Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Sparse Multiple Canonical Correlation Analysis With Application to Imaging (Epi)Genomics Study of Schizophrenia

Finding correlations across multiple data sets in imaging and (epi)genomics is a common challenge. Sparse multiple canonical correlation analysis (SMCCA) is a multivariate model widely used to extract contributing features from each data while maximizing the cross-modality correlation. The model is achieved by using the combination of pairwise covariances between any two data sets. However, the scales of different pairwise covariances could be quite different and the direct combination of pairwise covariances in SMCCA is unfair. The problem of “unfair combination of pairwise covariances” restricts the power of SMCCA for feature selection. In this paper, we propose a novel formulation of SMCCA, called adaptive SMCCA, to overcome the problem by introducing adaptive weights when combining pairwise covariances. Both simulation and real-data analysis show the outperformance of adaptive SMCCA in terms of feature selection over conventional SMCCA and SMCCA with fixed weights. Large-scale numerical experiments show that adaptive SMCCA converges as fast as conventional SMCCA. When applying it to imaging (epi)genetics study of schizophrenia subjects, we can detect significant (epi)genetic variants and brain regions, which are consistent with other existing reports. In addition, several significant brain-development related pathways, e.g., neural tube development, are detected by our model, demonstrating imaging epigenetic association may be overlooked by conventional SMCCA. All these results demonstrate that adaptive SMCCA are well suited for detecting three-way or multiway correlations and thus can find widespread applications in multiple omics and imaging data integration.
Efficient Oblivious Data Structures for Database Services on the Cloud

Database-as-a-service (DBaaS) allows the client to store and manage structured data on the cloud remotely. Despite its merits, DBaaS also brings significant privacy issues. Existing encryption techniques (e.g., SQL-aware encryption) can mitigate privacy concerns, but they still leak information through access patterns, which are vulnerable to statistical inference attacks. Oblivious Random Access Machine (ORAM) can seal such leakages; however, the recent studies showed significant challenges on the integration of ORAM into databases. That is, the direct usage of ORAM on databases is not only costly but also permits very limited query functionalities. In this paper, we propose new oblivious data structures called <italic>Oblivious Matrix Structure</italic> <inline-formula><tex-math notation="LaTeX">$(\mathsf {OMAT})$</tex-math><alternatives><mml:math><mml:mrow><mml:mo>(</mml:mo><mml:mi mathvariant="sans-serif">OMAT</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="hoang-ieq1-2879104.gif"/></alternatives></inline-formula> and <italic>Oblivious Tree Structure</italic> <inline-formula><tex-math notation="LaTeX">$(\mathsf {OTREE})$</tex-math><alternatives><mml:math><mml:mrow><mml:mo>(</mml:mo><mml:mi mathvariant="sans-serif">OTREE</mml:mi><mml:mo>)</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="hoang-ieq2-2879104.gif"/></alternatives></inline-formula>, which allow tree-based ORAM to be integrated into database systems in a more efficient manner with diverse query functionalities supported. <inline-formula><tex-math notation="LaTeX">$\mathsf {OMAT}$</tex-math><alternatives><mml:math><mml:mi mathvariant="sans-serif">OMAT</mml:mi></mml:math><inline-graphic xlink:href="hoang-ieq3-2879104.gif"/></alternatives></inline-formula> provides special ORAM packaging strategies for table structures, which not only offers a significantly better performance but also enables a broad range of query types that may not be efficient in existing frameworks. On the other hand, <inline-formula><tex-math notation="LaTeX">$\mathsf {OTREE}$</tex-math><alternatives><mml:math><mml:mi mathvariant="sans-serif">OTREE</mml:mi></mml:math><inline-graphic xlink:href="hoang-ieq4-2879104.gif"/></alternatives></inline-formula> allows oblivious conditional queries to be performed on tree-indexed databases more efficiently than existing techniques. We implemented our proposed techniques and evaluated their performance on a real cloud database with various metrics, compared with state-of-the-art counterparts.
Potential of oncolytic viruses in the treatment of multiple myeloma

