bluuebunny/crossref_metadata_2025_split huggingface dataset:
Human Rights–Based Social Work and the Natural Environment: Time for New Perspectives
Authors: Stamm Ingo 
Published: January 2023

AbstractThe natural environment and sustainability play an increasingly important role in social work as a discipline and profession. This is often described as the ecosocial paradigm. Even though the paradigm shares important ethical foundations with human rights–based social work, the connection between both is rarely examined in social work scholarship. This article addresses the gap by asking the following questions: How is the ecosocial paradigm linked to the human rights discourse in social work? What is the environmental dimension of human rights, and what implications does it have for social work? How can a human rights–based social work encompass the environmental dimension? In response, the article argues for the integration of new environmental perspectives into human rights–based social work. First, it shows that social work needs to refocus on collective human rights, such as the right to a healthy environment, recently recognized by the United Nations. Regarding the rights of children and youth, good examples of social work advocacy can already be found. Second, research knowledge and practice within the ecosocial paradigm are valuable resources for human rights–based social work, mainly regarding environmental justice and the principle of sustainability. Ultimately, it is only possible to strive for the realization of human rights, social change, and an inclusive and sustainable future if the natural environment is integrated as a social work concern.
Characterization from Diesel and Renewable Fuel Engine Exhaust: Particulate Size/Mass Distributions and Optical Properties
Authors: Sharma Nikhil , Mitra Kalyan , Pezer Jelena , Pathak Ravikant , Sjöblom Jonas 
Published: January 2023

AbstractCombustion of fossil fuel produces emissions and is one of the major environmental problems leading to climate change. Diesel engines are highly efficient but produce particulate emissions. These particulate emissions are considered dangerous to human health because inhaling particulates may cause respiratory and heart disease. Substituting fossil diesel fuel with renewable diesel fuel and using diesel particulate filters is one possibility to meet stringent legislative requirements. With this motivation, the present experimental investigation aimed to evaluate the particle size distribution (PSD), optical properties of particulate matter (PM) emitted, and the outcome of using an after-treatment system comprising of a diesel particle filter (DPF). This investigation aimed to make a comparative analysis of particulate emission upstream and downstream of the DPF with and without ultraviolet (UV) light (405 nm and 781 nm wavelength) turned on/off. Experiments were performed at (a) engine idle with a torque of 6 Nm at 750 rpm, IMEP of 1.35 bar and power of 0.5 kW, (b) engine at part load with a torque of 32 Nm at 1200 rpm, IMEP of 8.5 bar and power of 4.5 kW. Diesel engine was operated on two fuels (a) Diesel and (b) EHR7. Results showed that as and when UV light was turned on, a distinct nucleation mode that dominated the number concentration for both test fuels were observed. Downstream of the filter had relatively higher AAE values which show the contribution to climate change. Present experimental research is important for renewable fuel industries, industrial innovation's future, and the exhaust gas after-treatment system (EATS) community. The results contribute to knowledge for occupational exposure, human health, and the environment.
What would qualify an artificial intelligence for moral standing?
Authors: Ladak Ali 
Published: January 2023

AbstractWhat criteria must an artificial intelligence (AI) satisfy to qualify for moral standing? My starting point is that sentient AIs should qualify for moral standing. But future AIs may have unusual combinations of cognitive capacities, such as a high level of cognitive sophistication without sentience. This raises the question of whether sentience is a necessary criterion for moral standing, or merely sufficient. After reviewing nine criteria that have been proposed in the literature, I suggest that there is a strong case for thinking that some non-sentient AIs, such as those that are conscious and have non-valenced preferences and goals, and those that are non-conscious and have sufficiently cognitively complex preferences and goals, should qualify for moral standing. After responding to some challenges, I tentatively argue that taking into account uncertainty about which criteria an entity must satisfy to qualify for moral standing, and strategic considerations such as how such decisions will affect humans and other sentient entities, further supports granting moral standing to some non-sentient AIs. I highlight three implications: that the issue of AI moral standing may be more important, in terms of scale and urgency, than if either sentience or consciousness is necessary; that researchers working on policies designed to be inclusive of sentient AIs should broaden their scope to include all AIs with morally relevant interests; and even those who think AIs cannot be sentient or conscious should take the issue seriously. However, much uncertainty about these considerations remains, making this an important topic for future research.
Effect of U-shape external wall on heat transfer coefficients and building performances
Authors: Srhayri Imane , Hafs Hajar , Bah Abdellah 
Published: January 2023

