bluuebunny/crossref_metadata_2025 huggingface dataset:
Oral Microbiota Linking Associations of Dietary Factors with Recurrent Oral Ulcer
Authors: Wang Yetong , Yue Haiyan , Jiang Yuzhou , Huang Qiumin , Shen Jie , Hailili Gulisiya , Sun Zhonghan , Zhou Xiaofeng , Pu Yanni , Song Huiling , Yuan Changzheng , Zheng Yan
Published: May 2024

Recurrent oral ulcer (ROU) is a prevalent and painful oral disorder with implications beyond physical symptoms, impacting quality of life and necessitating comprehensive management. Understanding the interplays between dietary factors, oral microbiota, and ROU is crucial for developing targeted interventions to improve oral and systemic health. Dietary behaviors and plant-based diet indices including the healthful plant-based diet index (hPDI) were measured based on a validated food frequency questionnaire. Saliva microbial features were profiled using 16S rRNA gene amplicon sequencing. In this cross-sectional study of 579 community-based participants (aged 22–74 years, 66.5% females), 337 participants had ROU. Participants in the highest tertile of hPDI exhibited a 43% lower prevalence of ROU (odds ratio [OR] = 0.57, 95%CI: 0.34–0.94), compared to the lowest tertile, independent of demographics, lifestyle, and major chronic diseases. Participants with ROU tended to have lower oral bacterial richness (Observed ASVs, p < 0.05) and distinct bacterial structure compared to those without ROU (PERMANOVA, p = 0.02). The relative abundances of 16 bacterial genera were associated with ROU (p-FDR < 0.20). Of these, Olsenella, TM7x, and unclassified Muribaculaceae were identified as potential mediators in the association between hPDI and ROU (all p-mediations < 0.05). This study provides evidence of the intricate interplays among dietary factors, oral microbiota, and ROU, offering insights that may inform preventive and therapeutic strategies targeting diets and oral microbiomes.
Post-Transplant Diabetes Mellitus in Kidney-Transplanted Patients: Related Factors and Impact on Long-Term Outcome
Authors: Alfieri Carlo , Campioli Edoardo , Fiorina Paolo , Orsi Emanuela , Grancini Valeria , Regalia Anna , Campise Mariarosaria , Verdesca Simona , Delfrate Nicholas Walter , Molinari Paolo , Pisacreta Anna Maria , Favi Evaldo , Messa Piergiorgio , Castellano Giuseppe
Published: May 2024

This study aimed to investigate the prevalence and determinants of glucose metabolism abnormalities and their impact on long-term clinical outcomes in kidney transplant recipients (KTxps). A retrospective analysis of 832 KTxps (2004–2020) was performed. Patients were assessed at 1 (T1), 6 (T6), and 12 (T12) months post-transplantation and clinically followed for an average of 103 ± 60 months. At T6, 484 patients underwent an oral glucose tolerance test for the diagnosis of alterations in glucose metabolism (AMG+) or post-transplant diabetes mellitus (PTDM+). The prevalence of pre-transplant diabetes was 6.2%, with 22.4% of PTDM+ within the 1st year. Patients with AMG were older and exhibited altered lipid profiles, higher body mass index, and increased inflammatory indices. Age at transplantation, lipid profile, and inflammatory status were significant determinants of PTDM. Graft loss was unaffected by glucose metabolism alterations. Survival analysis demonstrated significantly worse long-term survival for KTxps with diabetes (pre- and PTDM+, p = 0.04). In a comparison of the ND and PTDM+ groups, no significant differences in death with a functioning graft were found. The AMG+ group exhibited worse survival (p < 0.001) than AMG−, even after excluding patients with diabetes mellitus. Future randomized controlled trials are necessary to delve deeper into this subject, specifically examining the effects of new antidiabetic treatments.
Organic Nanoparticles in Progressing Cardiovascular Disease Treatment and Diagnosis
Authors: Udriște Alexandru Scafa , Burdușel Alexandra Cristina , Niculescu Adelina-Gabriela , Rădulescu Marius , Balaure Paul Cătălin , Grumezescu Alexandru Mihai
Published: May 2024

Cardiovascular diseases (CVDs), the world’s most prominent cause of mortality, continue to be challenging conditions for patients, physicians, and researchers alike. CVDs comprise a wide range of illnesses affecting the heart, blood vessels, and the blood that flows through and between them. Advances in nanomedicine, a discipline focused on improving patient outcomes through revolutionary treatments, imaging agents, and ex vivo diagnostics, have created enthusiasm for overcoming limitations in CVDs’ therapeutic and diagnostic landscapes. Nanomedicine can be involved in clinical purposes for CVD through the augmentation of cardiac or heart-related biomaterials, which can be functionally, mechanically, immunologically, and electrically improved by incorporating nanomaterials; vasculature applications, which involve systemically injected nanotherapeutics and imaging nanodiagnostics, nano-enabled biomaterials, or tissue-nanoengineered solutions; and enhancement of sensitivity and/or specificity of ex vivo diagnostic devices for patient samples. Therefore, this review discusses the latest studies based on applying organic nanoparticles in cardiovascular illness, including drug-conjugated polymers, lipid nanoparticles, and micelles. Following the revised information, it can be concluded that organic nanoparticles may be the most appropriate type of treatment for cardiovascular diseases due to their biocompatibility and capacity to integrate various drugs.
Impact Response Features and Penetration Mechanism of UHMWPE Subjected to Handgun Bullet
Authors: Zhu Yihui , Song Yang , Wu Wei , Ma Jie , Fan Zhuangqing , Wen Yaoke , Xu Cheng , Xia Min , Da Weifeng
Published: May 2024

