Miracle-dz/UniFAR-FTUs huggingface dataset:
Dual threshold bit-swapping LFSR for power reduction in BIST

This paper proposes a novel idea for incorporating dual threshold voltage for Bit swapping LFSR (BS-LFSR) in order to obtain highly power efficient pattern generators for built in self-test (BIST) based VLSI architecture. BIST is a hardware entity, which is capable of testing the circuit during manufacturing as well as in situ conditions. It make use of different types of random generators for test vector generation to achieve maximum fault coverage. VLSI testing field demands low power designs for test pattern generation, as the device dimensions are shrinking drastically and most of them are made to be battery operated (portable devices). Current trends in test pattern generation make use of random pattern generator such as scan chain based generators, counter based circuits and Linear Feedback Shift Registers (LFSR) in which LFSR found to be common. In order to reduce the transition power due to high switching activity in test vector generation, the Bit-Swapped LFSR based pattern generators are used. Bit swapping LFSR will generate random test sequence with low switching power by finding the hamming distance between two adjacent patterns and it minimizes the hamming distance by utilizing a combinational logic. But the average power still remains high, for this reason an alternate design methodology is proposed. In the proposed design a convenient reduction in power is attained by providing dual threshold voltages to BS-LFSR architectures. All the above discussed BISTs were verified with a custom designed Circuit Under Test (CUT), defined in software simulators and the result seems to be encouraging.
2D Hexagonal Mesh Vs 3D Mesh Network on Chip: A Performance Evaluation

D Network on Chip (NoC) has emerged as a new platform to meet the performance requirements and scaling challenges of System on Chip. More investigations require addressing challenges in multiport topologies, minimizing foot printing of nodes and interconnections of wires. This paper discusses multi-port NoC topologies and routing in 2D hexagonal and 3D mesh NoC. Deadlock free routing for 2D hexagonal mesh topology is compared to ZXY routing in 3D mesh with similar number of nodes. Routing algorithms shows promising results, thus making the architecture and algorithm more suitable for the future NoC design.
Social Risk and Protective Child, Parenting, and Child Care Factors in Early Elementary School Years

Objective. African American children exposed to multiple social risk factors during early childhood often experience academic difficulties, so identification of protective factors is important. Design. Academic and school behavior trajectories from kindergarten through third grade were studied among 75 African American children who have been followed prospectively since infancy to test hypothesized protective factors: quality of home and child care environments during early childhood, child language and social skills at entry to kindergarten, and school characteristics. Results. Children exposed to multiple risks in early childhood showed lower levels of academic and social-emotional skills from kindergarten through third grade. Parenting mediated the association with risk. Children's language skills, parenting, and child care quality serve as protective factors in acquisition of mathematics skills and reduction in problem behaviors during the first 4 years of primary school for African American children facing multiple risks. Attending a school with a higher proportion of children from low-income families might predict increasing numbers of problem behaviors over time. Conclusions. Exposure to social risk in early childhood negatively predicted academic achievement and adjustment during early elementary school for African American children, in part through associations between exposure to social risk and less responsive and stimulating parenting. Furthermore, the negative associations between risk and academic outcomes were substantially weaker when children had more responsive and sensitive parents or child care providers or entered school with stronger language skills.
An Inference-based Collaborative Filtering Approach

In memory-based collaborative filtering, the existing methods conduct a prediction based on the overall consistency of two users or items. The major problem with these methods is that it is hard to find users/items that are overall consistent with the test user/item in the system. In addition, these methods are sometimes being over optimistic, and disregard some useful information in user profiles in making a prediction. This paper exposes the drawbacks in these methods and proposes an inference-based recommendation scheme to overcome those drawbacks. This model is based on the fact that any two users may have common interest genres as well as different ones, with the capability of making full use of rating information to capture accurately the relevance between item and user. Experimental results from two popular public datasets, EachMovie and Movielens, show that our approach improves significantly the prediction accuracy.
Contrasting Approaches to Perceiving and Acting With Others

