Miracle-dz/UniFAR-FTUs huggingface dataset:
GB Virus C infection in Patients With HIV/Hepatitis C Virus Coinfection: Improvement of the Liver Function in Chronic Hepatitis C

Background: Previous studies in patients with hepatitis C virus (HCV)/HIV coinfection have shown that the presence of GBV-C is associated with significantly less compensated and decompensated cirrhosis, and an improvement in cirrhosis-free survival. Objectives: This study aimed to describe the effect of GBV-C in patients with chronic hepatitis C and HIV coinfection. Patients and Methods: We retrospectively studied 105 injecting drug users with chronic hepatitis C and HIV coinfection and 72 patients with chronic HCV mono-infections. Plasma samples were tested for GBV-C RNA with primers to the 5’untranslated region gene. HIV and HCV viral load, CD4+ and CD8+ cell count, and the levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) were tested in all patients. Results: GBV-C RNA was identified in 34 (32.38%) of the patients with HIV/HCV coinfection, and in 24 (33.33%) of the patients with HCV mono-infection. GBV-C infection was associated with significantly lower ALT and AST levels in patients with chronic hepatitis C and HIV coinfection, but not in those HCV mono-infections. The presence of GBV-C infection was not correlated with CD4+ and CD8+ cell count, gender, age, HIV load, HCV load, and HCV genotype. Conclusions: This study found that GBV-C infection has a high frequency among injecting drug users with HIV/HCV coinfection and HCV mono-infection in Yunnan, China. In patients with chronic hepatitis C and HIV coinfection, GBV-C RNA was associated with significantly lower ALT and AST levels, suggesting a beneficial effect of GBV-C infection on chronic hepatitis C.
Optimal Operation of Climate Control Systems of Produce Storage Facilities in Smart Grids

This paper presents mathematical optimization models of produce storage facilities to optimize the operation of their energy systems in the context of smart grids. In the storage facilities, climate control of the storage rooms consumes considerable energy; thus, in this paper, a mathematical model of storage facilities appropriate for their optimal operation is developed, so that it can be implemented as a supervisory control in existing climate controllers. The proposed model incorporates weather forecasts, electricity price information, and the end-user preferences to optimally operate existing climate control systems in storage facilities. The objective is to minimize total energy costs and demand charges while considering important parameters of storage facilities, i.e., inside temperature and humidity should be kept within acceptable ranges. The performance of the proposed model for various electricity prices and weather conditions and their variations are studied via Monte Carlo Simulations (MCS). The presented simulation results show the effectiveness of the proposed model to reduce total energy costs while maintaining required operational constraints.
A Study on the Feasibility of Mobile Ad-Hoc Networks Applied to Foreign Objective Debris Detection System

Foreign Object Debris (FOD) on the runways or taxiways may damage airplanes and injure personnel in the airport. There are two main types of commercial FOD detection systems, i.e. Fixed and mobile. Nowadays, only one of these two main types of FOD detection systems is deployed in some airports. In this paper, we propose a total solution to support both of FOD detection system types based on Shanghai Hongqiao International Airport FOD prevention's requirements, i.e. Mobile Ad-Hoc Network (MANET) based FOD detection system. In this paper, a novel FOD detection system architecture is proposed. Then we study the feasibility of MANET applied to the proposed FOD detection system. In this proposed MANET, Wi-Fi and IEEE 802.11 are introduced to physical and MAC layer of wireless node, OLSR is used to provide network routing function, in addition, a novel multi-path data fusion mechanism is proposed to decrease the packet loss ratio.
Electronic data interchange

Electronic Data Interchange (EDI), a process to automate the exchange of information traditionally transmitted via trade documents, is examined. Trade documents include such administrative forms as: purchase orders, invoices, price lists, and bills of lading, among others. Currently, this type of information is transmitted by mail, courier, telephone or telex. The advantages of automating this information exchange are discussed. The major problem in accomplishing this automation is the total lack of consistency in end user document types, structure and format. This is compounded by the variety of data storage techniques and equipment, and the availability of suitable communication networks. Progress in overcoming these obstacles is outlined, with examples, for a publicly available electronic data interchange service.
Algebraic reputation model RepRank and its application to spambot detection

