approach for estimating soil attributes. Nevertheless, a comprehensive investigation of the most effective models, parameters, wavelengths, and data acquisition techniques is essential to ensure optimal predictive accuracy. This work aimed to (a) explore the potential of the soil spectral signature obtained in different spectral bands (VIS-NIR, SWIR, and VIS-NIR-SWIR) and, by using hyperspectral imaging and non-imaging sensors, in the predictive modeling of soil attributes; and (b) analyze the accuracy of different ML models in predicting particle size and soil organic carbon (SOC) applied to the spectral signature of different spectral bands. Six soil monoliths, located in the central north region of Parana, Brazil, were collected and scanned via hyperspectral cameras (VIS-NIR camera and SWIR camera) and spectroradiometer (VIS-NIR-SWIR) in the laboratory. The spectral signature of the soils was analyzed and subsequently applied to ML models to predict particle size and SOC. Each set of data obtained by the different sensors was evaluated separately. The algorithms used were k-nearest neighbors (KNN), support vector machine (SVM), random forest (RF), linear regression (LR), artificial neural network (NN), and partial least square regression (PLSR). The most promising predictive performance was observed for the complete VIS-NIR-SWIR spectrum, followed by SWIR and VIS-NIR. Meanwhile, KNN, RF, and NN models were the most promising algorithms in estimating soil attributes for the dataset obtained from both sensors. The general mean R2 (determination coefficient) values obtained using these models, considering the different spectral bands evaluated, were around 0.99, 0.98, and 0.97 for sand prediction, and around 0.99, 0.98, and 0.96 for clay prediction. The lower performances, obtained for the datasets from both sensors, were observed for silt and SOC, with R2 results between 0.40 and 0.59 for these models. KNN demonstrated the best predictive performance. Integrating effective ML models with robust sample databases, obtained by advanced hyperspectral imaging and spectroradiometers, can enhance the accuracy and efficiency of soil attribute prediction.
Transformer-Based Reinforcement Learning for Multi-Robot Autonomous Exploration
Authors: Chen Qihong , Wang Rui , Lyu Ming , Zhang Jie
Published: August 2024

A map of the environment is the basis for the robot’s navigation. Multi-robot collaborative autonomous exploration allows for rapidly constructing maps of unknown environments, essential for application areas such as search and rescue missions. Traditional autonomous exploration methods are inefficient due to the repetitive exploration problem. For this reason, we propose a multi-robot autonomous exploration method based on the Transformer model. Our multi-agent deep reinforcement learning method includes a multi-agent learning method to effectively improve exploration efficiency. We conducted experiments comparing our proposed method with existing methods in a simulation environment, and the experimental results showed that our proposed method had a good performance and a specific generalization ability.
User-Centric Cell-Free Massive MIMO with Low-Resolution ADCs for Massive Access
Authors: Kim Jin-Woo , Kim Hyoung-Do , Shin Kyung-Ho , Park Sang-Wook , Seo Seung-Hwan , Choi Yoon-Ju , You Young-Hwan , Song Hyoung-Kyu
Published: August 2024

This paper proposes a heuristic association algorithm between access points (APs) and user equipment (UE) in user-centric cell-free massive multiple-input-multiple-output (MIMO) systems, specifically targeting scenarios where UEs share the same frequency and time resources. The proposed algorithm prevents overserving APs and ensures the connectivity of all UEs, even when the number of UEs is significantly greater than the number of APs. Additionally, we assume the use of low-resolution analog-to-digital converters (ADCs) to reduce fronthaul capacity. While realistic massive access scenarios, such as those in Internet-of-Things (IoT) environments, often involve hundreds or thousands of UEs per AP using multiple access techniques to allocate different frequency and time resources, our study focuses on scenarios where UEs within each AP cluster share the same frequency and time resources to highlight the impact of pilot contamination in dense network environments. The proposed algorithm is validated through simulations, confirming that it guarantees the connection of all UEs and prevents overserving APs. Furthermore, we analyze the required fronthaul capacity based on quantization bits and confirm that the proposed algorithm outperforms existing algorithms in terms of SE and average SE performance for UEs.
The Focusing Properties of a Modular All-Metal Lens in the Near-Field Region
Authors: Zhang Qifei , Guo Linyan , Li Yunqing , Wang Chen
Published: August 2024

