Miracle-dz/UniFAR-FTUs huggingface dataset:
Simultaneous Codeword Optimization (SimCO) for Dictionary Update and Learning

We consider the data-driven dictionary learning problem. The goal is to seek an over-complete dictionary from which every training signal can be best approximated by a linear combination of only a few codewords. This task is often achieved by iteratively executing two operations: sparse coding and dictionary update. The focus of this paper is on the dictionary update step, where the dictionary is optimized with a given sparsity pattern. We propose a novel framework where an arbitrary set of codewords and the corresponding sparse coefficients are simultaneously updated, hence the term simultaneous codeword optimization (SimCO). The SimCO formulation not only generalizes benchmark mechanisms MOD and K-SVD, but also allows the discovery that singular points, rather than local minima, are the major bottleneck of dictionary update. To mitigate the problem caused by the singular points, regularized SimCO is proposed. First and second order optimization procedures are designed to solve regularized SimCO. Simulations show that regularization substantially improves the performance of dictionary learning.
GaN Power Transistors on Si Substrates for Switching Applications

In this paper, GaN power transistors on Si substrates for power switching application are reported. GaN heterojunction field-effect transistor (HFET) structure on Si is an important configuration in order to realize a low loss and high power devices as well as one of the cost-effective solutions. Current collapse phenomena are discussed for GaN-HFETs on Si substrate, resulting in suppression of the current collapse due to using the conducting Si substrate. Furthermore, attempts for normally off GaN-FETs were examined. A hybrid metal-oxide-semiconductor HFET structure is a promising candidate for obtaining devices with a lower on-resistance (Ron) and a high breakdown voltage (Vb).
Acceleration of sequence kernel computation for real-time speaker identification

The sequence kernel has been shown to be a promising kernel function for learning from sequential data such as speech and DNA. However, it is not scalable to massive datasets due to its high computational cost. In this paper, we propose a method of approximating the sequence kernel that is shown to be computationally very efficient. More specifically, we formulate the problem of approximating the sequence kernel as the problem of obtaining a pre-image in a reproducing kernel Hilbert space. The effectiveness of the proposed approximation is demonstrated in text-independent speaker identification experiments with 10 male speakers—our approach provides significant reduction in computation time with limited performance degradation. Based on the proposed method, we develop a real-time kernel-based speaker identification system using Virtual Studio Technology (VST).
MiR-34a Expression Has an Effect for Lower Risk of Metastasis and Associates with Expression Patterns Predicting Clinical Outcome in Breast Cancer

MiR-34a acts as a candidate tumour suppressor gene, and its expression is reduced in several cancer types. We aimed to study miR-34a expression in breast cancer and its correlation with tumour characteristics and clinical outcome, and regulatory links with other genes. We analysed miR-34a expression in 1,172 breast tumours on TMAs. 25% of the tumours showed high, 43% medium and 32% low expression of miR-34a. High miR-34a expression associated with poor prognostic factors for breast cancer: positive nodal status (p = 0.006), high tumour grade (p<0.0001), ER-negativity (p = 0.0002), HER2-positivity (p = 0.0002), high proliferation rate (p<0.0001), p53-positivity (p<0.0001), high cyclin E (p<0.0001) and γH2AX (p<0.0001). However, multivariate analysis adjusting for conventional prognostic factors indicated that high miR-34a expression in fact associated with a lower risk of recurrence or death from breast cancer (HR = 0.63, 95% CI = 0.41–0.96, p = 0.031). Gene expression analysis by differential miR-34a expression revealed an expression signature with an effect on both the 5-year and 10-year survival of the patients (p<0.001). Functional genomic analysis highlighted a novel regulatory role of the transcription factor MAZ, apart from the known control by p53, on the expression of miR-34a and a number of miR-34a targets. Our findings suggest that while miR-34a expression activation is a marker of aggressive breast tumour phenotype it exerts an independent effect for a lower risk of recurrence or death from breast cancer. We also present an expression signature of 190 genes associated with miR-34a expression. Our analysis for regulatory loops suggest that MAZ and p53 transcription factors co-operate in modulating miR-34a, as well as miR-34a targets involved in several cellular pathways. Taken together, these results suggest that the network of genes co-regulated with and targeted by miR-34a form a group of down-stream effectors that maybe of use in predicting clinical outcome, and that highlight novel regulatory mechanisms in breast cancer.
Type 2 diabetes in the Hispanic or Latino population: challenges and opportunities