Ensuring military and police personnel protection is vital for urban security. However, the impact response mechanism of the UHMWPE laminate used in ballistic helmets and vests remains unclear, making it hard to effectively protect the head, chest, and abdomen. This study utilized 3D-DIC technology to analyze UHMWPE laminate’s response to 9 mm lead-core pistol bullets traveling at 334.93 m/s. Damage mode and response characteristics were revealed, and an effective numerical calculation method was established that could reveal the energy conversion process. The bullet penetrated by 1.03 mm, causing noticeable fiber traction, resulting in cross-shaped failure due to fiber compression and aggregation. Bulge transitioned from circular to square, initially increasing rapidly, then slowing. Maximum in-plane shear strain occurred at ±45°, with values of 0.0904 and −0.0928. Model accuracy was confirmed by comparing strain distributions. The investigation focused on bullet-laminate interaction and energy conversion. Bullet’s kinetic energy is converted into laminate’s kinetic and internal energy, with the majority of erosion energy occurring in the first four equivalent sublaminates and the primary energy change in the system occurring at 75 μs in the fourth equivalent sublayer. The results show the damage mode and energy conversion of the laminate, providing theoretical support for understanding the impact response mechanism and improving the efficiency of protective energy absorption.
Cross-Modal Segmentation Network for Winter Wheat Mapping in Complex Terrain Using Remote-Sensing Multi-Temporal Images and DEM Data
Authors: Wang Nan , Wu Qingxi , Gui Yuanyuan , Hu Qiao , Li Wei
Published: May 2024

Winter wheat is a significant global food crop, and it is crucial to monitor its distribution for better agricultural management, land planning, and environmental sustainability. However, the distribution style of winter wheat planting fields is not consistent due to different terrain conditions. In mountainous areas, winter wheat planting units are smaller in size and fragmented in distribution compared to plain areas. Unfortunately, most crop-mapping research based on deep learning ignores the impact of topographic relief on crop distribution and struggles to handle hilly areas effectively. In this paper, we propose a cross-modal segmentation network for winter wheat mapping in complex terrain using remote-sensing multi-temporal images and DEM data. First, we propose a diverse receptive fusion (DRF) module, which applies a deformable receptive field to optical images during the feature fusion process, allowing it to match winter wheat plots of varying scales and a fixed receptive field to the DEM to extract evaluation features at a consistent scale. Second, we developed a distributed weight attention (DWA) module, which can enhance the feature intensity of winter wheat, thereby reducing the omission rate of planting areas, especially for the small-sized regions in hilly terrain. Furthermore, to demonstrate the performance of our model, we conducted extensive experiments and ablation studies on a large-scale dataset in Lanling county, Shandong province, China. Our results show that our proposed CM-Net is effective in mapping winter wheat in complex terrain.
Reconstruction of Hourly FY-4A AGRI Land Surface Temperature under Cloud-Covered Conditions Using a Hybrid Method Combining Spatial and Temporal Information
Authors: Li Yuxin , Zhu Shanyou , Zhang Guixin , Xu Wenjie , Jiang Wenhao , Xu Yongming
Published: May 2024

Land Surface Temperature (LST) products obtained by thermal infrared (TIR) remote sensing contain considerable blank areas due to the frequent occurrence of cloud coverage. The studies on the all-time reconstruction of the cloud-covered LST of geostationary meteorological satellite LST products are relatively few. To accurately fill the blank area, a hybrid method for reconstructing hourly FY-4A AGRI LST under cloud-covered conditions was proposed using a random forest (RF) regression algorithm and Savitzky-Golay (S-G) filtering. The ERA5-Land surface cumulative net radiation flux (SNR) reanalysis data was first introduced to represent the change in surface energy arising from cloud coverage. The RF regression method was used to estimate the LST correlation model based on clear-sky LST and the corresponding predictor variables, including the normalized difference vegetation index (NDVI), the normalized difference water index (NDWI), surface elevation and slope. The fitted model was then applied to reconstruct the cloud-covered LST. The S–G filtering method was used to smooth the outliers of reconstructed LST in the temporal dimension. The accuracy evaluation was performed using the measured LST of the representative meteorological stations after scale correction. The coefficients of determination derived with the reference LST were all above 0.73 on the three examined days, with a bias of −1.13–0.39 K, mean absolute errors (MAE) of 1.46–2.4 K, and root mean square errors (RMSE) of 1.77–3.2 K. These results indicate that the proposed method has strong potential for accurately restoring the spatial and temporal continuity of LST and can provide a solution for the production and research of gap-free LST products with high temporal resolution.
Satellite-Based Estimation of Near-Surface NO2 Concentration in Cloudy and Rainy Areas
Authors: Deng Fuliang , Chen Yijian , Liu Wenfeng , Li Lanhui , Chen Xiaojuan , Tiwari Pravash , Qin Kai
Published: May 2024

