bluuebunny/crossref_metadata_2025_split huggingface dataset:
Carbon redirection via tunable Fenton-like reactions under nanoconfinement toward sustainable water treatment
Authors: Gao Xiang , Yang Zhichao , Zhang Wen , Pan Bingcai 
Published: April 2024

AbstractThe ongoing pattern shift in water treatment from pollution control to energy recovery challenges the energy-intensive chemical oxidation processes that have been developed for over a century. Redirecting the pathways of carbon evolution from molecular fragmentation to polymerization is critical for energy harvesting during chemical oxidation, yet the regulation means remain to be exploited. Herein, by confining the widely-studied oxidation system—Mn3O4 catalytic activation of peroxymonosulfate—inside amorphous carbon nanotubes (ACNTs), we demonstrate that the pathways of contaminant conversion can be readily modulated by spatial nanoconfinement. Reducing the pore size of ACNTs from 120 to 20 nm monotonously improves the pathway selectivity toward oligomers, with the yield one order of magnitude higher under 20-nm nanoconfinement than in bulk. The interactions of Mn3O4 with ACNTs, reactant enrichment, and pH lowering under nanoconfinement are evidenced to collectively account for the enhanced selectivity toward polymerization. This work provides an adaptive paradigm for carbon redirection in a variety of catalytic oxidation processes toward energy harvesting and sustainable water purification.
A multimodal driver monitoring benchmark dataset for driver modeling in assisted driving automation
Authors: Dargahi Nobari Khazar , Bertram Torsten 
Published: March 2024

AbstractIn driver monitoring various data types are collected from drivers and used for interpreting, modeling, and predicting driver behavior, and designing interactions. Aim of this contribution is to introduce manD 1.0, a multimodal dataset that can be used as a benchmark for driver monitoring in the context of automated driving. manD is the short form of human dimension in automated driving. manD 1.0 refers to a dataset that contains data from multiple driver monitoring sensors collected from 50 participants, gender-balanced, aged between 21 to 65 years. They drove through five different driving scenarios in a static driving simulator under controlled laboratory conditions. The automation level (SAE International, Standard J3016) ranged from SAE L0 (no automation, manual) to SAE L3 (conditional automation, temporal). To capture data reflecting various mental and physical states of the subjects, the scenarios encompassed a range of distinct driving events and conditions. manD 1.0 includes environmental data such as traffic and weather conditions, vehicle data like the SAE level and driving parameters, and driver state that covers physiology, body movements, activities, gaze, and facial information, all synchronized. This dataset supports applications like data-driven modeling, prediction of driver reactions, crafting of interaction strategies, and research into motion sickness.
A fair bed allocation during COVID-19 pandemic using TOPSIS technique based on correlation coefficient for interval-valued pythagorean fuzzy hypersoft set
Authors: Zulqarnain Rana Muhammad , Ma Wen-Xiu , Siddique Imran , Ahmad Hijaz , Askar Sameh 
Published: April 2024

AbstractThe relationship between two variables is an essential factor in statistics, and the accuracy of the results depends on the data collected. However, the data collected for statistical analysis can be unclear and difficult to interpret. One way to predict how one variable will change about another is by using the correlation coefficient (CC), but this method is not commonly used in interval-valued Pythagorean fuzzy hypersoft set (IVPFHSS). The IVPFHSS is a more advanced and generalized form of the Pythagorean fuzzy hypersoft set (PFHSS), which allows for more precise and accurate analysis. In this research, we introduce the correlation coefficient (CC) and weighted correlation coefficient (WCC) for IVPFHSS and their essential properties. To demonstrate the applicability of these measures, we use the COVID-19 pandemic as an example and establish a prioritization technique for order preference by similarity to the ideal solution (TOPSIS) model. The technique is used to study the problem of optimizing the allocation of hospital beds during the pandemic. This study provides insights into the importance of utilizing correlation measures for decision-making in uncertain and complex situations like the COVID-19 pandemic. It is a robust multi-attribute decision-making (MADM) methodology with significant importance. Subsequently, it is planned to increase a dynamic bed allocation algorithm based on biogeography to accomplish the superlative decision-making system. Moreover, numerical investigations deliberate the best decision structures and deliver sensitivity analyses. The efficiency of our encouraged algorithm is more consistent than prevalent models, and it can effectively control and determine the optimal configurations for the study.
Information heterogeneity between progress notes by physicians and nurses for inpatients with digestive system diseases
Authors: Mashima Yukinori , Tanigawa Masatoshi , Yokoi Hideto 
Published: April 2024

