bluuebunny/crossref_metadata_2025_split huggingface dataset:
IASCAR: Incremental Answer Set Counting by Anytime Refinement
Authors: FICHTE JOHANNES K. , GAGGL SARAH ALICE , HECHER MARKUS , RUSOVAC DOMINIK 
Published: February 2024

AbstractAnswer set programming (ASP) is a popular declarative programming paradigm with various applications. Programs can easily have many answer sets that cannot be enumerated in practice, but counting still allows quantifying solution spaces. If one counts under assumptions on literals, one obtains a tool to comprehend parts of the solution space, so-called answer set navigation. However, navigating through parts of the solution space requires counting many times, which is expensive in theory. Knowledge compilation compiles instances into representations on which counting works in polynomial time. However, these techniques exist only for conjunctive normal form (CNF) formulas, and compiling ASP programs into CNF formulas can introduce an exponential overhead. This paper introduces a technique to iteratively count answer sets under assumptions on knowledge compilations of CNFs that encode supported models. Our anytime technique uses the inclusion–exclusion principle to improve bounds by over- and undercounting systematically. In a preliminary empirical analysis, we demonstrate promising results. After compiling the input (offline phase), our approach quickly (re)counts.
‘Working With the Whole Person’: Employability Keyworker Experiences of Supporting People Furthest From the Labour Market
Authors: Irvine Annie , McKenzie Joe , Brass Christine , Kelley Alex 
Published: February 2024

Abstract
This article explores the experiences of keyworkers within a third-sector employability programme targeted at people furthest from work. Using semi-structured qualitative interviews, the study investigated keyworker perspectives on effective elements of programme design, and what made the critical difference for those who did move into employment. Echoing previous research, findings confirmed the value of a holistic and personalised approach founded upon a consistent and long-term relationship of trust and support, through which programme participants developed the confidence and self-belief that was critical to progression towards employment. However, critical attention to the keyworker perspective offers novel insights, bringing to light challenges in defining role parameters and maintaining personal-professional boundaries in the interests of keyworkers and programme participants. We contribute to the body of research on employability practitioner perspectives, revealing that the strengths of person-centred support may simultaneously present tensions and wellbeing risks, where role parameters are very broadly defined.
Optimizing geriatric palliative care in Egypt: Comprehensive patient and family perspectives
Authors: Ibrahim Ateya Megahed , Zaghamir Donia Elsaid Fathi , Sultan Sultan Hosny Maher , Ibrahim Fatma Magdi , Abdel-Aziz Hassanat Ramadan 
Published: February 2024

AbstractObjectivesIn Egypt, palliative care for geriatric patients is understudied, necessitating exploration for service optimization. Amidst rising chronic illnesses and aging, understanding perspectives of geriatric patients and families is crucial for targeted improvements. This study aims to explore geriatric patients’ and their families’ perspectives on palliative care in Egypt, seeking opportunities to optimize service delivery for the elderly.MethodsEmploying a cross-sectional design with 110 geriatric patients and an equal number of family caregivers from the Damietta Oncology Institute and the pain treatment clinics for cancer patients at Zagazig University Hospital, the study focuses on a specialized pain clinic. Validated tools (Palliative Care Outcome Scale, Family Satisfaction with End-of-Life Care [FAMCARE] Scale, Edmonton Symptom Assessment System [ESAS], Caregiver Strain Index [CSI]) assess quality of life, family satisfaction, symptom severity, and caregiver strain.ResultsGeriatric patients (mean age: 65.0 ± 8.1 years; 45.5% male, 55.5% female) have diverse diagnoses (e.g., breast cancer 22%). Palliative care outcomes reveal challenges: low emotional well-being (2.6 ± 0.0) and alarming overall quality of life (1.8 ± 0.0). Family dissatisfaction (FAMCARE) is pervasive (total mean score 2.6 ± 0.5). Symptom severity (ESAS) is high, and caregiver strain (CSI) is notable (8.5 ± 2.2).Significance of the resultsThe findings underscore the significance of the challenges faced by geriatric patients and caregivers in palliative care. Patients confront considerable symptom burdens and emotional distress, while caregivers experience notable strain. Urgently needed are targeted interventions designed to enhance patient well-being, alleviate caregiver burden, and elevate satisfaction. The critical importance of implementing these interventions promptly is highlighted, as they are instrumental in improving the overall care experience for geriatric patients and their caregivers. Moreover, the results underscore the imperative of developing comprehensive support mechanisms to address the intricate dimensions of palliative care, ultimately contributing to a more compassionate and effective care continuum.
Unveiling the Global Extent of Land Subsidence: The Sinking Crisis
Authors: Davydzenka Tsimur , Tahmasebi Pejman , Shokri Nima 
Published: February 2024

