Miracle-dz/UniFAR-FTUs huggingface dataset:
Topographic Wear Monitoring of the Interface Tool/Workpiece in Milling AISI H13 Steel

The wear of TiCN coating carbide cutting tools (Sandvik® Grade 1010 and 4220) in different hard-milling machining conditions was monitored, analyzed, and discussed for AISI H13 steel. This material is commonly used in the forge industry in order to optimize the manufacturing process according to a qualimetry/cost compromise criterion. AISI H13 steel generally is used in modern production for high wear-resistant dies and molds. One of the most basic and primary geometric shapes in the manufacture of molds and die cavities is the geometry known as "inclined plane. " Experimental investigations were carried out on a "mold model" design with the aim of analyzing and optimizing the principal manufacturing conditions. The tests are dependent on manufacturing factors, particularly their impactin a complex tribological process. Five clearly defined different surfaces of the hardened AISI H13 steel model mold, with appropriate geometries were studied; i) vertical downward; ii) curved downward; iii) horizontal; iv) curved upward; and v) vertical upward.The analysis of cutting tool wear during this process was based on computerized measurements of visually observable wear and power consumption. Morphological investigations of the surface topography for the cutting tool, as well as of the work-piece surfaces, were systematically carried out. Moreover, the interactions with simultaneously measured energy consumption during the process are also explicated in the present study and therefore tentative methods to optimize hard-milling machining are offered.
Skin segmentation based on cellular learning automata

In this paper, we propose a novel algorithm that combines color and texture information of skin with cellular learning automata to segment skin-like regions in color images. First, the presence of skin colors in an image is detected, using a committee structure, to make decision from several explicit boundary skin models. Detected skin-color regions are then fed to a color texture extractor that extracts the texture features of skin regions via their color statistical properties and maps them to a skin probability map. Cellular learning automatons use this map to make decision on skin-like regions. The proposed algorithm has demonstrated true positive rate of about 83.4% and false positive rate of about 11.3% on the Compaq skin database. Experimental results show the effectiveness of the proposed algorithm.
The control of EGF signaling and cell fate in the Drosophila abdomen

How cells integrate both patterning and signaling information to select between distinct cell fates is a fundamental problem in developmental biology. In this short review, I focus on recent findings of how the Hox and senseless patterning genes regulate epidermal growth factor (EGF) signaling and cell fate within the Drosophila abdomen. In Li-Kroeger et al, we described how a Hox and Senseless transcription factor competition functions as a molecular switch on a cis-regulatory element in the rhomboid (rho) gene to control EGF signaling within the peripheral nervous system (PNS). Here, I discuss an additional implication of these findings: that rho contains at least two cis-regulatory elements to control EGF secretion from the PNS, each to induce a different cell fate.
The Development of the Older Persons and Informal Caregivers Survey Minimum DataSet (TOPICS-MDS): A Large-Scale Data Sharing Initiative

Introduction In 2008, the Ministry of Health, Welfare and Sport commissioned the National Care for the Elderly Programme. While numerous research projects in older persons’ health care were to be conducted under this national agenda, the Programme further advocated the development of The Older Persons and Informal Caregivers Survey Minimum DataSet (TOPICS-MDS) which would be integrated into all funded research protocols. In this context, we describe TOPICS data sharing initiative (www.topics-mds.eu). Materials and Methods A working group drafted TOPICS-MDS prototype, which was subsequently approved by a multidisciplinary panel. Using instruments validated for older populations, information was collected on demographics, morbidity, quality of life, functional limitations, mental health, social functioning and health service utilisation. For informal caregivers, information was collected on demographics, hours of informal care and quality of life (including subjective care-related burden). Results Between 2010 and 2013, a total of 41 research projects contributed data to TOPICS-MDS, resulting in preliminary data available for 32,310 older persons and 3,940 informal caregivers. The majority of studies sampled were from primary care settings and inclusion criteria differed across studies. Discussion TOPICS-MDS is a public data repository which contains essential data to better understand health challenges experienced by older persons and informal caregivers. Such findings are relevant for countries where increasing health-related expenditure has necessitated the evaluation of contemporary health care delivery. Although open sharing of data can be difficult to achieve in practice, proactively addressing issues of data protection, conflicting data analysis requests and funding limitations during TOPICS-MDS developmental phase has fostered a data sharing culture. To date, TOPICS-MDS has been successfully incorporated into 41 research projects, thus supporting the feasibility of constructing a large (>30,000 observations), standardised dataset pooled from various study protocols with different sampling frameworks. This unique implementation strategy improves efficiency and facilitates individual-level data meta-analysis.
Mu, delta, and kappa opioid receptor mRNA expression in the rat CNS: An in situ hybridization study

