bluuebunny/crossref_metadata_2025 huggingface dataset:
Research and Implementation of Agronomic Entity and Attribute Extraction Based on Target Localization
Authors: Guo Xiuming , Zhu Yeping , Li Shijuan , Wu Sheng , E Yue , Liu Shengping
Published: January 2025

The agronomic knowledge graph can provide accurate and reliable service support for agricultural production management. Agronomic knowledge often comes from unstructured text data, and efficient annotation of agricultural text data and construction of knowledge extraction models suitable for the characteristics of agronomic knowledge are two key points to create an agronomic knowledge graph. The proportion of attributes in agronomic knowledge is relatively high, but currently, the attribute annotation function of existing annotation tools is incomplete, and the annotation function and process are unclear. A scalable natural language annotation framework was proposed, which was able to flexibly configure the annotation process and annotation objects as needed, and the named entity was annotated in the corresponding mode. The current knowledge extraction models are mostly based on input text sequences, which has the problem of low feature utilization. However, the entities and attributes in agronomic knowledge have high similarity, and the position and type of entities and attributes can be directly calculated through their common features. An entity and attribute recognition model based on target localization, EntityDetectModel, was proposed. Firstly, Bert was used to extract text features with contextual information. Then, convolutional neural networks were used to extract features at different depths, and inter layer feature fusion was used to improve feature expression ability. Finally, the corresponding positions and types of named entities with different sizes were calculated based on the features at different depths. EntityDetectModel was compared with the other entity and relationship extraction models published in recent years and the results showed that the precision, recall, and F1 of EntityDetectModel were 91.0%, 83.4%, and 87.0%, respectively, which were superior to other comparison models. Using EntityDetectModel, a wheat agronomic knowledge graph was constructed.
High-Resolution Mapping of Cropland Soil Organic Carbon in Northern China
Authors: Wang Rui , Du Wenbo , Li Ping , Yao Zelong , Tian Huiwen
Published: January 2025

Mapping the high-precision spatiotemporal dynamics of soil organic carbon (SOC) in croplands is crucial for enhancing soil fertility and carbon sequestration and ensuring food security. We conducted field surveys and collected 1121 soil samples from cropland in Changzhi, northern China, in 2010 and 2020. Random Forest (RF) models combined with 19 environmental covariates were used to map the topsoil (0–20 cm) SOC in 2010 and 2020, and uncertainty maps were used to calculate the dynamic changes in cropland SOC between 2010 and 2020. Finally, RF and Structural Equation Modeling (SEM) were employed to explore the effects of climate, vegetation, topography, soil properties, and agricultural management on SOC variation in croplands. Compared to the prediction model using only natural variables (RF_C), the model incorporating agricultural management (RF_A) significantly improved the simulation accuracy of SOC. The coefficient of determination (R2) increased from 0.77 to 0.85, while the Root Mean Square Error (RMSE) decreased from 1.74 to 1.53 g kg−1, and the Mean Absolute Error (MAE) was reduced from 1.10 to 0.94 g kg−1. The uncertainty in our predictions was low, with an average value of only 0.39–0.66 g kg−1. From 2010 to 2020, SOC in the Changzhi croplands exhibited an overall increasing trend, with an average increase of 1.57 g kg−1. Climate change, agricultural management, and soil properties strongly influence SOC variation. Mean annual precipitation (MAP), drainage condition (DC), and net primary productivity (NPP) were the primary drivers of SOC variability. Our findings highlight the effectiveness of agricultural management for predicting SOC in croplands. Overall, the study confirms that improved agricultural management has great potential to increase soil carbon stocks, which may contribute to sustainable agricultural development.
Potential Impacts of Climate Change on the Spatial Distribution Pattern of Naked Oats in China
Authors: Yang Zhenwei , Yang Xujing , Huang Yuheng , Zhang Yalin , Guo Yao , Feng Meichen , Qin Mingxing , Jin Ning , Amjad Muhammad , Wang Chao , Zhang Meijun , Yang Wude
Published: January 2025

Naked oats, a significant minor cereal crop in China popular for its nutrient richness, have experienced a surge in production in recent years, fueled by the escalating demand for wholesome healthy food. However, the dispersed and disorganized cultivation plan of naked oats poses a significant constraint on its industrial progression. Considering the dual influence of cultivation, management techniques, and global climate change on the production of naked oats, this study explores the potential impacts of climate change on the spatial distribution and yield of this cereal crop. Leveraging CMIP6 climate models (BCC-CSM2-MR, CanESM5, CNRM-ESM2-1) and an optimized MaxEnt model (RM = 0.5, FC = LQ), we simulated potential climate-suitable zones for naked oats from 1990 to 2020 and forecasted alterations under various emission scenarios from 2021 to 2100. The model achieved an average accuracy test with high value (AUC = 0.945) in predicting suitable areas; with precipitation seasonality (Coefficient of Variation) (bio15, 21.70%) and topsoil pH (H2O) (T_PH_H2O, 21.00%) as key factors, both climate and soil properties have a greater influence. Simulation results showed that the climatically suitable area for naked oats increased under all scenarios, with the largest increase in the optimal growing area under ssp126 in the 2030s. The increase was 3.93% with an area of 0.77 × 106 km2. The study also compared the data from the main producing counties of naked oats in Shanxi Province from 2020 to 2022 for statistical purposes, and found that 39 counties were in high climatic suitability zones and 39 counties were in remarkably high climatic suitability zones. The agreement rate between planting areas and climatically suitable areas was as high as 97.44%. Further, the growing area expanded westward, increasing the production intensity. This study reveals the current spatial distribution pattern of naked oats, providing a scientific rationale for addressing climate change through multi-scenario predictions. Our findings have implications for optimizing cultivation layout and identifying optimal zones, supporting sustainable agricultural development strategies in China.
Canine Multicentric Lymphoma: Diagnostic, Treatment, and Prognostic Insights
Authors: Rocha Michelle do Carmo Pereira , Araújo Diana , Carvalho Fátima , Vale Nuno , Pazzini Josiane Morais , Feliciano Marcus Antônio Rossi , De Nardi Andrigo Barboza , Amorim Irina
Published: January 2025

