bluuebunny/crossref_metadata_2025_split huggingface dataset:
Semi-supervised attribute selection for partially labeled multiset-valued data
Authors: He Yuanzi , He Jiali , Liu Haotian , Li Zhaowen 
Published: November 2024

Abstract

In machine learning, when part of the data with labels needs to be pro- cessed, it is termed as a semi-supervised learning algorithm. Dataset with missing attribute values or labels is referred to as incomplete information sys- tem. Addressing incomplete information within a system poses a significant challenge, which can be effectively tackled through the application of rough set theory (R-theory). However, R-theory has its limits, it fails to consider the frequency of an attribute value and then can not well fit the distribu- tion of attribute values. If we consider partially labeled data and replace a missing attribute value with the multiset of all possible attribute values under the same attribute, then it leads to the emergence of partially labeled multiset-valued data. In semi-supervised learning algorithm, in order to save time and cost, a large number of redundant features need to be deleted. This paper studies semi-supervised attribute selection (ss-attribute selec- tion) for partially labeled multiset-valued data. Initially, a partially labeled multiset-valued decision information system (p-MSVDIS) is partitioned into two distinct systems: a labeled multiset-valued decision information system (l-MSVDIS) and an unlabeled multiset-valued decision information system (u-MSVDIS). Subsequently, using the indistinguishable relation, distinguish- able relation, and dependence function, two types of attribute subset impor- tance in a p-MSVDIS are defined. They are the weighted sum of l-MSVDIS and u-MSVDIS determined by the missing rate of labels and can be regarded as a uncertainty measurement (UM) of a p-MSVDIS. Next, an adaptive ss- attribute selection algorithm for a p-MSVDIS is introduced, leveraging the degrees of importance, allowing for automatic adaptation to diverse missing rates. Finally, 10 datasets are used for experiment and statistical analysis, the outcomes show the proposed algorithm has their advantage than some algorithms.
A Benchmark for Math Misconceptions: Bridging Gaps in Middle School Algebra with AI-Supported Instruction
Authors: Otero Nancy , Druga Stefania , Lan Andrew 
Published: November 2024

Abstract

This study introduces an evaluation benchmark for middle school algebra tobe used in artificial intelligence(AI) based educational platforms. The goal is tosupport the design of AI systems that can enhance learners’ conceptual under-standing of algebra by taking into account learners’ current level of algebracomprehension. The dataset comprises of 55 algebra misconceptions, commonerrors and 220 diagnostic examples identified in prior peer-reviewed studies. Weprovide an example application using GPT-4, observing a range of precisionand recall scores depending on the topic and experimental setup reaching 83.9%when including educators’ feedback and restricting it by topic. We found thattopics such as ratios and proportions prove as difficult for GTP-4 as they arefor students. We included a human assessment of GPT-4 results and feedbackfrom five middle school math educators on the clarity and occurrence of the mis-conceptions in the dataset and the potential use of AI in conjunction with thedataset. Most educators (80% or more) indicated that they encounter these mis-conceptions among their students, suggesting the dataset’s relevance to teachingmiddle school algebra. Despite varied familiarity with AI tools, four out of fiveeducators expressed interest in using the dataset with AI to diagnose students’misconceptions or train teachers. The results emphasize the importance of topic-constrained testing, the need for multimodal approaches, and the relevance ofhuman expertise in gaining practical insights when using AI for human learning.
Portability of Short Term Wind Power Forecasting
Authors: Deignan Cian , Sopeña Juan Gonzalez , Ghosh Bidisha , Pakrashi Vikram 
Published: November 2024

Abstract

Wind power forecasting (WPF) plays an increasingly important role in integrating wind power into electricity systems. The porta-bility of state-of-the-art WPF methods is assessed in this paper; the goal is to explore the influence of model hyperparameter configuration on forecasting performance. The overall aim is to expand understanding of WPF methods in order to improve the reliability and competitiveness of wind energy generation technologies.
The performance of two hybrid decomposition-based WPF methods are evaluated and compared, Variational Mode Decomposition & Feed Forward Neural Network (VMD-FFNN) and Ensemble Empirical Mode Decomposition & Feed Forward Neural Network (EEMD-FFNN). Supervisory Control and Data Acquisition (SCADA) data from wind farms in Ireland and the UK is utilised. The robustness and portability of the WPF methods when applied to different datasets is examined.
Both WPF methods produce robust and accurate forecasts across different datasets however, forecasts produced using low-resolution data are superior to high-resolution data forecasts. In the portability assessment, the forecasting performance is sensitive to two of the four model hyperparameters examined.
Introduction of a Novel Sunflower-Inspired Honeycomb Structure with Enhanced Energy Absorption Capacity under In-Plane Loading
Authors: Sarkhosh Reza 
Published: November 2024

