bluuebunny/crossref_metadata_2025_split huggingface dataset:
Superhydrophobic cellulose-nanofiber aerogels from waste cotton stalks for superior oil–water and emulsion separation
Authors: Zhang Chengbo , Chen GuoHao , Lang DaNing , Liu Gang , Wu RongLan , Wang Wei , Zhang Zheng , Li JiYang , Fu JiHong 
Published: August 2024

AbstractCellulose aerogel, a sustainable material characterized by low density and high porosity, demonstrates promising potential for addressing oil spill incidents. In this study, waste cotton stalk biomass was processed using formic acid and hydrogen peroxide to extract cellulose, resulting in the successful creation of a cost-effective aerogel. This material exhibits notable attributes: low density (21.1 mg cm−3), high porosity (91.5%), significant hydrophobicity (water contact angle of 147°), exceptional adsorption capacity (47.61 g g−1), and robust cycling performance (maintaining 94% adsorption capacity after 15 cycles). Moreover, the CNF/CS biomass aerogel boasts high mechanical strength and exceptional oil–water and emulsion separation properties. These characteristics position this aerogel as a promising solution for mitigating various sudden oil spill incidents, indicating its potential for widespread application.
Optimization of Joint Space Trajectories for Assistive Lower Limb Exoskeleton Robots: Real-Time and Flexible Gait Patterns
Authors: Mohamad Habib , Ozgoli Sadjaad , Kazemi Jafar 
Published: August 2024

AbstractThis research focuses on designing a real-time, flexible gait planner for lower limb exoskeleton robots to assist patients with lower limb disabilities. Given the dynamic nature of gait parameters, which vary according to ground conditions and user intent, the challenge lies in developing a gait planner capable of adapting to these changes in real-time. To avoid planning complications in the cartesian space and to comply with the speed constraints of joint motors, this paper proposes planning in joint space. Furthermore, the approach also considers the maximum speed capabilities of the joint motors, aiming to generate an executable gait pattern and simultaneously enhance the robot’s walking speed by determining the minimum time required for implementation. The introduced gait planner optimizes joint trajectories for minimal angular acceleration. To provide flexibility, generalized boundary conditions suitable for different scenarios are defined. The effectiveness of the proposed planner is validated through comprehensive performance analysis, simulations, and successful implementation trials on the Exoped® robot in various scenarios.
Ruin Probabilities as Recurrence Sequences in a Discrete-Time Risk Process
Authors: Cruz Ernesto , Rincón Luis , Santana David J. 
Published: August 2024

AbstractThe theory of linear recurrence sequences is applied to obtain an explicit formula for the ultimate ruin probability in a discrete-time risk process. It is assumed that the claims distribution is arbitrary but has finite support $$\varvec{\{0,1,\ldots ,m+1\}}$$

{
0
,
1
,
…
,
m
+
1
}

, for some integer $$\varvec{m\ge 1}$$

m
≥
1

. The method requires finding the zeroes of an m degree polynomial and solving a system of m linear equations. An approximation is derived and some numerical results and plots are provided as examples.
Endocannabinoid system and phytocannabinoids in the main species of veterinary interest: a comparative review
Authors: Di Salvo Alessandra , Chiaradia Elisabetta , Sforna Monica , della Rocca Giorgia 
Published: August 2024

AbstractSince the discovery of the endocannabinoid system and due to the empirical evidence of the therapeutic effects on several illnesses both in humans and animals that follow the administration of exogenous cannabinoids (i.e., phytocannabinoids), numerous studies have been conducted. These investigations aimed to identify the expression and distribution of cannabinoid receptors in healthy and pathologic organs and tissues of different animal species and to define the interactions of phytocannabinoids with these receptors. In the last decade, pharmacokinetics, efficacy and tolerability of many Cannabis derivatives formulations, mainly containing cannabidiol, in the main species of veterinary interest, have been also investigated. This manuscript summarizes the findings reported by the scientific studies published so far on the molecular mode of action of the main phytocannabinoids, the localization of cannabinoid receptors in organs and tissues, as well as the pharmacokinetics, efficacy and tolerability of Cannabis derivatives in dogs, cats, horses and other species of veterinary interest. A deep knowledge of these issues is crucial for the use of phytocannabinoids for therapeutic purposes in animal species.
Life satisfaction, psychological distress, compassion satisfaction and resilience: when the pleasure of helping others protects veterinary staff from emotional suffering
Authors: Peixoto Maria Manuela , Cunha Olga 
Published: August 2024

