bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhancing electrochemical carbon dioxide capture with supercapacitors
Authors: Xu Zhen , Mapstone Grace , Coady Zeke , Wang Mengnan , Spreng Tristan L. , Liu Xinyu , Molino Davide , Forse Alexander C. 
Published: September 2024

AbstractSupercapacitors are emerging as energy-efficient and robust devices for electrochemical CO2 capture. However, the impacts of electrode structure and charging protocols on CO2 capture performance remain unclear. Therefore, this study develops structure-property-performance correlations for supercapacitor electrodes at different charging conditions. We find that electrodes with large surface areas and low oxygen functionalization generally perform best, while a combination of micro- and mesopores is important to achieve fast CO2 capture rates. With these structural features and tunable charging protocols, YP80F activated carbon electrodes show the best CO2 capture performance with a capture rate of 350 mmolCO2 kg–1 h–1 and a low electrical energy consumption of 18 kJ molCO2–1 at 300 mA g–1 under CO2, together with a long lifetime over 12000 cycles at 150 mA g–1 under CO2 and excellent CO2 selectivity over N2 and O2. Operated in a “positive charging mode”, the system achieves excellent electrochemical reversibility with Coulombic efficiencies over 99.8% in the presence of approximately 15% O2, alongside stable cycling performance over 1000 cycles. This study paves the way for improved supercapacitor electrodes and charging protocols for electrochemical CO2 capture.
Bayesian optimization acquisition functions for accelerated search of cluster expansion convex hull of multi-component alloys
Authors: Wen Dongsheng , Tucker Victoria , Titus Michael S. 
Published: September 2024

AbstractAtomistic simulations are crucial for predicting material properties and understanding phase stability, essential for materials selection and development. However, the high computational cost of density functional theory calculations challenges the design of materials with complex structures and composition. This study introduces new data acquisition strategies using Bayesian-Gaussian optimization that efficiently integrate the geometry of the convex hull to optimize the yield of batch experiments. We developed uncertainty-based acquisition functions to prioritize the computation tasks of configurations of multi-component alloys, enhancing our ability to identify the ground-state line. Our methods were validated across diverse materials systems including Co-Ni alloys, Zr-O compounds, Ni-Al-Cr ternary alloys, and a planar defect system in intermetallic (Ni1−x, Cox)3Al. Compared to traditional genetic algorithms, our strategies reduce training parameters and user interaction, cutting the number of experiments needed to accurately determine the ground-state line by over 30%. These approaches can be expanded to multi-component systems and integrated with cost functions to further optimize experimental designs.
Tuning the Schottky barrier height in single- and bi-layer graphene-inserted MoS2/metal contacts
Authors: Zhao Xumei , Xia Caijuan , Li Lianbi , Wang Anxiang , Cao Dezhong , Zhang Baiyu , Fang Qinglong 
Published: September 2024

AbstractFirst-principle calculations based on density functional theory are employed to investigate the impact of graphene insertion on the electronic properties and Schottky barrier of MoS2/metals (Mg, Al, In, Cu, Ag, Au, Pd, Ti, and Sc) without deteriorating the intrinsic properties of the MoS2 layer. The results reveal that the charge transfer mainly occurs at the interface between the graphene and metal layers, with smaller transfer at the interface between bi-layer garphene or between graphene and MoS2. And the tunneling barrier exists at the interface between graphene and MoS2, which hinders electron injection from graphene to MoS2. Importantly, the Schottky barrier height ($$\Phi_{{\text{SB,N}}}$$

Φ
SB,N

) decreases upon graphene insertion into MoS2/metal contacts. Specifically, for single-layer graphene, the $$\Phi_{{\text{SB,N}}}$$

