bluuebunny/crossref_metadata_2025_split huggingface dataset:
Riskwatch: A Model for Improved Preoperative Risk Assessment of Anesthesia in Medical Science Using Machine Learning
Authors: Kaur Ekaspreet , Kaur Simrata , Singh Harjot , Kaur Bisman , Pannu HS 
Published: August 2024

Abstract

Anesthesia is a medical breakthrough with certain inherent risk factors. This paper presents a system for preoperative assessment of risks associated with anesthesia. To ensure patient safety, managing these risks is a top priority for anesthesiologists. An ever-increasing ratio of the number of surgeries to the number of doctors can inevitably lead to errors in risk judgment. This paper classifies patient data into four risk categories: due risk, low risk, moderate risk, and high risk based on supervised machine learning (ML) models. The data preprocessing technique of binning is applied to segregate the data. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to compare various supervised ML methods such as K nearest neighbors (KNN), logistic regression (LR), support vector machine (SVM), gradient boosting (GB), decision tree (DT), random forest (RF), and an ensemble model for multi-class classification. Explainable AI techniques like SHapley Additive exPlanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) offered valuable insights into the model’s decision-making process. The study compares ML models trained separately on raw and binned datasets, showing significant improvements in predictive accuracy with binning. The ensemble model achieved 95% accuracy in classifying the test patients using binned data. Our research introduces a ML-based system that can reduce preoperative risk and help anesthesiologists by providing real-time information, thereby enhancing patient safety, and reducing the likelihood of errors in preoperative risk judgment.
Inhibition of type 3 iodothyronine deiodinase enhances differentiation of human induced pluripotent stem cells to β cells
Authors: Maruoka Azusa , Kimura Azuma , Hattori Fumiyuki , Hitomi Hirofumi , Osafune Kenji , Shiojima Ichiro , Toyoda Nagaoki 
Published: August 2024

Abstract

Intracellular triiodothyronine (T3) level is up-regulated by type 2 iodothyronine deiodinase (Dio2), which converts thyroxine (T4) to T3, or is down-regulated by type 3 iodothyronine deiodinase (Dio3), which converts T3 to diiodothyronine. β cells derived from human induced pluripotent stem cells (hiPSCs) were examined to investigate the potential roles of deiodinases during differentiation of human pancreatic β cells. hiPSCs were differentiated stepwise over 29 days. The T3 level in the differentiated cells was determined by the T3 supplied to the medium, and the Dio3 in the cells as the differentiation medium contained T3 but not T4. The Dio3 expression significantly changed during the differentiation. Iopanoic acid (IOP), an inhibitor of Dio3 activity, was used to investigate the involvement of Dio3 during differentiation. The proportion of β cells that expressed both C-peptide and NKX6 homeobox 1 that differentiated in the presence of IOP (+IOP) on day (D) 29 (D-29) was significantly higher than that expressed in the absence of IOP (−IOP). The insulin content of differentiated+IOP cells on D-29 was significantly higher than that differentiated−IOP cells. These results suggest that Dio3 inhibition by IOP from D-0 to D-29 enhances the differentiation of hiPSCs to β cells.
Electroantennogram and olfactory behavioral responses of adult Nematus hequensis Xiao to volatiles from Salix alba leaves
Authors: Song Zhenhao , Chen Yiqu , Dong Xiao , Sun Zhaoxu , Guo Xinnan , Yu Kun , Tang Xiaoqin , Zang Jiancheng 
Published: August 2024

