bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on Recommendation of Core Competencies and Behavioral Indicators of Pilots Based on Collaborative Filtering
Authors: Xu Haiwen , Kong Yifan , Huang Hong , Liang Aimin , Zhao Yunxiang
Published: December 2024

This paper proposes a new model of collaborative filtering that introduces a user difference factor to address the issue of less pronounced similarity performance in traditional algorithms. The algorithm is applied to the recommendation of pilots’ core competency behavior indicators to support pilots’ daily training arrangements, improve their core competencies, and ensure civil aviation flight safety. Firstly, based on traditional collaborative filtering methods, a user difference factor is introduced to improve the Pearson similarity calculation model. Secondly, the advantages and disadvantages of collaborative filtering recommendation models were evaluated using various methods such as average absolute error, accuracy, recall, and diversity. Finally, the new model is applied to the recommendation of PLM core competency behavior indicators, providing a recommendation list of different pilot behavior indicators to support their rehabilitation or enhanced training plans and arrangements. The calculation results show that the new model of collaborative filtering demonstrates better advantages, not only reducing the MAE value, but also improving the accuracy, recall, and diversity of the calculation results, providing effective guidance and theoretical support for pilots’ flight training and safe flight.
Optimization Study on the Freshwater Production Ratio from the Freezing and Thawing Process of Saline Water with Varied Qualities
Authors: Feng Xinyu , Ding Xue , Yuan Jiale , Xu Wanli , Liu Jiao
Published: December 2024

Freezing saline water irrigation is an effective technique for leaching soil salts. However, the coupling effects between initial salinity, sodium adsorption ratio (SAR), and freezing temperature of saline water have not been systematically studied. Therefore, a three-factor and five-level quadratic general rotation combination design was adopted, employing indoor simulated freeze–thaw experiments to investigate the influence of these three factors on the freshwater production ratio. The results indicated the following: (1) Within the range of the set experimental factor levels, the freshwater production ratio after the freezing of saline water ranged from 23.34% to 81.11%. (2) The significant negative effect of the main factor on the freshwater production ratio was descending order: initial salinity > freezing temperature. Although the impact of saline water SAR on the freshwater production ratio is insignificant, the interaction between saline water SAR and the freezing temperature has a highly significant negative effect on the freshwater production ratio. (3) At least 83% of the salt content was leached out in the first 16 h when the ice was thawed at 6 °C. These findings are beneficial for selecting appropriate irrigation times based on irrigation water quality in the actual field application of saline water freezing irrigation, with the aim of more efficiently reducing soil salt content.
Engineering Soil Quality and Water Productivity Through Optimal Phosphogypsum Application Rates
Authors: Luo Anrong , Li Jun , Xiao Yanan , He Zijian , Liang Jiaping
Published: December 2024

Water scarcity and soil degradation pose challenges to sustainable agriculture. Phosphogypsum, a low-cost solid waste, shows potential as a soil amendment, but its impact on water saving and soil quality need further study. This research assessed the effects of phosphogypsum application rates (CK: no phosphogypsum, 0.075%, 0.15%, 0.3% and 0.6%) on soil infiltration, water retention, salinity, soil quality, crop yield and irrigation water productivity (IWP) to identify the optimal rate. Phosphogypsum application altered pore structure and water potential gradients, slowing wetting front migration, increasing infiltration duration (102 to 158 min), cumulative infiltration (17.37 to 27.44 cm) (p < 0.05) and soil water content (18.25% to 24.33%) (p < 0.05) as the rate increased from CK to 0.6%. It also enhanced water retention by enhancing soil aggregation and reducing evaporation.By promoting the formation and stabilization of soil aggregates, phosphogypsum application (CK to 0.6%) reduced bulk density from 1.20 g/cm3 to 1.12 g/cm3 (p < 0.05), while porosity, available nitrogen and urease activity increased by 3.70%, 39.42% and 82.61%, respectively (p < 0.05). These enhancements provided a strong foundation for improved crop performance. Specifically, phosphogypsum enhanced yield through three pathways: (1) improving soil physical properties, which influenced soil nutrients and then improved enzyme activities; (2) directly affecting soil nutrients, which impacted enzyme activities and increased yield; and (3) directly boosting enzyme activities, leading to increased yield. The comprehensive benefits of phosphogypsum initially increased and then decreased, with an optimal application rate of 0.45% determined through TOPSIS, a method that ranks alternatives based on their proximity to an ideal solution, considering factors including soil quality, crop yield and IWP. These findings confirm the feasibility of phosphogypsum as an effective resource to enhance water efficiency and soil quality, promoting sustainable agricultural practices.
Feature Selection in Cancer Classification: Utilizing Explainable Artificial Intelligence to Uncover Influential Genes in Machine Learning Models
Authors: Dalmolin Matheus , Azevedo Karolayne S. , Souza Luísa C. de , de Farias Caroline B. , Lichtenfels Martina , Fernandes Marcelo A. C.
Published: December 2024

