Miracle-dz/UniFAR-FTUs huggingface dataset:
Size-time complexity of Boolean networks for prefix computations

The prefix problem consists of computing all the products <italic>x</italic><subscrpt>0</subscrpt><italic>x</italic><subscrpt>1</subscrpt> … <italic>x<subscrpt>j</subscrpt></italic> (<italic>j</italic> = 0, … , <italic>N</italic> - 1), given a sequence x = (<italic>x</italic><subscrpt>0</subscrpt>, <italic>x</italic><subscrpt>1</subscrpt>, … , <italic>x</italic><subscrpt><italic>N-</italic>1</subscrpt>) of elements in a semigroup. In this paper we completely characterize the size-time complexity of computing prefixes with Boolean networks, which are synchronized interconnections of Boolean gates and one-bit storage devices. This complexity crucially depends upon two properties of the underlying semigroup, which we call cycle-freedom (no cycle of length greater than one in the Cayley graph of the semigroup), and memory-induciveness (arbitrarily long products of semigroup elements are true functions of all their factors). A nontrivial characterization is given of non-memory-inducive semigroups as those whose recurrent subsemigroup (formed by the elements with self-loops in the Cayley graph) is the direct product of a left-zero semigroup and a right-zero semigroup. Denoting by <italic>S</italic> and <italic>T</italic> size and computation time, respectively, we have S = &THgr;((<italic>N</italic>/<italic>T</italic>)log(<italic>N</italic>/<italic>T</italic>)) for memory-inducive non-cycle-free semigroups, and S = &THgr;(<italic>N</italic>/<italic>T</italic>) for all other semigroups. We have <italic>T</italic> ε [&OHgr;(log <italic>N</italic>), &Ogr;(<italic>N</italic>)] for all semigroups, with the exception of those whose recurrent subsemigroup is a right-zero semigroup, for which <italic>T</italic> ε [&OHgr;(1), &Ogr;(<italic>N</italic>)]. The preceding results are also extended to the VLSI model of computation. Area-time optimal circuits are obtained for both boundary and nonboundary I/O protocols.
Narrowband and Wideband Off-Grid Direction-of-Arrival Estimation via Sparse Bayesian Learning

The sparse Bayesian learning based relevance vector machine (SBLRVM) algorithm is a promising algorithm to estimate the directions-of-arrival (DOAs) of multiple narrowband signals. The parameters involved in the DOA estimation model are automatically estimated by the algorithm that makes it more attractive than the deterministic sparsity based DOA estimation algorithms in which fine-tuning of parameters is necessary. However, one limitation of the algorithm is that it assumes the DOAs of the signals to be exactly aligned with the angular grids, which may not be true in practice. In this paper, we first propose an off-grid version of the narrowband SBLRVM algorithm. Next, we propose an off-grid wideband SBLRVM algorithm. The algorithms assume that the true scenario DOAs of the signals are not exactly aligned with the angular grids and the parameters of the algorithms are automatically estimated by the expectation maximization approach. In the wideband DOA estimation algorithm, we estimate one spatial power spectrum by simultaneously exploiting sparsity from all frequency bins. We demonstrate the application of the proposed algorithms by analyzing data from the shallow water HF$\mathbf {97}$ ocean acoustic experiment. The estimated DOAs of a narrowband tonal from the experiment by using our proposed narrowband DOA estimation algorithm are consistent with the nonadaptive conventional beamformer. Processing a wideband chirp from the experiment shows that estimating one spatial power spectrum by simultaneously exploiting sparsity from all frequency bins using the proposed wideband DOA estimation algorithm is a more valuable processor than an incoherent combination of the power spectra from the individual frequency bins estimated using the proposed narrowband DOA estimation algorithm. Moreover, since our proposed algorithms are off-grid algorithms, an empirical analysis for the choice of the discretization interval of the angular spread is not required as opposed to the on-grid DOA estimation algorithms. This results in a reduced computational complexity.
A Reactive Robotized Interface for Lower Limb Rehabilitation: Clinical Results