Multiple myeloma (MM) is a clonal malignancy of plasma cells that is newly diagnosed in ~30,000 patients in the US each year. While recently developed therapies have improved the prognosis for MM patients, relapse rates remain unacceptably high. To overcome this challenge, researchers have begun to investigate the therapeutic potential of oncolytic viruses as a novel treatment option for MM. Preclinical work with these viruses has demonstrated that their infection can be highly specific for MM cells and results in impressive therapeutic efficacy in a variety of preclinical models. This has led to the recent initiation of several human trials. This review summarizes the current state of oncolytic therapy as a therapeutic option for MM and highlights a variety of areas that need to be addressed as the field moves forward.
File access extension of test code generation tool for Java programming learning assistant system

To advance Java programming studies, we have developed the Java Programming Learning Assistant System (JPLAS). The test code plays a critical role in verifying the correctness of the source code from a student automatically at the server in the code writing problem in JPLAS. Previously, we proposed the test code generation tool that automatically generates the test code from the given source code containing standard inputs/outputs that novice students are expected to study in advance. In this paper, we extend this tool to handle the source code with file inputs/outputs. By applying the extended tool to three codes containing file inputs/outputs, the correctness of the generated test codes is confirmed.
Smart energy management as a means towards improved energy efficiency

The costs associated with refrigerator equipment often represent more than half of the total energy costs in supermarkets. This presents a good motivation for running these systems efficiently. In this study, we investigate different ways to construct a reference behavior, which can serve as a baseline for judging the performance of energy consumption. We used 3 distinct learning models: Multiple Linear Regression, Random Forests, and Artificial Neural Networks. During our experiments we used a variation of the sliding window method in combination with learning curves. We applied this approach on five different supermarkets, across Portugal. We are able to create baselines using off-the-shelf data mining techniques. Moreover, we found a way to create them based on short term historical data. We believe that our research will serve as a base for future studies, for which we provide interesting directions.
Compatible Basal Area and Number of Trees Estimators from Remeasured Horizontal Point Samples

Compatible groups of estimators for total value at time 1 (VI), survivor growth (S), and ingrowth (I) for use with permanent horizontal point samples are evaluated for the special cases of estimating the change in both the number of trees and basal area. Caveats which should be observed before any one compatible grouping of estimators is chosen for a particular application are given. T HIS WORK EXAMINES THE ATTRIBUTES of the compatible estimators discussed in Roesch et al. (1989) for survivor growth (S), ingrowth (0 and total value at time 1 (Vi) when used to provide estimates for change in basal area and the number of trees. Survivor growth occurs on trees which were above some minimum merchantability limit at both times 1 and 2, while ingrowth is due to trees which were below the merchantability limit at time 1 and above the limit by time 2. In this paper we consider only one merchantability limit at a time and deliberately ignore the possibility of a tree growing out of one merchantability class into a larger merchantability class. Martin (1982) stated, explicitly, the six sample categories of trees possible on remeasured point samples. Two categories, " 0 " and " n " , consist of trees which were " out " (not sampled) at the first measurement and alive, and " in " (sampled) at the second measurement. Trees in the " 0 " category were below the minimum diameter at breast height (dbh), for their time 2 size class, at time 1 and are, therefore, ingrowth trees, while trees in the " n " category were above this minimum dbh and are, therefore, survivor trees. The other four categories included trees which were " in' the point sample at time 1. Ingrowth and survivor trees which were measured at both times fall into the '5 " and " s " categories, respectively. Trees which were " in' and above minimum dbh at the first measurement but die or are cut before the second measurement are sampled as " m " or " c, " respectively. To avoid ambiguity, we will not attach names to these samples (i.e., " ongrowth, " " ingrowth, " " nongrowth, " etc.), as was customary in the past (see, for example, Martin 1982, Iles and Beers 1983). The notation we will use follows that of Martin (1982), as augmented in Roesch et al.
Effects of a 10-Week Introductory Judo Course on Postural Control During a Bilateral Reactionary Gripping Task.