The μ, δ, and κ opioid receptors are the three main types of opioid receptors round in the central nervous system (CNS) and periphery. These receptors and the peptides with which they interact are important in a number of physiological functions, including analgesia, respiration, and hormonal regulation. This study examines the expression of μ, δ, and κ receptor mRNAs in the rat brain and spinal cord using in situ hybridization techniques. Tissue sections were hybridized with 35S‐labeled cRNA probes to the rat μ (744–1, 064 b), δ (304–1,287 b), and κ (1,351–2,124 b) receptors. Each mRNA demonstrates a distinct anatomical distribution that corresponds well to known receptor binding distributions. Cells expressing μ receptor mRNA are localized in such regions as the olfactory bulb, caudate‐putamen, nucleus accumbens, lateral and medial septum, diagonal band of Broca, bed nucleus of the stria terminalis, most thalamic nuclei, hippocampus, amygdala, medial preoptic area, superior and inferior colliculi, central gray, dorsal and median raphe, raphe magnus, locus coeruleus, parabrachial nucleus, pontine and medullary reticular nuclei, nucleus ambiguus, nucleus of the solitary tract, nucleus gracilis and cuneatus, dorsal motor nucleus of vagus, spinal cord, and dorsal root ganglia. Cellular localization of δ receptor mRNA varied from μ or κ, with expression in such regions as the olfactory bulb, allo‐ and neocortex, caudate‐putamen, nucleus accumbens, olfactory tubercle, ventromedial hypothalamus, hippocampus, amygdala, red nucleus, pontine nuclei, reticulotegmental nucleus, motor and spinal trigeminal, linear nucleus of the medulla, lateral reticular nucleus, spinal cord, and dorsal root ganglia. Cells expressing, κ receptor mRNA demonstrate a third pattern of expression, with cells localized in regions such as the claustrum, endopiriform nucleus, nucleus accumbens, olfactory tubercle, medial preoptic area, bed nucleus of the stria terminalis, amygdala, most hypothalamic nuclei, median eminence, infundibulum, substantia nigra, ventral tegmental area, raphe nuclei, paratrigeminal and spinal trigeminal, nucleus of the solitary tract, spinal cord, and dorsal root ganglia. These findings are discussed in relation to the physiologica functions associated with the opioid receptors.
Virtualization of 5G Cellular Networks as a Hierarchical Combinatorial Auction

Virtualization has been seen as one of the main evolution trends in the forthcoming fifth generation (5G) cellular networks which enables the decoupling of infrastructure from the services it provides. In this case, the roles of infrastructure providers (InPs) and mobile virtual network operators (MVNOs) can be logically separated and the resources (e.g., subchannels, power, and antennas) of a base station owned by an InP can be transparently shared by multiple MVNOs, while each MVNO virtually owns the entire BS. Naturally, the issue of resource allocation arises. In particular, the InP is required to abstract the physical resources into isolated slices for each MVNO who then allocates the resources within the slice to its subscribed users. In this paper, we aim to address this two-level hierarchical resource allocation problem while satisfying the requirements of efficient resource allocation, strict inter-slice isolation, and the ability of intra-slice customization. To this end, we design a hierarchical combinatorial auction mechanism, based on which a truthful and sub-efficient resource allocation framework is provided. Specifically, winner determination problems (WDPs) are formulated for the InP and MVNOs, and computationally tractable algorithms are proposed to solve these WDPs. Also, pricing schemes are designed to ensure incentive compatibility. The designed mechanism can achieve social efficiency in each level even if each party involved acts selfishly. Numerical results show the effectiveness of the proposed scheme.
Specific mutations within the AT-rich region of a plasmid replication origin affect either origin opening or helicase loading

