Miracle-dz/UniFAR-FTUs huggingface dataset:
Technological innovation and interfirm cooperation: an exploratory analysis using survey data from manufacturing firms in the metropolitan region of Vienna

This paper centres around two research questions: first, the identification of five types of networks that manufacturing firms located in the metropolitan region of Vienna may have created for different purposes and second, the question to what extent the likelihood of interfirm cooperation is conditioned by the general profile of manufacturing establishments and their technological resources. Although this paper focuses on the manufacturing sector, a special emphasis is placed on the electronics industry. The study utilises a recent postal survey providing data on size and organisation, products and markets, research and development, innovation and interfirm relationships. The analysis of the first question finds that first, networking does not yet seem to be a popular managerial and organisational concept for manufacturing firms located in the metropolitan region of Vienna; second, networking activities are primarily based on vertical relationships (customer, manufacturer supplier and producer service provider networks) rather than on horizontal linkages (producer networks, industry-university linkages); third, networks focusing on the later stages of the innovation process are less common than those focusing on the earlier stages; fourth, firms tend to rely on sources of technology from national and - especially - international networks. It appears that metropolitan networking is less common than has been thought. For technical advance spatial proximity does not seem to be very important. Turning to the second research question of the study, focusing on the adoption of the managerial and organisational concept of networking, the results are bolstering the argument that establishment traits and technology related-capabilities do play a role. The results achieved reveal, for example, that in-house research skills are a very good predictor for industry-university relationships.
Speaker interpolation in HMM-based speech synthesis system

This paper describes an approach to voice characteristics conversion for an HMM-based text-to-speech synthesis system using speaker interpolation.Although most text-to-speech synthesis systems which synthesize speech by concatenating speech units can synthesize speech with acceptable quality, they still cannot synthesize speech with various voice quality such as speaker individualities and emotions;In order to control speaker individualities and emotions, therefore, they need a large database, which records speech units with various voice characteristics in sythesis phase.On the other hand, our system synthesize speech with untrained speaker’s voice quality by interpolating HMM parameters among some representative speakers’ HMM sets.Accordingly, our system can synthesize speech with various voice quality without large database in synthesis phase.An HMM interpolation technique is derived from a probabilistic similarity measure for HMMs, and used to synthesize speech with untrained speaker’s voice quality by interpolating HMM parameters among some representative speakers’ HMM sets.The results of subjective experiments show that we can gradually change the voice quality of synthesized speech from one’s to the other’s by changing the interpolation ratio.
A heuristic for lot-sizing in multi-stage systems

This article considers the lot-sizing problem in multi-stage production settings with capacity-constrained resources. This problem deals with the determination of a production plan for the end item and its components in order to meet the forecast demand in each period of a planning horizon. The production plan should minimize the sum of production, setup and inventory costs. A heuristic method build upon a formulation of the problem in terms of echelon stock is developed. Computational results are reported and the solutions' quality is evaluated through Lagrangean lower bounds.
Removing fillers to induce semantic classes for a Chinese dialogue system

In this paper, we introduced an unsupervised method to remove fillers in spoken dialogues semi-automatically based on their probability distribution and the effect of removing fillers to induce semantic classes. We conduct the unigram and bigram distribution of fillers on our Chinese voice search data and find that only using these distributions, fillers are in the first 1% of all words. We also test the semantic class induction precision before fillers removing and after fillers removing on both human-to-computer corpus and human-to-human corpus. After removing fillers, the precision grows from 81.8% to 86.9% in human-to-computer dialogues and from 58.0% to 61.9% in human-to-human dialogues.
Effects of the Complex Mass Distribution of Dark Matter Halos on Weak-Lensing Cluster Surveys

Gravitational lensing effects arise from the light-ray deflection by all of the mass distribution along the line of sight. It is then expected that weak-lensing cluster surveys can provide us with true mass-selected cluster samples. With numerical simulations, we analyze the correspondence between peaks in the lensing convergence κ-map and dark matter halos. In particular, we emphasize the difference between the peak κ-value expected from a dark matter halo modeled as an isolated and spherical one, which exhibits a one-to-one correspondence with the halo mass at a given redshift, and that of the associated κ-peak from simulations. For halos with the same expected κ, their corresponding peak signals in the κ-map present a wide dispersion. At an angular smoothing scale of θG = 1′, our study shows that for relatively large clusters, the complex mass distribution of individual clusters is the main reason for the dispersion. The projection effect of uncorrelated structures does not play significant roles. The triaxiality of dark matter halos accounts for a large part of the dispersion, especially for the tail on the high-κ side. Thus, lensing-selected clusters are not really mass-selected. To better predict κ-selected cluster abundance for a cosmological model, one has to take into account the triaxial mass distribution of dark matter halos. On the other hand, for a significant number of clusters, their mass distribution is even more complex than that described by the triaxial model. Our analyses find that large substructures affect the identification of lensing clusters considerably. They could show up as separate peaks in the κ-map and cause a misassociation of the whole cluster with a peak resulting only from a large substructure. The lower end dispersion of κ is attributed mostly to this substructure effect. For θG = 2′, the projection effect can be significant and contributes to the dispersion at both high- and low-κ ends.
A Detailed Analysis of Contemporary ARM and x86 Architectures