Lymphoma accounts for 24% of all documented canine neoplasms and 85% of hematological malignancies, while multicentric lymphoma corresponds to 84% of all canine lymphomas. Canine lymphomas of B-cell origin account for 60% to 80% of lymphomas. Similar to humans, the histologic grade, architecture, as well as immunophenotype determination, are crucial. These lesions are the most prevalent spontaneous tumors in dogs and this species may be a valuable animal model for the study of human non-Hodgkin’s lymphoma. Therefore, it is important to investigate and assess therapeutic responses and to seek predictive and prognostic factors in order to allow for the development of an individualized and more effective therapy that increases survival. This review aims to describe current knowledge on the diagnosis, treatment, and prognostic factors of canine multicentric lymphoma.
A Decision Tree-Based Pattern Classification and Regression for a Mobility Support Scheme in Industrial Wireless Sensor Networks
Authors: Kim Cheonyong , Kim Sangdae
Published: January 2025

Industrial wireless sensor networks (IWSNs) are exploited to achieve various purposes, including enhancing productivity and reducing cost in a variety of industries, and they require low-delay and high-reliability packet transmission. To achieve these requirements, a network manager is responsible for constructing a graph, allocating resources, and determining the transmission cycle and path of each node in advance. However, this approach is inadequate for exploiting mobile devices that constantly change network topology because frequent graph reconstruction and resource reallocation are required. In other words, despite the increasing reliance on mobile devices in a variety of industries, existing schemes cannot adequately respond to path failures due to device movement and subsequent packet loss during recovery. For example, real-time tracking of mobile vehicles in mining operations is crucial for safety and efficiency, where path failures and packet loss can lead to significant issues. To solve this problem, we propose a mobility support scheme to prevent packet loss caused by device mobility. In the proposed scheme, we first classify mobility patterns based on the decision tree and then apply regression to predict their trajectories. By leveraging this predictive information, the network manager could preemptively adjust graph construction and resource allocation to accommodate topology changes. Performance evaluation results show that the predicted mobility patterns closely match the actual patterns, achieving a high packet delivery ratio compared to conventional schemes, while also enabling efficient resource management.
Uncovering Research Trends on Artificial Intelligence Risk Assessment in Businesses: A State-of-the-Art Perspective Using Bibliometric Analysis
Authors: Muria-Tarazón Juan Carlos , Oltra-Gutiérrez Juan Vicente , Oltra-Badenes Raúl , Escobar-Román Santiago
Published: January 2025

This paper presents a quantitative vision of the study of artificial intelligence risk assessment in business based on a bibliometric analysis of the most relevant publications. The main goal is to determine whether the risk assessment of artificial intelligence systems used in businesses is really a subject of increasing interest and to identify the most influential and productive sources of scientific research in this area. Data were collected from the Web of Science Core Collection, one of the most complete and prestigious databases. Regarding the temporal evolution of publications and citations this study evidences, this research subject shows rapid growth in the number of publications (at a compound annual rate of 31.20% from 2018 to 2024 inclusive), showing its high attraction for researchers, responding to the need to implement systematic risk assessment processes in the organizations using AI to mitigate potential harms, ensure compliance with regulations, and enhance artificial intelligence systems’ trust and adoption. Especially after the surge of large language models like ChatGPT or Gemini, AI is revolutionizing the dynamics of human–computer interaction using natural language, video, and audio. However, as the scientific community initiates rigorous studies on AI risk assessment within organizational contexts, it is imperative to consider critical issues such as data privacy, ethics, bias, and hallucinations to ensure the successful integration and interaction of AI systems with human operators. Furthermore, this paper constitutes a starting point, including for any researcher who wants to be introduced to this topic, indicating new challenges that should be dealt by researchers interested in AI and hot topics, in addition to the most relevant literature, authors, and journals about this research subject.
High-Pressure Hydrogen Charge Check-Valve Energy Loss-Based Correlation Analysis Affecting Internal Flow Characterizations
Authors: Oh Seung-Hun , Jang Sun-Min , Suh Hyun-Kyu
Published: January 2025