Satellite-based remote sensing enables the quantification of tropospheric NO2 concentrations, offering insights into their environmental and health impacts. However, remote sensing measurements are often impeded by extensive cloud cover and precipitation. The scarcity of valid NO2 observations in such meteorological conditions increases data gaps and thus hinders accurate characterization and variability of concentration across geographical regions. This study utilizes the Empirical Orthogonal Function interpolation in conjunction with the Extreme Gradient Boosting (XGBoost) algorithm and dense urban atmospheric observed station data to reconstruct continuous daily tropospheric NO2 column concentration data in cloudy and rainy areas and thereby improve the accuracy of NO2 concentration mapping in meteorologically obscured regions. Using Chengdu City as a case study, multiple datasets from satellite observations (TROPOspheric Monitoring Instrument, TROPOMI), near-surface NO2 measurements, meteorology, and ancillary data are leveraged to train models. The results showed that the integration of reconstructed satellite observations with provincial and municipal control surface measurements enables the XGBoost model to achieve heightened predictive accuracy (R2 = 0.87) and precision (RMSE = 5.36 μg/m3). Spatially, this approach effectively mitigates the problem of missing values in estimation results due to absent satellite data while simultaneously ensuring increased consistency with ground monitoring station data, yielding images with more continuous and refined details. These results underscore the potential for reconstructing satellite remote sensing information and combining it with dense ground observations to greatly improve NO2 mapping in cloudy and rainy areas.
Modeling of Cooperative Robotic Systems and Predictive Control Applied to Biped Robots and UAV-UGV Docking with Task Prioritization
Authors: Taner  Baris , Subbarao Kamesh
Published: May 2024

This paper studies a cooperative modeling framework to reduce the complexity in deriving the governing dynamical equations of complex systems composed of multiple bodies such as biped robots and unmanned aerial and ground vehicles. The approach also allows for an optimization-based trajectory generation for the complex system. This work also studies a fast–slow model predictive control strategy with task prioritization to perform docking maneuvers on cooperative systems. The method allows agents and a single agent to perform a docking maneuver. In addition, agents give different priorities to a specific subset of shared states. In this way, overall degrees of freedom to achieve the docking task are distributed among various subsets of the task space. The fast–slow model predictive control strategy uses non-linear and linear model predictive control formulations such that docking is handled as a non-linear problem until agents are close enough, where direct transcription is calculated using the Euler discretization method. During this phase, the trajectory generated is tracked with a linear model predictive controller and addresses the close proximity motion to complete docking. The trajectory generation and modeling is demonstrated on a biped robot, and the proposed MPC framework is illustrated in a case study, where a quadcopter docks on a non-holonomic rover using a leader–follower topology.
Integrating Wireless Remote Sensing and Sensors for Monitoring Pesticide Pollution in Surface and Groundwater
Authors: Mutunga Titus , Sinanovic Sinan , Harrison Colin S.
Published: May 2024

Water constitutes an indispensable resource crucial for the sustenance of humanity, as it plays an integral role in various sectors such as agriculture, industrial processes, and domestic consumption. Even though water covers 71% of the global land surface, governments have been grappling with the challenge of ensuring the provision of safe water for domestic use. A contributing factor to this situation is the persistent contamination of available water sources rendering them unfit for human consumption. A common contaminant, pesticides are not frequently tested for despite their serious effects on biodiversity. Pesticide determination in water quality assessment is a challenging task because the procedures involved in the extraction and detection are complex. This reduces their popularity in many monitoring campaigns despite their harmful effects. If the existing methods of pesticide analysis are adapted by leveraging new technologies, then information concerning their presence in water ecosystems can be exposed. Furthermore, beyond the advantages conferred by the integration of wireless sensor networks (WSNs), the Internet of Things (IoT), Machine Learning (ML), and big data analytics, a notable outcome is the attainment of a heightened degree of granularity in the information of water ecosystems. This paper discusses methods of pesticide detection in water, emphasizing the possible use of electrochemical sensors, biosensors, and paper-based sensors in wireless sensing. It also explores the application of WSNs in water, the IoT, computing models, ML, and big data analytics, and their potential for integration as technologies useful for pesticide monitoring in water.
Location-Aware Range-Error Correction for Improved UWB Localization
Authors: Coene Sander , Li Chenglong , Kram Sebastian , Tanghe Emmeric , Joseph Wout , Plets David
Published: May 2024