RISC vs. CISC wars raged in the 1980s when chip area and processor design complexity were the primary constraints and desktops and servers exclusively dominated the computing landscape. Today, energy and power are the primary design constraints and the computing landscape is significantly different: growth in tablets and smartphones running ARM (a RISC ISA) is surpassing that of desktops and laptops running x86 (a CISC ISA). Further, the traditionally low-power ARM ISA is entering the high-performance server market, while the traditionally high-performance x86 ISA is entering the mobile low-power device market. Thus, the question of whether ISA plays an intrinsic role in performance or energy efficiency is becoming important, and we seek to answer this question through a detailed measurement based study on real hardware running real applications. We analyze measurements on the ARM Cortex-A8 and Cortex-A9 and Intel Atom and Sandybridge i7 microprocessors over workloads spanning mobile, desktop, and server computing. Our methodical investigation demonstrates the role of ISA in modern microprocessors’ performance and energy efficiency. We find that ARM and x86 processors are simply engineering design points optimized for different levels of performance, and there is nothing fundamentally more energy efficient in one ISA class or the other. The ISA being RISC or CISC seems irrelevant.
Radiation induced CNS toxicity – molecular and cellular mechanisms

Radiotherapy of tumours proximal to normal CNS structures is limited by the sensitivity of the normal tissue. Prior to the development of prophylactic strategies or treatment protocols a detailed understanding of the mechanisms of radiation induced CNS toxicity is mandatory. Histological analysis of irradiated CNS specimens defines possible target structures prior to a delineation of cellular and molecular mechanisms. Several lesions can be distinguished: Demyelination, proliferative and degenerative glial reactions, endothelial cell loss and capillary occlusion. All changes are likely to result from complex alterations within several functional CNS compartments. Thus, a single mechanism responsible cannot be separated. At least four factors contribute to the development of CNS toxicity: (1) damage to vessel structures; (2) deletion of oligodendrocyte-2 astrocyte progenitors (O-2A) and mature oligodendrocytes; (3) deletion of neural stem cell populations in the hippocampus, cerebellum and cortex; (4) generalized alterations of cytokine expression. Several underlying cellular and molecular mechanisms involved in radiation induced CNS toxicity have been identified. The article reviews the currently available data on the cellular and molecular basis of radiation induced CNS side effects. © 2001 Cancer Research Campaign http://www.bjcancer. com
Tri-snRNP-associated proteins interact with subunits of the TRAMP and nuclear exosome complexes, linking RNA decay and pre-mRNA splicing

Nuclear RNA decay factors are involved in many different pathways including rRNA processing, snRNA and snoRNA biogenesis, pre-mRNA processing, and the rapid decay of cryptic intergenic transcripts. In contrast to its yeast counterpart, the mammalian nuclear decay machinery is largely uncharacterized. Here we report interactions of several putative components of the human nuclear RNA decay machinery, including the TRAMP complex protein Mtr4 and the nuclear exosome constituents PM/Scl-100 and PM/Scl-75, with components of the U4/U6.U5 tri-snRNP complex required for pre-mRNA splicing. The tri-snRNP component Prp31 interacts indirectly with Mtr4 and PM/Scl-100 in a manner that is dependent on the phosphorylation sites in the middle of the protein, while Prp3 and Prp4 interact with the nuclear decay complex independent of Prp31. Together our results suggest recruitment of the nuclear decay machinery to the spliceosome to ensure production of properly spliced mRNA.
A Distributed Control Architecture for Autonomous Robot Systems

The main advantage of distributed controlled robots and subsystems is the decentralized task execution by the system components. This way, properties for the design of flexible control architectures like modularity, fault-tolerance, integrability and extendibility are easily obtained, further it is possible to use the concepts of distributed knowledge and decentralized world representation. On the other hand, coordination between the components, for example path planning for collision avoidance between both manipulators in a two-arm-system, is very difficult to guarantee. To explain these concepts, the Karlsruhe Autonomous Mobile Robot KAMRO is considered which is being developed at IPR. The robot system consists of several subcomponents like two manipulators, hand-eyecameras, one overhead-camera and a mobile platform. Extensions to the distributed control architecture KAMARA (KAMROs Multi Agent Robot Architecture) are described that are responsible to overcome coordination problems, for example caused by the independent task execution of both manipulator systems. Further, it is explained which way the decentralized world representation can be used for parallel task execution. The described intelligent control architecture will replace the former control architecture of the autonomous robot KAMRO.
Experiments with Semi Automated Ontology Building using Text Onto Miner