Abstract

This study introduces a novel sunflower-inspired gradient structure where the size of hexagonal cells changes with a specific gradient in the radial direction. Subsequently, the crashworthiness and deformation performance of this structure were compared and analyzed with conventional honeycomb structures in both hollow and PU foam-filled states. In this research, specimens were first fabricated using additive manufacturing with PLA + material. After injecting polyurethane foam into the void spaces between cells, the specimens were subjected to quasi-static compressive loading in the in-plane direction at a 5 mm/min rate. The results showed that the sunflower-inspired honeycomb structure has significantly better crashworthiness and specific energy absorption properties than the conventional one. Based on these findings, it is concluded that the gradient design of cell sizes in the radial direction can lead to a 35% increase in specific energy absorption and a 20% increase in mean crushing force, along with a 143% improvement in crushing force efficiency, indicating enhanced performance in protective applications. Furthermore, it was demonstrated that the presence of foam can improve the performance of honeycomb structures. According to the results, foam-filled conventional honeycomb and sunflower-inspired honeycomb structures show increases of 43% and 41% in specific energy absorption, 82% and 89% in energy absorption and mean crushing force, and 23% and 10% in crushing force efficiency, respectively. The results indicate that the gradient design of cell sizes in the radial direction and the injection of PU foam into lattice structures can serve as a reference for designing energy absorbers with high-crashworthiness properties for various industries.
Inhibition of skin fibrosis via regulation of Th17/Treg imbalance in systemic sclerosis
Authors: Sekiguchi Akiko , Shimokawa Chikako , Kato Tamotsu , Uchiyama Akihiko , Yokoyama Yoko , Ogino Sachiko , Torii Ryoko , Hisaeda Hajime , Ohno Hiroshi , Motegi Sei-ichiro 
Published: November 2024

Abstract

Systemic sclerosis (SSc) is an idiopathic systemic connective tissue disorder characterized by fibrosis of the skin and internal organs, with growing interest in the imbalance between Th17 cells and regulatory T cells (Tregs) in the disease's pathogenesis. Heligmosomoides polygyrus (Hp), a natural intestinal parasite of mice, is known to induce Tregs in the host. We aimed to investigate the effects of Hp-induced Tregs on bleomycin-induced dermal fibrosis and clarify the role of the Th17/Treg balance in SSc fibrosis. Infection with Hp suppressed the development of bleomycin-induced dermal fibrosis and the infiltration of CD3+ T cells and CD68+ macrophages. Flow cytometric analysis revealed that Hp infection increased Tregs and inhibited the induction of bleomycin-induced Th17 cells. Treg depletion nullified these effects, suggesting that Hp-induced Tregs may prevent bleomycin-induced dermal fibrosis and inflammation. Analysis of the intestinal microbiota showed that bacteria positively correlated with Tregs exhibited a negative correlation with Th17 cells and dermal fibrosis in mice. SSc patients with severe fibrosis displayed a distinct microbiota profile. These results suggest that alterations in the intestinal microbiota may contribute to the Th17/Treg imbalance in SSc and its progression. Enhancing Tregs to regulate the Th17/Treg imbalance may present a promising strategy for suppressing fibrosis in SSc.
Study on the Overburden Movement Law in Strip Filling Mining of Upward Mining Faces
Authors: Huang Lingjin , Guan Weiming , Guan Yu , Zhao Hongchao , Zhang Zhiyi , Wen Yingyuan 
Published: November 2024