Φ
SB,N

of MoS2 contacted with Mg, In, Sc, and Ti are − 0.116 eV, − 0.116 eV, − 0.014 eV, and − 0.116 eV, respectively. Furthermore, with bilayer graphene, when by inserting bi-layer graphene, the negative n-type Schottky barrier of − 0.086 eV, − 0.114 eV, − 0.059 eV, − 0.008 eV, and − 0.0636 eV are observed for MoS2 contacted with the respective metals, respectively. These findings provide a practical guidance for developing and designing high-performance transition metal dichalcogenide nanoelectronic devices.
Clinical outcomes and radiolucent line analysis in cementless mobile-bearing total knee arthroplasty: a prospective multicentre study in Japan
Authors: Minoda Yukihide , Nakagawa Shigeru , Ueyama Hideki , Warashina Hideki , Kato Michitaka , Matsumoto Tomoyuki , Nozaki Masahiro , Kobayashi Makoto , Horikoshi Yukie , Yasuda Junko 
Published: September 2024

Abstract
The objective of this study was to assess radiolucent lines (RLLs) and to determine their effect on clinical outcomes of the newly introduced cementless mobile-bearing total knee arthroplasty (TKA) system. This was prospective, multicentre study. Seventy-eight patients with knee osteoarthritis who underwent primary TKA were enrolled. Patient-reported outcome measures (PROMs) and radiographic assessments were evaluated at preoperative baseline and at 6 weeks, 1 year, and 2 years after surgery. KOOS, PKIP, 2011KSS, EQ-5D-3L and SKO improved from preoperative baseline to all postoperative timepoints, with no loosening of components. No RLLs were detected at 6 weeks after surgery. However, RLLs ≥ 1 mm developed in 2.8% of the patients for the femur and 9.7% for the tibia at 1 year after surgery, and values were 5.7% and 10.9%, respectively, at 2 years after surgery. RLL incidence was not correlated with PROMs. Age, sex, body mass index, range of motion knee flexion, posterior cruciate ligament treatment and β angle did not impact the occurrence of RLLs. There were no intraoperative complications, revisions or reoperations. This TKA system improved PROMs and showed less incidence of RLLs compared to the previous reported TKA without implant-related complications.
Surface damage reduction effect of ultra-high working face in Shangwan coal mine
Authors: Xinjie L. I. U. , Yingming Yang , Yongqiang Zhao , Xiaolong WANG , Gang Liu , Zhuhe Xu 
Published: September 2024

AbstractGreen mining is the basic background of high-quality mining, and source reduction is the most important part, among which the optimization of working face height and length is the most active. How to control the working face parameters, reasonably evaluate the surface subsidence characteristics of the super-long working face, and identify the limit working face length and the surface discontinuous deformation threshold is particularly important. In order to solve the problem of irreversible damage to the surface caused by the mining process of the working face, this paper discusses the whole process of surface movement in the 8.8 m super-large mining height working face of Shangwan Coal Mine through field investigation, the maximum subsidence is 6.20 m, with a subsidence coefficient of 0.72. Combined with the inflection point trajectory, advancing degree and subsidence coefficient, the 0.9 coefficient of the working face subsidence basin boundary and the loss reduction strategy far from the limit working face threshold are proposed. The results show that the subsidence basin of 12,401 working face accounts for 34%, the continuous deformation area of surface accounts for 64%, and the influence area of discontinuous deformation area is within 10 times of mining height. With the help of borehole detection verification, the caving zone height within the coal seam overburden to be between 33.2 and 33.25 m and the fracture zone height between 118.08 and 132.83 m. Therefore, the caving ratio is about 3.8, and the fracture ratio is about 13–15, which provides a strong basis for the optimization design of working face and the timing of surface ecological management.
Effects of different phosphorus and potassium supply on the root architecture, phosphorus and potassium uptake, and utilization efficiency of hydroponic rice
Authors: Liu Ya , Gao Jiping , Zhao Yanze , Fu Yichen , Yan Bingchun , Wan Xue , Cheng Guoqing , Zhang Wenzhong 
Published: September 2024

