Miracle-dz/UniFAR-FTUs huggingface dataset:
GPUVolt: Modeling and characterizing voltage noise in GPU architectures

Voltage noise is a major obstacle in improving processor energy efficiency because it necessitates large operating voltage guardbands that increase overall power consumption and limit peak performance. Identifying the leading root causes of voltage noise is essential to minimize the unnecessary guardband and maximize the overall energy efficiency. We provide the first-ever modeling and characterization of voltage noise in GPUs based on a new simulation infrastructure called GPUVolt. Using it, we identify the key intracore microarchitectural components (e.g., the register file and special functional units) that significantly impact the GPU's voltage noise. We also demonstrate that intercore-aligned microarchitectural activity detrimentally impacts the chip-wide worst-case voltage droops. On the basis of these findings, we propose a combined register-file and execution-unit throttling mechanism that smooths GPU voltage noise and reduces the guardband requirement by as much as 29%.
Query-Time Reasoning in Uncertain RDF Knowledge Bases with Soft and Hard Rules

Recent advances in information extraction have paved the way for the automatic construction and growth of large, semantic knowledge bases from Web sources. However, the very nature of these extraction techniques entails that the resulting RDF knowledge bases may face a significant amount of incorrect, incomplete, or even inconsistent (i.e., uncertain) factual knowledge, which makes efficient query answering over this kind of uncertain RDF data a challenge. Our engine, coined URDF, augments first-order reasoning by a combination of soft rules (Datalog-style implications), which are grounded in a deductive fashion in order to derive new facts from existing ones, and hard rules (mutual-exclusiveness constraints), which enforce additional consistency constraints among both base and derived facts. At the core of our approach is an efficient approximation algorithm for this constrained form of the weighted MaxSAT problem with soft and hard rules, allowing us to dynamically resolve inconsistencies directly at query-time. Experiments on real-world and synthetic data confirm a high robustness and significantly improved runtime of our framework in comparison to state-of-the-art MCMC techniques.
Identification of a segment of the Escherichia coli Tsx protein that functions as a bacteriophage receptor area

The Escherichia coli outer membrane protein Tsx functions as a nucleoside-specific channel and serves as the receptor for colicin K and a number of T-even-type bacteriophages, including phage T6. To identify those segments of the Tsx protein that are important for its phage receptor function, we devised a selection and screening procedure which allowed us to isolate phage-resistant strains synthesizing normal amounts of Tsx. Three different Tsx-specific phages (T6, Ox1, and H3) were employed for the selection of phage-resistant derivatives of a strain expressing a tsx(+)-lacZ+ operon fusion, and 28 tsx mutants with impaired phage receptor function were characterized. Regardless of the Tsx-specific phage used for the initial mutant selection, cross-resistance against a set of six different Tsx phages invariably occurred. With one exception, these mutant Tsx proteins could still serve as a colicin K receptor. DNA sequence analysis of 10 mutant tsx genes revealed the presence of four distinct tsx alleles: two point mutations, an 18-bp deletion, and a 27-bp tandem duplication. In three isolates, Asn-249 was replaced by a Lys residue (tsx-504), and in four others, residue Asn-254 was replaced by Lys (tsx-505). The deletion (tsx-506; one isolate) removed six amino acids (residue 239 to residue 244) from the 272-residue Tsx polypeptide chain, and the DNA duplication (tsx-507; two isolates) resulted in the addition of nine extra amino acids (residue 229 to residue 237) to the Tsx protein. In contrast to the wild-type Tsx protein and the other mutant Tsx proteins the Tsx-507 protein was cleaved by trypsin when intact cells were treated with this protease. The Tsx proteins encoded by the four tsx alleles still functioned in deoxyadenosine uptake in vivo, demonstrating that their nucleoside-specific channel activity was not affected by the alterations that caused the loss of their phage receptor function. HTe changes in the Tsx polypeptide that confer resistance against the Tsx-specific phages are clustered in a small region near the carboxy terminus of Tsx. Our results are discussed in terms of a model for the topological organization of the carboxy-terminal end of the Tsx protein within the outer membrane.
CiCUTS: Combining System Execution Modeling Tools with Continuous Integration Environments