This paper presents clinical results from the use of monitor-nomad (MONIMAD), which is a reactive robotized interface for lower limb rehabilitation of patients suffering from cerebellar disease. The first problem to be addressed is the postural analysis of sit-to-stand motion. Experiments with healthy subjects were performed for this purpose. Analysis of external forces shows that sit-to-stand transfer can be subdivided into several phases: preacceleration, acceleration, start rising, and rising. Observation of center of pressure, ground forces, and horizontal components force on handles yields rules that identify the stability of the patient and adjust the robotic interface motion to the human voluntary movement. These rules are used in a fuzzy-based controller implementation. The controller is validated on experiments with diseased patients at Bellan Hospital, Paris, France.
Biomimetically Inspired Algorithm for Noise Reduction in Low Light Imaging

Over the last half-century, night vision device (NVD) technology has revolutionized the way humans operate within the nighttime environment. Incremental improvements to hardware over time have increased light capturing ability and resultant image representation. While future hardware improvements aim to reduce weight and increase field of view, the introduction of image processing software holds the key to future improvements in image resolution, contrast, and overall low light acuity. This work draws from physiological observations of nocturnal insect adaptations to low light conditions. The resulting algorithm demonstrates powerful low light image enhancement with possible future applications to NVDs.
Public versus Private Provision of Governance : The Case of Proxy Access

We use a unique setting to study the tradeoffs between universal regulatory mandates and private contracting in the field of corporate governance. Events surrounding the legal challenge of a 2010 proxy access rule allow us to benchmark the market’s expectation of the benefits of universally mandated proxy access even though this rule never came into effect. At the same time, a 2010 rule amendment facilitating shareholder proposals for proxy access opened a new channel for proxy access through “private ordering. ” We document that this private channel has been active, spawning about 160 proxy access proposals, and use the unexpected announcement of a major private ordering initiative to identify a 0.5 percent increase in shareholder value for the targeted firms. However, our findings also underscore that private ordering may lead to a second best outcome. We find that proponents do not selectively target those firms that were expected to benefit the most from universally mandated proxy access, and that tailoring of proposal terms is limited. Moreover, management is more likely to challenge proposals at firms that stand to benefit more. Overall, we find that private ordering creates value, but it may not efficiently deliver proxy access at the firms that need it most. JEL classification: G34, G38, K22
A Novel Approach for Finding Frequent Itemsets done by Comparison based Technique

Frequent pattern mining has been a focused theme in data mining research for over a decade. Abundant literature has been dedicated to this research and tremendous progress has been made, ranging from efficient and scalable algorithms for frequent itemset mining in transaction databases to numerous research frontiers, such as sequential pattern mining, structured pattern mining, correlation mining, associative classification, and frequent pattern-based clustering, as well as their broad applications. In this paper, we develop a new technique for more efficient pattern mining. Our method find frequent 1-itemset and then uses the heap tree sorting we are generating frequent patterns, so that many. We present efficient techniques to implement the new approach.
In vitro comparison of feline bone marrow-derived and adipose tissue-derived mesenchymal stem cells

Mesenchymal stem cells (MSC) are increasingly being proposed as a therapeutic option for a variety of different diseases in human and veterinary medicine. At present, MSC are most often collected from bone marrow (BM) or adipose tissue (AT) and enriched and expanded in vitro before being transferred into recipients. However, little is known regarding the culture characteristics of feline BM-derived (BM-MSC) versus AT-derived MSC (AT-MSC). We compared BM-MSC and AT-MSC from healthy cats with respect to in vitro growth and cell surface phenotype. Mesenchymal stem cells isolated from AT proliferated significantly faster than BM-MSC. Phenotypic differences between BM-MSC and AT-MSC were not present in the surface markers assessed. We conclude that BM-MSC and AT-MSC are similar phenotypically but that cultures of AT-MSC are easier to generate because of their higher intrinsic proliferative rate. Thus, AT-MSC may be the preferred MSC for clinical applications where rapid and efficient generation of MSC is important.
Importation and deprivation correlates of misconduct among Romanian inmates