Due to popularity surge social networks became lucrative targets for spammers and guerilla marketers, who are trying to game ranking systems and broadcast their messages at little to none cost. Ranking systems, for example Twitter's Trends, can be gamed by scripted users also called bots, who are automatically or semi-automatically twitting essentially the same message. Judging by the prices and abundance of supply from PR firms this is an easy to implement and widely used tactic, at least in Russian blogosphere. Aggregative analysis of social networks should at best mark those messages as spam or at least correctly downplay their importance as they represent opinions only of a few, if dedicated, users. Hence bot detection plays a crucial role in social network mining and analysis. In this paper we propose technique called RepRank which could be viewed as Markov chain based model for reputation propagation on graphs utilizing simultaneous trust and anti-trust propagation and provide effective numerical approach for its computation. Comparison with another models such as TrustRank and some of its modifications on sample of 320000 Russian speaking Twitter users is presented. The dataset is presented as well.
Improved quality check procedures of XBT profiles in MFS-VOS

Improved quality check procedures of XBT profiles in MFS-VOS F. Reseghetti, M. Borghini, and G. M. R. Manzella ENEA-CLIM-MED, Forte S. Teresa – Pozzuolo di Lerici, P.O. Box 224, 19100 La Spezia, Italy CNR-ISMAR, Physical Oceanography Sect. , Forte S. Teresa – Pozzuolo di Lerici, Italy ENEA-CLIM, Forte S. Teresa – Pozzuolo di Lerici, P.O. Box 224, 19100 La Spezia, Italy Received: 5 May 2006 – Accepted: 21 August 2006 – Published: 1 September 2006 Correspondence to: F. Reseghetti (reseghetti@santateresa.enea.it)
Factorizations of Ode's with Polynomial Nonlinearities *

We propose a factorization scheme for ordinary differential equations with polynomial nonlinearities (reaction-diffusion in the traveling frame and dampedanharmonic-oscillator equations) which is different and more efficient than that given by L.M. Berkovich in Sov. Math. Dokl. 45, 162 (1992). We then invert the factorization brackets in the SUSYQM style to get ODE’s with a different polynomial nonlinearity but displaying kink solutions of different width propagating at the same velocity as the kink solution of the original equation. We thus report an interesting pairing of this class of differential equations from the standpoint of their kink solutions that could have applications still unforeseen. We illustrate the mathematical procedure with several important cases, among which the generalized Fisher equation and the FitzHugh-Nagumo equation.
Browsing digital libraries with the aid of self-organizing maps

-Powerful methods for exploring and searching collections of free-form textual documents are needed to control the flood of digital information emerging from various sources. In this article we present a method, WEBSOM, for automatic organization of document collections based on full-text analysis using the Self-Organizing Map. The document collection is ordered on the map in such a way that similar documents lie near each other. The WWW-based user interface provides the basic functionalities necessary for intuitive exploration of the document space visualized with a map: moving on the map, zooming, and examining individual documents. We apply the method to the Usenet newsgroup comp.ai. neural-nets.
Noise modelling and estimation of hyperspectral data from airborne imaging spectrometers

The definition of noise models suitable for hyperspectral data is slightly different depending on whether whiskbroom or push-broom are dealt with. Focussing on the latter type (e.g., VIRS-200) the noise is intrinsically non-stationary in the raw digital counts. After calibration, i.e. removing the variability effects due to different gains and offsets of detectors, the noise will exhibit stationary statistics, at least spatially. Hence, separable 3D processes correlated across track (x), along track (y) and in the wavelength (? ), modelled as auto-regressive with GG statistics have been found to be adequate. Estimation of model parameters from the true data is accomplished through robust techniques relying on linear regressions calculated on scatter-plots of local statistics. An original procedure was devised to detect areas within the scatter-plot corresponding to statistically homogeneous pixels. Results on VIRS-200 data show that the noise is heavy-tailed (tails longer than those of a Gaussian PDF) and somewhat correlated along and across track by slightly different extents. Spectral correlation has been investigated as well and found to depend both on the sparseness (spectral sampling) and on the wavelength values of the bands that have been selected.
Program Committee Contextual Filtering of Rhetorical Relations in Discourse Structuring for Language Generation in Human-computer Dialogue 115 Extracting Preferences from Dialogue: towards a Theory of Strategic Conversation Comprehending Descriptions of Non-factual Desired Situations: Discourse Refe

