Miracle-dz/UniFAR-FTUs huggingface dataset:
New Detection Methods of DS-CDMA Signal at Lower SNR

D S-CDMA in the modern civil and military communications is widely used. Due to its low power spectral density, the DS-CDMA signal always floods in the background noise, bringing difficulties to the signal’s reconnaissance . Therefore, DS-CDMA signal detection has attracted attention of researchers. In this paper, the fourth-order moment chip (m4x(0,0,t) ) of DS-CDMA signal s is derived, against the background of Gaussian white noise, and get the conclusion that (m4x(0,0,t) can suppress Gaussian white noise. In order to reduce the estimation error of (m4x(0,0,t) , the quadratic fourth-order moment chip is proposed and finally t wo detection method s based on the quadratic fourth-order moment chip of DS-CDMA are proposed. Experimental results show that the detection performance of the method s is better than that of the double frequency method, spectrum-reprocessing method and cepstrum method. When the false alarm probability is 1%, the detection probability of presented methods reaches above 90% at SNR -2 2 d B .
Wide Coverage Symbolic Surface Realization

Recent evaluation techniques applied to corpus-based systems have been introduced that can predict quantitatively how well surface realizers will generate unseen sentences in isolation. We introduce a similar method for determining the coverage on the Fuf/Surge symbolic surface realizer, report that its coverage and accuracy on the Penn TreeBank is higher than that of a similar statistics-based generator, describe several benefits that can be used in other areas of computational linguistics, and present an updated version of Surge for use in the NLG community.
Ranking Technique to Improve Diversity in Recommender Systems

The role E-marketing became important in everyday life. To help them to give correct products to human users, Recommender Systems have been evolved. It helps to find products related to user’s interest. Mostly these systems employ collaborative filtering technique through which like minded users can be found. The key challenge is to attain quality in recommendations namely accuracy, diversity, novelty etc. Major algorithms have been focused on improving accuracy but diversity is important to have qualitative recommendations. On achieving diversity, distinct categories of items are taken for giving recommendations. Coverage is the main metric here. This paper gives one way to increase diversity by using LCM (Linear time Closed item set Miner) version 2 and I-Tree (Item-set tree). Data mining techniques are widely used in Recommender systems.
H ∞ Control for Networked Control Systems Under Communication Constraints

This note studies the problem of stabilizing networked control systems (NCSs) over random time-delay channels. In order to reduce the negative influences of communication constraints including signal transmission delay, data packet dropout and quantization effect, a new method on the H∞ controller design is presented. The proof techniques rely on Lyapunov function and linear matrix inequality (LMI) tools. The simulation results illustrate the effectiveness of the proposed method. Keywords-networked control systems (NCSs); time delay; data packet dropout; quantization;
Lactobacillus helveticus: the proteolytic system

Lactobacillus helveticus is one of the species of lactic acid bacteria (LAB) most commonly used in the production of fermented milk beverages and some types of hard cheese. The versatile nature of this bacterium is based on its highly efficient proteolytic system consisting of cell-envelope proteinases (CEPs), transport system and intracellular peptidases. Besides use of L. helveticus in cheese processing, the production of fermented milk preparations with health promoting properties has become an important industrial application. Studies have shown that fermented dairy products are able to decrease blood pressure, stimulate the immune system, promote calcium absorption, and exert an anti-virulent effect against pathogens. These beneficial effects are produced by a variety of peptides released during the hydrolysis of milk proteins by the proteolytic system of L. helveticus, which provides the bacterium with its nutritional requirements for growth. In recent years, studies have focused on understanding the factors that affect the kinetics of milk protein hydrolysis by specific strains and have concentrated on the effect of pH, temperature, growth phase, and matrix composition on the bacterial enzymatic system. This review focuses on the role of the proteolytic system of L. helveticus in the production of bioactive compounds formed during fermentation of dairy products. Taking advantage of the powerful proteolytic system of this bacterium opens up future opportunities to search for novel food-derived compounds with potential health promoting properties.
Albumin Kinetics in Patients Undergoing Major Abdominal Surgery

