Miracle-dz/UniFAR-FTUs huggingface dataset:
Sharing information in teams: giving up privacy or compromising on team performance?

Human teamwork can be supported by agent technology by providing each human team member with an agent that monitors, supports and advices the human. The agent can, for example, monitor the human's workload, and share that information with (agents of) other team members so that work can be distributed effectively. However, though sharing information can lead to a higher team performance, it may violate the individual team members' privacy. This raises the question what type of and how often information should be shared between team members. This paper addresses this question by studying the trade-off between privacy loss and team performance in the train traffic control domain. We provide a conceptual domain analysis, introduce a formal model of train traffic control teams and their dynamics, and describe an agent-based simulation experiment that investigates the effects of sharing different types and amounts of information on privacy loss and team performance. The results give insight in the extent to which different information types cause privacy loss and contribute to team performance. This work enables the design of privacy-sensitive support agents for teamwork.
Human Versus Automation in Responding to Failures: An Expected-Value Analysis

A simple analytical criterion is provided for deciding whether a human or automation is best for a failure detection task. The method is based on expected-value decision theory in much the same way as is signal detection. It requires specification of the probabilities of misses (false negatives) and false alarms (false positives) for both human and automation being considered, as well as factors independent of the choice - namely, costs and benefits of incorrect and correct decisions as well as the prior probability of failure. The method can also serve as a basis for comparing different modes of automation. Some limiting cases of application are discussed, as are some decision criteria other than expected value. Actual or potential applications include the design and evaluation of any system in which either humans or automation are being considered.
Accuracy of transbronchial biopsy as a rebiopsy method for patients with relapse of advanced non-small-cell lung cancer after systemic chemotherapy

Introduction Rebiopsy in patients with advanced non-small-cell lung cancer (NSCLC) resistant to systemic chemotherapy may yield information on the mechanisms of resistance and planning of subsequent treatment. Transbronchial biopsy (TBB) using a flexible bronchoscope has been commonly used for establishing the initial diagnosis of lung cancer. The aim of this study was to assess the accuracy and safety of TBB in patients with NSCLC relapse, and the factors affecting its diagnostic yield. Methods We retrospectively screened patients with advanced NSCLC who underwent TBB for rebiopsy after developing resistance to systemic chemotherapy at Kurume University Hospital between January 2012 and June 2016. A positive diagnostic result obtained by TBB was defined as malignancy determined on the basis of histological features that were adequate for mutational analysis or immunohistochemistry. Severe postprocedural complications were defined as those requiring invasive medical procedures or prolonged hospitalisation. Results 109 patients were enrolled in this retrospective study. Adequate tumour samples were collected from 88 of these patients, giving a high diagnostic yield of 80.7%. The diagnostic yield of TBB was not associated with tumour mutational status, the previous treatment regimen, or efficacy of the previous treatment. There were no severe postprocedural complications such as pneumothorax or serious haemorrhage. Conclusions TBB is considered one of the safest and most useful procedures for rebiopsy of NSCLC that has relapsed after chemotherapy, regardless of patient background and treatment history.
Facilitated isolation, purification, and analysis of glucuronoxylomannan of Cryptococcus neoformans

Cryptococcus neoformans was cultured in a chemically defined medium. The culture was adjusted to 0.25% formaldehyde or autoclaved after 5 days of growth at 35 degrees C, and a cell-free supernatant was obtained by centrifugation. Solid calcium acetate was added to the supernatant to give a 5% solution, and the pH was adjusted to approximately 5 with glacial acetic acid. The polysaccharide (PS) was precipitated by the addition of 3 volumes of 95% ethanol. The PS was dissolved in 0.2 M NaCl, and insoluble calcium salts were solubilized by the addition of several drops of glacial acetic acid. The PS solution was treated by ultrasonic irradiation for 15 min. This concurrently decreased the molecular weight of the PS and reduced the viscosity of the solution. The ultrasonically irradiated PS was precipitated by differential complexation with hexadecyltrimethylammonium bromide at 23 degrees C, the complex was dissolved in 1 M NaCl, and the glucuronoxylomannan was precipitated by adding 3 volumes of ethanol. The glucuronoxylomannan was dissolved in 1 M NaCl and then ultrasonically irradiated for 2 h to reduce the molecular mass to a limiting value of approximately 100 kDa (GXMS). The purified GXMS was centrifuged, dialyzed, and finally recovered by lyophilization. GXMS was chromatographed on DEAE-cellulose at reasonable concentrations without the complication of high solution viscosity. The sugar composition and structure of GXMS were determined by gas-liquid chromatography, permethylation gas-liquid chromatography-mass spectrometry, and 13C nuclear magnetic resonance spectroscopy. The improved solution characteristics of GXMS were ideal for the determination of its chemical and serological properties.
Adaptive block rearrangement