This study investigates the use of machine learning (ML) models combined with explainable artificial intelligence (XAI) techniques to identify the most influential genes in the classification of five recurrent cancer types in women: breast cancer (BRCA), lung adenocarcinoma (LUAD), thyroid cancer (THCA), ovarian cancer (OV), and colon adenocarcinoma (COAD). Gene expression data from RNA-seq, extracted from The Cancer Genome Atlas (TCGA), were used to train ML models, including decision trees (DTs), random forest (RF), and XGBoost (XGB), which achieved accuracies of 98.69%, 99.82%, and 99.37%, respectively. However, the challenges in this analysis included the high dimensionality of the dataset and the lack of transparency in the ML models. To mitigate these challenges, the SHAP (Shapley Additive Explanations) method was applied to generate a list of features, aiming to understand which characteristics influenced the models’ decision-making processes and, consequently, the prediction results for the five tumor types. The SHAP analysis identified 119, 80, and 10 genes for the RF, XGB, and DT models, respectively, totaling 209 genes, resulting in 172 unique genes. The new list, representing 0.8% of the original input features, is coherent and fully explainable, increasing confidence in the applied models. Additionally, the results suggest that the SHAP method can be effectively used as a feature selector in gene expression data. This approach not only enhances model transparency but also maintains high classification performance, highlighting its potential in identifying biologically relevant features that may serve as biomarkers for cancer diagnostics and treatment planning.
Lameness Recognition of Dairy Cows Based on Compensation Behaviour Analysis by Swing and Posture Features from Top View Depth Image
Authors: Zhang Ruihong , Zhao Kaixuan , Ji Jiangtao , Wang Jinjin
Published: December 2024

Top-view systems for lameness detection have advantages such as easy installation and minimal impact on farm work. However, the unclear lameness motion characteristics of the back result in lower recognition accuracy for these systems. Therefore, we analysed the compensatory behaviour of cows based on top-view walking videos, extracted compensatory motion features (CMFs), and constructed a model for recognising lameness in cows. By locating the hook, pin, sacrum, and spine positions, the motion trajectories of key points on the back were plotted. Based on motion trajectory analysis of 655 samples (258 sound, 267 mild lameness, and 130 severe lameness), the stability mechanisms of back movement posture were investigated, compensatory behaviours in lame cows were revealed, and methods for extracting CMFs were established, including swing and posture features. The feature correlation among differently scoring samples indicated that early-stage lame cows primarily exhibited compensatory swing, while those with severe lameness showed both compensatory swing and posture. Lameness classification models were constructed using machine learning and threshold discrimination methods, achieving classification accuracies of 81.6% and 83.05%, respectively. The threshold method reached a recall rate of 93.02% for sound cows. The proposed CMFs from back depth images are highly correlated with early lameness, improving the accuracy of top-view lameness detection systems.
Direct Determination of Flavanone Isomers in Citrus Juice by Paper Spray Tandem Mass Spectrometry
Authors: Bartella Lucia , Mazzotti Fabio , Santoro Ilaria , Talarico Ines Rosita , Di Donna Leonardo
Published: December 2024

A novel and efficient analytical protocol based on paper spray tandem mass spectrometry was developed for the determination of isomeric O-glycoside flavanones in citrus juices and beverages. This approach significantly reduces sample preparation time and solvent consumption compared to traditional chromatographic techniques. By exploiting the unique fragmentation patterns of these compounds, accurate quantification of both diglycosides and their individual isomers (neohesperidoside and rutinose derivatives) was achieved. The method demonstrated excellent analytical performance, with high accuracy, selectivity, and reproducibility. The impact of matrix effects was mitigated through the construction of ratio calibration curves, ensuring reliable quantification in complex matrices. Finally, a simple DPPH experiment to assay the antioxidant activity of each single positional isomer was performed, indicating the superior ability of neohesperidose conjugates. This simplified method offers a valuable tool for quality control, authenticity assessment and the study of health benefits associated with citrus consumption.
Regulation of Exogenous Strigolactone on Storage Substance Metabolism and Endogenous Hormone Levels in the Early Germination Stage of Rice Seeds Under Salt Stress
Authors: Zhang Jianqin , Zheng Dianfeng , Feng Naijie , Khan Aaqil , Deng Rui , Xiong Jian , Ding Linchong , Sun Zhiyuan , Li Jiahuan , Yang Xiaohui , Wu Chen
Published: December 2024

Salt stress inhibits rice seed germination. Strigolactone (GR24) plays a vital role in enhancing plant tolerance against salt stress. However, GR24’s impact on the metabolism of stored substances and endogenous hormones remains unclear. This study investigated the impact of exogenous GR24 on the metabolism of stored substances and endogenous hormones during the early stages of rice seed germination under salt stress. The results showed that salt stress significantly reduced the germination rate, germination potential, germination index, radicle length, germ length, and fresh and dry weights of the radicle and germ under salt stress. Pre-treatment (1.2 μmol L−1 GR24) significantly reduced the inhibition of salt stress on rice seed germination and seedling growth. GR24 promoted the decomposition of starch by enhancing the activities of α-amylase, β-amylase, and total amylase and improved the levels of soluble sugars and proteins and the conversion rate of substances under salt stress. GR24 effectively enhanced the activities of superoxide dismutase (SOD), catalase (CAT), and ascorbate peroxidase (APX); increased ascorbic acid (ASA) and glutathione (GSH) levels; and reduced malondialdehyde (MDA) content. This reduced the oxidative damage of salt stress. Furthermore, GR24 significantly increased the contents of strigolactones (SLs), auxin (IAA), gibberellin (GA3), cytokinin (CTK) as well as IAA/ABA, CTK/ABA, GA/ABA, and SL/ABA ratios and reduced abscisic acid (ABA) levels. The current findings indicate that GR24 effectively mitigates the adverse impact salt stress by regulating antioxidant enzyme activity and endogenous hormone balance.
Prediction of GNSS Velocity Accuracies Using Machine Learning Algorithms for Active Fault Slip Rate Determination and Earthquake Hazard Assessment
Authors: Solak Halil İbrahim
Published: December 2024

