bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tailoring Asymmetric RuCu Dual-Atom Electrocatalyst toward Ammonia Synthesis from Nitrate
Authors: Chen Wenxing , Liu Kaiyuan , Sun Zhiyi , Liu Xudong , Zhang Xiao , Zhou Boran , Chen Zhengbo , Zhou Qiang , Zhang Fang , Wang Yong , Gao Xin , Chen Pengwan 
Published: September 2024

Abstract

Atomically dispersed dual-atom catalysts (DACs) with asymmetric coordination are pivotal for enhancing economic efficiency and sustainable development in the electrochemical nitrate reduction reaction (NO3RR) to produce ammonia. However, rational design and rapid synthesis of DACs remain challenging. Here, we demonstrate the pulsed discharge method, which generates microsecond current pulses to inject substantial energy instantaneously into ruthenium (Ru) and copper (Cu) metal salt precursors supported by nitrogen-doped graphene aerogels (NGA). This process results in the atomically dispersed Ru and Cu dual atoms anchoring onto nanopore defects of NGA (RuCu DAs/NGA) through explosive decomposition of the metal salt nanocrystals. X-ray absorption spectroscopy analysis suggests an asymmetric RuN2-CuN3 coordination structure on NGA. The RuCu DAs/NGA catalyst exhibits outstanding electrochemical performance in NO3RR, achieving a Faraday efficiency of 97.8% and an ammonia yield rate of 3.07 mg h− 1 cm− 2 at -0.4 V vs. RHE. In situ studies monitor the evolution of RuCu active sites and reaction intermediates during the NO3RR process in real time. Density functional theory calculations reveal that the Ru-Cu sites in the asymmetric RuN2CuN3/C structure create a synergistic effect, optimizing intermediate adsorption and lowering the energy barrier of key elementary reactions. This pulsed discharge method is simple, ultra-fast, and versatile (e.g., applicable to PtCu, AgCu, and PdCu DAs on NGA), offering a general-purpose strategy for the precise preparation of atomically dispersed dual-atom catalysts, which are traditionally challenging to synthesize.
Disuse atrophy of articular cartilage can be restored by mechanical reloading in mice
Authors: Nomura Masato , Moriyama Hideki , Wakimoto Yoshio , Miura Yasushi 
Published: September 2024

Abstract

Background
Moderate mechanical stress generated by normal joint loading and movements helps maintain the health of articular cartilage. Despite growing interest in the pathogenesis of cartilage degeneration caused by reduced mechanical stress, its reversibility by mechanical reloading is less understood. This study aimed to investigate the response of articular cartilage exposed to mechanical reloading after unloading in vivo and in vitro.
Methods and results
Disuse atrophy was induced in the knee joint cartilage of adult mice through hindlimb unloading by tail suspension. For in vivo experiments, mice were subjected to reloading with or without daily exercise intervention or surgical destabilization of the knee joint. Microcomputed tomography and histomorphometric analyses were performed on the harvested knee joints. Matrix loss and thinning of articular cartilage due to unloading were fully or partially restored by reloading, and exercise intervention enhanced the restoration. Subchondral bone density decreased by unloading and increased to above-normal levels by reloading. The severity of cartilage damage caused by joint instability was not different even with prior non-weight bearing. For in vitro experiments, articular chondrocytes isolated from the healthy or unloaded joints of the mice were embedded in agarose gel. After dynamic compression loading, the expression levels of anabolic (Sox9, Col2a1, and Acan) and catabolic (Mmp13 and Adamts5) factors of cartilage were analyzed. In chondrocytes isolated from the unloaded joints, similar to those from healthy joints, dynamic compression increased the expression of anabolic factors but suppressed the expression of catabolic factors.
Conclusion
The results of this study indicate that the morphological changes in articular chondrocytes exposed to mechanical unloading may be restored by shifting extracellular matrix metabolism to anabolism in response to mechanical reloading.
Combination of Interscalen Brachial Plexus Block and Superficial Cervical Plexus Block in The Patient to be Operated to Clavicular Excision of Chordoma: A Case Report
Authors: polat Ezgi , kocoglu hasan , solcan seyit ibrahim 
Published: September 2024