In this paper, we present a novel localization scheme, location-aware ranging correction (LARC), to correct ranging estimates from ultra wideband (UWB) signals. Existing solutions to calculate ranging corrections rely solely on channel information features (e.g., signal energy, maximum amplitude, estimated range). We propose to incorporate a preliminary location estimate into a localization chain, such that location-based features can be calculated as inputs to a range-error prediction model. This way, we can add information to range-only measurements without relying on additional hardware such as an inertial measurement unit (IMU). This improves performance and reduces overfitting behavior. We demonstrate our LARC method using an open-access measurement dataset with distances up to 20 m, using a simple regression model that can run purely on the CPU in real-time. The inclusion of the proposed features for range-error mitigation decreases the ranging error 90th percentile (P90) by 58% to 15 cm (compared to the uncorrected range error), for an unseen trajectory. The 2D localization P90 error is improved by 21% to 18 cm. We show the robustness of our approach by comparing results to a changed environment, where metallic objects have been moved around the room. In this modified environment, we obtain a 56% better P90 ranging performance of 16 cm. The 2D localization P90 error improves as much as for the unchanged environment, by 17% to 18 cm, showing the robustness of our method. This method evolved from the first-ranking solution of the 2021 and 2022 International Conference on Indoor Position and Indoor Navigation (IPIN) Competition.
A Förster Resonance Energy Transfer (FRET)-Based Immune Assay for the Detection of Microcystin-LR in Drinking Water
Authors: Capo Alessandro , Pennacchio Angela , Montagnese Concetta , Hadjiantonis Antonis , Demosthenous Panayiota , Giusti Alessandro , Staiano Maria , D’Auria Sabato , Varriale Antonio
Published: May 2024

Cyanobacteria bloom is the term used to describe an abnormal and rapid growth of cyanobacteria in aquatic ecosystems such as lakes, rivers, and oceans as a consequence of anthropic factors, ecosystem degradation, or climate change. Cyanobacteria belonging to the genera Microcystis, Anabaena, Planktothrix, and Nostoc produce and release toxins called microcystins (MCs) into the water. MCs can have severe effects on human and animal health following their ingestion and inhalation. The MC structure is composed of a constant region (composed of five amino acid residues) and a variable region (composed of two amino acid residues). When the MC variable region is composed of arginine and leucine, it is named MC-LR. The most-common methods used to detect the presence of MC-LR in water are chromatographic-based methods (HPLC, LC/MS, GC/MS) and immunological-based methods (ELISA). In this work, we developed a new competitive Förster resonance energy transfer (FRET) assay to detect the presence of traces of MC-LR in water. Monoclonal antibody anti-MC-LR and MC-LR conjugated with bovine serum albumin (BSA) were labeled with the near-infrared fluorophores CF568 and CF647, respectively. Steady-state fluorescence measurements were performed to investigate the energy transfer process between anti-MC-LR 568 and MC-LR BSA 647 upon their interaction. Since the presence of unlabeled MC-LR competes with the labeled one, a lower efficiency of FRET process can be observed in the presence of an increasing amount of unlabeled MC-LR. The limit of detection (LoD) of the FRET assay is found to be 0.245 nM (0.245 µg/L). This value is lower than the provisional limit established by the World Health Organization (WHO) for quantifying the presence of MC-LR in drinking water.
Combining Different Wearable Devices to Assess Gait Speed in Real-World Settings
Authors: Zanoletti Michele , Bufano Pasquale , Bossi Francesco , Di Rienzo Francesco , Marinai Carlotta , Rho Gianluca , Vallati Carlo , Carbonaro Nicola , Greco Alberto , Laurino Marco , Tognetti Alessandro
Published: May 2024

Assessing mobility in daily life can provide significant insights into several clinical conditions, such as Chronic Obstructive Pulmonary Disease (COPD). In this paper, we present a comprehensive analysis of wearable devices’ performance in gait speed estimation and explore optimal device combinations for everyday use. Using data collected from smartphones, smartwatches, and smart shoes, we evaluated the individual capabilities of each device and explored their synergistic effects when combined, thereby accommodating the preferences and possibilities of individuals for wearing different types of devices. Our study involved 20 healthy subjects performing a modified Six-Minute Walking Test (6MWT) under various conditions. The results revealed only little performance differences among devices, with the combination of smartwatches and smart shoes exhibiting superior estimation accuracy. Particularly, smartwatches captured additional health-related information and demonstrated enhanced accuracy when paired with other devices. Surprisingly, wearing all devices concurrently did not yield optimal results, suggesting a potential redundancy in feature extraction. Feature importance analysis highlighted key variables contributing to gait speed estimation, providing valuable insights for model refinement.
The Impact of Economic Policy Uncertainty on Green Technology Innovation of New Energy Vehicle Enterprises in China
Authors: Zhao Qiu , Tang Chenxi
Published: May 2024

Against the backdrop of increasingly serious global carbon emissions and environmental challenges, new energy vehicles (NEVs), as important low-carbon means of transport, play a crucial role in reducing carbon emissions, enhancing energy efficiency, and promoting sustainable development. However, green technological innovation is under considerable pressure from economic policy uncertainty (EPU), and the exact effects are not well understood. Using panel data on listed companies’ green technological innovation from 2012 to 2022, this study examines the relationship between EPU and green technological innovation in Chinese NEV enterprises. The findings reveal that rising EPU has a significant negative impact on green technological innovation in these companies; however, company ESG performance and government financial subsidies can effectively mitigate this negative impact. Notably, in provinces where public environmental concerns are high, the moderating effect of government subsidies is weaker; while facing EPU, NEV manufacturers rely more on government subsidies for green technological innovation than do parts manufacturers. These findings provide critical insights for guiding NEV enterprises in coping with EPU, advancing green technological innovation, and offering appropriate support and incentives to policymakers.
Research on Efficient Suspension Vibration Reduction Configuration for Effectively Reducing Energy Consumption
Authors: Song Huixin , Dong Mingming , Gu Liang
Published: May 2024