AbstractLand subsidence, referring to the vertical sinking of land surface, is a significant geohazard posing serious risks to security of infrastructure, natural resources, built environment, and businesses in numerous places worldwide. Using deep learning approaches combined with more than 46,000 subsidence data, we predicted global land subsidence based on 23 environmental parameters. The generated global map of land subsidence covers historically documented and new subsiding areas. We estimate that more than 6.3 million square kilometers of the global land is influenced by significant subsidence rates. That includes 231,000 square kilometers of urban and dense settlement areas and a population of nearly 2 billion. The model revealed a positive correlation between the intensity of groundwater abstraction and the subsidence rate. Our results offer new insights regarding potential hotspots of land subsidence and provide the information required to devise necessary action plans and develop effective policies to mitigate this growing challenge worldwide.
The Effect of Intracrystalline Water on the Mechanical Properties of Olivine at Room Temperature
Authors: Kumamoto Kathryn M. , Hansen Lars N. , Breithaupt Thomas , Wallis David , Li Bo‐Shiuan , Armstrong David E. J. , Goldsby David L. , Li Yang (Will) , Warren Jessica M. , Wilkinson Angus J. 
Published: February 2024

AbstractThe effect of small concentrations of intracrystalline water on the strength of olivine is significant at asthenospheric temperatures but is poorly constrained at lower temperatures applicable to the shallow lithosphere. We examined the effect of water on the yield stress of olivine during low‐temperature plasticity using room‐temperature Berkovich nanoindentation. The presence of water in olivine (1,600 ppm H/Si) does not affect hardness or yield stress relative to dry olivine (≤40 ppm H/Si) outside of uncertainty but may slightly reduce Young’s modulus. Differences between water‐bearing and dry crystals in similar orientations were minor compared to differences between dry crystals in different orientations. These observations suggest water content does not affect the strength of olivine at low homologous temperatures. Thus, intracrystalline water does not play a role in olivine deformation at these temperatures, implying that water does not lead to weakening in the coldest portions of the mantle.
Paleoproterozoic Reworking of Archean Crust and Extreme Back‐Arc Metamorphism in the Enigmatic Southern Trans‐Hudson Orogen
Authors: Hillenbrand Ian W. , Gilmer Amy K. , Williams Michael L. , Souders A. Kate , Jercinovic Michael J. , Lowers Heather A. , Vazquez Jorge A. 
Published: February 2024

AbstractThe crustal evolution of the southernmost ∼2000–1800 Ma Trans‐Hudson orogen (THO) is enigmatic due to burial by Phanerozoic sediments. We provide new insights through petrochronologic analysis of a paragneiss drill core sample. Detrital zircon age peaks at 2625, 2340, and 1880 Ma and Hf isotopes suggest Paleoproterozoic arc development proximal to Archean source(s). Phase equilibria modeling and ternary feldspar thermometry suggest peak conditions of ≥1 GPa, ≥900°C, the first recognition of extreme, ultra‐high temperature metamorphism in the THO. The largely isobaric P‐T path, rapid heating rate, and ∼20 Myr duration (1872–1850 Ma) of peak conditions suggest that this metamorphism occurred in a back‐arc tectonic setting. The sample records post‐peak (1850–1815 Ma) mid‐crustal residence, slow cooling, and exhumation. Further retrogression occurred during Proterozoic regional exhumation (1630–1470 Ma) and Phanerozoic (360–220 Ma) reheating and/or fluid influx. Evidence for Paleoproterozoic arc(s) supports geophysical data for Archean cratonic and Paleoproterozoic arc crust in this region.
Aerosol Deposition and Snow Accumulation Processes From Beryllium‐7 Measurements in the Central Arctic Ocean: Results From the MOSAiC Expedition
Authors: Stephens Mark P. , Marsay Chris M. , Schneebeli Martin , Landing William M. , Buck Clifton S. , Geibert Walter 
Published: February 2024