Abstract

To investigate how leaf volatiles from Salix alba affect the orientation of Nematus hequensis Xiao adults towards host plant in the China, and to contribute to the development of plant-based attractants for N. hequensis, solid-phase microextraction (SPME) coupled with gas chromatograph-mass spectrometer (GC-MS) was employed. This method was used to extract, identify, and screen leaf volatiles of S.alba aged 10–15 years during the peak eclosion period of N. hequensis. Electroantennogram (EAG) and Y-shaped olfactometry assays were utilized to identify volatiles with relative content > 1% and determine the optimal concentration for attracting 1-day-old unmated female and male healthy adults.As a result,The findings revealed that 15 types of volatiles with relative content exceeding 1% included aldehydes, benzenes, esters, olefins, ethers, alcohols, and alkanes. Among these, three aldehydes ((E)-2-hexenal2, benzaldehyde, and benzaldehyde,2-hydroxy) elicited the strongest EAG response in both adults at a concentration of 100ug/µL, with (E)-2-hexenal2 exhibiting a greater effect than benzaldehyde,2-hydroxy, which in turn was more effective than benzaldehyde. At this concentration, the attractive effects of (E)-2-hexenal2 and benzaldehyde on both adults were also significant. Furthermore, cis-3-hexenyl isovalerate demonstrated a significant repellent effect on female adults at 10µg/µL. Notably, Butanoic acid,3-hexenyl ester, (Z),cis-3-hexenyl isovalerate, and benzaldehyde,2-hydroxy at concentrations of 1µg/µL, 10µg/µL, and 100µg/µL exhibited significant repellent effects on male adults.Unmated adults of N. hequensis exhibited varying degrees of EAG response to 15 volatiles. Remarkably, (E)-2-hexenal2 and benzaldehyde elicited significant EAG responses and attracted behavioral responses both male and female adult Nematus hequensis Xiao at 100 µg/µL.
An improved squirrel search algorithm for a coefficient inversion problem of a singularly perturbed reaction-diffusion equation
Authors: Mai Xiongfa , Bian Wenhe , Liu Li-Bin 
Published: August 2024

Abstract

A novel numerical algorithm is proposed for solving a coefficient inverse problem of a singularly perturbed reaction-diffusion equation with the final time observation data. Firstly, for the discretization scheme of the direct problem, the barycentric form rational spectral approach based on the sinh transformation is used to discretize the space derivative and the Crank-Nicolson finite difference scheme is utilized to approximate the time derivative. For the construction of inverse problem, we design a new fitness function about the reaction coefficient. Then integrating optimal neighborhood search strategy, random opposition based learning strategy and adaptive predator presence probability strategy, an improved squirrel search algorithm named NOISSA is proposed. Finally, 9 benchmark test functions are used to validate the performance of our proposed NOISSA. Moreover, numerical experiments are carried out to illustrate the advantage of our new algorithm in solving the coefficient inverse problems of singularly perturbed reaction-diffusion problems.
Quadcopter-Centric Crack Detection: YAML Algorithm Integration
Authors: Ganduri Krishna Vamshi , Pathri Bhargav Prajwal , Reddy Ruthwik , Thirunathi Murali Krishna , Alimilla AthriNandan , Talasila Siddhartha 
Published: August 2024

Abstract

The primary objective of this project is to design and create a wall crack detecting system that uses the Yet Another Markup Language (YOLO) v81 model and an aerial drone. Wall fissures present serious maintenance and safety issues for power plants, buildings, and infrastructure. The YOLOv3 model, which is renowned for its real-time object detection abilities, is a major component of the project. By incorporating this model into an aerial drone platform, the system's mobility and accessibility are increased, making it possible for it to inspect areas of buildings and structures that are difficult to reach. The general perspective offered by the drone's aerial perspective makes it possible to identify fractures early on that could otherwise go undetected. The training process is guided by the YAML configuration, which includes important parameters for the best model performance, like epochs, batch size, picture size (imgsz), and pretraining. The computing core for onboard deployment is one example of how the system is designed for integration. Important factors to consider are labour assignments, device management, and project-specific information specified in the YAML file. The objective of this project is to address real-time processing and remote monitoring challenges in infrastructure inspection situations and to develop a scalable and reliable system for automated wall crack recognition.
PRIMO-PenEasy Monte Carlo simulation compared with dosimetric results for 6MV photon beams in small fields
Authors: Díaz Nataly , Abaunza Amaia Villa , Muñoz Jorge , Udias Jose Manuel , Ibañez Paula 
Published: August 2024