System execution modeling (SEM) tools provide an effective means to evaluate the quality of service (QoS) of enterprise distributed real-time and embedded (DRE) systems. SEM tools facilitate testing and resolving performance issues throughout the entire development life-cycle, rather than waiting until final system integration. SEM tools have not historically focused on effective testing. New techniques are therefore needed to help bridge the gap between the early integration capabilities of SEM tools and testing so developers can focus on resolving strategic integration and performance issues, as opposed to wrestling with tedious and error-prone low-level testing concerns. This paper provides two contributions to research on using SEM tools to address enterprise DRE system integration challenges. First, we evaluate several approaches for combining continuous integration environments with SEM tools and describe CiCUTS, which combines the CUTS SEM tool with the CruiseControl.NET continuous integration environment. Second, we present a case study that shows how CiCUTS helps reduce the time and effort required to manage and execute integration tests that evaluate QoS metrics for a representative DRE system from the domain of shipboard computing. The results of our case study show that CiCUTS helps developers and testers ensure the performance of an example enterprise DRE system is within its QoS specifications throughout development, instead of waiting until system integration time to evaluate QoS.
Quality of Instruction: Examining Discourse in Middle Schoo Mathematics Instruction

According to the NCTM reform suggestions, when teachers are orchestrators of student interactions, students adopt a more active role in explaining and learning mathematics. This research, which mapped the nature and role of meaningful mathematical discourse, provides insights into discursive practices that lead to rich mathematical interactions. We observed, coded, and analyzed middle school algebra, number, and data lessons using a grounded theory approach. We organized the observed paths that emerged into a map depicting actual paths for mathematics discourse. The results indicated that communication pathways between the teacher and students occur in many ways, and certain student-initiated questions may trigger predictable teaching patterns. Conversation that originates with the teacher often results in dialogue that is one-dimensional, mostly provides factual information, and rarely results in rich, meaningful mathematical dialogue. However, when students engage in the teacher's conversation or they are persistent in their own questioning, teachers tended to provide more detailed explanations, and teachers often embellished with new examples and representations using nuanced solution methods. Although results seem to indicate that teaching children to be persistent with their questioning will enhance understanding, this behavior may be interpreted as threatening to some teachers. Therefore, caution is warranted when attempting to turn these findings into action. It is important that, before instructing students about being persistent with questions, teachers understand the students' intentions. Although participants did not have negative reactions to persistent student questioning, some children might experience negative responses without proper professional development for teachers.
Predicting software escalations with maximum ROI

Enterprise software vendors often have to release software products before all reported defects are corrected, and a small number of these reported defects will be escalated by customers whose businesses are seriously impacted. Escalated defects must be quickly resolved at a high cost by the software vendors. The total costs can be even greater, including loss of reputation, satisfaction, loyalty, and repeat revenue. In this paper, we develop an Escalation Prediction (EP) system to mine historic defect report data and predict the escalation risk of current defect reports for maximum ROI (Return On Investment). More specifically, we first describe a simple and general framework to convert the maximum ROI problem to cost-sensitive learning. We then apply and compare several best-known cost-sensitive learning approaches for EP. The EP system has produced promising results, and has been deployed in the product group of an enterprise software vendor. Conclusions drawn from this study also provide guidelines for mining imbalanced datasets and cost-sensitive learning.
Marking Observer in Labeled Petri Nets With Application to Supervisory Control

In this paper, we consider the problem of marking estimation in labeled Petri nets whose initial marking is known to belong to a given convex set, in the presence of silent transitions (i.e., transitions labeled with the empty word) and indistinguishable transitions (i.e., transitions sharing the same label with other transitions). First, we demonstrate that all sets of markings consistent with a given sequence of observations can be described in linear algebraic terms (as a union of convex sets); subsequently, this observation is used to construct (offline) a marking observer under appropriate boundedness assumptions. Using the marking observer we show how to derive, at design time, a state feedback control law under the assumption that all transitions sharing a label can be enabled or disabled simultaneously as a group; this way, the most burdensome part of the computations is performed offline.
Culture Differences, Difficulties, and Challenges of the Neurophysiological Methods in Marketing Research