This article proposes a modular and passive all-metal lens to achieve near-field focusing with adjustable focus. The proposed lens consists of all-metal units with the phase coverage range exceeding 360°, and the arrangement of units is guided by the phase compensation method. Specifically, using the strategy of module unit synthesis, the arrangement of lens units under different focuses can be assembled arbitrarily, which reduces the production costs by 39.3% and improves the freedom of lens design. The simulation and experimental results show that the lens exhibits excellent focusing properties and freely changes the position of the expected focus (0.30 m–0.75 m). Therefore, the modular all-metal lens designed in this article has the characteristics of high transparency and a high degree of freedom, which can provide low-cost and lightweight solutions for various applications in the field of antennas, such as near-field target detection, microwave imaging, biomedicine, and so on.
Adaptive Navigation Performance Evaluation Method for Civil Aircraft Navigation Systems with Unknown Time-Varying Sensor Noise
Authors: Dai Yuting , Lai Jizhou , Zhang Qieqie , Li Zhimin , Liu Rui
Published: August 2024

During civil aviation flights, the aircraft needs to accurately monitor the real-time navigation capability and determine whether the onboard navigation system performance meets the required navigation performance (RNP). The airborne flight management system (FMS) uses actual navigation performance (ANP) to quantitatively calculate the uncertainty of aircraft position estimation, and its evaluation accuracy is highly dependent on the position estimation covariance matrix (PECM) provided by the airborne integrated navigation system. This paper proposed an adaptive PECM estimation method based on variational Bayes (VB) to solve the problem of ANP misevaluation, which is caused by the traditional simple ANP model failing to accurately estimate PECM under unknown time-varying noise. Combined with the 3D ANP model proposed in this paper, the accuracy of ANP evaluation can be significantly improved. This enhancement contributes to ensured navigation integrity and operational safety during civil flight.
Errors in Estimating Lower-Limb Joint Angles and Moments during Walking Based on Pelvic Accelerations: Influence of Virtual Inertial Measurement Unit’s Frontal Plane Misalignment
Authors: Inai Takuma , Kobayashi Yoshiyuki , Sudo Motoki , Yamashiro Yukari , Ueda Tomoya
Published: August 2024

The accurate estimation of lower-limb joint angles and moments is crucial for assessing the progression of orthopedic diseases, with continuous monitoring during daily walking being essential. An inertial measurement unit (IMU) attached to the lower back has been used for this purpose, but the effect of IMU misalignment in the frontal plane on estimation accuracy remains unclear. This study investigated the impact of virtual IMU misalignment in the frontal plane on estimation errors of lower-limb joint angles and moments during walking. Motion capture data were recorded from 278 healthy adults walking at a comfortable speed. An estimation model was developed using principal component analysis and linear regression, with pelvic accelerations as independent variables and lower-limb joint angles and moments as dependent variables. Virtual IMU misalignments of −20°, −10°, 0°, 10°, and 20° in the frontal plane (five conditions) were simulated. The joint angles and moments were estimated and compared across these conditions. The results indicated that increasing virtual IMU misalignment in the frontal plane led to greater errors in the estimation of pelvis and hip angles, particularly in the frontal plane. For misalignments of ±20°, the errors in pelvis and hip angles were significantly amplified compared to well-aligned conditions. These findings underscore the importance of accounting for IMU misalignment when estimating these variables.
Affordable 3D Orientation Visualization Solution for Working Class Remotely Operated Vehicles (ROV)
Authors: Kasno Mohammad Afif , Yahaya Izzat Nadzmi , Jung Jin-Woo
Published: August 2024

ROV operators often encounter challenges with orientation awareness while operating underwater, primarily due to relying solely on 2D camera feeds to manually control the ROV robot arm. This limitation in underwater visibility and orientation awareness, as observed among Malaysian ROV operators, can compromise the accuracy of arm placement, and pose a risk of tool damage if not handle with care. To address this, a 3D orientation monitoring system for ROVs has been developed, leveraging measurement sensors with nine degrees of freedom (DOF). These sensors capture crucial parameters such as roll, pitch, yaw, and heading, providing real-time data on the ROV’s position along the X, Y, and Z axes to ensure precise orientation. These data are then utilized to generate and process 3D imaging and develop a corresponding 3D model of the operational ROV underwater, accurately reflecting its orientation in a visual representation by using an open-source platform. Due to constraints set by an agreement with the working class ROV operators, only short-term tests (up to 1 min) could be performed at the dockyard. A video demonstration of a working class ROV replica moving and reflecting in a 3D simulation in real-time was also presented. Despite these limitations, our findings demonstrate the feasibility and potential of a cost-effective 3D orientation visualization system for working class ROVs. With mean absolute error (MAE) error less than 2%, the results align with the performance expectations of the actual working ROV.
Lightweight Single Image Super-Resolution via Efficient Mixture of Transformers and Convolutional Networks
Authors: Xiao Luyang , Liao Xiangyu , Ren Chao
Published: August 2024

