Miracle-dz/UniFAR-FTUs huggingface dataset:
GPUWattch: enabling energy optimizations in GPGPUs

General-purpose GPUs (GPGPUs) are becoming prevalent in mainstream computing, and performance per watt has emerged as a more crucial evaluation metric than peak performance. As such, GPU architects require robust tools that will enable them to quickly explore new ways to optimize GPGPUs for energy efficiency. We propose a new GPGPU power model that is configurable, capable of cycle-level calculations, and carefully validated against real hardware measurements. To achieve configurability, we use a bottom-up methodology and abstract parameters from the microarchitectural components as the model's inputs. We developed a rigorous suite of 80 microbenchmarks that we use to bound any modeling uncertainties and inaccuracies. The power model is comprehensively validated against measurements of two commercially available GPUs, and the measured error is within 9.9% and 13.4% for the two target GPUs (GTX 480 and Quadro FX5600). The model also accurately tracks the power consumption trend over time. We integrated the power model with the cycle-level simulator GPGPU-Sim and demonstrate the energy savings by utilizing dynamic voltage and frequency scaling (DVFS) and clock gating. Traditional DVFS reduces GPU energy consumption by 14.4% by leveraging within-kernel runtime variations. More finer-grained SM cluster-level DVFS improves the energy savings from 6.6% to 13.6% for those benchmarks that show clustered execution behavior. We also show that clock gating inactive lanes during divergence reduces dynamic power by 11.2%.
Fault Bearing Identification Based on Wavelet Packet Transform Technique and Artificial Neural Network

Bearing race faults have been detected by using wavelet packet transform (WPT) technique, combined with a feature selection of energy spectrum. Vibration signals from ball bearings having defects on inner race and outer race have been considered for analysis. In the present fault diagnosis study, the artificial neural network techniques both using radical basis function (RBF) neural network and conventional back-propagation (BP) neural network are compared in the system to evaluate the proposed feature selection technique. The experimental results pointed out the proposed system achieved fault recognition rate of over 90% for various bearing working conditions. And RBF neural network is more effective than BP neural network in this fault diagnosis system.
Multilingualism, Citizenship, and Identity: Voices of youth and symbolic investments in an urban, globalized world Katrina Craig, Alan Leschied Preservice Teacher Attitudes and Confidence in Direct, Relational, Homophobic and Cyber Bullying

Preface Acknowledgements 1. Overlapping Identities, Symbolic Investments, and New Discursive Spaces 2. Exploring Interconnections between Globalization, Multilingualism, Multiculturalism, and Identity 3. An "ethnographie a geometrie variable": Theoretical and Methodological Considerations 4. Voices of Youth and Symbolic Investments: A Unique Case Study 5. Appropriating and Negotiating Symbolic Investments: Strategies Across, Between, and Within Multiple Spaces Conclusion: Implications and Future Directions for Interdisciplinary Research References Index.
Incremental and iterative monolingual clustering algorithms

To reduce speech recognition error rate we can use better statistical language models. These models can be improved by grouping words into word equivalence classes. Clustering algorithms can be used to automatically do this word grouping. We present an incremental clustering algorithm and two iterative clustering algorithms. Also, we compare them with previous algorithms. Theexperimental results show that the two iterative algorithms perform as well as previous ones. It should be pointed out that one of them, that uses the leaving one out technique, has the ability to automatically determine the optimum number of classes. These iterative algorithms are used by the incremental one. On the other hand, the proposed incremental algorithm achieves the best results of the compared algorithms, its behavior is the most regular with the variation of the number of classes and can automatically determine the optimum number of classes.
Cytoarchitectonic development of the prefrontal cortex in the rat