Prokaryotic and eukaryotic replicons possess a distinctive region containing a higher than average number of adenine and thymine residues (the AT-rich region) where, during the process of replication initiation, the initial destabilization (opening) of the double helix takes place. In many prokaryotic origins, this region consists of repeated 13-mer motifs whose function has not yet been specified. Here we identify specific mutations within the 13-mer sequences of the broad-host-range plasmid RK2 that can result in defective origin opening or that do not affect opening but induce defects in helicase loading. We also show that after the initial recruitment of helicase at the DnaA-box sequences of the plasmid origin, the helicase is translocated to the AT-rich region in a reaction requiring specific sequence of the 13-mers and appropriate facing of the origin motifs. Our results demonstrate that specific sequences within the AT-rich region of a replication origin are required for either origin opening or helicase loading.
The Weighted Suffix Tree: An Efficient Data Structure for Handling Molecular Weighted Sequences and its Applications

In this paper we introduce the Weighted Suffix Tree, an efficient data structure for computing string regularities in weighted sequences of molecular data. Molecular Weighted Sequences can model important biological processes such as the DNA Assembly Process or the DNA-Protein Binding Process. Thus pattern matching or identification of repeated patterns, in biological weighted sequences is a very important procedure in the translation of gene expression and regulation. We present time and space efficient algorithms for constructing the weighted suffix tree and some applications of the proposed data structure to problems taken from the Molecular Biology area such as pattern matching, repeats discovery, discovery of the longest common subsequence of two weighted sequences and computation of covers.
Condate: a proto-language at the confluence between checking and compiling

Recent years have seen the advent of many different tools for program checking against user-defined properties. Despite this encouraging trend, checking technology is used still marginally today, and only on an occasional basis. Existing checkers are standalone tools, associated --- correctly or not --- with low efficiency, and duplicating much work already done in the compiler. We believe that, as a complement to more precise verifiers, the next generation of compilers should integrate some amount of user-defined checks that can be performed efficientlyCombining checking and compiling enables a pervasive propagation of checking technology and continuous use of checking throughout development. It also enables cross-fertilization between the two passes, resulting in increased expressiveness, precision, and even in improved complexity of the checking algorithm.We illustrate this integrated approach with a full-fledged checking compiler for C, extensible through Condate. Condate is a declarative language for expressing simple user-defined program properties to be checked in addition to normal compilation. Condate mixes in a very concise form syntactic, semantic, control flow, and data flow properties. These properties are defined as a new class of regular path expressions over the control-flow graph, checkable in linear time and covering many useful checks.We demonstrate the viability of the integrated approach based on Condate by applying it to successfully check some parts of the Linux kernel.
Unbiased equation-error approach for efficient IIR system identification

Based on the equation-error approach, a weighted least squares algorithm with a generalized unit-norm constraint is developed for unbiased infinite impulse response (HR) system identification in the presence of white input and/or output noise. Through using a weighting matrix, the proposed estimator can be considered as a generalization of the Koopmans-Levin method and it produces better estimation accuracy. Computer simulations are included to evaluate the estimator performance for IIR parameters in different conditions.
Unsupervised language model adaptation using latent Dirichlet allocation and dynamic marginals