AbstractThis study focused on the heterogeneity in progress notes written by physicians or nurses. A total of 806 days of progress notes written by physicians or nurses from 83 randomly selected patients hospitalized in the Gastroenterology Department at Kagawa University Hospital from January to December 2021 were analyzed. We extracted symptoms as the International Classification of Diseases (ICD) Chapter 18 (R00–R99, hereinafter R codes) from each progress note using MedNER-J natural language processing software and counted the days one or more symptoms were extracted to calculate the extraction rate. The R-code extraction rate was significantly higher from progress notes by nurses than by physicians (physicians 68.5% vs. nurses 75.2%; p = 0.00112), regardless of specialty. By contrast, the R-code subcategory R10–R19 for digestive system symptoms (44.2 vs. 37.5%, respectively; p = 0.00299) and many chapters of ICD codes for disease names, as represented by Chapter 11 K00–K93 (68.4 vs. 30.9%, respectively; p < 0.001), were frequently extracted from the progress notes by physicians, reflecting their specialty. We believe that understanding the information heterogeneity of medical documents, which can be the basis of medical artificial intelligence, is crucial, and this study is a pioneering step in that direction.
Aspirin/amoxicillin loaded chitosan microparticles and polydopamine modified titanium implants to combat infections and promote osteogenesis
Authors: Shi Yun , Lai Yongzhen , Guo Yan , Cai Zhiyu , Mao Chuanqing , Lu Meng , Ren Chengyan , Ong Joo L. , Chen Weihui 
Published: April 2024

AbstractIt is known that titanium (Ti) implant surfaces exhibit poor antibacterial properties and osteogenesis. In this study, chitosan particles loaded with aspirin, amoxicillin or aspirin + amoxicillin were synthesized and coated onto implant surfaces. In addition to analysing the surface characteristics of the modified Ti surfaces, the effects of the modified Ti surfaces on the adhesion and viability of rat bone marrow-derived stem cells (rBMSCs) were evaluated. The metabolic activities of Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) biofilms on the modified Ti surfaces were also measured in vitro. Moreover, S. aureus was tested for its antibacterial effect by coating it in vivo. Using water as the droplet medium, the contact angles of the modified Ti surfaces increased from 44.12 ± 1.75° to 58.37 ± 4.15°. In comparison to those of the other groups tested, significant increases in rBMSC adhesion and proliferation were observed in the presence of aspirin + amoxicillin-loaded microspheres, whereas a significant reduction in the metabolic level of biofilms was observed in the presence of aspirin + amoxicillin-loaded microspheres both in vitro and in vivo. Aspirin and amoxicillin could be used in combination to coat implant surfaces to mitigate bacterial activities and promote osteogenesis.
Image convolution techniques integrated with YOLOv3 algorithm in motion object data filtering and detection
Authors: Cheng Mai , Liu Mengyuan 
Published: April 2024

AbstractIn order to address the challenges of identifying, detecting, and tracking moving objects in video surveillance, this paper emphasizes image-based dynamic entity detection. It delves into the complexities of numerous moving objects, dense targets, and intricate backgrounds. Leveraging the You Only Look Once (YOLOv3) algorithm framework, this paper proposes improvements in image segmentation and data filtering to address these challenges. These enhancements form a novel multi-object detection algorithm based on an improved YOLOv3 framework, specifically designed for video applications. Experimental validation demonstrates the feasibility of this algorithm, with success rates exceeding 60% for videos such as “jogging”, “subway”, “video 1”, and “video 2”. Notably, the detection success rates for “jogging” and “video 1” consistently surpass 80%, indicating outstanding detection performance. Although the accuracy slightly decreases for “Bolt” and “Walking2”, success rates still hover around 70%. Comparative analysis with other algorithms reveals that this method’s tracking accuracy surpasses that of particle filters, Discriminative Scale Space Tracker (DSST), and Scale Adaptive Multiple Features (SAMF) algorithms, with an accuracy of 0.822. This indicates superior overall performance in target tracking. Therefore, the improved YOLOv3-based multi-object detection and tracking algorithm demonstrates robust filtering and detection capabilities in noise-resistant experiments, making it highly suitable for various detection tasks in practical applications. It can address inherent limitations such as missed detections, false positives, and imprecise localization. These improvements significantly enhance the efficiency and accuracy of target detection, providing valuable insights for researchers in the field of object detection, tracking, and recognition in video surveillance.
Efficacy and safety of radiofrequency ablation versus surgical sympathectomy in palmar hyperhidrosis
Authors: Zhong Yiyue , Zhu Yanwen , Li Jiayan , Yang Xiaowei , Feng Zhiying , Liu Haipeng , Liang Zhu , Lin Baoquan , Liu Zhifeng , Wang Xin , Luo Weibin , Zhu Jian , Li Bin , Lai Shangdao , Jiang Weize , Wu Jiayuan , Li Daheng , Zhang Liangqing , Huang Bing , Tang Jing 
Published: April 2024

