bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reinforcement Learning‐Based Prescribed Performance Formation Control for USVs With Collision Avoidance and Preserved Connectivity
Authors: Li Gengqi , Wang Wei , Cao Liang 
Published: January 2025

ABSTRACTThis paper proposes the reinforcement learning‐based prescribed performance optimal formation control approach for a fleet of unmanned surface vehicles (USVs) with collision avoidance and preserved connectivity. Firstly, to improve the prescribed performance of formation errors while ensuring collision avoidance and preserving connectivity between two successive USVs, the monotone tube boundary functions are designed. Compared to the traditional exponential form of prescribed performance control, the formation error can converge accurately to the vicinity of the origin within a predefined time, and the overshoot of the formation error is constrained. Secondly, in order to derive realistic optimal solutions, an actor‐critic reinforcement learning algorithm is implemented and the unknown parameters are approximated using identifier neural networks, which simplifies the Hamilton‐Jacobi‐Bellman equation to obtain optimal control solutions. Meanwhile, to simplify the computational complexity, a simple positive function is designed, and the gradient descent method is applied to it such that the simplified critic and actor weight updating laws are acquired. Finally, within the framework of the backstepping method, the adaptive optimal formation control strategy ensures that USVs follow a given reference trajectory and maintain the required line‐of‐sight (LOS) range between two consecutive USVs. The feasibility and effectiveness of the proposed control approach are well illustrated by the simulation results.
Event‐Triggered Integral Sliding Mode Control for Nonlinear Networked Cascade Control Systems With Uncertain Delay
Authors: Du Zhaoping , Wang Haojie , Li Jianzhen , Yang Xiaofei , Ye Hui 
Published: January 2025

ABSTRACTThis article investigates the problem of event‐triggered integral sliding mode control (ISMC) for a class of nonlinear networked cascade control systems (NCCSs). Due to the limited communication bandwidth between network nodes, uncertain delay can occur during transmission. This may result in a deterioration of the capabilities of NCCS and system instability in certain instances. Thus, an event‐triggered mechanism (ETM) and ISMC are introduced into the system, and a new model is constructed to increase the network bandwidth and reduce the effect of nonlinear perturbation. After that, the design of two controllers and ETM is accomplished through the use of the Lyapunov generalized method and linear matrix inequality (LMI) techniques. Finally, a simulation example of a power plant model is given to verify the effectiveness of the method. The results show that, for the first time, the event‐triggered ISMC is applied to NCCSs, which greatly saves the network bandwidth resources. The states of the system can reach the sliding mode surface (SMS) in finite time and remain stabilized there afterward, which ensures the stable operation of the system.
Oxygen Reduction Reaction Catalysts for Zinc‐Air Batteries Featuring Single Cobalt Atoms in a Nitrogen‐Doped 3D‐Interconnected Porous Graphene Framework
Authors: Zou Jiaxin , Bao Lishi , Sun Qifeng , Bao Chenguang , Chen Hui , Liu Hongbo 
Published: January 2025

AbstractSingle‐atom catalysts (SACs) with high activity and efficient atom utilization for oxygen reduction reactions (ORRs) are imperative for rechargeable Zinc‐air batteries (ZABs). However, it is still a prominent challenge to construct a noble‐metal‐free SAC with low cost but high efficiency. Herein, a novel nitrogen‐doped graphene (NrGO) based SAC, immobilized with atomically dispersed single cobalt (Co) atoms (Co‐NrGO‐SAC), is reported for ORRs. In this 3D NrGO, the Co‐N4 sites endow high‐efficiency ORR activity, and the 3D‐interconnected porous architectures of NrGOs guarantee numberous active sites accessibility. Compared to commercial Pt/C catalyst (≈5.8 mA cm−2), as‐prepared Co‐NrGO‐SACs presents considerable limiting current density of ≈5.9 mA cm−2, prominent half‐wave potential of ≈0.84 V, onset potential of ≈1.05 V, and as well as superior methanol resistance. Particularly, ZABs with Co‐NrGO‐SACs deliver remarkable power density (≈240 mW cm−2), super durability of over 233 h at 5 mA cm−2, outperforming noble‐metal‐based benchmarks. This work provides an effective noble‐metal free carbon‐based SAC nano‐engineering for superdurable ZABs.
Atomically Dispersed Fe‐Mo Catalysts Mediate Fenton‐Like Reaction to Efficiently Degrade Chlorophenol Pollutants Through Synergistic Oxidation and Dechlorination Reactions
Authors: Xiao Han , Luo Di , Fang Duoduo , Yang Yupeng , Zi Jiangzhi , Lian Zichao 
Published: January 2025