ABSTRACT Given recent technological improvements, social consumer researchers are reaching out for disciplines such as neuroscience and biomedical engineering. The purpose of this article is threefold. First, we briefly review each neurophysiological method. Second, we present cultural studies in marketing showing the importance of using neurophysiological tools in different cultures. Third, we discuss reasons why some areas have not benefitted from this interdisciplinary approach yet. For that, we interviewed Latin American researchers because of the importance of this region and the very little academic discussion on the challenges and caveats associated with conducting consumer research in this region. We conclude the article with insights to overcome these challenges.
Analysis of the Golgi Apparatus in Arabidopsis Seed Coat Cells during Polarized Secretion of Pectin-Rich Mucilage[W][OA]

Differentiation of the Arabidopsis thaliana seed coat cells includes a secretory phase where large amounts of pectinaceous mucilage are deposited to a specific domain of the cell wall. During this phase, Golgi stacks had cisternae with swollen margins and trans-Golgi networks consisting of interconnected vesicular clusters. The proportion of Golgi stacks producing mucilage was determined by immunogold labeling and transmission electron microscopy using an antimucilage antibody, CCRC-M36. The large percentage of stacks found to contain mucilage supports a model where all Golgi stacks produce mucilage synchronously, rather than having a subset of specialist Golgi producing pectin product. Initiation of mucilage biosynthesis was also correlated with an increase in the number of Golgi stacks per cell. Interestingly, though the morphology of individual Golgi stacks was dependent on the volume of mucilage produced, the number was not, suggesting that proliferation of Golgi stacks is developmentally programmed. Mapping the position of mucilage-producing Golgi stacks within developing seed coat cells and live-cell imaging of cells labeled with a trans-Golgi marker showed that stacks were randomly distributed throughout the cytoplasm rather than clustered at the site of secretion. These data indicate that the destination of cargo has little effect on the location of the Golgi stack within the cell.
Contour Deletion as a Method for Identifying the Weights of Features Underlying Object Recognition

A prerequisite for comparative work on object recognition is a method for identifying the features actually extracted from the form. The method introduced here with pigeons is discrimination training between two simple line drawings, followed by a generalization test in which contour is deleted from the reinforced drawing. In Condition 1, the line drawings were a square (S+) versus a triangle (S−); for Condition 2, the line drawings were planar projections of a cube (S+) versus a truncated pyramid (S−). The generalization decrement between responses to S+ and responses to test stimuli provides a quantitative index of the weight assigned to each feature. Contour deletion at either vertices or midsegments produced a decrement in the rate of responding, showing that each contour was represented as a feature. The generalization decrement to forms containing vertices with midsegments deleted was larger than the generalization decrement to forms containing midsegments with vertices deleted. Therefore, it appears that midsegments are weighted more strongly as features than vertices. Contour deletion provides a direct method for identifying the visual features underlying object recognition and lays a foundation for the development of comparative theories of object recognition.
Manufacture and Characterization of High Q-Factor Inductors Based on CMOS-MEMS Techniques

A high Q-factor (quality-factor) spiral inductor fabricated by the CMOS (complementary metal oxide semiconductor) process and a post-process was investigated. The spiral inductor is manufactured on a silicon substrate. A post-process is used to remove the underlying silicon substrate in order to reduce the substrate loss and to enhance the Q-factor of the inductor. The post-process adopts RIE (reactive ion etching) to etch the sacrificial oxide layer, and then TMAH (tetramethylammonium hydroxide) is employed to remove the silicon substrate for obtaining the suspended spiral inductor. The advantage of this post-processing method is its compatibility with the CMOS process. The performance of the spiral inductor is measured by an Agilent 8510C network analyzer and a Cascade probe station. Experimental results show that the Q-factor and inductance of the spiral inductor are 15 at 15 GHz and 1.8 nH at 1 GHz, respectively.
Real-time pedestrian detection in urban scenarios

