Miracle-dz/UniFAR-FTUs huggingface dataset:
Dimension-Grouped Mixed Membership Models for Multivariate Categorical Data

Mixed Membership Models (MMMs) are a popular family of latent structure models for complex multivariate data. Instead of forcing each subject to belong to a single cluster, MMMs incorporate a vector of subject-specific weights characterizing partial membership across clusters. With this flexibility come challenges in uniquely identifying, estimating, and interpreting the parameters. In this article, we propose a new class of Dimension-Grouped MMMs (Gro-M$^3$s) for multivariate categorical data, which improve parsimony and interpretability. In Gro-M$^3$s, observed variables are partitioned into groups such that the latent membership is constant for variables within a group but can differ across groups. Traditional latent class models are obtained when all variables are in one group, while traditional MMMs are obtained when each variable is in its own group. The new model corresponds to a novel decomposition of probability tensors. Theoretically, we derive transparent identifiability conditions for both the unknown grouping structure and model parameters in general settings. Methodologically, we propose a Bayesian approach for Dirichlet Gro-M$^3$s to inferring the variable grouping structure and estimating model parameters. Simulation results demonstrate good computational performance and empirically confirm the identifiability results. We illustrate the new methodology through applications to a functional disability survey dataset and a personality test dataset.
Adiabatic Path from Fractional Chern Insulators to the Tao-Thouless State

In view of the evolution from the integer to fractional quantum Hall effect, the next frontier in the research of topological insulators is to investigate what happens in fractionally filled topological flat bands. A particularly pressing question is if there exists the lattice analogue of the Laughlin state in the 1/3-filled Chern flat band, dubbed as the Chern-Laughlin state. The answer depends crucially on the form of the electron-electron interaction, which can generate various competing ground states such as the Laughlin, stripe/nematic, parafermion, and parton states. Unfortunately, it is difficult to precisely characterize the exact ground state as any of these candidate ground states due to the lack of appropriate order parameters. Here, we propose that the existence of an adiabatic path from fractional Chern insulators to the Tao-Thouless state, i.e., the root partition state of the Laughlin state in the thin torus limit, can serve as an effective order parameter for the ChernLaughlin state. Specifically, by devising the piecewise hybrid adiabatic path of first transforming the electron-electron interaction and then taking the thin torus limit, it is shown that Chern flat bands with the nearest-neighbor interaction can indeed host the Chern-Laughlin state at 1/3 filling. This method can be extended to possible FCIs at other general fillings of the Jain sequence.
Simulating magnetized neutron stars with discontinuous Galerkin methods

Discontinuous Galerkin methods are popular because they can achieve high order where the solution is smooth, because they can capture shocks while needing only nearest-neighbor communication, and because they are relatively easy to formulate on complex meshes. We perform a detailed comparison of various limiting strategies presented in the literature applied to the equations of general relativistic magnetohydrodynamics. We compare the standard minmod/$\Lambda\Pi^N$ limiter, the hierarchical limiter of Krivodonova, the simple WENO limiter, the HWENO limiter, and a discontinuous Galerkin-finite-difference hybrid method. The ultimate goal is to understand what limiting strategies are able to robustly simulate magnetized TOV stars without any fine-tuning of parameters. Among the limiters explored here, the only limiting strategy we can endorse is a discontinuous Galerkin-finite-difference hybrid method.
Exploring Multi-dimensional Hierarchical Network Topologies for Efficient Distributed Training of Trillion Parameter DL Models

Deep Neural Networks have gained significant attraction due to their wide applicability in different domains. DNN sizes and training samples are constantly growing, making training of such workloads more challenging. Distributed training is a solution to reduce the training time. High-performance distributed training platforms should leverage multi-dimensional hierarchical networks, which interconnect accelerators through different levels of the network, to dramatically reduce expensive NICs required for the scale-out network. However, it comes at the expense of communication overhead between distributed accelerators to exchange gradients or input/output activation. In order to allow for further scaling of the workloads, communication overhead needs to be minimized. In this paper, we motivate the fact that in training platforms, adding more intermediate network dimensions is beneficial for efficiently mitigating the excessive use of expensive NIC resources. Further, we address different challenges of the DNN training on hierarchical networks. We discuss when designing the interconnect, how to distribute network bandwidth resources across different dimensions in order to (i) maximize BW utilization of all dimensions, and (ii) minimizing the overall training time for the target workload. We then implement a framework that, for a given workload, determines the best network configuration that maximizes performance, or performance-per-cost.
In Situ Detection of Kinetic-size Magnetic Holes in the Martian Magnetosheath

