Miracle-dz/UniFAR-FTUs huggingface dataset:
Leading to Change / Effective Grading Practices

If you wanted to make just one change that would immediately reduce student failure rates, then the most effective place to start would be challenging prevailing grading practices. How can I be so sure? Try this experiment in your next faculty meeting. Ask your colleagues to calculate the final grade for a student who receives the following 10 grades during a semester: C, C, MA (Missing Assignment), D, C, B, MA, MA, B, A. I have done this experiment with thousands of teachers and administrators in the United States, Canada, and Argentina. Every time—bar none—I get the same results: The final grades range from F to A and include everything in between.
Managing Shared L2 Caches on Multicore Systems in Software

—Most of today’s multi-core processors feature shared L2 caches. A major problem faced by such architectures is cache contention, where multiple cores compete for usage of the single shared L2 cache. Uncontrolled sharing leads to scenarios where one core evicts useful L2 cache content belonging to another core. To address this problem, we have implemented a software mechanism in the operating system that allows for partitioning of the shared L2 cache by guiding the allocation of physical pages. This mechanism, which can also be applied to virtual machine monitors, provides isolation capabilities that lead to reduced contention. We show that this mechanism is effective in reducing cache contention in multiprogrammed SPECcpu2000 and SPECjbb2000 workloads. Performance improvements of up to 17% were achieved without adversely affecting co-scheduled applications. Inorderto effectively size L2 cache partitions, a quantiﬁable metric is needed to properly
Gender Differences Time Trends for Metabolic Syndrome and Its Components among Tehranian Children and Adolescents

Aims. To investigate the trend of metabolic syndrome and its components in Tehran children and adolescents during a median followup of 6.6 years. Methods. Data from 1999–2001 (phase I), 2002–2005 (phase II), and 2006–2008 (phase III) of the Tehran, Lipid and Glucose Study were analyzed (n = 5439; age 6–18 years) for the trend of metabolic syndrome (MetS) and its components. General estimation equation (GEE) models were used to analyze this correlated data. Results. The crude prevalence of MetS for boys at baseline was 13.2%, which increased to 16.4% in the third phase. In girls, the prevalence of Mets decreased from 11.8% at baseline to 6% during followup. The odd ratios (OR) of obesity over the whole study period were raised in both sexes. The OR of abdominal obesity increased significantly in boys, but no change was observed in girls. No significant OR was observed in boys, while OR for MetS was shown to have a decreasing trend in girls during the followup. In the three time points, the ORs of MetS decreased significantly in girls but no significant difference was observed in boys. Conclusion. Inspite of increasing trend for obesity in both sexes, the trend of MetS decreased in girls and was relatively stable in boys, in Tehranian children, and adolescents.
Thesis for the Degree of Doctor of Philosophy Systems Biology of the Gut Microbiome in Metabolic Diseases Systems Biology of the Gut Microbiome in Metabolic Diseases

