Miracle-dz/UniFAR-FTUs huggingface dataset:
On the Convergence of Continuous Constrained Optimization for Structure Learning

Structure learning of directed acyclic graphs (DAGs) is a fundamental problem in many scientific endeavors. A new line of work, based on NOTEARS (Zheng et al., 2018), reformulates the structure learning problem as a continuous optimization one by leveraging an algebraic characterization of DAG constraint. The constrained problem is typically solved using the augmented Lagrangian method (ALM) which is often preferred to the quadratic penalty method (QPM) by virtue of its convergence result that does not require the penalty coefficient to go to infinity, hence avoiding ill-conditioning. In this work, we review the standard convergence result of the ALM and show that the required conditions are not satisfied in the recent continuous constrained formulation for learning DAGs. We demonstrate empirically that its behavior is akin to that of the QPM which is prone to ill-conditioning, thus motivating the use of second-order method in this setting. We also establish the convergence guarantee of QPM to a DAG solution, under mild conditions, based on a property of the DAG constraint term.
Structural study of TATB under detonation-induced shock conditions

We explore the response of the insensitive high explosive (IHE) 1,3,5-Triamino-2,4,6- trinitrobenzene (TATB) under detonation-induced shock conditions using in-situ synchrotron X-ray diffraction in the 100 ns time scale using either a conventional or a colliding detonation drive. In all of the detonation experiments on various sizes and morphologies of TATB, we observe an extended stability of the TATB triclinic crystal structure. As the detonation front passes through the TATB, X-ray diffraction indicates a portion of the TATB exhibits a compression up to 30+ GPa, followed subsequently by a pressure release and continued decomposition over a few hundred nanoseconds. Likewise, for colliding detonation-driven shock compression of single crystals of TATB, a significant portion of the triclinic crystal structure appears to be stable up to 60+ GPa. Conversely, in similar detonations of a LLM-105 PBX, X-ray diffraction is simply indicative of decomposition without the apparent compression and slow decomposition seen in TATB. The results indicate the surprising resilience of TATB under these high-pressure, temperature and shock conditions, providing a baseline for understanding the insensitivity of TATB that is considered the industry standard for an insensitive high explosive. The results also provide intriguing information for the extended reaction zone in TATB, and the hot-spot mechanisms for initiating and propagating detonation in this uniquely insensitive explosive.
Joint Analysis and Prediction of Human Actions and Paths in Video

With the advancement in computer vision deep learning, systems now are able to analyze an unprecedented amount of rich visual information from videos to enable applications such as autonomous driving, socially-aware robot assistant and public safety monitoring. Deciphering human behaviors to predict their future paths/trajectories and what they would do from videos is important in these applications. However, modern vision systems in self-driving applications usually perform the detection (perception) and prediction task in separate components, which leads to error propagation and sub-optimal performance. More importantly, these systems do not provide high-level semantic attributes to reason about pedestrian future. This design hinders prediction performance in video data from diverse domains and unseen scenarios. To enable optimal future human behavioral forecasting, it is crucial for the system to be able to detect and analyze human activities leading up to the prediction period, passing informative features to the subsequent prediction module for context understanding. In this thesis, with the goal of improving the performance and generalization ability of future trajectory and action prediction models, we conduct human action analysis and jointly optimize models for action detection, prediction and trajectory prediction.
Logarithmic Regret for Reinforcement Learning with Linear Function Approximation

Reinforcement learning (RL) with linear function approximation has received increasing attention recently. However, existing work has focused on obtaining $\sqrt{T}$-type regret bound, where $T$ is the number of steps. In this paper, we show that logarithmic regret is attainable under two recently proposed linear MDP assumptions provided that there exists a positive sub-optimality gap for the optimal action-value function. In specific, under the linear MDP assumption (Jin et al. 2019), the LSVI-UCB algorithm can achieve $\tilde{O}(d^{3}H^5/\text{gap}_{\text{min}}\cdot \log(T))$ regret; and under the linear mixture model assumption (Ayoub et al. 2020), the UCRL-VTR algorithm can achieve $\tilde{O}(d^{2}H^5/\text{gap}_{\text{min}}\cdot \log^3(T))$ regret, where $d$ is the dimension of feature mapping, $H$ is the length of episode, and $\text{gap}_{\text{min}}$ is the minimum of sub-optimality gap. To the best of our knowledge, these are the first logarithmic regret bounds for RL with linear function approximation.
Control and implementation of fluid-driven soft gripper with dynamic uncertainty of object