Purpose of reviewTo describe how type 2 diabetes affects the Latino or Hispanic population in the United States, and identify the multiple challenges and opportunities to improve diabetes care in this rapidly growing group. Recent findingsThree compelling reasons justify the work in this area. First, this group has become the largest minority in the country, representing 13.7% of the total population. Based on current growth rates, one in four individuals will be of Hispanic origin by the year 2050. Second, this population suffers from very high rates of type 2 diabetes, obesity, the metabolic syndrome and their multiple vascular complications. A genetic tendency to develop insulin resistance and abdominal obesity, along with multiple nutritional, lifestyle, socio-economic and cultural factors, influence the development and course of type 2 diabetes among Latinos. Third, Hispanics have lagged behind in their diabetes care when compared with the predominant non-Hispanic White population. SummaryUnderstanding the challenges and opportunities in Latinos with diabetes is necessary to develop and implement comprehensive culturally oriented diabetes care, education, outreach and research programs. Some of these strategies may also be beneficial for other groups and can contribute to better integrate our societies.
Effects of N-acetylcysteine plus deferoxamine in lipopolysaccharide-induced acute lung injury in the rat*

Objectives:Interventions that reduce the generation or the effects of reactive oxygen species exert controversial effects in animal models of lung injury, and these could be secondary to the pro-oxidant effects of antioxidants generally by their interaction with iron. We here describe the effects of N-acetylcysteine, deferoxamine, or both in the treatment of acute lung injury induced by intratracheal lipopolysaccharide injection. Design:Prospective, randomized, controlled experiment. Setting:Animal basic science laboratory. Subjects:Male Wistar rats, weighing 200–250 g. Interventions:Rats exposed intratracheally to lipopolysaccharide were treated with N-acetylcysteine (20 mg/kg subcutaneously 3, 6, and 12 hrs after lipopolysaccharide instillation), deferoxamine (20 mg/kg subcutaneously 3 hrs after lipopolysaccharide instillation), N-acetylcysteine (20 mg/kg, 3, 6, and 12 hrs after lipopolysaccharide instillation) plus deferoxamine (20 mg/kg 3 hrs after lipopolysaccharide instillation), or vehicle. Measurements and Main Results:Acute lung injury was induced by intratracheal instillation of lipopolysaccharide in Wistar rats. The animals were randomly divided into five groups: group 1, control with instillation of isotonic saline; group 2, lipopolysaccharide treated with saline; group 3, lipopolysaccharide treated with N-acetylcysteine; group 4, lipopolysaccharide treated with deferoxamine; and group 5, lipopolysaccharide treated with N-acetylcysteine plus deferoxamine. Several times after lipopolysaccharide instillation, the rats were killed and a bronchoalveolar lavage was performed to determine thiobarbituric acid reactive species, protein carbonyls, superoxide dismutase and catalase activities, mitochondrial superoxide production (oxidative stress variables), the degree of the alveolar-capillary membrane compromise, and inflammatory infiltration. Samples from the lung were isolated and assayed for oxidative stress variables or histopathologic analyses. N-acetylcysteine plus deferoxamine decreased bronchoalveolar lavage fluid protein, inflammatory cells, oxidative damage variables, and proinflammatory cytokines. N-acetylcysteine plus deferoxamine treatment significantly attenuated lung oxidative damage, mitochondrial superoxide production, and histopathologic alterations after lipopolysaccharide instillation. Conclusions:Our data provide the first experimental demonstration that N-acetylcysteine plus deferoxamine decreases oxidative stress and mitochondrial dysfunction and limits inflammatory response and alveolar pathology induced by lipopolysaccharide in the rat.
The Child Affective Facial Expression (CAFE) set: validity and reliability from untrained adults

