Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of aerosol particle number size distribution and source attribution at three megacities in China

• Particle sources were identified and quantified in three Chinese megacities by K-means clustering. • Frequent Nocturnal Nucleation Events have been observed in Beijing and Guangzhou. • Traffic emissions were the main contributor in Beijing and Guangzhou. quantified the pollution contributions from different sources by applying the k-means clustering analysis to observational datasets of environmental quantities. Clustering results showed that traffic emissions were the main contributor in Beijing and Guangzhou, with direct and significant impacts ranging from 37% to 45%, respectively.
Experimental Brain Death Models in Liver Transplantation Experimental Brain Death Models in Liver Transplantation

Most organs for transplantation are currently procured from brain-dead donors; how- ever, brain death is an important risk factor in liver transplantation. In addition, to counteract the shortage of liver grafts, transplant centers accept the use of sub-optimal livers, which may show higher risk of primary non-function or initial poor function. Very few literatures exist regarding liver transplantation using brain-dead donors, or about brain death and its effects on sub-optimal grafts in such surgical situation. This chapter aims to describe the pathophysiological changes occurring in liver grafts during brain death and focuses on the strengths and limitations of experimental models used to study the effect of brain death on optimal and sub-optimal (specially steatotic) liver grafts. Depending on the use of experimental models that simulate as much as possible the surgical conditions present in clinical practice, therapeutic strategies designed in animal models could be more successfully translated to the bedside.
Board 24: The Effects of Mobile Circuits Tutor on Students’ Problem-solving Self-efﬁcacy and Anxiety

— This research study investigated the effects of an assistive mobile learning environment (MLE) on students’ self-efficacy and anxiety of problem-solving. Eighty-three college students were randomly assigned into one of three groups and participated the study for an entire semester. The control group did not have access to the app. Participants were split into two treatment group s based on one of the two versions of the MLE tutor (CircuitITS or Circuit Test Taker). Scores from three examinations were recorded from all students throughout the semester. The combined experimental group were asked to complete scales measuring self-efficacy and anxiety at three time points that coincided with midterm examinations. Multilevel longitudinal modeling (MLM) was used to assess the effects of the assistive MLEs on problem-solving self-efficacy and anxiety. MLM was also used to assess effects of problem-solving self-efficacy (NTSEI) scores and problem-solving anxiety (PSA) scores on student examination scores. Results showed a significant negative effect of CircuitITS on NTSEI scores but a positive significant effect of NTSEI scores on exam scores for both tutors. This research study provides results that are counterintuitive to the proposed outcome suggesting that CircuitITS produced a reduction in problem-solving self-efficacy among its users. Although s tudents w ho utilized CircuitITS experienced a decreased perceived ability to problem solve, both tutors showed significant increases in examination scores. ( Abstract )
The Role of T RM Cells in the Pathogenesis of Vitiligo—A Review of the Current State-Of-The-Art

: Vitiligo is the most common hypopigmentation disease a ﬀ ecting both the skin and mucous membranes. The pathogenesis of this disorder is complex and involves the inﬂuence of genetic and environmental factors, oxidative stress, and autoimmune responses. Recent studies have indicated that skin lesions observed in vitiligo tend to recur in the same places where they were found before treatment. This phenomenon is explained by the presence of recently discovered tissue-resident memory T cells (T RM ), whose primary function is to provide antiviral and antibacterial protection in non-lymphoid tissues. T RM cells show the presence of CD49a, CD69, and CD103 markers on their surface, although not all of them express these particles. Due to their ability to produce and secrete perforin, IFN- γ , and granzyme B, T RM cells demonstrate a cytotoxic e ﬀ ect on melanocytes, thus inducing depigmented lesions in the course of the vitiligo. It has been proved that the occurrence of T RM cells largely depends on IL-15, which promotes the T RM function ex vivo. The ﬁndings above, as well as their reference to the pathogenesis of autoimmune skin diseases will have a considerable inﬂuence on the development of new therapeutic strategies in the near future. This article presents an up-to-date review of information regarding the role of T RM cells in the development and progression of vitiligo. and IFN-  which indicate a cytotoxic effect on melanocytes. Additionally, T RM produce chemokines CXCL9 and CXCL10, which, after binding with receptor CXCR3 on the surface of T RCM cells, influence their recruitment from the blood vessels to the skin. Next, through the synergistic effect, they cause the depigmentation of the skin in the course of disease.
Green Bandits - preliminary version ∗

