Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic identification and removal of artifacts in EEG using a probabilistic multi-class SVM approach with error correction

A novel electroencephalogram (EEG) artifact removal method is presented in this paper. The proposed method combines a probabilistic multi-class Support Vector Machine (SVM) and an error correction algorithm for component classification, where i) the probabilistic multi-class SVM is modified to properly handle the unbalanced nature of component classification and ii) the error correction algorithm is used to accommodate the structural information of the learning problem. The proposed component classifier was tested on real-life EEG data and it significantly outperformed the standard SVM used in the literature. A qualitative evaluation on the reconstructed EEG shows that the proposed artifact removal method greatly reduced the amount of artifacts while well preserving brain activities in almost all EEG epochs.
Quality of life with visual acuity loss from diabetic retinopathy and age-related macular degeneration.

OBJECTIVE To compare the quality of life in patients with visual acuity loss occurring secondary to diabetic retinopathy with visual acuity loss occurring secondary to age-related macular degeneration (ARMD). METHODS Consecutive patients with diabetic retinopathy and ARMD were evaluated using the time trade-off method of utility value analysis. Both groups were stratified according to the degree of visual acuity loss in the better-seeing eye (group 1: 20/20-20/25, group 2: 20/30-20/40, group 3: 20/50-20/100, group 4: < or =20/200). Utility values obtained from the patients, once stratified for visual acuity group, were compared with use of the t test and the Mann-Whitney U test. In addition, a 2-way analysis of variance was performed to control for potential confounding variables. RESULTS No difference was found between the utility value means of the diabetic retinopathy (n = 333) and ARMD (n = 246) subgroups stratified according to visual acuity levels: group 1, P =. 54; group 2, P =. 96; group 3, P =. 09; and group 4, P =. 32. A 2-way analysis of variance demonstrated that, among the variables of ocular disease, sex, age, and visual acuity in the better-seeing eye, only visual acuity was significantly associated with utility values (P =.003). CONCLUSIONS At similar levels of visual acuity loss, that associated with diabetic retinopathy causes a similar reduction in quality of life to that associated with ARMD. This information has important implications for use in cost-utility analyses of ophthalmic interventions.
Diabetes, Hypertension, and Cardiovascular Disease: An Update

Abstract—Cardiovascular diseases (CVDs) are the major causes of mortality in persons with diabetes, and many factors, including hypertension, contribute to this high prevalence of CVD. Hypertension is approximately twice as frequent in patients with diabetes compared with patients without the disease. Conversely, recent data suggest that hypertensive persons are more predisposed to the development of diabetes than are normotensive persons. Furthermore, up to 75% of CVD in diabetes may be attributable to hypertension, leading to recommendations for more aggressive treatment (ie, reducing blood pressure to <130/85 mm Hg) in persons with coexistent diabetes and hypertension. Other important risk factors for CVD in these patients include the following: obesity, atherosclerosis, dyslipidemia, microalbuminuria, endothelial dysfunction, platelet hyperaggregability, coagulation abnormalities, and “diabetic cardiomyopathy. ” The cardiomyopathy associated with diabetes is a unique myopathic state that appears to be independent of macrovascular/microvascular disease and contributes significantly to CVD morbidity and mortality in diabetic patients, especially those with coexistent hypertension. This update reviews the current knowledge regarding these risk factors and their treatment, with special emphasis on the cardiometabolic syndrome, hypertension, microalbuminuria, and diabetic cardiomyopathy. This update also examines the role of the renin-angiotensin system in the increased risk for CVD in diabetic patients and the impact of interrupting this system on the development of clinical diabetes as well as CVD.
Inhibition of benzo(a)pyrene-induced mouse forestomach neoplasia by dietary soy sauce.

