Miracle-dz/UniFAR-FTUs huggingface dataset:
See-your-room: indoor localization with camera vision

Indoor Localization has attracted much research effort recently. Most existing approaches require pre-deployed comprehensive location services and, more importantly, rely on dedicatedly installed infrastructure. This incurs a high deployment, maintenance and usage overhead. We present See-Your-Room, a precise and robust localization approach with public cameras which are already existed in today's buildings. Computer Vision systems, however, are difficult to achieve people's position directly from photos. To detect people in the room and achieve their poses efficiently, we combine detection method with pose estimation method. To transform people's position in the photos which are taken by public camera to the indoor map, we use projection transformation with four pairs of points. We implement See-Your-Room on commercial cameras, say ceiling cameras in three diverse rooms. The evaluation results show that See-Your-Room achieves an immediate detection success rate of 90% and an average localization error of 14.32cm in 3D environment.1
Speaker Recognition Using Kernel K-mean Clustering and SVM

We proposed a novel approach that is based on the kernel K-means clustering and support vector machine(SVM),set up a support vector machine for each two speakers,here kernel K-means clustering is exploited to input speech signal of SVM into a given amount of clusters choosing the effective samples as the input of SVM.In this paper,we proposed approach acquiring the effective of clustering and reduction of speech data,and it greatly improved recognition rate.The experimental results show the proposed approach performances are better than tradition approaches in the SVM as classier.
Finding Minimal d-separators in Linear Time and Applications

The study of graphical causal models is fundamentally the study of separations and conditional independences. We provide linear-time algorithms for two graphical primitives: to test, if a given set is a minimal d -separator, and to ﬁnd a minimal d -separator in directed acyclic graphs (DAGs), completed partially directed acyclic graphs (CPDAGs) and restricted chain graphs (RCGs) as well as minimal m - separators in ancestral graphs (AGs). These algorithms improve the runtime of the best previously known algorithms for minimal separators that are based on moralization and thus require quadratic time to construct and handle the moral graph. (Minimal) separating sets have important applications like ﬁnding (minimal) covariate adjustment sets or conditional instrumental variables.
Guaranteed Scalable Learning of Latent Tree Models

Author(s): Huang, Furong; Niranjan, UN; Perros, Ioakeim; Chen, Robert; Sun, Jimeng; Anandkumar, Anima | Abstract: We present an integrated approach for structure and parameter estimation in latent tree graphical models. Our overall approach follows a "divide-and-conquer" strategy that learns models over small groups of variables and iteratively merges onto a global solution. The structure learning involves combinatorial operations such as minimum spanning tree construction and local recursive grouping; the parameter learning is based on the method of moments and on tensor decompositions. Our method is guaranteed to correctly recover the unknown tree structure and the model parameters with low sample complexity for the class of linear multivariate latent tree models which includes discrete and Gaussian distributions, and Gaussian mixtures. Our bulk asynchronous parallel algorithm is implemented in parallel and the parallel computation complexity increases only logarithmically with the number of variables and linearly with dimensionality of each variable.
Spatial Opacity Maps for Direct Volume Rendering of Regions of Interest

Despite the mature state of the volume rendering field, its adoption in medical applications is hindered by its complex parametrization and control, and 2D slice based tools are still preferred for clinical workflows. In this paper, we introduce the concept of spatial opacity maps as an interactive tool for exploring volumetric data focusing on the rendering of features of interest. In a region growing fashion, the maps are dynamically created from a user input on the 2D slices, taking into account not only the density values of the structure but also the topology. Using this approach, an inexperienced user is able to generate meaningful 3D renderings with no need to tweak non-intuitive visualization parameters. The spatial opacity maps are independent of the current visualization parameters and they can be easily plugged into the volume rendering integral and combined with other approaches for region of interest (ROI) visualization. We combine our approach with a simple automatic transfer function generation algorithm to improve the visualization of the contextual data.
Broad-Spectrum Antibacterial Characteristics of Four Novel Borate-Based Bioactive Glasses