In this study, we analyzed changes in flow characteristics and energy-dissipation characteristics due to changes in hydrogen temperature and inlet/outlet differential pressure in a check valve, which affect the storage safety and reliability of high-pressure hydrogen refueling systems. The effects of flow separation and recirculation flow generation at the back end of the valve were investigated, and the pressure, flow rate, pressure coefficient, and energy dissipation at the core part (where the hydrogen inflow is blocked) and the outlet part (where the hydrogen is discharged) were numerically analyzed. The hydrogen-inlet temperature (Tin) was selected as 233 K, 293 K, and 363 K, and the differential pressure (∆P) was selected in the range of 2 to 10 MPa in 2 MPa steps. To ensure the reliability of the numerical results, mesh dependence was performed, and the effect of the mesh geometry on the results was less than 2%. The numerical simulation results showed that the hydrogen introduced into the core part is discharged into the discharge part, and the pressure decreases by up to 6% and the velocity increases by up to 16% at the 95 mm position of the L-shaped curved tube. In addition, for the hydrogen-inlet temperature of 233 K in the L-shaped curved tube, the flow velocity decreases by up to 60% and the pressure coefficient increases at the 2.3 mm point in the Y-axis direction, indicating that the main flow area is biased towards the bottom of the valve due to the constriction of the veins caused by flow separation. The TDR results showed that the hydrogen discharge to the discharge region increased by 96% at 95 mm compared to 90 mm, and the turbulent kinetic energy of the hydrogen was dissipated, resulting in a temperature increase of up to 4.5 K. The exergy destruction was maximized in the core region where flow separation occurs, indicating that the pressure, velocity, and TDR changes due to flow separation and recombination have a significant impact on the energy loss of the flow in the check valve.
Design Considerations for a Compressed Stiffened Plate with Skin–Stringer Debonding Based on the Evaluation of Adhesive Layer Stress Distribution
Authors: Frulla Giacomo , Parente Giovanni
Published: January 2025

An extensive application of stiffened panels is considered standard for aerospace wing construction both for reducing the structural weight and fulfilling the regulatory requirements. The connection based on the adhesive layer between the skin and stringer introduces the possibility of debonding during operative conditions. The design procedure is strongly influenced by this anomaly, requiring the definition of a criterion for identifying the limit in debonding extension for safe operation. A procedure based on the investigation of the stress state in the adhesive layer is proposed in order to identify the typical behaviour of compressed plate, including damage situation, and a specific indication for design procedure is derived based on the debonding dimension. Critical and post-critical configuration were investigated both globally and locally to fix sensitive parameters. A conclusive guideline is discussed and presented. The analysis is applied to an isotropic plate in order to point out the main characteristics of the related design procedure. No conceptual changes are expected with the introduction of composite material that can influence the distribution of stress according to the chosen lay-up but not the basic design concept in the plate behaviour.
Binary Mixture of Neonicotinoid–Pyrethroid Insecticide: Impact on Survival, Cognitive Learning, and Memory in Apis mellifera jemenitica
Authors: Abuagla Mohamedazim I. B. , Iqbal Javaid , Raweh Hael S. A. , Abdelaziz Abdelsalam S. A. , Alqarni Abdulaziz S.
Published: January 2025

The impact of agrochemicals on pollinators, especially honey bees, has drawn significant attention due to its critical implications for worldwide food stability and ecosystems. Given the potential threat of insecticides to honey bees, bees may encounter multiple insecticides simultaneously during foraging. This study investigated the toxic effect of an insecticide mixture (IM) containing acetamiprid (neonicotinoid) and deltamethrin (pyrethroid) on the survival and cognitive appetitive performance of Apis mellifera jemenitica, a vital native pollinator in arid regions of Saudi Arabia. The lethal concentration (LC50) was determined by assessing bees’ mortality rates following exposure to IM through topical and oral routes. Significant bee mortality occurred at 4–48 h post treatment with IM through both exposure routes, showing a trend of increased mortality with higher IM concentrations compared to the control bees. Throughout all tested times, topical exposure proved relatively more effective, resulting in significantly greater bee mortality compared to oral exposure to IM. Food intake declined progressively with rising IM concentrations during oral exposure. The LC50 values of IM at 24 h after treatment were 12.24 ppm for topical and 10.45 ppm for oral exposure. The corresponding LC10, LC20, and LC30 values were 3.75 ppm, 5.63 ppm, and 7.54 ppm for topical exposure and 2.45 ppm, 4.04 ppm, and 5.78 ppm for oral exposure, respectively. The combination index (CI) revealed a synergistic effect (0.43) for topical exposure and antagonistic effects (1.43) for oral exposure, highlighting differential toxicity dynamics. IM exposure significantly impaired cognitive acquisition and memory reinforcement in honey bees, as demonstrated through behavioral assays, indicating potential neurotoxic effects. Learning and memory formation significantly declined at 2, 12, and 24 h after exposure to sublethal concentrations of IM through both topical and oral routes. Thus, evaluating the interactive impact of multiple pesticides on bees’ health and cognitive function is essential, particularly in regions where diverse agrochemicals are routinely utilized.
Modulation of Autophagy by Oncosuppressor FAM46C and Its Implications for Cancer Therapy: An Intriguing Perspective
Authors: Manfrini Nicola
Published: January 2025

