Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust speech recognition in the automobile

In this paper we discuss a number of the ways in which the recognition accuracy of automatic speech recognition systems is affected by ambient noise in the automobile, along with the extent to which various techniques for robust speech recognition can provide for more robust recognition. We consider separately the effects of engine noise, interference by turbulent air outside the car, interference by sounds from the car’s radio, and interference by the sounds of the car’s windshield wipers. Recognition accuracy was compared using baseline processing, cepstral mean normalization (CMN), and codeword-dependent cepstral normalization (CDCN). The greatest degradation in recognition accuracy was produced by interference from AM-radio talk shows. The use of CMN and especially CDCN was found to be significantly improve recognition accuracy, except for the effects of interference from radio talk shows at low car speeds. This type of interference is effectively suppressed through the use of adaptive noise cancellation techniques.
Artificial syntactic violations activate Broca's region

Abstract In the present study, using event-related functional magnetic resonance imaging, we investigated a group of participants on a grammaticality classification task after they had been exposed to well-formed consonant strings generated from an artificial regular grammar. We used an implicit acquisition paradigm in which the participants were exposed to positive examples. The objective of this study was to investigate whether brain regions related to language processing overlap with the brain regions activated by the grammaticality classification task used in the present study. Recent meta-analyses of functional neuroimaging studies indicate that syntactic processing is related to the left inferior frontal gyrus (Brodmann’s areas 44 and 45) or Broca’s region. In the present study, we observed that artificial grammaticality violations activated Broca’s region in all participants. This observation lends some support to the suggestions that artificial grammar learning represents a model for investigating aspects of language learning in infants [TICS 4 (2000) 178] and adults [Proceedings of the National Academy of Sciences of United States of America 99 (2002) 529].
WebPro : an easy-to-use accessible web-based project administration system

Administering complex research projects entails considerable effort especially for sharing a common understanding of project goals and for timely monitoring of progress. Additional difficulties may be encountered if project members are distributed in different geographical locations and speak different languages. One approach to the solution of this problem is the use of specialised on-line tools. Several existing project management tools have been reviewed to analyse the extent of assistance offered to project members. For the majority of the project stakeholders, existing tools appear rather complicated to use and difficult to learn. Based upon our findings, an interactive, user -friendly and accessible web-based application has been designed and implemented to support on-line project administration, through a set of easy-to-learn and easy-to-use facilities. WebPro provides facilities to project members, according to their role in the project and the assigned tasks. The evaluation of WebPro has confirmed that it improves specific aspects of project administration tasks, by facilitating a higher degree of user interaction; it is user -friendly, by offering possibilities for overall reduction of the time required for the accomplishment of certain project tasks and it is accessible by people with disabilities, by complying with WCAG 1.0 Level A guidelines. Doulgeraki, Partarakis, Karampelas & Stephanidis, 2004 WebPro
A novel nonsense mutation in CRYBB1 associated with autosomal dominant congenital cataract

Purpose To identify the molecular defect underlying an autosomal dominant congenital nuclear cataract in a Chinese family. Methods Twenty-two members of a three-generation pedigree were recruited, clinical examinations were performed, and genomic DNA was extracted from peripheral blood leukocytes. All members were genotyped with polymorphic microsatellite markers adjacent to each of the known cataract-related genes. Linkage analysis was performed after genotyping. Candidate genes were screened for mutation using direct sequencing. Individuals were screened for presence of a mutation by restriction fragment length polymorphism (RFLP) analysis. Results Linkage analysis identified a maximum LOD score of 3.31 (recombination fraction [θ]=0.0) with marker D22S1167 on chromosome 22, which flanks the β-crystallin gene cluster (CRYBB3, CRYBB2, CRYBB1, and CRYBA4). Sequencing the coding regions and the flanking intronic sequences of these four candidate genes identified a novel, heterozygous C→T transition in exon 6 of CRYBB1 in the affected individuals of the family. This single nucleotide change introduced a novel BfaI site and was predicted to result in a nonsense mutation at codon 223 that changed a phylogenetically conserved amino acid to a stop codon (p.Q223X). RFLP analysis confirmed that this mutation co-segregated with the disease phenotype in all available family members and was not found in 100 normal unrelated individuals from the same ethnic background. Conclusions This study has identified a novel nonsense mutation in CRYBB1 (p.Q223X) associated with autosomal dominant congenital nuclear cataract.
Scaling Up the Training of Deep CNNs for Human Action Recognition

