Miracle-dz/UniFAR-FTUs huggingface dataset:
An Energy-Balanced Variable Range Transmission Scheme in Wireless Sensor Networks

Prolonging the network lifetime is one of design challenges for data transmission in wireless sensor networks(WSNs) which are affected by the energy sink-hole problem. Recent researches show the energy sink-hole problem can be overcome by balancing the sensor energy consumptions. In this paper, we present an energy-balanced consumption scheme by varying the transmission ranges of sensors in a circular WSNs. In our scheme, the circular field is sliced into K concentric circular bands with different widths, the sensors deliver its data to the sink with a range of the band width in a hop-by-hop mode. The analysis shows that to keep energy-balanced consumption the widths of the bands can be determined only by the first band (the inner band) width. To meet the constraints of fixed circular network radius, a binary search algorithm has been designed for searching the first band width. Numerical results show that the band widths should become wide with its distance to the sink increasing in order to guaranteing the energy-balanced consumption. It is also shown that there is an optimal band number to minimize the total energy consumption, which is proportional to the network circular radius, that is there is an optimal average band width.
Pathogen evolution across the agro-ecological interface: implications for disease management

Infectious disease is a major causal factor in the demography of human, plant and animal populations. While it is generally accepted in medical, veterinary and agricultural contexts that variation in host resistance and pathogen virulence and aggressiveness is of central importance to understanding patterns of infection, there has been remarkably little effort to directly investigate causal links between population genetic structure and disease dynamics, and even less work on factors influencing host–pathogen coevolution. The lack of empirical evidence is particularly surprising, given the potential for such variation to not only affect disease dynamics and prevalence, but also when or where new diseases or pathotypes emerge. Increasingly, this lack of knowledge has led to calls for an integrated approach to disease management, incorporating both ecological and evolutionary processes. Here, we argue that plant pathogens occurring in agro‐ecosystems represent one clear example where the application of evolutionary principles to disease management would be of great benefit, as well as providing model systems for advancing our ability to generalize about the long‐term coevolutionary dynamics of host–pathogen systems. We suggest that this is particularly the case given that agro‐ecological host–pathogen interactions represent a diversity of situations ranging from those that only involve agricultural crops through to those that also include weedy crop relatives or even unrelated native plant communities. We begin by examining some of the criteria that are important in determining involvement in agricultural pathogen evolution by noncrop plants. Throughout we use empirical examples to illustrate the fact that different processes may dominate in different systems, and suggest that consideration of life history and spatial structure are central to understanding dynamics and direction of the interaction. We then discuss the implications that such interactions have for disease management in agro‐ecosystems and how we can influence those outcomes. Finally, we identify several major gaps where future research could increase our ability to utilize evolutionary principles in managing disease in agro‐ecosystems.
Prediction of Transformer Insulation Life with an Effect of Environmental Variables

The Hot Spot Temperature (HST) value depends on the ambient temperature, the rise in the top oil temperature (TOT) over the ambient temperature, and the rise in the winding HST over the top oil temperature. In this paper a new semi-physical model comprising of the environmental variables for the estimation of HST and loss of insulation life in transformer is proposed. The winding hot-spot temperature can be calculated as a function of the top-oil temperature that can be estimated using the transformer loading data, top oil temperature lagged regressor value, ambient temperature, wind velocity and solar heat radiation effect. The estimated HST is compared with measured data of a power transformer in operation. The proposed model has been validated using real data gathered from a 100 MVA power transformer. General Terms Power Transformer, Ambient Temperature.
Power-efficient computing for compute-intensive GPGPU applications