Abstract

Dosimetric validation of clinically prescribed plans for small fields requires adapted instrumentation that ensures high accuracy and spatial resolution. The objective of this study is to propose a solution by employing PRIMO-penEasy MC simulation for scenarios where obtaining direct measurements is impractical, poses challenges, or leads to inconsistencies in measurements from various detectors when assessing treatments involving small fields. This study presents the application of three distinct tools: the Semiflex ionization chamber PTW, model 31010, placed in an acrylic tank filled with water; EBT3 radiochromic films positioned between layers of a solid water phantom; and PRIMO-PenEasy Monte Carlo (MC) simulations for small photon beams. The experimental dosimetric outcomes were acquired at San Ignacio University Hospital in Bogota, Colombia, involving two small fields and one conventional field. These fields were generated using an Axesse-type linear accelerator.
Radiochromic film show better agreement with MC simulation compared to the semiflex ionization chamber data, due to the fact that measurements with the 1 ionization chamber involve averaging the dose across the detection volume. Additionally, variations in off-axis ratios are observed in both crossplane and inplane directions. This difference is more evident in the case of two small fields compared to a conventional field. This observation can be attributed to the specific opening direction of the multi-blade collimation system and XY-jaws.
Our study demonstrated that PRIMO-PenEasy MC simulation provides precise dose distributions and can be used as an alternative computational method to obtain the characteristics of small photon beams from an Axesse-type linear accelerator. The simulation results offer a means to reconcile disparities observed in values measured with different detectors. The values computed by PRIMO-PenEasy Monte Carlo (MC) can serve as a reliable indicator of accuracy and, consequently, be employed for dosimetric validation of prescribed clinical plans.
Preparation of nickel sulfide electrode material by starch assisted hydrothermal process and its electrochemical properties
Authors: Wang Yili , Yang Pan , Wei Kang , Sheng Zizhi , Huang Ruonan , Huang Wendeng , Deng Jianping 
Published: August 2024

Abstract

As a novel form of energy storage apparatus, the supercapacitor has garnered substantial attention in academic research due to its superior energy density compared to dielectric capacitors, as well as its enhanced power density and cycle life in comparison to batteries. The electrode material, which a critical component of supercapacitors, plays a significant role in shaping their overall performance. In this work, nanometer nickel sulfide electrode materials with uniform particles were prepared by soluble starch assisted hydrothermal method and assembled into supercapacitors. Through electrochemical testing, the specific capacity of the prepared NiS electrode can reach 1979.2F·g-1 at the current density of 1A·g-1, and the capacity retention rate of the device is 52.8% after 10000 constant current charge and discharge at the current density of 3A·g-1, indicating that the device has good cycle stability. This study provides a practical basis for the development of high efficiency and low cost energy conversion with storage technology.
Meta-HGNet: Meta-Heterogeneous Generalized Network for Visible Infrared Person Re-identification
Authors: Jiale Zhang , Baohua Zhang , Dongyang Wu , Yu Gu , Jianjun Li , Jingyu Wang 
Published: August 2024