Convolutional deep neural networks (CNNs) has been shown to perform well in difficult learning tasks such as object recognition. They are gaining huge importance in recent times but are computationally intensive. Typically trained on massive datasets, two-dimensional CNNs are used for image classification and recognition purposes and consume huge computational time. For applications like human action recognition involving video inputs, their 3D counterparts termed as 3D convolutional neural networks (3D-CNNs) are employed. Scaling up the computations to support large datasets and accelerating the training on these models for high performance has been the need of the hour especially in 3D deep learning models since the extended connectivity of CNN in the time domain takes huge time for training the model. Also there is a need to look at the model parameters and hyper parameters that determine both the computational performance as well as the accuracy of the deep neural network. Accelerators such as Graphics Processing Units (GPUs) and multi-cores provide a means for speeding up the training of CNNs and achieve higher performance by parallelizing the training of these models by taking advantage of data and model parallelism. In this work we use multi-core CPUs and GPUs to scale-up the training of 3D-CNNs. We achieve a faster implementation as well as report how various network parameters affect the performance of the model thereby providing recommendations on initializing the values of the same. The code scales up well on multi-cores and GPUs, with a speedup of 10x on CPUs and achieves almost 12x on GPUs compared to the serial version. Our work infers that 3D-CNN code scales up best on CPUs when the convolution step is implemented with a highly parallel FFT based approach, thereby achieving the performance comparable to GPUs using OpenMP.
The role of regions and sub-national actors in Europe

The essays gathered in this collection examine the involvement of self-governing sub-national and regional actors in the law and policy-making of the European Union. State power is today exercised in the context of the complex institutional environment of the EU. But what of regions and sub-national actors? Are their interests adequately represented; can they advance them or can they,at least, protect them from unwitting or calculated damage? This book surveys the broad questions of law and political science and investigates the contribution of the EU's Committee of the Regions and also 'bottom-up' initiatives launched by the regions themselves. Given that much regional autonomy has been hard won, one would suppose that the centralising influence flowing from the EU's intrusion into the domestic settlement would be treated with extreme caution by the regions. Moreover, among the Member States there is great diversity in the patterns of political organisation adopted to cope with the tension between the centralisation of power and respect for local autonomy. Case studies including Spain, Germany and Finland reveal that there is no single consistent historical narrative. States change, as the UK's recent experience illustrates. The book offers findings that are interesting at a general level in investigating patterns of multi-level governance, but is also rich in case-specific information.
Tool demo: testing configurable systems with FeatureIDE

Most software systems are designed to provide custom functionality using configuration options. Testing such systems is challenging as running tests of a single configuration is often not sufficient, because defects may appear in other configurations. Ideally, all configurations of a software system should be tested, which is usually not applicable in practice due to the combinatorial explosion with respect to the configuration options. Multiple sampling strategies aim to reduce the set of tested configurations to a feasible amount, such as T-wise sampling, random configurations, and user-defined configurations. However, these strategies are often not applied in practice as they require manual effort or a specialized testing framework. Within our tool FeatureIDE, we integrate all aforementioned strategies and reduce the manual effort by automating the process of generating and testing configurations. Furthermore, we provide support for unit testing to avoid redundant test executions and for variability-aware testing. With this extension of FeatureIDE, we aim to make recent testing techniques for configurable systems applicable in practice.
UML dialect for designing object-relational databases

The market trends indicate that the next generation database technology will be dominated by object-relational systems. This shift to the new technology calls for visual modeling techniques to facilitate the design of object-relational database systems. Even though Unified Modeling Language (UML) is not currently equiped to manage this task, it can be extended for it.The paper defines design constructs needed for the development of an object-relational database system. The constructs include those that assist in the migration process from a relational to an object-relational database. Both data and procedural constructs are considered. Many UML extensions in the proposed UML dialect are derived by stereotyping existing UML elements. New classes are created to model object-relational constructs, and they are assigned their own distinct icons. Any special constraints on relationships between concepts in the extended UML are explained through practical examples. The mappings from design models to an object-relational implementation are exemplified.
Feature extraction techniques for face identification