AbstractPhosphorus (P) and potassium (K) affect seedling growth, root configuration, and nutrient uptake in hydroponic rice, but there are few studies on all growth stages of rice. The purpose of this experiment was to determine the response characteristics of root morphology, plant physiology, and P and K uptake and utilization efficiency to different supplies of P and K. Two local conventional rice varieties (Shennong 265 and Liaojing 294) were used as experimental materials across four treatments, including HPHK (sufficient P and K supply), HPLK (sufficient P supply under low K levels), LPHK (sufficient K supply under low P levels) and LPLK (low P and K levels) in a hydroponic setting. The results showed that HPHK and HPLK significantly decreased the acid phosphatase activity of leaves and roots from full heading to filling stages when compared to LPHK and LPLK. Sufficient supply of P or K significantly increased the accumulation of P and K (aboveground, leaves, stem sheath, and whole plant) and root morphological parameters (root length, root surface area, total root volume, and tips) during major growth stages when compared to LP or LK levels. HPHK was significantly higher than other treatments in terms of dry weight and the root activity at the main growth stage, P and K uptake rates in nutrient solutions at various stages, related P and K efficiency at the maturity stage, yield, effective panicle number, and grain number per panicle. In addition, the effect of HPHK on the above indexes were significantly greater than those of single sufficient supply of P or K. In conclusion, HPHK can improve plant configuration, increase plant P and K absorption and root activity, and increase rice yield and related P and K utilization efficiency.
An Introduction to Machine Learning for Speech-Language Pathologists: Concepts, Terminology, and Emerging Applications
Authors: Cordella Claire , Marte Manuel J. , Liu Hantian , Kiran Swathi 
Published: September 2024

Purpose:
The purpose of this article is to orient both clinicians and researchers to machine learning (ML) approaches as applied to the field of speech-language pathology. We first introduce key ML concepts and terminology and proceed to feature exemplar papers of recent work utilizing ML techniques in speech-language pathology. We also discuss the limitations, cautions, and challenges to the implementation of ML and related techniques in speech-language pathology.

Conclusions:
Readers are introduced to broad ML concepts, including common ML tasks (e.g., classification, regression), and specific types of ML models (e.g., linear/logistic regression, random forest, support vector machines, neural networks). Key considerations for developing, evaluating, validating, and interpreting ML models are discussed. An application section reviews six exemplar published papers in the aphasiology literature that have utilized ML approaches. Lastly, limitations to the implementation of ML approaches are discussed, including issues of reliability, validity, bias, and explainability. We highlight emergent solutions and next steps to facilitate responsible and clinically meaningful use of ML approaches in speech-language pathology moving forward.
YOLO-CIANNA: Galaxy detection with deep learning in radio data
Authors: Cornu D. , Salomé P. , Semelin B. , Marchal A. , Freundlich J. , Aicardi S. , Lu X. , Sainton G. , Mertens F. , Combes F. , Tasse C. 
Published: September 2024

Context. The upcoming Square Kilometer Array (SKA) will set a new standard regarding data volume generated by an astronomical instrument, which is likely to challenge widely adopted data-analysis tools that scale inadequately with the data size.Aims. The aim of this study is to develop a new source detection and characterization method for massive radio astronomical datasets based on modern deep-learning object detection techniques. For this, we seek to identify the specific strengths and weaknesses of this type of approach when applied to astronomical data.Methods. We introduce YOLO-CIANNA, a highly customized deep-learning object detector designed specifically for astronomical datasets. In this paper, we present the method and describe all the elements introduced to address the specific challenges of radio astronomical images. We then demonstrate the capabilities of this method by applying it to simulated 2D continuum images from the SKA observatory Science Data Challenge 1 (SDC1) dataset.Results. Using the SDC1 metric, we improve the challenge-winning score by +139% and the score of the only other post-challenge participation by +61%. Our catalog has a detection purity of 94% while detecting 40–60% more sources than previous top-score results, and exhibits strong characterization accuracy. The trained model can also be forced to reach 99% purity in post-process and still detect 10–30% more sources than the other top-score methods. It is also computationally efficient, with a peak prediction speed of 500 images of 512×512 pixels per second on a single GPU.Conclusions. YOLO-CIANNA achieves state-of-the-art detection and characterization results on the simulated SDC1 dataset and is expected to transfer well to observational data from SKA precursors.
Environmental Impact Targets for Sustainable Foods Based on Their Nutritional Value
Authors: Sherwood James 
Published: September 2024