Abstract
Introduction
Individuals working in veterinary field suffer significantly from mental health problems, and research has extensively focused on psychological and work-related predictors of psychological distress. This study intended to approach psychological distress through a positive lens by investigating the predictive role of life satisfaction on psychological distress in veterinary staff, and the mediating effect of compassion satisfaction, resilience and perceived social support.

Methodology
A total of 868 veterinary staff (i.e. veterinarians, veterinary nurses, veterinary assistants and veterinary administrative staff) completed a web-survey assessing life satisfaction, psychological distress, compassion satisfaction, resilience, and social support.

Results
Life satisfaction negatively predicts psychological distress, and compassion satisfaction and resilience showed a mediation effect on the relationship between life satisfaction and psychological distress, with compassion satisfaction explaining 59% and resilience 6.4% of the effect of life satisfaction on psychological distress.

Conclusion
Current data support the role of life satisfaction as a protective dimension on psychological distress within a broader sample population of veterinary staff in Portugal, highlighting the role of compassion satisfaction and resilience in contributing in minimising distress among veterinary staff.
Preliminary assessment of TNM classification performance for pancreatic cancer in Japanese radiology reports using GPT-4
Authors: Suzuki Kazufumi , Yamada Hiroki , Yamazaki Hiroshi , Honda Goro , Sakai Shuji 
Published: August 2024

Abstract
Purpose
A large-scale language model is expected to have been trained with a large volume of data including cancer treatment protocols. The current study aimed to investigate the use of generative pretrained transformer 4 (GPT-4) for identifying the TNM classification of pancreatic cancers from existing radiology reports written in Japanese.

Materials and methods
We screened 100 consecutive radiology reports on computed tomography scan for pancreatic cancer from April 2020 to June 2022. GPT-4 was requested to classify the TNM from the radiology reports based on the General Rules for the Study of Pancreatic Cancer 7th Edition. The accuracy and kappa coefficient of the TNM classifications by GPT-4 was evaluated with the classifications by two experienced abdominal radiologists as gold standard.

Results
The accuracy values of the T, N, and M factors were 0.73, 0.91, and 0.93, respectively. The kappa coefficients were 0.45 for T, 0.79 for N, and 0.83 for M.

Conclusion
Although GPT is familiar with the TNM classification for pancreatic cancer, its performance in classifying actual cases in this experiment may not be adequate.
Convergence error analysis of reflected gradient Langevin dynamics for non-convex constrained optimization
Authors: Sato Kanji , Takeda Akiko , Kawai Reiichiro , Suzuki Taiji 
Published: August 2024

AbstractGradient Langevin dynamics and a variety of its variants have attracted increasing attention owing to their convergence towards the global optimal solution, initially in the unconstrained convex framework while recently even in convex constrained non-convex problems. In the present work, we extend those frameworks to non-convex problems on a non-convex feasible region with a global optimization algorithm built upon reflected gradient Langevin dynamics and derive its convergence rates. By effectively making use of its reflection at the boundary in combination with the probabilistic representation for the Poisson equation with the Neumann boundary condition, we present promising convergence rates, particularly faster than the existing one for convex constrained non-convex problems.
Two-component integrable extension of general heavenly equation
Authors: Kryński Wojciech , Sergyeyev Artur 
Published: August 2024