For face recognition, it is very important determining which features of the faces will be used in the classification process. The identification based on appearance uses the pixels of the corresponding image to extract the features. Using the pixels directly is not very efficient due to the high dimensionality of the resulting features which results in a poor discriminative capability between different persons and in increased computational complexity. Implementing any kind of data transform could be a good strategy for reducing the dimensionality of the data and increasing the discriminator capability. Using PCA or DCT transforms it is possible to implement systems with a good rate of recognition if the number of recognizable persons is low. In this project, it has been investigated others features extraction techniques, especially the ones based on Local Binary Patterns.
Optimized Termite: A bio-inspired routing algorithm for MANET's

A Mobile Adhoc Network (MANET) is a collection of mobile nodes connected by the Wireless medium and each mobile node is aware of only its neighbours. Due to mobility of these mobile nodes the topology changes dynamically. Such a dynamic network topology makes the task of routing a challenging one. Recently, a new class of routing algorithms based on Swarm Intelligence has emerged. These algorithms are inspired by nature's self-organizing systems like ant-colonies, bird-flocks, honey-bees, school of fish, spiders and fireflies. The characteristics of such algorithms are their capability of self-organization, adaptation to the changing conditions, self healing and local decision making. In this work, a routing protocol inspired by the termite activity in nature, called Optimized-Termite (Opt-Termite), is proposed. Opt-Termite uses concept of stigmergy for self-organization, thereby reducing the control packet overhead. Opt-Termite mainly concentrates on load balancing for optimization. With Opt-Termite, a route with less loaded mobile nodes in terms of traffic will be chosen to reach destination. The routing information at each node gets influenced by the movement of packets and the routing table will be updated accordingly. It also allows the use of multiple paths and each packet is routed randomly and independently. Opt-Termite is implemented in ns-2 and its performance is compared with traditional routing protocol AODV. Opt-Termite's performance has been promising.
System Dynamics Modeling for Analyzing Business Model Innovation

The Blue Economy is a worldwide leading initiative seeking to bridge the gap between value generation and positive socio-environmental impact. In the paper at hand we aim to analyze one specific business model innovation developed by the Blue Economy and creating an established proof of concept for it. For this, we use System Dynamics modeling and create six sub-models in order to transparently analyze the case in a traceable approach. We believe this contributes to a better resilience in society and the strengthening of democracy.
Pseudomonas aeruginosa PAO1 virulence factors and poplar tree response in the rhizosphere

Whole‐transcriptome analysis was used here for the first time in the rhizosphere to discern the genes involved in the pathogenic response of Pseudomonas aeruginosa PAO1 as well as to discern the response of the poplar tree. Differential gene expression shows that 185 genes of the bacterium and 753 genes of the poplar tree were induced in the rhizosphere. Using the P. aeruginosa transcriptome analysis, isogenic knockout mutants, and two novel plant assays (poplar and barley), seven novel PAO1 virulence genes were identified (PA1385, PA2146, PA2462, PA2463, PA2663, PA4150 and PA4295). The uncharacterized putative haemolysin repressor, PA2463, upon inactivation, resulted in greater poplar virulence and elevated haemolysis while this mutant remained competitive in the rhizosphere. In addition, disruption of the haemolysin gene itself (PA2462) reduced the haemolytic activity of P. aeruginosa, caused less cytotoxicity and reduced barley virulence, as expected. Inactivating PA1385, a putative glycosyl transferase, reduced both poplar and barley virulence. Furthermore, disrupting PA2663, a putative membrane protein, reduced biofilm formation by 20‐fold. Inactivation of PA3476 (rhlI) increased virulence with barley as well as haemolytic activity and cytotoxicity, so quorum sensing is important in plant pathogenesis. Hence, this strategy is capable of elucidating virulence genes for an important pathogen.
Pseudo-Roughness for Haptic Interaction : Considering Collisions with Arbitrary-Shaped Objects

An increased number of polygons in virtual objects cause a delay in simulation time, making it difficult to handle haptic interactions, which need real-time processing in virtual worlds. Previous studies reduced the number of polygons in objects by representing the roughness of an object’s surface as a texture, thus reducing the processing time. However, it is difficult to simulate the interaction of an arbitrary-shaped object with this pseudo-roughness, because the conventional methods cannot accept that the object makes contact with two or more points of the polygons at the same time. To solve these problems, we propose a PPRM (plural pixels reference method), an interaction method for merging pixel values of textures that skips the process of copying polygons from the pixels of textures. Experimental results show that the PPRM has a faster processing speed than the conventional method when using a large number of polygons, and is more accurate than the conventional method.
Relationship of Human Resource Investment, Human Capital and Hi-Tech Firm's Performance