We show that Japanese-style fermented soy sauce (shoyu) contains anticarcinogenic activity. Female ICR mice were fed a semipurified diet containing soy sauce (0-30%). Two weeks later a regimen consisting of 4 doses of benzo(a)pyrene (1 dose/week p.o. for 4 weeks) was begun to initiate forestomach neoplasia. Twenty-three weeks after the first intubation the animals were sacrificed, and forestomach neoplasms were counted and histologically confirmed. Soy sauce produced a significant dose-dependent reduction in forestomach neoplasms, which appeared to be maximal when soy sauce constituted 20% of the diet. Exposure to nitrite (0-500 ppm through drinking water) neither enhanced nor diminished the anticarcinogenic effect of the dietary soy sauce. Soy sauce was found to contain antioxidant activity which may be related to the observed anticarcinogenic effect. Contrary to expectations, mouse forestomach ornithine decarboxylase activity was induced by soy sauce. This appeared to be due at least in part to the relatively high sodium chloride content of soy sauce.
Low-power bufferless resonant clock distribution networks

The major design challenges toward a highly power- efficient bufferless resonant clock distribution network is discussed. The presented discussion is supported by measurements on three different clock distribution networks implemented in a test chip fabricated in 0.13-mum standard CMOS process. In addition to presenting a detailed power comparison between these networks and the conventional buffer-driven scheme, the clock jitter characteristic in bufferless clock distribution is discussed. Furthermore, injection-locking phenomenon is utilized to suppress data- dependent jitter and to achieve a low-jitter clock distribution.
MicroRNA-124 functions as a tumor suppressor and indicates prognosis in human osteosarcoma

MicroRNA-124 (miR-124) has been demonstrated to be downregulated in numerous human malignancies and correlated with tumor progression. However, its expression and clinical significance in osteosarcoma remains unclear. Thus, the aim of the present study was to explore the effects of miR-124 in osteosarcoma tumorigenesis and development. Using reverse transcription-quantitative polymerase chain reaction, miR-124 expression was detected in primary osteosarcoma tissues and osteosarcoma cell lines. The correlation of miR-124 expression with clinicopathological factors and prognosis was statistically analyzed. MTT, flow cytometric, and Transwell invasion and migration assays were used to test the proliferation, apoptosis, invasion and migration of osteosarcoma cells transfected with miR-124 mimic. It was found that the expression levels of miR-124 in osteosarcoma tissues were significantly lower than those in corresponding noncancerous bone tissues (P<0.001). In addition, miR-124 downregulation more frequently occurred in osteosarcoma specimens with advanced clinical stage (P<0.001), positive distant metastasis (P=0.005) and poor response to neoadjuvant chemotherapy (P=0.013). Univariate and multivariate analysis identified low miR-124 expression as an unfavorable prognostic factor for overall survival. Furthermore, transfection of miR-124 mimic into MG63 cells was able to reduce cell proliferation, invasion and migration, and promote cell apoptosis. These findings indicate that miR-124 may act not only as a novel diagnostic and prognostic marker, but also as a potential target for the molecular therapy of osteosarcoma.
Interaction of lobed kudzuvine root, rhizoma chuanxiong with both acetylcholinesterase and beta-amyloid (Aβ1-42)

Background: Lobed kudzuvine root and rhizoma chuanxiong are effective drugs in traditional Chinese medicine. Objective: Extracts of the two medicines were investigated for their in vitro of beta-amyloid (Aβ1-42)-aggregation-and acetylcholinesterase (AChE)-inhibitory activities. Materials and Methods: The interaction of lobed kudzuvine root, rhizoma chuanxiong with both acetylcholinesterase and beta-amyloid (Aβ1-42) were studied by Michaelis–Menten equations, Thioflavin T (ThT) fluorescence analysis and transmission electron microscope (TEM). Results: Inhibition of acetylcholinesterase showed that 1-butanol fraction of the two medicines were noncompetitive inhibition, apparent inhibition constants were 9.947 and 7.1523. ThT fluorescence analysis and TEM results indicated that inhibition of the water fraction and 1-butanol fraction (both lobed kudzuvine root and rhizoma chuanxiong) was better. Conclusion: The result supported further research on chemical constituents and pharmacological mechanisms.
Spectral texturing for real-time applications