Depression in magnetic field strength with a scale below one proton gyroradius is referred to as a kinetic-size magnetic hole (KSMH). KSMHs are frequently observed near Earth’s space environments and are thought to play an important role in electron energization and energy dissipation in space plasmas. Recently, KSMHs have been evidenced in the Venusian magnetosheath. However, observations of KSMHs in other planetary environments are still lacking. In this study, we present the in situ detection of KSMHs in the Martian magnetosheath using Mars Atmosphere and Volatile EvolutioN (MAVEN) for the first time. The distribution of KSMHs is asymmetry in the southern–northern hemisphere and no obvious asymmetry in the dawn–dusk hemisphere. The observed KSMHs are accompanied by increases in the electron fluxes in the perpendicular direction, indicating the cues of trapped electrons and the formation of electron vortices inside KSMHs. These features are similar to the observations in the Earth’s magnetosheath and magnetotail plasma sheet and the Venusian magnetosheath. This implies that KSMHs are a universal magnetic structure in space.
Untrained Graph Neural Networks for Denoising

A fundamental problem in signal processing is to denoise a signal. While there are many well-performing methods for denoising signals defined on regular domains, including images defined on a two-dimensional pixel grid, many important classes of signals are defined over irregular domains that can be conveniently represented by a graph. This paper introduces two untrained graph neural network architectures for graph signal denoising, develops theoretical guarantees for their denoising capabilities in a simple setup, and provides empirical evidence in more general scenarios. The two architectures differ on how they incorporate the information encoded in the graph, with one relying on graph convolutions and the other employing graph upsampling operators based on hierarchical clustering. Each architecture implements a different prior over the targeted signals. Finally, we provide numerical experiments with synthetic and real datasets that i) asses the denoising behavior predicted by our theoretical results and ii) compare the denoising performance of our architectures with that of existing alternatives.
Beyond Triplet Loss: Meta Prototypical N-Tuple Loss for Person Re-identification

Person Re-identification (ReID) aims at matching a person of interest across images. In convolutional neural network (CNN) based approaches, loss design plays a vital role in pulling closer features of the same identity and pushing far apart features of different identities. In recent years, triplet loss achieves superior performance and is predominant in ReID. However, triplet loss considers only three instances of two classes in per-query optimization (with an anchor sample as query) and it is actually equivalent to a two-class classification. There is a lack of loss design which enables the joint optimization of multiple instances (of multiple classes) within per-query optimization for person ReID. In this paper, we introduce a multi-class classification loss, i.e., N-tuple loss, to jointly consider multiple ($N$) instances for per-query optimization. This in fact aligns better with the ReID test/inference process, which conducts the ranking/comparisons among multiple instances. Furthermore, for more efficient multi-class classification, we propose a new meta prototypical N-tuple loss. With the multi-class classification incorporated, our model achieves the state-of-the-art performance on the benchmark person ReID datasets
Investigation on Heat Transfer in Small Hydrocarbon Rocket Combustion Chambers

Low costs and nonhazardous properties draw interest in application of hydrocarbon fuels in liquid rocket engines. Within this work, results of experiments on heat transfer, film cooling, transpiration cooled and convectively cooled fiber-reinforced ceramics conducted at a kerosene/oxygen rocket combustion chamber test facility are presented. The experimental data serves as the base for design and validation of simple-to-use models and correlations, which allow estimates of heat flux and cooling needs for the preliminary design of hydrocarbon fuel rocket engines.
The Effect of Pulmonary Rehabilitation on Respiratory Functions, and the Quality of Life, following Coronary Artery Bypass Grafting: A Randomised Controlled Study