How and why the presence of a person directly affects the perception and action of another person is a phenomenon that has been approached in a limited and piecemeal fashion within psychology. This kind of diffuse strategy has failed to capture the jointness of perception and action within and between people. In contradistinction, the authors offer a perspective that retains both integrally social features (e.g., involves interaction) and yet adequately exploits the current state of knowledge regarding the ecological properties of perception–action, while at the same time drawing on aspects of dynamic systems theory. In this article the authors review the best attempts to examine how one individual affects another's perceptions and actions in the emergence of a social unit of action. Two important approaches, the individual-level and cognitive dynamics approaches, have yielded insights that derive in significant degree from principles of ecological psychology and/or dynamical systems theory. Prototypic of the individual-level approach is a focus on what can be perceived by coactors with the aim of uncovering how the dispositional qualities (affordances) of another person are informationally specified during social interaction. In contrast, the cognitive dynamics approach simulates dynamical characteristics of cognition and psychological influence with the aim of uncovering how cooperative interaction emerges out of its component parts. The authors argue that these approaches involve, respectively, insufficient mutuality and insufficient embodiment. Consequently, a social synergy perspective is discussed that approaches the problem of socially cooperative interaction at the relational, nonreductive level, using novel methods to examine how social perception and action emerge through self-organizing processes. The coupling of Gibson's ideas with those of Bernstein forms a natural basis for looking at the traditional psychological topics of perceiving, acting, and knowing as activities of ecosystems rather than isolated animals. (Shaw, Mace, & Turvey, 2001, p. xiv)
Aspects of Prophylactic Vaccination against Cervical Cancer and Other Human Papillomavirus-Related Cancers in Developing Countries

Cervical cancer and other human papillomavirus- (HPV-) related cancers are preventable, but preventive measures implemented in developing countries and especially in low-income rural regions have not been effective. Cervical cancer burden derived from sexually transmitted HPV infections is the heaviest in developing countries, and a dramatic increase in the number of cervical cancer cases is predicted, if no intervention is implemented in the near future. HPV vaccines offer an efficient way to prevent related cancers. Recently implemented school-based HPV vaccination demonstration programmes can help tackle the challenges linked with vaccine coverage, and access to vaccination and health services, but prevention strategies need to be modified according to regional characteristics. In urban regions WHO-recommended vaccination strategies might be enough to significantly reduce HPV-related disease burden, but in the rural regions additional vaccination strategies, vaccinating both sexes rather than only females when school attendance is the highest and applying a two-dose regime, need to be considered. From the point of view of both public health and ethics identification of the most effective prevention strategies is pivotal, especially when access to health services is limited. Considering cost-effectiveness versus justice further research on optional vaccination strategies is warranted.
Physiological and Molecular Characterization of a Synechocystis sp. PCC 6803 Mutant Lacking Histidine Kinase Slr1759 and Response Regulator Slr1760

Abstract The hybrid sensory histidine kinase Slr1759 of the cyanobacterium Synechocystis sp. strain PCC 6803 contains multiple sensory domains and a multi-step phosphorelay system. Immuno blot analysis provided evidence that the histidine kinase Slr1759 is associated with the cytoplasmic membrane. The gene slr1759 is part of an operon together with slr1760, encoding a response regulator. A comparative investigation was performed on Synechocystis sp. strain PCC 6803 wild type (WT) and an insertionally inactivated slr1759-mutant (Hik14) which also lacks the transcript for the response regulator Slr1760. The mutant Hik14 grew significantly slower than WT in the early growth phase, when both were inoculated with a low cell density into BG11 medium without additional buffer and when aerated with air enriched with 2% CO2. Since the aeration with CO2-enriched air results in a decrease of the pH value in the medium, the growth experiments indicated that Hik14 is not able to adjust its metabolic activities as rapidly as WT to compensate for a larger decrease of the pH value in the medium. No significant differences in growth between Hik14 and WT were observed when cells were inoculated with a higher cell density in BG11 medium or when the BG11 medium contained 50 mm Epps-NaOH, pH 7.5, to prevent the pH drop. This Hik14 phenotype has so far only been seen under the above defined growth condition. Results of photosynthetic activity measurements as well as Northern blot-, immuno blot-, and metabolite analyses suggest that the two-component system Slr1759/Slr1760 has a function in the coordination of several metabolic activities which is in good agreement with the complex domain structure of Slr1759. The direct targets of this two-component system have so far not been identified.
A proposed system for gender classification using lower part of face image