AbstractRadiofrequency ablation (RFA) comparative efficacy of treatments using video-assisted thoracoscopic sympathectomy (VATS) in the long term remains uncertain in patients with palmar hyperhidrosis (PHH). This study aimed to compare the efficacy and safety of RFA and VATS in patients with PHH. We recruited patients aged ≥ 14 years with diagnosed PHH from 14 centres in China. The treatment options of RFA or VATS were assigned to two cohort in patients with PHH. The primary outcome was the efficacy at 1-year. A total of 807 patients were enrolled. After propensity score matching, the rate of complete remission was lower in RFA group than VATS group (95% CI 0.21–0.57; p < 0.001). However, the rates of palmar dryness (95% CI 0.38–0.92; p = 0.020), postoperative pain (95% CI 0.13–0.33; p < 0.001), and surgery-related complications (95% CI 0.19–0.85; p = 0.020) were lower in RFA group than in VATS group, but skin temperature rise was more common in RFA group (95% CI 1.84–3.58; p < 0.001). RFA had a lower success rate than VATS for the complete remission of PHH. However, the symptom burden and cost are lower in patients undergoing RFA compared to those undergoing VATS.Trial Registration: ChiCTR2000039576, URL: http://www.chictr.org.cn/index.aspx.
A methodology for image-based measurement of plate movement in disengaged wet clutches
Authors: Pointner-Gabriel Lukas , Flamm Simon , Schneider Thomas , Stahl Karsten 
Published: April 2024

AbstractThe drag loss behavior of a disengaged wet clutch is influenced, among other things, by the movement of the plates. Therefore, knowledge about the plate movement is essential for investigating and optimizing the drag loss behavior. This paper presents a methodology for image-based measurement of plate movement in disengaged wet clutches. A drag torque test rig is equipped with a camera to create the image series. The oil displacement from the measuring zone is crucial to obtain permanent optical access to the clutch pack. The rough plate positions are determined by segmentation using thresholding and template matching. Using the Canny edge detector significantly improves the accuracy of the position evaluation. The plate positions are finally converted into a metric unit based on the real plate thicknesses. The clearances are calculated from the determined positions of two adjacent plates. In the ideal case, an evaluation accuracy in the range of a few micrometers can be achieved. The image evaluation methodology is universally applicable to different clutch sizes, friction systems, plate types, and plate numbers. The methodology enables researchers to generate fundamental knowledge and derive design guidelines based on this, for example. In the development phase, it can also be used to optimize the design and operating parameters.
Dynamics of the time-fractional reaction–diffusion coupled equations in biological and chemical processes
Authors: Ghafoor Abdul , Fiaz Muhammad , Hussain Manzoor , Ullah Asad , Ismail Emad A. A. , Awwad Fuad A. 
Published: March 2024

AbstractThis paper aims to demonstrate a numerical strategy via finite difference formulations for time fractional reaction–diffusion models which are ubiquitous in chemical and biological phenomena. The time-fractional derivative is considered in the Caputo sense for both linear and nonlinear problems. First, the Caputo derivative is replaced with a quadrature formula, then an implicit method is used for the remaining part. In the linear case, the proposed strategy reduces the time fractional models into linear simultaneous equations. In nonlinear cases, Quasilinearization is utilized to tackle the nonlinear parts. With this strategy, solutions of the fractional system transform into linear algebraic systems which are easy to solve. Next, the Von Neumann method is implemented to examine the stability of the scheme which discloses that the scheme is unconditionally stable. Further, the applicability of the presented scheme is tested with different linear and nonlinear models which include the one dimensional Schnakenberg and Gray–Scott models, and one and two dimensional Brusselator models. To analyze the accuracy of the present technique two norms namely, $$\mathbb {L}_{\infty }$$