AbstractWe introduce an integrable two-component extension of the general heavenly equation and prove that the solutions of this extension are in one-to-one correspondence with 4-dimensional hyper-para-Hermitian metrics. Furthermore, we demonstrate that if the metrics in question are hyper-para-Kähler, then our system reduces to the general heavenly equation. We also present an infinite hierarchy of nonlocal symmetries, as well as a recursion operator, for the system under study.
Crossing the Trust Gap in Medical AI: Building an Abductive Bridge for xAI
Authors: Gouveia Steven S. , Malík Jaroslav 
Published: August 2024

AbstractIn this paper, we argue that one way to approach what is known in the literature as the “Trust Gap” in Medical AI is to focus on explanations from an Explainable AI (xAI) perspective. Against the current framework on xAI – which does not offer a real solution – we argue for a pragmatist turn, one that focuses on understanding how we provide explanations in Traditional Medicine (TM), composed by human agents only. Following this, explanations have two specific relevant components: they are usually (i) social and (ii) abductive. Explanations, in this sense, ought to provide understanding by answering contrastive why-questions: “Why had P happened instead of Q?” (Miller in AI 267:1–38, 2019) (Sect. 1). In order to test the relevancy of this concept of explanation in medical xAI, we offer several reasons to argue that abductions are crucial for medical reasoning and provide a crucial tool to deal with trust gaps between human agents (Sect. 2). If abductions are relevant in TM, we can test the capability of Artificial Intelligence systems on this merit. Therefore, we provide an analysis of the capacity for social and abductive reasoning of different AI technologies. Accordingly, we posit that Large Language Models (LLMs) and transformer architectures exhibit a noteworthy potential for effective engagement in abductive reasoning. By leveraging the potential abductive capabilities of LLMs and transformers, we anticipate a paradigm shift in the integration of explanations within AI systems. This, in turn, has the potential to enhance the trustworthiness of AI-driven medical decisions, bridging the Trust Gap that has been a prominent challenge in the field of Medical AI (Sect. 3). This development holds the potential to not only improve the interpretability of AI-generated medical insights but also to guarantee that trust among practitioners, patients, and stakeholders in the healthcare domain is still present.
Encircling the Liouvillian exceptional points: a brief review
Authors: Sun Konghao , Yi Wei 
Published: August 2024

AbstractExceptional points are the branch-point singularities of non-Hermitian Hamiltonians and have rich consequences in open-system dynamics. While the exceptional points and their critical phenomena are widely studied in the non-Hermitian settings without quantum jumps, they also emerge in open quantum systems depicted by the Lindblad master equations, wherein they are identified as the degeneracies in the Liouvillian eigenspectrum. These Liouvillian exceptional points often have distinct properties compared to their counterparts in non-Hermitian Hamiltonians, leading to fundamental modifications of the steady states or the steady-state-approaching dynamics. Since the Liouvillian exceptional points widely exist in quantum systems such as the atomic vapors, superconducting qubits, and ultracold ions and atoms, they have received increasing amount of attention of late. Here, we present a brief review on an important aspect of the dynamic consequence of Liouvillian exceptional points, namely the chiral state transfer induced by the parametric encircling the Liouvillian exceptional points. Our review focuses on the theoretical description and experimental observation of the phenomena in atomic systems that are experimentally accessible. We also discuss the ongoing effort to unveil the collective dynamic phenomena close to the Liouvillian exceptional points, as a consequence of the many-body effects therein. Formally, these phenomena are the quantum-many-body counterparts to those in classical open systems with nonlinearity, but hold intriguing new potentials for quantum applications.
Hospital management and challenges during COVID-19 outbreaks: lessons from a level 1 hospital in the southeast of Iran-case study
Authors: Esmaeilian Saeid , Mohajeri Elham , Hoseinyazdi Meisam , Ghorbani Mohammad , Rahmanipour Elham , Sarmast Kamran 
Published: August 2024

Abstract
Background
The COVID-19 pandemic has presented unparalleled challenges to hospitals globally, particularly those in resource-limited settings. This case study elucidates the experiences and lessons from managing a 40-bed public hospital in Rask, Iran, during the pandemic.