Abstract

Strip filling mining can effectively improve the recovery rate of coal resources and promote the healthy development of the coal industry. To explore the movement patterns of overburden in strip filling mining, this study takes a mine in Tuokexun as the research object and employs theoretical analysis, numerical simulation, and similar experiments to investigate the stability of the composite structure in upward mining faces and the stress distribution and fracture characteristics of the overburden at different stages of strip filling mining. The results indicate that when the width of the isolation coal pillar is set at 15 m and the filling body width is 150 m, a stable supporting structure can be formed. During the filling mining stage, the range of overburden damage presents an upward-tilting trapezoidal distribution, yet remains overall intact, significantly reducing the probability of impact hazards. In the collapsed mining stage, the initial fracture step distances of the immediate roof and basic roof are 40 m and 80 m, respectively, with a periodic fracture step distance of 20 m. The overburden displacement is relatively gentle, and the degree of stress concentration is low, which is beneficial for the stability and safety of underground mining.
Reorganization of orbitofrontal neuronal clusters induced by neuromodulation of dopamine D2 receptor reverses risk-prone behavior in male rats with inflammatory pain
Authors: Dourado Margarida , Cardoso-Cruz Helder , Monteiro Clara , Galhardo Vasco 
Published: November 2024

Abstract

Dopamine (DA) is believed to play a crucial role in maintaining the integrity of the rodent orbitofrontal cortex (OFC) networks during risk-based decision-making processes. Chronic pain conditions can lead to impaired DAergic signaling, which, in turn, may affect the motivational control of risk-based responses. Nevertheless, the neural mechanisms underlying this instability are poorly understood. In this study, we aimed to investigate whether this impairment is dependent on the activity of the DA D2 receptor (D2r). To address this hypothesis, we implanted bilateral matrices of multielectrodes into the OFC of male rats and recorded the neural activity while they performed a food-reinforced rodent gambling task (rGT). We evaluated behavioral performance and neural activity patterns before and after inducing a model of inflammatory pain – complete Freund’s adjuvant (CFA) model. Our findings revealed that rats treated with CFA exhibited an abnormal preference for the large/uncertain reward during rGT performance. This altered behavioral choice profile could be reversed by prior systemic administration of D2r ligands (0.05 mg/kg, quinpirole or raclopride), indicating a potential role of D2r in the decision-making process required for this task. The administration of these ligands at the specified dosages did not affect pain responses, but lead to a significant reorganization of OFC neuronal clusters that support goal-directed choice responses in the rGT. Finally, we found evidence that CFA-treated rats exhibit OFC functional changes, namely an upregulation of DA D1 receptor (D1r) and a downregulation of DA beta-hydroxylase (DH). These results demonstrate that the disruption of DAergic balance in the OFC networks is crucial for the development of high-risk decision profiles during painful conditions.
The use of laser-assisted cart positioning significantly reduces the docking time of multimodular robotic systems
Authors: Baunacke Martin , Hirtsiefer Christopher , Herout Roman , Mehralivand Sherif , Oelkers Susanne , Kaske Oliver , Franz Claudia , Thomas Christian 
Published: November 2024

Abstract

Background
The Hugo RAS system is characterized by its multimodular design, which leads to an increased docking effort. Exact data for docking time and the learning curve is missing. We describe for the first time the use of a laser-guided cart positioning to reduce the docking time.
Methods
In this prospective monocentric study, the docking time was evalutated for a consecutive series of pelvic surgeries with the Hugo RAS system. In a subgroup, a cross-line laser was adapted at the cart for positioning using fix points at the ceiling. The medical personnel were classified as “inexperienced” with ≤ 5 consecutive dockings and as “experienced” with > 5 consecutive dockings.
Results
From 10/2023 to 08/2024, 82 procedures were performed with the Hugo RAS. For the evaluation 75 procedures could be considered. The mean docking time was 7.6 ± 3.5 min. There was a reduction in docking time from 13.5 ± 3.7 min in the first 5 procedures to 4.4 ± 0.9 min in the last 5 procedures (p < 0.001). Docking with laser (n = 45) was faster than without laser (n = 30) (6.2 ± 2.5 vs. 9.8 ± 3.7 min, p < 0.001). Faster docking time was observed with inexperienced surgical nursing staff with laser than without laser (10.4 ± 3.7 vs. 5.4 ± 1.4 min; p < 0.001). With experienced nursing staff, the laser had no influence (6.6 ± 1.3 vs. 6.7 ± 2.9 min; p = 0.9). As a reference docking time for daVinci Xi procedures was 2.4 ± 1.7 min (n = 5).
Conclusion
Laser-guided cart positioning has a significant impact on docking time, especially for unexperienced medical personnel. Especially in the times of experienced staff shortage, laser-guided cart positioning can save operating time.
Preoperative malnutrition is a risk factor for prolonged postoperative ileus for patients undergoing gastrointestinal surgery
Authors: Zhu Zhenming , He Baoguo , He Juan , Ma Xuan , Gao Qun , Huang Yinghui , Chu Yuning , Ma Li 
Published: November 2024