An adaptive technique for reducing disk seek times is described. The technique copies frequently referenced blocks from their original locations to reserved space near the middle of the disk. Reference frequencies need not be known in advance. Instead, they are estimated by monitoring the stream of arriving requests. Trace-driven simulations show that seek times can be cut substantially by copying only a small number of blocks using this technique. The technique has been implemented by modifying a UNIX device driver. No modifications are required to the file system that uses the driver.
Study on algorithms of determining basic probability assignment function in Dempster-Shafer evidence theory

Dempster-Shafer evidence theory (D-S theory) provides a useful computational scheme for integrating uncertainty information from multiple sources in artificial intelligence systems. D-S evidence theory is a useful method for dealing with uncertainty problems. Therefore, it has been successfully applied in data fusion and pattern recognition. However, it also has some shortcomings. The key problem to D-S reasoning is basic probability assignment (BPA) function, which to a great extent limits its applications. To solve this problem, this paper presents three methods to constructing the BPA function. These methods are based on gray correlation analysis, fuzzy sets, and attribute measure respectively. Furthermore, experiments of recognizing the emitter purpose are selected to demonstrate these methods of determining the BPA function proposed. Experimental results show that the performance of these new methods is accurate and effective.
Fully-Coupled Characterization of Thermo-Electro-Magneto-Mechanical Materials

Smart materials exhibit powerful nonlinear 3D coupling and anisotropy. However, the design and associated models, experimental characterization, and control design of smart systems are in general 1D. This reduced framework severely limits applications to 1D. The research presented here enables the tailoring of composition and processing to produce multifunctional materials with targeted performance properties that are fully nonlinear and 3D. A complete combinatorial analysis of seventy-two possible energy functions and state variables that describe 3D, nonlinear, coupled behavior of thermo-electro-magneto-mechanical materials is created. Each set of state variables and corresponding energy function correlates with a given set of experiments, the independent variables being controlled and the dependent variables being the measured responses. The constitutive equations with respect to each of these energy functions are derived in a systematic way by combining the mesoscale Maxwell equations, the balance laws of mechanics, and the balance law of entropy. The application of this framework to a new class of magnetostrictive Iron-Gallium alloys (Galfenol) is investigated with the intent to implement these alloys in a new class of fuel injectors to achieve unprecedented dynamic response and performance. The possibility of determining the full 3D constitutive behavior of Galfenol from simple, 1D macroscopic experiments in combination with analytical models based on knowledge of the crystal structure is explored. In this respect, a FEM formulation is presented. ii
Volume 2 IDENTIFICATION OF OESTRONE SULPHATASE INHIBITORS IN BREAST CYST FLUID : A NEW TREATMENT FOR BREAST CANCER i

Introduction Oestrogens play an important role in the development of breast cancer. Oestrone sulphate is a major source of active oestrogens in the breast, being converted to oestrone by oestrone sulphatase. Oestrone is then converted to oestradiol, a potent oestrogen strongly implicated in the development of breast cancer, by the enzyme 1713-hydroxysteroiddehydrogenase. In vitro oestrone sulphatase activity in breast tissue has been shown to be at least 1.000 times as high as aromatase activity, which converts androgens to oestrogens. Hence, local production of active oestrogens from oestrone sulphate is a very important source of oestrogens in breast tumours. I have previously found that breast cyst fluid is a potent inhibitor of oestrone sulphatase activity in certain breast cancer cell lines. Oestrone sulphatase inhibition is potentially of great importance in the treatment of women with hormonedependent breast cancers. The aim of this study was to identify the substances present in breast cyst fluid which are responsible for the oestrone sulphatase inhibitory property of breast cyst fluid.
Effect of molecular crowding on DNA polymerase activity

Live cells contain high concentrations of macromolecules, but almost all experimental biochemical data have been generated from dilute solutions that do not reflect conditions in vivo. To understand biomolecular behavior in vivo, properties studied in vitro are extrapolated to conditions in vivo; however, the molecular conditions within live cells are inherently crowded. The present study investigates the effect of molecular crowding on DNA polymerase activity using polyethylene glycol PEG of various molecular weights as a crowding agent. Polymerase activity assays under various conditions demonstrated that the activities of T7 and Taq DNA polymerases depend on the molecular weight and concentration of the crowding agent. Furthermore, equilibrium and kinetic analyses demonstrated that the binding affinity and catalytic activity of the polymerase increase and decrease, respectively, with increasing PEG concentrations. Based on quantitative parameters of the polymerase reactions, we improved the efficiency of PCR amplification under conditions of molecular crowding. These results suggest that quantitative measurements of biomolecular structure and function are useful for understanding the behavior of biomolecules in vivo and for biotechnology applications in vitro.
Image de-noising of a metal matrix composite microstructure using Sure-let wavelet and weighted bilateral filter