Background The drop in plasma albumin concentration following surgical trauma is well known, but the temporal pattern of the detailed mechanisms behind are less well described. The aim of this explorative study was to assess changes in albumin synthesis and transcapillary escape rate (TER) following major surgical trauma, at the time of peak elevations in two well-recognized markers of inflammation. Methods This was a clinical trial of radiolabeled human serum albumin for the study of TER and plasma volume. Ten patients were studied immediately preoperatively and on the 2nd postoperative day after major pancreatic surgery. Albumin synthesis rate was measured by the flooding dose technique employing incorporation of isotopically labelled phenylalanine. Results Fractional synthesis rate of albumin increased from 11.7 (95% CI: 8.9, 14.5) to 15.0 (11.7, 18.4) %/day (p = 0.027), whereas the corresponding absolute synthesis rate was unchanged, 175 (138, 212) versus 150 (107, 192) mg/kg/day (p = 0.21). TER was unchanged, 4.9 (3.1, 6.8) %/hour versus 5.5 (3.9, 7.2) (p = 0.63). Plasma volume was unchanged but plasma albumin decreased from 33.5 (30.9, 36.2) to 22.1 (19.8, 24.3) g/L. (p<0.001). Conclusion Two days after major abdominal surgery, at the time-point when two biomarkers of generalised inflammation were at their peak and the plasma albumin concentration had decreased by 33%, we were unable to show any difference in the absolute synthesis rate of albumin, TER and plasma volume as compared with values obtained immediately pre-operatively. This suggests that capillary leakage, if elevated postoperatively, had ceased at that time-point. The temporal relations between albumin kinetics, capillary leakage and generalised inflammation need to be further explored. Trial Registration clinicaltrialsregister.eu: EudraCT 2010-08529-21 ClinicalTrials.gov NCT01194492
StoRM: A Stochastic Recognition and Mining processor

Recognition and Mining applications are becoming prevalent across the entire spectrum of computing platforms, and place very high demands on their capabilities. We propose a Stochastic Recognition and Mining processor (StoRM), which uses Stochastic Computing (SC) to efficiently realize computational kernels from these domains. Stochastic computing facilitates compact, power-efficient realization of arithmetic operations by representing and processing information as pseudo-random bit-streams. However, the overhead of conversion between representations, and the exponential relationship between precision and bit-stream length, are key challenges that limit the efficiency of stochastic designs. The proposed architecture for StoRM consists of a 2D array of Stochastic Processing Elements (StoPEs) with a streaming memory hierarchy, enabling binary-to-stochastic conversion to be amortized across rows or columns of StoPEs. We propose vector processing and segmented stochastic processing in the StoPEs to mitigate the unfavorable tradeoff between precision and bit-stream length. We also exploit the compactness of StoPEs to increase parallelism, thereby improving performance and energy efficiency. Finally, leveraging the resilience of RM applications to approximations in their computations, we design StoRM to support modulation of the stochastic bit-stream length, and utilize this capability to to optimize energy for a desired output quality. StoRM achieves 2-3X energy-delay improvements over a conventional design without sacrificing output quality, and upto 10X (20X) improvements when upto 5% (10%) loss in output quality is allowed. Our results also demonstrate that the proposed design techniques greatly enhance the applicability and benefits of stochastic computing.
Patient-to-Patient Transmission of Hepatitis C at Iranian Thalassemia Centers Shown by Genetic Characterization of Viral Strains