This study examined the effect of a 10-week introductory judo course on postural control during a bilateral reactionary gripping task using different stance conditions. A total of 20 volunteers were divided into experimental (JDO) and control (CON) groups. Countermovement jump was measured and center of pressure variables were evaluated while performing a bilateral reactionary gripping task under different stance conditions during pre- and posttesting. No interactions were observed for the center of pressure variables (p > .05), while both countermovement jump power (+165.4 W; p = .036) and height (+3.5 cm; p = .018) significantly improved in the JDO group following the 10-week course. Results indicate that 10 weeks of an introductory judo course has no effect on postural control while performing a bilateral reactionary gripping task using different stance conditions.
Cottontail Rabbit Papillomavirus (CRPV) Model System to Test Antiviral and Immunotherapeutic Strategies

The cottontail rabbit papillomavirus (CRPV)/rabbit model has proven to be the most versatile pre-clinical model to test antiviral, immunopotentiating and immunotherapeutic strategies for papilloma-virus infections. We have utilized this model for many years and have recently observed significant improvements in the utility of the model. Improvements have included various techniques to infect rabbit skin sites with strains of wild-type and mutant CRPV DNA prepared using standard molecular biological procedures. A better understanding of the virus life cycle in vivo has been gained also from these studies such that we now have several defined strains of CRPV including i) antigenically diverse strains of CRPV, ii) mutant strains of CRPV with reduced growth rates, and iii) mutant strains of CRPV that demonstrate accelerated malignant progression rates. Collectively, these mutant genomes provide laboratories with a powerful pre-clinical model to assess a variety of antiviral therapies. Many of the treatments already tested in the CRPV/rabbit model have shown parallel efficacy against HPV infections in a clinical setting. Some of our recent experiences with the CRPV/rabbit model are outlined in this brief overview.
Rubric system for evaluation of crown preparation performed by dental students

OBJECTIVE This study aimed to investigate the use of an analytic rubric system for the evaluation of all-ceramic crown preparation on the right maxillary central incisor performed by the dental students. MATERIALS AND METHODS Seventy-two-third-year students and 8 faculty members from prosthodontics participated in this double-blind study. The students prepared an ivorine tooth # 11 for all-ceramic crown. The students were given clear instructions regarding the all-ceramic crown preparation and informed about the criteria for the assessment of the preparation. An analytic rubric based on 10-point scale for assessment of various preparation parameters was used by the 8 examiners. Descriptive statistics, ANOVA and post hoc Tukey tests were used for statistical analysis. RESULTS One-way analysis of variance indicated significance amongst the examiners for all the parameters except for time management. The overall mean scoring by examiners was 7.60 ± 1.18, with highest and lowest mean scores for Examiner 1 (8.02 ± 1.06) and Examiner 4 (6.82 ± 1.50), respectively. The highest number of interexaminer variation (difference) in scoring was found for two plane reduction, and the least difference amongst the examiners was observed for finishing of margins and walls of the preparation. Examiner 4 had the highest number of significant difference with the rest of the examiners. The students scored least marks in axial reduction (56.33%) and preservation of adjacent teeth (66.9%). CONCLUSIONS Criteria-based assessment using analytic rubric for crown preparations in pre-clinical fixed prosthodontics is an effective tool for finding the errors/weak areas of dental students.
The neural correlates of morphological complexity processing: Detecting structure in pseudowords