Abstract

Background: Clavicular surgery can be performed under general or regional anesthesia with peripheral nerve blocks.
Case: A 29-year-old man with cerebrovascular disease, interstitial lung disease, tumour in lung, right vocal cord paralysis, cervical, thoracic and lumbar stabilization was scheduled for regional anesthesia to undergo metastatic chordoma at clavicle. Considering the risks, the patient who will be operated on for tumour excision in the right clavicle, who is predicted to have difficult intubation due to limitation of extension secondary to a previous posterior cervical instrumentation, is treated with interscalene brachial plexus block and superficial cervical plexus block combination to avoid multiple drug use and complications that may arise during intubation.
Conclusions: Regional anesthesia seems like a reasonable alternative to general anesthesia and may be a good option for perioperative analgesia management in clavicle surgery.
Knowledge, attitudes, and practices of clerkship supervisors regarding the biopsychosocial approach at the University of Botswana's Faculty of Medicine
Authors: Tshitenge Stephane , Molebatsi Katlego P. , Moeng Lesedi , Mothule Reneilwe S. , Moeti Bofelo , Manko Ronald O.B. , Moses Mompoloki M. 
Published: September 2024

Abstract

Background
The biopsychosocial and spiritual model (BPSM), commonly known as the body-mind-unity, does not contradict the biological model; it aims to expand health professionals understanding by integrating psychological and eco-social elements as influential factors in health and disease. We investigated the knowledge, attitude, and practice (KAP) of University of Botswana faculty of medicine (UB-FOM) clerkship supervisors on BPSM.
Methods
This was a quantitative cross-sectional survey. We distributed online (using Microsoft Forms) and self-administered paper-based questionnaires to clerkship departments. We gathered KAP information using a five-point Likert scale and an open-ended question section that asked respondents to elaborate on the factors they believed could limit their application of the BPSM.
Results
Forty-eight clerkship supervisors completed the questionnaire. Most participants (n = 38, 79.2%) reported that they received training on the BPSM throughout their undergraduate or postgraduate education. UB-FOM clerkship supervisors appreciated the importance of considering all four dimensions of health in any healthcare activity (mean score = 4.14 > weighted mean score of 4.04). They also noted the intricate nature of the interaction between psychological and physical health elements (mean score = 4.18 > weighted mean score of 4.04). However, they did not feel comfortable instructing medical students on the model during clinical rotation (mean score = 3.98 < weighted mean score = 4.04), and they expressed scepticism over the ability of psychosocial processes and treatments to alter medical illnesses. Additionally, they did not feel the importance of incorporating the spiritual evaluation into medical practice (mean score = 3.82 < weighted mean score of 4.04).
Obstacles to the implementation of a BPSM included time constraints during consultations and burden, a negative "attitude" towards the BPSM, a lack of updated training, and a defined guideline for the BSPM.
Conclusion
UB-FOM Clerkship supervisors appreciated the importance of considering all four dimensions of health in any healthcare activity. However, they did not feel comfortable instructing medical students on the model during clinical rotation, and they expressed scepticism over the ability of psychosocial processes and treatments to alter medical illnesses. We recommend implementation research that specifically targets the beliefs and attitudes of clerkship supervisors.
Enhancing Infiltration Rate Predictions with Hybrid Machine Learning and Empirical Models: Addressing Challenges in Southern India
Authors: Ramaswamy Mooganayakanakote Veeranna , Kumaraswamy Yashas Kumar Hanumapura , Reddy Varshini Jaganatha , Nyamathi Shivakumar J 
Published: September 2024