GNSS technology utilizes satellite signals to determine the position of a point on Earth. Using this location information, the GNSS velocities of the points can be calculated. GNSS velocity accuracies are crucial for studies requiring high precision, as fault slip rates typically range within a few millimeters per year. This study employs machine learning (ML) algorithms to predict GNSS velocity accuracies for fault slip rate estimation and earthquake hazard analysis. GNSS data from four CORS stations collected over 1-, 2-, and 3-year intervals with observation durations of 2, 4, 6, 8, and 12 h, were analyzed to generate velocity estimates. Position accuracies, observation intervals, and corresponding velocity accuracies formed two datasets for the East and North components. ML models, including Support Vector Machine, Random Forest, K-Nearest Neighbors, and Multiple Linear Regression, were used to model the relationship between position and velocity accuracies. The findings reveal that the Random Forest, which makes more accurate and reliable predictions by evaluating many decision trees together, achieved over 90% accuracy for both components. Velocity accuracies of ±1.3 mm/year were obtained for 1-year interval data, while accuracies of ±0.6 mm/year were achieved for the 2- and 3-year intervals. Three campaigns were deemed sufficient for Holocene faults with higher slip rates. However, for Quaternary faults with lower slip rates, longer observation periods or additional campaigns are necessary to ensure reliable velocity estimates. This highlights the need for GNSS observation planning based on fault activity.
Embrace the Era of Drones: A New Practical Design Approach to Emergency Rescue Drones
Authors: Wang Zhiyuan , Yang Ke , Wang Yonggang , Zhu Zechen , Liang Xiuli
Published: December 2024

To increase user satisfaction with emergency rescue drone products, a product modelling design method based on the fuzzy Kano-QFD-FBS model is proposed. First, the initial user requirements for the emergency rescue drone products are obtained through a questionnaire, and the fuzzy Kano model is utilised and combined with the better–worse coefficient method to categorise the attributes, define the priorities of the user requirements, and screen out the key user requirements. Second, the QFD model is used to construct the quality house, analyse the key user requirements quantitatively, and obtain the design elements and weights of the emergency rescue drone product. The obtained key design elements are subsequently imported into the FBS model to complete the mapping transformation from the functional elements to the structural elements of the emergency rescue drone products and realise the styling design of the emergency rescue drone products. Finally, the user satisfaction scale based on appearance, functionality, and interaction was developed and the System Usability Scale (SUS) was used to evaluate user satisfaction with the emergency rescue drone design scheme. The new design scheme scored higher and showed significant differences in satisfaction ratings compared to the previous scheme. Hefei Jiaxun Technology Co., Ltd. carried out product development for the design scheme. At present, physical products have been sold on the market and have achieved good results. Hefei Jiaxun Technology Co., Ltd. conducted a survey on consumer satisfaction with this product, and the results revealed that customer satisfaction increased by 11.9% compared with that of previous products. Compared with similar products in the market, the consumer satisfaction with this product increased by 13.5%, indicating that it has obvious market competitiveness. This study shows that the method of product styling design based on the fuzzy Kano-QFD-FBS model can comprehensively acquire and analyse user requirements, realise accurate mapping from user requirements to product design elements, and output the specific solution of the emergency rescue drone product styling design. The design scheme performs well in meeting user requirements, verifies the feasibility and effectiveness of the fuzzy Kano-QFD-FBS model in the styling design study of emergency rescue drones, and provides a new paradigm for emergency rescue product design.
Numerical Solution of Oxygen Diffusion Problem in Spherical Cell
Authors: Belabbes Soumaya , Boureghda Abdellatif
Published: December 2024

This study addresses the diffusion of oxygen in a spherical geometry with simultaneous absorption at a constant rate. The analytical method assumes a polynomial representation of the oxygen concentration profile, leading to a system of differential equations through mathematical manipulation. A numerical scheme is then employed to solve this system, linking the moving boundary and its velocity to determine the unknown functions within the assumed polynomial. An approximate analytical solution is obtained and compared with other methods, demonstrating very good agreement. This approach provides a novel method for addressing oxygen diffusion in spherical geometries, combining analytical techniques with numerical computations to efficiently solve for oxygen concentration profiles and moving boundary dynamics.
The Edge Odd Graceful Labeling of Water Wheel Graphs
Authors: Aljohani Mohammed , Daoud Salama Nagy
Published: December 2024