Abstract
Human activities create an immense strain on many ecological processes. Agriculture and the wider food supply sector is the source of much of this environmental damage. The traditional interpretation of environmental impacts provided by life cycle assessments (LCAs) does not provide any understanding of whether a product or process is sustainable or not. Recently, Planetary Boundaries have quantified sustainable limits to human activities at the global scale. Here we shall merge the analysis of LCA with the context provided by Planetary Boundaries to understand the sustainability of foods. The resulting metric, ‘Performance-weighted Environmental Sustainability’, was used to analyse the land use change, freshwater use, and climate change impacts of foods, and create a sustainable diet plan. The results of this analysis indicate that very few foods are truly sustainable. A case study on milk alternatives suggests no plant-based drinks are actually sustainable, although soymilk has the most preferable balance of high nutritional content and low environmental impacts. A sustainable daily meal plan was also designed and compared to typical dietary recommendations. Animal products could not be incorporated into the sustainable meal plan due to their high environmental impact. Conversely, bread is high in fibre and protein and has a relatively low environmental impact, making it the ideal basis for a sustainable vegan diet supplemented with vegetables, nuts, and soy products. Finally, an interactive tool has been provided to assist with the understanding of the ‘Performance-weighted Environmental Sustainability’ metric and encourage the design of healthy and sustainable meals.

Information
© The Author 2024
Arbitrability of cryptocurrency disputes in India
Authors: Nema Purvi 
Published: September 2024

Abstract
Over the past decade, the growth of cryptocurrencies has amazed policymakers worldwide, prompting governments, international organizations, and corporations to address the increasing financial activity in this unregulated and decentralized industry. The murmurs of crypto disputes accelerated after the dramatic collapse of the crypto-trading platform Binance on the day Bitcoin was valued very low, leading to huge losses for its investors. This incident has led to discussions about the potential of using a private forum, such as arbitration, to resolve conflicts in the crypto world. However, adopting arbitration in cryptocurrency disputes raises complex questions, such as whether or not cryptocurrency disputes can be settled by arbitration. This article explores the issue of arbitrability of cryptocurrency-related disputes in India, particularly those related to payment and security tokens. Before discussing the issue of arbitrability, the article will first provide an overview of Indian law on cryptocurrencies, including their validity and regulation. Based on this legal background, it will examine the scope of arbitrability under the Arbitration and Conciliation Act of 1996, focusing on the subject matter in dispute and the public policy test.
Interpreting the Paris Agreement in its Normative Environment
Authors: Rajamani Lavanya 
Published: September 2024

Abstract
International and regional courts are increasingly being asked to determine the rights and responsibilities of states in relation to climate harm. The context for such requests is that the 2015 Paris Agreement, comprising primarily procedural obligations and obligations of conduct, and premised on national determination, appears by itself radically insufficient to resolve the existential climate crisis the planet is facing. This article explores if this is indeed the case and argues that the 2015 Paris Agreement must be interpreted in its ‘normative environment’. The ‘normative environment’ includes the customary international law principle of harm prevention, other treaties, including human rights ones, and a set of principles of varying legal status but considerable operational relevance and guidance. This article examines specific obligations from the 2015 Paris Agreement and seeks to concretize and strengthen them based on this interpretative approach. While such strengthened obligations might yet be insufficient to decisively resolve the climate crisis, these nevertheless reflect a richer account of international legal resolve relating to climate change—one that is premised on an understanding of international law as a seamless web of inter-locking obligations rather than of treaties functioning as atomistic reflections of state consent in that area.
Zinc-alpha2-glycoprotein modulates blood pressure by regulating renal lipid metabolism reprogramming-mediated urinary Na+ excretion in hypertension
Authors: Zhou Xiaoxin , Deng Chunyan , Chen Lin , Lei Lifu , Wang Xiaoliang , Zheng Shuo , Chen Caiyu , Du Chengfeng , Schini-Kerth Valérie B , Yang Jian 
Published: September 2024