AbstractWe keep the focus in this paper on the heat transfer coefficients affecting the performance of building for different climatic zones of Morocco. In this respect, the building model is developed using COMSOL Multiphysics based on the convective and radiative equations. Furthermore, the U-shape of the south external wall of the building is modified and tested according to three scenarios (A 0.25 m, B 0.75 m, and C 1.25 m). The results showed a significant increase of radiative heat transfer coefficient (HTC) by 33% and 64.62% by increasing the U-shape from 0.25 to 0.75 m and from 0.75 m to 1.25 m respectively. In fact, the convective coefficient decreases progressively in the U-shape wall. Hence, a maximum reduction of total energy consumption is observed as well as the HTC decreases.
Using electron fluid models to analyze plasma thruster discharges
Authors: Ahedo Eduardo 
Published: January 2023

AbstractFluid models of the slow-dynamics of magnetized, weakly-collisional electrons lead to build computationally-affordable, long-time simulations of plasma discharges in Hall-effect and electrodeless plasma thrusters. This paper discusses the main assumptions and techniques used in 1D to 3D electron fluid models, and some examples illustrate their capabilities. Critical aspects of these fluid models are the expressions for the pressure tensor, the heat flux vector, the plasma-wall fluxes, and the high-frequency-averaged electron transport and heating caused by plasma waves, generated either by turbulence or external irradiation. The different orders of magnitude of the three scalar momentum equations characterize the electron anisotropic transport. Central points of the discussion are: the role of electron inertia, magnetically-aligned meshes versus Cartesian-type ones, the use of a thermalized potential and the infinite mobility limit, the existence of convective-type heat fluxes, and the modeling of the Debye sheath, and wall fluxes. Plasma plume models present their own peculiarities, related to anomalous parallel cooling and heat flux closures, the matching of finite plume domains with quiescent infinity, and solving fully collisionless expansions. Solutions of two 1D electron kinetic models are used to derive kinetically-consistent fluid models and compare them with more conventional ones.
Road Network Detection from Aerial Imagery of Urban Areas Using Deep ResUNet in Combination with the B-snake Algorithm
Authors: Munawar Hafiz Suliman , Hammad Ahmed W. A. , Waller S. Travis , Shahzad Danish , Islam Md. Rafiqul 
Published: January 2023

AbstractRoad network detection is critical to enhance disaster response and detecting a safe evacuation route. Due to expanding computational capacity, road extraction from aerial imagery has been investigated extensively in the literature, specifically in the last decade. Previous studies have mainly proposed methods based on pixel classification or image segmentation as road/non-road images, such as thresholding, edge-based segmentation, k-means clustering, histogram-based segmentation, etc. However, these methods have limitations of over-segmentation, sensitivity to noise, and distortion in images. This study considers the case study of Hawkesbury Nepean valley, NSW, Australia, which is prone to flood and has been selected for road network extraction. For road area extraction, the application of semantic segmentation along with residual learning and U-Net is suggested. Public road datasets were used for training and testing purposes. The study suggested a framework to train and test datasets with the application of the deep ResUnet architecture. Based on maximal similarity, the regions were merged, and the road network was extracted with the B-snake algorithm application. The proposed framework (baseline + region merging + B-snake) improved performance when evaluated on the synthetically modified dataset. It was evident that in comparison with the baseline, region merging and addition of the B-snake algorithm improved significantly, achieving a value of 0.92 for precision and 0.897 for recall.
Ion Acceleration at the Quasi‐Parallel Shock: The Source Distributions of the Diffuse Ions
Authors: Trattner K. J. , Fuselier S. A. , Schwartz S. J. , Kucharek H. , Burch J. L. , Ergun R. E. , Petrinec S. M. , Madanian H. 
Published: January 2023