Present study proposes a fast gender classification system from frontal facial images using features selected from mouth and chin only. In most of the study on gender classification found in literature deals with lots of features which makes the classification system a complex one whereas reducing the number of features makes the system simpler but selection of Present study proposes a fast gender classification system from frontal facial images using features selected from mouth and chin only. In most of the study on gender classification found in literature deals with lots of features which makes the classification system a complex one whereas reducing the number of features makes the system simpler but selection of features also plays important role in gender classification. Generally lower part of face image carries sufficient information regarding gender of a person. So in this study, features from lower part of face are considered for gender identification. Proposed method works in four steps-a) Extraction of the Lower part of frontal face images using the method geometric model proposed by Bhattacharjee et al. b) Construction of Gray Level Co-occurrence Matrix from the extracted image c) Extraction of Features from GLCM and d) Classification of the face using a standard classifiers. The proposed method has been tested on 75 male and 35 female color face images of standard FRAV2D database and some face images captured using standard camera. Experimental result shows the effectiveness of this simple gender classification system which achieves 94.34±1.8% accuracy on test data.features also plays important role in gender classification. Generally lower part of face image carries sufficient information regarding gender of a person. So in this study, features from lower part of face are considered for gender identification. Proposed method works in four steps-a) Extraction of the Lower part of frontal face images using the method geometric model proposed by Bhattacharjee et al. b) Construction of Gray Level Co-occurrence Matrix from the extracted image c) Extraction of Features from GLCM and d) Classification of the face using a standard classifiers. The proposed method has been tested on 75 male and 35 female color face images of standard FRAV2D database and some face images captured using standard camera. Experimental result shows the effectiveness of this simple gender classification system which achieves 94.34±1.8% accuracy on test data.
Syntactic pattern matching with GraphSpider and MPL

We present MPL (Metapattern Language), a new formalism for defining patterns over dependency-parsed text, and GraphSpider, a matching engine for extracting dependency subgraphs which match against MPL patterns. Using a regexp-like syntax, MPL allows the definition of subgraphs matching user-specified patterns which can be constrained by word or word class, part-of speech tag, dependency type and direction, and presence of named variables in particular locations. Although MPL and Graph- Spider are general-purpose, we developed a set of patterns to capture biomolecular interactions which achieved very high precision results (92.6% at 31.2% recall) on the LLL Challenge corpus. MPL specifications and pattern sets, and the GraphSpider software, are available on SourceForge: http://graphspider.sf. net/
Bandwidth Enhancement by Master Modulation of Optical Injection-Locked Lasers

In normal injection-locked semiconductor lasers, the modulation signals are applied to the slave laser. In this paper, we show that modulating the master light before injection exhibits distinctive modulation dynamics and frequency response. We first present a detailed theoretical model and simulation results. Experimentally, we have successfully demonstrated both master amplitude and master phase modulation. The resulting 3-dB bandwidths have been enhanced by up to three times, exceeding 50 GHz. The resonance frequency of the combined lasers is greater than 100 GHz.
A low-complexity time-domain signal processing algorithm for N-continuous OFDM

N-continuous orthogonal frequency division multiplexing (OFDM) is a promising sidelobe suppression technique by enhancing the continuity between adjacent symbols with higher-order derivatives. However, it has high computational complexity due to the large-scale matrix operations in frequency domain. In this paper, a low-complexity time-domain signal processing (TDSP) algorithm for N-continuous OFDM is proposed. Based on linear combination of basis vectors, it utilizes small-scale matrix operations to generate the coordinates to construct N-continuous OFDM signal. Simulation results approve that the proposed algorithm achieves dramatic complexity reduction with identical sidelobe suppression and BER performance compared to conventional frequency-domain processed N-continuous OFDM.
Radio study of X-ray clusters of galaxies — I. A3528: a pre-merging cluster in the core of the Shapley Supercluster

As part of an extensive radio–IR–optical–X-ray study of ROSAT clusters of galaxies in the Hydra region we have observed the bimodal Abell cluster A3528, located in the core of the Shapley Supercluster (z ≃ 0.053), with the Molonglo Observatory Synthesis Telescope at 843 MHz and the Australia Telescope Compact Array at 1.4 and 2.4 GHz. This is part I in a series of papers which looks at the relationship between the radio and X-ray emission in samples of ROSAT selected clusters. The radio source characteristics — tailed morphologies and steep spectra — are consistent with the effects of a dense intracluster medium and the pre-merging environment of A3528. In particular, we present evidence that the minor member of the radio-loud dumbbell galaxy located at the centre of the northern component of A3528 is on a plunging orbit. We speculate that this orbit may have been induced by the tidal interactions between the merging components of A3528. In addition, the radio source associated with the dominant member of the dumbbell galaxy exhibits many of the characteristics of compact steep spectrum sources. We argue that the radio emission from this source was triggered ∼ 106 yr ago by tidal interactions between the two members of the dumbbell galaxy, strengthening the argument that compact steep spectrum (CSS) sources are young. Re-analysis of archive pointed Position Sensitive Proportional Counter (PSPC) data using multiresolution filtering suggests the presence of an AGN and/or a cooling flow in the southern component of A3528.
The Hybrid Synthetic Microdata Platform: A Method for Statistical Disclosure Control

Owners of biobanks are in an unfortunate position: on the one hand, they need to protect the privacy of their participants, whereas on the other, their usefulness relies on the disclosure of the data they hold. Existing methods for Statistical Disclosure Control attempt to find a balance between utility and confidentiality, but come at a cost for the analysts of the data. We outline an alternative perspective to the balance between confidentiality and utility. By combining the generation of synthetic data with the automated execution of data analyses, biobank owners can guarantee the privacy of their participants, yet allow the analysts to work in an unrestricted manner.
Is LTE-Advanced really advanced?