Methods
Data were gathered through focus group discussions with the management team and key informants, supplemented by document analysis. Thematic analysis was employed to discern key themes and subthemes related to the challenges encountered and solutions implemented by the hospital.

Results
The study underscores the necessity of a dynamic management team, effective external stakeholder communication, staff involvement in decision-making, and establishing connections with pre-hospital care units. It also emphasizes the need for adaptable protocols, comprehensive staff training, and infrastructure enhancements. Despite these strategies, the hospital grappled with unresolved issues such as inadequate disaster planning, ethical dilemmas, and poor inter-hospital coordination.

Conclusion
This case study offers insights into managing a small hospital in a resource-limited setting during a health crisis, highlighting the importance of effective leadership, staff support, infrastructural flexibility, and community engagement. The lessons gleaned can guide the development of context-specific strategies to bolster the resilience and preparedness of similar hospitals. Further research is warranted to assess the long-term impacts of the pandemic on these hospitals and to explore the perspectives of frontline staff, patients, and families for a more comprehensive understanding of effective hospital management during health disasters.
Selection tests work better than we think they do, and have for years
Authors: Foster Jeff L. , Steel Piers , Harms Peter D. , O’Neill Thomas A. , Wood Dustin 
Published: August 2024

AbstractWe can make better decisions when we have a better understanding of the different sources of variance that impact job performance ratings. A failure to do so cannot only lead to inaccurate conclusions when interpreting job performance ratings, but often misguided efforts aimed at improving our ability to explain and predict them. In this paper, we outline six recommendations relating to the interpretation of predictive validity coefficients and efforts aimed at predicting job performance ratings. The first three focus on the need to evaluate the effectiveness of selection instruments and systems based only on the variance they can possibly account for. When doing so, we find that it is not only possible to account for the majority of the variance in job performance ratings that most select systems can possibly predict, but that we’ve been able to account for this variance for years. Our last three recommendations focus on the need to incorporate components related to additional sources of variance in our predictive models. We conclude with a discussion of their implications for both research and practice.
Impacts of Sea‐Level Rise on Coastal Groundwater Table Simulated by an Earth System Model With a Land‐Ocean Coupling Scheme
Authors: Xu Donghui , Bisht Gautam , Feng Dongyu , Tan Zeli , Li Lingcheng , Qiu Han , Leung L. Ruby 
Published: August 2024

AbstractSea‐level rise (SLR) poses a severe threat to the coastal environment through seawater intrusion into freshwater aquifers. The rising groundwater table also exacerbates the risk of pluvial, fluvial, and groundwater flooding in coastal regions. However, current Earth system models (ESMs) commonly ignore the exchanges of water at the land‐ocean interface. To address this gap, we developed a novel land‐ocean hydrologic coupling scheme in a state‐of‐the‐science ESM, the Energy Exascale Earth System Model version 2 (E3SMv2). The new scheme includes the lateral exchange between seawater and groundwater and the vertical infiltration of seawater driven by the SLR‐induced inundation. Simulations were performed with the updated E3SMv2 for the global land‐ocean interface to assess the impacts of SLR on coastal groundwater under a high CO2 emission scenario. By the middle of this century, seawater infiltration on the inundated areas will be the dominant component in the land‐ocean coupling process, while the lateral subsurface flow exchange will be much smaller. The SLR‐induced seawater infiltration will raise the groundwater levels, enhance evapotranspiration, and increase runoff with distinct spatial patterns globally in the future. Although the coupling process is induced by SLR, we found topography and warming temperature have more control on the coupling impacts, probably due to the relatively modest magnitude of SLR during the selected future period. Overall, our study suggests significant groundwater and seawater exchange at the land‐ocean interface, which needs to be considered in ESMs.
Interaction Between Typhoon, Marine Heatwaves, and Internal Tides: Observational Insights From Ieodo Ocean Research Station in the Northern East China Sea
Authors: Saranya J. S. , Dasgupta Panini , Nam SungHyun 
Published: August 2024