A graph, G=(V,E), is edge odd graceful if it possesses edge odd graceful labeling. This labeling is defined as a bijection g:E(G)→{1,3,…,2m−1}, from which an injective transformation is derived, g*:V(G)→{1,2,3,…,2m−1}, from the rule that the image of u∈V(G) under g* is ∑uv∈E(G)g(uv)mod(2m). The main objective of this manuscript is to introduce new classes of planar graphs, namely water wheel graphs, WWn; triangulated water wheel graphs, TWn; closed water wheel graphs, CWn; and closed triangulated water wheel graphs, CTn. Furthermore, we specify conditions for these graphs to allow for edge odd graceful labelings.
Co-Secure Domination Number in Some Graphs
Authors: Cui Jiatong , Li Tianhao , Zhang Jiayuan , Chen Xiaodong , Xiong Liming
Published: December 2024

Let G be a graph and S⊆V(G). If S is a dominating set of G, and for each vertex u∈V(G)−S, there is a neighbor of u in S, denoted by v, such that (S∖{v})∪{u} is a dominating set of G, then S is a secure dominating set (SDS) of G. Conversely, S is a co-secure dominating set (CSDS) of G if S is a dominating set of G and for each vertex v in S, V(G)−S contains a neighbor of v, denoted by u, such that (S∖{v})∪{u} is a dominating set of G. The minimum cardinality of a CSDS (resp. SDS) of G is the co-secure (resp. secure) domination number of G. We use γcs(G) and γs(G) to denote the co-secure domination number and secure domination number of G, respectively. Arumugam et al. proposed two questions: (1) Characterize a graph G with γcs(G)=α(G), where α(G) is the independence number of G; (2) Characterize a graph G with γcs(G)=γs(G). In this paper, we characterize some forbidden induced subgraphs for a graph G with γcs(G)=α(G); moreover, we obtain that γcs(G)=γs(G) for each {K3,C5,P5}-free graph G with δ(G)≥2. Our conclusions can generalize some known results.
IL-18 Blockage Reduces Neuroinflammation and Promotes Functional Recovery in a Mouse Model of Spinal Cord Injury
Authors: Begum Easmin , Mahmod Md Rashel , Rahman Md Mahbobur , Fukuma Fumiko , Urano Takeshi , Fujita Yuki
Published: December 2024

The prognosis of spinal cord injury (SCI) is closely linked to secondary injury processes, predominantly driven by neuroinflammation. Interleukin-18 (IL-18) plays a pivotal role in this inflammatory response. In previous work, we developed an anti-IL-18 antibody capable of neutralizing the active form of IL-18. This study evaluated the functional effects of this antibody in a mouse model of SCI. IL-18 expression was significantly upregulated in the spinal cord following injury. In a mouse model of SCI (C57BL/6J strain), mice were administered 150 μg of the anti-IL-18 antibody intraperitoneally. IL-18 inhibition via antibody treatment facilitated motor functional recovery post-injury. This intervention reduced neuronal death, reactive gliosis, microglia/macrophage activation, and neutrophil infiltration. Additionally, IL-18 inhibition lowered the expression of pro-inflammatory factors, such as IL-1β and the M1 microglia/macrophage marker Ccl17, while enhancing the expression of the M2 microglia/macrophage marker Arginase 1. Collectively, our findings demonstrate that IL-18 inhibition promotes motor recovery and facilitates the polarization of M1 microglia/macrophages to the M2 phenotype, thereby fostering a neuroprotective immune microenvironment in mice with SCI.
Application of Spatial Transcriptomics in Digestive System Tumors
Authors: Huang Bowen , Chen Yingjia , Yuan Shuqiang
Published: December 2024

In the field of digestive system tumor research, spatial transcriptomics technologies are used to delve into the spatial structure and the spatial heterogeneity of tumors and to analyze the tumor microenvironment (TME) and the inter-cellular interactions within it by revealing gene expression in tumors. These technologies are also instrumental in the diagnosis, prognosis, and treatment of digestive system tumors. This review provides a concise introduction to spatial transcriptomics and summarizes recent advances, application prospects, and technical challenges of these technologies in digestive system tumor research. This review also discusses the importance of combining spatial transcriptomics with single-cell RNA sequencing (scRNA-seq), artificial intelligence, and machine learning in digestive system cancer research.
Design and Validation of a Biomimetic Leg-Claw Mechanism Capable of Perching and Grasping for Multirotor Drones
Authors: Zhao Yan , Xiang Ruzhi , Li Hui , Wang Chang , Zhang Jianhua , Liu Xuan , Hao Yufei
Published: December 2024

Multirotor drones are widely used in fields such as environmental monitoring, agricultural inspection, and package delivery, but they still face numerous challenges in durability and aerial operation capabilities. To address these issues, this paper presents a biomimetic leg-claw mechanism (LCM) inspired by the biomechanics of birds. The claw of the LCM adopts a bistable gripper design that can rapidly close through external impact or actively close via the coordination of internal mechanisms. Additionally, its foldable, parallelogram-shaped legs bend under external forces, stretching the main tendon. A ratchet and pawl mechanism at the knee joint locks the leg in the bent position, thereby enhancing the gripping force of the claw. This paper calculates and experimentally verifies the degrees of freedom in different states, the forces required to open and close the gripper, the application scenarios of active and passive grasping, and the maximum load capacity of the mechanism. Furthermore, perching experiments demonstrate that the LCM enables the drone to perch stably on objects of varying diameters.
Investigating Energy Performance Criteria in Compliance with Iranian National Building Regulations: The Role of Residential Building Envelope Adjacency
Authors: Soltan Ahmadi Payam , Khoshgard Ahmad , Ahmadi Danesh Ashtiani Hossein
Published: December 2024