Morphological complexity is a highly debated issue in visual word recognition. Previous neuroimaging studies have shown that speakers are sensitive to degrees of morphological complexity. Two‐step derived complex words (bridging through bridgeN > bridgeV > bridging) led to more enhanced activation in the left inferior frontal gyrus than their 1‐step derived counterparts (running through runV > running). However, it remains unclear whether sensitivity to degrees of morphological complexity extends to pseudowords. If this were the case, it would indicate that abstract knowledge of morphological structure is independent of lexicality. We addressed this question by investigating the processing of two sets of pseudowords in German. Both sets contained morphologically viable two‐step derived pseudowords differing in the number of derivational steps required to access an existing lexical representation and therefore the degree of structural analysis expected during processing. Using a 2 × 2 factorial design, we found lexicality effects to be distinct from processing signatures relating to structural analysis in pseudowords. Semantically‐driven processes such as lexical search showed a more frontal distribution while combinatorial processes related to structural analysis engaged more parietal parts of the network. Specifically, more complex pseudowords showed increased activation in parietal regions (right superior parietal lobe and left precuneus) relative to pseudowords that required less structural analysis to arrive at an existing lexical representation. As the two sets were matched on cohort size and surface form, these results highlight the role of internal levels of morphological structure even in forms that do not possess a lexical representation.
Fast Saddle-Point Algorithm for Generalized Dantzig Selector and FDR Control with Ordered L1-Norm

In this paper we propose a primal-dual proximal extragradient algorithm to solve the generalized Dantzig selector (GDS) estimation problem, based on a new convex-concave saddle-point (SP) reformulation. Our new formulation makes it possible to adopt recent developments in saddle-point optimization, to achieve the optimal $O(1/k)$ rate of convergence. Compared to the optimal non-SP algorithms, ours do not require specification of sensitive parameters that affect algorithm performance or solution quality. We also provide a new analysis showing a possibility of local acceleration to achieve the rate of $O(1/k^2)$ in special cases even without strong convexity or strong smoothness. As an application, we propose a GDS equipped with the ordered $\ell_1$-norm, showing its false discovery rate control properties in variable selection. Algorithm performance is compared between ours and other alternatives, including the linearized ADMM, Nesterov's smoothing, Nemirovski's mirror-prox, and the accelerated hybrid proximal extragradient techniques.
Short oligonucleotide probes containing G-stacks display abnormal binding affinity on Affymetrix microarrays

MOTIVATION In microarray experiments, probe design is critical to the specific and accurate measurement of target concentrations. Current designs select suitable probes through in silico scanning of transcriptome/genome based on first principles. However, due to lack of tools, the observed microarray data have not been used to assess the performance of individual probes to provide feedback to improve future designs. RESULT In this study, we describe a probe performance assessment method based on the concordance of the observed signals from probes that share common targets. Using this method, we found that probes containing multiple guanines in a row (G-stacks) have abnormal binding behavior compared with other probes, both in gene expression assays and genotyping assays using Affymetrix microarrays. These probes are less likely to covary with other probes that interrogate the same genes. Moreover, we found that these probes are much more likely to produce outliers when fitting the observed signals according to the positional dependent nearest neighbor model, which gives reasonable estimates of binding affinity for most other probes. These results suggest that probes containing G-stacks tend to have increased cross hybridization signals and reduced target-specific hybridization signals, presumably due to multiplex binding forming G-quartet structures. Our findings are expected to be useful in microarray design and data analysis.
A systematic review and meta-analysis