The goal of this workshop series is to provide a forum for presenting recent research on constraints in discourse. The target areas include the recognition of discourse structure as well as the interpretation and generation of discourse in a broad variety of domains. The workshop is open to talks that further our theoretical understanding of the role of constraints in discourse, as well as empirical studies that shed light on their empirical validity. The workshop is explicitly intended for discussion and comparison of theoretical accounts that lay the ground for applications. Berry Claus: Comprehending descriptions of non-factual desired situations: Discourse referents and motor actions 3 Laurence Danlos: D-STAG: Parsing discourse with Synchronous TAG and SDRT background 5 Julia Hirschberg: A question of questions: Prosodic cues to question form and function 7 Paul Piwek: Constraints in natural language generation 9 Regular Papers Maria Averintseva-Klisch, Sebastian Buecking: What's wrong with 'Diana'? – Discourse-pragmatic constraints on bare proper names in German 11 Ildikó Berzlánovich, Markus Egg, Gisela Redeker: Coherence structure and lexical cohesion in expository and persuasive texts 19 Laurence Danlos, Pierre Hankach: Right frontier constraint for discourses in non-canonical order 27 Michael Grabski: Connectives that manage perspectives in discourse. On the function of German nämlich, schließlich, and also 37 Katja Jasinskaja, Antje Roßdeutscher: Towards generating narratives from a preverbal message: A DRT-based approach 45 Jacques Jayez, Mathilde Dargnat: The interpretation of continuative cues in SDRT 53 Departures from tree structures in discourse: Shared arguments in the Penn Discourse Treebank 61 Rudy Loock: Appositive relative clauses and their competing allostructures in English: an information packaging approach 69 Manfred Stede, Kristin Irsig: Complex connectives in German: Complications for local coherence analysis 77 Marianne Vergez-Couret, Laurent Prévot, Myriam Bras: Interleaved discourse, the case of two-step enumerative structures 85 Posters Rodrigo Agerri: Does Blocking Affect Metaphor Interpretation? It is well accepted that dialogues are structured by various moves that the participants make. Participants answer questions posed by other dialogue participants. They ask follow up questions. They explain why things that they said happened happened; they provide narrative sequences in which events are temporally and spatially ordered together. They elaborate and defend claims that they have made. In this talk, I will investigate how agents can reason about their own dialogue moves. This is important if we are to analyse strategic conversations, conversations that are driven by the participants' particular preferences, not just by cooperative principles like …
ROBUST DECENTRALIZED CONTROL OF REACTIVE DISTILLATION PROCESS IN DIMETHYLACETAMIDE PRODUCTION

Abstract The paper deals with the sequential synthesis procedure of decentralized (multi-loop) PID-controllers based on the estimation of control loops interaction in the form of multiplicative plant uncertainty. It is shown that the each synthesis iteration is accompanied by the correction of the robust performance criteria for the coupled SISO-systems. The results of industrial application of proposed sequential design for reactive distillation unit is cited as well as comparison analysis with the other techniques is given.
The Magic of Pushing Extrema into Recursion: Simple, Powerful Datalog Programs