I consider a dynamic model of N players making decisions over fossil energy consumption and green technology investments. The investment technology is modeled as a one-armed bandit: it is unknown to all players whether investments may or may not yield positive returns. The potential for returns are perfectly correlated between players, therefore investments by each player generate information that is valuable to all players. The ﬁndings in the paper underline the need for Pigouvian taxation of greenhouse gas emissions, by showing that when this speciﬁc information structure is in place, such taxation will not only implement ﬁrst-best energy consumption levels, but also reduce the prevailing underinvestment problem below the level for a comparable standard technology. To implement the ﬁrst-best investment and emission levels, a state-dependent investment subsidy is needed in addition to a Pigouvian tax. This is the case even though there are no technological spillovers or hold-up problems in the model. Furthermore, the subsidy required to implement eﬃcient investment levels is decreasing in the probability that the technology will succeed, over the range it is used.
A damage-plasticity model for the dynamic failure of concrete

A constitutive model based on the combination of damage mechanics and plasticity is developed to analyse concrete structures subjected to dynamic loading. The aim is to obtain a model, which requires input parameters with clear physical meanings. The model should describe the important characteristics of concrete subjected to multiaxial and rate-depending loading. This is achieved by combining an effective stress based plasticity model with an isotropic damage model based on plastic and elastic strain measures. The model response in tension, uni-, bi- and tri-axial compression is compared to experimental results in the literature.
Mutual Information of Three-State Low Activity Diluted Neural Networks with Self-Control

The influence of a macroscopic time-dependent threshold on the retrieval process of three-state extremely diluted neural networks is examined. If the threshold is chosen appropriately in function of the noise and the pattern activity of the network, adapting itself in the course of the time evolution, it guarantees an autonomous functioning of the network. It is found that this self-control mechanism considerably improves the retrieval quality, especially in the limit of low activity, including the storage capacity, the basins of attraction and the information content. The mutual information is shown to be the relevant parameter to study the retrieval quality of such low activity models. Numerical results confirm these observations.
Application of domain decomposition methods to problems in topology optimisation

Determination of the optimal layout of structures can be seen in everyday life, from nature to industry, with research dating back to the eighteenth century. The focus of this thesis involves investigation into the relatively modern field of topology optimisation, where the aim is to determine both the optimal shape and topology of structures. However, the inherent large-scale nature means that even problems defined using a relatively coarse finite element discretisation can be computationally demanding. This thesis aims to describe alternative approaches allowing for the practical use of topology optimisation on a large scale. Commonly used solution methods will be compared and scrutinised, with observations used in the application of a novel substructuring domain decomposition method for the subsequent large-scale linear systems. Numerical and analytical investigations involving the governing equations of linear elasticity will lead to the development of three different algorithms for compliance minimisation problems in topology optimisation. Each algorithm will involve an appropriate preconditioning strategy incorporating a matrix representation of a discrete interpolation norm, with numerical results indicating mesh independent performance.
University of Birmingham A study of CP violation in B ± DK ± and B ± D p ± decays with D K 0 K ± p final states LHCb Collaboration

Citation for published version (Harvard): LHCb Collaboration, Aaij, R, Adeva, B, Adinolfi, M, Affolder, A, Ajaltouni, Z, Albrecht, J, Alessio, F, Alexander, M & Ali, S 2014, 'A study of CP violation in B± DK± and B± D p ± decays with D K0K± p final states', Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics, vol. 733, pp. 36-45. https://doi.org/10.1016/j.physletb. 2014.03. 051
Scene-level Tracking and Reconstruction without Object Priors