LTE-Advanced (LTE-A) theoretically can provide better network performance than 4G LTE. Mobile carriers around the globe are eager to deploy LTE-A to attract more subscribers. However, is it really making difference to the user experience compared to the existing LTE service? To investigate this question, we collected the network performance log from 111 user smartphones on 3G, LTE, and LTE-A. For in-depth analysis, we also asked for privacy information, such as data plan, subscribed network, monthly payment details, and etc. By analyzing the collected log, we observed that (i) LTE-A was faster than LTE only for download bandwidth by 14.1%, yet the users pay on average 13.6% more for LTE-A; (ii) the mVoIP traffic was blocked by all carriers when the users exceed their mVoIP quota; (iii) the subscribed data plan showed no discrimination in network performance.
Clustering Wireless Sensor Nodes Using Caterpillar Graph 3. Introduction

A wireless sensor network is a collection of nodes organized into a cooperative network [1]. Currently, wireless sensor networks are beginning to be deployed at an accelerated space. It is not unreasonable to expect that in 10-15 years that the world will be covered with wireless sensor networks with access to them via the Internet. This can be considered as the Internet becoming a physical network. This new technology is exciting with unlimited potential for numerous application areas management, homeland defense, and smart spaces. Since a wireless sensor network is a distributed real-time system a natural question is how many solutions from distributed and real-time systems can be used in these new systems? Unfortunately, very little prior work can be applied and new solutions are necessary in all areas of the system. The main reason is that the set of assumptions underlying previous work has changed dramatically. Most past distributed systems research has assumed that the systems are wired, have unlimited power, are not real-time, have user interfaces such as screens and mice, have a fixed set of resources, treat each node in the system as very important and are location independent. In contrast, for wireless sensor networks, the systems are wireless, have scarce power, are real-time, utilize sensors and actuators as interfaces, have dynamically changing sets of resources, aggregate behavior is important and location is critical. Many wireless sensor networks also
Goals and Benchmarks for Automated Map Reasoning

Tarski? Givant? s map calculus is briefly reviewed, and a plan of research is outlined aimed at investigating applications of this ground equational formalism in the theorem-proving field. The main goal is to create synergy between first-order predicate calculus and the map calculus. Techniques for translating isolated sentences, as well as entire theories, from first-order logic into map calculus are designed, or in some cases simply brought nearer through the exercise of specifying properties of a few familiar structures (natural numbers, nested lists, finite sets, lattices). It is also highlighted to what extent a state-of-the-art theorem-prover for first-order logic, namely Otter, can be exploited not only to emulate, but also to reason about, map calculus. Issues regarding “safe" forms of map reasoning are singled out, in sight of possible generalizations to the database area.
Insider Trading in Credit Derivatives Viral

Insider trading in the credit derivatives market has become a significant concern for regulators and participants. This paper attempts to quantify the problem. Using news reflected in the stock market as a benchmark for public information, we find significant incremental information revelation in the credit default swap market under circumstances consistent with the use of non-public information by informed banks. The information revelation occurs only for negative credit news and for entities that subsequently experience adverse shocks, and increases with the number of a firm’s relationship banks. We find no evidence, however, that the degree of asymmetric information adversely affects prices or liquidity in either the equity or credit markets. r 2006 Elsevier B.V. All rights reserved. JEL classification: G12; G13; G14; G20; D8
Predicting gene ontology annotations from sequence data using kernel-based machine learning algorithms

In this early part of the post-genomic era, the inference of the functions associated with gene products is a necessary first step in understanding the development and maintenance of living cells. We describe the development of a machine learning method for predicting biological process as defined by the gene ontology (GO). The algorithm uses features that can be generated from amino acid sequence alone, and does not require further experimental studies such as microarrays, 2-hybrid screens or systematic 'pull-down' assays. The budding yeast Saccharomyces cerevisiae is used because of its comprehensive set of functional annotations, but the approach is sufficiently general for application to other eukaryote genomes. The input data include phylogenetic profiles, which represent the distribution of orthologous proteins in the genomes of other organisms, position-specific scoring matrices, and secondary structure and dynamic disorder predictions. These are encoded using diffusion kernels, which are used to represent pair-wise relationships such as sequence or secondary structure element similarity between nodes (proteins) in a graph. These kernels are benchmarked on the process prediction problem using a maximal margin (SVM) learning algorithm.