Miracle-dz/UniFAR-FTUs huggingface dataset:
Scripting distributed scientific workflows using Weaver

Weaver is a high‐level distributed computing framework that enables researchers to construct scalable scientific data‐processing workflows. Instead of developing a new workflow language, we introduce a domain‐specific language built on top of Python called Weaver, which takes advantage of users' familiarity with the programming language, minimizes barriers to adoption, and allows for integration with a rich ecosystem of existing software. In this paper, we provide an overview of Weaver's programming model, which allows users to organize and specify scientific workflows by using a collection of datasets, functions, and abstractions. We also explain how these workflow specifications are compiled into a directed acyclic graph that is used by the Makeflow workflow manager to dispatch work to a variety of distributed execution platforms. To demonstrate the power and benefits of using the framework in constructing scientific research applications, the paper examines four distinct real‐world applications scripted using Weaver and analyzes the performance, scalability, and impact of the distributed generated scientific workflows. Copyright © 2011 John Wiley & Sons, Ltd.
Inhibition of DNA replication fork progression and mutagenic potential of 1, N6-ethenoadenine and 8-oxoguanine in human cell extracts

Comparative mutagenesis of 1,N6-ethenoadenine (εA) and 8-oxoguanine (8-oxoG), two endogenous DNA lesions that are also formed by exogenous DNA damaging agents, have been evaluated in HeLa and xeroderma pigmentosum variant (XPV) cell extracts. Two-dimensional gel electrophoresis of the duplex M13mp2SV vector containing these lesions established that there was significant inhibition of replication fork movement past εA, whereas 8-oxoG caused only minor stalling of fork progression. In extracts of HeLa cells, εA was weakly mutagenic inducing all three base substitutions in approximately equal frequency, whereas 8-oxoG was 10-fold more mutagenic inducing primarily G→T transversions. These data suggest that 8-oxoG is a miscoding lesion that presents a minimal, if any, block to DNA replication in human cells. We hypothesized that bypass of εA proceeded principally by an error-free mechanism in which the undamaged strand was used as a template, since this lesion strongly blocked fork progression. To examine this, we determined the sequence of replication products derived from templates in which a G was placed across from the εA. Consistent with our hypothesis, 93% of the progeny were derived from replication of the undamaged strand. When translesion synthesis occurred, εA→T mutations increased 3-fold in products derived from the mismatched εA: G construct compared with those derived from the εA: T construct. More efficient repair of εA in the εA: T construct may have been responsible for lower mutation frequency. Primer extension studies with purified pol η have shown that this polymerase is highly error-prone when bypassing εA. To examine if pol η is the primary mutagenic translesion polymerase in human cells, we determined the lesion bypass characteristics of extracts derived from XPV cells, which lack this polymerase. The εA: T construct induced εA→G and εA→C mutant frequencies that were approximately the same as those observed using the HeLa extracts. However, εA→T events were increased 5-fold relative to HeLa extracts. These data support a model in which pol η-mediated translesion synthesis past this adduct is error-free in the context of semiconservative replication in the presence of fidelity factors such as PCNA.
A Mobile Food Record For Integrated Dietary Assessment

This paper presents an integrated dietary assessment system based on food image analysis that uses mobile devices or smartphones. We describe two components of our integrated system: a mobile application and an image-based food nutrient database that is connected to the mobile application. An easy-to-use mobile application user interface is described that was designed based on user preferences as well as the requirements of the image analysis methods. The user interface is validated by user feedback collected from several studies. Food nutrient and image databases are also described which facilitates image-based dietary assessment and enable dietitians and other healthcare professionals to monitor patients dietary intake in real-time. The system has been tested and validated in several user studies involving more than 500 users who took more than 60,000 food images under controlled and community-dwelling conditions.
Segmentation of bio-signals in field recordings using fundamental frequency detection