This paper presents an overview of Text-Onto-Miner (TOM) – a natural language analysis system, developed by Institute of Computer Science of the Warsaw University of Technology during a research project supported by France Telecom. The main purpose of TOM is testing various algorithms and approaches that could be applied to the problem of building ontologies semi-automatically. It is also an efficient and extensible text mining system, that could be used in many applications related to natural language document processing.
Antisymmetry and Word Order in Serial Constructions

Strict head-final surface order derives from underlying left-headedness in Ijo, a Niger-Congo language of Nigeria. A word order anomaly in Ijo SERIAL VERB CONSTRUCTIONS (SVCs) strongly suggests this, and left-to-right asymmetric c-command among internal arguments of SVCs confirms it. The anomaly is universal among surface right-headed languages with SVCs, indicating that deep left-headedness is universal, as antisymmetry theory predicts (Kayne 1994). Assuming complements are in Specs, and that a light verb v selects every VP (Chomsky 1999), I derive VOVO from OVOV by two instances of V-to-v movement. I argue for a nonuniform approach to SVCs, involving relations of both raising (Campbell 1989) and control (Collins 1997). Other aspects of SVC word order are predictable from a universal thematic hierarchy nontheme > theme, and short scrambling (Takano 1998).
Unfolding the potential of computational musicology

This paper addresses current chances and challenges in computational musicology. Computational musicology is a genuinely interdisciplinary research area that requires the contribution of questions, methods and insights from both musicology and computer science. This paper demonstrates how computational approaches to musicological questions generate new perspectives for musicology. In turn, computational musicology has the potential to become an indispensible partner for computer science in Music Information Retrieval. We argue that, for unfolding the potential of computational musicology, the full interdisciplinary enterprise has yet to be realized and we discuss examples of promising collaborative
Wavelet LPC With Neural Network for Speaker Identification System

In this study, an average framing linear prediction coding (AFLPC) technique for text-independent speaker identification systems is proposed.The study of the combination of modified LPC with wavelet transform (WT), termed AFLPC, is presented for speaker identification based on our previous paper. The study procedure is based on feature extraction and voice classification. In the phase of classification, feed forward backprobagationneural network (FFBPN) is applied because of its rapid response and ease in implementation. In the practical investigation, performance of different wavelet transforms in conjunction with AFLPC were compared with one another. In addition, the capability analysis on the proposed system was examined by comparing it with other systems proposed in literature. Consequently, the FFBPNclassifier achieves a better recognition rate (97.36%) with the wavelet packet (WP) and AFLPC termed WPLPCF feature extraction method. It is also suggested to analyze the proposed system in additive white Gaussian noise (AWGN) and real noise environments.
Convergence Properties of Crystal Structure Prediction by Quasi-Random Sampling

Generating sets of trial structures that sample the configurational space of crystal packing possibilities is an essential step in the process of ab initio crystal structure prediction (CSP). One effective methodology for performing such a search relies on low-discrepancy, quasi-random sampling, and our implementation of such a search for molecular crystals is described in this paper. Herein we restrict ourselves to rigid organic molecules and, by considering their geometric properties, build trial crystal packings as starting points for local lattice energy minimization. We also describe a method to match instances of the same structure, which we use to measure the convergence of our packing search toward completeness. The use of these tools is demonstrated for a set of molecules with diverse molecular characteristics and as representative of areas of application where CSP has been applied. An important finding is that the lowest energy crystal structures are typically located early and frequently during a quasi-random search of phase space. It is usually the complete sampling of higher energy structures that requires extended sampling. We show how the procedure can first be refined, through targetting the volume of the generated crystal structures, and then extended across a range of space groups to make a full CSP search and locate experimentally observed and lists of hypothetical polymorphs. As the described method has also been created to lie at the base of more involved approaches to CSP, which are being developed within the Global Lattice Energy Explorer (Glee) software, a few of these extensions are briefly discussed.
Cis-Regulatory Elements in the Accord Retrotransposon Result in Tissue-Specific Expression of the Drosophila melanogaster Insecticide Resistance Gene Cyp6g1

Transposable elements are a major mutation source and powerful agents of adaptive change. Some transposable element insertions in genomes increase to a high frequency because of the selective advantage the mutant phenotype provides. Cyp6g1-mediated insecticide resistance in Drosophila melanogaster is due to the upregulation of the cytochrome P450 gene Cyp6g1, leading to the resistance to a variety of insecticide classes. The upregulation of Cyp6g1 is correlated with the presence of the long terminal repeat (LTR) of an Accord retrotransposon inserted 291bp upstream of the Cyp6g1 transcription start site. This resistant allele (DDT-R) is currently at a high frequency in D. melanogaster populations around the world. Here, we characterize the spatial expression of Cyp6g1 in insecticide-resistant and -susceptible strains. We show that the Accord LTR insertion is indeed the resistance-associated mutation and demonstrate that the Accord LTR carries regulatory sequences that increase the expression of Cyp6g1 in tissues important for detoxification, the midgut, Malpighian tubules, and the fat body. This study provides a significant example of how changes in tissue-specific gene expression caused by transposable-element insertions can contribute to adaptation.
Fundamental Properties of O-Type Stars