Correctional literature on determinants of prisoner misconduct is largely focused on the situation in the USA or West European countries. This study expands the research in this field by presenting findings from Romania, an East European country whose prison system faces severe problems, among which overcrowding and poor confinement conditions are of the utmost concern. Therefore a survey was conducted on a sample of 280 adult male inmates in four large Romanian prisons. These exceptional data were supplemented with information from official records drawn from the prison administration’s databases. A unique combination of importation and deprivation factors, with a particular focus on several prison deprivations perceived by inmates as problematic, is examined in relation to the prevalence of four types of inmate misbehaviour: total misconduct, contraband infractions, violence and defiance. The findings show a clear relationship between importation and deprivation characteristics and prison misconduct. Also a differential impact of these characteristics is shown, depending on the type of prison infraction examined. The study concludes by advancing a set of policy recommendations to reduce the incidence of institutional misconduct in Romanian prisons.
Face Recognition with Multi-Layer Perceptrons

We present a face recognition system (still in development) with principal component analysis for feature extraction, and multi-layered perceptrons for classiication. For single multi-layered perceptrons, the average performance of our best classiier is 89.1% on a test set of 200 face images, while the single best result is 90.5% correct classiication. We explore three diierent ways of constructing a neural network committee, and the best performance achieved with a committee is 92% correct classiication.
CRYPTANITE: A New Look to the World of Social Networks Using Deep Learning

This paper aims at elaborating the basic form and features of a social network for a school or college. We have improvised existing technologies used in popular social networking sites like twitter, to include some of the new state of the art technologies in machine learning to build features that captivate the audience to use our network over others. The piece of software developed is similar to twitter along with additional features described later in the paper. These features include Image Captioning, Auto-Tagging of Tweets, Sentiment Detection, Spam Filtering and an Innovative News Feed Generator. With the large amount of data available on other popular networking sites the possibility of missing out on vital information within these sites is high. The sole purpose of our site is to ensure that students are well aware of any important information regarding the college. The site aims to increase interaction between fellow students as well as teachers. Students can post pictures of the campus, share important updates, connect with seniors, bond on similar interests and organize various activities all under one roof. This makes the learning process a more enjoyable and enriching experience.
The Perception Of Homeless People: Important Factors In Determining Perceptions Of The Homeless As Dangerous

This study uses two quantitative and two qualitative data sources to determine if homeless people are viewed as dangerous and if they are what factors contribute to this perception. Areas examined are respondent’s characteristics, media affects and the perceived rights of homeless people to urban space. Actual levels of perpetration among the homeless are examined to allow for comparisons between perception and reality to be made. Findings showed that race plays a major role in the perception of homeless people among whites, while gender is more influential among blacks. There was no relationship between media and perceptions. A negative relationship was found between support of rights of the homeless and the perception that they are dangerous. While the homeless have higher incarceration rate as compared to the poor-but-never-homeless, the crimes for which they are sentenced appear to be non-violent in nature and are often what are characterized as nuisance crimes. Recommendations were made to study actual perpetration rates among the homeless to allow for a more in-depth analysis of criminal involvement.
Dignity and Psychotherapeutic Considerations in End-of-Life Care

The basic tenets of palliative care are frequently subsumed under the goal of helping patients to die with dignity. Our research group has studied the issue of dignity, with dying patients serving as the primary informants. This paper reviews some of our findings, including an overview of the Dignity Model that derives from our empirical work. Furthermore, this paper summarizes various psychotherapeutic approaches which have been considered for this vulnerable patient population. Finally, we provide the rationale based on the Dignity Model for a psychotherapeutic intervention we have coined Dignity Therapy. This brief, individualized therapeutic approach has been informed by our dignity work, and specifically designed for application in patients nearing death.
Infant growth and the thymus: Data from two South American native societies