Objective Examining the effects of a pulmonary rehabilitation (PR) program applied to patients undergoing coronary artery bypass grafting (CABG) surgery with open heart technique on respiratory functions, functional capacity, and quality of life (QoL). Design This randomised controlled study applied the Consolidated Standards of Reporting Trials statement. Methods The study was conducted with two groups: the intervention group (n = 25) and the control group (n = 25). The control group received standard care after coronary artery bypass grafting. On the contrary, the experimental group participated in a PR program created by the researchers in addition to standard care. After coronary artery bypass grafting, the respiratory functions (on the 4th day of clinical care) and QoL (at the 6th week) of both groups were evaluated. The primary outcome measure was the respiratory function (forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and FEV1/FVC). The secondary outcome measure of this study was the QoL. Results When the average pulmonary function test values of the patients were examined, the mean FVC and FEV1 values of the patients in the intervention group on the 4th day of clinical care were significantly higher with a medium level size effect than the control group (p = 0.027; effect size (d) = 0.643; p < 0.024; effect size (d) = 0.658, respectively). At the postoperative 6th week measurement of QoL, a decrease was observed in all subdimensions of the scale, albeit less in the intervention group (p < 0.05). There was a decrease in both the mental and physical component summary of QoL (p < 0.05). Conclusion The results of this study revealed that pulmonary rehabilitation applied to patients who have undergone coronary artery bypass graft recover their functional capacity faster.
Effects of GLP-1 Receptor Agonists on Bone Mineral Density in Patients with Type 2 Diabetes Mellitus: A 52-Week Clinical Study

Introduction Hypoglycemic drugs affect the bone quality and the risk of fractures in patients with type 2 diabetes mellitus (T2DM). We aimed to investigate the effects of glucagon-like peptide-1 receptor agonists (GLP-1RAs) and insulin on bone mineral density (BMD) in T2DM. Methods In this single-blinded study, a total of 65 patients with T2DM were randomly assigned into four groups for 52 weeks: the exenatide group (n = 19), dulaglutide group (n = 19), insulin glargine group (n = 10), and placebo (n = 17). General clinical data were collected, and BMD was measured by dual-energy X-ray absorptiometry. Results Compared with baseline, the glycosylated hemoglobin (HbA1c) decreased significantly in the exenatide (8.11 ± 0.24% vs. 7.40 ± 0.16%, P = 0.007), dulaglutide (8.77 ± 0.37% vs. 7.06 ± 0.28%, P < 0.001), and insulin glargine (8.57 ± 0.24% vs. 7.23 ± 0.25%, P < 0.001) groups after treatment. In the exenatide group, the BMD of the total hip increased. In the dulaglutide group, only the BMD of the femoral neck decreased (P = 0.027), but the magnitude of decrease was less than that in the placebo group; the BMD of L1-L4, femoral neck, and total hip decreased significantly (P < 0.05) in the placebo group, while in the insulin glargine group, the BMD of L2, L4, and L1-4 increased (P < 0.05). Compared with the placebo group, the BMD of the femoral neck and total hip in the exenatide group and the insulin glargine group were increased significantly (P < 0.05); compared with the exenatide group, the BMD of L4 in the insulin glargine group was also increased (P = 0.001). Conclusions Compared with the placebo, GLP-1RAs demonstrated an increase of BMD at multiple sites of the body after treatment, which may not exacerbate the consequences of bone fragility. Therefore, GLP-1RAs might be considered for patients with T2DM. This trial is registered with ClinicalTrials.gov NCT01648582.
Behavioral Activation (BA) in the Management of Depression in an Adolescent with Down Syndrome in Dubai