The peak compute performance of GPUs has been increased by integrating more compute resources and operating them at higher frequency. However, such approaches significantly increase power consumption of GPUs, limiting further performance increase due to the power constraint. Facing such a challenge, we propose three techniques to improve power efficiency and performance of GPUs in this paper. First, we observe that many GPGPU applications are integer-intensive. For such applications, we combine a pair of dependent integer instructions into a composite instruction that can be executed by an enhanced fused multiply-add unit. Second, we observe that computations for many instructions are duplicated across multiple threads. We dynamically detect such instructions and execute them in a separate scalar unit. Finally, we observe that 16 or fewer bits are sufficient for accurate representation of operands and results of many instructions. Thus, we split the 32-bit datapath into two 16-bit datapath slices that can concurrently issue and execute up to two such instructions per cycle. All three proposed techniques can considerably increase utilization of compute resources, improving power efficiency and performance by 20% and 15%, respectively.
Findings with 0.25 mg Dexamethasone Suppression Test in Eating Disorders: Association with Childhood Trauma

ABSTRACT Introduction: While both blunted and enhanced cortisol suppression following a dexamethasone suppression test (DST) are described in eating disorders, some evidence suggests that enhanced cortisol suppression might be associated with the presence of trauma history. The objective of this study is to investigate hypothalamic-pituitary-adrenal axis response to a modified DST in eating disorders and its relationship with childhood trauma. Methods: Fifty-two patients with eating disorders were studied with a 0.25 mg DST and with measures of childhood trauma. Conclusion: Patients with bulimia symptoms had significantly greater cortisol suppression than controls and restrictive anorexia patients (F=8.2, P<.05). Cortisol suppression was significantly correlated with intensity of childhood traumatic events (F=0.32, P<.05). Hypersensitive hypothalamic-pituitary-adrenal axis response to DST in eating disorders may be related with a history of childhood trauma and suggests some biological similarities with posttraumatic syndromes that should be further explored.
Holoentropy enabled-decision tree for automatic classification of diabetic retinopathy using retinal fundus images

Abstract Diabetic retinopathy (DR) is the most common diabetic eye disease. Doctors are using various test methods to detect DR. But, the availability of test methods and requirements of domain experts pose a new challenge in the automatic detection of DR. In order to fulfill this objective, a variety of algorithms has been developed in the literature. In this paper, we propose a system consisting of a novel sparking process and a holoentropy-based decision tree for automatic classification of DR images to further improve the effectiveness. The sparking process algorithm is developed for automatic segmentation of blood vessels through the estimation of optimal threshold. The holoentropy enabled decision tree is newly developed for automatic classification of retinal images into normal or abnormal using hybrid features which preserve the disease-level patterns even more than the signal level of the feature. The effectiveness of the proposed system is analyzed using standard fundus image databases DIARETDB0 and DIARETDB1 for sensitivity, specificity and accuracy. The proposed system yields sensitivity, specificity and accuracy values of 96.72%, 97.01% and 96.45%, respectively. The experimental result reveals that the proposed technique outperforms the existing algorithms.
Microfluidic-assisted synthesis and release properties of multi-domain polymer microparticles drug carriers

Characteristics and release properties of drug loaded microparticles depend upon material used and choice of production method. Conversely to most of the conventional ones, microfluidic methods give an edge by improving the control over droplet generation, size and size distribution. Capillary-based microfluidic devices were successfully used to obtain monodisperse drug(s) loaded microbeads, janus, core-shell and trojan particles using UV initiated free radical polymerization while keeping activity of active loaded molecules. These devices can be assembled in a short period of time and a slight change in design gives completely different microparticles morphologies. These particles were developed with the aim to address different issues experienced in oral drug delivery. For instance microbeads can be used to deliver NASIDs in a sustained release manner while janus particles can release two APIs with completely different properties (solubility, compatibility) also in a sustained release manner. Core-shell particles were designed to target colonic region of human intestine for dual drug delivery. Trojan particles were synthesized in a new semi-continuous microfluidic process, thus improving nanoparticles safety handling and release in simulated gastric fluid. Each system was fully characterized to insure batch to batch consistency and reproducibility. In general, the release of active ingredients was controlled by tuning the operating and material parameters like phases flow rates, nature and concentration of drug, (co)monomers, surfactant and crosslinker, pH of release media with the result of different particle morphologies, sizes and shapes or matrix crosslinking density.
A Cognitive Learning Perspective on Encoding and Decoding E-mails