We introduce a novel query optimization method based on pushing extrema and other integrity constraints into recursion. This optimization produces an efficient operational semantics for the goals declaratively specified by the original program that is stratified with respect to negation and aggregates. Complex algorithms can now be specified via simpler programs, and then implemented via optimized rules that use min and max aggregates in the seminaive fixpoint computation to achieve safe and efficient execution. This optimization dovetails with recent advances that entail the use of monotonic aggregates in recursion and leads to efficient implementation, as demonstrated by the scalable Datalog systems we have recently developed.
The Effects of Rewarding User Engagement – The Case of Facebook Apps

We study the market for apps on Facebook, the dominant social networking platform, and make use of a rule change by Facebook by which highly engaging apps were rewarded with further opportunities to engage users. The rule change led to new applications with significantly higher user ratings being developed. Moreover, user ratings became more important drivers of app success. Other drivers of app success are also affected by the rule change; sheer network size became a less important driver for app success, update frequency benefitted apps more in staying successful, and active users of Facebook apps declined less rapidly with age. Our results show that social media channels do not necessarily have to be managed through hard exclusion of participants but can also be steered through “softer” changes in reward and incentive systems.
Metacomprehension judgements reflect the belief that diagrams improve learning from text

In two experiments we systematically explored whether people consider the format of text materials when judging their text learning, and whether doing so might inappropriately bias their judgements. Participants studied either text with diagrams (multimedia) or text alone and made both per-paragraph judgements and global judgements of their text learning. In Experiment 1 they judged their learning to be better for text with diagrams than for text alone. In that study, however, test performance was greater for multimedia, so the judgements may reflect either a belief in the power of multimedia or on-line processing. Experiment 2 replicated this finding and also included a third group that read texts with pictures that did not improve text performance. Judgements made by this group were just as high as those made by participants who received the effective multimedia format. These results confirm the hypothesis that people's metacomprehension judgements can be influenced by their beliefs about text format. Over-reliance on this multimedia heuristic, however, might reduce judgement accuracy in situations where it is invalid.
Hydrophobic Amino Acid Residues in the Acceptor Binding Site Are Main Determinants for Reaction Mechanism and Specificity of Cyclodextrin-glycosyltransferase*

Cyclodextrin-glycosyltransferases (CGTases) (EC 2.4.1.19) preferably catalyze transglycosylation reactions with glucosyl residues as acceptor, whereas the homologous α-amylases catalyze hydrolysis reactions using water as acceptor. This difference in reaction specificity is most likely caused by the acceptor binding site. To investigate this in detail we altered the acceptor site residues Lys-232, Phe-183, Phe-259, and Glu-264 ofBacillus circulans strain 251 CGTase using site-directed mutagenesis. Lys-232 is of general importance for catalysis, which appears to result mainly from stabilization of the conformation of the loop containing the catalytic nucleophile Asp-229 and His-233, a residue that has been implied in transition state stabilization. Glu-264 contributes to the disproportionation reaction only, where it is involved in initial binding of the (maltose) acceptor. Phe-183 and Phe-259 play important and distinct roles in the transglycosylation reactions catalyzed by CGTase. Mutation of Phe-183 affects especially the cyclization and coupling reactions, whereas Phe-259 is most important for the cyclization and disproportionation reactions. Moreover, the hydrophobisity of Phe-183 and Phe-259 limits the hydrolyzing activity of the enzyme. Hydrolysis can be enhanced by making these residues more polar, which concomitantly results in a lower transglycosylation activity. A double mutant was constructed that yielded an enzyme preferring hydrolysis over cyclization (15:1), whereas the wild type favors cyclization over hydrolysis (90:1).
Development of the Monsi-Saeki theory on canopy structure and function.