Cancer is one of the major challenges in medicine, necessitating continuous advancements in therapeutic approaches. Autophagy, an intracellular pathway essential for cellular homeostasis and stress response, has emerged as a promising target for cancer treatment. In this context, FAM46C, a novel pan-cancer tumour suppressor, has been shown to induce apoptosis in multiple myeloma cells through indirect inhibition of autophagy. Here, we discuss how FAM46C-induced autophagic dampening could offer new opportunities for global cancer therapy. Specifically, we explore two scenarios in which the expression of a functional FAM46C may either sensitize cancer cells to autophagic inhibition or antagonize their sensitivity. We further comment on how this synergism/antagonism could be used to refine strategies for cancer treatment, positioning FAM46C as a pivotal factor in future cancer therapy development.
The Role of Immune Cells in Moyamoya Disease
Authors: Wang Sheng , Jiang Qian , Liu Yuan , Zhang Xincheng , Huang Yimin , Zhang Huaqiu
Published: January 2025

Moyamoya disease (MMD) is a rare progressive cerebrovascular disorder characterized by the stenosis or occlusion of the terminal segments of the internal carotid arteries, leading to the development of abnormal collateral vascular networks. These networks are a compensatory mechanism for reduced blood flow to the brain. Despite extensive research, the exact etiology of MMD remains unknown, although recent studies suggest that immune system dysfunction plays a critical role in its pathogenesis. In particular, the involvement of immune cells such as T cells, macrophages, and dendritic cells has been increasingly recognized. These immune cells contribute to the inflammatory process and vascular remodeling observed in MMD patients, further complicating the disease’s progression. Inflammation and immune-mediated damage to the vessel walls may accelerate the narrowing and occlusion of arteries, exacerbating ischemic events in the brain. Additionally, studies have revealed that certain genetic and environmental factors can influence immune system activation in MMD, linking these pathways to disease development. This review aims to provide a comprehensive overview of the immune mechanisms at play in MMD, focusing on how immune cells participate in vascular injury and remodeling. Understanding these immunological processes may offer new therapeutic targets to halt or reverse disease progression, potentially leading to more effective treatment strategies for MMD.
Long-Term Structural Health Monitoring of Kashima Lighthouse
Authors: Aoki Takayoshi , Kawase Minami , Zhang Jingyao , Sabia Donato , Demarie Giacomo Vincenzo , Quattrone Antonino , Sato Daisuke
Published: January 2025

The Kashima Lighthouse, one of the lighthouses that suffered damage in the 2011 Great East Japan Earthquake, required a careful investigation to estimate its long-term behavior and seismic vulnerability. This study, therefore, undertook a meticulous process of the dynamic testing, dynamic identification, and long-term structural health monitoring of the Kashima Lighthouse. The results of dynamic tests reveal that the fundamental frequencies of the Kashima Lighthouse are estimated to be around 2.60 Hz and 2.63 Hz in the east–west and north–south directions, respectively. The natural modes and damping factors are identified using an SSIM (Stochastic Subspace Identification Method). This paper also discusses the result of long-term structural health monitoring, where machine learning techniques were applied for data processing, highlighting the rigor and thoroughness of this research.
DEAPR: Differential Expression and Pathway Ranking Tool Demonstrates NRASG12V and NRASG12D Mutations Have Differing Effects in THP-1 Cells
Authors: Rathe Susan K. , White Jeremy P. , Sachs Zohar , Largaespada David A.
Published: January 2025

Background/Objectives: NRAS mutations are found in approximately 10% of patients with acute myeloid leukemia (AML), with nearly half of those occurring at codon 12, but little is known about how differing G12 mutants affect cancer cell activity. Methods: A novel bioinformatic technique, differential expression and pathway ranking (DEAPR), was used to identify the most prominent changes in terms of both individual genes and associated pathways when comparing AML THP-1 cells containing an NRASG12D mutation with B11 cells, which are THP-1-derived cells with the NRASG12D allele removed and a dox-inducible NRASG12V allele introduced. Results: In total, 1456 differentially expressed (DE) protein-coding genes were uniquely associated to the NRASG12D mutation, while 585 DE protein-coding genes were specific to the NRASG12V mutation. The innate immune system pathway was prominent in both mutant-specific lists, even though the genes involved were not in both lists. Furthermore, the two calprotectin genes (S100A8 and S100A9), also associated with innate immunity, were upregulated in the NRASG12D mutant and downregulated in the NRASG12V mutant. Conclusions: This study, using the DEAPR strategy, clearly demonstrates the dramatic changes associated with two seemingly similar NRAS mutations, suggesting the deployment of different treatment strategies based on the type of NRAS mutation present.
Relative Dose Intensity of Daratumumab, Lenalidomide, and Dexamethasone in Multiple Myeloma
Authors: Suzuki Kazuhito , Gunji Tadahiro , Kawashima Masaharu , Uryu Hideki , Nagao Riku , Saito Takeshi , Nishiwaki Kaichi , Yano Shingo
Published: January 2025