In this paper, we propose a Local Global Union Network (LGUN), which effectively combines the strengths of Transformers and Convolutional Networks to develop a lightweight and high-performance network suitable for Single Image Super-Resolution (SISR). Specifically, we make use of the advantages of Transformers to provide input-adaptation weighting and global context interaction. We also make use of the advantages of Convolutional Networks to include spatial inductive biases and local connectivity. In the shallow layer, the local spatial information is encoded by Multi-order Local Hierarchical Attention (MLHA). In the deeper layer, we utilize Dynamic Global Sparse Attention (DGSA), which is based on the Multi-stage Token Selection (MTS) strategy to model global context dependencies. Moreover, we also conduct extensive experiments on both natural and satellite datasets, acquired through optical and satellite sensors, respectively, demonstrating that LGUN outperforms existing methods.
Eddy Current-Based Identification and Depth Investigation of Microdefects in Steel Filaments
Authors: Tran Kim Sang , Shirinzadeh Bijan , Smith Julian
Published: August 2024

In the field of quality control, the critical challenge of analyzing microdefects in steel filament holds significant importance. This is particularly vital, as steel filaments serve as reinforced fibers in the use and applications within various component manufacturing industries. This paper addresses the crucial requirement of identifying and investigating microdefects in steel filaments. Eddy current signals are used for the identification of microdefects, and an in-depth investigation is conducted. The core objective is to establish the relationship between the depth of defects and the signals detected through the eddy current sensing principle. The threshold of the eddy current instrument was set at 10%, corresponding to a created depth of 20 µm, to identify defective specimens. A total of 30 defective samples were analyzed, and the phase angles between the experimental and theoretical results were compared. The depths of defects ranged from 20 to 60 µm, with one sample having a depth exceeding 75 µm. The calculated threshold of 10.18% closely aligns with the set threshold of 10%, with a difference of only 1.77%. The resulting root mean square error (RMSE) was found to be 10.53 degrees, equivalent to 3.49 µm for the difference in depth and phase between measured results and estimated results. This underscores the methodology’s accuracy and its applicability across diverse manufacturing industries.
Design and Implementation of a Generalized Safety Fault Diagnosis System for China Space Station Scientific Experimental Rack
Authors: Wang Yifeng , Zou Tianji , Guo Lin , Zhang Chenchen , Zhang Lu
Published: August 2024

As astronauts stay in the China Space Station for a long time during the operation phase, how to ensure the long-term safety of the scientific experimental rack (SER) in the field of space application is a problem that needs to be solved urgently. Each SER in the field of space station applications is a complex system that faces risks from different hazards. At present, there is no generalized monitoring and diagnosis system for the common risks faced by the SER. In this paper, a generalized safety fault diagnosis system is proposed to ensure the long-term safe and stable work of SERs in orbit, considering the actual risks faced by the SER. With the design of a generalized main control board, a measurement and control board, and an SSPC (solid-state power controller) board, the software and hardware cooperate to realize the acquisition of various physical quantities, data processing, power supply and distribution management, and other functions. Combined with relevant fault detection algorithms, the real-time detection and diagnosis of the relevant risks, abnormality warnings, and fault disposal operations are realized, which can effectively ensure the safety of the payloads in the field of space application, astronauts, and the space-station system.
A Precise Pulmonary Airway Tree Segmentation Method Using Quasi-Spherical Region Constraint and Tracheal Wall Gap Sealing
Authors: Hu Zhanming , Ren Tonglong , Ren Meirong , Cui Wentao , Dong Enqing , Xue Peng
Published: August 2024

Accurate segmentation of the pulmonary airway tree is crucial for diagnosing lung diseases. To tackle the issues of low segmentation accuracy and frequent leaks in existing methods, this paper proposes a precise segmentation method using quasi-spherical region-constrained wavefront propagation with tracheal wall gap sealing. Based on the characteristic that the surface formed by seed points approximates the airway cross-section, the width of the unsegmented airway is calculated, determining the initial quasi-spherical constraint region. Using the wavefront propagation method, seed points are continuously propagated and segmented along the tracheal wall within the quasi-spherical constraint region, thus overcoming the need to determine complex segmentation directions. To seal tracheal wall gaps, a morphological closing operation is utilized to extract the characteristics of small holes and locate low-brightness tracheal wall gaps. By filling the CT values at these gaps, the method seals the tracheal wall gaps. Extensive experiments on the EXACT09 dataset demonstrate that our algorithm ranks third in segmentation completeness. Moreover, its performance in preventing airway leaks is significantly better than the top-two algorithms, effectively preventing large-scale leak-induced spread.
Expert Evaluation of the Significance of Criteria for Electric Vehicle Deployment: A Case Study of Lithuania
Authors: Sivilevičius Henrikas , Žuraulis Vidas , Bražiūnas Justas
Published: August 2024