AbstractWe use a tracer method involving the cosmogenic radioisotope beryllium‐7 (half‐life = 53.3 days) to follow the deposition of aerosols and the fate of snow on the MOSAiC ice floe during winter and spring 2019–2020. When examined alongside data from earlier studies in the Arctic Ocean that covered summer and fall, Be‐7 inventories indicate a summertime peak for aerosol Be‐7 deposition fluxes coinciding with seasonal minima boundary‐level aerosol concentrations, which suggests that deposition fluxes are primarily controlled by precipitation. This conclusion is supported by the linear relationship between Be‐7 fluxes and precipitation rates derived from data from the MOSAiC and SHEBA expeditions. Inventories of Be‐7 within the snow column exhibited evidence of significant redistribution. Be‐7 deficits, relative to the flux, were observed in areas of level sea ice while excess Be‐7 was found associated with deformed ice features such as pressure ridges, leading to the following estimates for the distribution of snow on the ice floe in May 2020: 75–93% of the snow mass is found on deformed sea ice with the remainder on level ice. Furthermore, uncertainties associated with measurements of Be‐7 concentrations within the ocean mixed layer would allow for losses of snow through open leads of up to approximately 20% of the flux. Our snow distribution estimates agree with data from repeat snow depth transect measurements. These results suggest that Be‐7 can be a useful tool in studying snow redistribution.
Elucidating Dissolved Organic Sulfur in the Coastal Environment by Improved Online Liquid Chromatography Coupled to FT‐ICR Mass Spectrometry
Authors: Chen Shuang , Qi Yulin , Xie Qiaorong , Ma Chao , Zhong Shujun , Wu Libin , Fu Pingqing 
Published: February 2024

AbstractDissolved organic sulfur (DOS) is an important component of dissolved organic matter (DOM) and widely exists at the land‐atmosphere interface. However, the characterization of DOS at the molecular level among different environmental samples in coastal regions has not been sufficiently focused. Here, we investigated DOS in aerosol, rainwater, and river water samples in Shanghai using an improved method–online liquid chromatography coupled to Fourier transform ion cyclotron resonance mass spectrometry (LC‐FT‐ICR MS). This system is utilized to separate DOS from complicated environmental matrices. The results showed that the average relative abundance of DOS in three different environmental media (aerosol, rainwater, and river water samples) accounted for 16.8%, 21.9% and 13.1%, respectively. The common molecules of the three mediums in coastal Shanghai contain an abundance of aromatic and aliphatic DOS of anthropogenic origin in addition to the natural sources of sea spray. Notably, results from a new structural classification scheme for DOS demonstrate that anthropogenic sulfonates and their derivatives are widely spread, although their molecular diversity in different medium was recorded due to complex environmental conditions and diverse sources.
Revealing the Influencing Factors of an Oxygenated Volatile Organic Compounds (OVOCs) Source Apportionment Model: A Case Study of a Dense Urban Agglomeration in the Winter
Authors: Zou Y. , Guan X. H. , Flores R. M. , Yan X. L. , Fan L. Y. , Deng T. , Deng X. J. , Ye D. Q. 
Published: February 2024

AbstractUnderstanding sources of oxygenated volatile organic compounds (OVOCs) in the atmosphere still has large uncertainties. In this study, an improved OVOC source apportionment model was developed by principal component analysis and multiple linear regression based on the online monitoring of nonmethane hydrocarbons (NMHCs) and OVOCs in a dense urban agglomeration in the winter. The modeled concentrations were in good agreement with the measured concentrations (R2 = 0.56–0.97). The concentrations of major OVOCs, except for 2‐methylacrolein, were greatly affected by anthropogenic sources (15.8%–76.8%) and secondary generation (0.0%–51.7%), while transport and natural sources contributed to 0.0%–26.8% and 0.0%–32.0%, respectively. The selection of isoprene as the natural tracer led to an underestimation of the OVOC species from primary emission and an overestimation from natural sources. In addition, photochemical reactions significantly reduced the simulation accuracy of the model for NMHCs in the afternoon, with the R2 of 0.60 ± 0.23, which was lower than the overall value of 0.82 ± 0.11. However, the R2 for OVOCs (0.83 ± 0.14) did not decrease significantly in the afternoon due to the compensation of secondary oxidation. Furthermore, the concentration gradient distribution of the species gradually changes from a normal distribution to an exponential normal distribution with a decrease in concentration, the accuracy of the model was influenced by the degree of matching between tracer and species concentration gradient as species concentration change. Developing models with additional tracers at different concentration levels may enhance the robustness of the OVOC source apportionment model without increasing its complexity.
Modeling the Flow and Geomorphic Heterogeneity Induced by Salt Marsh Vegetation Patches Based on Convolutional Neural Network UNet‐Flow
Authors: Chen Zhipeng , Luo Feng , Li Ruijie , Zhang Chi 
Published: February 2024