Energy consumption modeling in buildings is crucial for calculating energy performance indices and establishing criteria for energy labeling. Different countries utilize diverse approaches to calculate these indices based on energy efficiency regulations and classifications. In recent years, Iran has established energy compliance standards, outlined in Article 19 of the National Building Regulations, to improve the energy efficiency of buildings. This study aims to develop a systematic methodology for assessing energy consumption indicators in residential buildings using the criteria specified in the Iranian National Building Regulations. Our research examines three specific energy standard categories in residential buildings to evaluate the suitability of the energy compliance specifications and identify the distribution of energy indices, rather than relying solely on the fixed values prescribed in the regulations. Initially, three model building shapes were analyzed to demonstrate how different building envelope designs affect energy performance. This study fills a critical research gap by estimating energy consumption indices through a novel methodology that combines regression analysis and Monte Carlo simulation for the three energy classifications specified in Article 19 of the Iranian National Building Regulations. The study employs a permutation approach to evaluate the primary energy consumption indicators and the uncertainties arising from various adjacency configurations. Extensive simulations were conducted, resulting in the development of regression equations that account for the surface area of the building envelope adjacent to the outdoor environment. The Monte Carlo method was used to assess potential fluctuations in the adiabatic area of the building envelope and the area adjacent to the external environment for buildings with varying orientations, allowing for the generation of probability distributions for energy consumption intensities. The sensitivity analysis identified the critical components of the building envelope and their orientation that significantly impact the uncertainty of energy efficiency. The findings revealed that the west and east walls of buildings adjacent to the outdoor environment substantially influence the uncertainty of energy consumption. In contrast, the floor surface and south wall had the least significant effect on annual energy uncertainty. This innovative approach represents a significant advancement in the field. It plays a specific role in energy labeling for buildings by calculating the required standard deviation in energy consumption indices resulting from various envelope adjacencies. This research also has practical implications for building design and energy efficiency measurement.
Preparation and Application of Highly Efficient Self-Cleaning Coating g-C3N4/MoS2@PDMS
Authors: Gao Chunhua , Sima Yifei , Xiang Cong , Lv Zerun
Published: December 2024

Photocatalytic coatings are capable of achieving pollution-free degradation of organic pollutants on the surface of buildings. The preparation of photocatalytic coatings with high degradation efficiency, stability and durability constitutes a significant challenge in current widespread applications. This study prepared g-C3N4/MoS2 photocatalytic materials through a simple hydrothermal combined low-temperature calcination process, and selected the materials through characterization and photocatalytic degradation of organic wastewater experiments. Finally, poly(dimethylsiloxane) (PDMS) was added to obtain a g-C3N4/MoS2@PDMS coating. The coating was applied to the concrete surface, and, in the experiment, the coating showed good durability, stability, and high photocatalytic activity.
Minimally Invasive Fetoscopic Resection of Life-Threatening Amniotic Band Constrictions in a Human Fetus at 22 + 2 Weeks of Gestation Complicated by Subtotal Chorioamniotic Separation and Partial Placental Abruption
Authors: Riehle Nadja , Nowak Oliver , Messroghli Leila , Wakerlin Samantha , Schaible Thomas , Kohl Thomas
Published: December 2024

Amniotic band syndrome is a constrictive phenomenon in fetal development that can provoke limb autoamputation, malformation, trunk division, and umbilical cord strangulation. The latter two complications will ultimately lead to fetal demise if left untreated. If detected early enough, select cases may benefit from prenatal resection of the amniotic bands, thus preventing amputation and fetal death. Yet, especially in the presence of complete chorioamniotic separation, these procedures are rare, technically difficult, and not without significant risk. Objectives: The purpose of this report is to present the surgical technique and outcome of a challenging percutaneous fetoscopic intervention in a human fetus with amniotic band constrictions of a fetal thigh, retroplacental hematoma, partial placental abruption, subtotal chorioamniotic separation, and multiple amniotic bands encircling the umbilical cord. Methods: Minimally invasive, fetoscopic surgery to salvage the fetal life and lower leg was performed at 22 + 2 weeks of gestation under general maternofetal anesthesia. Results: Total resection of all amniotic bands was achieved, notwithstanding the aforementioned challenges. No surgical complications were observed. Despite preterm delivery at 25 + 4 weeks of gestation, the postnatal experience for the infant was favorable and uncomplicated as it furthermore benefitted from neonatal intensive care. At almost three years of age, the child remains healthy and demonstrates normal function of the formerly constricted leg. Conclusions: Our case shows that the combination of tested percutaneous fetoscopic techniques, high-risk obstetrics, and modern neonatology can overcome multiple obstacles in order to save a fetal patient stuck in a near-hopeless situation.
Effectiveness of Antiviral Treatment with Intravenous Peramivir and Oral Oseltamivir for Seasonal Influenza in Children
Authors: Byun Young-hoon , Kim Ji-Eun , Paek So-Hyun , Kim Min-Jung , Park Soo Hyun , Song Ho-Young , Kwon Jaehyun
Published: December 2024