Emotional development is one of the largest and most productive areas of psychological research. For decades, researchers have been fascinated by how humans respond to, detect, and interpret emotional facial expressions. Much of the research in this area has relied on controlled stimulus sets of adults posing various facial expressions. Here we introduce a new stimulus set of emotional facial expressions into the domain of research on emotional development—The Child Affective Facial Expression set (CAFE). The CAFE set features photographs of a racially and ethnically diverse group of 2- to 8-year-old children posing for six emotional facial expressions—angry, fearful, sad, happy, surprised, and disgusted—and a neutral face. In the current work, we describe the set and report validity and reliability data on the set from 100 untrained adult participants.
Complexity of irreducibility testing for a system of linear ordinary differential equations

Let a system of linear ordinary differential equations of the first order <italic>Y</italic>′ = <italic>AY</italic> be given, where <italic>A</italic> is <italic>n</italic> × <italic>n</italic> matrix over a field <italic>F</italic>(<italic>X</italic>), assume that the degree deg<subscrpt><italic>X</italic></subscrpt>(<italic>A</italic>) < <italic>d</italic> and the size of any coefficient occurring in <italic>A</italic> is at most <italic>M</italic>. The system <italic>Y</italic>′ = <italic>AY</italic> is called reducible if it is equivalent (over the field <italic>F</italic>(<italic>X</italic>)) to a system <italic>Y</italic>&prime<subscrpt>1</subscrpt> = <italic>A</italic><subscrpt>1</subscrpt><italic>Y</italic><subscrpt>1</subscrpt> with a matrix <italic>A</italic><subscrpt>1</subscrpt> of the form <italic>A</italic><subscrpt>1</subscrpt> = (<italic>A</italic><subscrpt>1,1</subscrpt> 0) (<italic>A</italic><subscrpt>2,1</subscrpt> <italic>A</italic><subscrpt>2,2</subscrpt>) An algorithm is described for testing irreducibility of the system with the running time exp(<italic>M</italic>(<italic>d2<supscrpt>n</supscrpt></italic>)<italic><supscrpt>d2<supscrpt>n</supscrpt></supscrpt></italic>).
Analysis of Rainfall Data based on GSMaP and TRMM towards Observations Data in Yogyakarta

In reality, to obtain a complete and representative rainfall observations data in a particular area is quite difficult. Therefore, to complement the existence of rainfall data, satellite data is used, so the rainfall data can got by us for a region that has limited equipment, then the characteristics of rainfall can knew by us in that region. The purpose of this study is to analyzed the validity of GSMaP (Global Satellite Mapping of Precipitation) and TRMM (Tropical Rainfall Measuring Mission) data with in-situ rainfall data in Yogyakarta during the period (2012-2016). The method used is to process GSMaP and TRMM data into daily, decade, monthly, and seasonal data to compare with in situ data and perform statistical tests. Based on the results it can be seen that during the observation period for DJF (December-January-February), the highest GSMaP and TRMM rainfall correlations occur in decade-1 and decade-3 respectively. In MAM (March-April-May), GSMaP (decade-2) and TRMM (decade-1), while in JJA (June-July-August) for GSMaP (decade-2) and TRMM (decade-3), and in SON (September-October-November) for GSMaP (decade-3) and TRMM (decade-2). Therefore it can be concluded that the correlation between GSMaP and TRMM with in situ data, the best occurs on average in decade-2 and decade-3.
IITD-IBMIRL System for Question Answering Using Pattern Matching, Semantic Type and Semantic Category Recognition

A Question Answering (QA) system aims to return exact answers to natural language questions. While today information retrieval techniques are quite successful at locating within large collections of documents those that are relevant to a user’s query, QA techniques that extract the exact answer from these retrieved documents still do not obtain very good accuracies. We approached the TREC 2007 Question Answering task as a semantics based question to answer matching problem. Given a question we aimed to extract the relevant semantic entities in it so that we can pin-point the answer. In this paper we show that our technique obtains reasonable accuracy compared to other systems.
Conformational Dynamics and Antigenicity in the Disordered Malaria Antigen Merozoite Surface Protein 2