The high e-mail amounts that individuals sent back and forth each day are one of the major causes for information overload. Knowledge seems to help overcoming information overload. However, it is not clear which knowledge areas are helpful. Therefore, we examine knowledge areas supporting the encoding and decoding of e-mails by investigating cognitive processes that allow knowledge building to avoid e-mail induced information overload. A novel theoretical perspective is developed which draws on knowledge as acquired schemas which allows bypassing working memory through automation. We employed a case study design which results in a conceptual model relating three knowledge areas: (1) channel knowledge, (2) message topic knowledge, and (3) communication partner knowledge. By drawing on cognitive load theory, we explain how these knowledge areas allow the reduction of e-mail induced cognitive load as a conceptualization of information overload.
A minimum-delay-difference method for mitigating cross-traffic impact on capacity measurement

The accuracy and speed of path capacity measurement could be seriously affected by the presence of cross traffic on the path. In this paper, we propose a new cross-traffic filtering method called minimum delay difference (MDDIF). Unlike the classic packet-pair dispersion techniques, the MDDIF method can obtain accurate capacity estimate from the minimal possible delay of packets from different packet pairs. We have proved that the MDDIF method is correct and that it takes less time to obtain accurate samples than the minimum delay sum (MDSUM) method. We also present analytical and measurement results to evaluate the MDDIF method and to compare its performance with the MDSUM method.
Tuning MAX – MIN Ant System with off-line and on-line methods

In this paper, we study two approaches for tuning parameters of optimization algorithms: off-line and on-line tuning. The goal of tuning is to find an appropriate configuration of an algorithm, where a configuration is a specific setting of all parameters. In off-line tuning, the appropriate configuration is chosen after a preliminary phase. In on-line tuning, the configuration might be changed during the solution process to adapt to the instance being solved and possibly to the state of the search. Parameter tuning is very important in swarm intelligence: the performance of many techniques is strongly influenced by the configuration chosen. In this paper, we study the performance of MAX–MIN Ant System when its parameters are tuned off-line and when they are tuned on-line. We consider one off-line and five on-line methods, and we tackle two combinatorial optimization problems. The results show that off-line tuning generally outperforms on-line tuning. In some cases, on-line tuning achieves better results than off-line tuning, but the best on-line method is not always the same.
Combination of biological screening in a cellular model of viral latency with virtual 1 screening identifies novel compounds that reactivate HIV-1 2 3 Short title : HIV reactivation from latency by MMQO 4 5

word count: 211 26 Text word count: 7,242 27 28 # Present address: Department of Cell Biology, Immunology and Neurosciences, Faculty of Medicine, University of Barcelona, Barcelona, Spain. Copyright © 2012, American Society for Microbiology. All Rights Reserved. J. Virol. doi:10.1128/JVI.05972-11 JVI Accepts, published online ahead of print on 18 January 2012 on July 2, 2017 by gest http/jvi.asm . rg/ D ow nladed fom
Molecular cloning and transcriptional regulation of ompT, a ToxR‐repressed gene in Vibrio cholerae