This study presents the hierarchical structure of 50 sub-criteria divided into 7 main criteria for the assessment of electric vehicle (EV) deployment. Two options, Average Rank Transformations and Analytic Hierarchy Process methods, were applied in determining the local weights of the sub-criteria. The sufficient compatibility of expert opinions was accomplished using the averages of the ranks of the main criteria and sub-criteria as the result of solving the problem. The averages of the local weights were calculated employing three Multiple Criteria Decision-Making methods that increased the reliability of the research results. Based on this, the global weights and priorities of the sub-criteria were evaluated. The experts suppose that EV deployment at the national level is mainly affected by the higher cost of manufacturing and purchasing EVs, the application of financial incentives for purchasing EVs, the lack of exhausted gasses, the installation of fast charging points, and the absence of infrastructure in the five largest cities nationwide. The obtained results demonstrate that out of 50 sub-criteria, the cumulative global weight of the 10 most important sub-criteria (mainly based in economics) amounts to more than 35%, whereas that of the 22 most important sub-criteria have a weight above the average (0.2), reaching approximately 65%. The findings can be put into practice by state decision makers of EV deployment.
Environmental Protection Tax Reform in China: A Catalyst or a Barrier to Total Factor Productivity? An Analysis through a Quasi-Natural Experiment
Authors: Wang Jingjing , Pan Yuhan , Tang Decai
Published: August 2024

China’s 2018 environmental protection tax (EPT) reform was introduced in response to increasing concerns about environmental degradation. It aimed to use fiscal policy to enhance environmental governance while fostering economic productivity. This study employs a difference-in-differences approach to analyze panel data from publicly listed companies between 2009 and 2019. It examines the reform’s influence on total factor productivity (TFP) in pollution-intensive industries, addressing both environmental and economic objectives. The results reveal that the tax reform significantly enhances TFP, acting as a robust catalyst for economic growth rather than a barrier. This effect is particularly strong in state-owned enterprises and those with less-severe financing constraints. Mechanism analysis indicates that the reform boosts TFP through the promotion of green innovations and alleviation of financing constraints. These findings provide empirical evidence at the micro-level of the reform’s efficacy in promoting sustainable business practices. The study offers insights for future environmental tax policies in China and underscores the necessity of aligning environmental and economic strategies to achieve sustainable development.
Analysis of the Prices of Recycling Byproducts Obtained from Mechanical–Biological Treatment Plants in the Valencian Community (Spain)
Authors: Rodrigo-Ilarri Javier , Rodrigo-Clavero María-Elena
Published: August 2024

Municipal solid waste (MSW) management in Spain, particularly in the Valencian Community, heavily relies on mechanical–biological treatment (MBT) plants followed by landfill disposal. These MBT facilities utilize mechanical processes like shredding, screening, and sorting to segregate recyclables (metals, plastics, paper) from organic material and other nonrecyclables. While public funding supports these plants, private entities manage them through complex, long-term concession contracts. This structure restricts access to crucial data on the sale prices of the byproducts generated during MBT. Publicly available information on relevant company and administration websites is typically absent, hindering transparency surrounding byproduct revenue. This study addresses this gap by analyzing 2012’s available data on revenues obtained from byproduct sales following mechanical treatment at MBT plants within the Valencian Community and comparing them with Spanish national data. This research revealed a significant finding—the statistical distribution of average prices obtained from Ecoembes auctions in the Valencian Community mirrored the corresponding distribution for prices calculated from auctions conducted in other Spanish regions. This suggests a potential uniformity in byproduct pricing across the country. It has also been found that none of the analyzed price distributions exhibited a normal (Gaussian) distribution. The findings also highlight the need for alternative pricing models that move beyond simple averages and account for regional variations and outliers. As actual prices are not available after 2012, this lack of transparency poses a challenge in comprehensively evaluating the economic viability of MBT plants. Furthermore, it raises concerns regarding whether the revenue generated from byproduct sales reflects fair market value. Limited public access to this information can potentially indicate conflicts of interest or inefficiencies within the waste management system.
Distribution of Heavy Metals in the Surrounding Mining Region of Kizhnica in Kosovo
Authors: Zeqiri Lavdim , Ukić Šime , Ćurković Lidija , Djokic Jelena , Kerolli Mustafa Mihone
Published: August 2024