The thymus plays an important role in the development of the immune system, yet little is known about the patterns and sources of variation in postnatal thymic development. The aim of this study is to contribute cross‐cultural data on thymus size in infants from two South American native populations, the Tsimane of Bolivia and the Pumé of Venezuela. Thymic ultrasonography was performed and standard anthropometric measures collected from 86 Tsimane and Pumé infants. Patterns of infant growth and thymus size were compared between the two populations and the relationship between nutritional status and thymus size was assessed. Despite nearly identical anthropometric trajectories, Tsimane infants had larger thymuses than Pumé infants at all ages. Population, infant age, and infant mid‐upper arm circumference were significant predictors of thymus area in the Tsimane and Pumé infants. This finding reveals a cross‐cultural difference in thymus size that is not driven by nutritional status. We suggest that future studies focus on isolating prenatal and postnatal environmental factors underlying cross‐cultural variation in thymic development. Am. J. Hum. Biol., 2012. © 2012 Wiley Periodicals, Inc.
Personalized Pathway Enrichment Map of Putative Cancer Genes from Next Generation Sequencing Data

Background Pathway analysis of a set of genes represents an important area in large-scale omic data analysis. However, the application of traditional pathway enrichment methods to next-generation sequencing (NGS) data is prone to several potential biases, including genomic/genetic factors (e.g., the particular disease and gene length) and environmental factors (e.g., personal life-style and frequency and dosage of exposure to mutagens). Therefore, novel methods are urgently needed for these new data types, especially for individual-specific genome data. Methodology In this study, we proposed a novel method for the pathway analysis of NGS mutation data by explicitly taking into account the gene-wise mutation rate. We estimated the gene-wise mutation rate based on the individual-specific background mutation rate along with the gene length. Taking the mutation rate as a weight for each gene, our weighted resampling strategy builds the null distribution for each pathway while matching the gene length patterns. The empirical P value obtained then provides an adjusted statistical evaluation. Principal Findings/Conclusions We demonstrated our weighted resampling method to a lung adenocarcinomas dataset and a glioblastoma dataset, and compared it to other widely applied methods. By explicitly adjusting gene-length, the weighted resampling method performs as well as the standard methods for significant pathways with strong evidence. Importantly, our method could effectively reject many marginally significant pathways detected by standard methods, including several long-gene-based, cancer-unrelated pathways. We further demonstrated that by reducing such biases, pathway crosstalk for each individual and pathway co-mutation map across multiple individuals can be objectively explored and evaluated. This method performs pathway analysis in a sample-centered fashion, and provides an alternative way for accurate analysis of cancer-personalized genomes. It can be extended to other types of genomic data (genotyping and methylation) that have similar bias problems.
High‐resolution structure of a polyomavirus VP1‐oligosaccharide complex: implications for assembly and receptor binding

The crystal structure of a recombinant polyomavirus VP1 pentamer (residues 32‐320) in complex with a branched disialylated hexasaccharide receptor fragment has been determined at 1.9 Å resolution. The result extends our understanding of oligosaccharide receptor recognition. It also suggests a mechanism for enhancing the fidelity of virus assembly. We have previously described the structure of the complete polyomavirus particle complexed with this receptor fragment at 3.65 Å. The model presented here offers a much more refined view of the interactions that determine carbohydrate recognition and allows us to assign additional specific contacts, in particular those involving the (α2,6)‐linked, branching sialic acid. The structure of the unliganded VP1 pentamer, determined independently, shows that the oligosaccharide fits into a preformed groove and induces no measurable structural rearrangements. A comparison with assembled VP1 in the virus capsid reveals a rearrangement of residues 32‐45 at the base of the pentamer. This segment may help prevent the formation of incorrectly assembled particles by reducing the likelihood that the C‐terminal arm will fold back into its pentamer of origin.
Application-Specific Network-on-Chip synthesis with topology-aware floorplanning