Merozoite surface protein 2 (MSP2) of Plasmodium falciparum is an abundant, intrinsically disordered protein that is GPI-anchored to the surface of the invasive blood stage of the malaria parasite. Recombinant MSP2 has been trialled as a component of a malaria vaccine, and is one of several disordered proteins that are candidates for inclusion in vaccines for malaria and other diseases. Nonetheless, little is known about the implications of protein disorder for the development of an effective antibody response. We have therefore undertaken a detailed analysis of the conformational dynamics of the two allelic forms of MSP2 (3D7 and FC27) using NMR spectroscopy. Chemical shifts and NMR relaxation data indicate that conformational and dynamic properties of the N- and C-terminal conserved regions in the two forms of MSP2 are essentially identical, but significant variation exists between and within the central variable regions. We observe a strong relationship between the conformational dynamics and the antigenicity of MSP2, as assessed with antisera to recombinant MSP2. Regions of increased conformational order in MSP2, including those in the conserved regions, are more strongly antigenic, while the most flexible regions are minimally antigenic. This suggests that modifications that increase conformational order may offer a means to tune the antigenicity of MSP2 and other disordered antigens, with implications for vaccine design.
Guest Editorial Body Sensor Networks: From Theory to Emerging Applications

The use of sensor networks for healthcare, well-being, and working in extreme environments has long roots in the engineering sector in medicine and biology community. With the maturity of wireless sensor networks, body area networks (BANs), and wireless BANs (WBANs), recent efforts in promoting the concept of body sensor networks (BSNs) aim to move beyond sensor connectivity to adopt a system-level approach to address issues related to biosensor design, interfacing, and embodiment, as well as ultralow-power processing/communication, power scavenging, autonomic sensing, data mining, inferencing, and integrated wireless sensor microsystems. As a result, the system architecture based on WBAN and BSN is becoming a widely accepted method of organization for ambulatory and ubiquitous monitoring systems. This editorial paper presents a snapshot of the current research and emerging applications and addresses some of the challenges and implementation issues.
I too, am America: a review of research on systemic lupus erythematosus in African-Americans

Systemic lupus erythematosus (SLE) is a multi-organ autoimmune disorder that can cause significant morbidity and mortality. A large body of evidence has shown that African-Americans experience the disease more severely than other racial-ethnic groups. Relevant literature for the years 2000 to August 2015 were obtained from systematic searches of PubMed, Scopus, and the EBSCOHost platform that includes MEDLINE, CINAHL, etc. to evaluate research focused on SLE in African-Americans. Thirty-six of the 1502 articles were classified according to their level of evidence. The systematic review of the literature reported a wide range of adverse outcomes in African-American SLE patients and risk factors observed in other mono and multi-ethnic investigations. Studies limited to African-Americans with SLE identified novel methods for more precise ascertainment of risk and observed novel findings that hadn't been previously reported in African-Americans with SLE. Both environmental and genetic studies included in this review have highlighted unique African-American populations in an attempt to isolate risk attributable to African ancestry and observed increased genetic influence on overall disease in this cohort. The review also revealed emerging research in areas of quality of life, race-tailored interventions, and self-management. This review reemphasizes the importance of additional studies to better elucidate the natural history of SLE in African-Americans and optimize therapeutic strategies for those who are identified as being at high risk.
Modeling sediment yield and deposition using the SWAT model : a case study of Cubuk I and Cubuk II reservoirs, Turkey

Sediment deposition in a reservoir alters not only the esthetic quality but also the useful life of the reservoir as a result of lost storage capacity and operating flexibility. The research reported here enhances understanding of correlations between potential control variables and the resulting sediment yield to reservoirs. Better understanding of which factors determine sediment yield rate to reservoirs can facilitate estimation of the probable lifespan of a reservoir and appropriate mitigation measures to limit reservoir sedimentation. The Soil and Water Assessment Tool (SWAT) was applied to the Ankara Cayi Catchment, which includes 4932 km2 in Turkey. SWAT was calibrated for monthly data at an upstream sediment gauging site draining approximately 322 km2. Data from 1987-1993 were used for calibration and from 1980-1984 for validation because of non-available observed data at the main outlet. A local sensitivity analysis was performed on 34 input parameters in terms of model outputs such as water and sediment yield. The most sensitive model parameters affecting sediment yield are ALPHA (Base Flow), ICN (Curve Number), CN_F (Initial Runoff Curve Number), ESCO (Soil Evaporation Compensation Factor), SLSUBB (Average Slope Length), and SOL_Z (Soil Depth). In the study, NS (NashSutcliffe Coefficient) and RE (Relative Error) were used for assessing compatibility of the model. SWAT outputs indicate that the model performs reasonably on stream flow (NSE=0.55) and relatively well on suspended sediment (NSE=0.85). Testing the SWAT model applicability in the watershed and identifying the source of uncertainty lay the groundwork for further research in the region.
IMPROVING MULTI-CAMERA ACTIVITY RECOGNITION BY EMPLOYING NEURAL NETWORK BASED READJUSTMENT