Background Hepatitis C is prevalent among thalassemia patients in Iran. It is mainly transfusion mediated, in particular among patients treated before 1996 when blood screening was introduced. Objectives The current study aimed to investigate why patients still seroconvert to anti-HCV in Iranian thalassemia centers. Patients and Methods During 2006-2007 sera were sampled from 217 anti-HCV positive thalassemia patients at nine thalassemia centers in Tehran and Amol city, where 34 (16%) patients had been infected after 1996. The HCV subtype could be determined by sequencing and phylogenetic analysis of partial NS5B and/or 5׳NCR-core region in 130 strains. Results 1a (53%) was predominant followed by 3a (30%), 1b (15%), and one strain each of 2k, 3k and 4a. Phylogenetic analysis revealed 19 clades with up to five strains diverging with less than six nucleotides from each other within subtypes 1a and 3a. Strains in seven clades were from nine patients infected between 1999 and 2005 and similar to strains from eight patients infected before 1996, indicating ongoing transmission at the centers. Further epidemiological investigation revealed that 28 patients infected with strains within the same clade had frequently been transfused at the same shift sitting on the same bed. An additional eight patients with related strains had frequently been transfused simultaneously in the same room. Conclusions The results suggest nosocomial transmission at these thalassemia centers both before and after the introduction of blood screening. Further training of staff and strict adherence to preventive measures are thus essential to reduce the incidence of new HCV infections.
HIT2 Joint NLP Lab at the NTCIR-9 Intent Task

report hereby is to represent the principle, the searching process and experiment results. We report our systems and experiments in the intent task of NTCIR 9. The research aims at evaluating the effectiveness of the proposed methods on query intent mining and results diversification in terms of web search. In the subtopic mining subtask, we combine the extracted candidates from search logs and Wikipedia. An improvement could be seen after incorporating query intents from different resources. In the document ranking subtask, greedy algorithms are taken to select documents with the high diversified score and return a re-ranked list of diversified documents based on query subtopics. The experiment results show that the method, that is combining subtopic results directly, outperforms MMR.
An Approach to Workflow Scheduling using Priority in Cloud Computing Environment

Cloud Computing delivers computing resources as a service over a network (Internet) to the customers. The tasks or jobs of the users would require to be executed in a particular order to complete the whole task. Workflow scheduling manages the execution of the inter-dependent tasks on the distributed resources. Workflow scheduling algorithms are used to allocate the resources to workflow tasks in a manner that preserves the dependency constraints. At the same time, the tasks must be scheduled efficiently in order to minimize the execution time as well as cost incurred in using the heterogeneous resources of the cloud. This paper proposes a multiple criteria decision making model for scheduling tasks based on priority and cost.
Electroencephalographic detection of visual saliency of motion towards a practical brain-computer interface for video analysis

Though Electroencephalography (EEG)-based brain-computer interfaces (BCI) have come to outperform pure computer vision algorithms on difficult image triage tasks, none of these BCIs have leveraged the effects of motion on the human visual attention system. Here we consider the advantages of leveraging the effects of motion by testing a new method for EEG-based target detection using Rapid Serial Visual Presentation (RSVP) of short moving image clips. Comparatively, canonical methods present the operator with still images only. Our experiments show that presenting moving images in RSVP instead of still images significantly increases performance (p < 0.0005). In addition, we investigate the effect of increasing target load in RSVP of moving image clips and find some support for the hypothesis that detection will decrease as target load is increased.
Towards a micro-blog platform for sensing and easing adolescent psychological pressures

Adolescent mental health cannot be ignored, and psychological pressure is one of the prominent problems of current teenagers. Micro-blog, as the most important information exchange and broadcast tool in the current society, is becoming an important channel for teenagers' information acquisition, inter-interaction, self-expression, emotion release due to its unique equality, freedom, fragmentation, individuality characteristics. This poster envisions a micro-blog platform, aiming to (1) sense psychological pressures through teenagers' tweets, and (2) assist teenagers to release their stress through micro-blog. A method for timely detecting psychological pressures from teenagers' tweets is particularly described. Our preliminary experimental results on real data demonstrate the validity of the approach. We also discuss ways to assist teenagers to release their pressures through micro-blog at the end of the poster.
Growth of Intermediate-Mass Black Holes in the Hierarchical Formation of Small Spiral Galaxies in the High-z Universe