AbstractThe two‐way interactions between biological and physical processes, bio‐geomorphic feedback, play a vital role in landscape formation and evolution in salt marshes. Patchy vegetation represents a typical form of scale‐dependent feedback in salt marshes and is primarily responsible for the formation of efficient drainage networks. The intuitive manifestation of scale‐dependent feedback is the heterogeneity of flow and landscape. Process‐based modeling is an essential tool for exploring flow heterogeneity, but calculations for small spatial scales and over long time frames can be prohibitively costly. In this study, we proposed a deep learning model architecture, UNet‐Flow, based on convolutional neural networks (CNNs), which is used to build a surrogate model to simulate a flow field induced by salt marsh patchy vegetation. After optimizing and evaluating the model, we discovered that UNet‐Flow exhibits a speed improvement of over four orders of magnitude compared to single‐process simulations using the free surface flow model TELEMAC‐2D, with acceptable levels of error. Furthermore, we proposed an approach that combines the process‐based model SISYPHE with the deep learning method to model geomorphic heterogeneity. After numerous simulations of flow heterogeneity modeling using UNet‐Flow, we obtained a significant logarithmic relationship between scale‐dependent feedback strength and vegetation stem density, and an ascending‐descending trend in feedback strength was observed as the number or surface area of vegetation patches increased. Finally, we investigated the relationship between geomorphic heterogeneity and vegetation‐related variables. This study represents a noteworthy effort to study bio‐geomorphology using deep learning methods.
Regional Low Flow Hydrology: Model Development and Evaluation
Authors: Chagas Vinícius B. P. , Chaffe Pedro L. B. , Blöschl Günter 
Published: February 2024

AbstractLow flows result from the interplay of climatic variability and catchment storage dynamics, but it is unclear which of these variables is more relevant for explaining low flow spatial patterns. Here, we develop a new conceptual model that integrates process‐based hydrological knowledge with statistics and test it for 1,400 Brazilian catchments. Through comparative hydrology, we isolate the low flow generating mechanisms and estimate their components using linear model trees. The model explains 58% of the spatial variance in 7‐day minimum annual flows (Qmin) based on climate and catchment characteristics. The primary Qmin controls depend on the spatial scale of analysis. Catchment characteristics govern Qmin up to the continental scale (107 km2), where their relative importance matches that of climate. At subcontinental scales, catchment characteristics are twice as important as climate in predicting Qmin, suggesting that low flows are governed by the catchment's capacity to attenuate the climatic variability through water storage. Geological properties are the most important catchment characteristics, particularly bedrock type, lithology and topographic slope, determining streamflow recession rates in the dry season. Soil properties, primarily soil class and depth, are half as important as geology. Climate impacts Qmin mainly through mean annual rainfall minus evaporation, representing the potential groundwater recharge, while dry‐season length has the lowest impact. These results hold mainly for highly seasonal and snow‐free climates. Low flow hydrology that combines statistics with process understanding offers a promising framework for understanding regional low flow generating mechanisms and could support other estimation models than that presented here.
Nanotechnology’s frontier in combatting infectious and inflammatory diseases: prevention and treatment
Authors: Huang Yujing , Guo Xiaohan , Wu Yi , Chen Xingyu , Feng Lixiang , Xie Na , Shen Guobo 
Published: February 2024