This paper gives an account of the cytoarchitectonic characteristics that make it possible to delineate, from as early as day 6, different subareas of the prefrontal cortex of the rat. Three phases can be distinguished during postnatal development. The first phase (from day 1 until day 18) is dominated by differentiation of the neurons within the cortical plate and by the formation of the cortical layers. At day 1, regional differences are observed in the cytoarchitecture of the cortical plate which correspond to the future subareas of the prefrontal cortex. The formation of layer IV occurs in the dorsolateral cortex around day 6, and from this age the agranular prefrontal cortex is well demarcated from the other parts of the frontal cortex. Between day 6 and day 10, the cortical plate has disappeared and all cortical layers can be recognized in the prefrontal cortex. Differentiation of the cells within the cortical layers changes the cytoarchitectonic character of the layers through day 18. During the second phase (from day 18 until day 30) little change occurs in the cytoarchitectonic characteristics of the prefrontal subareas. During the third phase (from day 30 until day 90) the delineation of the cortical layers becomes less clear in Nissl‐stained sections, and the individual cytoarchitectonic variance increases. On the basis of cytoarchitectonic criteria it can be concluded that the orbital prefrontal cortex develops earlier than does the medial prefrontal cortex.
Sec-independent Protein Translocation in Escherichia coli

In Escherichia coli, transmembrane translocation of proteins can proceed by a number of routes. A subset of periplasmic proteins are exported via the Tat pathway to which proteins are directed by N-terminal “transfer peptides” bearing the consensus (S/T)RRXFLK “twin-arginine” motif. The Tat system involves the integral membrane proteins TatA, TatB, TatC, and TatE. Of these, TatA, TatB, and TatE are homologues of the Hcf106 component of the ΔpH-dependent protein import system of plant thylakoids. Deletion of the tatB gene alone is sufficient to block the export of seven endogenous Tat substrates, including hydrogenase-2. Complementation analysis indicates that while TatA and TatE are functionally interchangeable, the TatB protein is functionally distinct. This conclusion is supported by the observation that Helicobacter pylori tatA will complement an E. coli tatA mutant, but not a tatB mutant. Analysis of Tat component stability in various tat deletion backgrounds shows that TatC is rapidly degraded in the absence of TatB suggesting that TatC complexes, and is stabilized by, TatB.
Weighted-$L^\infty$ and pointwise space-time decay estimates for wave equations with potentials and initial data of low regularity

We prove weighted-$L^\infty$ and pointwise space-time decay estimates for weak solutions of a class of wave equations with time-independent potentials and subject to initial data, both of low regularity, satisfying given decay bounds at infinity. The rate of their decay depends on the asymptotic behaviour of the potential and of the data. The technique is robust enough to treat also more regular solutions and provides decay estimates for arbitrary derivatives, provided the potential and the data have sufficient regularity, but it is restricted to potentials of bounded strength (such that $-\Delta-|V|$ has no negative eigenvalues).
Post-floorplanning power optimization for MSV-driven application specific NoC design

In this paper, a transitive closure graph (TCG)-based post-floorplanning repacking algorithm is proposed for power optimization of Multiple Supply Voltages (MSV)-driven application specific 2D NoC. Through a five-stage processing including floorplan representation, preconditioning, objective insertion point calculation, TCG modification and ILP-based incremental repacking, the total communication power can be optimized without changing much of the original floorplan. Experimental results show that the proposed method can reduce the communication power by 28.3%.
Improving vulnerability detection measurement: [test suites and software security assurance]

The Software Assurance Metrics and Tool Evaluation (SAMATE) project at the National Institute of Standards and Technology (NIST) has created the Software Assurance Reference Dataset (SARD) to provide researchers and software security assurance tool developers with a set of known security flaws. As part of an empirical evaluation of a runtime monitoring framework, two test suites were executed and monitored, revealing deficiencies which led to a collaboration with the NIST SAMATE team to provide replacements. Test Suites 45 and 46 are analyzed, discussed, and updated to improve accuracy, consistency, preciseness, and automation. Empirical results show metrics such as recall, precision, and F-Measure are all impacted by invalid base assumptions regarding the test suites.
A low-complexity Gaussian message passing iterative detector for massive MU-MIMO systems