Analysis of material microstructure images have been an important research topic. In fact, multiple pertinent information can be extracted from material texture images such as inclusions, fraction surfaces, heterogeneous components, crystallographic planes orientation, porosity and so on. Actually, this information depends from the amount of noise included in the image. Thus, it is very important to enhance methods exploited for image de-nosing in such cases. In fact, images issued from scanned electronic microscopy as well as computed tomography are used in multiple security applications such as baggage screening and in the encrypted domain, it used to protect privacy of outsourced data in cloud computing. In this paper, we propose a comparative study between two popular techniques used in image de-noising that are; Sure-let wavelet technique and weighted bilateral filtering. Our goal is to grasp the versatility of those methods in de-noising microstructure composite material images. Results of both outputs are well discussed. In our case, we found that sure-let wavelet de-noising gives better output results quantitatively and qualitatively.
Concepts and diagram elements for architectural knowledge management

Capturing architectural knowledge is very important for the evolution of software products. There is increasing awareness that an essential part of this knowledge is in fact the very process of architectural reasoning and decision making, and not just its end results. Therefore, a conceptual framework is needed that provides support for the process of architectural reasoning and making decisions. In this paper we introduce diagrams that advance existing achievements, address observed problems, and capture known insights in order to facilitate the process of architectural reasoning and its documentation, and in that way provide support for processes such as e.g. product evolution, architecture evaluation, and change impact analysis. An approach to architectural knowledge management is proposed in which a software architecture is modeled by a set of architectural reasoning diagrams, where each diagram is composed of several layers and addresses certain aspects of the system. These diagrams supplement existing ways to capture architecture descriptions, they share a set of common elements, and capture design decisions, their motivations and dependencies. A metamodel is given that defines those common elements and also defines the dependencies that exist between these elements both within and between layers. The proposed concepts and diagrams are illustrated on a software architecture for a component-based framework that needs to satisfy a given set of requirements and to address concerns of particular stakeholders.
A study on LVCSR and keyword search for tagalog

We describe a state-of-the-art large vocabulary continuous speech recognition (LVCSR) and keyword search (KWS) sys-tem trained on roughly 70 hours of conversational telephone speech. Using the Kaldi speech recognition toolkit, we investigate several aspects: for the acoustic front-end, we analyze the use of mel-frequency cepstral coefﬁcients (MFCC), pitch and probability-of-voicing (PoV), and deep neural network (DNN) bottleneck (BN) features, as well as their feature-level combination (“tandem”). For the acoustic-phonetic decision tree, we explore different hidden Markov model (HMM) topologies for the glottalization phoneme /? / to model its typically short duration. For the acoustic model, we compare regular continuous HMM with a sort of multi-codebook subspace Gaussian mixture model (SGMM) that lead to an overall best word error rate (WER) of 58.7% and 56.3%, respectively. The KWS is implemented as a word lattice search, and is augmented by a syllable lattice back-up search to capture out-of-vocabulary keywords as well as misrecognized lexical surface forms due to ambiguous preﬁx and hyphenation rules.
Characterization of the Mantle Transcriptome of Yesso Scallop (Patinopecten yessoensis): Identification of Genes Potentially Involved in Biomineralization and Pigmentation

The Yesso scallop Patinopecten yessoensis is an economically important marine bivalve species in aquaculture and fishery in Asian countries. However, limited genomic resources are available for this scallop, which hampers investigations into molecular mechanisms underlying their unique biological characteristics, such as shell formation and pigmentation. Mantle is the special tissue of P. yessoensis that secretes biomineralization proteins inducing shell deposition as well as pigmentation on the shells. However, a current deficiency of transcriptome information limits insight into mechanisms of shell formation and pigmentation in this species. In this study, the transcriptome of the mantle of P. yessoensis was deeply sequenced and characterized using Illumina RNA-seq technology. A total of 86,521 unique transcripts are assembled from 55,884,122 reads that passed quality filters, and annotated, using Gene Ontology classification. A total of 259 pathways are identified in the mantle transcriptome, including the calcium signaling and melanogenesis pathways. A total of 237 unigenes that are homologous to 102 reported biomineralization genes are identified, and 121 unigenes that are homologous to 93 known proteins related to melanin biosynthesis are found. Twenty-three annotated unigenes, which are mainly homologous to calmodulin and related proteins, Ca2+/calmodulin-dependent protein kinase, adenylate/guanylate cyclase, and tyrosinase family are potentially involved in both biomineralization and melanin biosynthesis. It is suggested that these genes are probably not limited in function to induce shell deposition by calcium metabolism, but may also be involved in pigmentation of the shells of the scallop. This potentially supports the idea that there might be a link between calcium metabolism and melanin biosynthesis, which was previously found in vertebrates. The findings presented here will notably advance the understanding of the sophisticated processes of shell formation as well as shell pigmentation in P. yessoensis and other bivalve species, and also provide new evidence on gene expression for the understanding of pigmentation and biomineralization not only in invertebrates but also probably in vertebrates.
Fitting Spheres to Range Data From 3-D Imaging Systems