Abstract

Despite the success of machine learning (ML) in many disciplines, its application in hydrology, especially in water-scarce regions, faces challenges due to the lack of interpretability and physical consistency. This study addresses these challenges by integrating established empirical hydrological models with ML techniques to predict infiltration rates in water-scarce regions of southern India. Data from 199 observations across 11 sites, including soil characteristics and infiltration measurements, were used to parameterize traditional models like Philip's, Horton's, and Kostiakov's, which were then combined with Artificial Neural Networks (ANN) and the MissForest (MF) algorithm to form hybrid models. The results demonstrate that hybrid models, particularly those based on Philip's model, significantly improve prediction accuracy (R²: 0.76–0.92, RMSE: 0.08–0.2 cm/min, and LCE: 0.11–0.71 with more predictors) across all target sites while retaining interpretability. This approach leverages the strengths of both empirical models and machine learning, addressing the limitations of each. The study highlights that while empirical models are data-driven and may introduce uncertainties, combining them with ML techniques can enhance predictive power and provide a more robust understanding of infiltration dynamics. This is particularly valuable in regions where direct measurement is challenging. The hybrid models facilitate accurate predictions using minimal data from readily accessible locations, offering a practical solution for effective water resource management and soil conservation in semi-arid and data-scarce regions. By blending empirical knowledge with machine learning algorithms, this approach not only improves accuracy but also enhances the physical meaningfulness of hydrological models, providing a balanced and innovative solution to hydrological modeling challenges.
Automated Amniotic Fluid Volume Assessment Using YOLOv8 for Enhanced Fetal Health Diagnosis in Ultrasound Imaging
Authors: Rafi Muhammad , Frnda Jaroslav , Khan Daniyal Ahmed , Irfan Minhal , Siddiqui Abdul Rafay 
Published: September 2024

Abstract

Amniotic Fluid (AF) is crucial for fetal development, and changes in its volume can signal maternal and fetal health issues. This study focuses on the challenges of accurately assessing Amniotic Fluid Volume (AFV) due to the dependence on the skill of the sonographer. To improve this process, we used segmentation techniques to clearly define AF compartments. We applied the YOLOv8 model to segment AF in ultrasound (US) images. After segmentation, we used contour detection technique to estimate AFV using the Single Deepest Pocket (SDP) method, classifying the results into three clinical categories: adequate, polyhydramnios, and oligohydramnios. We also used the Phi3 Large Language Model(LLM) to process the diagnoses and SDP values, generating associated risks through Prompt Engineering and integration with Langchain and Ollama. The dataset included 3335 US images, ensuring thorough analysis and validation. The study showed strong performance in AF segmentation, achieving a mean Average Precision at an IoU threshold of 0.50 (mAP50) of 0.84. These results demonstrate the model's effectiveness in accurately detecting amniotic fluid. This research advances automated AF analysis, providing valuable support for sonographers in assessing fetal health.
\newline\newline\noindent\textbf{Keywords:} amniotic fluid volume, single deepest pocket, obstetric ultrasound, computer vision, natural language processing, deep learning
π-π Interactions-Directed Asymmetric Hydrogenation of Sterically Unbiased Aromatic Ketones
Authors: Zhang Xumu , Song Jingyuan , Xiao Renwei , He Hui , Wang Li , Huang Fanping , Zhao Menglong , Liu Donghuang , Ni Shao-Fei , Chen Gen-Qiang 
Published: September 2024

Abstract

Transition metal-catalyzed asymmetric hydrogenation of ketones has been well established; however, the asymmetric hydrogenation of sterically unbiased ketones remains a formidable challenge, due to the difficulty in control of enantioselectivity. Herein, we have developed a highly practical and efficient protocol for the asymmetric hydrogenation of sterically unbiased aromatic ketones, and a series of chiral cyclic diaryl alcohols, including the key intermediate of Baloxavir (super Tamiflu), with up to 99% yield and up to 99% ee. Mechanistic investigations indicate that iridium precursor [Ir(COD)Cl]2 could undergo an intramolecular oxidative C-H activation with the oxa-spirocyclic ligand to produce a highly rigid butterfly-shaped complex which is responsible for achieving high enantioselectivity, and X-ray diffraction analysis indicate that the ligand behaves as a tetradentate PNNC ligand, which could inhibit the toxicity of the sulfur-containing substrate to the catalyst. Preliminary DFT calculations and NCI analysis demonstrated that π-π interactions between the substrate and catalyst played a key role in the control of enantioselectivity. Furthermore, the synthetic potential of our catalytic system was verified by the gram-scale asymmetric hydrogenation, and Baloxavir intermediate was obtained with retention of enantioselectivity.
Diurnal Characteristics and Sources Apportionment of Atmospheric PM2.5 in a Medium-sized City in East China
Authors: Meng Lingshuo , Du Yang , Che Hanxiong , Zhou Jiawei , Bao Zhier , Liu Yiliang , Han Yan , Qi Xin , Long Xin , Chen Yang 
Published: September 2024