In this sketch we present a new method for rendering large-scale, high-resolution, non-repetitive textures in real-time using multi layer texturing. The basic idea of spectral texturing is to construct the nal texture by multiple texture layers where each layer provides a certain range of the spectrum of the texture’s spatial frequencies. Alpha channels are used to introduce statistical dependencies between the frequency bands. This approach extends a method called detail texturing, which does not use alpha channels to model higher statistical properties of the resulting texture. Other approaches to generate textures with specied statistical properties, like [DeBonet 1997], are not suitable for real-time use and would require storage of the generated texture. Spectral texturing is very easy to implement, runs on all contemporary 3d graphics cards, and is especially suitable for naturalistic textures in real-time applications which are viewed from a large range of distances.
Genotype-environment interactions and schizophrenia

Nature and nurture are not separate. Instead it is important to investigate the interplay between genes and environment and how they influence on another. To an important degree, genetic effects on behavior come about because they either influence the extent to which the individual is likely to be exposed to individual differences in environmental risk or they affect how susceptible the individual is to environmental adversities. The current inability to explain or predict which genetically predisposed individuals will finally become schizophrenic has forced us to confront our ignorance of the precise mechanism and mode of the transmission of this disorder. Zubin's proposal to view the schizophrenic as a vulnerable individual who develops a temporary episode only under certain provocations can help place the controversy in proper perspective. Vulnerability (predisposition, diathesis) to schizophrenia can be defined as the individual's characteristic treshold beyond which stressful events produce decompensation manifest in the clinically diagnosable symptom picture.
Gene Therapy of the Corneal Epithelium

Despite much progress, conventional therapies have been unable to adequately treat many common disorders involving the corneal epithelium. Processes such as corneal neovascularization, conjuctivalization of the ocular surface, recurrent erosions, dry eye syndrome, and neurotrophic keratopathy are quite frequently found to be resistant to our current treatment modalities. Our knowledge of the molecular mechanisms responsible for these disorders has flourished, but few if any of our treatments reflect our newly acquired knowledge. Most of our treatment of epithelial disease requires the repeat usage of topical drugs that are not specific for the pathophysiology of the disease to be treated, but instead effect a host of biologic processes, one of which may be involved in the pathophysiology. For many of the aforementioned disease processes, tailored molecular therapy in the form of gene therapy may prove to be more effective and harbor fewer side effects (Table 1). Since the description of DNA as the fundamental genetic code, scientists and physicians have worked to use our understanding of genes to treat human disease. Gene therapy has been applied to a host of diseases, and over the next few years, more gene therapies will become part of our clinical armamentarium. Recent progress has been made in the use of gene targeting vectors to alter gene expression in the cornea as a prelude to potential gene therapies. This review will briefly discuss gene vectors and describe the progress made in corneal epithelial gene transfer. Particular emphasis will be placed on special properties of the corneal epithelium that influence its potential as a target for gene therapy.
Toward Engineering a Secure Android Ecosystem

The openness and extensibility of Android have made it a popular platform for mobile devices and a strong candidate to drive the Internet-of-Things. Unfortunately, these properties also leave Android vulnerable, attracting attacks for profit or fun. To mitigate these threats, numerous issue-specific solutions have been proposed. With the increasing number and complexity of security problems and solutions, we believe this is the right moment to step back and systematically re-evaluate the Android security architecture and security practices in the ecosystem. We organize the most recent security research on the Android platform into two categories: the software stack and the ecosystem. For each category, we provide a comprehensive narrative of the problem space, highlight the limitations of the proposed solutions, and identify open problems for future research. Based on our collection of knowledge, we envision a blueprint for engineering a secure, next-generation Android ecosystem.
X MARCKS the spot: myristoylated alanine-rich C kinase substrate in neuronal function and disease