Bioactive glasses have been developed for medical applications in the body for bone and tissue repair and regeneration. We have developed a borate-containing bioactive glass (13-93B3, referred to as B3), which is undergoing clinical trials to assess its wound-healing properties. To complement the healing properties of B3, metal ion dopants have been added to enhance its antimicrobial properties. Bioactive glasses doped with silver, gallium or iodine ions were found to have broad spectrum antimicrobial effects on clinically relevant bacteria including MRSA. While the B3 glass alone was sufficient to produce antibacterial effects on select bacteria, adding dopants enhanced the broad-spectrum antibacterial properties: Live-Dead staining fluorescence microscopy suggests cell membrane integrity is disrupted in gram positive bacteria exposed to the glass compounds, but not gram negative bacteria, indicating multiple mechanisms of action for each glass formulation.
Performance Enhancement of Metaframeworks Through Metagrammars

This paper describes techniques for improving the performance of meta framework developed by combining C++ and Java language segments. Augmented versions of existing languages can be developed by combining good properties of those languages. It increases the flexibility of programmers in using language constructs of those languages. The framework identifies and parses source code with C++ and Java language statements using metagrammar developed and create a unified AST for the hybrid source code. Bytecodes are generated for AST and interpreted. The performance of Bytecodes can be improved through optimization techniques associated with metagrammars, like constant propagation which identifies constant values for vari- ables and propagate it to the place where the variable occurs and replace it with corresponding value. Function inlining and exception optimization greatly improves the execution time performance of Bytecodes. Optimiza- tion through metagrammars eliminates rigorous analysis of bytecodes to identify hot spots and optimize them.
Improvement for Migration Operator in Biogeography-Based Optimization Algorithm

In original biogeography-based optimization ( BBO ) ,the migration and mutation operators are applied to evolve the population. BBO is often used to solve single-objective optimization problems. When the original migration operator of BBO is applied to solve continuous multi-objective optimization problems,the diversity of the population is decreased sharply. In this paper,the migration operator of BBO is developed and the perturbation factor is introduced to increase the diversity of the population. Thus,a biogeography-based multi-objective evolutionary algorithm ( BBMOEA) is proposed. Compared with the algorithm under the action of the original migration operator on benchmark test problems,the simulation results illustrate the effectiveness and efficiency of the developed migration operator. Meanwhile,compared with SPEA 2 and NSGA-Ⅱ,the experimental results show that the solution set gained by algorithm BBMOEA has good convergence and even distribution.
Improvement of decoding engine & phonetic decision tree in acoustic modeling for online large vocabulary conversational speech recognition

In this work, new approaches are proposed for online large vocabulary conversational speech recognition, including a fast confusion network algorithm, novel features and a Random Forests based classifier for word confidence annotation, new improvements in speech decoding speed and latency, novel lookahead phonetic decision tree state tying and Random Forests of phonetic decision tree state tying for acoustic modeling of speech sound units. The fast confusion network algorithm significantly improves the time complexity from O(T) to O(T), with T equaling the number of links in a word lattice. Several novel features, as well as Random Forests based classification technique are proposed to improve word annotation accuracy for automatic captioning. In order to improve the speed of speech decoding engine, we propose to use complementary word confidence scores to prune uncompetitive search paths, and use subspace distribution clustering hidden Markov modeling to speed up computation of acoustic scores and local confidence scores. We further integrate pre-backtrace in decoding search to significantly reduce captioning latency. In this work we also investigate novel approaches to improve the performance of phonetic decision tree state tying, including two lookahead methods and a Random Forests method. Constrained lookahead method finds an optimal question among n pre-selected questions for each split node to decrease effects of outliers, and it also discounts the contributions of likelihood gains by deeper decedents. Stochastic full lookahead method uses sub-tree size instead of likelihood gain as a measure for phonetic question selection, in order to produce small trees with better generalization capability and consistent with training data. The Random Forests method uses an ensemble of phonetic decision trees to derive a single strong model for each speech unit. We investigate several methods of combining the acoustic scores from multiple models obtained from multiple phonetic decision trees in decoding search. We further propose clustering methods to compact the Random Forests generated acoustic models to speed up decoding search.
Social support and depression among community dwelling older adults in Asia: a systematic review