Application-Specific Network-on-Chip (ASNoC) architecture is more promising than regular network-on-Chip(NoC) for some particular applications. In ASNoC Design, one of the key challenges is to generate the most suitable and power efficient NoC topology. In previous works, the placement of the cores and network components, and the path allocation are explored separately. However, the path allocation strongly depends on the placement of cores and network components. In this paper, we integrate these steps together through the floorplanning with the cluster reconstruction and path allocation (FCRPA). Several SoC benchmarks have been tested and the results showed improvements over the latest works.
Sensitivity and specificity of inferring genetic regulatory interactions from microarray experiments with dynamic Bayesian networks

MOTIVATION Bayesian networks have been applied to infer genetic regulatory interactions from microarray gene expression data. This inference problem is particularly hard in that interactions between hundreds of genes have to be learned from very small data sets, typically containing only a few dozen time points during a cell cycle. Most previous studies have assessed the inference results on real gene expression data by comparing predicted genetic regulatory interactions with those known from the biological literature. This approach is controversial due to the absence of known gold standards, which renders the estimation of the sensitivity and specificity, that is, the true and (complementary) false detection rate, unreliable and difficult. The objective of the present study is to test the viability of the Bayesian network paradigm in a realistic simulation study. First, gene expression data are simulated from a realistic biological network involving DNAs, mRNAs, inactive protein monomers and active protein dimers. Then, interaction networks are inferred from these data in a reverse engineering approach, using Bayesian networks and Bayesian learning with Markov chain Monte Carlo. RESULTS The simulation results are presented as receiver operator characteristics curves. This allows estimating the proportion of spurious gene interactions incurred for a specified target proportion of recovered true interactions. The findings demonstrate how the network inference performance varies with the training set size, the degree of inadequacy of prior assumptions, the experimental sampling strategy and the inclusion of further, sequence-based information. AVAILABILITY The programs and data used in the present study are available from http://www.bioss. sari.ac. uk/~dirk/Supplements
Improved Runtime and Transfer Time Prediction Mechanisms in a Network Enabled Servers Middleware

In this paper we address the problem of accurately estimating the runtime and communication time of a client request in a Network Enabled Server (NES) middleware such as GridSolve. We use a template based model for the runtime estimation and a client-server communication test for the transfer time estimation. We implement these two mechanisms in GridSolve and test them on a real testbed. Experiments show that they allow for significant improvement in terms of client execution time on various scenarios.
Poly[[(N,N-dimethylformamide-κO)(μ3-pyrazine-2,3-dicarboxylato-κ4 N 1,O2:O 3:O 3)copper(II)] monohydrate]

In the title compound, {[Cu(C6H2N2O4)(C3H7NO)]·H2O}n, the Cu(II) atom is coordinated by an N,O-bidentate pyrazine-2,3-dicarboxylate (pzdc) dianion, two O atoms from two other pzdc anions and one O atom from the dimethlyformamide ligand, forming a distorted square-pyramidal CuNO4 geometry. The polymeric character of the structure is established by the formation of layers parallel to (100) via bridging pzdc ligands. O—H⋯O hydrogen bonding between water molecules and uncoordinated carboxylate O atoms leads to additional stabilization of the structure.
Performance Comparison of Serial Concatenated Convolutional Codes and Parallel Concatenated Convolutional Codes on Faded Channels

The performance comparison of Serially Concatenated Convolutional Codes (SCCC) and Parallel Concatenated Convolutional Codes (PCCC) is evaluated on Additive White Gaussian Noise model channel, which is used as a basis, and actions of SCCC and PCCC on Raleigh faded channels are evaluated in this research work. In DCS the SCCC and PCCC are utilized to reduce the bit error rates. SCCC and PCCC encoder consists of RSCC. The major thrust is iterative decoding. This research has utilized BCJR and TDA decoding algorithms. This research analyzed SCCC and PCCC with interleaved scheme. The BPSK modulation was considered. Performance metric for SCCC and PCCC over Memory less AWGN channel, and memory based channels i.e. Rayleigh slow and fast Faded Channel is BER verses SNR.