This paper considers a low-complexity Gaussian Message Passing Iterative Detection (GMPID) method over a pairwise graph for a massive Multiuser Multiple-Input Multiple-Output (MU-MIMO) system, in which a base station with M antennas serves K Gaussian sources simultaneously. Both K and M are large numbers and we consider the cases that K <; M in this paper. The GMPID is a message passing algorithm based on a fully connected loopy graph, which is well known that it is not convergent in some cases. In this paper, we first analyse the convergence of GMPID. Two sufficient conditions that the GMPID converges to the Minimum Mean Square Error (MMSE) detection are proposed. However, the GMPID may still not converge when K/M > (√2 - l)2. Therefore, a new convergent GMPID with equally low complexity called SA-GMPID is proposed, which converges to the MMSE detection for any K <; M with a faster convergence speed. Finally, numerical results are provided to verify the validity and accuracy of the proposed theoretical results.
Sorting Nexin 17 Interacts Directly with Kinesin Superfamily KIF 1 B β Protein

199 Corresponding to: Dae-Hyun Seog, Department of Biochemistry, College of Medicine, Inje University, 633-165, Gaegeom-dong, Busanjin-gu, Busan 614-735, Korea. (Tel) 82-51-890-6974, (Fax) 82-51-894-4500, (E-mail) daehyun@inje.ac. kr ABBREVIATIONS: KIF, kinesin superfamily protein; SNX, sorting nexin; CMT2A, Charcot-Marie-Tooth disease type 2A; PX, phox homology. Sorting Nexin 17 Interacts Directly with Kinesin Superfamily KIF1Bβ Protein
Parts for the Whole: The DCT Norm for Extreme Visual Recovery

Here we study the extreme visual recovery problem, in which over 90\% of pixel values in a given image are missing. Existing low rank-based algorithms are only effective for recovering data with at most 90\% missing values. Thus, we exploit visual data's smoothness property to help solve this challenging extreme visual recovery problem. Based on the Discrete Cosine Transformation (DCT), we propose a novel DCT norm that involves all pixels and produces smooth estimations in any view. Our theoretical analysis shows that the total variation (TV) norm, which only achieves local smoothness, is a special case of the proposed DCT norm. We also develop a new visual recovery algorithm by minimizing the DCT and nuclear norms to achieve a more visually pleasing estimation. Experimental results on a benchmark image dataset demonstrate that the proposed approach is superior to state-of-the-art methods in terms of peak signal-to-noise ratio and structural similarity.
Intrauterine inflammation alters fetal cardiopulmonary and cerebral haemodynamics in sheep

• Intrauterine inflammation impairs fetal pulmonary vascular development and increases cerebral metabolism in fetal sheep. Whether these structural and metabolic changes have functional consequences for fetal cardiopulmonary and cerebral haemodynamics is presently unknown. • We demonstrated that intra‐amniotic administration of lipopolysaccharide increased fetal pulmonary vascular resistance, and reduced pulmonary blood flow and carotid arterial oxygen content in the fetus and caused a transient increase in fetal cerebral blood flow. These effects occurred over a time course consistent with previously observed effects on pulmonary vascular development and cerebral metabolism. • Our data suggest that pathophysiological changes in cardiopulmonary and cerebral haemodynamics observed in fetuses exposed to intrauterine inflammation may be present and detectable in human pregnancies, offering potential for detecting fetuses affected by intrauterine inflammation.
Teaching Entrepreneurship: A Practice-Based Approach

Contents: 1. Teaching Entrepreneurship as a Method that Requires Practice The Five Practices of Entrepreneurship Education: The Theory 2. The Practice of Play 3. The Practice of Empathy 4. The Practice of Creation 5. The Practice of Experimentation 6. The Practice of Reflection The Five Practices of Entrepreneurship Education: The Application 7. Exercises to Practice Play 8. Exercises to Practice Empathy 9. Exercises to Practice Creation 10. Exercises to Practice Experimentation 11. Exercises to Practice Reflection 12. A Final Note: The Practices Support Accreditation
Less Can Be More: Micro-managing VMs in Amazon EC2