Abstract

Background
Prolonged postoperative ileus (PPOI), a common complication after gastrointestinal (GI) surgery, seriously affects the postoperative recovery rate. However, there are few previous studies on the effect of preoperative nutritional status on the occurrence of PPOI in patients with GI cancer. Therefore, we aimed to evaluate the value of preoperative nutritional status for predicting the occurrence of PPOI in patients undergoing GI surgery.
Methods
We retrospectively analysed the clinical data of GI cancer patients who were admitted to our hospital between June 2021 and June 2023. The nutritional status of all patients was assessed using the Nutritional Risk Screening 2002 (NRS2002) and the Patient-Generated Subjective Global Assessment (PG-SGA). The independent risk factors for PPOI identified via univariate and multivariate logistic regression analyses were used to establish nomogram for the prediction of PPOI.
Results
The clinical data of 310 patients with GI cancer who underwent surgical resection were analysed. PG-SGA score, serum albumin concentration, haemoglobin concentration, operation time, tumour stage, and previous abdominal surgery are independent risk factors for PPOI. The nomogram developed to predict PPOI performed well (AUC = 0.835). The calibration curve showed high consistency between the observed and predicted results. The decision curve analysis (DCA) revealed that the nomogram was clinically useful. The predictive ability of this nomogram is better than that of albumin level and PG-SGA score.
Conclusion
The preoperative nutritional status of GI cancer patients has a significant effect on the occurrence of PPOI. The nomogram developed in this study accurately predicted PPOI in GI surgery patients.
Effects of novice developed TIG welding parameters on the microstructures and hardness of API 5L X65 High-Strength Low-Alloy (HSLA) Steel
Authors: Ahmad Arsalan , Iqbal Shanail , Bilal Sammama , Khan Umar 
Published: November 2024

Abstract

API 5L X65 is a commonly utilized pipeline material for gas transportation by Sui Northern Gas Pipelines (SNGPL) Private Limited, which employs submerged arc welding (SAW). Three samples, sourced from in-service seamless pipe with a 3x6 inches cross-section, were subjected to TIG welding experiments. Basic techniques, including gas, lathe, shaper, and hacksaw cuttings, were employed to prepare the samples. The microstructural analysis and hardness test results indicated that the lowest current was optimal, as per Ohm's law (V = IR). The low current in amperes (A) and high resistance resulted in a higher melting temperature, increasing molten puddle flowability and ease of control. Conversely, high current welding (120 A) led to the formation of porosity defects, as confirmed by radiographic tests, which also showed a lack of penetration (LOP). The hardness testing further supported HV (HRB) scale values for the low current welded samples, while the high current welded sample exhibited poor hardness due to low temperatures and insufficient weld zone fusion. In summary, the results from microstructural analysis, radiographic testing, and hardness testing, all indicate that TIG welding is a suitable procedure for repairing API 5L X65 steel due to the ease of controlling microstructures at low currents in the weldment.
EF-RT-DETR: A Efficient Focused Real-Time DETR Model for Pavement Diseases Detection
Authors: Han Tao , Hou Shuainan , Gao Can , Xu Shanyong , Pang Jiale , Gu Hai , Huang Yourui 
Published: November 2024

Abstract

Pavement disease classification and localisation is the key to intelligent road health monitoring. Aiming at the problems of complex road background, various shapes of disease objects and high hardware resource requirements. An efficient focusing real-time DETR pavement diseases detection model (EF-RT-DETR) is proposed.Firstly, based on RT-DETR, a DBBNCSPELAN backbone network is designed for capturing fine features. Secondly, the feature focusing module is used to replace the AIFI module to effectively reduce the noise impact and improve the local detail processing. Finally, the Efficient Multi-Feature Fusion module is used in the feature fusion stage to facilitate the interaction between local and global features. On RDD2022, the experimental results show that EF-RT-DETR improves 9.5% and 7.1% relative to RT-DETR on mAP$50 and mAP50:95, respectively, with a 34.7% reduction in computation and a 22.0% reduction in the number of parameters, which achieves real-time and accurate detection of pavement diseases.
Mathematics Subject Classification (2020) 68T07 · 68U10 · 68T05
A pyrene-derived fluorescent probe for the visual detection of protamine and trypsin activity
Authors: Xiong Longjun , Jiao Yutian , Liu Yu , Wei Gongli , Xu Baocai , Zhao Li 
Published: November 2024