Background: Daratumumab (DARA), lenalidomide (LEN), and dexamethasone (DEX, DRd) are one of standards of care for patients with multiple myeloma (MM); however, the clinical impact of relative dose intensity (RDI) remains unclear. In this retrospective study, the aim was to analyze the relationship between the RDI and clinical outcomes in patients with myeloma treated with DRd. Methods: The numbers of patients with newly diagnosed, relapsed, and/or refractory MM were 40 and 71, respectively. Results: The median patient age was 74 years, and the median RDIs for DARA, LEN, and DEX were 84.0%, 39.4%, and 14.6%, respectively. At a median 26.8 months follow-up interval, the 2-year time to the next treatment (TTNT) of the high RDI of DARA (cutoff, 90%) was greater than that of the low RDI of DARA (77.3% vs. 51.6%, p < 0.001), and the 2-year overall survival (OS) of the low RDI of DEX (cutoff, 15%) was longer than that of the high RDI of DEX (87.7% vs. 61.0%, p = 0.027). Multivariate analysis showed that a high RDI for DARA and low RDI for DEX were associated with longer TTNT and OS (hazard ratio, 0.503, p = 0.044; hazard ratio 0.426, p = 0.022, respectively). The high RDI of DARA and low RDI of DEX reduced the incidence of severe infections (p = 0.040 and 0.049). Conclusion: The high RDI of DARA and low RDI of DEX predicted good clinical outcomes in this study’s cohort.
Early Synapse-Specific Alterations of Photoreceptor Mitochondria in the EAE Mouse Model of Multiple Sclerosis
Authors: Ibrahim Dalia R. , Schwarz Karin , Suiwal Shweta , Maragkou Sofia , Schmitz Frank
Published: January 2025

Multiple sclerosis (MS) is an inflammatory autoimmune disease of the central nervous system (CNS) linked to many neurological disabilities. The visual system is frequently impaired in MS. In previous studies, we observed early malfunctions of rod photoreceptor ribbon synapses in the EAE mouse model of MS that included alterations in synaptic vesicle cycling and disturbances of presynaptic Ca2+ homeostasis. Since these presynaptic events are highly energy-demanding, we analyzed whether synaptic mitochondria, which play a major role in synaptic energy metabolism, might be involved at that early stage. Rod photoreceptor presynaptic terminals contain a single large mitochondrion next to the synaptic ribbon. In the present study, we analyzed the expression of functionally relevant mitochondrial proteins (MIC60, ATP5B, COX1, PINK1, DRP1) by high-resolution qualitative and quantitative immunofluorescence microscopy, immunogold electron microscopy and quantitative Western blot experiments. We observed a decreased expression of many functionally relevant proteins in the synaptic mitochondria of EAE photoreceptors at an early stage, suggesting that early mitochondrial dysfunctions play an important role in the early synapse pathology. Interestingly, mitochondria in presynaptic photoreceptor terminals were strongly compromised in early EAE, whereas extra-synaptic mitochondria in photoreceptor inner segments remained unchanged, demonstrating a functional heterogeneity of photoreceptor mitochondria.
Research on the Weakening Process at the Interface of Bonded-Layer Composite Structures Using Ultrasonic Longitudinal Waves
Authors: Bu Fanqiang , Gui Liangqin , Wang Xingguo , Li Xiaogao , Shen Guolang , Ma Chengwen , Tang Guoxing
Published: January 2025

The interface weakening process of bonded-layer composite structures is calculated, simulated, and experimentally investigated using ultrasonic longitudinal waves. Firstly, the reflection coefficients of echoes are calculated theoretically. Subsequently, a time-domain simulation model of bonded-layer composite structures is established. The propagation law of ultrasonic waves in bonded-layer composite structures is obtained. The relationship between different bonding interface states and the ultrasonic reflection characteristics are investigated through ultrasonic experiments on bonded composite structures. The theoretical calculation, simulation, and experimental results are as follows: when the bonding strength of the bonding layer changes from weak to strong, the amplitude of the first echo gradually decreases, the amplitude of the second echo progressively increases, and the amplitude of the third echo is basically unchanged; when the bonding strength of the upper interface changes from weak to strong, the amplitudes of the first and the second echoes are same as in the previous variation whereas the amplitude of the third echo slightly increases; when the bonding strength of the lower interface changes from weak to strong, the amplitudes of the first and the third echoes remain essentially unchanged, but the amplitude of the second echo progressively increases in the experiment compared with the theoretical calculation and simulation. In addition, the time of the first echo remains broadly unchanged, and the times of the second and the third echoes gradually decrease under all conditions.
Optimizing Loss Functions for You Only Look Once Models: Improving Object Detection in Agricultural Datasets
Authors: Matsui Atsuki , Ishibashi Ryuto , Meng Lin
Published: January 2025