In this paper, we introduce an unsupervised language model adaptation approach using latent Dirichlet allocation (LDA) and dynamic marginals: locally estimated (smoothed) unigram probabilities from in-domain text data. In LDA analysis, topic clusters are formed by using a hard-clustering method assigning one topic to one document based on the maximum number of words chosen from a topic for that document. The n-grams of the topic generated by hard-clustering are used to compute the mixture weights of the component topic models. Instead of using all the words of the training vocabulary, selected words are used for LDA analysis, which are chosen by incorporating some information retrieval techniques. We adapted the LDA adapted topic model by minimizing the Kullback-Leibler (KL) divergence between the final adapted model and the LDA adapted topic model subject to a constraint that the marginalized unigram probability distribution of the final adapted model is equal to the dynamic marginals. We have compared our approach with the conventional adapted model obtained by minimizing the KL divergence between the background model and the adapted model using the above constraint. We have seen that our approach gives significant perplexity and word error rate (WER) reductions over the traditional approach.
The case for compensatory processes in the relationship between anxiety and error monitoring: a reply to Proudfit, Inzlicht, and Mennin

(1) We clarify that our view does in fact place motivation and emotion centerstage in the anxiety-ERN relationship. (2) We reiterate that there is currently little compelling evidence that an enlarged ERN in anxious individuals reflects “the disposition to respond more strongly to uncertain threat” (Proudfit et al., 2013, p. 1). (3) We emphasize that our analysis focuses specifically on the functional significance of the elevated ERN characteristic of many anxious individuals.
Regulation of Hippocampal Glucocorticoid Receptor Gene Transcription and Protein Expression In Vivo

Glucocorticoid receptors (GRs) are glucocorticoid-activated transcription factors that modulate expression of a variety of neuronal genes. Appropriate control of GR expression is therefore critical for maintenance of cellular and organismic homeostasis. The present study assessed glucocorticoid regulation of the GR at the gene, mRNA, and protein level. Removal of circulating glucocorticoids (adrenalectomy) increased GR mRNA expression in CA1 and dentate gyrus (DG). Corticosterone (CORT) replacement normalized GR mRNA expression, whereas high doses slightly decreased GR mRNA in CA1. Parallel increases were observed using a probe complementary to the distal 3′ untranslated region, indicating that mRNA changes were not attributable to selection of alternative polyadenylation site. Expression of a GR intronic sequence was also increased by adrenalectomy, consistent with increased gene transcription. Analysis of regional GR protein expression by immunoautoradiography did not reveal changes in GR protein in pyramidal cell layers; however, increased GR signal was seen in the stratum radiatum, indicating redistribution of GR to the cytosol. Western blot analysis confirmed adrenalectomy-induced increases in hippocampal GR levels. Administration of the mineralocorticoid receptor (MR) antagonist spironolactone increased both GR mRNA and protein in CA1 and DG, consistent with MR-mediated inhibition of GR transcription. However, high-dose CORT treatment did not decrease GR mRNA or protein levels. Chronic stress exposure did not downregulate GR mRNA or protein in hippocampus. The results suggest that the hippocampal GR is subject to heterologous regulation by the MR. In contrast, GR autoregulation is only evident during prolonged exposure to high-circulating glucocorticoid levels.
Practical Analysis of Big Acoustic Sensor Data for Environmental Monitoring

Monitoring the environment with acoustic sensors is an effective method for understanding changes in ecosystems. Through extensive monitoring, large-scale, ecologically relevant, datasets can be produced that can inform environmental policy. The collection of acoustic sensor data is a solved problem, the current challenge is the management and analysis of raw audio data to produce useful datasets for ecologists. This paper presents the applied research we use to analyze big acoustic datasets. Its core contribution is the presentation of practical large-scale acoustic data analysis methodologies. We describe details of the data workflows we use to provide both citizen scientists and researchers practical access to large volumes of ecoacoustic data. Finally, we propose a work in progress large-scale architecture for analysis driven by a hybrid cloud-and-local production-grade website.
Almanac 2012—adult cardiac surgery: the national society journals present selected research that has driven recent advances in clinical cardiology