AbstractChlorophenols are difficult to degrade and mineralize by traditional advanced oxidation processes due to the strong electronegativity of chlorine. Here, a dual‐site atomically dispersed catalyst (FeMoNC) is reported, which Fe/Mo supported on mesoporous nitrogen‐doped carbon is prepared through high‐temperature migration. The FeMoNC exhibits a high dechlorination rate of 93.3% within 1 min. Theoretical calculation suggested that the doping of high‐valence Mo6+ as the electron reservoir, promoted electronic delocalization at Fe sites, thereby enhancing the adsorption and dissociation of peroxymonosulfate (PMS), subsequent generation of Fe (IV) = O and singlet oxygen (1O2) species. An interesting finding is that Mo sites can adsorb chlorine sites in 4‐chlorophenol (4‐CP) and induce C─Cl bond fracture. Thus, the FeMoNC/PMS system has high catalytic performance due to the synergistic effects of Mo‐induced dechlorination and non‐radical species (Fe(IV) = O and 1O2) as the degradation pathways, the degradation efficiency of 99.1% of 4‐CP within 5 min without significant performance decline after 168 h ≈15,120‐bed volumes. These findings can advance mechanistic understanding of PMS activation at the molecular level and guide the rational design of efficient eco‐friendly single‐atom catalysts (SACs) catalysts with bimetallic atomic sites.
Induction of Nanoscale Magnetic Ordering in Non‐Ferrous Layered Double Hydroxides: Stabilizing Spintronic Electrocatalysis
Authors: Kansal Sakshi , Ravindran Rahul , Srivastava Alok Kumar , Chandra Amreesh 
Published: January 2025

AbstractInducing magnetic ordering in a non‐ferrous layered double hydroxides (LDHs) instigates higher spin polarization, which leads to enhanced efficiency during oxygen evolution reaction (OER). In nano‐sized magnetic materials, the concept of elongated grains drives domain alignment under the application of an external magnetic field. Hence, near the solid electrode interface, modified magnetohydrodynamics (MHD) positively impacts the electrocatalytic ability of non‐ferrous nanocatalysts. Consequently, significant improvement in the water‐splitting kinetics can be obtained by using even low magnetic fields. At 100 Gauss, 20% and 10% decrement in the overpotential is reported for OER and hydrogen evolution reaction (HER), respectively. Density functional theory (DFT) calculations are also presented to explain the thermodynamics of the HER/OER processes. It is established that the Gibbs energy of the process can reduce the exchange energy barrier by using dopant like cobalt. The additional cobalt metal active site have the highest probability for adsorption of reactive intermediates during HER and OER, which results in higher efficiencies.
Droplet‐Based EPR Spectroscopy for Real‐Time Monitoring of Liquid‐Phase Catalytic Reactions
Authors: Moragues Thomas , Agrachev Mikhail , Mitchell Sharon , Jeschke Gunnar , Pérez‐Ramírez Javier , deMello Andrew J. 
Published: January 2025

AbstractIn situ monitoring is essential for catalytic process design, offering real‐time insights into active structures and reactive intermediates. Electron paramagnetic resonance (EPR) spectroscopy excels at probing geometric and electronic properties of paramagnetic species during reactions. Yet, state‐of‐the‐art liquid‐phase EPR methods, like flat cells, require custom resonators, consume large amounts of reagents, and are unsuited for tracking initial kinetics or use with solid catalysts. To overcome these limitations, a droplet‐based microfluidics platform is introduced for real‐time EPR monitoring of liquid‐phase catalytic reactions. By encapsulating solid and dissolved species within nanoliter droplets, this approach enables precise control over mass transport, reduces reagent consumption, and maintains uniform residence times irrespective of acquisition duration, permitting precise analysis of each spectral component under identical conditions. The platform's compatibility with standard resonators facilitates straightforward integration into any EPR spectrometer. Its versatility is demonstrated by monitoring dynamic ligand exchange processes, key for activating homogeneous catalysts, and tracking redox and radical kinetics in ascorbic acid oxidation by Cu(II) catalysts. Importantly, this method captures both supported and dissolved transition metal species, offering comprehensive insights into catalyst deactivation via metal leaching. This microfluidic approach sets a new standard for liquid‐phase in situ EPR measurements, advancing studies of homogeneous and heterogeneous catalytic systems.
Stress Release of Zincophilic N‐Doped Carbon@Sn Composite on High‐Curvature Surface of Zinc Foam for Dendrite‐Free 3D Zinc Anode
Authors: Lin Yunhui , Lin Fang , Zhang Ming , Jiao Xingxing , Dong Panpan , Yang Weiqing 
Published: January 2025