This study investigated the distribution of heavy metals in agricultural soils in the vicinity of three large mining landfills of the Kizhnica mine in the Republic of Kosovo. The mining sector is one of the most important sectors of Kosovo’s economic development, and the Kizhnica mine is one of the most important ore producers in Kosovo. Besides the positive aspects, the development of production also has some negative side effects, such as the generation of industrial waste and the possible contamination of surrounding areas, including agricultural land. Therefore, ten sampling sites were selected in the vicinity of the Kizhnica mine. These sites were characterized and assessed as the most important due to the anthropogenic impact of mineral processing and open-tailing waste deposits in Kizhnica. The concentration of Pb, Zn, Cu, As, Cd, Ni, Mn and Sb in the selected samples was determined using inductively coupled plasma–optical emission spectrometry. The data obtained were used to create geochemical maps and calculate the contamination factor, pollution load index and geoaccumulation index. Cluster analysis, Pearson correlation coefficient and air spatial distribution patterns using the air dispersion model were used to evaluate within the area. The results showed that heavy metal levels are influenced by the anthropogenic nature of pollution, confirming a current ecological threat from mining activities in the region. In order to improve waste management, reduce the hazardous impacts of mining and contribute to the sustainable development of the region, the potential reuse of the deposited waste material in the construction industry is proposed.
Sustainable Transportation: Exploring the Node Importance Evolution of Rail Transit Networks during Peak Hours
Authors: Zhang Chen , Liang Yichen , Tian Tian , Peng Peng
Published: August 2024

The scientific and rational assessment of the evolution of node importance in rail transit line networks is important for the sustainability of transportation systems. Based on the complex network theory, this study develops a weighted network model using the Space L method. It first considers the network topology, the mutual influence of neighboring nodes of the transportation system, and the land use intensity in the station influence domain to construct a comprehensive index evaluation system of node importance. It then uses the covariance-weighted principal component analysis algorithm to more comprehensively evaluate the node importance evolution mechanism and analyzes the similarity and difference of the sorting set by adopting three different methods. The interaction mechanism between the distribution of important nodes and the evolution of land use intensity is explored in detail based on the fractal dimension theory. The Xi’an rail transit network is considered an example of qualitative and quantitative analysis. The obtained results show that the importance of nodes varies at different times of the day and the complexity of the morning peak is more prominent. Over time, articulated fragments with significance values greater than 0.5 are formed around the station, which are aligned with the direction of urban development, creating a sustainable mechanism of interaction. As the network’s crucial nodes in the center of gravity increase and the southern network expands, along with the increased intensity of the city’s land utilization, the degree of alignment in evolution becomes increasingly substantial. Different strategies for attaching the network, organized based on the size of Si can lead to the rapid damage of the network (reducing it to 0.2). The identification of crucial nodes highlighted in this paper serves as an effective representation of the functional characteristics of the nodes in transportation networks. The results obtained can provide a reference for the operation and management of metro systems and further promote the sustainable development of transportation networks.
Walkability Indices—The State of the Art and Future Directions: A Systematic Review
Authors: Venerandi Alessandro , Mellen Hal , Romice Ombretta , Porta Sergio
Published: August 2024

This systematic review aims to illustrate the state of the art of walkability indices and future research directions. A comprehensive search in the general Google database and Google Scholar identified a total of 45 records published between 2005 and 2023. Using a selection process based on the PRISMA model, 32 records were identified as meeting the inclusion criteria. These are organized incrementally, highlighting their novelty relative to preceding studies, and divided into sectors of prevalent application. The 5Ds theory provides a first contribution by identifying walkability metrics based on proximity to amenities, land use diversity, and density. Recent advancements, leveraging GIS systems and open data, have expanded such metrics to include green spaces, footpath design, and noise pollution. However, these developments remain largely tied to the catchment area logic and offer coarse descriptions of the built environment’s morphological structure, often lacking justification for metric selection and weighting. To address these shortcomings, future research should use more detailed descriptions of urban form, balance metric comprehensiveness with data availability, employ robust methods for metric selection, and explore alternative weighting techniques based on cognitive and emotional responses to urban settings. These efforts are crucial for advancing the understanding and measurement of walkability in the context of the compact city and place-making paradigms.
Driving Analysis and Multi Scenario Simulation of Ecosystem Carbon Storage Changes Based on the InVEST-PLUS Coupling Model: A Case Study of Jianli City in the Jianghan Plain of China
Authors: Shao Jun , Wang Yuxian , Tang Mingdong , Hu Xinran
Published: August 2024