BACKGROUND AND AIMS Monsi and Saeki (1953) published the first mathematical model of canopy photosynthesis that was based on the light attenuation within a canopy and a light response of leaf photosynthesis. This paper reviews the evolution and development of their theory. SCOPE Monsi and Saeki showed that under full light conditions, canopy photosynthesis is maximized at a high leaf area index (LAI, total leaf area per unit ground area) with vertically inclined leaves, while under low light conditions, it is at a low LAI with horizontal leaves. They suggested that actual plants develop a stand structure to maximize canopy photosynthesis. Combination of the Monsi-Saeki model with the cost-benefit hypothesis in resource use led to a new canopy photosynthesis model, where leaf nitrogen distribution and associated photosynthetic capacity were taken into account. The gradient of leaf nitrogen in a canopy was shown to be a direct response to the gradient of light. This response enables plants to use light and nitrogen efficiently, two resources whose supply is limited in the natural environment. CONCLUSION The canopy photosynthesis model stimulated studies to scale-up from chloroplast biochemistry to canopy carbon gain and to analyse the resource-use strategy of species and individuals growing at different light and nitrogen availabilities. Canopy photosynthesis models are useful to analyse the size structure of populations in plant communities and to predict the structure and function of future terrestrial ecosystems.
Best wavelet-packet bases for audio coding using perceptual and rate-distortion criteria

This paper presents a new approach to the adaptation of a wavelet filterbank based on perceptual and rate-distortion criteria. The system makes use of a wavelet-packet transform where each subband can have an individual time-segmentation. Boundary effects can be avoided by using overlapping blocks of samples and therefore switching bases is possible at every tree-level without affecting other subbands. A modified psychoacoustic model using perceptual entropy can control the switching of the wavelet filterbank and the individual time-segmentation of every subband allows one to take advantage of temporal masking. Additionally a rate-distortion measure can control the filterbank for lossless audio coding applications or in cases where large coding gains can be achieved without using perceptual criteria. The weight of the perceptual measure as well as the weight of the rate-distortion measure can be selected individually, enabling to trade lossless coding versus perceptual coding.
Statistical Methods for Computational Markets

We design, implement and evaluate statistical methods for managing uncertainty when consuming and provisioning resources in a federated computational market. To enable efficient allocation of resources in this environment, providers need to know consumers’ risk preferences, and the expected future demand. The guarantee levels to offer thus depend on techniques to forecast future usage and to accurately capture and model uncertainties. Our main contribution in this thesis is threefold; first, we evaluate a set of techniques to forecast demand in computational markets; second, we design a scalable method which captures a succinct summary of usage statistics and allows consumers to express risk preferences; and finally we propose a method for providers to set resource prices and determine guarantee levels to offer. The methods employed are based on fundamental concepts in probability theory, and are thus easy to implement, as well as to analyze and evaluate. The key component of our solution is a predictor that dynamically constructs approximations of the price probability density and quantile functions for arbitrary resources in a computational market. Because highly fluctuating and skewed demand is common in these markets, it is difficult to accurately and automatically construct representations of arbitrary demand distributions. We discovered that a technique based on the Chebyshev inequality and empirical prediction bounds, which estimates worst case bounds on deviations from the mean given a variance, provided the most reliable forecasts for a set of representative high performance and shared cluster workload traces. We further show how these forecasts can help the consumers determine how much to spend given a risk preference and how providers can offer admission control services with different guarantee levels given a recent history of resource prices.
HIGH PERFORMANCE ALGORITHMS FOR THE CONTROL OF BUCK DC-DC CONVERTERS

In this paper, two control methods are presented for controlling the DC-DC converters. These proposed control algorithms are tailored to buck DC-DC converter, so as to optimize the performance of the converter. First, a model predictive control (MPC) method which uses a short prediction horizon is proposed. Since a short prediction horizon is used, the optimization solution can be derived analytically so that the algorithm becomes simple enough and can be implemented on-line. Further, the reference tracking error of inductance current is chosen as the penalized output. Second, a three-level hysteresis control method is proposed. This is naturally the extension of the conventional hysteresis control. The basic principle is to set the duty ratio in the central layer band as the steady-state duty ratio. Lastly, the load identification based on an adaptation of fuzzy control is proposed. Computer simulations have been carried out to investigate the effectiveness of the proposed algorithms. Comparison with the well-known PID-PWM method is also presented. The advantage of this approach lies in its good trade-off between simple implementation, rise-time and overshoot in the output voltage response