Background:Minimally invasive pancreaticoduodenectomy (MIPD) remains one of the most challenging abdominal procedures. Safety and feasibility remain controversial when comparing MIPD with open pancreaticoduodenectomy (OPD). The aim of this systematic review and meta-analysis was to evaluate the feasibility and safety of MIPD versus OPD. Methods: A systematic review of the literature was performed to identify studies comparing MIPD and OPD. Postoperative complications, intraoperative outcomes and oncologic data, and postoperative recovery were compared. Results: There were 27 studies that matched the selection criteria. Totally 1306 cases of MIPD and 5603 cases of OPD were included. MIPD was associated with a reduction in postoperative hemorrhage (odds ratio [OR] 1.60; 95% confidence interval [CI] 1.03–2.49; P= .04) and wound infection (OR 0.44, 95% CI 0.30–0.66, P< .0001). MIPD was also associated with less estimated blood loss (mean difference [MD] 300.14 mL, 95% CI 400.11 to 200.17 mL, P< .00001), a lower transfusion rate (OR 0.46, 95% CI 0.35–0.61; P< .00001) and a shorter length of hospital stay (MD 2.95 d, 95%CI 3.91 to 2.00 d, P< .00001) than OPD. Meanwhile, theMIPD group had a higher R0 resection rate (OR 1.45, 95%CI 1.18–1.78,P= .0003) andmore lymph nodes harvested (MD 1.34, 95% CI 0.14–2.53, P= .03). However, the minimally invasive approach proved to have much longer operative time (MD 71.00minutes; 95% CI 27.01–115.00minutes; P= .002) than OPD. Finally, there were no significant differences between the 2 procedures in postoperative pancreatic fistula (P= .30), delayed gastric emptying (P= .07), bile leakage (P= .98), mortality (P= .88), tumor size (P= .15), vascular resection (P= .68), or reoperation rate (P= .11). Conclusions: Our results suggest that MIPD is currently safe, feasible, and worthwhile. Future large-volume, well-designed randomized controlled trials (RCT) with extensive follow-up are awaited to further clarify this role. Abbreviations: CI = confidence interval, DGE = delayed gastric emptying, EBL = estimated blood loss, ISGPF = International Study Group on Pancreatic Fistula, MD = mean difference, MIPD = minimally invasive pancreaticoduodenectomy, OPD = open pancreaticoduodenectomy, OR = odds ratio, POPF = postoperative pancreatic fistula, RCT = randomized controlled trial.
12 Myocardial Self-Repair and Congenital Heart Disease

In this chapter we will explore the current understanding about the dynamics of myocardial cell populations after birth and how they may contribute to homeostasis and response to injury. Recent investigations of myocardial cell biology have revealed that the heart is not the terminally differentiated organ it was once thought to be. We now know that myocardium contains limited populations of cardiac progenitor cells (CPC) that are capable of generating all myocardial cell types. The changes in myocardial cell populations with time and the role these changes play in neonatal myocardial tissue expansion will be discussed. The contribution of CPC to heart growth and therapeutic strategies for congenital cardiac diseases will be explored.
HBST: A Hamming Distance Embedding Binary Search Tree for Feature-Based Visual Place Recognition

Reliable and efficient visual place recognition is a major building block of modern SLAM systems. Leveraging on our prior work, in this letter, we present a Hamming distance embedding binary search tree (HBST) approach for binary descriptor matching and image retrieval. HBST allows for descriptor search and insertion in logarithmic time by exploiting particular properties of binary descriptors. We support the idea behind our search structure with a thorough analysis on the exploited descriptor properties and their effects on completeness and complexity of search and insertion. To validate our claims, we conducted comparative experiments for HBST and several state-of-the-art methods on a broad range of publicly available datasets. HBST is available as a compact open-source C++ header-only library.
Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research

The purpose of this technical report is two-fold. First of all, it introduces a suite of challenging continuous control tasks (integrated with OpenAI Gym) based on currently existing robotics hardware. The tasks include pushing, sliding and pick & place with a Fetch robotic arm as well as in-hand object manipulation with a Shadow Dexterous Hand. All tasks have sparse binary rewards and follow a Multi-Goal Reinforcement Learning (RL) framework in which an agent is told what to do using an additional input. The second part of the paper presents a set of concrete research ideas for improving RL algorithms, most of which are related to Multi-Goal RL and Hindsight Experience Replay.
Exploring Hidden Dimensions in Parallelizing Convolutional Neural Networks

The past few years have witnessed growth in the size and computational requirements for training deep convolutional neural networks. Current approaches parallelize the training process onto multiple devices by applying a single parallelization strategy (e.g., data or model parallelism) to all layers in a network. Although easy to reason about, this design results in suboptimal runtime performance in large-scale distributed training, since different layers in a network may prefer different parallelization strategies. In this paper, we propose layer-wise parallelism that allows each layer in a network to use an individual parallelization strategy. We jointly optimize how each layer is parallelized by solving a graph search problem. Our experiments show that layer-wise parallelism outperforms current parallelization approaches by increasing training speed, reducing communication costs, achieving better scalability to multiple GPUs, while maintaining the same network accuracy.