Intracellular protein-protein interactions are dynamic events requiring tightly regulated spatial and temporal checkpoints. But how are these spatial and temporal cues integrated to produce highly specific molecular response patterns? A helpful analogy to this process is that of a cellular map, one based on the fleeting localization and activity of various coordinating proteins that direct a wide array of interactions between key molecules. One such protein, myristoylated alanine-rich C-kinase substrate (MARCKS) has recently emerged as an important component of this cellular map, governing a wide variety of protein interactions in every cell type within the brain. In addition to its well-documented interactions with the actin cytoskeleton, MARCKS has been found to interact with a number of other proteins involved in processes ranging from intracellular signaling to process outgrowth. Here, we will explore these diverse interactions and their role in an array of brain-specific functions that have important implications for many neurological conditions.
Frame of Reference Effects on Scientific Visualization Subtasks

Performance measures for 3 frames of reference (full exocentric, full egocentric, and tethered) were contrasted across 4 different scientific visualization subtasks: search, travel, local judgment support, and global judgment support. Participants were instructed to locate and follow a designated path through 15 simple virtual environments and to answer simple questions about that environment. Each participant completed 5 trials in every frame of reference condition (exocentric, egocentric, and tethered). The results revealed that frames of reference that utilize egocentric or tethered viewpoints support better travel performance, especially when nearing the target. However, the exocentric frame of reference supported better performance in the search subtasks and in the local and global judgment subtasks. Actual or potential applications of this research include proper uses of virtual reality to support certain scientific visualization subtasks.
Accelerating multi-party scheduling for transaction-level modeling

Transaction-level modeling is an essential component of system-level design. This paper advocates using rendezvous, a construct common to concurrent programming languages, as a theoretical foundation for transactions. Compared to regular function calls, rendezvous are atomic and support multipartiness and parallel composition. However, scheduling multiparty rendezvous is a challenging task due to its NP-hard complexity. This paper describes a heuristic algorithm that significantly reduces the scheduling complexity in practice. It first constructs a relationship graph among rendezvous. It then simplifies the graph and translates it into a decision tree, which assists the scheduler in partitioning and pruning the search space. Our experimental results show that the algorithm is able to improve the efficiency of the scheduler significantly.
Scalable Diagnosability Checking of Event-Driven Systems

Diagnosability of systems is an essential property that determines how accurate any diagnostic reasoning can be on a system given any sequence of observations. Generally, in the literature of dynamic event-driven systems, diagnosability analysis is performed by algorithms that consider a system as a whole and their response is either a positive answer or a counter example. In this paper, we present an original framework for diagnosability checking. The diagnosability problem is solved in a distributed way in order to take into account the distributed nature of realistic problems. As opposed to all other approaches, our algorithm also provides an exhaustive and synthetic view of the reasons why the system is not diagnosable. Finally, the presented algorithm is scalable in practice: it provides an approximate and useful solution if the computational resources are not sufficient.
Frequency of application of topical corticosteroids: an overview

The frequency of application of topical corticosteroids has remained an unresolved issue through the decades with most textbooks and physicians recommending multiple daily use. This review focuses on the rationale of once daily application of corticoids as an effective treatment in some patients. Dermatopharmacokinetic data relevant to the dosage and frequency of application of topical corticoids are discussed. Clinical trials on the efficacy of once daily vs. twice daily applications are evaluated.
Cohesive Modeling , Analysis and Simulation for Spoken Urdu Language Numbers with Fourier Descriptors and Neural Networks

This unified research describes spoken Urdu numbers investigative analysis from ‘siffar’ (zero) to ‘nau’ (nine) for making a concrete foundation in recognition of Urdu language. Sound samples from multiple speakers were utilized to extract different features using Fourier descriptor and Neural networks. Initial processing of data, i.e. normalizing and time-slicing was done using a combination of Simulink in MATLAB. Afterwards, the MATLAB tool box commands were used for calculation of Fourier descriptions and correlations. The correlation allowed comparison of the same words spoken by the same and different speakers. The analysis presented in this paper laid a foundation step in exploring Urdu language in developing an Urdu speech recognition system. In this paper the speech recognition feed-forward neural network models in Matlab were developed. The models and algorithm exhibited high training and testing accuracies. Our major goal work involves in the future use of TI TMS320C6000 DSK series or linear predictive coding. Such a system can be potentially utilized in implementation of a voice-driven help setup in different systems. Such as multi media, voice controlled tele-customer services.
High resolution spaceborne SAR focusing by SVD -