Reducing vehicle energy consumption is crucial for sustainable development, especially in the context of energy crises and environmental pollution. Energy regenerative suspension offers a promising solution, yet its practical implementation faces challenges like inertial mass issues, cost, and reliability concerns. This study introduces a novel suspension configuration, optimizing shock absorber technology with energy regenerative principles. The objective is to drastically cut energy consumption. Through a frequency domain analysis, this study identifies the root causes of increased energy consumption and worsened vibration in traditional suspensions. This study presents a comparative analysis of the frequency-domain characteristics between the novel suspension configuration and the traditional one. This study reveals that the new configuration exhibits a low-pass filtering effect on the shock absorber’s velocity, effectively minimizing vibrations in the low-frequency range, while mitigating their impact in the high-frequency range. This approach mitigates the trade-off between increased energy consumption and worsened vibration in the high-frequency range, making it a promising solution. Simulations show that this configuration significantly reduces acceleration by 7.04% and suspension power consumption by 10.47% at 60 km/h on the D-level road, while maintaining handling stability. This makes it a promising candidate for future energy-efficient suspension systems.
Intellectual Capital and Bank Stability in Saudi Arabia: Navigating the Dynamics in a Transforming Economy
Authors: Elmahgop Faiza Omer
Published: May 2024

This research investigates the influence of intellectual capital on the stability of banks in the evolving context of Saudi Arabia’s banking sector. Against the backdrop of rapid economic reforms under Vision 2030 and the challenges imposed by the COVID-19 pandemic, this research incorporates specific metrics related to these contexts and provides a nuanced analysis of how intellectual capital and its components (human capital efficiency (HCE), structural capital efficiency (SCE), and capital employed efficiency (CEE)) affect the financial stability of Saudi banks. This research analyzes a decade-long panel dataset for ten major Saudi banks from 2012 to 2022, utilizing both fixed-effects and cross-section random-effects models to discern the impact of intellectual capital on bank stability. The findings reveal a positive overall influence of intellectual capital on bank stability; however, individual components present a complex relationship, with CEE showing a positive association and HCE and SCE demonstrating unexpected negative correlations with bank stability. The research identifies leverage (LEV) as a significant factor negatively impacting stability. Operational efficiency (OPEF) and size (SIZE) also negatively affect stability. Surprisingly, macroeconomic indicators and bank size exhibit non-significant effects on bank stability. Similarly, the direct impact of the COVID-19 pandemic was found to be non-significant, suggesting a resilient banking environment or the presence of effective mitigating strategies. As Saudi Arabia continues its ambitious economic transformation, this research underscores the critical role of effectively managed intellectual capital in ensuring the banking sector’s stability. It provides a foundation for ongoing research in this vital area.
The Development of Modeling Shared Spaces to Support Sustainable Transport Systems: Introduction to the Integrated Pedestrian–Vehicle Model (IPVM)
Authors: Slack-Smith Delilah , Wijayaratna Kasun P. , Zeibots Michelle
Published: May 2024

The significance of developing shared road infrastructure in cities throughout the world is growing. Driven by the need to improve traffic management in ways that enhance multiple sustainability outcomes, developing the tools needed to test shared space proposals is becoming more sought after by responsible agencies. This paper reviews approaches to simulation modeling focused on representing and assessing shared spaces, culminating in a new approach presented here called the Integrated Pedestrian–Vehicle Model (IPVM)—a novel framework that combines social force models, car-following models and other algorithms from the robotics domain to better describe both mobility and activity within a shared space. The IPVM recognizes that while shared spaces are inherently multimodal, past efforts have tended to use pedestrian models as a starting point. Most consider the interaction of pedestrians with other pedestrians and static road infrastructure. Shared space models are generally microscopic models that integrate a social force model with a variety of car-following models to describe the interaction between vehicles and pedestrians. However, there is little research and few practical methodologies that address the long-range conflict avoidance between vehicles and pedestrians. This aspect is crucial for accurately representing the desire lines and pathways of pedestrians and active transport users in complex environments like shared spaces. The IPVM describes and visualizes shared road infrastructure with an absence of separating infrastructure between users and outputs. It generates metrics that can be used in conjunction with the latest evaluation approaches to gauge the sustainability credentials of shared space road proposals. Enhanced modeling of shared space solutions can lead to more effective implementation, which can potentially reduce the presence of cars, increase public and active transport use and lead to a more sustainable transport system.
Evaluating Competitiveness of Container Shipping Operators in the Sustainability and Digitalization Era
Authors: Yu Hongchu , Zhang Ming , Cui Chang , Xu Lei , Lin Shi , Xu Jing
Published: May 2024