Japan faces a significant labor shortage due to an aging population, particularly in the agricultural sector. The rising average age of farmers and the declining participation of younger individuals threaten the sustainability of farming practices. These trends reduce the availability of agricultural labor and pose a risk to lowering Japan’s food self-sufficiency rate. The reliance on food imports raises concerns regarding price fluctuations and sanitation standards. Moreover, the challenging working conditions in agriculture and a lack of technological innovation have hindered productivity and increased the burden on the existing workforce. To address these challenges, “smart agriculture” presents a promising solution. By leveraging advanced technologies such as sensors, drones, the Internet of Things (IoT), and automation, smart agriculture aims to optimize farm operations. Real-time data collection and AI-driven analysis play a crucial role in monitoring crop growth, assessing soil conditions, and improving overall efficiency. This study proposes enhancements to the YOLO (You Only Look Once) object detection model to develop an automated tomato harvesting system. This system uses a camera to detect tomatoes and assess their ripeness for harvest. Our objective is to streamline the harvesting process through AI technology. Our improved YOLO model integrates two novel loss functions to enhance detection accuracy. The first, “VSR”, refines the model’s ability to classify tomatoes and determine their harvest readiness. The second, “SBCE”, enhances the detection of small tomatoes by training the model to recognize a range of object sizes within the dataset. These improvements have significantly increased the system’s detection performance. Our experimental results demonstrate that the mean Average Precision (mAP) of YOLOv7-tiny improved from 61.81% to 70.21%. Additionally, the F1 score increased from 0.61 to 0.71 and the mean Intersection over Union (mIoU) rose from 65.03% to 66.44% on the tomato dataset. These findings underscore the potential of our proposed system to enhance efficiency in agricultural practices.
Optimizing Adherence to Oral Anticancer Agents: Results from an Implementation Mapping Study
Authors: Muluneh Benyam , Upchurch Maurlia , Mackler Emily , Bryant Ashley Leak , Wood William A. , Wheeler Stephanie B. , Zullig Leah L. , Lafata Jennifer Elston
Published: January 2025

Clinical trials inform cancer care, yet real-world outcomes often diverge due to patient-related factors, like age, organ dysfunction, and nonadherence to oral anticancer agents (OAAs). While oncology organizations emphasize patient support programs, practical guidance on designing and implementing these programs is limited. We conducted a two-phase, mixed-methods study to enhance the adoption, implementation, and sustainability of an OAA adherence program (OAP). In phase 1, we used implementation mapping (IM) with a multidisciplinary expert panel to develop six strategies: (1) memorandum of understanding (MOU), (2) data-driven presentation, (3) standard operating procedures (SOPs), (4) motivational interviewing (MI) training, (5) electronic health record (EHR) templates, and (6) key performance indicators (KPIs). In phase 2, oncology professionals (n = 34) completed surveys, and a subset (n = 10) participated in interviews to assess feasibility, acceptability, and appropriateness. EHR templates and SOPs were rated as the most feasible and acceptable strategies, while MI training and formal agreements received moderate ratings. Interviews highlighted the importance of leadership buy-in, incremental implementation, and clear documentation. Participants valued KPIs for tracking adherence and outcomes but noted resource constraints and staff workload as challenges. Using IM, we co-developed strategies to activate OAA adherence-focused clinical programs. Tools standardizing care, like EHR templates and SOPs, were highly endorsed. Future work will test these strategies in a hybrid trial to improve real-world oncology outcomes.
Stochastic Potential Game-Based Target Tracking and Encirclement Approach for Multiple Unmanned Aerial Vehicles System
Authors: Yang Kejie , Zhu Ming , Guo Xiao , Zhang Yifei , Zhou Yuting
Published: January 2025

Utilizing fully distributed intelligent control algorithms has enabled the gradual adoption of the multiple unmanned aerial vehicles system for executing Target Tracking and Encirclement missions in industrial and civil applications. Restricted by the evasion behavior of the target, current studies focus on constructing zero-sum game settings, and existing strategy solvers that accommodate continuous state-action spaces have exhibited only modest performance. To tackle the challenges mentioned above, we devise a Stochastic Potential Game framework to model the mission scenario while considering the environment’s limited observability. Furthermore, a multi-agent reinforcement learning method is proposed to estimate the near Nash Equilibrium strategy in the above game scenario, which utilizes time-serial relative kinematic information and obstacle observation. In addition, considering collision avoidance and cooperative tracking, several techniques, such as novel reward functions and recurrent network structures, are presented to optimize the training process. The results of numerical simulations demonstrate that the proposed method exhibits superior search capability for Nash strategies. Moreover, through dynamic virtual experiments conducted with speed and attitude controllers, it has been shown that well-trained actors can effectively act as practical navigators for the real-time swarm control.
A VANET, Multi-Hop-Enabled, Dynamic Traffic Assignment for Road Networks
Authors: Arellano Wilmer , Mahgoub Imad
Published: January 2025

Traffic congestion imposes burdens on society and individuals. In 2022, the average congestion cost per auto commuter in the USA was USD1259. New possibilities to increase traffic efficiency are now available as vehicles can interact using Vehicular Ad Hoc Network (VANET) systems, a subset of the Internet of Vehicles (IoV). The traffic assignment problem deals with road network traffic optimization. It is a complex and challenging problem. A few solutions incorporating VANET technology have been presented; most are centralized or depend on infrastructure. In previous work, we introduced Road-ACO, an ant colony optimization (ACO), single-hop, decentralized, infrastructure-less, VANET solution. In this paper, we propose a new multi-hop-enabled, decentralized, ant-colony-inspired algorithm for dynamic highway traffic assignment. The algorithm works for large road networks and requires no infrastructure. We develop Veins framework-based simulations to evaluate the algorithm’s performance. The results indicate that the proposed algorithm consistently outperforms Road-ACO and performs optimally on road segments up to 4000 m long, with improvements of up to 40% on average travel time.
EdgeUP: Utilization and Priority-Aware Load Balancing in Edge Computing
Authors: Nguyen Lan Anh , Kim Sunggon , Son Yongseok
Published: January 2025