Objectives This review aims to: (1) explore the social support measures in studies examining the association between social support and depression among community-dwelling older adults in Asia and (2) the evidence of association. Design A systematic review was conducted using electronic databases of CINAHL, PubMed, PsychINFO, Psychology and Behavioural Sciences Collection, SocINDEX and Web of Science for articles published until the 11th of January 2018. Eligibility criteria All observational studies investigating the association between social support and depression among community-dwelling older adults in Asia were included. Participants Older adults aged 60 years and more who are living in the community. Exposure measures Social support. Outcome measures Depression. Results We retrieved16 356 records and screened 66 full-text articles. Twenty-four observational studies were included in the review. They consisted of five cohort studies and 19 cross-sectional studies. Social support was found to be measured by multiple components, most commonly through a combination of structural and functional constructs. Perceived social support is more commonly measured compared with received social support. Good overall social support, having a spouse or partner, living with family, having a large social network, having more contact with family and friends, having emotional and instrumental support, good support from family and satisfaction with social support are associated with less depressive symptoms among community-dwelling older adults in Asia. Conclusions There were 20 different social support measures and we applied a framework to allow for better comparability. Our findings emphasised the association between good social support and decrease depression among older adults. Compared with western populations, family support has a greater influence on depression among community-dwelling older adults in Asia. This indicates that the family institution needs to be incorporated into designed programmes and interventions when addressing depression in the Asian context. Trial registration number CRD42017074897.
CD8+ T-cells Negatively Regulate Inflammation Post-Myocardial Infarction.

The adaptive immune response is key for cardiac wound healing post-myocardial infarction (MI) despite low T-cell numbers. We hypothesized that CD8+ T-cells regulate the inflammatory response leading to decreased survival and cardiac function post-MI. We performed permanent occlusion of the left anterior descending coronary artery on C57BL/6J and CD8atm1Mak mice (deficient in functional CD8+ T-cells). CD8atm1Mak had increased survival at 7 days post-MI compared to that of the WT, and improved cardiac physiology at day 7 post-MI. Despite having less mortality, 100% of the CD8atm1Mak group died due to cardiac rupture compared to only 33% of the WT. Picrosirius red staining and collagen immunoblotting indicated an acceleration of fibrosis in the infarct area as well as remote area in the CD8atm1Mak mice; however, this increase was due to elevated soluble collagen implicating poor scar formation. Plasma and tissue inflammation was exacerbated as indicated by higher levels of Cxcl1, Ccl11, MMP-2 and -9. Immunohistochemistry and flow cytometry indicated that CD8atm1Mak group had augmented numbers of neutrophils and macrophages at post-MI day 3 and increased mast cell markers at post-MI day 7. Cleavage of MerTK was increased in the CD8tm1Mak mice resulting in delayed removal of necrotic tissue. In conclusion, despite having improved cardiac physiology and overall survival, CD8atm1Mak mice had increased innate inflammation and poor scar formation leading to higher incidence of cardiac rupture. Our data suggest that the role of CD8+ T-cells in post-MI recovery may be both beneficial and detrimental to cardiac remodeling and is mediated via a cell-specific mechanism.
Mitochondria in the biology, pathogenesis, and treatment of hepatitis virus infections

Hepatitis virus infections affect a large proportion of the global population. The host responds rapidly to viral infection by orchestrating a variety of cellular machineries, in particular, the mitochondrial compartment. Mitochondria actively regulate viral infections through modulation of the cellular innate immunity and reprogramming of metabolism. In turn, hepatitis viruses are able to modulate the morphodynamics and functions of mitochondria, but the mode of actions are distinct with respect to different types of hepatitis viruses. The resulting mutual interactions between viruses and mitochondria partially explain the clinical presentation of viral hepatitis, influence the response to antiviral treatment, and offer rational avenues for novel therapy. In this review, we aim to consider in depth the multifaceted interactions of mitochondria with hepatitis virus infections and emphasize the implications for understanding pathogenesis and advancing therapeutic development.
Feasibility and cardiac synchrony of permanent left bundle branch pacing through the interventricular septum.