AbstractCommercial 3D zinc foam anodes with high deposition space and ion permeation have shown great potential in aqueous ion batteries. However, the local accumulated stress from its high‐curvature surface exacerbates the Zn dendrite issue, leading to poor reversibility. Herein, we have employed zincophilic N‐doped carbon@Sn composites (N‐C@Sn) as nano‐fillings to effectively release the local stress of high curvature surface of 3D Zn foams toward dendrite‐free anode in aqueous zinc ion battery (AZIB). These electronegative and conductive N‐C@Sn nano‐fillings as supporters can provide a highly zincophilic channel for initial Zn nucleation and reduce local current density for regulating Zn deposition. Uniform Zn deposition further assists homogenous stress distribution on the platting surface, which gives a positive feedback loop to improve anode reversibility. As a result, zinc foam with N‐C@Sn composite (ZCSn Foam) symmetric cell achieves a long cycle lifespan of 1100h at 0.5 mA cm−2, much more than that of Zn Foam (∼80 h lifespan). The full cell ZCSn Foam||MnO2 exhibits remarkable reversibility with 67% retention after 1000 cycles at 0.8 A g−1 and 76% after 1600 cycles at 2 Ag−1. This 3D‐constructing strategy may offer a promising and practical pathway for metal anode application.
Robotic devices for Structural Health Monitoring
Authors: Górski Marcin , Grzyb Krzysztof , Zając Jakub 
Published: January 2025

AbstractThe last decade has seen the dynamic development of robotic tools, particularly the unmanned aerial vehicle (UAV). Miniaturization, improvement of control tools, and specialization of these devices have made them tools that are eagerly used by various industries, including the construction industry. Initially, UAVs were used for visual inspections; today, highly specialized devices are an increasingly important element of Structural Health Monitoring (SHM), assessing the condition of structures and estimating their load‐bearing capacity. This article aims to present the current state of technology in robotic solutions in SHM, with particular emphasis on those providing possibilities for contact‐based diagnostics. The work refers to wheeled robots and drones, including functional tools for diagnostics of the bond quality of the fiber‐reinforced polymers strengthening overlays with the concrete surface. The paper reviews the types, scope, and methodology of data collection by robotic devices. It also shows attempts to integrate data with other SHM methods, incorporate them into the building information modeling environment, and create a digital twin of the structure. It also indicates further directions of work already initiated in the automated assessment of load‐bearing capacity and estimation of the safety level of structures.
High Schools' Role in Promoting Equity for Multilingual Learners' Access to College
Authors: Kanno Yasuko , Leider Christine Montecillo , Li Kuang , David Nick , Chen Erning “Henry” 
Published: January 2025

AbstractHigh school plays a pivotal role in preparing students for college. Accordingly, a large body of research examines how high schools shape general education students' postsecondary options. However, there is a dearth of research on high schools' role in promoting multilingual learners' (MLs) college access. MLs' educational experiences differ from those of other minoritized students because MLs are still developing English language proficiency while also learning academic content. It is thus important to examine high schools' role in shaping MLs' postsecondary pathways. Adopting a multisite qualitative case study approach and an ecology of equity framework, we compare the policies and practices of two Massachusetts public high schools that both successfully expanded MLs' postsecondary options but in different ways. We argue that expanding equity in MLs' college access looks very different depending on the context of schools and the socioeconomic circumstances and the immigration status of the students they serve. Sending many MLs to 4‐year colleges need not be the only measure of success; expanding MLs' awareness of other postsecondary options and helping them choose a path that is aligned with their goals is also a valid approach to equity.
Family Poultry Farming in Sri Lanka: An Integral Component of Protein Security, Poverty Alleviation and Public Health
Authors: Pujani Gunasekara Umayangana , Wasantha Kalupahana Anil , Deepachandi Gunasekara Yasodhara , Silva‐Fletcher Ayona , Sagarika Kalupahana Ruwani 
Published: January 2025