This paper introduces a dynamic context-aware load balancing mechanism called EdgeUP, which leverages dynamic contexts of both edge nodes and IoT devices to balance tasks on edge nodes optimally. To perform this, we devised a lightweight load balancer to allocate tasks optimally based on CPU utilization across edge nodes while satisfying the task priority of IoT devices. We implemented EdgeUP on real edge devices (i.e., Raspberry Pi 400) and evaluated it in terms of the average CPU utilization of edge nodes, idle CPU distance, and execution time. The experimental results show that EdgeUP outperforms three conventional load balancing algorithms, including round-robin, hill climbing, and K-Means, by 5.6×, 2.1×, and 3.6×, respectively.
Chemicals in European Residences—Part II: A Review of Emissions, Concentrations, and Health Effects of Semi-Volatile Organic Compounds (SVOCs)
Authors: Landeg-Cox Charlotte , Middleton Alice , Halios Christos , Marczylo Tim , Dimitroulopoulou Sani
Published: January 2025

This comprehensive review reports on concentrations, sources, emissions, and potential health effects from Semi-Volatile Organic Compounds (SVOCs) identified in the internal home environment in European residences. A total of 84 studies were identified, and concentrations were collated for inhalation exposure from dust, air and aerosol. A total of 298 individual SVOCs were identified and 67 compounds belonging to eight chemical classes: phthalates, flame retardants, polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), per- and polyfluorinated alkyl substances (PFAS), biocides, bisphenols and musks were prioritised. Phthalates are the most abundant SVOCs with DEHP being the most abundant in both the dust and aerosol phases (WAGMs 426.4 μg g−1 and 52.2 ng m−3, respectively) followed by DBP for dust (WAGMs are 95.9 μg g−1). In the air, the most abundant SVOCs are DiBP (284.1 ng m−3), DBP (179.5 ng m−3), DEHP (106.2 ng m−3) and DMP (27.79 ng m−3). Chemicals from all SVOC categories are emitted from building and construction materials, furnishings and consumer products, especially phthalates. Both legacy chemicals and their alternatives were detected. Complexities of reporting on SVOCs included differing sampling methodologies, multiple standards in their definition, lack of industry data, and toxicological data focused primarily on ingestion not inhalation exposures. Further research is recommended to develop the evidence base for potential health effects including via inhalation, reporting of emission rates and undertaking future monitoring studies.
Thermomechanical Treatment of SRF for Enhanced Fuel Properties
Authors: Prokeš Rostislav , Diviš Jan , Ryšavý Jiří , Jezerská Lucie , Niedźwiecki Łukasz , Vilas David Patiño , Mościcki Krzysztof , Mlonka-Mędrala Agata , Yan Wei-Mon , Žurovec David , Čespiva Jakub
Published: January 2025

Solid recovered fuel (SRF) is highly suited for thermal treatment, but its low bulk density and other physical properties limit the number of compatible energy systems that can effectively process it. This study presents the findings on SRF energy utilisation, focusing on mechanical treatment and a novel approach to its small-scale co-combustion with certified softwood (SW) pellets and catalytic flue gas control. In this study, the processes of certified SRF feedstock characterisation and mechanical treatment were thoroughly examined. Unique SRF pellets of proper mechanical properties were experimentally prepared for real-scale experiments. Mechanical and chemical properties, such as mechanical resilience, toughness, moisture and heating value, were examined and compared with standard SW A1 class pellets. The prepared SRF pellets possessed an energy density of 30.5 MJ∙kg−1, meeting the strict requirements from multiple perspectives. The influence of pelletisation temperature on pellet quality was investigated. It was found that increased resilience and a water content of 1.59% were achieved at a process temperature equal to 75 °C. Moreover, the moisture resilience was found to be significantly better (0.5 vs. 14.23%) compared with commercial SW pellets, while the hardness and durability values were reasonably similar: 40.7 vs. 45.2 kg and 98.74 vs. 98.99%, respectively. This study demonstrates that SRF pellets, with their improved mechanical and energy properties, are a viable alternative fuel, from a technical standpoint, which can be fully utilised in existing combustion units.
Accidents and Incidents Related to Eruptive Fire Behavior in Greece
Authors: Athanasiou Miltiadis , Karadimitris Athanasios , Xanthopoulos Gavriil , Avramidou Evangelia V.
Published: January 2025