In pathogenic Vibrio cholerae, at least 17 genes are co‐ordinately regulated by ToxR. Most of these genes, including those that encode cholera toxin (CT), toxin co‐regulated pilus (TCP), accessory colonization factor (ACF) and OmpU, are positively regulated. OmpT is the only identified protein under negative regulation of ToxR. To understand the molecular mechanism by which ToxR represses OmpT expression, we cloned ompT and characterized the ompT promoter and its interaction with ToxR. Sequence analysis revealed that ompT encodes a predicted 35.8 kDa outer membrane porin of V. cholerae. Primer extension analysis identified a transcriptional start site 104 bp upstream of the translational start codon. Both primer extension analysis and promoter fusion studies showed that ToxR represses OmpT expression at the transcriptional level. Promoter fusion studies also suggest that cyclic AMP receptor protein (CRP) is involved in ompT activation. Gel mobility shift assays combined with DNase I footprinting analysis demonstrated that ToxR mediates repression of ompT transcription by directly binding to an A/T‐rich region between −95 and −30 of the ompT promoter. To further understand how the interaction of ToxR with different promoters results in its function as an activator or repressor, we have also mapped the regions on the ctxAB and toxT promoters to which ToxR binds. The regions protected by ToxR on each of these promoters are all A/T rich and large in size, although they are positioned differently relative to each transcriptional start site.
Adaptive minimum-BER linear multiuser detection for DS-CDMA signals in multipath channels

The problem of constructing adaptive minimum bit error rate (MBER) linear multiuser detectors is considered for direct-sequence code division multiple access (DS-CDMA) signals transmitted through multipath channels. Based on the approach of kernel density estimation for approximating the bit error rate (BER) from training data, a least mean squares (LMS) style stochastic gradient adaptive algorithm is developed for training linear multiuser detectors. Computer simulation is used to study the convergence speed and steady-state BER misadjustment of this adaptive MBER linear multiuser detector, and the results show that it outperforms an existing LMS-style adaptive MBER algorithm presented by Yeh et al. (see Proc. Globecom, Sydney, Australia, p.3590-95, 1998).
Chloroform-sensing properties of plasmonic nanostructures using poly(methyl methacrylate) transduction layer

The design and development of a sensitive, fast and selective chloroform vapour sensor based on a poly(methyl methacrylate) (PMMA) transduction layer and a plasmonic nanostructures transducer is presented. The PMMA layer swelled when it was in exposure to the vapours, which would in turn bring in an extinction efficiency change in the localised surface plasmon resonance (LSPR) spectrum for triangular silver nanoprisms. The LSPR spectral response to chloroform and other vapours was measured by a UV-vis spectrometer in real time. Experiment results showed that the PMMA-LSPR sensor indicated a sensitivity of 4.76 x 10(-5) ppm(-1) and a detection limit of 21 ppm. A fast, stable and reversible response was observed during positive and negative test cycles upon variations of the environment in the gas cell between clean air and saturated chloroform contained air. The PMMA-LSPR sensor also showed good selectivity of chloroform when it was exposed to vapours with different functional groups. It has been demonstrated that plasmonic nanostructures coated with PMMA transduction films can be applied to chloroform sensing and vapour classifying applications.
Electronic Communications of the EASST Volume 33 ( 2010 ) Proceedings of the Fourth International Workshop on Foundations and Techniques for Open Source Software Certification ( OpenCert 2010 ) GUI Inspection from Source Code Analysis

Graphical user interfaces (GUIs) are critical components of today’s software. Given their increased relevance, the correctness and usability of GUIs are becoming essential. This paper describes the latest results in the development of our tool to reverse engineer the GUI layer of interactive computing systems. We use static analysis techniques to generate models of the user interface behavior from source code. Models help in graphical user interface inspection by allowing designers to concentrate on its more important aspects. One particular type of model that the tool is able to generate is state machines. The paper shows how graph theory can be useful when applied to these models. A number of metrics and algorithms are used in the analysis of aspects of the user interface’s quality. The ultimate goal of the tool is to enable analysis of interactive system through GUIs source code inspection.
An Interactive Segmentation Method Based on Superpixel

This paper proposes an interactive image-segmentation method which is based on superpixel. To achieve fast segmentation, the method is used to establish a Graphcut model using superpixels as nodes, and a new energy function is proposed. Experimental results demonstrate that the authors' method has excellent per- formance in terms of segmentation accuracy and computation efficiency compared with other segmentation algo- rithm based on pixels.
Intelligent Data Analysis and its challenges in big data environment