AIMS Left bundle branch pacing (LBBP) recently emerges as a novel pacing modality. We aimed to evaluate the feasibility and cardiac synchrony of permanent LBBP in bradycardia patients. METHODS AND RESULTS Left bundle branch pacing was successfully performed in 56 pacemaker-indicated patients with normal cardiac function. Left bundle branch pacing was achieved by penetrating the interventricular septum (IVS) into the left side sub-endocardium with the pacing lead. His-bundle pacing (HBP) was successfully performed in another 29 patients, 19 of whom had right ventricular septal pacing (RVSP) for backup pacing. The QRS duration, left ventricular (LV) activation time (LVAT), and mechanical synchrony using phase analysis of gated SPECT myocardial perfusion imaging were evaluated. Paced QRS duration in LBBP group was significantly shorter than that in RVSP group (117.8 ± 11.0 ms vs. 158.1 ± 11.1 ms, P < 0.0001) and wider than that in HBP group (99.7 ± 15.6 ms, P < 0.0001). Left bundle branch potential was recorded during procedure in 37 patients (67.3%). Left bundle branch pacing patients with potential had shorter LVAT than those without potential (73.1 ± 11.3 ms vs. 83.2 ± 16.8 ms, P = 0.03). Left bundle branch pacing patients with potential had similar LV mechanical synchrony to those in HBP group. R-wave amplitude and capture threshold of LBBP were 17.0 ± 6.7 mV and 0.5 ± 0.1 V, respectively at implant and remained stable during a mean follow-up of 4.5 months without lead-related complications. CONCLUSION Permanent LBBP through IVS is safe and feasible in bradycardia patients. Left bundle branch pacing could achieve favourable cardiac electrical and LV mechanical synchrony.
The Altered Transcriptome and DNA Methylation Profiles of Docetaxel Resistance in Breast Cancer PDX Models

Taxanes are standard therapy in clinical practice for metastatic breast cancer; however, primary or acquired chemoresistance are a common cause of mortality. Breast cancer patient-derived xenografts (PDX) are powerful tools for the study of cancer biology and drug treatment response. Specific DNA methylation patterns have been associated to different breast cancer subtypes but its association with chemoresistance remains unstudied. Aiming to elucidate docetaxel resistance mechanisms, we performed genome-wide DNA methylation in breast cancer PDX models, including luminal and triple-negative breast cancer (TNBC) models sensitive to docetaxel, their matched models after emergence of chemoresistance and residual disease after short-term docetaxel treatment. We found that DNA methylation profiles from breast cancer PDX models maintain the subtype-specific methylation patterns of clinical samples. Two main DNA methylation clusters were found in TNBC PDX and remain stable during the emergence of docetaxel resistance; however, some genes/pathways were differentially methylated according to docetaxel response. A DNA methylation signature of resistance able to segregate TNBC based on chemotherapy response was identified. Transcriptomic profiling of selected sensitive/resistant pairs and integrative analysis with methylation data demonstrated correlation between some differentially methylated and expressed genes in docetaxel-resistant TNBC PDX models. Multiple gene expression changes were found after the emergence of docetaxel resistance in TNBC. DNA methylation and transcriptional changes identified between docetaxel-sensitive and -resistant TNBC PDX models or residual disease may have predictive value for chemotherapy response in TNBC. Implications: Subtype-specific DNA methylation patterns are maintained in breast cancer PDX models. While no global methylation changes were found, we uncovered differentially DNA methylated and expressed genes/pathways associated with the emergence of docetaxel resistance in TNBC.
Children with Tourette Syndrome in the United States: Parent-Reported Diagnosis, Co-Occurring Disorders, Severity, and Influence of Activities on Tics.