L
∞

and $$\mathbb {L}_{2}$$

L
2

, and relative error are addressed. Moreover, the obtained outcomes are shown tabulated and graphically which identifies that the scheme properly works for the time fractional reaction–diffusion systems.
Speeding up the classical simulation of Gaussian boson sampling with limited connectivity
Authors: Yang Tian-Yu , Wang Xiang-Bin 
Published: April 2024

AbstractGaussian boson sampling (GBS) plays a crucially important role in demonstrating quantum advantage. As a major imperfection, the limited connectivity of the linear optical network weakens the quantum advantage result in recent experiments. In this work, we introduce an enhanced classical algorithm for simulating GBS processes with limited connectivity. It computes the loop Hafnian of an$$n \times n$$n×nsymmetric matrix with bandwidthwin$$O(nw2^w)$$O(nw2w)time. It is better than the previous fastest algorithm which runs in$$O(nw^2 2^w)$$O(nw22w)time. This classical algorithm is helpful on clarifying how limited connectivity affects the computational complexity of GBS and tightening the boundary for achieving quantum advantage in the GBS problem.
Contrasting responses of Thermocyclops crassus and T. oithonoides (Crustacea, Copepoda) to thermal stress
Authors: Nowakowski Kacper , Sługocki Łukasz 
Published: April 2024

AbstractThermal tolerance is a critical factor influencing the survival of living organisms. This study focuses on the thermal resistance of copepod species, Thermocyclops crassus (Fischer, 1853) and T. oithonoides (Sars G.O., 1863), with overlapping distribution ranges in Europe. Short-term heat shock experiments were conducted to assess the thermal resistance of these copepods, considering various temperature increments and exposure durations. Additionally, the study explored the influence of heat shock on egg sac shedding, a vital indicator of population dynamics. Results indicate that widely distributed T. crassus exhibits higher thermal tolerance compared to narrowly distributed T. oithonoides, with survival rates varying under different heat shock conditions. Furthermore, T. crassus demonstrated a quicker response in dropping egg sacs in response to thermal stress, suggesting a potential adaptive mechanism for the survival of adults. However, rapid egg sac droppings pose high risks for eggs facing unfavorable conditions. T. crassus, inhabiting environments with greater temperature fluctuations such as the littoral and pelagial zones, exhibited better survival mechanisms compared to T. oithonoides, which predominantly resides in the pelagic zone. The findings have implications for understanding copepod responses to global warming and thermal pollution. This research contributes insights into the adaptive strategies of thermophilic copepod species and their ecological consequences.
In vivo evaluation of safety and performance of a tapered nitinol venous stent with inclined proximal end in an ovine iliac venous model
Authors: Wu Zhongjian , Zhou Zhengtong , Bian Chunjing , Guo Lianrui , Tong Zhu , Guo Jianming , Qi Lixing , Cui Shijun , Zhang Chengchao , Chen Yilong , Huang Wei , Gu Yongquan 
Published: April 2024

AbstractA tapered stent with inclined proximal end is designed for fitting the iliac anatomically. The aim of the present study was to evaluate the safety and performance of the new stent in ovine left iliac veins. The experiment was performed in 30 adult sheep, and one nitinol-based VENA-BT® iliac venous stent (KYD stent) was implanted into each animal’s left common iliac vein. Follow-up in all sheep consisted of angiographic, macroscopic, and microscopic examinations at Day 0 (< 24 h), Day 30, Day 90, Day 180 and Day 360 post-stenting (six animals per each time-point). 30 healthy ~ 50 kg sheep were included in this study and randomly divided into five groups according to the follow-up timepoint. All stents were implanted successfully into the left ovine common iliac vein. No significant migration occurred at follow-up. There is no statistically significant difference between the groups (p > 0.05), indicating no serious lumen loss occurred during the follow-up period. Common iliac venous pressure was further measured and the results further indicated the lumen patency at follow-up. Histological examinations indicated that no vessel injury and wall rupture, stent damage, and luminal thrombus occurred. There was moderate inflammatory cell infiltration around the stent in Day-0 and Day-30 groups with the average inflammation score of 2.278 and 2.167, respectively. The inflammatory reaction was significantly reduced in Day-90, Day-180 and Day-360 groups and the average inflammation scores were 0.9444 (p < 0.001, Day-90 vs Day-0), 1.167 (p < 0.001, Day-180 vs Day-0) and 0.667 (p < 0.001, Day-90 vs Day-0), respectively. The microscopic examinations found that the stents were well covered by endothelial cells in all follow-up time points. The results suggested that the KYD stent is feasible and safe in animal model. Future clinical studies may be required to further evaluate its safety and efficacy.
LncRNA GAS5 restrains ISO-induced cardiac fibrosis by modulating mir-217 regulation of SIRT1
Authors: Zhang Yan-hong , Sun Ting-ting , Liu Zhen-hua , Li Xu , Fan Xiao-Fang , Han Li-ping 
Published: April 2024