Depression has been commonly treated with psychotherapy and/or pharmacotherapy for several decades. Ongoing research in the field has suggested promise for behavioral activation (BA), a form of psychotherapeutic intervention, as a means of increasing engagement in adaptive activities and developing skills to counter avoidance in individuals suffering from depression. In this case report, we present the treatment course of BA for an adolescent with Down syndrome (DS), presenting with depression. A multidisciplinary approach was utilized in developing a personalized management plan for the patient since the initial presentation. Sessions at the outpatient psychiatry clinic alternated between in-person visits and virtual ones, due to circumstances associated with physical distancing with the COVID-19 pandemic. Parents were included as integral parts of the management plan, and education, strategic implementation of BA, and barriers to care were discussed extensively to support the adolescent through the course of her treatment. Within 6 weeks of introducing BA, positive outcomes were noted in the patient, with the resolution of her clinical depression. In this report, we discuss BA further as a potentially effective therapeutic approach to the treatment of depressive symptoms in children and adolescents with DS and intellectual disabilities.
Identification of Potential Core Genes in Parkinson's Disease Using Bioinformatics Analysis

Purpose This study aimed to explore new core genes related to the occurrence of Parkinson's disease (PD) and core genes that can lead to the progression of PD. Methods The expression profile data of GSE42966, which contained six substantia nigra tissues isolated from normal individuals and nine substantia nigra tissues isolated from patients with PD, were obtained from Gene Expression Omnibus. Differentially expressed genes (DEGs) were identified, followed by functional enrichment analysis and protein-protein interaction (PPI) network construction. We then identified 10 hub genes and analyzed their expression in different Braak stages. Results A total of 773 DEGs were identified that were significantly enriched in metabolic pathways. Ten hub genes were identified through the PPI network, namely, GNG3, MAPK1, FPR1, ATP5B, GNG2, PRKACA, HRAS, HSPA8, PSAP, and GABBR2. The expression of HRAS was different in patients with PD with Braak stages 3 and 4. Conclusion These 10 hub genes and the metabolic pathways they are enriched in may be involved in the pathogenesis of PD. HRAS may have potential value in predicting the progression of PD.
Effect of Harvesting Ages on Yield and Yield Components of Sugar Cane Varieties Cultivated at Finchaa Sugar Factory, Oromia, Ethiopia

This study was initiated with the objective of determining the effect of different harvesting ages (12, 13, 14, 15, and 16 months) on yield and yield components of selected the two sugar cane varieties (B52/298 and NCo 334) grown in Finchaa sugar factory, Oromia, Ethiopia. A field experiment was conducted at Finchaa sugarcane plantation using a randomized complete block design of a factorial arrangement of 2 × 5 with three replications. The data were performed using SAS version 9.3, and a significant difference was considered at p ≤ 0.05. The results showed that B52/298 variety had a higher estimated recoverable sucrose than NCo 334 variety. The results also indicated that as harvesting ages increase yield, yield components of sugar cane quality are increased. The maximum sugar yield of 1.89-ton ha-1 month-1 was obtained at the harvesting age of 15 months. There was a significant difference (p < 0.05) between harvesting age and sugarcane varieties on cane yield, sugar yield, brix percent juice, pol percent, and recoverable sugar. Generally, the findings imply that as harvesting ages in month increase, brix percent juice, estimated recoverable sucrose, and sucrose percentage in both varieties were simultaneously increased. The findings suggested that B52/298 sugar cane variety with harvesting age between 14 and 16 is highly recommended to obtain optimum sugar cane yield and yield components at the tropical areas of Finchaa sugar factory.
Primary Testis Leiomyosarcoma: A Case Report

Primary leiomyosarcoma in testis is an uncommon tumor with few cases reported. It generally develops after radiotherapy or long-term taking anabolic steroid medication. We report a 53-year-old male patient with primary testis leiomyosarcoma who presented with painless testicular enlargement without any known predisposing factors. Ultrasound revealed a large heterogeneous left testicular solid lesion. Alpha-fetoprotein (AFP) and beta-human chorionic gonadotrophin (beta-HCG) levels in serum were normal. Left radical orchidectomy following with histology assessment established a diagnosis of primary leiomyosarcoma of testis. No data of cancer metastasis was established. The patient didn’t receive any adjuvant therapy. There wasn’t any evidence of recurrence after 1 year follow-up. Leiomyosarcoma must be one of the differential diagnoses of seronegative tumors in testis. The motivation for this paper is the extreme infrequency of the situation and the differential diagnosis by all expansive inguinoscrotal tumors.
A Population Based Study of Liver Function amongst Adults with Hyperuricemia and Gout in the United States