Cover: Concept of metagenomics: DNA is extracted and sequenced from a microbial community. Sequences are annotated to metabolic functions. Abstract The human body is hosting a tremendous number of microbial cells and many of these reside in our gut. The gut microbes perform breakdown of indigestible dietary components and contribute to energy harvesting from food. Furthermore, there is a constant interaction between our microbes and our immune system to fend of pathogens and tolerate commensals. Evidence suggests that the composition of the gut microbiota is altered in obesity and could contribute to development of obesity related metabolic diseases. This thesis presents results that show an association between the gut microbiome, the collective genomes of the microbiota, and symptomatic atherosclerosis. The gut microbiome was also found to be associated with diabetes and a classifying model for diabetic status was developed. A novel method for grouping genes into metagenomic clusters that are likely derived from the same genome is also presented. Bariatric surgery is an effective method for treating obesity and reduces the risk of its co-morbidities. It was also found that the gut metagenome is altered considerably after bariatric surgery. Two software tools for metagenomic data analysis and hypothesis testing are presented. MEDUSA is software for quality control and annotation of metagenomic sequence reads. MEDUSA was used for the analysis of 782 gut metagenomes and a global human gut microbial gene catalogue was constructed and evaluated. FANTOM is software with a graphical user interphase that provides hypothesis testing in a taxonomical and functional context. To model key metabolic functions of gut microbes, genome-scale metabolic models of three species from the human gut are presented and their interactions are evaluated. This work contributes to the knowledge of associations between the gut microbiota and metabolic diseases. A number of novel methods for data analysis of gut metagenome data are presented. Data Utilization and Analysis and construction of a global gut microbial gene catalogue (Submitted) VII. (2013). Genome-scale metabolic reconstructions of Bifidobacterium adolescentis L2-32 and Faecalibacterium prausnitzii A2-165 and their interaction. (Submitted) v Contributions I. Performed metagenomic data analysis. Drafted and edited the paper. II. Performed metagenomic data analysis. Participated in drafting and editing of the paper. III. Performed metagenomic data analysis. Participated in drafting and editing of the paper. IV. Drafted and edited the paper. V. Supervised the work in detail and participated in drafting and editing of the paper. VI. Designed the …
Two field BPS solutions for generalized Lorentz breaking models

In this work we present nonlinear models in two-dimensional space-time of two interacting scalar fields in the Lorentz and CPT violating scenarios. We discuss the soliton solutions for these models as well as the question of stability for them. This is done by generalizing a model recently published by Barreto and collaborators and also by getting new solutions for the model introduced by them.
Private Stream Aggregation Revisited

In this work, we investigate the problem of private statistical analysis in the distributed and semi-honest setting. In particular, we study properties of Private Stream Aggregation schemes, first introduced by Shi et al. \cite{2}. These are computationally secure protocols for the aggregation of data in a network and have a very small communication cost. We show that such schemes can be built upon any key-homomorphic \textit{weak} pseudo-random function. Thus, in contrast to the aforementioned work, our security definition can be achieved in the \textit{standard model}. In addition, we give a computationally efficient instantiation of this protocol based on the Decisional Diffie-Hellman problem. Moreover, we show that every mechanism which preserves $(\epsilon,\delta)$-differential privacy provides \textit{computational} $(\epsilon,\delta)$-differential privacy when it is executed through a Private Stream Aggregation scheme. Finally, we introduce a novel perturbation mechanism based on the \textit{Skellam distribution} that is suited for the distributed setting, and compare its performances with those of previous solutions.
Optimization of the Mobile Router and Traffic Sources in Vehicular Delay-Tolerant Network

Vehicular delay-tolerant networks (VDTNs) are introduced for communications between traffic sources and sinks, in which direct end-to-end connection is not available. In this VDTN, mobile routers installed on the vehicles are used as carriers to carry data from traffic sources to sinks. We first present the optimization formulation based on the constrained Markov decision process (CMDP) to obtain an optimal decision for the mobile router on whether to accept packets from a traffic source. This decision is made to maximize the reward of data delivery while the quality-of-service (QoS) performance is guaranteed. Then, the noncooperative game and optimization formulations are presented for the cases when traffic sources have a self-interest to maximize their own benefit and a global interest to maximize the total benefit of the network, respectively. From the performance evaluation, a mobile router with CMDP optimization can achieve the highest reward while the maximum packet-blocking probability requirement is met. With noncooperative game formulation for the traffic sources, the Nash equilibrium can be obtained. Alternatively, if the traffic sources are cooperative, the largest total benefit of the network can be achieved.
RTEMS Core Analysis for Space Applications

Overheads due to context switching and external interrupt management are core characteristics for Real-Time Operating Systems (RTOS) since they play a central role in their performance and timeliness. In this paper we evaluate two core characteristics for the Real-Time Executive for Multiprocessor Systems (RTEMS), an operating system used for supporting space applications. Our assessment makes use of an external non-intrusive measurement tool based on a Field-Programmable Gate Array (FPGA). Measurement data are then transferred to an external computer and analyzed off-line. Experiments are carried out on a device that complies with the Brazilian space program recommendation.
Predictive display for mobile manipulators in unknown environments using online vision-based monocular modeling and localization