In space borne SAR, the orbit curvature may prevent the use of the ωk processor, causing artifacts that depend on both the extent of the orbit arc and the slant range interval. A viable solution has been derived by extending the SVD-STOLT approach proposed for geophysical applications to microwave SAR. The resulting processor has the same simple scheme as the ωk approach, but a different (numerical) computation of both the reference and the Stolt interpolation.
Evaluation of Acceptable Charging Current of Power Li-Ion Batteries Based on Polarization Characteristics

Battery polarization voltage characteristics of power Li-ion batteries are investigated at different charging rates. The polarization voltage is small and relatively stable in the middle state of charge (SOC) range, whereas at both ends of SOC, the polarization voltage is enlarged and varies rapidly. Meanwhile, there is an approximate linear relationship between polarization voltage and charging rate. Taking polarization time constant into account, an acceptable charging current curve is developed, which prevents charging current from being out of range. This curve takes polarization voltage and charge cutoff voltage as constraints to describe acceptable charging current value at different SOC. Based on this curve, the battery can be charged from 20% SOC to 80% SOC within 33 min. The average polarization and the maximum temperature rise are approximately equivalent to those of 0.5C constant current-constant voltage charging method. The experimental results demonstrate that the proposed charging mode can balance charging speed, charging polarization, and temperature rise.
Brief report: primary infection with zidovudine-resistant human immunodeficiency virus type 1.

Strains of human immunodeficiency virus type 1 (HIV-1) with reduced sensitivity to zidovudine have been isolated from patients treated with this drug for six months or more1. Resistance to zidovudine is associated with late-stage disease, low CD4 lymphocyte counts, longer antiretroviral therapy, and specific mutations in the reverse transcriptase gene of HIV-12,3. The clinical importance of infections with resistant HIV-1 isolates is not well understood. We describe a patient with symptomatic HIV-1 infection who had primary infection with a virus resistant to zidovudine, according to both phenotypic and genotypic analyses. Case Report The patient was a 20-year-old .
Sparse online model learning for robot control with support vector regression

The increasing complexity of modern robots makes it prohibitively hard to accurately model such systems as required by many applications. In such cases, machine learning methods offer a promising alternative for approximating such models using measured data. To date, high computational demands have largely restricted machine learning techniques to mostly offline applications. However, making the robots adaptive to changes in the dynamics and to cope with unexplored areas of the state space requires online learning. In this paper, we propose an approximation of the support vector regression (SVR) by sparsification based on the linear independency of training data. As a result, we obtain a method which is applicable in real-time online learning. It exhibits competitive learning accuracy when compared with standard regression techniques, such as v-SVR, Gaussian process regression (GPR) and locally weighted projection regression (LWPR).
Distributed Resource Discovery in the Machine-to-Machine Applications

One challenging problem in Machine-to-Machine (M2M) applications is to efficiently discover the resources provided by a huge number of heterogeneous devices. This paper proposes distributed resource discovery architecture (DRD) for M2M applications. The DRD supports heterogeneous devices in resource description registration and discovery of resource value. It achieves interoperability among heterogeneous devices in disparate networks and enables resource access from the Internet. In the DRD, a resource registration component is designed for storing resource descriptions, a resource discovery component is designed to retrieve resource values on behalf of clients after getting address information by looking up resource descriptions. The DRD utilizes a peer-to-peer overlay to distribute workload and avoid single point of failure. A real-world prototype is implemented and verified with a simple demo. Preliminary evaluation on response time of resource discovery is provided.