AbstractConsidering the effect of SIRT1 on improving myocardial fibrosis and GAS5 inhibiting occurrence and development of myocardial fibrosis at the cellular level, the aim of the present study was to investigate whether LncRNA GAS5 could attenuate cardiac fibrosis through regulating mir-217/SIRT1, and whether the NLRP3 inflammasome activation was involved in this process. Isoprenaline (ISO) was given subcutaneously to the male C57BL/6 mice to induce myocardial fibrosis and the AAV9 vectors were randomly injected into the left ventricle of each mouse to overexpress GAS5. Primary myocardial fibroblasts (MCFs) derived from neonatal C57BL/6 mice and TGF-β1 were used to induce fibrosis. And the GAS5 overexpressed MCFs were treated with mir-217 mimics and mir-217 inhibitor respectively. Then the assays of expression levels of NLRP3, Caspase-1, IL-1β and SIRT1 were conducted. The findings indicated that the overexpression of GAS5 reduced the expression levels of collagen, NLRP3, Capase-1, IL-1β and SIRT1 in ISO treated mice and TGF-β1 treated MCFs. However, this effect was significantly weakened after mir-217 overexpression, but was further enhanced after knockdown of mir-217. mir-217 down-regulates the expression of SIRT1, leading to increased activation of the NLRP3 inflammasome and subsequent pyroptosis. LncRNA GAS5 alleviates cardiac fibrosis induced via regulating mir-217/SIRT1 pathway.
Machine learning-based survival prediction nomogram for postoperative parotid mucoepidermoid carcinoma
Authors: Huang Zongwei , Chen Zihan , Li Ying , Lin Ting , Cai Sunqin , Wu Wenxi , Wu Lishui , Xu Siqi , Lu Jun , Qiu Sufang 
Published: April 2024

AbstractParotid mucoepidermoid carcinoma (P-MEC) is a significant histopathological subtype of salivary gland cancer with inherent heterogeneity and complexity. Existing clinical models inadequately offer personalized treatment options for patients. In response, we assessed the efficacy of four machine learning algorithms vis-à-vis traditional analysis in forecasting the overall survival (OS) of P-MEC patients. Using the SEER database, we analyzed data from 882 postoperative P-MEC patients (stages I–IVA). Single-factor Cox regression and four machine learning techniques (random forest, LASSO, XGBoost, best subset regression) were employed for variable selection. The optimal model was derived via stepwise backward regression, Akaike Information Criterion (AIC), and Area Under the Curve (AUC). Bootstrap resampling facilitated internal validation, while prediction accuracy was gauged through C-index, time-dependent ROC curve, and calibration curve. The model’s clinical relevance was ascertained using decision curve analysis (DCA). The study found 3-, 5-, and 10-year OS rates of 0.887, 0.841, and 0.753, respectively. XGBoost, BSR, and LASSO stood out in predictive efficacy, identifying seven key prognostic factors including age, pathological grade, T stage, N stage, radiation therapy, chemotherapy, and marital status. A subsequent nomogram revealed a C-index of 0.8499 (3-year), 0.8557 (5-year), and 0.8375 (10-year) and AUC values of 0.8670, 0.8879, and 0.8767, respectively. The model also highlighted the clinical significance of postoperative radiotherapy across varying risk levels. Our prognostic model, grounded in machine learning, surpasses traditional models in prediction and offer superior visualization of variable importance.