To tele-operate a robot, visual feedback is critical. However, communication channel latency can delay feedback to the point where the operator is impeded in performing his task. This work presents a vision-based “predictive display” system that compensates for visual delay. The approach is online and relatively uncalibrated, thus it has the advantage of being useful in unknown environments and many applications. From monocular eye-in-hand video, we incrementally compute a 3D graphics model of the robot site in real time using our new technique. The method exploits free-space/occlusion constraints on the scene to produce a physically consistent mesh. Novel vantage points are immediately rendered in response to the operator's control commands, without waiting for delayed video. We implement a full prototype tele-operation system where the operator controls, via a PHANTOM Omni device, a Barrett WAM robot mounted on a mobile Segway. Experiments with this setup validate the efficacy of the proposed approach. We demonstrate significant improvement in task completion time with predictive display on a real robot, while our previous related results were established only in simulation.
Situated interaction in ubiquitous computing

The situations in which human-computer interaction takes place are increasingly varied, as computers become highly portable and embedded in everyday environments. Research reported from different communities (Wearable Computing, Mobile Computing, HCI, CSCW, Augmented Reality) indicates that awareness of situations can lead to improvement of human-computer interaction. We propose a workshop at CHI2000 to provide a forum to discuss situational awareness and situated interaction.With the availability of sensing technologies, such as measuring the surrounding light conditions, the motion of the user, the orientation of a display, users' position relative to an information appliance, the number of users in front of a device, users' emotional state (bio-sensors), etc., this situational context can be captured and used as additional input to the system. The interaction process can benefit from the additional knowledge about the situation [1].
Exchange protein activated by cyclic AMP 2 (Epac2) plays a specific and time‐limited role in memory retrieval

Knowledge on the molecular mechanisms involved in memory retrieval is limited due to the lack of tools to study this stage of the memory process. Here we report that exchange proteins activated by cAMP (Epac) play a surprisingly specific role in memory retrieval. Intrahippocampal injection of the Epac activator 8‐pCPT‐2′O‐Me‐cAMP was shown to improve fear memory retrieval in contextual fear conditioning whereas acquisition and consolidation were not affected. The retrieval enhancing effect of the Epac activator was even more prominent in the passive avoidance paradigm. Down‐regulation of Epac2 expression in the hippocampal CA1 area impaired fear memory retrieval when the memory test was performed 72 h after training, but not when tested after 17 days. Our data thus identify an important time‐limited role for hippocampal Epac2 signaling in cognition and opens new avenues to investigate the molecular mechanisms underlying memory retrieval. © 2009 Wiley‐Liss, Inc.
NECLC at Multilingual Opinion Analysis Task in NTCIR8

paper, we briefly describe our machine-learning based method used in the NITCIR8 MOAT task, particularly, the opinioned sentence judgment subtask on both English side and Chinese side. We view this subtask as a binary classification problem and build a supervised-learning based framework. To extract meaningful sentiment features, we propose several n-gram patterns to assemble basic words and part-of-speech tags. Meanwhile, our basic classifiers are trained merely on the previous NTICR annotated corpus, in which samples are inadequate and unbalanced. Thus, we adopt a few self-learning strategies to utilize the NTCIR8 testing corpus to adjust our basic classifiers. Using the same learning framework in both language sides, we get similar performances.
Single-Scale Retinex Using Digital Signal Processors