Abstract

To investigate the characteristics and sources of atmospheric fine particulate matter (PM2.5) in the medium-sized cities in East China, continuous observation of PM2.5 was conducted in Huai'an City from April 18th to May 11st, 2021. During the observation process, the average mass concentration of PM2.5 was 58.5 ± 26.9 µg/m3, with a low-to-high trend for observation periods: midnight and early morning < night < morning < afternoon. The composition of PM2.5 remained consistent across all sampling periods, with the highest content being water-soluble ions, followed by carbonaceous components. The total concentration of water-soluble ions in PM2.5 accounted for 43.4% of PM2.5, and the secondary inorganic components (NH + 4, NO- 3, and SO2- 4) were the main ion components, accounting for 36.1%, 33.6%, and 18.2% of the total ion concentration, respectively. The organic carbon (OC) and element carbon (EC) were 11.5 ± 5.0 µg/m3 and 1.4 ± 0.9 µg/m3, with OC/EC ratio more than 2 in all periods, indicating a significant presence of secondary pollution throughout the observation process. The positive matrix factorization (PMF) model results indicate that the atmospheric PM2.5 in Huai'an was influenced by vehicle exhaust (29.6%), other sources (19.0%), dust sources (18.5%), and secondary sources (13.9%). The sources of PM2.5 were mainly secondary sources during midnight and early morning (18.0%), soil dust during morning and night (21.7% and 20.0%), and motor vehicle exhaust in the afternoon (21.8%), respectively. The results of this study have significance for the scientific prevention and control of atmospheric PM2.5 in East China.
Experimental study of a drill-string test rig and the construction of torsional stability maps
Authors: Santos Adriano D. dos , Costa André L. D. da , Fleury Agenor T. , Ritto Thiago G. 
Published: September 2024

Abstract

This paper presents an experimental study of a test rig designed to emulate drill-string dynamic phenomena and construct torsional stability maps. The primary objective is to analyze the torsional vibration of a slender shaft subjected to frictional torque induced by pins, considering various imposed axial forces and rotational speeds. A methodology for building the stability map is proposed. Three different scenarios that influence torsional behavior are analyzed, resulting in distinct stability maps. The findings indicate that initiating shaft rotation prior to axial contact and applying axial oscillations during contact contribute to improving torsional stability. Overall, the study highlights the significance of these factors in understanding and enhancing torsional stability in drill-string systems.
Stress Relaxation Curves Modelling for Creep-Fatigue Damage Estimation of Nickel-based Alloy 617
Authors: Dewa Rando Tungga 
Published: September 2024

Abstract

This paper focuses on the model assessment for characterizing the stress relaxation behavior for creep-fatigue damage estimation of Alloy 617, this is to generate an overall model for verification of relaxed stress at long-term prediction. The creep-fatigue tests were initially conducted under tension hold only, with a variety of hold times and total strain ranges. In this study, the predictive performance of the models is selected and fitted to the short-term stress relaxation data sets, then extrapolated to some extent. The models include classical relaxation models, long-term creep models, and model integration. Peleg’s model shows the most superior results in comparison to the other leading models according to the R² value. The creep-fatigue damage calculation is performed once again according to the ideal model. The results show that the damage estimations are more accurate, meaning that the data points are closer to the draft Alloy 617 code case. The fractured surface shows a brittle crack initiation at the oxide surface followed by a transgranular crack.
Enzyme- and GSH-responsive gelatin coated magnetic multi-shell hollow mesoporous organosilicon nanoparticles for avermectin controlled-release
Authors: Gao Jiazhen , Luo Pengyu , Shen Siqiang , Liu Ying , Li Xiaoyun , Wang Xiaoying 
Published: September 2024