AbstractThe terrestrial bow shock is the boundary that slows and diverts the supermagnetosonic solar wind around the terrestrial magnetosphere by converting the kinetic energy of the solar wind into thermal and magnetic energy. Shock fronts are an important acceleration site for ions and electrons in collisionless plasmas, and are responsible for much of the particle acceleration in solar, planetary, and astrophysical regions. One of the fundamental outstanding questions of ion acceleration at shocks for which the upstream magnetic field is nearly aligned with the shock normal (i.e., quasi‐parallel shocks) is which portion of the incoming solar wind ion distribution ultimately becomes the seed population that is subsequently accelerated to high energies. This study discusses distribution functions of protons and alpha particles observed by the HPCA and FPI instruments onboard the MMS satellites during a crossing of the quasi‐parallel bow shock. The bow shock transition from the downstream region into the upstream solar wind shows the occasional presence of reflected ions and a population of 90° pitch angle ions in the shock ramp consistent with shock drift accelerated ions. Both populations contribute to the seed population of the shock accelerated ions known as the diffuse ion population.
An Adaptive Auto‐Reduction Solver for Speeding Up Integration of Chemical Kinetics in Atmospheric Chemistry Models: Implementation and Evaluation in the Kinetic Pre‐Processor (KPP) Version 3.0.0
Authors: Lin Haipeng , Long Michael S. , Sander Rolf , Sandu Adrian , Yantosca Robert M. , Estrada Lucas A. , Shen Lu , Jacob Daniel J. 
Published: January 2023

AbstractKinetic integration of large and stiff chemical mechanisms is a computational bottleneck in models of atmospheric chemistry. It requires implicit solution of the coupled system of kinetic differential equations with time‐consuming construction and inversion of the Jacobian matrix. We present here a new version of the Kinetic Pre‐Processor (KPP 3.0.0) for fast integration of chemical kinetics featuring a range of improvements over previous versions in performance, diagnostics, versatility, and community openness. KPP 3.0.0 includes a new adaptive auto‐reduction solver to decrease the size of any mechanism locally and on the fly under conditions where full complexity is not needed, by partitioning species as “fast” or “slow” based on their local production and loss rates. Previous implementations of this adaptive solver suffered from excessive overhead in the repeated construction of the local Jacobian matrix or were hard‐wired to specific mechanisms. Here we retain the general applicability of the method to any mechanism and avoid overhead by using pre‐computed Jacobian matrix terms for the full mechanism and cropping the matrix locally to remove the slow species with no change in memory allocation. We apply this adaptive solver within KPP 3.0.0 to the GEOS‐Chem global 3‐D model of atmospheric chemistry and demonstrate a 32% reduction in solver time while maintaining a mean error lower than 1% for key species in the troposphere.
Characterization of circSCL38A1 as a novel oncogene in bladder cancer via targeting ILF3/TGF-β2 signaling axis
Authors: Li Peilong , Mi Qi , Yan Suzhen , Xie Yan , Cui Zilian , Zhang Shujun , Wang Yifan , Gao Huiru , Wang Yunshan , Li Juan , Du Lutao , Wang Chuanxin 
Published: January 2023

AbstractThe regulatory role of circRNAs in cancer metastasis has become a focused issue in recent years. To date, however, the discovery of novel functional circRNAs and their regulatory mechanisms via binding with RBPs in bladder cancer (BC) are still lacking. Here, we screened out circSLC38A1 based on our sequencing data and followed validation with clinical tissue samples and cell lines. Functional assays showed that circSLC38A1 promoted BC cell invasion in vitro and lung metastasis of mice in vivo. By conducting RNA pull-down, mass spectrum, and RIP assays, circSLC38A1 was found to interact with Interleukin enhancer-binding factor 3 (ILF3), and stabilize ILF3 protein via modulating the ubiquitination process. By integrating our CUT&Tag-seq and RNA-seq data, TGF-β2 was identified as the functional target of the circSLC38A1-ILF3 complex. In addition, m6A methylation was enriched in circSLC38A1 and contributed to its upregulation. Clinically, circSLC38A1 was identified in serum exosomes of BC patients and could distinguish BC patients from healthy individuals with a diagnostic accuracy of 0.878. Thus, our study revealed an essential role and clinical significance of circSLC38A1 in BC via activating the transcription of TGF-β2 in an ILF3-dependent manner, extending the understanding of the importance of circRNA-mediated transcriptional regulation in BC metastasis.
Optogenetic frequency scrambling of hippocampal theta oscillations dissociates working memory retrieval from hippocampal spatiotemporal codes
Authors: Etter Guillaume , van der Veldt Suzanne , Choi Jisoo , Williams Sylvain 
Published: January 2023