Abstract

Visible infrared person re-identification plays an important role in heterogeneous modality image person identity matching, however, significant modality differences increase cross modality image matching errors. The existing cross-modality re-identification person re-identification methods only utilize modality homogeneous shared features, ignoring specific representations of modality heterogeneity, which prevents fast fitting convergence and reduces cross-modality re-identification accuracy. To address the above problems, this paper proposes a novel Meta-heterogeneous generalized network (Meta-HGNet), which introduces a meta-learning strategy to simulate the training and testing process in order to improve the heterogeneous generalization ability of the network. The Meta-HGNet consists of two modules: the Meta-Optimization Feature Module (MOF) and the Meta-Feature Coupling module (MFC). To enhance the discriminative properties of homogeneous and heterogeneous modality features, the MOF is used to extract homogeneous shared features, separate heterogeneous specific representations and learn their contextual relationships. Then, the MFC reduces the discrepancy between meta-sample features and shared discriminative features by extracting meta-sample features, fusing them with modality shared discriminative features, and the feature fusion weights are adjusted by using the dual constraints of meta-sample testing loss (MTloss) and meta-sample coupling loss (MSCloss). As a result, the proposed model adaptively adjusts the weighting parameters without introducing additional network parameters for fast fitting convergence, which further improves the generalization of visible-infrared person re-identification, and the effectiveness and superiority of the proposed method is verified through experiments on three cross-modality re-identification datasets.
Investigating Elbow Dislocation and Instability: A 3D Finite Element Analysis Approach
Authors: Kork Samer Al , Youssef Karim , Said Sherif , ElSayed Fahmi , Karar Abdullah , Al-Barakeh Zaher , Abraham Edward , Amirouche Farid , Beyrouthy Taha 
Published: August 2024

Abstract

Elbow dislocation and instability present significant clinical challenges, necessitating a thorough understanding of the underlyingbio-mechanical mechanisms. In this study, a quasi-static three-dimensional finite element model of the human elbow joint isdeveloped to investigate stress distribution and stages of dislocation in the human elbow under various loading conditions. Themodel simulates the elbow joint in different degrees of flexion (30°, 45°, 60°, and 90°) and forearm positions (pronation andsupination), providing detailed insights into the progression of dislocation. Significant findings include the identification of highstress concentrations on the humerus at 90° flexion and on the radial and coronoid processes at 30°, 45°, and 60° flexion.Three reproducible stages of dislocation were observed, particularly in flexed positions with forearm pronation or supination.These stages align with experimental observations1 and highlight the initial occurrence of bony failures, such as radial headand ulnar coronoid fractures, preceding soft tissue tears. Clinically, the study underscores that early-stage low-impact posteriorelbow dislocations retain enough stability to be managed with closed reduction and early mobilization. However, as dislocationsprogress, significant damage to the medial and lateral collateral ligaments is expected, necessitating more invasive treatments.This research provides valuable bio-mechanical insights into elbow dislocation, aiding in the development of improved treatmentstrategies and enhancing patient outcomes through precise and timely clinical interventions. The validated FEM serves as apowerful tool for pre-surgical planning offering a comprehensive understanding of elbow joint mechanics
Persistent macroeconomic damages raise social cost of carbon
Authors: Wenz Leonie , Kotz Maximilian , Callahan Christopher , Stechemesser Annika 
Published: August 2024

Abstract

The social cost of carbon (SCC) is a central tool for climate policy-making. Estimates of the SCC depend crucially on their representation of climate damages. Recent developments in climate econometrics have increased the level of spatial detail, constrained the persistence, and widened the scope of climatic drivers of impacts on macroeconomic growth, but their implications for the SCC remain unexplored. Here we integrate a reduced form representation of such empirical damages in the state-of-the-art Integrated Assessment Model GIVE. At a near-term discount rate of 2%, damages imply a SCC of $2520 with a likely range of $1330-4250 based on uncertainty in the econometric, climate and integrated assessment models, an order of magnitude greater than recent sector-specific calibrations. Accounting for the variability of temperature and the variability and extremes of precipitation increases estimates of the SCC by over 80% compared to damages from average temperature alone. Constraining the persistence of impacts on growth alters the SCC by orders of magnitude, increasing over forty-fold compared to empirical specifications which assume no persistence and decreasing four-fold compared to those which assume infinite persistence. Exploring the potential of adaptation to reduce damages, we find that halving economic vulnerability to impacts within the next 23 years would be necessary to bring the SCC below 1000$.
Filming nanodroplet running and jetting mediated by nanoscale solid-gas and solid-liquid interface
Authors: Chen Bin , Xu Linfeng , Cao Zetan , Liu Zhiwen , Zheng Cheng , Peng Simin , Lu Yong 
Published: August 2024