This paper provides information about (a) 15 wildfire-related accidents that took place during 12 wildfires due to eruptive fire behavior in the 1982–2016 period and (b) six additional cases of “chimney effect” and “flame attachment” occurrence that caused no deaths or injuries, in the 2007–2019 period, in Greece. The work is based on (i) detailed documentation and reconstruction of wildfire behavior and spread, (ii) coupling of wildfire behavior with geospatial data and analysis, (iii) location information and field evidence for firefighter and citizen fatalities, and (iv) events surrounding those fatal accidents. These are matched with corresponding weather and fuel information, creating a rather complete picture of the conditions that entail a great risk to firefighters and citizens. The objectives of our effort are (a) to identify the common elements present in these cases and extract conclusions about the common denominators that may lead to fatal or near-fatal firefighter accidents, (b) to discuss how the findings compare with similar accidents in other countries, and (c) to develop clear messages for firefighters and citizens to help improve their safety.
Age and Feeding Habits of Trematomus bernacchii in the Ross Sea
Authors: Li Zhenlin , Sun Peng , Xu Siqing , Wang Yehui , Tian Yongjun
Published: January 2025

Trematomus bernacchii is a widely distributed, commercially valuable species that plays a significant role in the Benthic ecosystem of the Southern Ocean. Current research mainly explores its molecular responses to cold adaptation and environmental stress, while questions regarding its biological characteristics, such as length-related and sex-related differences in diet, remain to be addressed. This study assessed the age and feeding habits of T. bernacchii in the Ross Sea through stomach content morphological analysis and DNA metabarcoding analysis, examining dietary shifts by growth and sex. The research revealed that T. bernacchii primarily feeds on fish eggs, polychaetes, echinoderms, and mollusks. Other dietary components include algae, cnidarians, and crustaceans. Minor dietary differences were found between sexes. Polychaetes dominated all size classes, with Crustacea and Cnidaria declining as body length increased, while Echinoderms and Mollusca were more abundant in larger specimens. Evidence of egg cannibalism was also noted. These findings enhance our understanding of the trophic ecology of T. bernacchii and contribute to the construction of the Benthic food web of the Ross Sea.
Optimization of the Preparation Process of Crosslinked Polyvinyl Alcohol and Its Thermal Stability in Cementing Slurry
Authors: Li Junhao , Ai Haochen , Wang Qingchen , He Huifeng , Chang Xiaofeng , Chen Gang , Golian-Struhárová Alena , Slaný Michal , Qin Fangling
Published: January 2025

This study focuses on addressing the limitations of fluid loss additive in cement slurry under higher temperatures. The synthesis process of glutaraldehyde-crosslinked polyvinyl alcohol (PVA) was optimized to develop an efficient fluid loss additive for oil well cement slurries. Using one-factor experiments and the uniform design method, the optimal synthesis parameters were established: a reaction temperature of 50 °C; an acid concentration of 1 mol/L; a PVA mass concentration of 8%; a molar ratio of glutaraldehyde to PVA hydroxyl group of 1.47; and a crosslinking degree of 1.49%. The optimized crosslinked PVA demonstrated the ability to control API fluid loss within 50 mL when applied at 1% concentration in cement slurry under conditions of 30–110 °C and 6.9 MPa. Rheological analysis at medium and high temperatures revealed improved slurry properties, including smooth thickening curves and unaffected compressive strength. Further analyses, including thermogravimetric analysis (TGA), Zeta potential testing, and scanning electron microscopy (SEM), revealed that the crosslinked PVA hydrogel remained thermally stable up to 260 °C. Chemical crosslinking transformed the linear PVA into a network structure, enhancing its molecular weight, viscoelasticity, and thermal stability. This thermal resistance mechanism is attributed to the hydrogel’s high-strength reticular structure which forms a uniform, dense, and highly stable adsorption layer, thereby improving both the additive’s efficiency and the hydrogel’s temperature resistance.
Differential Metabolite Analysis of Anthocyanins in Variously Colored Petal Types During Different Developmental Stages of Sophora japonica L.
Authors: Guan Lingshan , Ji Xinyue , Sun Tao , Mu Yanjuan , Wang Yan , Han Yi , Sun Yanguo , Li Xinhui , Xie Kongan , Zhang Shuxin , Song Chenxia , Lu Yizeng
Published: January 2025

Flower color serves as a vital ornamental feature of landscape plants; Sophora japonica L. mutant ‘AM’ exhibits the different colors from the common S. japonica. ‘AM’, presenting with a light purple-red wing and keel and yellowish-white flag petals, while common S. japonica is yellow and white. The metabolites contributing to this color specificity in red-flowered S. japonica ‘AM’ are not yet fully understood. In this study, the flag, wing, and keel petals were collected from ‘AM’ at various phases, including the flower bud phase, initial flowering phase, full bloom phase, and final flowering phase, for conducting the metabolic assays targeting anthocyanins. Subsequently, we identified 45 anthocyanin-related metabolites, including nine flavonoids and 36 anthocyanins. Ten major floral chromoside metabolites were found to affect the coloration differences among the petals, where the most abundant anthocyanin was cyanidin-3-O-glucoside (Cy3G), which was much higher in the keel petal (LGB) and wing petal (YB) than in the flag petal (QB), and similarly, during the four periods of different petal types, the Cy3G content was higher in the initial flowering stage (S2), the full bloom stage (S3), and the final flowering stage (S4) than the flower bud stage (S1), which was in accordance with the trend of the observed petal floral color phenotypic difference measurement correlation. This suggested that the Cy3G accumulation was the primary factor driving the distinct coloration of varying types of petals. These findings could contribute to the understanding of the biochemical mechanisms underlying S. japonica petal coloration and may support future efforts in flower color improvement.