Abstract

Aims
Organs modulating blood pressure are associated with a common cytokine known as adipokines. We chose Zinc-alpha2-glycoprotein (ZAG) due to its prioritized transcriptional level in the database. Previous studies showed that ZAG is involved in metabolic disorders. The aim of this study was to investigate its role in hypertension.

Methods and results
Serum ZAG levels were assessed in hypertensive and healthy participants. Blood pressure was monitored in Azgp1−/− mice and other animal models by 24-hour ambulatory implanted telemetric transmitters and tail-cuff method. Multi-omics analysis of proteomics and metabolomics were performed to explore possible mechanisms. Serum ZAG levels were significantly decreased and associated with morning urine Na+ excretion in hypertensive participants in a cross-sectional study. This study firstly reported that Azgp1−/− mice exhibited increased blood pressure and impaired urinary Na+ excretion, which were restored by AAV9-mediated renal tubule Azgp1 rescue. Azgp1 knockout caused the reprogramming of renal lipid metabolism, and increased Na+/H+-exchanger (NHE) activity in the renal cortex. Administration with a NHE inhibitor EIPA reversed the impaired urinary Na+ excretion in Azgp1−/− mice. Moreover, the activity of carnitine palmitoyltransferase 1 (CPT1), a key enzyme of fatty acid β-oxidation, was decreased, and the levels of malonyl-CoA, an inhibitor of CPT1, were increased in renal cortex of Azgp1−/− mice. Renal Cpt1 rescue improved urinary Na+ excretion and blood pressure in Azgp1−/− mice, accompanied by decreased renal fatty acid levels and NHE activity. Finally, administration of recombinant ZAG protein improved blood pressure and urinary Na+ excretion in spontaneous hypertension rats.

Conclusion
Deficiency of Azgp1 increased the malonyl CoA-mediated inhibition of CPT1 activity, leading to renal lipid metabolism reprogramming, resulting in accumulated fatty acids and increased NHE activity, subsequently decreasing urinary Na+ excretion and causing hypertension. These findings may provide a potential kidney-targeted therapy in the prevention and treatment of hypertension.
Effects of self-perception of aging interventions in older adults: A systematic review and meta-analysis
Authors: Zhu Mingyue , Chen Huimin , Ding Xiaotong , Li Zheng 
Published: September 2024

Abstract

Background and Objectives
Self-perception of aging (SPA) is associated with various health outcomes in the aging process. This study aimed to conduct a systematic review of existing interventions targeting SPA among older adults, and to synthesize their effects on self-perception of aging, physical performance, and mental health.

Research Design and Methods
A systematic search was performed in PubMed, Embase, PsycINFO, CINAHL, Web of Science, CENTRAL, CNKI, SinoMed, VIP, and WanFang databases for randomized controlled trials that reported intervention effects on self-perception of aging, physical performance, and mental health in older adults. Two researchers independently conducted study selection, data extraction and quality assessment.

Results
A total of 16 studies were included for qualitative analysis, and 12 studies of them were included for meta-analysis. The results showed a significant impact of interventions on self-perception of aging, with the effect size of -0.56 (95% CI -1.06 to -0.07, P=0.03). And the results also supported a significant improvement in physical performance and mental health among older adults.

Discussion and Implications
Self-perception of aging interventions present a promising approach to enhance positive aging perception for older adults, with potential benefits extending to physical performance and mental health. However, larger-scale and more robust trials are still required to validate these findings and obtain more accurate conclusions.