To examine the association between uric acid levels and liver enzyme functions amongst adults with hyperuricemia and gout in the United States. The National Health and Nutrition Examination Survey (NHANES) data from 2007 to 2016 was used to study the research objective. Data were analyzed for descriptive statistics and for differences using the t test, Chi-square test and ANOVA. A regression analysis was performed to determine association between demographics and liver enzymes. A p value of <0.05 or <0.001 was considered statistically significant. A total of 14,946 adults (≥20 yrs.) were included in this study. Sample mean age was 49 ± 0.15 yrs. , and 54% were female. Overall, 15% adults had elevated uric acid levels (≥6.8 mg/dL), men had significantly higher uric acid levels than women (6 mg/dL vs. 4.8 mg/dL). High uric acid levels were associated with more than two times higher odds of elevated ALT, AST and GGT (p < 0.001). Similarly, gender-based target uric acid values were associated with two-fold increased odds of GGT, over one-and-a-half fold higher odds of ALT and AST (p < 0.001). Regression analysis showed significant association between age, gender, race/ethnicity, body mass index, and hypertension and ALT, AST, ALP, total bilirubin and GGT (p < 0.001). Adults with hyperuricemia and gout are most likely to develop liver dysfunctions and suffer associated morbidities. Such patients need to be appropriately monitored and managed for their liver functions and to prevent associated morbidities.
Stereoscopic Visual Perceptual Learning in Seniors

Background: We showed that seniors can improve their stereoscopic ability (stereoacuity) and corresponding reaction time with repetitive training and, furthermore, that these improvements through training are still present even after a longer period of time without training. Methods: Eleven seniors (average age: 85.90 years) trained twice a week for six weeks with dynamic stereoscopic perception training using a vision training apparatus (c-Digital Vision Trainer®). Stereoscopic training was performed in 12 training session (n = 3072) of visual tasks. The task was to identify and select one of four figures (stereoscopic stimuli) that was of a different disparity using a controller. The tests included a dynamic training (showing rotating balls) and a static test (showing plates without movement). Before and after training, the stereoacuity and the corresponding reaction times were identified with the static stereotest in order to determine the individual training success. The changes in respect to reaction time of stereoscopic stimuli with decreasing disparity were calculated. Results: After 6 weeks of training, reaction time improved in the median from 936 arcsec to 511 arcsec. Stereoscopic vision improved from 138 arcsec to 69 arcsec, which is an improvement of two levels of difficulty. After 6 months without training, the improvement, achieved by training, remained stable. Conclusions: In older people, visual training leads to a significant, long-lasting improvement in stereoscopic vision and the corresponding reaction time in seniors. This indicates cortical plasticity even in old age.
Influence of Dental Implant Diameter and Bone Quality on the Biomechanics of Single-Crown Restoration. A Finite Element Analysis

Background: Success of an implant-supported prosthesis is highly dependent on implant diameter and bone quality. The objective of this study is to assess these two variables under axial or 30° angulated loading. Methods: The study was conducted using finite element model simulations of dental implants with an unchanging length of 6.5 mm and varying diameters of Ø3. 3; Ø3. 5; Ø3. 75; Ø4, Ø4. 25 and Ø4. 75 mm. The implants were placed in an axial position and a 2 mm high straight transepithelial (intermediate abutment) was used to perform a single tooth restoration. Four bone quality scenarios, Type IV, III, II or 0-I bone, were simulated from a simplified model of the mandible. A 200N load was applied both axially and at a 30° angle to the occlusal surface of the prosthesis, which was 11 mm above the implant platform, and the equivalent Von Mises stress in the bone was analyzed. Results: The maximum stress value was obtained for the Ø3. 3 implant in Type IV bone (235 MPa), while the lowest value was obtained for the Ø4. 75 implant and in Type 0-I bone (41 MPa). Regardless of the implant diameter, an improvement in bone quality produced a reduction in bone stress. The same effect was observed as the implant diameter was increased, being this effect even more pronounced. Conclusions: Implant diameter has an important effect on bone stress, with a reduction in stress as the implant diameter increases.