The Retinex is an image enhancement algorithm that improves the brightness, contrast and sharpness of an image. It performs a non-linear spatial/spectral transform that provides simultaneous dynamic range compression and color constancy. It has been used for a wide variety of applications ranging from aviation safety to general purpose photography. Many potential applications require the use of Retinex processing at video frame rates. This is difficult to achieve with general purpose processors because the algorithm contains a large number of complex computations and data transfers. In addition, many of these applications also constrain the potential architectures to embedded processors to save power, weight and cost. Thus we have focused on digital signal processors (DSPs) and field programmable gate arrays (FPGAs) as potential solutions for real-time Retinex processing. In previous efforts we attained a 21 (full) frame per second (fps) processing rate for the single-scale monochromatic Retinex with a TMS320C6711 DSP operating at 150 MHz. This was achieved after several significant code improvements and optimizations. Since then we have migrated our design to the slightly more powerful TMS320C6713 DSP and the fixed point TMS320DM642 DSP. In this paper we briefly discuss the Retinex algorithm, the performance of the algorithm executing on the TMS320C6713 and the TMS320DM642, and compare the results with the TMS320C6711.
Supplementary Appendices for " a Study of Situationally Aware Routing for Emergency Responders " a Nomenclature

T c = congested link travel time (seconds) T f = free-flow link travel time (seconds) v = link traffic volume (vehicles) c = link capacity (vehicles) α, β = volume/delay coefficients S r c = regular vehicle congested link travel speed (feet/hour) S e c = emergency vehicle congested link travel speed (feet/hour) S f = free-flow link travel speed (feet/hour) u = utilization of road segment in Arena (percent) w = weather slowdown effect (percent) e = EMS vehicle slowdown effect (percent) X = the set of candidate nodes ¯ X = the set of all nodes not yet optimized L = the set of all links in the network l j = travel time or cost from the origin to node j l ij = travel time or cost from node i to node j p j = predecessor of node j R = performance measure of estimated travel time technique A e = Estimated EMS travel time (minutes) A s = Average EMS travel time from five simulation replications (minutes) M in s = Minimum EMS travel time from five simulation replications (minutes) M ax s = Maximum EMS travel time from five simulation replications (minutes) V ar s = Variance of EMS travel time from five simulation replications (minutes 2) VSCP = Variance-Constrained Shortest Path x ij = decision variable in the VCSP problem (1 if link i to j is used, 0 otherwise) λ = limiting value for the constraints in the VCSP problem µ = dual variable of the VCSP used in solving the dual problem v ij = variance of link i to j in the VCSP problem c ijkl = covariance between links i to j and k to l
System reliability approach to rock slope stability

A systematic quantitative methodology for the reliability analysis of stability of rock slopes is presented. A sliding mass resting on an inclined plane and composed of two blocks separated by a vertical tension crack is considered, and a disjoint cut-set system formulation is proposed, with each cut-set corresponding to a different failure mode of the slope. Methods for the evaluation of the system reliability problem are discussed and applied to solve an example problem. Monte Carlo simulation method may be used to obtain the ‘‘exact’’ solution, at the expense of a higher computational cost, while methods based on first order approximations are found to be computationally efficient and to provide information of interest for the design process, but they are also shown not to be particularly accurate in some cases. The results also show that reliability bounds based on linear programming provide a flexible way of estimating the range of possible failure probabilities, and that accurate estimations of the probability of failure are obtained when sufficient information is considered. r 2006 Elsevier Ltd. All rights reserved.
Power and Area Minimization of Reconfigurable FFT Processors: A 3GPP-LTE Example

This paper presents a design methodology for power and area minimization of flexible FFT processors. The methodology is based on the power-area tradeoff space obtained by adjusting algorithm, architecture, and circuit variables. Radix factorization is the main technique for achieving high energy efficiency with flexibility, followed by architecture parallelism and delay line circuits. The flexibility is provided by reconfigurable processing units that support radix-2/4/8/16 factorizations. As a proof of concept, a 128- to 2048-point FFT processor for 3GPP-LTE standard has been implemented in a 65-nm CMOS process. The processor designed for minimum power-area product is integrated in 1.25 × 1.1 mm2 and dissipates 4.05 mW at 0.45 V for the 20 MHz LTE bandwidth. The energy dissipation ranging from 2.5 to 103.7 nJ/FFT for 128 to 2048 points makes it the lowest energy flexible FFT.
JAK2-Centered Interactome Hotspot Identified by an Integrative Network Algorithm in Acute Stanford Type A Aortic Dissection