Soft grippers, for stable grasping of objects, with high compliance could be considered a suitable candidate for replacement of conventional rigid grippers, and in recent years, they have been emerging exponentially in industries. Not only are these highly adaptable grippers capable of static grasping of an object, but also they can be utilized for performing object manipulation tasks. Plenty of contemporary studies have been emphasizing on static grasping ability of soft grippers. However, in this thesis, planar in-hand object manipulation in a soft gripper which comprises a pair of soft finger is investigated.
Characterization of Colloidal Gas Aphron-Fluids Produced from a New Plant-Based Surfactant

Colloidal gas aphrons (CGAs) are gas bubbles with diameters ranging from 10 to 100 microns, generated by intense stirring of a surfactant solution at high speed. The surface activity and aggregation behavior of the surfactant affects the size/size distribution, stability, and other physicochemical properties of generated aphrons. Therefore, selection of a suitable surfactant is important for the generation of microbubbles with the desired properties. The goal of this articleis to investigate the potential use of a new plant-derived surfactant as an aphronizer surfactant in preparation of CGA-based drilling fluids for accomplishing desirable rheological and filtration properties. For this purpose, natural surfactant obtained from leaves of special tree, namely, Zizyphusspina Christi and used for preparation of aphron-based fluids. To achieve the research objectives, laboratory tests of suspension generation, microscopic visualization, initial yield, filtration loss, and rheological characterization with varying concentrations of surfactant and polymer were performed. Experimental results demonstrate that newly proposed biosurfactant has a great potential for application in preparation of CGA-based drilling fluids for implementation in petroleum drilling industry.
Lethal COVID-19: Radiologic-Pathologic Correlation of the Lungs

Purpose The purpose of this retrospective study was to correlate CT patterns of fatal cases of coronavirus disease 2019 (COVID-19) with postmortem pathology observations. Materials and Methods The study included 70 lung lobes of 14 patients who died of reverse-transcription polymerase chain reaction–confirmed COVID-19. All patients underwent antemortem CT and autopsy between March 9 and April 30, 2020. Board-certified radiologists and pathologists performed lobewise correlations of pulmonary observations. In a consensus reading, 267 radiologic and 257 histopathologic observations of the lungs were recorded and systematically graded according to severity. These observations were matched and evaluated. Results Predominant CT observations were ground-glass opacities (GGO) (59/70 lobes examined) and areas of consolidation (33/70). The histopathologic observations were consistent with diffuse alveolar damage (70/70) and capillary dilatation and congestion (70/70), often accompanied by microthrombi (27/70), superimposed acute bronchopneumonia (17/70), and leukocytoclastic vasculitis (7/70). Four patients had pulmonary emboli. Bronchial wall thickening at CT histologically corresponded with acute bronchopneumonia. GGOs and consolidations corresponded with mixed histopathologic observations, including capillary dilatation and congestion, interstitial edema, diffuse alveolar damage, and microthrombosis. Vascular alterations were prominent observations at both CT and histopathology. Conclusion A significant proportion of GGO correlated with the pathologic processes of diffuse alveolar damage, capillary dilatation and congestion, and microthrombosis. Our results confirm the presence and underline the importance of vascular alterations as key pathophysiologic drivers in lethal COVID-19. Supplemental material is available for this article. © RSNA, 2020
Perceived Quality of Healthcare and Availability of Supplies Determine Household-Level Willingness to Join a Community-Based Health Insurance Scheme in Amhara Region, Ethiopia

Purpose The Ethiopian health system has been challenged by a shortage of funds and is heavily reliant on foreign donation. However, voluntary community-based health insurance (CBHI) has been implemented to reach and cover the very large agricultural sector since 2010. Thus, the level of acceptability of the scheme needs to be regularly assessed through households’ willingness to join before the nationwide rollout of the scheme. This study was intended to assess the level of willingness to join in community-based health insurance and associated factors in northwest Ethiopia. Patients and Methods Using a pretested structured questionnaire, a cross-sectional community-based study was conducted in 2017 in Amhara Region, northwest Ethiopia. Using a multi-stage sampling method, from 15 clusters in which CBHI was implemented, 1,179 households without CBHI membership were included as a sample for the study. Bivariable and multivariable logistic regression was fitted to assess the association between predictor variables and the outcome of interest. Results Out of the total (1,179) participants, 60.5% (713) were willing to join the scheme. Households’ occupation (AOR=2.26; 95% CI:=1.12–5.07), perceived good (AOR=2.21; 95% CI:=1.53−3.21), and medium (AOR=1.44; 95% CI=1.22–2.0) healthcare quality and richer wealth status (AOR=1.72; 95% CI=1.08–2.73) were associated with higher odds of willingness to join the scheme. Conclusion As The study revealed that level of willingness to join is lower compared to other studies. Therefore, social protection activities for the low-income population and enhancement of the capacity of health facilities are crucial.
Evaluation of the Current Knowledge About Bacterial Endocarditis Prevention Among General Dentists in the City of Santo Domingo, Dominican Republic