A real-time pedestrian detection system is presented that runs at 24 fps on standard VGA resolution input images (640×480px) using only CPU processing. The detection algorithm uses a variable sized sliding window and intelligent simplifications such as a sparse scale space and fast candidate selection to obtain the desired speed. Details are provided about the initial version of the system ported on a mobile device. We also present a new labeled pedestrian dataset that was captured from a moving car that is suitable for training and testing pedestrian detection methods in urban scenarios.
Episialin (MUC1) overexpression inhibits integrin-mediated cell adhesion to extracellular matrix components

Episialin (MUC1) is a transmembrane molecule with a large mucin-like extracellular domain protruding high above the cell surface. The molecule is located at the apical side of most glandular epithelial cells, whereas in carcinoma cells it is often present at the entire surface and it is frequently expressed in abnormally large quantities. We have previously shown that overexpression of episialin reduces cell- cell interactions. Here we show that the integrin-mediated adhesion to extracellular matrix of transfectants of a melanoma cell line (A375), a transformed epithelial cell line (MDCK-ras-e) and a human breast epithelial cell line (HBL-100) is reduced by high levels of episialin. This reduction can be reversed by inducing high avidity of the beta 1 integrins by mAb TS2/16 (at least for beta 1-mediated adhesion). The adhesion can also be restored by redistribution of episialin on the cell surface by monoclonal antibodies into patches or caps. Similarly, capping of episialin on ZR-75-1 breast carcinoma cells, growing in suspension, caused adherence and spreading of these cells. We propose that there is a delicate balance between adhesion and anti-adhesion forces in episialin expressing cells, which can be shifted towards adhesion by strengthening the integrin-mediated adhesion, or towards anti-adhesion by increasing the level of expression of episialin.
Spoofing detection employing infinite impulse response — constant Q transform-based feature representations

Speaker recognition researchers acknowledge that systems which aim to verify speakers automatically based on their pronunciation of an utterance are vulnerable to spoofing attacks using voice conversion and speech synthesis technologies. The first automatic speaker verification spoofing and countermeasures challenge (ASVspoof2015) was designed to stimulate interest in this problem among the speaker recognition communities. In the course of the challenge and subsequently, it became clear that the most effective countermeasures against spoofing attacks are low-level acoustic features (typically extracted at 10 ms intervals) designed to detect artifacts in synthetic or voice converted speech. In this work, we demonstrate the effectiveness of the infinite impulse response — constant Q transform (IIR-CQT) spectrum-based cepstral coefficients (ICQC) as anti-spoofing front-end. The IIR-CQT spectrum is estimated by filtering the multi-resolution fast Fourier transform with an infinite impulse response filter. These features can be used on their own with a standard Gaussian mixture model backend to detect spoofing attacks or they can be used in tandem with bottleneck features which are extracted from a bottleneck layer in a deep neural network designed to discriminate between synthetic and natural speech. We show that the ICQC features are capable of producing very low equal error rates on the individual spoofing attacks in the ASVspoof2015 data set (0.02% on the known attacks, 0.23% on the unknown attacks, and 0.13% on average). Moreover, with a single decision threshold (common to all of the attacks), the ICQC front end yielded an equal error rate of 0.20%.
A Dynamic Fuzzy Clustering Scheme in Overlay Multicast

This paper proposed a dynamic fuzzy clustering scheme with adaptive fuzzy threshold to the hierarchical topology optimization in overlay multicast. The scheme firstly normalized the two routing metrics - overlay path delay and overlay node access bandwidth-- to comprise the clustering feature vector, and then calculated the Euclidean distance within each pair of overlay nodes to construct the fuzzy membership matrix. Furthermore, inspired by the statistic histogram principle, the scheme dynamically adapted the fuzzy clustering threshold to the statistic results from the fuzzy membership matrix for the better clustering results. Compared with non-clustering method and HCM, the experiments illustrated that the proposed scheme performs better in both the clustering performance and the routing optimization.
Ex vivo Analysis of Resident Hepatic Pro-inflammatory CD 1 d-reactive T cells & Hepatocyte Surface CD 1 d Expression in Hepatitis C