This study aims to comprehensively analyze the operational status and international competitiveness of global container shipping enterprises in the era of sustainability and digitalization within the field of international container transportation. Utilizing the entropy method, this study quantitatively evaluates the direct operational strength of 14 leading container shipping enterprises while considering multiple factors including environmental protection, service quality, company scale, customer satisfaction, research and development level, and brand influence. The contributions of this study to the existing knowledge are primarily manifested in several aspects: firstly, by constructing a comprehensive evaluation framework, it offers a new perspective for assessing the international competitiveness of container shipping enterprises, facilitating a more comprehensive understanding of their strengths and weaknesses. Secondly, this study emphasizes the crucial roles of environmental protection and customer service in the competitiveness of shipping enterprises, providing new strategic directions for the industry’s sustainable development and digital transformation. Lastly, through detailed analysis of the operational performance of different companies, this study provides specific improvement suggestions for shipping enterprises, aiding them in achieving more precise management and more efficient development. The research findings demonstrate that companies exhibit varied performance in different aspects, showcasing their respective strengths and challenges. Particularly, this study identifies leading enterprises that have made significant progress in environmental technology innovation and customer service, while also highlighting deficiencies in some companies regarding scale expansion and brand building. These findings not only offer valuable insights for the development of the shipping industry but also serve as a window for policymakers, investors, and consumers to gain a deeper understanding of the shipping market. Through the thorough analysis conducted in this study, we aim to contribute to the sustainable development and digital transformation of the global container shipping industry.
Analysis of the Driving Mechanism of Urban Carbon Emission Correlation Network in Shandong Province Based on TERGM
Authors: Song Jiekun , Xiao Huisheng , Liu Zhicheng
Published: May 2024

Analyzing the driving factors and mechanisms of urban carbon emission correlation networks can provide effective carbon reduction decision-making support for Shandong Province and other regions with similar industrial characteristics. Based on industrial carbon emission data from various cities in Shandong Province from 2013 to 2021, the spatial correlation network of carbon emission was established by using a modified gravity model. The characteristics of the network were explored by using the Social Network Analysis (SNA) method, and significant factors affecting the network were identified through Quadratic Assignment Procedure (QAP) correlation analysis and motif analysis. The driving mechanism of the carbon emission correlation network was analyzed by using Temporal Exponential Random Graph Models (TERGMs). The results show that: (1) The spatial correlation network of urban carbon emission in Shandong Province exhibits multi-threaded complex network correlations with a relatively stable structure, overcoming geographical distance limitations. (2) Qingdao, Jinan, and Rizhao have high degree centrality, betweenness centrality, and closeness centrality in the network, with Qingdao and Jinan being relatively central. (3) Shandong Province can be spatially clustered into four regions, each with distinct roles, displaying a certain “neighboring clustering” phenomenon. (4) Endogenous network structures such as Mutual, Ctriple, and Gwesp significantly impact the formation and evolution of the network, while Twopath does not show the expected impact; FDI can promote the generation of carbon emission reception relationships in the spatial correlation network; IR can promote the generation of carbon emission spillover relationships in the spatial correlation network; GS, differences in GDP, differences in EI, and similarities of IR can promote the generation of organic correlations within the network; on the temporal level, the spatial correlation network of urban carbon emission in Shandong Province has shown significant stability during the study period.
Impacts of Crop-Specific Agricultural Practices on the Accumulation of Heavy Metals in Soil in Kvemo Kartli Region (Georgia): A Preliminary Assessment
Authors: Gventsadze Giorgi , Ghambashidze Giorgi , Chankseliani Zaur , Sarjveladze Ioseb , Blum Winfried E. H.
Published: May 2024

Maintaining sufficient levels of plant nutrients in the soil and controlling certain heavy metals, which can be toxic to the environment, are critical to ensure sustainable agricultural production. The study aimed to assess the linkage of crop-specific agricultural practices established by farmers in the Kvemo Kartli region (Georgia) with metal accumulation in soils of agricultural lands being subject to influence from polluted irrigation water in the past. In particular, we tried to identify the primary sources of micro-nutrients, including iron (Fe), copper (Cu), manganese (Mn), nickel (Ni), and zinc (Zn), and toxic elements such as cadmium (Cd) and lead (Pb), and the share of the contaminated irrigation water and other factors related to agricultural practices under different land uses, such as intensive and extensive arable farming, vineyards, orchards, and permanent pastures having the least disturbed soil. Based on principal component analysis, five primary sources were identified and categorized according to farmer interviews and previous studies conducted in the region. The results showed that increased concentrations of plant-available Cu, Zn, Cd, and Pb were mainly associated with irrigation water and intensive use of fungicides; Fe, Mn, and Ni were closely linked to several factors, such as the mineralogical composition of soils, minerals, and organic fertilizers inputs; and atmospheric deposition from diffuse sources, where exhausts from transport are probably the primary source. During our study, we attempted to differentiate irrigation water inputs from fungicides using simulation based on irrigation patterns and irrigation water quality on the one hand and fungicide application rates and their metal contents on the other. The simulation revealed that the intensive application of fungicides, especially in vineyards, is more significant in enriching soils with Cu and Zn than irrigation water. Identification of factorial dependences was supported by statistical analysis and application of several contamination assessment methods: contamination factor (CF), pollution load index (PLI), single-factor pollution index (PI), Nemerow’s comprehensive pollution index (PIN), enrichment factor (EF), and geo-accumulation index (Igeo). Applied environmental indices indicate that the soils under the former and existing vineyards are the most enriched with Cu and Zn, highlighting the significance of agricultural practices on heavy metal accumulations in the soils of agricultural lands.
Effective Stakeholder Management for Inclusive Post-Flood Management: Sri Lanka as a Case Study
Authors: Mendis Kalindu , Thayaparan Menaha , Kaluarachchi Yamuna , Ingirige Bingunath
Published: May 2024