This review covers the important publications in adult cardiac surgery in the last few years, including the current evidence base for surgical revascularisation and the use of off-pump surgery, bilateral internal mammary arteries and endoscopic vein harvesting. The changes in conventional aortic valve surgery are described alongside the outcomes of clinical trials and registries for transcatheter aortic valve implantation, and the introduction of less invasive and novel approaches of conventional aortic valve replacement surgery. Surgery for mitral valve disease is also considered, with particular reference to surgery for asymptomatic degenerative mitral regurgitation.
UvA-DARE ( Digital Academic Repository ) An information theoretic approach to verification of modular Bayesian fusion systems

This paper introduces an information theoretic approach to verification of causal models in modular Bayesian fusion systems. We assume distributed fusion systems which are gradually extended by adding new modules, each having a limited domain knowledge captured in local Bayesian networks. However, since different modules originate from different, independent design processes important dependencies between the variables in different modules might not correctly be captured in the distributed fusion system. This could have a significant impact on the fusion quality. The introduced method supports discovery of significant dependencies which are ignored in the distributed fusion system.
Generating Random Regular Graphs

Random regular graphs play a central role in combinatorics and theoretical computer science. In this paper, we analyze a simple algorithm introduced by Steger and Wormald [10] and prove that it produces an asymptotically uniform random regular graph in a polynomial time. Precisely, for fixed d and n with d = O(n1/3−ε), it is shown that the algorithm generates an asymptotically uniform random d-regular graph on n vertices in time O(nd2). This confirms a conjecture of Wormald. The key ingredient in the proof is a recently developed concentration inequality by the second author.The algorithm works for relatively large d in practical (quadratic) time and can be used to derive many properties of uniform random regular graphs.
Genetic basis of limb-girdle muscular dystrophies: the 2014 update

Limb-girdle muscular dystrophies (LGMD) are a highly heterogeneous group of muscle disorders, which first affect the voluntary muscles of the hip and shoulder areas. The definition is highly descriptive and less ambiguous by exclusion: non-Xlinked, non-FSH, non-myotonic, non-distal, nonsyndromic, and non-congenital. At present, the genetic classification is becoming too complex, since the acronym LGMD has also been used for a number of other myopathic disorders with overlapping phenotypes. Today, the list of genes to be screened is too large for the gene-by-gene approach and it is well suited for targeted next generation sequencing (NGS) panels that should include any gene that has been so far associated with a clinical picture of LGMD. The present review has the aim of recapitulating the genetic basis of LGMD ordering and of proposing a nomenclature for the orphan forms. This is useful given the pace of new discoveries. Thity-one loci have been identified so far, eight autosomal dominant and 23 autosomal recessive. The dominant forms (LGMD1) are: LGMD1A (myotilin), LGMD1B (lamin A/C), LGMD1C (caveolin 3), LGMD1D (DNAJB6), LGMD1E (desmin), LGMD1F (transportin 3), LGMD1G (HNRPDL), LGMD1H (chr. 3). The autosomal recessive forms (LGMD2) are: LGMD2A (calpain 3), LGMD2B (dysferlin), LGMD2C (γ sarcoglycan), LGMD2D (α sarcoglycan), LGMD2E (β sarcoglycan), LGMD2F (δ sarcoglycan), LGMD2G (telethonin), LGMD2H (TRIM32), LGMD2I (FKRP), LGMD2J (titin), LGMD2K (POMT1), LGMD2L (anoctamin 5), LGMD2M (fukutin), LGMD2N (POMT2), LGMD2O (POMTnG1), LGMD2P (dystroglycan), LGMD2Q (plectin), LGMD2R (desmin), LGMD2S (TRAPPC11), LGMD2T (GMPPB), LGMD2U (ISPD), LGMD2V (Glucosidase, alpha ), LGMD2W (PINCH2).