Hepatic CD1d-restricted and natural killer T cell populations are heterogeneous. Classical ‘Type 1’ α-galactosylceramide-reactive CD1d-restricted T cells express ‘invariant’ TCRα (‘iNKT’). iNKT dominating rodent liver are implicated in inflammation, including in hepatitis models. Low levels of iNKT are detected in human liver, decreased in subjects with chronic hepatitis C (CHC). However, high levels of human hepatic CD161±CD56± non-invariant pro-inflammatory CD1drestricted ‘Type 2’ T cells have been identified in vitro. Unlike rodents, healthy human hepatocytes only express trace and intracellular CD1d. Total hepatic CD1d appears to be increased in CHC and primary biliary cirrhosis. Direct ex vivo analysis of human intra-hepatic lymphocytes (IHL), including matched ex vivo versus in vitro expanded IHL, demonstrated detectable non-invariant CD1d-reactivity in substantial proportions of HCV-positive livers and significant fractions of HCV-negative livers. However, α-galactosylceramide-reactive iNKT were detected only relatively rarely. Liver CD1drestricted IHL produced IFNγ, variable levels of IL-10, and modest levels of Th2 cytokines IL-4 and IL-13 ex vivo. In a novel FACS assay, a major fraction (10–20%) of hepatic T cells rapidly produced IFNγ and up-regulated activation marker CD69 in response to CD1d. As previously only shown with murine iNKT, non-invariant human CD1d-specific responses were augmented by IL-12. Interestingly, CD1d was also found selectively expressed on the surface of hepatocytes in CHC, but not those CHC subjects with history of alcohol usage or resolved CHC. In contrast to hepatic iNKT, non-invariant IFNγ-producing Type 2 CD1d-reactive NKT cells are commonly detected in CHC, together with cognate ligand CD1d, implicating them in CHC liver damage. Correspondence: Dr. Exley, Brigham & Women’s Hospital, 75 Francis Street, Boston, MA 02115. mexley@partners.org. +Current addresses: Surgery, Kasumigaura Medical Center, Ibaraki, Japan. #Medical Oncology, Vrije Universiteit, Amsterdam. ^AVEO Pharmaceuticals, Cambridge, MA. *Vertex Pharmaceuticals, Cambridge, MA. Disclosure Authors declare no competing interests. NIH Public Access Author Manuscript J Viral Hepat. Author manuscript; available in PMC 2014 August 01. Published in final edited form as: J Viral Hepat. 2013 August ; 20(8): 556–565. doi:10.1111/jvh.12081. N IH -P A A uhor M anscript N IH -P A A uhor M anscript N IH -P A A uhor M anscript
BM3D mridenoising equipped with noise invalidation technique

Block-matching and 3D filtering (BM3D) has shown a great success in image denoising. In this work we propose a new denoising approach for Magnetic Resonance Imaging (MRI) based on a modified BM3D algorithm. BM3D is a combination of nonlocal approach, 3D wavelet shrinkage, and 3D Wiener filtering. We improve the wavelet thresholding stage of BM3D using Noise Invalidation Denoising (NIDe) technique. The new approach provides the optimum wavelet threshold automatically and adaptive to the statistical characteristics of the available data. This is an advantage over the existing denoising stage of BM3D that currently uses an adhoc thresholding value. Combining the proposed BM3D approach with Variance Stabilization Transformation (VST) enables the use of the proposed method for Magnetic Resonance (MR) Image denoising. In our Simulations, the proposed method outperforms the state of the art BM3D based MRI denoising methods in the sense of PSNR and SSIM for T1, T2 and PD weighted MR images.
Extrusion versus diffusion: mechanisms for recovery from sodium loads in mouse CA1 pyramidal neurons

Neuronal activity causes local or global sodium signalling in neurons, depending on the pattern of synaptic activity. Recovery from global sodium loads critically relies on Na+/K+‐ATPase and an intact energy metabolism in both somata and dendrites. For recovery from local sodium loads in dendrites, Na+/K+‐ATPase activity is not required per se. Instead, recovery is predominately mediated by lateral diffusion, exhibiting rates that are 10‐fold higher than for global sodium signals. Recovery from local dendritic sodium increases is still efficient during short periods of energy deprivation, indicating that fast diffusion of sodium to non‐stimulated regions strongly reduces local energy requirements.