Abstract

To enhance the utilization of pesticides and reduce environmental risks, we constructed the magnetic recyclable and dual stimulus-responsive nanoparticles to achieve on-demand pesticide release. Magnetic multi-shell hollow mesoporous organosilicon nanoparticles (mMSN) were prepared by one-step hydrothermal method and loaded with pesticide avermectin (A@mMSN), afterwards A@mMSN were coated with gelatin through emulsification and chemical cross-linking to prepare A@mMSN@G microspheres (21.5 ± 9.7 µm). After being absorbed by the pests, the gelatin layer was hydrolyzed with the neutral protease, and the disulfide bonds within mMSN framework were decomposed by glutathione (GSH), endowing A@mMSN@G microspheres with enzyme and GSH responsiveness to achieve sustained avermectin release till 7 days (about 3.5 times that of the commercial avermectin emulsion). Importantly, the A@mMSN@G microspheres containing Fe3O4 nanoparticles could be easily magnetically collected from soil with a recovery rate of 41.7%, to reduce the environmental risks. With excellent biosafety, A@mMSN@G microspheres showed outstanding pest control effects till two weeks and the growth of cabbage was not affected by it. Therefore, based on the recyclability and dual stimulus-responsive controllable release, the fabricated A@mMSN@G microspheres have broad application potential in pesticide delivery.
Experimental Study on the Flexural Behavior of Ferrocement Slab Panels With Supplementary Cementitious Silica Fume and Fiber Materials
Authors: Kaushik Pooja , Hassan Owais Ul , Sharif Mohammed 
Published: September 2024

Abstract

Ferrocement is a composite construction material with slender sections or panels, a rich cementitious mortar, and steel wire mesh as its principal reinforcing agent. The mortar matrix is designed to achieve optimal strength, density, impermeability, and workability, minimizing void formation and preventing map cracking. A study evaluated the workability and flexural strength of mortars prepared using three types of fine aggregates: Badarpur sand, Yamuna River sand, and Kilned Brick Powder. The mortar classifications included conventional mortar compositions (MCS), mortars with flyash and Silica Fume (MFSS), and mortars with flyash, silica fume, and human hair (MFSHS). The results showed that mixes incorporating these materials significantly improved workability, with MFSS-2 showing the highest increase (42.50%). The high-strength formulations with supplementary materials were superior in terms of stiffness and structural integrity, with MFSHS-1 showing the least deflection for any given load. The addition of 1% human hair fibers in the mortar matrix improved flexural strength in panels, acting as micro-reinforcements, enhancing the tensile strength alongwith mortar ductility.
A hybrid design for Phase I clinical trials
Authors: Xiao Jiacheng , Zhang Weijia , Jin Qiuqi 
Published: September 2024

Abstract

Background: How to determine the maximum tolerated dose (MTD) is the primary objective in phase I clinical trial. The study indicates that the trial would fail, largely because a suboptimal dose is recommended to the further stage. The overly toxic dose assigned to patients during the treatment could lead to irreversible damage and even death, as a result, the safety of the design has been frequently emphasized.
Methods: We propose a novel hybrid design that incorporates the CRM into the Keyboard design. Results: The hybrid design has superiorities in safety control and accuracy of recommendation over the existing designs.
Conclusion: The hybrid design maximizes the merits and minimizes the limitations. In other words, the proposed the method possesses these two advantages, the overdose control and full use of information, meanwhile, the aggressive dose transition of the CRM has been avoided.
Enhanced Reinforcement Learning-based Resource Allocation and Interference Mitigation in Beyond 5G D2D Heterogeneous Networks
Authors: Edla Susmitha , Dharani M 
Published: September 2024

Abstract

The increasing demands for higher data rates in Beyond 5G (B5G) networks necessitate the effective deployment of small cells (SCs) to ensure optimal Quality of Service (QoS) for cell edge user equipment (CEUE) in densely populated areas. Our study introduces an advanced two-step algorithm that leverages reinforcement learning to match dynamic resources and optimize power allocation to maximize network performance. Initially, our upgraded algorithm employs a novel Q-learning approach to optimally pair user equipment (UEs) with available resources, focusing on sum-rate maximization while minimizing interference at each step. Subsequently, we enhance the power allocation strategy using a sophisticated differential evolution algorithm that adapts to varying network conditions, ensuring robust QoS for CEUEs. The proposed method not only refines the matching and power allocation processes, but also introduces adap-tive thresholds for real-time network adjustments, contributing to a substantial performance increase over existing methods. Our results indicate improvements in sum-rate by at least 15% and 35% in interference reduction compared to conventional techniques. This study not only underscores the efficiency of the integrated reinforcement learning approach in dense B5G environments but also sets a foundation for future research in autonomous network management.