The carbon storage capacity of terrestrial ecosystems serves as a crucial metric for assessing ecosystem health and their resilience to climate change. By evaluating the effects of land use alterations on this storage, carbon management strategies can be improved, thereby promoting carbon reduction and sequestration. While county-level cities are pivotal to ecological conservation and high-quality development, they often face developmental challenges. Striking a balance between economic growth and meeting peak carbon emissions and carbon neutrality objectives is particularly challenging. Consequently, there is an urgent need to bolster research into carbon storage management. The study focuses on Jianli City, employing the InVEST model and land use data to examine the response patterns of land use changes and terrestrial system carbon storage from 2000 to 2020. Using the PLUS model, the study simulated the land use and carbon storage in Jianli City for the year 2035 under three scenarios: Natural Development scenario, Urban Expansion scenario, and Ecology and food security scenario. Our findings indicate the following: (1) Between 2000 and 2020, significant shifts in land use were observed in Jianli City. These changes predominantly manifested as the interchange between Cropland and Water areas and the enlargement of impervious surfaces, leading to a decrease of 691,790.27 Mg in carbon storage. (2) Under the proposed scenarios—Natural Development scenario, Urban Expansion scenario, and Ecology and food security scenario—the estimated carbon storage capacities in Jianli City were 39.95 Tg, 39.90 Tg, and 40.14 Tg, respectively. When compared with the 2020 data, all these estimates showed an increase. In essence, our study offers insights into optimizing land use structures from a carbon storage standpoint to ensure stability in Jianli’s carbon storage levels while mitigating the risks associated with carbon fixation. This has profound implications for the harmonious evolution of regional eco-economies.
Formation of Symmetric Gradient Microstructure in Carbon Steel Bars
Authors: Volokitina Irina , Volokitin Andrey , Makhmutov Bolat
Published: August 2024

In recent years, severe plastic deformation has attracted the most attention as a way to improve the mechanical properties of steel bars. Obtaining ultrafine grains and nanostructures in such bars leads to a strong increase in strength properties but strongly reduces their plastic properties. This study shows that the formation of a gradient microstructure allows simultaneous improvement in the strength and plastic properties of carbon steel bars, taking into account the symmetry of the microstructure distribution from the center of machining. A new combined technology is proposed to obtain such a microstructure. This technology consists of drawing bars from medium carbon steel on a radial-displacement rolling mill and carrying out subsequent drawing. Steel bars with a diameter of 30 mm were strained in three passes to a diameter of 16 mm at room temperature. The results show that the average value of microhardness in the center, neutral, and surface areas for the three straining cycles were 1890 MPa, 2335 MPa, and 2920 MPa, respectively. This symmetrical distribution of microhardness confirms the gradient microstructure. Strength characteristics also increased almost twofold: the yield strength increased from 330 to 735 MPa, and the ultimate strength increased from 600 MPa to 1025 MPa. Relative elongation decreased from 18 to 14 MPa, and relative reduction decreased from 40 to 31%, but remained at a fairly good level for AISI 1045 steel. The validity of all results was confirmed through numerous experiments using a set of traditional and modern research methods, which included optical, scanning, and transmission microscopy. EBSD analysis allowed precise positioning of the field of vision for studying microstructural changes across the entire bar cross-section. All of these methods used together, including tensile testing of the mechanical properties and the fractographic method, allow us to assess changes in microhardness and the reproduction of results.
Towards a Warm Holographic Equation of State by an Einstein–Maxwell-Dilaton Model
Authors: Zöllner Rico , Kämpfer Burkhard
Published: August 2024

The holographic Einstein–Maxwell-dilaton model is employed to map state-of-the-art lattice QCD thermodynamics data from the temperature (T) axis towards the baryon–chemical potential (μB) axis and aims to gain a warm equation of state (EoS) of deconfined QCD matter which can be supplemented with a cool and confined part suitable for subsequent compact (neutron) star (merger) investigations. The model exhibits a critical end point (CEP) at TCEP=O(100) MeV and μBCEP=500…700 MeV with an emerging first-order phase transition (FOPT) curve which extends to large values of μB without approaching the μB axis. We consider the impact and peculiarities of the related phase structure on the EoS for the employed dilaton potential and dynamical coupling parameterizations. These seem to prevent the design of an overall trustable EoS without recourse to hybrid constructions.
MAS-Net: Multi-Attention Hybrid Network for Superpixel Segmentation
Authors: Yan Guanghui , Wei Chenzhen , Jia Xiaohong , Li Yonghui , Chang Wenwen
Published: August 2024

Superpixels, as essential mid-level image representations, have been widely used in computer vision due to their computational efficiency and redundant compression. Compared with traditional superpixel methods, superpixel algorithms based on deep learning frameworks demonstrate significant advantages in segmentation accuracy. However, existing deep learning-based superpixel algorithms suffer from a loss of details due to convolution and upsampling operations in their encoder–decoder structure, which weakens their semantic detection capabilities. To overcome these limitations, we propose a novel superpixel segmentation network based on a multi-attention hybrid network (MAS-Net). MAS-Net is still based on an efficient symmetric encoder–decoder architecture. First, utilizing residual structure based on a parameter-free attention module at the feature encoding stage enhanced the capture of fine-grained features. Second, adoption of a global semantic fusion self-attention module was used at the feature selection stage to reconstruct the feature map. Finally, fusing the channel with the spatial attention mechanism at the feature-decoding stage was undertaken to obtain superpixel segmentation results with enhanced boundary adherence. Experimental results on real-world image datasets demonstrated that the proposed method achieved competitive results in terms of visual quality and metrics, such as ASA and BR-BP, compared with the state-of-the-art approaches.
Diagnosis of Nutrient Discharges and Management Alternatives in Developing Countries and the Use of Microalgae as a Potential Solution: A Case Study from Different Provinces in Antioquia, Colombia
Authors: Pérez Mesa Alejandro , Saldarriaga Molina Julio Cesar , Ríos Luis Alberto , Ocampo Echeverri Esteban , Ocampo Echeverri David
Published: August 2024