Combining a theoretical model of mass accretion onto a galactic center with a high-resolution N-body/smoothed particle hydrodynamics (SPH) simulation, we investigate the formation of an intermediate-mass black hole (IMBH) during the hierarchical formation of a small spiral galaxy (with a total mass of 1010 M☉) in the high-z universe. We found that the rate of average mass accretion to the nucleus due to the radiation drag exerted by newly formed stars in the forming galaxy is ≈10-5 M☉ yr-1. As a result of this accretion, an IMBH with ≈104 M☉ can be formed in the center of the spiral galaxy at z ~ 4. We found that a central BH coevolves with the dark matter halo from z ~ 15 to 2. The mass ratio of the BH to the dark matter halo is nearly constant, ≈(1-3) × 10-6 from z ~ 10 to 2. This is because change in the dark matter potential enhances star formation in the central part of the galaxy, and as a result the BH evolves due to mass accretion via the radiation drag. Therefore, our model naturally predicts a correlation between massive BHs and dark matter halos. Moreover, it is found that the final BH-to-bulge mass ratio (≈5 × 10-5) in a small spiral galaxy at high-z is much smaller than that in the large galaxies (≈10-3). Our results also suggest that the scatter in the observed scaling relations between the bulge mass and black hole mass are caused by a time lag between BH growth and growth of the bulge mass. We also predict that the X-ray luminosity of active galactic nuclei (AGNs) is positively correlated with the CO luminosity in the central region. By comparing our results with the properties of Lyman break galaxies (LBGs), it is predicted that some LBGs have massive BHs of ≈106-107 M☉.
State estimation for optimal control of a nonlinear system

Two estimation techniques, the extended Kalman filter (EKF) and the iterative extended Kalman filter (IEKF), have been applied to a nonlinear time-varying system that has nonmeasurable state variables. An iterative solution to a fed-batch fermentation process is reported using the EKF based on measurements of the oxygen and carbon dioxide concentrations. The results demonstrate that this estimation technique can be successfully applied to complex biological processes. If the nonlinearities of these systems are sufficiently important or if a long delay in the estimation cannot be permitted for a particular process, then the IEKF can be selected. <<ETX>>
Mining user browsing pattern based on representative set

Web log contains large volume of user browsing information. How to mine user browsing patterns is an important research topic. On the analysis of the present algorithms for mining user interests, user-interest can be used for mining user browsing patterns. In order to cluster overlapping objects effectively, a new concept-Cut Plane is introduced. And for achieving reasonable and acceptable running speed, representative set is presented too. On all of these foundations, RSBUBP (Representative Set Based User Browsing Patterns) algorithm is proposed. Experiments showed that it was accurate and scalable. It's suitable for application in E-business, such as to optimize Web site or to design personalized service.
Beyond Chomsky versus Skinner: frequency, language processing and aphasia