ABSTRACTFamily poultry farming plays a crucial role in ensuring protein availability and household income, particularly in low‐income families. This study investigates the knowledge, attitudes and practices of family poultry farmers regarding poultry diseases, biosecurity and vaccinations. The research involved surveying 150 farmers in a selected area in Sri Lanka's western province, revealing significant knowledge gaps, particularly in understanding poultry diseases, their causes, transmission pathways and potential impacts on humans. Most respondents demonstrated a lack of familiarity with biosecurity practices, with only a small fraction accurately identified recommended measures. Among the total respondents, only 16.7% were familiar with the term ‘biosecurity’. Additionally, only 29.3% recognized that family poultry could pose a threat to public health. A significant majority (84.67%) admitted to not knowing which diseases could be effectively prevented through vaccination, and 80% of respondents had never vaccinated their birds. These findings highlight the challenges faced by family poultry farmers due to their limited understanding of crucial aspects of poultry management. The study underscores the need for government intervention and policy development to address these issues. Education and training programmes are essential to enhance farmers’ awareness regarding disease control, biosecurity measures and the benefits of vaccination.
3-D Discrete Vortex and Convection for the Lorenz System
Authors: Kawamoto Shunji 
Published: January 2025

Abstract
The Lorenz system is well known as a three-dimensional (3-D) mathematical model for atmospheric convection and is considered from the viewpoint of discrete chaos functions. Firstly, the 3-D generalized Lorenz map with system parameters is proposed, and the bifurcation diagrams are calculated to find discrete limit cycles. Then, the 3-D orbit solutions are shown to have the 2-D limit cycles with active dynamics on the x–y plane. Finally, the 3-D discrete vortices with distortion are numerically illustrated, depending on the system parameters and initial conditions of cells. In particular, the 3-D vortices with distortion and convection correspond to the 2-D limit cycles, which are briefly discussed on high or low atmospheric pressure of atmospheric convection and on 3-D climate change for the Lorenz system, as nonlinear dynamics of 3-D nonequilibrium open systems.
Investigating the Constraints and Mitigation Strategies for the Adoption of Sustainable Land Management Practices in Erosion-prone Areas of Southeast Nigeria
Authors: Olumba Cynthia Nneka , Garrod Guy , Areal Francisco 
Published: January 2025

Abstract
The adoption of sustainable land management practices (SLMPs) is crucial to improve soil health, and farm yield, and potentially limit the degradation of agricultural and ecological systems. However, farmers still encounter diverse challenges when trying to implement SLMPs. Research on the potential mitigation strategies to address the complex challenges to the adoption of SLMPs in the developing countries context is limited. Accordingly, this study investigates the constraints to adopting SLMPs using household survey data collected from 480 sampled farmers in erosion-prone areas of southeast Nigeria. Also, through focus groups and interviews with key stakeholders in the land sector, the study investigates the potential mitigation strategies to address the constraints. Descriptive statistics were used to explore the characteristics of the farmers, while Principal component analysis (PCA) was used to analyse the constraints to the adoption of SLMPs. The qualitative data collected were analysed using inductive thematic analysis. The PCA result identified economic/financial factors as the principal constraint to the adoption of SLMPs. Other barriers to the adoption of SLMPs in the study area include constraints related to the characteristics of the SLMPs, institutional constraints and constraints related to land property rights. Based on the stakeholders’ perspectives, financial and economic support, improved R&D, knowledge exchange and advisory system, policy and regulatory solutions, and multi-stakeholder engagement are important strategies to tackle the constraints to the adoption of SLMPs. Insights from this study could help practitioners, conservation planners and policymakers design more targeted and effective interventions to promote the widespread adoption of SLMPs.
CXR-LLaVA: a multimodal large language model for interpreting chest X-ray images
Authors: Lee Seowoo , Youn Jiwon , Kim Hyungjin , Kim Mansu , Yoon Soon Ho 
Published: January 2025

Abstract

Objective
This study aimed to develop an open-source multimodal large language model (CXR-LLaVA) for interpreting chest X-ray images (CXRs), leveraging recent advances in large language models (LLMs) to potentially replicate the image interpretation skills of human radiologists.