Monitoring animal species by means of the automatic sound recognition is nowadays a research field of high interest. One of the challenges of this area lies in the segmentation of the species vocalizations. Recordings acquired in natural habitats are contaminated with the sounds emitted by other species and different kinds of background noise. If the data is “clean” a robust segmentation is feasible, otherwise a pre-processing stage must be carefully performed in order to recover relevant information over the noise effect. In this manuscript, we propose the use of the Karnuhen-Loeve Transform noise reduction algorithm as an additional pre-processing sub-stage. We also propose a segmentation method based on the Fundamental Frequency detection and Voiced/Unvoiced segmentation, implemented with the Voice Analysis software Praat. Preliminary results show that the proposed pre-processing scheme improves the segmentation process, with results comparable to the commercial software Song Scope.
Analysis On Fisher Discriminant Criterion And Linear Separability Of Feature Space

For feature extraction resulted from Fisher discriminant analysis (FDA), it is expected that the optimal feature space is as low-dimensional as possible while its linear separability among different classes is as large as possible. Note that the existing theoretical expectation on the optimal feature dimensionality may contradict with experimental results. Due to this, we address the optimal feature dimensionality problem with this paper. The multi-dimension Fisher criterion is used to measure the linear separability of the feature space obtained using FDA and to analyze the optimal feature dimensionality problem. We also attempt to answer the question "what kind of real-world application is FDA competent for". Theoretical analysis shows that the genuine optimal feature dimensionality should be lower than that presented by Jin et al. A number of experiments illustrate that the proposed optimal feature extraction does have advantages
Experimental study on neighbor selection policy for Phoenix Network Coordinate system

Network Coordinate (NC) which provides efficient distance prediction with scalable measurements, brings benefits to various network applications. Phoenix Network Coordinate system is a recently proposed dot product based NC system with high prediction accuracy and better robustness. In this paper, we discuss the neighbor selection policies for Phoenix and propose a modified Phoenix with Hybrid neighbor selection policy. Extensive experiments have been carried out to evaluate the performance of Phoenix NC systems with different neighbor selection policies. The results show that the system with Hybrid policy achieves lower relative errors (REs) and obtains a higher accuracy in selecting the nearest neighbor host. Moreover, the Hybrid policy based Phoenix NC system has a better performance in the application of Overlay Multicast. It reduces the tree cost of the ESM and MST multicast tree construction by at least 20%.
Prediction of International Stock Markets Based on Hybrid Intelligent Systems

This paper compares the accuracy of three hybrid intelligent systems in forecasting ten international stock market indices; namely the CAC40, DAX, FTSE, Hang Seng, KOSPI, NASDAQ, NIKKEI, S&P500, Taiwan stock market price index, and the Canadian TSE. In particular, genetic algorithms (GA) are used to optimize the topology and parameters of the adaptive time delay neural networks (ATNN) and the time delay neural networks (TDNN). The third intelligent system is the adaptive neuro-fuzzy inference system (ANFIS) that basically integrates fuzzy logic into the artificial neural network (ANN) to better model information and explain decision making process. Based on out-of-sample simulation results, it was found that contrary to the literature GA-TDNN significantly outperforms GA-ATDNN. In addition, ANFIS was found to be more effective in forecasting CAC40, FTSE, Hang Seng, NIKKEI, Taiwan, and TSE price level. In contrary, GA-TDNN and GA-ATDNN were found to be superior to ANFIS in predicting DAX, KOSPI, and NASDAQ future prices.
A video-based support system for nighttime navigation in semi-structured environments

This paper describes the development of a vision-based, nighttime navigation support system for automotive vehicles driving in semi-structured environments. The focus is on automatic reduction of glare produced by high beams from incoming vehicles and on generation of virtual lanes that are overlaid on the image where actual road markings should exist. To accomplish these goals, we develop video-based robust techniques that produce enhanced road images in real-time. The proposed techniques are validated by experiments with real video streams, which demonstrates the system's performance and accuracy under real conditions.
Effects of a shared vision on the attitudes of teachers towards outcomes-based education