Background/Objectives: Influenza poses significant risks in children, causing complications like febrile seizures and hospitalizations. Antiviral treatments include oseltamivir and peramivir, both FDA-approved neuraminidase inhibitors. This study aims to compare the effectiveness of intravenous peramivir and oral oseltamivir in pediatric patients presenting to an emergency department, with a primary focus on the revisit rate within 72 h post-treatment. Methods: A retrospective study analyzed 1327 children aged 1–15 years diagnosed with influenza A or B between 1 January 2019 and 29 February 2020, at a single urban hospital. Patients were divided into oseltamivir (n = 1243) and peramivir (n = 84) groups. Data included demographics, clinical symptoms, emergency department stays, and revisit rates. Fisher’s exact test was used for analysis, with p-values < 0.05 considered significant. Results: A total of 1327 pediatric patients were included, with 1243 receiving oseltamivir and 84 receiving peramivir. Patients in the peramivir group were older (median age 5.88 years vs. 4.54 years, p = 0.002) and had higher rates of gastrointestinal symptoms. The emergency department length of stay was significantly longer in the peramivir group (167 min vs. 63 min, p < 0.001). The revisit rate within 3 days was 5.63% for oseltamivir and 9.52% for peramivir, with no statistically significant difference (p = 0.22). Conclusions: Peramivir presents as an effective alternative treatment for influenza in children, particularly in situations where oral administration is not feasible due to gastrointestinal intolerance, highlighting the importance of an alternative route of antiviral administration.
Security Proof of Single-Source Shortest Distance Protocols Built on Secure Multiparty Computation Protocols
Authors: Anagreh Mohammad , Laud Peeter
Published: December 2024

Secure secret-sharing Single-Source Shortest Distance (SSSD) protocols, based on secure multiparty computation (SMC), offer a promising solution for securely distributing and managing sensitive information among multiple parties. However, formal security proofs for these protocols have largely been unexplored. This paper addresses this gap by providing the first security proof for the SSSD protocols using the privacy-preserving Bellman–Ford protocols. These new protocols offer significant enhancements in efficiency, particularly in handling large-scale graphs due to parallel computation. In our previous work, published in MDPI Cryptography, we introduced these protocols and presented extensive experiments on the Sharemind system that demonstrated their efficiency. However, that work did not include security proofs. Building on this foundation, the current paper rigorously proves the security of these protocols, offering valuable insights into their robustness and reliability. Furthermore, we discuss the adversarial model, security definitions, cryptographic assumptions, and sophisticated reduction techniques employed in the proof. This paper not only validates the security of the proposed protocols but also provides a detailed comparison of their performance with existing methods, highlighting their strengths and potential for future research in the field.
Integrated Prediction of Gas Metal Arc Welding Multi-Layer Welding Heat Cycle, Ferrite Fraction, and Joint Hardness of X80 Pipeline Steel
Authors: Yan Chen , Li Haonan , Yang Die , Gao Yanan , Deng Jun , Zhang Zhihang , Dong Zhibo
Published: December 2024

X80 pipeline steel is widely used in oil and gas pipelines because of its excellent strength, toughness, and corrosion resistance. It is welded via gas metal arc welding (GMAW), risking high cold crack sensitivities. There is a certain relationship between the joint hardness and cold crack sensitivity of welded joints; thus, predicting the joint hardness is necessary. Considering the inefficiency of welding experiments and the complexity of welding parameters, we designed a set of processes from temperature field analysis to microstructure prediction and finally hardness prediction. Firstly, we calculated the thermal cycle curve during welding through multi-layer welding numerical simulation using the finite element method (FEM). Afterwards, BP neural networks were used to predict the cooling rates in the temperature interval that ferrite nuclears and grows. Introducing the cooling rates to the Leblond function, the ferrite fraction of the joint was given. Based on the predicted ferrite fraction, mapping relationships between joint hardness and the joint ferrite fraction were built using BP neural networks. The results shows that the error during phase fraction prediction is less than 8%, and during joint hardness prediction, it is less than 5%.
Matched Unrelated Donor Hematopoietic Cell Transplantation: Increased Usage and Improvements in Clinical Outcomes in Canada
Authors: Seftel Matthew D. , Musto Grace , Allan David , Bucher Oliver , Hay Kevin , Pasic Ivan , Truong Tony , Paulson Kristjan
Published: December 2024

In allogeneic hematopoietic cell transplantation (HCT), a minority of patients have access to a suitable human leukocyte antigen (HLA)-matched related donor (MRD). To fill this gap, matched unrelated donors (MUDs) are an increasingly selected donor source. Usage and outcomes after MUD HCT for Canada are not described. We investigated temporal trends in MUD compared to MRD HCT from 2000 to 2019 using data reported to the Cell Therapy and Transplant Canada (CTTC) Registry. Of 7571 first allogeneic HCTs between 2000 and 2019, the proportion of MUD HCTs rose from 35.1% to 56.3% in the early (2000–2009) and later (2010–2019) eras, respectively. Comparing the two donor sources, the 5-year overall survival (OS) after MUD HCT for patients with malignant diseases was inferior to MRD HCT in the early era (p < 0.001). However, in the later era, OS was comparable for the two donor sources (p = 0.969). For patients with non-malignant diseases, the 5-year OS after MUD HCT was inferior to MRD in the early era (p < 0.001), but in the later era, the 5-year OS was similar between the two donor sources (p = 0.209). Improvements in OS after MUD HCT were accompanied by corresponding reductions in the 2-year non-relapse mortality after MUD HCT. We conclude that MUDs are the most common donor source in Canada, and key clinical outcomes after MUD have improved over time.
Noise-Perception Multi-Frame Collaborative Network for Enhanced Polyp Detection in Endoscopic Videos
Authors: Li Haoran , Zhen Guoyong , Chu Chengqun , Ma Yuting , Zhao Yongnan
Published: December 2024