This research aims to propose management strategies to mitigate eutrophication caused by inefficient wastewater treatment plants in Colombia. The information analyzed was provided by environmental authorities such as IDEAM, CORANTIOQUIA, and CORNARE in Antioquia, where the average concentrations of phosphorus in wastewater from municipal, livestock, and industrial activities are 5.1, 30.6, and 29.1 mg P/L. The total nitrogen concentrations are 77, 143, and 121 mg N/L, respectively, surpassing the limit concentrations stated by the European Union, the United States, and Mexico, among others, while Colombia has not established its own limits. Including limitations for nutrient concentrations will align Colombia with the 2050 Sustainable Development Goals (SDGs), where microalgae species like Chlorella or Scenedesmus could be used in wastewater treatment systems for municipalities and industries. These microalgae can capture organic matter, nutrients, and greenhouse emissions and reduce the concentrations observed in natural water. They could also be an alternative for capturing heavy metals and some pollutants of emerging concern. In addition to the ecological and social benefits, the algal biomass could be valorized by transforming it into biological products such as fuels, fertilizers, and pigments when micropollutants are not present, reducing operational costs for treatment systems.
An Increase in Stream Water DOC Concentrations May Not Necessarily Imply an Increase in DOC Fluxes in Areas Affected by Acid Deposition and Climate Change—An Example from Central European Catchments
Authors: Hruška Jakub , Krám Pavel
Published: August 2024

Over a period of 30 years (1993–2022), headwater catchments in the Slavkov Forest (Czech Republic) exhibited a robust increase in stream water DOC (dissolved organic carbon) concentrations following a significant reduction in acidic atmospheric deposition. Sulfur deposition decreased from 34 kg ha−1 yr−1 in 1993 to 2.6 kg ha−1 yr−1 in 2022. Three Norway-spruce-dominated research sites—Černý Potok (CEP), a 15.2 ha peatbog catchment, Lysina (LYS), a 27.3 ha granitic catchment, and Pluhův Bor (PLB), a 21.6 ha serpentinite catchment, were investigated. The three–year average DOC concentration increased from 48.2 mg L−1 (1993–1995) to 68.3 mg L−1 (2020–2022) at CEP (0.69 mg L−1 yr−1). LYS showed an increase from 16.9 mg L−1 to 25.4 mg L−1 (0.30 mg L−1 yr−1 annually). The largest increase was recorded at PLB, with an increase from 15.7 mg L−1 to 36.7 mg L−1 (0.89 mg L−1 yr−1). A decline in ionic strength was identified as the main driver of the DOC increase. The annual runoff declined significantly at CEP and LYS from 465 mm to 331 mm as a result of rising air temperatures and reduced precipitation between 2014 and 2022. PLB (average of 266 mm) did not show a statistically significant decline. Recently, PLB experienced significant deforestation that likely lowered transpiration and thus increased catchment runoff. As a result, DOC fluxes did not change significantly at CEP (average 210 kg ha−1 yr−1) and LYS (90 kg ha −1 yr−1). However, PLB’s DOC flux more than doubled, increasing from 44 to 106 kg ha−1 yr−1. Drivers connected with global change, such as increasing temperatures, or potential chemical drivers, such as reductions in Al concentrations and pH changes, were not able to explain the observed changes in DOC concentra tions and fluxes.
Chronic kidney disease and the alternative labels used by GPs in Australia: a qualitative interview study
Authors: Guppy Michelle , Bowles Esther Joy , Glasziou Paul , Doust Jenny
Published: August 2024

Background

Guidelines for terminology defining chronic kidney disease (CKD) have been in use for 20 years. Age is not currently considered in the guideline definition of CKD. In previous studies, GPs have been reluctant to give older patients the label of CKD.

Aim

To determine what language GPs are using to describe or label CKD with their older patients, and to explore the reasons for their use of alternative language.

Design & setting

This was a descriptive qualitative interview study of Australian GPs.

Method

Twenty-seven GPs were recruited via email and interviewed regarding their management of CKD. GPs were asked what language and terminology they used when discussing a diagnosis of CKD with their older patients.