Currently, much is being written about leadership styles in schools and the introduction of an outcomes-based education (OBE) in South Africa. This investigation was therefore conducted to ascertain the effects of a shared vision on staff attitudes towards curriculum change and the implementation of OBE. The findings of this study indicate that a shared vision alone does not guarantee the successful implementation of OBE. Systemic paradigm shifts require a fundamental change to the old order. This necessitates the retraining of educators and the provision of materials that could contribute substantially to the formulation of a shared vision on Transformational OBE. However, the interviews strongly indicated that schools, especially historically Black schools, were under-resourced and lacked the capacity to implement OBE successfully and this impacted negatively on a shared vision. The problems are further exacerbated by the inability of the Department of Education to address these problems realistically and to enforce the implementation of OBE prematurely.
Simple and efficient rate control for H.264/AVC

In order to get accurately the coding characteristics of current basic unit, a novel adaptive coding characteristic prediction scheme called texture-complexity estimation is proposed. Through adaptive linear texture-complexity and overhead prediction model as well as optimum bits allocation scheme, we can obtain current basic unit coding parameter such as texture-complexity, overhead bits count and texture bits budget, and then the quantization parameter can be directly calculated. Simulation results show that the H.264 encoder, using the proposed rate control algorithm, achieves a visual quality improvement up to 0.388 dB, meets better with target bit rates and produces more flat bit-rate curve than that using the H.264 previous rate control method (JVT-G012).
System-Level Bus-Based Communication Architecture Exploration Using a Pseudoparallel Algorithm

Growing complexity in system-on-a-chip (SoC) design demands effective approaches to explore various architectures quickly for the target applications. With the common use of intellectual properties (IPs) in SoC and the large amount of data interchanges among IPs, communication architecture significantly affects the system in terms of power and performance. Therefore, designers should carefully plan the communication architecture to meet the power and performance requirements. While repeatedly performing a power optimization under a performance constraint approach N times seems practical for the power and performance co-exploration, the time required to explore such solutions inevitably increases, since there are numerous performance constraints. This paper presents a pseudo-parallel method for bus architecture exploration at the system level (PBAES) to speedup the power and performance of co-exploration time. PBAES can intelligently search interesting portions of the design space to enhance the efficiency of co-exploration, and share the candidate solutions of each to achieve a more rapid overall exploration. The experimental results indicate that PBAES is 1.6 times to 14 times faster than an approach without the pseudo-parallel method with a generated architecture of similar quality.
Revisiting the Perceptron Predictor Again

We introduce a new kind of branch predictor, the hashed perceptron predictor, which merges the concepts behind the gshare and perceptron branch predictors. This is done by fetching the perceptron weights using the exclusive-or of branch addresses and branch history. This predictor can achieve superior accuracy to a path-based and a global perceptron predictor, previously the most accurate fully dynamic branch predictors known in the literature, at the same storage budgets. Additionally, it reduces the number of adders by a factor of four compared to a path-based perceptron. We also show how such a predictor can be ahead pipelined to yield one cycle effective latency, making it the first standalone perceptron predictor. On the SPEC integer set of benchmarks, the hashed ahead-pipelined path-based perceptron predictor (hashed perceptron for short) improves accuracy by 20% over a path-based perceptron and improves IPC by 5.8%. We believe these improvements make the perceptron predictor a promising choice as a branch predictor for a future high-performance microprocessor.
Glycemic Index, Glycemic Load, Carbohydrates, and Type 2 Diabetes