We present the first real-time system capable of tracking and reconstructing, individually, every visible object in a given scene, without any form of prior on the rigidness of the objects, texture existence, or object category. In contrast with previous methods such as Co-Fusion and MaskFusion that first segment the scene into individual objects and then process each object independently, the proposed method dynamically segments the non-rigid scene as part of the tracking and reconstruction process. When new measurements indicate topology change, reconstructed models are updated in real-time to reflect that change. Our proposed system can provide the live geometry and deformation of all visible objects in a novel scene in real-time, which makes it possible to be integrated seamlessly into numerous existing robotics applications that rely on object models for grasping and manipulation. The capabilities of the proposed system are demonstrated in challenging scenes that contain multiple rigid and non-rigid objects. Supplementary material, including video, can be found at https://github.com/changhaonan/STAR-no-prior.
Earth and Planetary Science Letters First direct observation of coseismic slip and seaﬂoor rupture along a submarine normal fault and implications for fault slip history

Properly assessing the extent and magnitude of fault ruptures associated with large earthquakes is critical for understanding fault behavior and associated hazard. Submarine faults can trigger tsunamis, whose characteristics are deﬁned by the geometry of seaﬂoor displacement, studied primarily through indirect observations (e.g., seismic event parameters, seismic proﬁles, shipboard bathymetry, coring) rather than direct ones. Using deep-sea vehicles, we identify for the ﬁrst time a marker of coseismic slip on a submarine fault plane along the Roseau Fault (Lesser Antilles), and measure its vertical displacement of ∼ 0 . 9 m in situ. We also map recent ﬁssuring and faulting of sediments on the hangingwall, along ∼ 3 km of rupture in close proximity to the fault’s base, and document the reactivation of erosion and sedimentation within and downslope of the scarp. These deformation structures were caused by the 2004 M w 6.3 Les Saintes earthquake, which triggered a subsequent tsunami. Their characterization informs estimates of earthquake recurrence on this fault and provides new constraints on the geometry of fault rupture, which is both shorter and displays locally larger coseismic displacements than available model predictions that lack ﬁeld constraints. This methodology of detailed ﬁeld observations coupled with near-bottom geophysical surveying can be readily applied to numerous submarine fault systems, and should prove useful in evaluating seismic and tsunamigenic hazard in all geodynamic contexts.
COPD_A_327887 2845..2856

1State Key Laboratory of Respiratory Disease, Guangzhou Chest Hospital, Guangzhou, Guangdong, People’s Republic of China; 2State Key Laboratory of Respiratory Disease, Guangzhou Medical University, Guangzhou, Guangdong, People’s Republic of China; 3The Second Hospital, University of South China, Hengyang, Hunan, People’s Republic of China; 4School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou, Guangdong, People’s Republic of China; 5State Key Laboratory of Respiratory Diseases, National Clinical Research Center for Respiratory Diseases, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, People’s Republic of China Background and Purpose: PM2.5-associated airway inflammation has recently been recognized as pivotal to the development of COPD. Aberrant glycogen synthase kinase (GSK)-3β signaling is linked to the inflammatory response. Therefore, we investigated the effects of GSK-3β inhibitors on the PM2.5-induced inflammatory response in bronchial epithelial cells. Methods: The production of phosphorylated GSK-3β (p-GSK-3β) was analyzed by immunohistochemistry with PM2.5-induced mice. HBECs were treated with various inhibitors targeting GSK-3β or JNK before PM2.5 stimulation. The production of GSK-3β signaling was analyzed by Western blotting. Inflammatory cytokine production was detected by qRT– PCR and ELISA. Results: PM2.5 exposure caused lung inflammation, upregulated serum concentrations of HMGB1 and IL-6, decreased IL-10 expression, and significantly attenuated p-GSK-3β production in mice. HBECs exposed to PM2.5 showed significantly reduced p-GSK-3β production, an increased ratio of p-JNK/JNK, increased NF-κB activation and IκB degradation, and upregulated the inflammatory cytokines HMGB1 and IL-6. Intervention with GSK3β inhibitors TDZD-8 and SB216763 significantly suppressed PM2.5-induced outcomes. Moreover, the JNK inhibitor SP600125 also reduced the level of NF-κB phosphorylation induced by PM2.5. The differences in the levels of inflammation-related cytokines in the TDZD-8 groups were greater than those in the SB216763 groups. Conclusion: Inhibition of GSK-3β weakens the PM2.5-induced inflammatory response by regulating the JNK/NF-κB signaling pathway in bronchial epithelial cells.
Hall and Spin Hall Viscosity in 2d Topological Systems