Infective endocarditis (IE) is a life-threatening disease caused by bacterial adherence to the lining of the heart and heart valve, and it can be caused by bacterial contamination of the bloodstream during invasive dental procedures. The American Heart Association (AHA) recommended guidelines for antibiotic prophylaxis in 2008 before invasive dental procedures; however, in the Dominican Republic, no official guidelines or regulations on this topic have been yet established. This study aimed to evaluate the current knowledge about bacterial endocarditis prevention among dentists in Santo Domingo. The study participants were dentists who attended a conference organized by Universidad Federico Henríquez y Carvajal (n = 95), of which 74 responded to the questionnaire survey. Seventy-eight percentage of the participants responded that an indication of antibiotics is recommended in cases of prophylaxis for IE. The prescription of antibiotics was applied to patients with prosthetic valves (78.4%), presented a history of previous IE (77%) among others. Among all the interventions in which the respondents would prescribe antibiotics, tooth extraction (70.7%) was the most frequent. Amoxicillin was the preferred drug choice (63.5%) and clindamycin was the antibiotic of choice in allergic patients (55.4%). Even though the choice of antibiotics were according to AHA guidelines (2008), majority of the dentists (58.82 and 55.4%) were not aware of the correct dosage and timing of administration of azithromycin and clindamycin in drugs in patients allergic to penicillin.
The Emotion Regulation Roots of Job Satisfaction

Job satisfaction is a core variable in the study and practice of organizational psychology because of its implications for desirable work outcomes. Knowledge of its antecedents is abundant and informative, but there are still psychological processes underlying job satisfaction that have not received complete attention. This is the case of employee emotion regulation. In this study, we argue that employees’ behaviors directed to manage their affective states participate in their level of job satisfaction and hypothesize that employee affect-improving and -worsening emotion regulation behaviors increase and decrease, respectively, job satisfaction, through the experience of positive and negative affect. Using a diary study with a sample of professionals from diverse jobs and organizations, for the most part, the mediational hypotheses were supported by the results albeit a more complex relationship was found in the case of affect worsening emotion regulation. This study contributes to expanding the job satisfaction and emotion regulation literatures and informs practitioners in people management in organizations about another route to foster and sustain positive attitudes at work.
Mitochondrial DNA Affects the Expression of Nuclear Genes Involved in Immune and Stress Responses in a Breast Cancer Model

Tumor cells without mitochondrial (mt) DNA (ρ0 cells) are auxotrophic for uridine, and their growth is supported by pyruvate. While ATP synthesis in ρ0 cells relies on glycolysis, they fail to form tumors unless they acquire mitochondria from stromal cells. Mitochondrial acquisition restores respiration that is essential for de novo pyrimidine biosynthesis and for mitochondrial ATP production. The physiological processes that underpin intercellular mitochondrial transfer to tumor cells lacking mtDNA and the metabolic remodeling and restored tumorigenic properties of cells that acquire mitochondria are not well understood. Here, we investigated the changes in mitochondrial and nuclear gene expression that accompany mtDNA deletion and acquisition in metastatic murine 4T1 breast cancer cells. Loss of mitochondrial gene expression in 4T1ρ0 cells was restored in cells recovered from subcutaneous tumors that grew from 4T1ρ0 cells following acquisition of mtDNA from host cells. In contrast, the expression of most nuclear genes that encode respiratory complex subunits and mitochondrial ribosomal subunits was not greatly affected by loss of mtDNA, indicating ineffective mitochondria-to-nucleus communication systems for these nuclear genes. Further, analysis of nuclear genes whose expression was compromised in 4T1ρ0 cells showed that immune- and stress-related genes were the most highly differentially expressed, representing over 70% of those with greater than 16-fold higher expression in 4T1 compared with 4T1ρ0 cells. The monocyte recruiting chemokine, Ccl2, and Psmb8, a subunit of the immunoproteasome that generates MHCI-binding peptides, were the most highly differentially expressed. Early monocyte/macrophage recruitment into the tumor mass was compromised in 4T1ρ0 cells but recovered before mtDNA could be detected. Taken together, our results show that mitochondrial acquisition by tumor cells without mtDNA results in bioenergetic remodeling and re-expression of genes involved in immune function and stress adaptation.
Responses of Plant Biomass in the Brazilian Savanna to Frequent Fires