OBJECTIVE Diets with high glycemic index (GI), with high glycemic load (GL), or high in all carbohydrates may predispose to higher blood glucose and insulin concentrations, glucose intolerance, and risk of type 2 diabetes. We aimed to conduct a systematic literature review and dose–response meta-analysis of evidence from prospective cohorts. RESEARCH DESIGN AND METHODS We searched the Cochrane Library, MEDLINE, MEDLINE in-process, Embase, CAB Abstracts, ISI Web of Science, and BIOSIS for prospective studies of GI, GL, and total carbohydrates in relation to risk of type 2 diabetes up to 17 July 2012. Data were extracted from 24 publications on 21 cohort studies. Studies using different exposure categories were combined on the same scale using linear and nonlinear dose–response trends. Summary relative risks (RRs) were estimated using random-effects meta-analysis. RESULTS The summary RR was 1.08 per 5 GI units (95% CI 1.02–1.15; P = 0.01), 1.03 per 20 GL units (95% CI 1.00–1.05; P = 0.02), and 0.97 per 50 g/day of carbohydrate (95% CI 0.90–1.06; P = 0.5). Dose–response trends were linear for GI and GL but more complex for total carbohydrate intake. Heterogeneity was high for all exposures (I2 >50%), partly accounted for by different covariate adjustment and length of follow-up. CONCLUSIONS Included studies were observational and should be interpreted cautiously. However, our findings are consistent with protective effects of low dietary GI and GL, quantifying the range of intakes associated with lower risk. Future research could focus on the type of sugars and other carbohydrates associated with greatest risk.
A CRITICAL FEMINIST EXPLORATION OF SUCCESSFUL AGING AND ADAPTATION OF INTERSECTING MARGINALIZED IDENTITIES: OLDER AFRICAN AMERICAN WOMEN'S PERCEPTIONS AND DEFINITIONS

A CRITICAL FEMINIST EXPLORATION OF SUCCESSFUL AGING AND ADAPTATION OF INTERSECTING MARGINALIZED IDENTITIES: OLDER AFRICAN AMERICAN WOMEN’S PERCEPTIONS AND DEFINITIONS by Jacquelyn Manning Dantis The purpose of this study was to explore if intersecting socially constructed identities of race, gender and age influenced how a sample of 18 older African American women, 40 and over, define and experience successful aging. And, if and how do participants deviate from Rowe and Kahn’s model. Due to the heterogeneity of ethnic backgrounds for individuals of African descent, my sample included only women who self-identify as African American/black. Because the overall objective was to understand heterogeneity in the aging experiences of African American women, the following primary questions were addressed: 1) How do older African American women who reside in challenging environments and/or lived through challenging experiences define successful aging? ; 2) Do older African American women who reside in challenging environments and/or lived through challenging experiences see themselves as having positive marginality? If so, is it relevant to their intersecting identities based on race, gender and age? and 3) If these women experience positive marginality, does this positive marginality help them age successfully based their definition of successful aging? Results show that the intersection of gender and age does directly influence the way participants saw and defined successful aging. As aging women, participants saw being a woman was significant to partnering, physical attractiveness, and medical issues centered on menopause, in addition to illnesses directly linked to being a woman, such as breast or uterine cancer. Results of this study did not find that race and gender intersect. However, racial discrimination across the life did have an impact on their beliefs about themselves and others as they aged. With race, gender and aging, participants’ perspectives depended heavily upon their life experiences with social structures and personal struggles with male domination, in addition to abuse and health concerns from their past, present and future outcomes. Positive marginality did not emerge from the data as constructed by Unger (1998). It is concluded from the findings of this study that a unifying multidimensional model of successful aging is needed. It is suggested here that gender and age be examined further as influential social constructs on well-being and life. A CRITICAL FEMINIST EXPLORATION OF SUCCESSFUL AGING AND ADAPTATION OF INTERSECTING MARGINALIZED IDENTITIES: OLDER AFRICAN AMERICAN WOMEN’S PERCEPTIONS AND DEFINITIONS
Online structure learning for robust object tracking