We study responses to metric perturbation in topological insulator models. In this paper we introduce a novel quantity, Hall viscosity to particle density ratio, which is analogous to the viscosity to entropy ratio suggested by AdS/CFT correspondence. This quantity corresponds to the filling fraction which characterizes the quantum Hall states, and hence it could be discussed in Haldane's zero-field quantum Hall system. We also consider dissipationless viscosity in the time reversal invariant quantum spin Hall system, which is related to a spin current.
SCCAA_A_268940 117..136

Department of Molecular Medicine, College of Medicine and Medical Sciences, Princess Al-Jawhara Center for Molecular Medicine and Inherited Disorders, Arabian Gulf University, Manama, Bahrain Introduction: Osteoarthritis causes a progressive deterioration to the protective cartilage between the joints leading to chronic pain and disability. This review focuses on the intrinsic potential of MSCs to stabilize and repair the cartilage tissue of the knee joint in knee osteoarthritis (KOA) patients. Methods: An online search through the PubMed database was conducted, limiting the search to the English language and human clinical trials within the past 5 years. Twentyone clinical trials passed the inclusion criteria. Combined, those trials involved the participation of 589 patients where the progress of the treatments was monitored between a 4-month to 7-years period. The cartilage volume and defects were observed through an MRI to provide an objective assessment. While the pain and knee function were monitored using KOOS, VAS, and WOMAC scoring scales providing a subjective assessment. Results: MRI scans obtained from clinical trials demonstrate a slowed progression of cartilage degeneration and early signs of cartilage regeneration in KOA patients at the 12month follow-up period. No major adverse effects were observed post-intervention. The overall KOOS, WOMAC, and VAS scores in patients receiving MSC treatment were reduced, suggesting subjective improvements in knee function and pain reduction when compared to patients in the placebo group. Conclusion: The use of MSC therapy is a valid form of treatment for KOA as it targets the disease itself rather than the symptoms. We found MSC therapy in KOA patients to be safe, effective, and feasible in its execution.
Identification of OST1-Interacting Proteins Reveals Interactions

1 RUNNING HEAD 1 Identification of OST1-Interacting Proteins 2 3 CORRESPONDING AUTHOR 4 Julian I. Schroeder 5 University of California San Diego, Division of Biological Sciences, Cell and Developmental 6 Biology Section and Center for Food and Fuel for the 21 Century, 9500 Gilman Drive #0116, 7 La Jolla, CA 92093-0116, USA. 8 Phone: (858) 534-7759, Fax: (858) 534-7108, Email: jischroeder@ucsd.edu 9 10 RESEARCH AREA 11 Signaling and Response 12
Never change a winning chunk