This study aimed to examine post-flood management, with a particular focus on enhancing the inclusivity of marginalised communities through stakeholder analysis. This study was based on an interpretivist mixed method approach, under which 30 semi-structured stakeholder interviews were conducted. Interest versus power versus actual engagement matrix, social network analysis, and thematic analysis techniques were employed under the stakeholder analysis tool to analyse the collected data. The findings highlight the lack of clearly defined responsibilities among key stakeholders. Marginalised communities and community-based organisations have a high level of interests but a low level of power in decision making, resulting in weak engagement and the exclusion of their perceptions. This lack of collaboration and coordination among stakeholders has made marginalised communities more vulnerable in post-flood situations, as their interests are not defended. The findings emphasise the importance of conducting stakeholder analysis in the decision-making process to enhance stakeholder engagement and interaction, as well as promote inclusivity of marginalised communities in the post-flood recovery efforts of the government. Finally, this study recommends developing strategies to improve collaboration among stakeholders, fostering inclusiveness and customising these strategies according to the different types of stakeholders identified through stakeholder analysis.
Estimation of Phytoplankton Primary Productivity in Qinghai Lake Using Ocean Color Satellite Data: Seasonal and Interannual Variations
Authors: Ban Xuan , Dang Yingchao , Shu Peng , Qi Hongfang , Luo Ying , Xiao Fei , Feng Qi , Zhou Yadong
Published: May 2024

Estimation of primary production in Qinghai Lake is crucial for the aquatic ecosystem management in the northeastern Qinghai–Tibet Plateau. This study used the Vertically Generalized Production Model (VGPM) with ocean color satellite data to estimate phytoplankton primary productivity (PP) in Qinghai Lake during the non-freezing period from 2002 to 2023. Field data from 2018 and 2023 were used to calibrate and verify the model. The results showed a seasonal trend in chlorophyll-a and PP, with the lowest values in May and peaks from June to September. Qinghai Lake was identified as oligotrophic, with annual mean chlorophyl-a of 0.24–0.40 µg/L and PP of 40–369 mg C/m2/day. The spatial distribution of PP was low in the center of the lake and high near the shores and estuaries. An interesting periodic increasing trend in PP every 2 to 4 years was observed from 2002 to 2023. This study established a remote sensing method for PP assessment in Qinghai Lake, revealing seasonal and interannual variations and providing a useful example for monitoring large saline mountain lakes.
Formation of Abnormal Gas-Geochemical Fields and Dissolved Gases Transport at the Shallow Northeastern Shelf of Sakhalin Island in Warm Season: Expedition Data and Remote Sensing
Authors: Syrbu Nadezhda , Kholmogorov Andrey , Stepochkin Igor , Lobanov Vyacheslav , Shkorba Svetlana
Published: May 2024

Our paper deals with gas-geochemical measurements of CH4 and CO2, as well as the first measurements of dissolved H2 and He in the waters of the eastern shelf of Sakhalin Island, obtained during cruise 68 on the R/V Akademik Oparin (OP68) on 12–18 August 2023. The shallow eastern shelf has high concentrations of dissolved methane and helium in the water. The combined anomalies of methane and helium indicate the presence of an ascending deep fluid. The sources of methane in the studied area are the underlying oil- and gas-bearing rocks extending to the coast of the island. The deep faults of the region and the minor discontinuities that accompany them along the eastern coast of Sakhalin Island create a fluid-permeable geological environment both on the shallow shelf and on the coastal part of the island. East Sakhalin current and counter-current influence gases that migrate from lithospheric sources; these currents form a special hydrological regime that ensures high solubility of the gases released and their transfer under the lower boundary of the seasonal pycnocline to the east, where they are involved in the general circulation of the Sea of Okhotsk.
A New Concept of Flashboard Risers in Controlled Drainage Structures
Authors: Napierała Michał
Published: May 2024

Drainage water management (DWM), also known as controlled drainage (CD), is one of the edge-of-field strategies mainly designed to reduce the nitrate load from subsurface drainage systems. By limiting runoff, we also increase local retention, contributing to the sustainable management of water resources. For that purpose, CD involves using different kinds of controlled drainage devices. They are usually based on simple flashboard risers or stop-logs that regulate the drainage intensity by raising and lowering the drainage outlet. The problem with this type of device is the need for manual control, which can cause the CD system to be more demanding in terms of maintenance. A new approach to water management by CD allows the possibility of individual disassembly of each board without necessarily removing all of them. Thanks to the use of sideling runners, the water management process is much quicker. This is especially important when a farmer needs to manage water in a few controlled drainage devices in the field. The different variants of the design are shown here, as well as the way of stop-log assembly and control and the costs of maintaining similar devices. The advantages and disadvantages are described, and the usefulness of the new patented solution is assessed.
Use of lupine with bischofite in feeding of broiler chickens
Authors:   Federal State Budgetary Educational Institution of Higher Education “Volgograd State Agrarian University”, Russia, Volgograd, Korneeva O. V. , Karapetyan A. K. ,   Federal State Budgetary Educational Institution of Higher Education “Volgograd State Agrarian University”, Russia, Volgograd
Published: May 2024