AbstractInflammation-associated diseases encompass a range of infectious diseases and non-infectious inflammatory diseases, which continuously pose one of the most serious threats to human health, attributed to factors such as the emergence of new pathogens, increasing drug resistance, changes in living environments and lifestyles, and the aging population. Despite rapid advancements in mechanistic research and drug development for these diseases, current treatments often have limited efficacy and notable side effects, necessitating the development of more effective and targeted anti-inflammatory therapies. In recent years, the rapid development of nanotechnology has provided crucial technological support for the prevention, treatment, and detection of inflammation-associated diseases. Various types of nanoparticles (NPs) play significant roles, serving as vaccine vehicles to enhance immunogenicity and as drug carriers to improve targeting and bioavailability. NPs can also directly combat pathogens and inflammation. In addition, nanotechnology has facilitated the development of biosensors for pathogen detection and imaging techniques for inflammatory diseases. This review categorizes and characterizes different types of NPs, summarizes their applications in the prevention, treatment, and detection of infectious and inflammatory diseases. It also discusses the challenges associated with clinical translation in this field and explores the latest developments and prospects. In conclusion, nanotechnology opens up new possibilities for the comprehensive management of infectious and inflammatory diseases.
CD4+ T cells produce IFN-I to license cDC1s for induction of cytotoxic T-cell activity in human tumors
Authors: Lei Xin , de Groot Daniël C. , Welters Marij J. P. , de Wit Tom , Schrama Ellen , van Eenennaam Hans , Santegoets Saskia J. , Oosenbrug Timo , van der Veen Annemarthe , Vos Joris L. , Zuur Charlotte L. , de Miranda Noel F. C. C. , Jacobs Heinz , van der Burg Sjoerd H. , Borst Jannie , Xiao Yanling 
Published: February 2024

AbstractCD4+ T cells can "help” or "license” conventional type 1 dendritic cells (cDC1s) to induce CD8+ cytotoxic T lymphocyte (CTL) anticancer responses, as proven in mouse models. We recently identified cDC1s with a transcriptomic imprint of CD4+ T-cell help, specifically in T-cell-infiltrated human cancers, and these cells were associated with a good prognosis and response to PD-1-targeting immunotherapy. Here, we delineate the mechanism of cDC1 licensing by CD4+ T cells in humans. Activated CD4+ T cells produce IFNβ via the STING pathway, which promotes MHC-I antigen (cross-)presentation by cDC1s and thereby improves their ability to induce CTL anticancer responses. In cooperation with CD40 ligand (L), IFNβ also optimizes the costimulatory and other functions of cDC1s required for CTL response induction. IFN-I-producing CD4+ T cells are present in diverse T-cell-infiltrated cancers and likely deliver “help” signals to CTLs locally, according to their transcriptomic profile and colocalization with “helped/licensed” cDCs and tumor-reactive CD8+ T cells. In agreement with this scenario, the presence of IFN-I-producing CD4+ T cells in the TME is associated with overall survival and the response to PD-1 checkpoint blockade in cancer patients.
Multi-molecular hyperspectral PRM-SRS microscopy
Authors: Zhang Wenxu , Li Yajuan , Fung Anthony A. , Li Zhi , Jang Hongje , Zha Honghao , Chen Xiaoping , Gao Fangyuan , Wu Jane Y. , Sheng Huaxin , Yao Junjie , Skowronska-Krawczyk Dorota , Jain Sanjay , Shi Lingyan 
Published: February 2024

AbstractLipids play crucial roles in many biological processes. Mapping spatial distributions and examining the metabolic dynamics of different lipid subtypes in cells and tissues are critical to better understanding their roles in aging and diseases. Commonly used imaging methods (such as mass spectrometry-based, fluorescence labeling, conventional optical imaging) can disrupt the native environment of cells/tissues, have limited spatial or spectral resolution, or cannot distinguish different lipid subtypes. Here we present a hyperspectral imaging platform that integrates a Penalized Reference Matching algorithm with Stimulated Raman Scattering (PRM-SRS) microscopy. Using this platform, we visualize and identify high density lipoprotein particles in human kidney, a high cholesterol to phosphatidylethanolamine ratio inside granule cells of mouse hippocampus, and subcellular distributions of sphingosine and cardiolipin in human brain. Our PRM-SRS displays unique advantages of enhanced chemical specificity, subcellular resolution, and fast data processing in distinguishing lipid subtypes in different organs and species.