Materials and methods
For training, we collected 592,580 publicly available CXRs, of which 374,881 had labels for certain radiographic abnormalities (Dataset 1) and 217,699 provided free-text radiology reports (Dataset 2). After pre-training a vision transformer with Dataset 1, we integrated it with an LLM influenced by the LLaVA network. Then, the model was fine-tuned, primarily using Dataset 2. The model’s diagnostic performance for major pathological findings was evaluated, along with the acceptability of radiologic reports by human radiologists, to gauge its potential for autonomous reporting.

Results
The model demonstrated impressive performance in test sets, achieving an average F1 score of 0.81 for six major pathological findings in the MIMIC internal test set and 0.56 for six major pathological findings in the external test set. The model’s F1 scores surpassed those of GPT-4-vision and Gemini-Pro-Vision in both test sets. In human radiologist evaluations of the external test set, the model achieved a 72.7% success rate in autonomous reporting, slightly below the 84.0% rate of ground truth reports.

Conclusion
This study highlights the significant potential of multimodal LLMs for CXR interpretation, while also acknowledging the performance limitations. Despite these challenges, we believe that making our model open-source will catalyze further research, expanding its effectiveness and applicability in various clinical contexts.

Key Points

Question

How can a multimodal large language model be adapted to interpret chest X-rays and generate radiologic reports?

Findings

The developed CXR-LLaVA model effectively detects major pathological findings in chest X-rays and generates radiologic reports with a higher accuracy compared to general-purpose models.

Clinical relevance

This study demonstrates the potential of multimodal large language models to support radiologists by autonomously generating chest X-ray reports, potentially reducing diagnostic workloads and improving radiologist efficiency.
Clinical and magnetic resonance imaging outcome after proximal hamstring tendon repair at mean 3 years follow-up
Authors: Sgustav Carlo , Lacheta Lucca , Stöckle Ulrich , Akgün Doruk , Geisel Dominik , Park Hi-Un , Marth Adrian , Kim Suchung 
Published: January 2025

Abstract

Purpose
The purpose of this study was to assess clinical and radiological outcome in patients after proximal hamstring tendon repair. We hypothesized that there is a significant correlation among subjective clinical outcome and interlimb asymmetries in muscle strength, fatty infiltration, and hamstring volume.

Methods
This retrospective monocentric case series included patients with surgical repair after proximal hamstring tendon rupture. Clinical outcome was assessed utilizing: Healthy Days Core Module (CDC HRQOL-4), numeric pain rating scale (NRS), modified Harris Hip Score (mHHS), Tegner Activity Scale (TAS), return to pre-injury activity level (RTPA), and patient satisfaction score. Postoperative hamstring strength was measured using a handheld dynamometer and radiological outcome was determined by postoperative magnetic resonance imaging (MRI).

Results
Twenty-seven patients with a mean age of 51.2 (± 12.6) years were available for follow-up at a mean of 41.11 (± 18.4) months. Patients state a mean of 10.6 (± 11.5) days in the unhealthy days (UHD) index and 88.9% show “good health” in the simple summary score (SSS). Mean subjective outcome scores were as follows: NRS 1.1 (± 2.4), mHHS 90.3 (± 14.8) and TAS 5.7 (± 2.2). A total of 59.3% RTPA and 88.9% state to be somewhat or very satisfied with their surgery. Mean interlimb strength ratio was 0.88 (± 0.21). MRI demonstrated a fully restored muscle–tendon unit, significantly greater fatty infiltration in the injured hamstrings (p = 0.009, d = 0.558), and a mean interlimb hamstring volume ratio of 0.94 (± 0.11). With respect to the 10% benchmark, patients had no significant asymmetries in muscle strength (p = 0.677, d = 0.084) or hamstring volume (p = 0.102, d = − 0.34). Correlation analysis revealed moderate correlation among asymmetries in strength and volume (p = 0.073, r = 0.373). In patients with the operated side inferior to the healthy side (n = 15), there was strong correlation among asymmetries in strength and volume (p = 0.002, r = 0.725). Statistically significant correlation was found between interlimb muscle volume atrophy and increase in fatty infiltration (p = 0.015, r = 0.481).

Conclusion
Proximal hamstring repair results in good clinical outcome with satisfactory recovery of hamstring strength and volume. Interlimb asymmetries, in terms of muscle strength, fatty infiltration, and hamstring volume do not correlate with clinical outcome.

Study Type
Retrospective cohort study; Level of evidence, 3.