Micro instances (t1. micro) are the class of Amazon EC2 virtual machines (VMs) offering the lowest operational costs for applications with short bursts in their CPU requirements. As processing proceeds, EC2 throttles CPU capacity of micro instances in a complex, unpredictable, manner. This paper aims at making micro instances more predictable and efficient to use. First, we present a characterization of EC2 micro instances that evaluates the complex interactions between cost, performance, idleness and CPU throttling. Next, we define adaptive algorithms to manage CPU consumption by learning the workload characteristics at runtime and by injecting idleness to diminish host-level throttling. We show that a gradient-hill strategy leads to favorable results. For CPU bound workloads, we observe that a significant portion of jobs (up to 65%) can have end-to-end times that are even four times shorter than those of the more expensive m1. small class. Our algorithms drastically reduce the long tails of job execution times on the micro instances, resulting to favorable comparisons against even small instances.
Performance Modelling of Adaptive VANET with Enhanced Priority Scheme

In this paper, we present an analytical and simulated study on the performance of adaptive vehicular ad hoc networks (VANET) priority based on Transmission Distance Reliability Range (TDRR) and data type. VANET topology changes rapidly due to its inherent nature of high mobility nodes and unpredictable environments. Therefore, nodes in VANET must be able to adapt to the ever changing environment and optimize parameters to enhance performance. However, there is a lack of adaptability in the current VANET scheme. Existing VANET IEEE802.11p’s Enhanced Distributed Channel Access; EDCA assigns priority solely based on data type. In this paper, we propose a new priority scheme which utilizes Markov model to perform TDRR prediction and assign priorities based on the proposed Markov TDRR Prediction with Enhanced Priority VANET Scheme (MarPVS). Subsequently, we performed an analytical study on MarPVS performance modeling. In particular, considering five different priority levels defined in MarPVS, we derived the probability of successful transmission, the number of low priority messages in back off process and concurrent low priority transmission. Finally, the results are used to derive the average transmission delay for data types defined in MarPVS. Numerical results are provided along with simulation results which confirm the accuracy of the proposed analysis. Simulation results demonstrate that the proposed MarPVS results in lower transmission latency and higher packet success rate in comparison with the default IEEE802.11p scheme and greedy scheduler scheme.
Organization of the face representation in macaque motor cortex

We stimulated with microelectrodes the face representation in precentral motor cortex in macaque monkeys. Responses were very discrete; at threshold current levels the usual response was a small focus of movement in part of a muscle. Facial muscles cluster together in the posterior and anterior portions of the precentral gyrus with tongue movements represented in the intervening region and along the lateral extent. Within each cluster there are multiple representations of individual muscle movements. In long penetrations down the anterior wall of the central sulcus we were able to advance the electrode tangentially through cortex. In these penetrations we encountered a series of discrete zones each of which was related to the movement of a particular muscle or part of a muscle in the face. The lowest threshold points were found in the center of each zone, and a the microelectrode progressed toward the edge, thresholds rose until there was a shift to a new muscle movement. Successive stimulation points separated by as little as 50 μm could yield different responses. These zones could be either roughly cylindrical or take the form of narrow curving bands running mediolaterally across cortex. There is a tendency for adjacent muscles to occur together, and the representation may be roughly topographical within the limits set by the morphological structure of the muscles themselves. The most commonly evoked muscle response was in zygomaticus, which retracts the corners of the mouth in expressions of fear and anger.
The blue water footprint and land use of biofuels from algae

Biofuels from microalgae are potentially important sources of liquid renewable energy. Algae are not yet produced on a large scale, but research shows promising results. This study assesses the blue water footprint (WF) and land use of algae‐based biofuels. It combines the WF concept with an energy balance approach to determine the blue WF of net energy. The study considers open ponds and closed photobioreactors (PBRs). All systems have a positive energy balance, with output‐input ratios ranging between 1.13 and 1.98. This study shows that the WF of algae‐based biofuels lies between 8 and 193 m3/GJ net energy provided. The land use of microalgal biofuels ranges from 20 to 200 m2/GJ net energy. For a scenario in which algae‐based biofuels provide 3.5% of the transportation fuels in the European Union in 2030, the system with the highest land productivity needs 17,000 km2 to produce the 850 PJ/yr. Producing all algae‐based biofuels through the system with the highest water productivity would lead to a blue WF of 7 Gm3/yr, which is equivalent to 15% of the present blue WF in the EU28. A transition to algae‐based transportation fuels will substantially increase competition over water and land resources.
The Sliding Filament Model