Intelligent Data Analysis (IDA) is one of the most important approaches in the field of data mining, which attracts great concerns from the researchers. Based on the basic principles of IDA and the features of datasets that IDA handles, the development of IDA is briefly summarized from three aspects, i.e., algorithm principle, the scale and type of the dataset. Moreover, the challenges facing the IDA in big data environment are analyzed from four views, including big data management, data collection, data analysis, and application pattern. It is also cleared that in order to extract more values from data, the further development of IDA should combine practical applications and theoretical researches together.
System Combination for Machine Translation Based on Text-to-Text Generation

In this paper, we introduce a novel translation system combination framework using a text-to-text generation technique. We are motivated by the observation that for many translation sentences, some of their constituents may be poorly translated, while others may be well translated. Moreover, it is often the case that other systems can provide good alternatives to problematic constituents. In our approach, the system constructs paraphrase lattices representing all possible hypotheses for the same source sentence. We then use a text-to-text generator operating on those lattices to generate those hypotheses. We filter ungrammatical combinations using a feature-based lexical-ized tree adjoining grammars (FB-LTAG) and then use a TER-based metric to compute a consensus score function to select the best translation among grammatical hypotheses. The system combination gains 1.38 BLEU points over the best individual system.
Evolution of Sphingomonad Gene Clusters Related to Pesticide Catabolism Revealed by Genome Sequence and Mobilomics of Sphingobium herbicidovorans MH

Abstract Bacterial degraders of chlorophenoxy herbicides have been isolated from various ecosystems, including pristine environments. Among these degraders, the sphingomonads constitute a prominent group that displays versatile xenobiotic-degradation capabilities. Four separate sequencing strategies were required to provide the complete sequence of the complex and plastic genome of the canonical chlorophenoxy herbicide-degrading Sphingobium herbicidovorans MH. The genome has an intricate organization of the chlorophenoxy-herbicide catabolic genes sdpA, rdpA, and cadABCD that encode the (R)- and (S)-enantiomer-specific 2,4-dichlorophenoxypropionate dioxygenases and four subunits of a Rieske non-heme iron oxygenase involved in 2-methyl-chlorophenoxyacetic acid degradation, respectively. Several major genomic rearrangements are proposed to help understand the evolution and mobility of these important genes and their genetic context. Single-strain mobilomic sequence analysis uncovered plasmids and insertion sequence-associated circular intermediates in this environmentally important bacterium and enabled the description of evolutionary models for pesticide degradation in strain MH and related organisms. The mobilome presented a complex mosaic of mobile genetic elements including four plasmids and several circular intermediate DNA molecules of insertion-sequence elements and transposons that are central to the evolution of xenobiotics degradation. Furthermore, two individual chromosomally integrated prophages were shown to excise and form free circular DNA molecules. This approach holds great potential for improving the understanding of genome plasticity, evolution, and microbial ecology.
Accelerated exposure tests as evaluation tool for estimating life of organic coatings on steel bridges

The present study performed accelerated exposure tests on 5 types of painting systems, which are commonly used for steel bridges in Japan, and discussed corrosion degradation from initial defects on the paintings. The structural steel plates were surface treated and painted conforming to the ‘Japanese painting manual’, and circular defects with 0·2, 1·0 and 2·0 mm in diameters reaching the steel substrate were created on each of the painted plate. The painted steels were exposed into an environmental testing chamber controlled by the S6 cycle test condition, which is a laboratory cyclic accelerated exposure test condition of spraying/wetting/drying, for up to 600 days. The corrosion degradation curve of the each painting system was evaluated based on rusting area from the circular defects, which was measured by using laser focus measuring instrument at 250 μm intervals. The proposed degradation curves were applied to evaluating remaining lifetime of the painted steels with initial defects to the future conditions. The evaluation procedure for field environments was also presented based on the acceleration coefficient of the S6 cycle tests and the amount of flying salt.