Fire has been a natural feature of the ecosystem for million years. Still, currently fire regimes have been increasingly altered by human activities and climate change, causing economic losses, air pollution, and environmental damage. In Brazil, savannas (locally known as the Cerrado) occupy almost 25% of the area of the country and contain 70% of the concentrated burned area. Fire frequency is related to the use of biannual fire in agricultural practices, aiming at cleaning cattle pastures, which act as ignition sources for the surrounding natural vegetation. Here, we present an ecological model to demonstrate how biennial fire affects plant biomass and carbon release from fine fuel in the Cerrado. The BEFIRE model (Behavior and Effect of Fire) is the first quantitative model to simulate the relationships between fire frequency, plant biomass, and fire-associated emissions based on the synthesis of knowledge about fire behavior and the effects on ecosystems compiled from experimental burnings in the Cerrado. Our model uses microclimate variables and vegetation structure (the amount of the aboveground biomass of trees, shrubs, herbs, and grasses) as inputs, and generates outputs related to the fire behavior (fire spread rate, fire intensity, and heat released) and the fire effects on the dynamic of plant biomass and post-fire carbon emissions. The BEFIRE model predicts that biennial fires allow for the recovery of the biomass of herbs and grasses, due to its fast growth. However, this fire interval does not allow for the recovery of the biomass of shrubs and trees. These growth limitations alter the co-existence of trees/shrubs and herbs/grasses and prevent the uptake of the total amount of emitted carbon from the combustion of fine fuel. Based on the model results, we proposed some recommendations for fire management in this threatened biome.
SCGA‐Net: Skip Connections Global Attention Network for Image Restoration

Deep convolutional neural networks (DCNN) have shown their advantages in the image restoration tasks. But most existing DCNN‐based methods still suffer from the residual corruptions and coarse textures. In this paper, we propose a general framework “Skip Connections Global Attention Network” to focus on the semantics delivery from shallow layers to deep layers for low‐level vision tasks including image dehazing, image denoising, and low‐light image enhancement. First of all, by applying dense dilated convolution and multi‐scale feature fusion mechanism, we establish a novel encoder‐decoder network framework to aggregate large‐scale spatial context and enhance feature reuse. Secondly, the solution we proposed for skipping connection uses attention mechanism to constraint information, thereby enhancing the high‐frequency details of feature maps and suppressing the output of corruptions. Finally, we also present a novel attention module dubbed global constraint attention, which could effectively captures the relationship between pixels on the entire feature maps, to obtain the subtle differences among pixels and produce an overall optimal 3D attention maps. Extensive experiments demonstrate that the proposed method achieves significant improvements over the state‐of‐the‐art methods in image dehazing, image denoising, and low‐light image enhancement.
Regional Differences in the Gut Microbiota and Gut-Associated Immunologic Factors in the Ileum and Cecum of Rats With Collagen-Induced Arthritis

Rheumatoid arthritis (RA) is a common autoimmune disease characterized by chronic inflammation and a multifactorial etiology. We previously showed that gut microbiota dysbiosis in the rat ileum is involved in the development of collagen-induced arthritis (CIA). The gut microbiota in the distinct gastrointestinal tract (GIT) plays region-specific roles, but information on the different roles of the microbiota in distinct GIT compartments of CIA rats is limited. This study aimed to evaluate the region-specific differences in the gut microbial communities and certain gut-associated immunologic factors in the ileum and cecum of CIA rats. Ileal and cecal digesta were collected from CIA and control rats for microbiome analysis. We determined the microbial richness, diversity and taxa as well as the expression of interleukin (IL)-1β and IL-17A in the epithelium and lamina propria of the ileum and cecum mucosal layers. The CIA-induced microbiota alterations in the ileum differed from those in the cecum. The ileal microbiota were more markedly influenced in CIA, as revealed by sharp reductions in the abundances of the families Enterococcaceae, Lactobacillaceae and Streptococcaceae and the genera Lactobacillus and Lactococcus. Moreover, significant increases in IL-1β, and IL-17A mRNA expression were detected in only the ileal epithelium and lamina propria of the mucosal layer. Therefore, the microbial characteristics in the ileum were consistent with the immune-mediated inflammatory features of CIA, suggesting that the ileal microbiota might better represent the CIA-induced inflammatory responses than the cecal microbiota and that these responses might partially impact the progression of RA by regulating intestinal mucosal immunity.
Colorization of Line Drawings with Empty Pupils

Many studies have recently applied deep learning to the automatic colorization of line drawings. However, it is difficult to paint empty pupils using existing methods because the convolutional neural network are trained with pupils that have edges, which are generated from color images using image processing. Most actual line drawings have empty pupils that artists must paint in. In this paper, we propose a novel network model that transfers the pupil details in a reference color image to input line drawings with empty pupils. We also propose a method for accurately and automatically colorizing eyes. In this method, eye patches are extracted from a reference color image and automatically added to an input line drawing as color hints using our pupil position estimation network.