The accurate detection and localization of polyps during endoscopic examinations are critical for early disease diagnosis and cancer prevention. However, the presence of artifacts and noise, along with the high similarity between polyps and surrounding tissues in color, shape, and texture complicates polyp detection in video frames. To tackle these challenges, we deployed multivariate regression analysis to refine the model and introduced a Noise-Suppressing Perception Network (NSPNet) designed for enhanced performance. NSPNet leverages wavelet transform to enhance the model’s resistance to noise and artifacts while improving a multi-frame collaborative detection strategy for dynamic polyp detection in endoscopic videos, efficiently utilizing temporal information to strengthen features across frames. Specifically, we designed a High-Low Frequency Feature Fusion (HFLF) framework, which allows the model to capture high-frequency details more effectively. Additionally, we introduced an improved STFT-LSTM Polyp Detection (SLPD) module that utilizes temporal information from video sequences to enhance feature fusion in dynamic environments. Lastly, we integrated an Image Augmentation Polyp Detection (IAPD) module to improve performance on unseen data through preprocessing enhancement strategies. Extensive experiments demonstrate that NSPNet outperforms nine SOTA methods across four datasets on key performance metrics, including F1Score and recall.
A Deep Reinforcement Learning-Based Dynamic Replenishment Approach for Multi-Echelon Inventory Considering Cost Optimization
Authors: Zhang Yang , He Lili , Zheng Junhong
Published: December 2024

In the fast-moving consumer goods (FMCG) industry, inventory management is a critical component of supply chain management because it directly impacts cost efficiency and customer satisfaction. For instance, effective inventory management can minimize overstocking and reduce replenishment delays, which are particularly important in multi-echelon supply chain systems characterized by high complexity and dynamic demand. This study proposes a method based on deep reinforcement learning (DRL) aimed at optimizing replenishment decisions in multi-echelon inventory systems for FMCG industries. We designed a Dynamic Replenishment FMCG Multi-Echelon Optimization (ME-DRFO) model and incorporated a Markov Decision Process (MDP) to model the multi-echelon inventory system. By applying an improved Soft Actor–Critic with an adaptive alpha and learning rate (SAC-AlphaLR) algorithm, which introduces adaptive temperature parameters and adaptive learning rate mechanisms, our approach not only dynamically adapts to environmental changes but also effectively balances exploration and exploitation, ultimately achieving global replenishment cost minimization while ensuring supply chain stability. Through numerical experiments, our method demonstrates excellent performance by reducing replenishment costs by 12.31% and decreasing inventory shortages to 2.21%, significantly outperforming traditional methods such as overstocking, Particle Swarm Optimization (PSO), and the standard Soft Actor–Critic (SAC). This research provides new theoretical insights into multi-echelon inventory optimization and practical solutions for effectively managing complex supply chains under uncertain and dynamic conditions.
Energy Poverty in Bosnia and Herzegovina: Challenges, Solutions, and Policy Recommendations
Authors: Muftić Dedović Maja , Avdaković Samir , Mujezinović Adnan , Dautbašić Nedis , Alihodžić Ajdin , Memić Adin
Published: December 2024

Energy poverty remains a significant issue in Bosnia and Herzegovina, characterized by limited access to affordable and sustainable energy sources. This paper examines the prevalence of energy poverty among 1500 retiree households and evaluates the potential of photovoltaic (PV) systems as a solution. The research highlights the multidimensional nature of energy poverty, incorporating variables such as income, energy expenditures, and heating methods. Using statistical methods, including factor analysis and regression models, the research developed an energy poverty index (EPI) to categorize households and identify key drivers of energy poverty. The findings reveal that 96.5% of households experience moderate to high energy poverty when transport costs are included, dropping to 84.3% when these costs are excluded. Households using wood for heating, with a combined rooftop area of 26,104 m2, could generate 7,831,200 kWh of solar energy annually, reducing CO2 emissions by 1,389,825 kg. The aggregated payback period for PV investments is approximately 9.3 years, demonstrating financial viability. The paper underscores the potential of energy communities in pooling resources, facilitating rooftop leasing for PV installations, and promoting policy reforms to promote renewable energy adoption. This research contributes to the understanding of energy poverty dynamics and provides actionable recommendations for integrating PV power plants, fostering energy equity, and reducing environmental impacts.
Numerical Assessment of a Heavy-Duty (HD) Spark Ignition (SI) Biogas Engine
Authors: Ballerini Alberto , Lucchini Tommaso , Onorati Angelo
Published: December 2024