AbstractThe precise temporal coordination of activity in the brain is thought to be fundamental for memory function. Inhibitory neurons in the medial septum provide a prominent source of innervation to the hippocampus and play a major role in controlling hippocampal theta (~8 Hz) oscillations. While pharmacological inhibition of medial septal neurons is known to disrupt memory, the exact role of septal inhibitory neurons in regulating hippocampal representations and memory is not fully understood. Here, we dissociate the role of theta rhythms in spatiotemporal coding and memory using an all-optical interrogation and recording approach. We find that optogenetic frequency scrambling stimulations abolish theta oscillations and modulate a portion of neurons in the hippocampus. Such stimulation decreased episodic and working memory retrieval while leaving hippocampal spatiotemporal codes intact. Our study suggests that theta rhythms play an essential role in memory but may not be necessary for hippocampal spatiotemporal codes.
Topological identification and interpretation for single-cell gene regulation elucidation across multiple platforms using scMGCA
Authors: Yu Zhuohan , Su Yanchi , Lu Yifu , Yang Yuning , Wang Fuzhou , Zhang Shixiong , Chang Yi , Wong Ka-Chun , Li Xiangtao 
Published: January 2023

AbstractSingle-cell RNA sequencing provides high-throughput gene expression information to explore cellular heterogeneity at the individual cell level. A major challenge in characterizing high-throughput gene expression data arises from challenges related to dimensionality, and the prevalence of dropout events. To address these concerns, we develop a deep graph learning method, scMGCA, for single-cell data analysis. scMGCA is based on a graph-embedding autoencoder that simultaneously learns cell-cell topology representation and cluster assignments. We show that scMGCA is accurate and effective for cell segregation and batch effect correction, outperforming other state-of-the-art models across multiple platforms. In addition, we perform genomic interpretation on the key compressed transcriptomic space of the graph-embedding autoencoder to demonstrate the underlying gene regulation mechanism. We demonstrate that in a pancreatic ductal adenocarcinoma dataset, scMGCA successfully provides annotations on the specific cell types and reveals differential gene expression levels across multiple tumor-associated and cell signalling pathways.
Polyamine metabolism impacts T cell dysfunction in the oral mucosa of people living with HIV
Authors: Mahalingam S. S. , Jayaraman S. , Bhaskaran N. , Schneider E. , Faddoul F. , Paes da Silva A. , Lederman M. M. , Asaad R. , Adkins-Travis K. , Shriver L. P. , Pandiyan P. 
Published: January 2023

AbstractMetabolic changes in immune cells contribute to both physiological and pathophysiological outcomes of immune reactions. Here, by comparing protein expression, transcriptome, and salivary metabolome profiles of uninfected and HIV+ individuals, we found perturbations of polyamine metabolism in the oral mucosa of HIV+ patients. Mechanistic studies using an in vitro human tonsil organoid infection model revealed that HIV infection of T cells also resulted in increased polyamine synthesis, which was dependent on the activities of caspase-1, IL-1β, and ornithine decarboxylase-1. HIV-1 also led to a heightened expression of polyamine synthesis intermediates including ornithine decarboxylase-1 as well as an elevated dysfunctional regulatory T cell (TregDys)/T helper 17 (Th17) cell ratios. Blockade of caspase-1 and polyamine synthesis intermediates reversed the TregDys phenotype showing the direct role of polyamine pathway in altering T cell functions during HIV-1 infection. Lastly, oral mucosal TregDys/Th17 ratios and CD4 hyperactivation positively correlated with salivary putrescine levels, which were found to be elevated in the saliva of HIV+ patients. Thus, by revealing the role of aberrantly increased polyamine synthesis during HIV infection, our study unveils a mechanism by which chronic viral infections could drive distinct T cell effector programs and Treg dysfunction.
A wearable cardiac ultrasound imager
Authors: Hu Hongjie , Huang Hao , Li Mohan , Gao Xiaoxiang , Yin Lu , Qi Ruixiang , Wu Ray S. , Chen Xiangjun , Ma Yuxiang , Shi Keren , Li Chenghai , Maus Timothy M. , Huang Brady , Lu Chengchangfeng , Lin Muyang , Zhou Sai , Lou Zhiyuan , Gu Yue , Chen Yimu , Lei Yusheng , Wang Xinyu , Wang Ruotao , Yue Wentong , Yang Xinyi , Bian Yizhou , Mu Jing , Park Geonho , Xiang Shu , Cai Shengqiang , Corey Paul W. , Wang Joseph , Xu Sheng 
Published: January 2023