Two error functions used for nonlinear least squares (LS) fitting of spheres to range data from 3-D imaging systems are discussed: the orthogonal error function and the directional error function. Both functions allow unrestricted gradient-based minimization and were tested on more than 40 data sets collected under different experimental conditions (e.g., different sphere diameters, instruments, data density, and data noise). It was found that the orthogonal error function results in two local minima and that the outcome of the optimization depends on the choice of starting point. The centroid of the data points is commonly used as the starting point for the nonlinear LS solution, but the choice of starting point is sensitive to data segmentation and, for some sparse and noisy data sets, can lead to a spurious minimum that does not correspond to the center of a real sphere. The directional error function has only one minimum; therefore, it is not sensitive to the starting point and is more suitable for applications that require fully automated sphere fitting.
Load-aware reconfiguration of LTE-antennas dynamic cell-phone network adaptation using organic network control

The utilisation of cell phone networks increases continuously, especially driven by the introduction of new mobile services and smart phones. Network operators can follow two directions to deal with the problem: either install new hardware or increase the efficiency of the existing infrastructure. This paper presents a novel algorithm to improve the efficiency of current networks by allowing for a self-organised load-dependent reconfiguration of antennas. The algorithm is capable of identifying hotspot traffic, assigning this to a neighbouring cell, and learning the best strategy at runtime. This leads to a self-improving intelligent control mechanism. The simulation-based evaluation results demonstrate the potential benefit, while simultaneously keeping the hardware's deterioration at a comparable level.
Transcriptome Analysis Reveals Differential Splicing Events in IPF Lung Tissue

Idiopathic pulmonary fibrosis (IPF) is a complex disease in which a multitude of proteins and networks are disrupted. Interrogation of the transcriptome through RNA sequencing (RNA-Seq) enables the determination of genes whose differential expression is most significant in IPF, as well as the detection of alternative splicing events which are not easily observed with traditional microarray experiments. We sequenced messenger RNA from 8 IPF lung samples and 7 healthy controls on an Illumina HiSeq 2000, and found evidence for substantial differential gene expression and differential splicing. 873 genes were differentially expressed in IPF (FDR<5%), and 440 unique genes had significant differential splicing events in at least one exonic region (FDR<5%). We used qPCR to validate the differential exon usage in the second and third most significant exonic regions, in the genes COL6A3 (RNA-Seq adjusted pval = 7.18e-10) and POSTN (RNA-Seq adjusted pval = 2.06e-09), which encode the extracellular matrix proteins collagen alpha-3(VI) and periostin. The increased gene-level expression of periostin has been associated with IPF and its clinical progression, but its differential splicing has not been studied in the context of this disease. Our results suggest that alternative splicing of these and other genes may be involved in the pathogenesis of IPF. We have developed an interactive web application which allows users to explore the results of our RNA-Seq experiment, as well as those of two previously published microarray experiments, and we hope that this will serve as a resource for future investigations of gene regulation in IPF.
Integer programming for combinatorial auction winner determination

Combinatorial auctions are important as they enable bidders to place bids on combinations of items. Compared to other auction mechanisms, they often increase the efficiency of the auction, while keeping low risks for bidders. However, the determination of an optimal winner combination in combinatorial auctions is a complex computational problem. In this paper we: 1) compare recent algorithms for winner determination to traditional algorithms; 2) present and benchmark a mixed integer programming approach to the problem, which enables very general auctions to be treated efficiently by standard integer programming algorithms (and hereby also by commercially available software); and 3) discuss the impact of the probability distributions chosen for benchmarking.
Coverage aspects of cooperative multi-hop line networks in correlated shadowed environment

We develop a stochastic model to characterize the effects of correlated shadow fading on a linear cooperative multi-hop wireless network. A one-dimensional network of equally-spaced nodes is considered, where a group of nodes transmits cooperatively to another group of nodes under large-scale fading effects. The transmission from one level to another is modeled as a Markov process and the transition probability matrix of the Markov chain is derived, which depends upon the underlying distribution of the received power. The received power is modeled as a log-normal random variable and its distribution is derived by using Fenton-Wilkinson's approach. The eigen-decomposition of the transition matrix provides insightful information about the network coverage and various other parameters. We quantify the values of signal-to-noise ratio margin required to get a desired coverage distance under a given quality of service and standard deviation of shadowing constraints. The accuracy of the model is validated by matching both the simulation and analytical results.