We present a comprehensive analysis of high-resolution, far-ultraviolet HST STIS, FUSE, and optical spectra of 18 O stars in the Small Magellanic Cloud. Our analysis is based on the OSTAR2002 grid of NLTE metal-line-blanketed model atmospheres calculated with our code TLUSTY. We systematically explore and present the sensitivity of various UV and optical lines to different stellar parameters. We have obtained consistent fits of the UV and the optical spectrum to derive the effective temperature, surface gravity, surface composition, and microturbulent velocity of each star. Stellar radii, masses, and luminosities follow directly. For stars of the same spectral subtype, we find a general good agreement between effective temperature determinations obtained with TLUSTY, CMFGEN, and FASTWIND models, which are all lower than the standard Teff calibration of O stars. We propose a new calibration between the spectral type and effective temperature based on our results from UV metal lines, as well as optical hydrogen and helium lines. The lower effective temperatures translate into ionizing luminosities that are smaller by a factor of 3 compared to luminosities inferred from previous standard calibrations. The chemical composition analysis reveals that the surface of about 80% of the program stars is moderately to strongly enriched in nitrogen, while showing the original helium, carbon, and oxygen abundances. Our results support the new stellar evolution models that predict that the surface of fast rotating stars becomes nitrogen-rich during the main-sequence phase because of rotationally induced mixing. Enrichment factors are, however, larger than predicted by stellar evolution models. Most stars exhibit the ``mass discrepancy'' problem, which we interpret as a result of fast rotation that lowers the measured effective gravity. Nitrogen enrichment and low spectroscopic masses are therefore two manifestations of fast rotation. Our study thus emphasizes the importance of rotation in our understanding of the properties of massive stars and provides a framework for investigating populations of low-metallicity massive stars at low and high redshifts.
Concurrent caching

A concurrent cache design is presented which allows cached data to be spread across a cluster of computers. The implementation separates persistent storage from cache storage and abstracts the cache behaviour so that the user can experiment with cache size and replacement policy to optimize performance for a given system, even if the production data store is not available. Using processes to implement cached objects allows for runtime configurability and adaptive use policies as well as parallelization to optimize resource access efficiency.
Localization of passive UHF RFID tags on the assembly line

As the internet of things (IOT) develops, radio frequency identification (RFID), a key technology of IOT, is gaining more and more attention. In some manufacturing applications, such as the assembly line, the localization of the specific product is very important for the customized production. To improve the performance of the assembly line localization system, the method of using the phase of one RFID reader antenna is proposed. Note that the phase reflected by the tags is distance sensitive, which is able to locate the tags accurately. Through modeling analysis and experimental results on a motorized stage, it shows that the localization accuracy of using the phase reflected by the passive UHF RFID tags on the linear assembly line can meet the demand of the practical application.
WACCO and LOKO: Strong Consistency at Global Scale

Motivated by a vision for future global-scale services supporting frequent updates and widespread concurrent reads, we propose a scalable object-sharing system called WACCO offering strong consistency semantics. WACCO propagates read responses on a tree-based topology to satisfy broad demand and migrates objects dynamically to place them close to that demand. To demonstrate WACCO, we use it to develop a service called LOKO that could roughly encompass the current duties of the DNS and simultaneously support fine-grained status updates (e.g., Currently preferred routes) in a future Internet. We evaluate LOKO, including the performance impact of updates, migration, and fault tolerance, using a trace of DNS queries served by Akamai.
Exploring family values

Exploring Family Values by Jaime L. Carr Dr. Christopher Heavey, Examination Committee Chair Associate Professor o f Psychology University o f Nevada, Las Vegas This exploratory study sought to develop an empirically based scale to measure family values (Family Values Scale), and to then begin to establish the validity o f this instrument. This scale consists o f two major subscales. Family Priority and Traditionality. Results indicate that these two subscales have acceptable internal consistency and temporal stability. Subject were students from the University o f Nevada, Las Vegas (N = 380). Scores on the Family Values Scale were compared to scales measuring social desirability, selfrsm, satisfaction with life, perceived stress, social support, and psychological symptomotology. Results indicated that the Family Priority subscale is significantly related to satisfaction with life, social support, and psychological symptomotology. Further, the Traditionality subscale is significantly related to satisfaction with life. Neither subscale was related to stress. Limitations o f this study and directions for future research are offered.