This research tested the effects of human resource (HR) investment through human capital (HC) to hi-tech firm's performance. Eleven hypotheses of relations among HR investment, HC and hi-tech firm's performance are proposed in the article. The research used a sample of Chinese hi-tech firms. A variance analysis indicated that HR investment is significantly related to higher level of HC in a hi-tech firm, and HR investment is indirectly related to overall hi-tech firm performance through firm-level HC.
Topology Formation in mesh networks considering Role Suitability

The paper studies various mesh topology formation techniques that can be used to aid the development of large-scale capillary networks. The work focuses on how mesh networks can be established using Bluetooth Low Energy exploiting the heterogeneous characteristics of the devices in the network. A novel algorithm called Topology Formation considering Role Suitability (TFRS) is proposed aiming to maximize the network lifetime. The algorithm employs a newly introduced metric called role suitability metric (RSM) to assign the best role among master, relay and slave to a participating device. The RSM metric is computed from device characteristics including, but not limited to, energy, mobility and computational capability. We use system-level simulation to evaluate the performance of the proposed algorithm against a reference under a homogeneous deployment scenario consisting of heterogeneous devices. Results show that the network lifetime can be improved significantly when the topology is formed considering the device characteristics for both master role selection and relay selection. TFRS can achieve 20% to 40% higher network lifetime depending on the deployment characteristics over the reference algorithm.
Plasmid-based target protectors allow specific blockade of miRNA silencing activity in mammalian developmental systems

Over the past decade, microRNAs (miRNAs) have emerged as essential posttranscriptional regulators of gene expression. Though a great deal has been discovered about miRNA genomics, biogenesis, mechanisms, and functions, the challenge of attributing phenotypes of altered miRNA expression to specific targets still remains. Here, we apply the existing target protector concept of blocking miRNA action at a single binding site in the 3′untranslated region (3′UTR) of its target to a plasmid-based approach. We optimize and demonstrate target protector efficacy in vitro, where it blocks repression of a luciferase construct and an endogenous protein. Using the developing mouse cortex as a model, we validate that target protectors are effective in vivo, where protectors for the miR-19a binding sites in the Pten 3′UTR alter proliferation and specification of neural progenitors, phenocopying Pten ectopic expression phenotypes. Our study introduces a new tool for analyzing specific miRNA:target interactions across mammalian developmental systems, facilitating further miRNA functional discoveries.
3 Shock Management of Shock

In thermodynamic terms, the purpose of the heart is simple enough. Its sole function is to generate useful energy (as opposed to heat, which it also generates) and then transfer that energy into the pulmonary artery and the aortic root as efficiently as possible. The useful energy transferred into the pulmonary artery from the right ventricle moves the blood through the lungs and into the left atrium and ventricle during diastole.The useful energy transferred into the aortic root from the left ventricle moves the blood throughout the body. The blood delivers nutrients (including oxygen) to metabolizing tissues, removes waste products from those tissues, carries heat from those tissues to the skin (where the heat is dissipated into the environment), and transports hormones and intermediate products of metabolism from one part of the body to another.The remaining energy in the blood pushes the blood into the right atrium and ventricle during diastole. This useful energy has two components: flow and pressure. Flow, in the case of the cardiovascular system, is cardiac output. The pressures of interest are the mean pressures in the roots of the pulmonary artery and the aorta [see Figure 1]. These pressures, like all those we describe in this chapter, are expressed as being above (or occasionally below) atmospheric pressure and are measured with transducers placed at the level of the right atrium. The formula for calculating the amount of useful energy transferred into the root of the pulmonary artery from the right ventricle (per unit time—typically 1 minute) is the cardiac output multiplied by the mean pressure in the pulmonary artery.The useful energy transferred into the aortic root from the left ventricle (per unit time) is the cardiac output multiplied by the mean aortic root pressure.1-3 If the amount of useful energy transferred into the roots of the pulmonary artery and the aorta is insufficient to meet the body’s basic metabolic needs, the patient is said to be in shock. Shock can James W. Holcroft, M.D., F.A. C.S. , John T. Anderson, M.D., F.A. C.S. , and Matthew J. Sena, M.D.