The background for this special issue of Aphasiology on Frequency, Language Processing and Aphasia reaches nearly 60 years into the past. In 1959, Chomsky, critiquing Skinner’s Verbal Behavior, deployed an explosive set of arguments against the behaviourist analysis of language (Chomsky, 1959, 1967). Linguists in increasing numbers lined up behind Chomsky’s powerful contentions, and the overall effects were far-reaching. But because behaviourism invoked frequency and probability as explanations and as measures, linguists (who had none of our present tools for getting good numerical information about linguistic events), in endorsing Chomsky, seem to have been convinced for many years that because frequency could not explain everything, it could not explain ANYTHING. Other differences also divided most linguists from most psychologists interested in language (Ervin-Tripp & Slobin, 1966), even after the “cognitive revolution” in psychology (Miller, 2003) was well underway and behaviourismhad become history—in particular, psycholinguists attempting to test claims of linguistic theories often found it impossible to keep up with the relatively rapid evolution of those theories, so most of us just gave up on testing linguists’ claims and set about trying to understand sentence production and comprehension on our own. By now, most sub-areas of linguistics and psycholinguistics have rather different goals and different criteria for what constitutes progress towards them. Linguistics wants the “best” description of synchronic grammar (where what “best” means might be “most parsimonious grammar” or “most intuitively satisfying description of data from the largest number of languages” or something in between). And in general, linguists remain much more concerned with the mental representation of linguistic structures than how they are processed by speakers and hearers. Psycholinguistics, on the other hand, wants descriptions of human language processing that give the best approximation of people’s responses to a large range of processing demands, over a full range of populations. The importance of this difference will be evident from the papers in this special issue. One major implication of the work reported here is that psycholinguistics can and should look at the effects of a large set of potentially relevant variables rather than being constrained to considering just the variables that are sanctioned by particular linguistic theories. The variables discussed in this issue include (1) various kinds of morphological and lexical frequency measures—see Bastiaanse, Wieling, and Wolthuis; Baayen, Milin, and Ramscar; (2) expectedness/surprisal/conditional frequency—see Gahl and Menn; Gibson, Sandberg, Bergen, Fedorenko, and Kiran; Van Ewijk and Avrutin and (3) age of acquisition—see Brysbaert and Ellis; Baayen et al. A second major implication is that because of the brain’s capacity for both parallel processing and top-down processing, psycholinguistics is not constrained to the linear APHASIOLOGY, 2016 VOL. 30, NO. 11, 1169–1173 http://dx.doi. org/10.1080/02687038.2016. 1168920
Ju n 20 07 Black holes thermodynamics to all order in the Planck length in extra dimensions

We investigate the effects to all orders in the Planck length, from a generalized uncertainty principle, on the thermodynamic parameters of radiating Schwarzschild black holes in a scenario with large extra dimesions. We show that black holes in this framework are hotter, decay faster and are less classical objects. Particularly, we show that the final stage of the radiation process is a black hole remnant with zero entropy, zero heat capacity and non zero finite temperature. We finally compare our results with the ones obtained in the standard Hawking picture and with the generalized uncertainty principle to leading order in the Planck length. Black holes thermodynamics to all order in the Planck length in extra dimensions 2
Retrieval of multimedia stimuli with semantic and emotional cues: Suggestions from a controlled study

The ability to efficiently search pictures with annotated semantics and emotion is an important problem for Human-Computer Interaction with considerable interdisciplinary significance. Accuracy and speed of the multimedia retrieval process depends on the chosen metadata annotation model. The quality of such multifaceted retrieval is opposed to the potential complexity of data setup procedures and development of multimedia annotations. Additionally, a recent study has shown that databases of emotionally annotated multimedia are still being predominately searched manually which highlights the need to study this retrieval modality. To this regard we present a study with N = 75 participants aimed to evaluate the influence of keywords and dimensional emotions in manual retrieval of pictures. The study showed that if the multimedia database is comparatively small emotional annotations are sufficient to achieve a fast retrieval despite comparatively lesser overall accuracy. In a larger dataset semantic annotations became necessary for efficient retrieval although they contributed to a slower beginning of the search process. The experiment was performed in a controlled environment with a team of psychology experts. The results were statistically consistent with validates measures of the participants' perceptual speed.
JP Albar domains with their structural distribution Selection of antibody probes to correlate protein sequence

We propose a new approach that permits correlation of specific domains defined by their primary sequence with their location in the structure of complex macromolecular aggregates. It is based on the combination of well-established structural analysis methods that incorporate the use of overlapping peptides on cellulose membranes for the isolation and purification of specific antibodies from a polyclonal antiserum. Monospecific antibodies to the connector protein of bacteriophagef29 were isolated from polyclonal antisera using a new development of the spotscan method. These antibodies can be purified in quantities that allow antigenicity testing in enzyme-linked immunosorbent assays, Western blotting and immunoprecipitations, demonstrating the specificity of this isolation procedure. This approach has allowed us to generate direct antibody probes for immunoelectron microscopy mapping of different connector protein domains in a low resolution three-dimensional epitope map.