In this paper, we aim to track objects that undergo abrupt appearance changes and heavy occlusions. To address these problems, we propose an online structure learning algorithm which contains two layers, block-based online random forest classifiers (BORFs) and online structure models (OSMs). BORFs are able to handle occlusion problems since they model local appearances of the target. To further improve the accuracy and reliability, the algorithm utilizes relational models as context information to combine BORFs into the online structure models. Capturing the discriminative parts of targets with online learnt structures, OSMs help locate targets accurately even when they are heavily occluded. In addition, OSMs guide the block occlusion reasoning and the update scheme of BORFs and relational models, which can handle appearance changes and drift problems effectively. Experiments on challenging videos show that the proposed tracker performs better than several state-of-the-art algorithms which demonstrate the effectiveness of our approach.
A full end-to-end platform as a service for smart city applications

This paper presents COMPOSE, an open-source Platform as a Service (PaaS) for developing Smart City solutions based on connected objects. COMPOSE is built around open-source components that allow storing, streaming and processing of sensor data, communication with connected objects using M2M protocols, service discovery, data provenance and multi-tenancy, deployment and scalable hosting of applications in a cloud environment, workflow editing and cross-platform smartphone application development. A use case developed for deployment in the city of Barcelona that utilizes the aforementioned components among with parking and traffic sensors is also presented.
A deterministic near-linear time algorithm for finding minimum cuts in planar graphs

We present a simple deterministic <i>O</i>(<i>n</i> log<sup>2</sup> <i>n</i>)-time divide-and-conquer algorithm for finding minimum cuts in planar graphs. This can be compared to a randomized algorithm for general graphs by Karger that runs in time <i>O</i>(<i>m</i> log<sup>3</sup> <i>n</i>) and also a deterministic algorithm for general graphs by Nagamochi and Ibaraki that runs in time <i>O</i>(<i>mn</i> + <i>n</i><sup>2</sup> log <i>n</i>). We use shortest paths in the dual graphs to partition the problem, and use the relationship between minimum cuts in primal graphs and shortest paths in dual graphs to find minimum cuts that cross the partitions efficiently.
Efficacy of a Metalloproteinase Inhibitor in Spinal Cord Injured Dogs

Matrix metalloproteinase-9 is elevated within the acutely injured murine spinal cord and blockade of this early proteolytic activity with GM6001, a broad-spectrum matrix metalloproteinase inhibitor, results in improved recovery after spinal cord injury. As matrix metalloproteinase-9 is likewise acutely elevated in dogs with naturally occurring spinal cord injuries, we evaluated efficacy of GM6001 solubilized in dimethyl sulfoxide in this second species. Safety and pharmacokinetic studies were conducted in naïve dogs. After confirming safety, subsequent pharmacokinetic analyses demonstrated that a 100 mg/kg subcutaneous dose of GM6001 resulted in plasma concentrations that peaked shortly after administration and were sustained for at least 4 days at levels that produced robust in vitro inhibition of matrix metalloproteinase-9. A randomized, blinded, placebo-controlled study was then conducted to assess efficacy of GM6001 given within 48 hours of spinal cord injury. Dogs were enrolled in 3 groups: GM6001 dissolved in dimethyl sulfoxide (n = 35), dimethyl sulfoxide (n = 37), or saline (n = 41). Matrix metalloproteinase activity was increased in the serum of injured dogs and GM6001 reduced this serum protease activity compared to the other two groups. To assess recovery, dogs were a priori stratified into a severely injured group and a mild-to-moderate injured group, using a Modified Frankel Scale. The Texas Spinal Cord Injury Score was then used to assess long-term motor/sensory function. In dogs with severe spinal cord injuries, those treated with saline had a mean motor score of 2 (95% CI 0–4.0) that was significantly (P<0.05; generalized linear model) less than the estimated mean motor score for dogs receiving dimethyl sulfoxide (mean, 5; 95% CI 2.0–8.0) or GM6001 (mean, 5; 95% CI 2.0–8.0). As there was no independent effect of GM6001, we attribute improved neurological outcomes to dimethyl sulfoxide, a pleotropic agent that may target diverse secondary pathogenic events that emerge in the acutely injured cord.