Abstract

Nanodroplets at multiphase interfaces are ubiquitous in nature with implications ranging from fundamental interfacial science to industrial applications including catalytic, environmental, biological and medical processes. Direct observation of the full dynamic evolutions of liquid metal nanodroplets at nanoscale multiphase interfaces offers indispensable insights, however, remains challenging and unclear at the moment. Here, we have fabricated massive ready-to-use gas and liquid cells containing HgS nanocrystals through electrospinning and achieved the statistical investigations of full picture of Hg nanodroplets evolving at solid-gas and solid-liquid interfaces by in-situ transmission electron microscopy. Upon the electron-beam excitation of HgS in the gas cells, the voids nucleated, grew and then coalesced into the crack-like feature preferentially along the < 001 > direction through the bridges. Meanwhile, the Hg nanodroplets formed, moved rapidly on the ratchet surface with the velocity of several tens of nm/s and were finally evolved into bigger ones through the nanobridges with the relatively large gap of ~ 6 nm. Distinctly and surprisingly, mediated by the solid-liquid interface at nanoscale, the liquid Hg with the ink-like feature jetted in the liquid cells. Such ink-jetting behavior would occur multiple times with the intervals from several to several tens of seconds, which was modulated through the competition between the reductive electrons and the oxidative species derived from the radiolysis of liquid by the electron-beam. In-depth understanding of distinct nanodroplets dynamics at nanoscale solid-gas and solid-liquid interfaces offers a feasible approach of designing liquid metal-based nanocomplexes with regulatory interfacial, morphological and rheological functionalities.
Women at Work: Unveiling the Impact of FLFPR and Adolescent Fertility on India's Economic Landscape
Authors: Sharma P.K. , Chandauriya Mahima 
Published: August 2024

Abstract

This paper explores the relationship between female labour force participation (FLFPR), adolescent fertility rates, and economic development in India from 2012 to 2022. Drawing on regression analysis and secondary data sources, including the World Bank and the International Labour Organisation, the study investigates the impact of FLFPR, normalised weight (FGERSE), and adolescent fertility rates on GDP per capita. Results indicate a strong positive correlation between FLFPR and GDP per capita, highlighting the significant role of women in driving economic growth. Conversely, adolescent fertility rates exhibit a negative correlation with GDP per capita, emphasising the need for policies to address reproductive health outcomes. The findings underscore the importance of promoting gender inclusivity education to foster sustainable economic development and gender equality in India.
Green solid-state synthesis of Cu4O3/biochar composites with high antimicrobial activity
Authors: Sun Ke , Yang Wenyi , Shen Yiheng , Wang Zihan , Wang Yindian , Chen Hongxia , Liu Yi 
Published: August 2024

Abstract

Infectious diseases caused by pathogenic microorganisms have inflicted significant calamities upon human society. The Cu4O3/biochar composites with high efficacy of antimicrobial properties are developed for the first time via a green solid synthesis strategy of ball milling and sintering processes in this work. The mechanistic investigation revealed that the biochar, e.g. corn stover, plays multiple physiochemical roles as a support carrier, dispersant, and reducing agent, regulating elegantly the stoichiometric ratio of Cu2O and CuO. The potent antimicrobial activities of the Cu4O3/biochar composite were confirmed against E. coli, S. aureus, and methicillin-resistant Staphylococcus aureus MRSA through minimum inhibitory concentration (MIC) testing, exhibiting extremely low MIC values against the Gram-positive strains S. aureus and MRSA. Furthermore, the antibacterial mechanisms of the Cu4O3/biochar composite were studied through the experiments and quantum mechanical computations, showing the enhanced effects between the successive release of Cu(I)/Cu(II) ions and the generation of reactive oxygen species. This work reports the first solid-state symproportionation reactions of CuOx to prepare high-purity Cu4O3, stabilized by biochar with the advantages of simplicity, low cost, brevity, mild reaction conditions, and eco-friendliness. The Cu4O3/biochar composite can be applied as additives in anti-bacterial materials to protect against harmful microbial infections including superbugs.