This review will describe the investigation of the mechanism of muscle contraction and cell motility from 1972 to the present. The preceding article in this issue by Andrew Szent-Gyorgyi covers the period up to 1972. In 1972 the field of actomyosin interactions was summarized in a conference at Cold
Sparse Matrix Vector Processing Formats

In this dissertation we have identified vector processing shortcomings related to the efficient storing and processing of sparse matrices. To alleviate existent problems we propose two storage formats denoted as Block Based Compression Storage (BBCS) format and Hierarchical Sparse Matrix (HiSM) storage. Furthermore we propose vector architectural instruction set extensions and microarchitecture mechanisms to speed up frequently used sparse matrix operations using the proposed formats. Finally we identified the lack of benchmarks that cover both format and sparse matrix operations. We introduced a benchmark that covers both. To evaluate our proposal we developed a simulator based on SimpleScalar, extended so that it incorporates our proposed changes and established the following. Regarding storage space our proposed formats require 72% to 78% of the storage space needed for Compressed Row Storage (CRS) or the Jagged Diagonal (JD) storage, both commonly used sparse matrix storage formats. Regarding Sparse Matrix Vector Multiplication (SMVM) both BBCS and HiSM achieve a considerable performance speedup when compared to CRS and JD. More in particular, when performing the SMVM using the HiSM format and the newly proposed instructions we can achieve a speedup of 5.3 and 4.07 versus CRS and JD respectively. Additionally, the operation of element insertion using HiSM can be sped up by a factor of 2-400 depending on the sparsity of the matrix. Furthermore, we show that we can increase the performance of the transposition operation by a factor of 17.7 when compared to CRS.
Educating All: Multicultural Perspectives in the Primary School

Researching education for all becoming a pupil - the first term at school ruled out or rescued? the process of statementing becoming a junior - pupil development following transfer from infants into the middle years - transfer at nine plus learning through friendship pupil perceptions of religious and cultural diversity multicultural mathematics - a whole school approach living and growing - developing multicultural perspectives in a Church of England junior school.
Protection for Large Scale Naturalistic Driving Videos

A common pool of naturalistic driving data is necessary to develop and compare algorithms that infer driver behavior, in order to improve driving safety. The SHRP 2 naturalistic driving study (NDS) is currently collecting such data for the past two years which will result in approximately 4 petabytes of data, 1 million hours of video, 3000 subjects, 5 million trips, 33 million miles driven and 4 billion GPS points [1]. The Transportation Research Board, however, is working on details to give public access to this data due to personal identifiable information and protection of privacy. We propose and implement de-identification filters for protecting the privacy of drivers while preserving details to infer driver behavior, such as the gaze direction, and show promising results.
Exploiting User Demographic Attributes for Solving Cold-Start Problem in Recommender System

—Recommender systems have been used tremendously academically and commercially, recommendations generated by these systems aim to offer relevant interesting items to users. Several approaches have been suggested for providing users with recommendations using their rating history, most of these approaches suffer from new user problem (cold-start) which is the initial lack of items ratings. In this paper we suggest utilizing new user demographic data to provide recommendations instead of using rating history to avoid cold-start problem. We present a framework for evaluating the usage of different demographic attributes, such as age, gender, and occupation, for recommendation generation. Experiments are executed using MovieLens dataset to evaluate the performance of the proposed framework.
Diagnostic criteria for multiple sclerosis: 2010 Revisions to the McDonald criteria

New evidence and consensus has led to further revision of the McDonald Criteria for diagnosis of multiple sclerosis. The use of imaging for demonstration of dissemination of central nervous system lesions in space and time has been simplified, and in some circumstances dissemination in space and time can be established by a single scan. These revisions simplify the Criteria, preserve their diagnostic sensitivity and specificity, address their applicability across populations, and may allow earlier diagnosis and more uniform and widespread use. Ann Neurol 2011