Abstract

A pyrene-derived fluorescent probe (P4CG) was designed and synthesized for the purpose of detecting protamine and trypsin activity. The anionic probe self-assembled with protamine, driven by electrostatic and hydrophobic interactions, exhibiting a sensing behavior towards protamine in a fluorescence ratiometric manner. The assay demonstrated high sensitivity, with a limit of detection (LOD) of 13.8 ng/mL, and exhibited selectivity in the HEPES buffer solution. Moreover, the P4CG-protamine complex enables the monitoring of trypsin activity with satisfactory sensitivity and selectivity. The presence of the trypsin inhibitor resulted in the inhibition of the hydrolysis of protamine, which in turn led to a diminished fluorescence recovery. Consequently, this assay can be employed for the screening of trypsin inhibitors.
Finite element method and experimental research on the temperature field of GH4169 in robotic belt grinding
Authors: Zu Xinpeng , Wang Yifei , Gong Yadong , Liu Mingjun , Li Zeming , Sun Yao , Zhao Jibin 
Published: November 2024

Abstract

Robotic belt grinding has become an important method for precision machining because of its flexibility, high efficiency, and high machining accuracy. However, in the grinding process, heat accumulates and creates thermal stresses in the cutting zone, which leads to an increase in workpiece temperature. In this paper, the whole robotic belt grinding process is discretized into a macroscopic tool-workpiece contact process finite element model, a microscopic mechanical-thermal coupling cutting zone temperature field model, and a macroscopic workpiece temperature field model. The normal load curve of single abrasive particle accumulation and the temperature distribution curve of the cutting zone serves as the interface connecting these three different scale models. The proposed FEM model is verified by the robotic belt grinding experiment. The simulation results are in good agreement with the experimental results, with an average prediction error of 3.16%. The research can lay a theoretical foundation for the prediction of grinding temperature distribution.
Effect of post-harvest processing on nutritional and antioxidant activities of Ulva sp. originating from Bangladesh
Authors: Mojumder Suman , Barua Oishee , Sharma Rahul , Akhter Yeasmin , Sikdar Dwaipayan , Roy Sajal , Moniruzzaman Mohammad , Roy Uttam Kumer 
Published: November 2024

Abstract

To optimize the utility of seaweeds, post-harvest processing is typically essential, serving to prevent decay, extend shelf life, and facilitate the extraction of specific chemical components. In this study, the presence of a variety of nutritionally important compounds in Ulva sp. (grown locally in Bangladesh) was investigated following different treatments: washing with fresh water (fresh), followed by air drying and oven drying. The analysis encompassed the determination of proximate composition (carbohydrates, proteins, lipids, ash, and moisture), elements (C, H, N, S and P), minerals (K, Ca, Mg and Fe), potential bioactive compounds (phenolics, flavonoids, chlorophyll and carotenoids), and in vitro antioxidant activities. The findings indicated that fresh samples exhibited higher levels of nutrients, bioactive compounds, and antioxidant activities. The highest levels of primary metabolites [carbohydrates (50.03 ± 1.74%, DW), protein (11.02 ± 2.35%, DW), lipid (4.16 ± 0.07%,, DW)], pigments [chlorophyll (0.602 ± 0.012%, DW), carotenoid (0.057 ± 0.005%, DW)], moisture (90.28 ± 0.0%) and antioxidant activities [total antioxidant capacity (10.2 ± 0.20 mgAAE/g, DW), reducing power (0.26 ± 0.02 mgAAE/g, DW), ferric reducing antioxidant power (29.61 ± 2.02 mmol Fe2+/g, DW)] were observed in fresh samples. Air-dried and oven-dried samples showed no significant differences in concentrations of these phytochemicals and antioxidant activities except that phenolic and flavonoid contents. Ulva sp. also showed having a notable amount of certain elements [C (27.02 ± 2.01%), H (5.56 ± 0.38%), N (3.48 ± 0.19%), S (5.95 ± 0.32%) and P (0.91 ± 0.02%)] and minerals [K (0.67 ± 0.01%), Ca (0.94 ± 0.13%), Mg (0.59 ± 0.01%) and Fe (0.21 ± 0.01%)]. In conclusion, fresh Ulva sp. could be more preferable to retain nutritional qualities compared to an air-dried or oven-dried processed sample.