AbstractContinuous imaging of cardiac functions is highly desirable for the assessment of long-term cardiovascular health, detection of acute cardiac dysfunction and clinical management of critically ill or surgical patients1–4. However, conventional non-invasive approaches to image the cardiac function cannot provide continuous measurements owing to device bulkiness5–11, and existing wearable cardiac devices can only capture signals on the skin12–16. Here we report a wearable ultrasonic device for continuous, real-time and direct cardiac function assessment. We introduce innovations in device design and material fabrication that improve the mechanical coupling between the device and human skin, allowing the left ventricle to be examined from different views during motion. We also develop a deep learning model that automatically extracts the left ventricular volume from the continuous image recording, yielding waveforms of key cardiac performance indices such as stroke volume, cardiac output and ejection fraction. This technology enables dynamic wearable monitoring of cardiac performance with substantially improved accuracy in various environments.
Mitochondrial complexome reveals quality-control pathways of protein import
Authors: Schulte Uwe , den Brave Fabian , Haupt Alexander , Gupta Arushi , Song Jiyao , Müller Catrin S. , Engelke Jeannine , Mishra Swadha , Mårtensson Christoph , Ellenrieder Lars , Priesnitz Chantal , Straub Sebastian P. , Doan Kim Nguyen , Kulawiak Bogusz , Bildl Wolfgang , Rampelt Heike , Wiedemann Nils , Pfanner Nikolaus , Fakler Bernd , Becker Thomas 
Published: January 2023

AbstractMitochondria have crucial roles in cellular energetics, metabolism, signalling and quality control1–4. They contain around 1,000 different proteins that often assemble into complexes and supercomplexes such as respiratory complexes and preprotein translocases1,3–7. The composition of the mitochondrial proteome has been characterized1,3,5,6; however, the organization of mitochondrial proteins into stable and dynamic assemblies is poorly understood for major parts of the proteome1,4,7. Here we report quantitative mapping of mitochondrial protein assemblies using high-resolution complexome profiling of more than 90% of the yeast mitochondrial proteome, termed MitCOM. An analysis of the MitCOM dataset resolves >5,200 protein peaks with an average of six peaks per protein and demonstrates a notable complexity of mitochondrial protein assemblies with distinct appearance for respiration, metabolism, biogenesis, dynamics, regulation and redox processes. We detect interactors of the mitochondrial receptor for cytosolic ribosomes, of prohibitin scaffolds and of respiratory complexes. The identification of quality-control factors operating at the mitochondrial protein entry gate reveals pathways for preprotein ubiquitylation, deubiquitylation and degradation. Interactions between the peptidyl-tRNA hydrolase Pth2 and the entry gate led to the elucidation of a constitutive pathway for the removal of preproteins. The MitCOM dataset—which is accessible through an interactive profile viewer—is a comprehensive resource for the identification, organization and interaction of mitochondrial machineries and pathways.
Heteroleptic Ir(III)-based near-infrared organic light-emitting diodes with high radiance capacity
Authors: Park Yongjin , Lee Gyeong Seok , Lee Woochan , Yoo Seunghyup , Kim Yun-Hi , Choi Kyung-Cheol 
Published: January 2023

AbstractNear-infrared organic light-emitting diodes (NIR OLEDs) with heavy metals are regularly reported due to the advantages of their various applications in healthcare services, veil authentication, and night vision displays. For commercial applications, it is necessary to look at radiance capacity (RC) instead of radiance because of power consumption. However, recent papers still reported only simple high radiance performance and do not look at device from the point of view of RC. To overcome this hurdle, we designed Ir(III)-based heteroleptic NIR materials with two types of auxiliary ligand. The proposed emitters achieve a highly oriented horizontal dipole ratio (Ir(mCPDTiq)2tmd, complex1: 80%, Ir(mCPDTiq)2acac, complex2: 81%) with a short radiative lifetime (1: 386 ns,2: 323 ns). The device also shows an extremely low turn-on voltage (Von) of 2.2 V and a high RC of 720 mW/sr/m2/V. The results on the Vonand RC of the device is demonstrated an outstanding performance among the Ir(III)-based NIR OLEDs with a similar emission peak.