Cet article traite de la persistence à l’oral. Par persistence j’entends le fait qu’un locuteur aura tendance à réutiliser des éléments phonologiques et morphologiques, ainsi que des structures du discours antérieur. Dans le cadre d’une étude de cas, j’analyse l’alternance entre la complémentation gérondive et la complémentation infinitive à l’aide d’un modèle de régression logistique appliqué à des données linguistiques de corpus afin de démontrer que (i) les bases de données de corpus sont tout aussi utilisables que les bases de données psycholinguistiques, (ii) les schémas de persistence sont suffisament clairs pour pouvoir être prédits, et (iii) la magnitude de la persistence dépend de variables secondaires telle que la distance entre les deux éléments. Pour conclure, cet article s’intéressera à la signification de ce phénomène pour la théorie et la pratique linguistique.
Popular Perceptions of Democracy in China Characteristics and Longitudinal Changes

Democracy is a contested concept; this article empirically examines how Chinese people understand the concept of democracy in practice when they use this term. Using four rounds of national survey data, we seek to clarify the characteristics of the Chinese people’s perception of democracy and its longitudinal changes during the past few decades. The results show an increase in the percentage of people who view democracy procedurally. The popular perception of democracy does matter. People who view democracy substantively tend to see democracy as less suitable for China, and to overrate the democratic level of the current regime, compared to those who view democracy procedurally. No matter how people perceive it, satisfaction with democracy has declined over the past decade. The demographic analysis shows that Chinese youth adhere to a procedural concept of democracy more than a substantive one, which has important implications for China’s future political development.
Machine Learning for Pulmonology: Disease Prognosis and Evaluation Metric for Generated Data

Artificial Intelligence (AI) has seen a significant growth in the past decade in various wide ranging domains. Machine learning (ML) methods have been applied in healthcare for various tasks like disease diagnosis, disease progression and outcome prediction, etc. ML aids healthcare systems by executing medical tasks with expert-level performance in lesser time, thereby enabling optimized resource allocation, targeted care and accelerated decision-making. This thesis presents two different applications of AI in pulmonology, a domain of healthcare that deals with respiratory diseases. The first application of ML in pulmonology is about how ML is employed for early mortality prediction of COVID-19 patients. The coronavirus disease 2019 (COVID-19), caused by the virus SARS-CoV-2, is an acute respiratory disease that has been classified as a pandemic by the World Health Organization (WHO). The sudden spike in the number of infections and high mortality rates have put immense pressure on the public healthcare systems. Hence, it is crucial to identify the key factors for mortality prediction to optimize patient treatment strategy. Since routine blood test results are more widely available compared to other forms of data like X-rays, CT-scans and ultrasounds, this thesis focuses on ML methods based on blood tests data to predict COVID-19 mortality risk. A powerful combination of five features: neutrophils, lymphocytes, lactate dehydrogenase (LDH), high-sensitivity C-reactive protein (hs-CRP) and age helps to predict mortality with 96% accuracy. Various ML models (neural networks, logistic regression, XGBoost, random forests, SVM and decision trees) have been trained and their performances have been compared to determine the model that achieves consistently high accuracy across the days that span the disease. The best performing method using XGBoost feature importance and neural network classification, predicts with an accuracy of 90% as early as 16 days before the outcome. Robust testing with three cases based on days to outcome confirms the strong predictive performance and practicality of the proposed model.
Corporate Social Responsibility, Shariah-Compliance, and Earnings Quality Abdullah Alsaadi, M. Shahid Ebrahim & Aziz

This study examines the effect of two potential sources of ethical principles on earnings quality: corporate social responsibility (CSR) and membership in a Shariah index. We define membership in a Shariah index as the adherence to an ethical code that relates to Islam. Our sample comprises firms in ten European Union countries for the period from 2003 to 2013. The empirical results show that firms with a high degree of CSR are less likely to manage earnings. In contrast, membership in a Shariah index leads to earnings manipulation. Our results are robust after using several alternative quality metrics for earnings. Furthermore, our empirical results indicate that highly rated CSR firms that are not Shariah-compliant are less likely to engage in earnings manipulation. Further, institutional factors are also important in determining the link between CSR, Shariah-compliance, and the quality of financial reporting.