In this paper, we propose a method to enhance activity recognition in complex environments, where problems like occlusions, outliers and illumination changes occur. In order to address the problems induced by the dependency on the camera's viewpoint, multiple cameras are used in an endeavor to exploit redundancies. We initially examine the effectiveness of various information stream fusion approaches based on hidden Markov models, including Student's t-endowed models for tolerance to outliers. Following, we introduce a neural network-based readjustment mechanism that fits these fusion schemes and aims at dynamically correcting erroneous classification results for image sequences, thus improving the overall recognition rates. The proposed approaches are evaluated under complex real life activity recognition scenarios, and the acquired results are compared and discussed.
Correlations of SELENOF and SELENOP genotypes with serum selenium levels and prostate cancer

Selenium status is inversely associated with the incidence of prostate cancer. However, supplementation trials have not indicated a benefit of selenium supplementation in reducing cancer risk. Polymorphisms in the gene encoding selenoprotein 15 (SELENOF) are associated with cancer incidence/mortality and present disproportionately in African Americans. Relationships among the genotype of selenoproteins implicated in increased cancer risk, selenium status, and race with prostate cancer were investigated.
E-cient Implementation of the K-SVD Algorithm and the Batch-OMP Method

The K-SVD algorithm is a highly efiective method of training overcomplete dictionaries for sparse signal representation. In this report we discuss an e‐cient implementation of this algorithm, which both accelerates it and reduces its memory consumption. The two basic components of our implementation are the replacement of the exact SVD computation with a much quicker approximation, and the use of the Batch-OMP method for performing the sparse-coding operations. Batch-OMP, which we also present in this report, is an implementation of the Orthogonal Matching Pursuit (OMP) algorithm which is speciflcally optimized for sparse-coding large sets of signals over the same dictionary. The Batch-OMP implementation is useful for a variety of sparsity-based techniques which involve coding large numbers of signals. In the report, we discuss the Batch-OMP and K-SVD implementations and analyze their complexities. The report is accompanied by Matlab r toolboxes which implement these techniques, and can be downloaded at http://www.cs. technion.ac. il/~ronrubin/software.html.
A 1.5-V 3.2Gb/s/pin Graphic DDR4 SDRAM with Dual-Clock System, 4 Phase Input Strobing and Low Jitter Fully Analog DLL

A 1.5V, 512 Mbit GDDR4 SDRAM using a 90-nm DRAM process has been developed. The data rate is 3.2 Gbps/pin, which corresponds to 12.8 GBps in x32 GDDR4 based I/O. A multi-divided architecture consisting of 4 independent 128 Mb core arrays is designed to reduce power and output noise. Also, a dual-clock system, 4 phase data input strobe scheme and 4 phase fully analog DLL are used to increase internal timing margins.
RNAi analysis reveals an unexpected role for topoisomerase II in chromosome arm congression to a metaphase plate

DNA topoisomerase II (Topo II) is a major component of mitotic chromosomes and an important drug target in cancer chemotherapy, however, its role in chromosome structure and dynamics remains controversial. We have used RNAi to deplete Topo II in Drosophila S2 cells in order to carry out a detailed functional analysis of the role of the protein during mitosis. We find that Topo II is not required for the assembly of a functional kinetochore or the targeting of chromosomal passenger proteins, nonetheless, it is essential for anaphase sister chromatid separation. In response to a long-running controversy, we show that Topo II does have some role in mitotic chromatin condensation. Chromosomes formed in its absence have a 2.5-fold decrease in the level of chromatin compaction, and are morphologically abnormal. However, it is clear that the overall programme of mitotic chromosome condensation can proceed without Topo II. Surprisingly, in metaphase cells depleted of Topo II, one or more chromosome arms frequently stretch out from the metaphase plate to the vicinity of the spindle pole. This is not kinetochore-based movement, as the centromere of the affected chromosome is located on the plate. This observation raises the possibility that further unexpected functions for Topo II may remain to be discovered.