The precise mechanisms underlying dissections, especially those without connective tissue diseases or congenital vascular diseases, are incompletely understood. This study attempted to identify both the expression profile of the dissected ascending aorta and the interactome hotspots associated with the disease, using microarray technology and gene regulatory network analysis. There were 2,737 genes differentially expressed between patients with acute Stanford type A aortic dissection and controls. Eight interactome hotspots significantly associated with aortic dissection were identified by an integrative network algorithm. In particular, we identified a JAK2-centered expression module, which was validated in an independent gene expression microarray data set, and which was characterized by over-expressed cytokines and receptors in acute aortic dissection cases, indicating that JAK2 may play a key role in the inflammatory process, which potentially contributes to the occurrence of acute aortic dissection. Overall, the analytical strategy used in this study offered the possibility to identify functional relevant network modules and subsequently facilitated the biological interpretation in the complicated disease.
Aqueous Oxidative Heck Reaction as a Protein-Labeling Strategy

An increasing number of chemical reactions are being employed for bio‐orthogonal ligation of detection labels to protein‐bound functional groups. Several of these strategies, however, are limited in their application to pure proteins and are ineffective in complex biological samples such as cell lysates. Here we present the palladium‐catalyzed oxidative Heck reaction as a new and robust bio‐orthogonal strategy for linking functionalized arylboronic acids to protein‐bound alkenes in high yields and with excellent chemoselectivity even in the presence of complex protein mixtures from living cells. Advantageously, this reaction proceeds under aerobic conditions, whereas most other metal‐catalyzed reactions require inert atmosphere.
A modular RNN-based method for continuous Mandarin speech recognition

A new modular recurrent neural network (MRNN)-based method for continuous Mandarin speech recognition (CMSR) is proposed. The MRNN recognizer is composed of four main modules. The first is a sub-MRNN module whose function is to generate discriminant functions for all 412 base-syllables. It accomplishes the task by using four recurrent neural network (RNN) submodules. The second is an RNN module which is designed to detect syllable boundaries for providing timing cues in order to help solve the time-alignment problem. The third is also an RNN module whose function is to generate discriminant functions for 143 intersyllable diphone-like units to compensate the intersyllable coarticulation effect. The fourth is a dynamic programming (DP)-based recognition search module. Its function is to integrate the other three modules and solve the time-alignment problem for generating the recognized base-syllable sequence. A new multilevel pruning scheme designed to speed up the recognition process is also proposed. The whole MRNN can be trained by a sophisticated three-stage minimum classification error/generalized probabilistic descent (MCE/GPD) algorithm. Experimental results showed that the proposed method performed better than the maximum likelihood (ML)-trained hidden Markov model (HMM) method and is comparable to the MCE/GPD-trained HMM method. The multilevel pruning scheme was also found to be very efficient.
Estimation of a Common Mean and Weighted Means Statistics

Abstract Measurements made by several laboratories may exhibit nonnegligible between-laboratory variability, as well as different within-laboratory variances. Also, the number of measurements made at each laboratory often differ. Questions of fundamental importance in the analysis of such data are how to form a best consensus mean, and what uncertainty to attach to this estimate. An estimation equation approach due to Mandel and Paule is often used at the National Institute of Standards and Technology (NIST), particularly when certifying standard reference materials. Primary goals of this article are to study the theoretical properties of this method, and to compare it with some alternative methods, in particular to the maximum likelihood estimator (MLE). Toward this end, we show that the Mandel-Paule solution can be interpreted as a simplified version of the maximum likelihood method. A class of weighted means statistics is investigated for situations where the number of laboratories is large. This class.