Currently, feed and mineral substances of non-traditional origin are widely used in feeding animals and poultry. The effectiveness of using new mineral complexes and non-traditional feed ingredients is constantly being studied. In this regard, the study of mineral additives and non-traditional feeds, as well as the eff ectiveness of their use in feeding animals and poultry is an urgent problem. The purpose of the work was to study the use of lupine together with bischofite in feeding of broiler chickens. In order to achieve the purpose of research two scientific and economic experiments were carried out on broiler chickens of the cross Ross 308 to study the infl uence of an alternative feed protein (lupine variety Deco) and a natural mineral additive (bischofi te) on the quality of the resulting products. The duration of each scientific and economic experiment was 37 days. It was found in the results of the first scientific and economic experiment that the use of lupine of the variety Deco and the natural mineral additive bischofite in the diets of broiler chickens in the feed composition made it possible to obtain additional profi t in the amount of 197,64–1345,38 rubles per 120 heads of broilers. The level of profi tability in the 1st experimental group of broiler chickens was higher by 1,01 abs.%, in the 2nd experimental group by 6,72 abs.% and in the 3rd experimental group by 4,03 abs.% compared to the control group. In the control group this figure was 19,77 %. It was established in the results of the second scientific and economic experiment that the use of variety lupine Deco and the natural mineral additive bischofi te in the diets of broiler chickens contributed to additional profi t in the amount of 1171,51 rubles per on 120 heads of broilers. The level of profitability in the experimental group was higher by 5,56 abs.% compared to the control group.
Metabolism and productivity of quails of Estonian breed when feeding the feed additive Krezatsin
Authors:   Federal State Budgetary Educational Institution of Higher Education “National Research Mordovian State University named after N. P. Ogarev”, Russia, Republic of Mordovia, Saransk, Gayirbegov D. Sh. , Engurazov G. A. ,   Federal State Budgetary Educational Institution of Higher Education “National Research Mordovian State University named after N. P. Ogarev”, Russia, Republic of Mordovia, Saransk
Published: May 2024

The purpose of the work was to establish the metabolism and productivity of quails of Estonian breed when fed with the Krezatsin feed additive. Under the conditions of a quail farm, the feasibility of using the feed additive Krezatsin in the diets of quails of Estonian breed has been scientifi cally substantiated and proven. Its optimal dose in compound feed for quails has been identifi ed. It has been shown that the use of the Krezatsin additive in feeding quails increased the nutritional value of their feeding, had a positive effect on digestibility, the use of dietary nutrients, growth energy, the livability of quails, their egg and meat productivity. The use this additive reduced feed intake per unit of production. The data obtained in the experiment made it possible to theoretically substantiate and recommend additional resources for production to increase the effi ciency of quail production by optimizing the Krezatsin feed additive in their diets. It has been proven that the use of this additive when rearing quails in an amount of 50 mg per 100 g of compound feed contributed to the normalization of metabolism in the body of quails, significantly increased the digestibility of dry matter by 2,25 abs.%, organic matter by 2,16 abs.%, raw protein by 3,38 abs.%, crude fat by 2,67 abs.%, crude fi ber by 2,76 abs.% and nitrogen-free extractive substances by 1,16 abs.%. The tested additive contributed to better nitrogen absorption and use of macroelements diet. Feeding the studied additive as part of the compound feed contributed to an increase in the live weight of quails by 3,4 %, egg productivity by 6,0 %, improved the quality of eggs and reduced the compound feed intake per unit of production by 3,4 %.
Perancangan Aplikasi Mobile Pembukuan Pengadaan Kayu Bangsal Delima Jambi Berbasis Android
Authors: Yudhistira Reynaldi , Gunardi  , Nugroho Agus
Published: May 2024

Penelitian ini dilatar belakangi oleh belum adanya aplikasi pembukuan yang dapat diakses dimana saja oleh pemilik Bangsal Delima Jambi. Hal ini disebabkan karena sistem pembukuan bersifat manual dan tidak bisa dibawa dimana saja. Tujuan dari penelitian ini adalah untuk merancang aplikasi pembukuan untuk pemilik dengan menggunakan mobile. Metode pengembangan sistem yang digunakan adalah pengumpulan data dan wawancara dan juga menggunakan metode waterfall dengan menggunakan alat permodelan use case diagram, activity diagram, class diagram, dan flowchart. Perangkat lunak yang digunakan adalah Android Studio dan Firebase. Dengan dirancangnya aplikasi mobile ini dapat diakses dimana saja dan kapan saja.