Results

'Labelling of CKD', the language that GPs use when talking about CKD with their patients, emerged as a major theme from the initial GP interviews. Sub-themes emerged, including types of alternative labels and rationale for alternative labels. GPs used descriptions of 'reduced kidney function' to explain CKD to their patients, either in parallel with the diagnosis of CKD or instead of it. GPs had concerns about the words 'chronic' and 'disease', and used different terminology to explain these words to patients when diagnosing them with CKD.

Conclusion

GPs use alternative descriptions to explain mild decrease in kidney function with older patients. Alternative labels that denote level of risk to older patients, without creating unnecessary concern about normal age-related kidney function, need to be explored.
Information Design for the Development of Aceh's Door Batik Pattern on Font Medium
Authors: Fauzi Ahmad Nurzaeni , Wantoro  , Salvina Mauliza
Published: August 2024

Aceh is one of the provinces in Indonesia. Aceh also has batik with its own distinctive motif. One of the most popular motifs is the Pintu Aceh motif, this motif adapts from existing motifs that are commonly found in typical Acehnese handicrafts. Although it’s popular, but still the lack of media introduction developed further to the maximum. In terms of visual, The Pintu Aceh motif has the potential to be a more interesting media. The purpose of this design is to introduce aceh’s batik Pintu Aceh motif culture in digital-based in order to adjust the development of the times and technology. Through this design, one of the introductions of Indonesian culture that can be accepted and recognized through the characteristics of Aceh Pintu Aceh batik motifs. This design was written using qualitative writing method, which is sourced from books, journals, or articles. To complete the data and references, the author also conducted research through questionnaires to reach the target audience, in order to know the opinions of the public about Aceh batik motifs Pintu Aceh, especially in the media of interesting introduction. Therefore, the design of this information is made through font media by adaptingthe character of Pintu Aceh batik motif. It’s hoped that this design can foster knowledge about Aceh batik motifs Pintu Aceh and be proud of the strength of Indonesian culture, especially Aceh.
Improve Employee Productivity by Applying Green Human Resources Management and Increasing Employee Job Satisfaction
Authors: Rahma Saura Jeane Aquar , Soegoto Herman
Published: August 2024

This research aims to analyze the impact of applying green human resources management and increasing employee job satisfaction improving employee productivity. The research was conducted at the Institute for Development of Applied Nuclear Science and Technology with the employees as the research subject. The data used in this research are primary in form of a questionnaire and secondary data obtained from various scientific literature such as academic journals, digital books, and various documents from the organization. Multiple Linear Regression was used to analyze the respondents’ answers with a total of 134 employees, and the hypotheses were tested using the t-test and f-test. The result shows that employee productivity was simultaneously positively and significantly affected by green human resources management and employee job satisfaction. Employee productivity was partially positively and significantly affected by green human resources management and employee job satisfaction, which means that employee productivity will improve by implementing the green human resources management and increasing employee job satisfaction. This research is expected to impact the improvement of employee productivity by implementing green human resources management to increase employee job satisfaction.
Need Analysis of Japanese Grammar Learning Media
Authors: Ramadhan K , Setiana S M
Published: August 2024

This study aims to analyze the needs of grammar learning media in Kiso Nihongo Course. This study used a quantitative descriptive method using a questionnaire research technique. The questionnaire used is a closed-type questionnaire with several statements distributed via Google Forms. The respondent for this study was 25 students of the Japanese Department Faculty of Humanities Universitas Komputer Indonesia for the academic year 2022/2023. The results showed that learning Japanese grammar which is currently taking place in the Japanese Department at the Universitas Komputer Indonesia is going well. However, students feel that Japanese grammar learning media is needed to help the Japanese grammar learning process become better. Most of the students said that Japanese grammar learning media was needed to help them understand the material in the Kiso Nihongo Course. Learning media that are believed to be effective in helping the Japanese grammar learning process are video tutorials type. To improve the quality of learning Japanese grammar, the use of various media is needed. By conducting this study, the expected outcome is learning media for Japanese grammar that suit the needs of students can be created to make the learning process at the Kiso Nihongo Course better.
Dark Effects in Ankoku Joshi Movie
Authors: Wahyu Rifqy Adiyatama , Febrianty Fenny
Published: August 2024

Lighting is the crucial aspect of a movie since it may convey the intended message to the audience. The main goal of this research is to analysing the dark effect as an aesthetic component in the Ankoku Joshi movie. The theory used in the analysis of the data is John Fiske's semiotic theory combined using the Descriptive Analysis methods in this study. The main subject from this study is Ankoku Joshi movie. Through this research it is known that dark lighting effects are supported by other elements such as character expressions, timing, music and sound effects. The dark effect reinforces the impression of 'dark, ugliness, evil' in the story that becomes the beauty or aesthetics in the Ankoku Joshi movie.