OBJECTIVE Describe the diagnostic process for Tourette syndrome (TS) based on parent report, as well as TS severity and associated impairment; the influence of common daily activities on tics; and the presence of co-occurring mental, behavioral, and developmental disorders among children in the United States. METHODS Parent-report data from the 2014 National Survey of the Diagnosis and Treatment of ADHD and Tourette Syndrome on 115 children ever diagnosed with TS were analyzed. Descriptive, unweighted analyses included frequencies and percentages, and means and standard deviations. Fisher's exact test and t-tests were calculated to determine statistically significant differences. RESULTS The mean age that tics were first noticed was 6.3 years, and, on average, TS was diagnosed at 7.7 years. The time from initially noticing tics to TS diagnosis averaged 1.7 years. The mean age when TS symptoms were most severe was 9.3 years. Tic severity was associated with impaired child functioning but not tic noticeability. Almost 70% of parents reported that fatigue and major transitions made their child's tics worse. Children with ever-diagnosed TS had a mean of 3.2 ever-diagnosed co-occurring mental, behavioral, or developmental disorders; a quarter (26.9%) had 5 or more co-occurring disorders. DISCUSSION In this sample of children with TS, the time to diagnosis averaged less than 2 years from when tics were initially noticed. More severe TS was associated with greater functional impairment, and co-occurring disorders were common among children with TS. This study provides insight into the current experiences of children with TS in the United States and their families.
Hepatocellular carcinoma ≤ 4 cm treated with radiofrequency ablation with or without percutaneous ethanol injection.

BACKGROUND To compare the survival of Chinese cirrhotic patients with hepatocellular carcinoma (HCC) ≤ 4 cm who underwent radiofrequency ablation (RFA) alone or a combination of RFA with percutaneous ethanol injection (PEI). MATERIAL AND METHODS Retrospective analysis was performed for 681 cases with HCC ≤ 4 cm who were treated with RFA alone or RFA combined with PEI (RFA + PEI) between 2004 and 2011. RESULTS As a result, 180 patients in each group were selected after propensity score matching (PSM). Higher overall survival (OS) and recurrence-free survival (RFS) rates were achieved by RFA + PEI compared with RFA alone (P = 0.019 and 0.009, respectively). The 1-, 3-, and 5-year cumulative OS rates were 78.0, 44.4, and 30.1% for patients in RFA group and 88.2, 58.0, and 41.1% for patients in RFA + PEI group, respectively. Besides, the 1-, 3-, and 5-year cumulative RFS rates were 77.0, 43.8, and 29.2% in RFA group, and 87.9, 57.6, and 38.4% in RFA + PEI group, respectively. The local recurrence, complete ablation and five-year mortality showed no distinct differences between RFA and RFA + PEI groups in three subgroups classified with tumor size. Moreover, Cox regression multivariate analysis results showed that sex and treatment approach were significantly related to OS, whereas sex, status of HBsAg, local recurrence, and number of tumor nodule were related to RFS. CONCLUSION Therefore, the combination of RFA and PEI yielded better OS and RFS rates than RFA alone for Chinese patients with HCC ≤ 4 cm.
The effect of constant-intensity endurance training and high-intensity interval training on aerobic and anaerobic parameters in youth

ABSTRACT Introduction: High-Intensity Interval Training (HIIT) and Constant-Intensity Endurance Training (CIET) improves peak oxygen uptake (V̇O2) similarly in adults; but in children this remains unclear, as does the influence of maturity. Methods: Thirty-seven boys formed three groups: HIIT (football; n = 14; 14.3 ± 3.1 years), CIET (distance runners; n = 12; 13.1 ± 2.5 years) and a control (CON) group (n = 11; 13.7 ± 3.2 years). Peak V̇O2 and gas exchange threshold (GET) were determined from a ramp test and anaerobic performance using a 30 m sprint pre-and-post a three-month training cycle. Results: The HIIT groups peak V̇O2 was significantly higher than the CON group pre (peak V̇O2: 2.54 ± 0.63 l·min-1 vs 2.03 ± 0.53 l·min-1, d = 0.88; GET: 1.41 ± 0.26 l·min-1 vs 1.13 ± 0.29 l·min-1, d = 1.02) and post-training (peak V̇O2: 2.63 ± 0.73 l·min-1 vs 2.08 ± 0.64 l·min-1, d = 0.80; GET: 1.32 ± 0.33 l·min-1 vs 1.15 ± 0.38 l·min-1, d = 0.48). All groups showed a similar magnitude of change during the training (p > 0.05). Conclusion: HIIT was not superior to CIET for improving aerobic or anaerobic parameters in adolescents. Secondly, pre- and post-pubertal participants demonstrated similar trainability.