AbstractTyphoons, fueled by warm sea surface waters, heighten concern as they increasingly interact with frequent Marine Heatwaves (MHWs) in a changing climate. Typhoon Hinnamnor (2022) weakened and re‐intensified as it approached the Korean Strait, interacting with an underlying MHW in the northern East China Sea (nECS). In‐situ observations and reanalysis products revealed a significant increase in latent heat loss from the nECS during the MHW period, contributing to the typhoon re‐intensification. Strong sea surface wind forcing with the typhoon enhanced vertical mixing and upwelling, resulting in a pronounced (0.90°C) sea surface cooling after the typhoon passage, facilitating MHW disappearance with reduced thermal stratification. During MHWs, increased background stratification increases temperature oscillations associated with semidiurnal internal tides. Furthermore, post‐typhoon changes in stratification weakened semidiurnal internal tides due to unfavorable conditions for generation from a nearby source. These findings highlight the importance of continuous time‐series observations to monitor interactions among climatic extremes.
Indian Ocean Dipole Variations During the Last Millennium in PMIP3 Simulations
Authors: Tejavath Charan Teja , Ashok Karumuri , Chakraborty Supriyo , Pentakota Sreenivas 
Published: August 2024

AbstractEarlier proxy‐observational studies, and a sole modeling study, suggest that the Indian Ocean Dipole (IOD), an important global climate driver, exhibited multi‐scale temporal variability during the Last Millennium (LM; CE 0851–1849, with relatively high number of strong positive IOD events during the Little Ice Age (LIA; CE 1550–1749), and strong negative IOD events during the Medieval Warm Period (MWP; CE 1000–1199). Using nine model simulations from the PMIP3, we study the IOD variability during the LM after due validation of the simulated current day (CE 1850–2005) IOD variability. Majority of the models simulate relatively higher number of positive IOD events during the MWP, and negative IOD events in the LIA, commensurate with simulated background conditions. However, higher number of strong positive IOD events are simulated relative to the negative IODs during the LIA, in agreement with proxy‐observations, apparently owing to increased coupled feedback during positive IODs.
A Constrained Spectral Approximation of Subgrid‐Scale Orography on Unstructured Grids
Authors: Chew Ray , Dolaptchiev Stamen , Wedel Maja‐Sophie , Achatz Ulrich 
Published: August 2024

AbstractThe representation of subgrid‐scale orography is a challenge in the physical parameterization of orographic gravity‐wave sources in weather forecasting. A significant hurdle is encoding as much physical information with as simple a representation as possible. Other issues include scale awareness, that is, the orographic representation has to change according to the grid cell size and usability on unstructured geodesic grids with non‐quadrilateral grid cells. This work introduces a novel spectral analysis method approximating a scale‐aware spectrum of subgrid‐scale orography on unstructured geodesic grids. The dimension of the physical orographic data is reduced by more than two orders of magnitude in its spectral representation. Simultaneously, the power of the approximated spectrum is close to the physical value. The method is based on well‐known least‐squares spectral analyses. However, it is robust to the choice of the free parameters, and tuning the algorithm is generally unnecessary. Numerical experiments involving an idealized setup show that this novel spectral analysis performs significantly better than a straightforward least‐squares spectral analysis in representing the physical energy of a spectrum. Studies involving real‐world topographic data are conducted, and reasonable error scores within ±10% error relative to the maximum physical quantity of interest are achieved across different grid sizes and background wind speeds. The deterministic behavior of the method is investigated along with its principal capabilities and potential biases, and it is shown that the error scores can be iteratively improved if an optimization target is known. Discussions on the method's limitations and broader applicability conclude this work.