This paper examines the feasibility of converting a Heavy-Duty (HD) Spark Ignition (SI) Compressed Natural Gas (CNG) engine to biogas fuel. A One-Dimensional (1D) simulation tool was used to model a commercially available HD SI CNG engine. The model was validated by comparing experimental and computed in-cylinder pressure, brake power, fuel, and air mass flow rates. The engine was then modified to use biogas with an injection system based on existing designs from the literature. A Spark Advance (SA) sweep was performed to assess the engine’s performance at full load. The chosen equivalence ratio was 0.85, and the engine speed was 1500 rpm. The Maximum Brake Power (MBP) and Maximum Brake Efficiency (MBE) operating points were identified. Partial load analysis was conducted starting from the MBP conditions. Results in terms of brake power, brake efficiency, and NOx emissions are presented. Conversion to biofuel results in a reduction in power and efficiency of 33% and 4%, respectively, at 1500 rpm and full load conditions. Brake Specific NOx emissions remained comparable. This numerical study demonstrates the feasibility of biogas conversion for HD SI engines, offering a renewable fuel alternative to reduce greenhouse gas emissions, though with trade-offs in power and efficiency.
A Semiconductor Current-Limiting Device Based on a DC Converter
Authors: Safonov Evgeniy P. , Frolov Vladimir Ya. , Boeshko Anton V. , Dautov Ruslan S.
Published: December 2024

Short-circuit currents in autonomous and isolated electrical complexes today are approaching the switching capacity of operated circuit breakers. Since the existing equivalents cannot ensure the necessary reliability of power supply to consumers in emergency situations, it is pertinent to assess the need for developing new types of current-limiting devices (CLDs). This paper proposes an electrical circuit of a semiconductor current-limiting device based on a step-down DC-DC converter, where the main switch is a thyristor with an artificially switched circuit. Transient processes during the operation of the device are considered in detail. A mathematical model of the device is also provided. This model was verified by modeling the CLD circuit in MATLAB Simulink. In turn, the validity of the computer model used was proven experimentally. During the experiments, the current-limiting efficiency of the circuit was demonstrated, and its proposed mathematical model was also confirmed. This research was carried out as part of the project within the State Assignment FSEG-2023-0012.
Study of Fire Plume Behavior and Maximum Ceiling Temperature Rise in a Curved Tunnel Driven by the Coupling of Blockage Effect and Longitudinal Ventilation
Authors: Zhang Xin , Li Jie , He Hao , Chen Xiaofeng , Zhu Kai , Yin Mingjian , Cao Ying , Wu Ke
Published: December 2024

Tunnel fires often lead to vehicles being trapped inside, causing the “blocking effect”. In this work, fire plume behavior and the maximum ceiling temperature rise in a curved tunnel with blocked vehicles under longitudinal ventilation conditions are studied numerically. The results show that, in curved tunnels, the fire plume in the quasi-stable state exhibits dynamic deflections between the concave and convex walls of the tunnel, so the location of high-temperature zones varies accordingly. The flow field structure in the near field of the blockage and the fire source is complex but can be decoupled into four characteristic sub-structures, i.e., the free shear layer, recirculation I above the vehicle blockage, recirculation II behind the downstream of the blockage, and recirculation III at the top of the tunnel. Recirculation I and II pull the fire plume upstream, while free shear layer and recirculation III pull the flame downstream. The final plume deflection direction depends on the relative strengths of these two pulling forces. As the longitudinal air velocity increases, the plume deflection direction changes from downstream to upstream of the fire source, forming the “downstream tilt—touch the ceiling above the fire source—upstream tilt” mode, resulting in the maximum ceiling temperature rise fluctuating in a decreasing-increasing-decreasing trend. Moreover, the higher the blocking ratio, the lower the critical air velocity required to induce the transition of the plume deflection directions, e.g., a critical wind speed of 3 m/s for a blockage ratio of 0.46 and a critical wind speed of 1 m/s for a blockage ratio of 0.62. Finally, a semi-empirical equation of the maximum ceiling temperature rise in curved tunnels, considering both longitudinal wind and the vehicle blocking ratio, is proposed and validated. This work highlights the multi-dimensional and non-stable plume behavior pattern in a complex tunnel fire scenario, thus providing a deeper understanding to improve the classical tunnel fire dynamic system.
Strangulation Using Cable Ties and a Suicidal Manner of Death: A Case Report and Literature Review Addressing an Atypical Suicidal Mode
Authors: Cecannecchia Camilla , De Simone Stefania , Baldari Benedetta , Cipolloni Luigi , Cioffi Andrea
Published: December 2024

Background: Strangulation by ligature, most frequently employed for homicidal purposes, is not a common suicide method. Even more infrequent is the use by the victim of cable ties as a tool of self-strangulation. Methods: We describe a case of a 50-year-old woman who was found dead with a cable tie tight around her neck. In our case, analysis of the circumstantial data and the psychopathological history of the victim—along with an external examination, an autopsy, and toxicological findings—was crucial in the differential diagnosis between death intentionally inflicted by a third person and suicide. Through a narrative review conducted by performing a literature search using online resources (PubMed, Google Scholar, and ScienceDirect). Results: we were only able to identify eight similar cases. Conclusions: These were compared with our case, to trace similarities and differences, useful in guiding the forensic doctor in the diagnosis of death in such circumstances.