Miracle-dz/UniFAR-FTUs huggingface dataset:
Biological Significance of Local TGF-β Activation in Liver Diseases

The cytokine transforming growth factor-β (TGF-β) plays a pivotal role in a diverse range of cellular responses, including cell proliferation, apoptosis, differentiation, migration, adhesion, angiogenesis, stimulation of extracellular matrix (ECM) synthesis, and downregulation of ECM degradation. TGF-β and its receptors are ubiquitously expressed by most cell types and tissues in vivo. In intact adult tissues and organs, TGF-β is secreted in a biologically inactive (latent) form associated in a non-covalent complex with the ECM. In response to injury, local latent TGF-β complexes are converted into active TGF-β according to a tissue- and injury type-specific activation mechanism. Such a well and tightly orchestrated regulation in TGF-β activity enables an immediate, highly localized response to type-specific tissue injury. In the pathological process of liver fibrosis, TGF-β plays as a master profibrogenic cytokine in promoting activation and myofibroblastic differentiation of hepatic stellate cells, a central event in liver fibrogenesis. Continuous and/or persistent TGF-β signaling induces sustained production of ECM components and of tissue inhibitor of metalloproteinase synthesis. Therefore, the regulation of locally activated TGF-β levels is increasingly recognized as a therapeutic target for liver fibrogenesis. This review summarizes our present knowledge of the activation mechanisms and bioavailability of latent TGF-β in biological and pathological processes in the liver.
Randomized controlled trials of individual-level, population-level, and multilevel interventions for preventing sexually transmitted infections: what has worked?

BACKGROUND Previous reviews of interventions to prevent sexually transmitted infections (STIs) focused mostly on human immunodeficiency virus (HIV) infection. We reviewed trials of interventions to prevent sexual transmission of any STI, employing a multilevel perspective. METHODS We searched MEDLINE, the Cochrane Central Register of Controlled Trials, and recent unpublished presentations through 2003, to identify randomized controlled trials of preventive STI interventions having systematic, objective measurement of STI outcomes. We classified trials according to intervention target and level of randomization (individual, group, or community); impact target (acquisition, transmission, or complications of STI); and primary intervention modality. RESULTS Of 83 trials identified, 41 met inclusion criteria, including trials of 28 individual-level, 9 group-level, and 4 community-level interventions. Among individual- and group-level interventions, 32 targeted acquisition, 4 targeted transmission, and 1 targeted complications of STI. The 4 intervention modalities most often used included behavior change (12 studies), vaccination (7 studies), use of topical microbicides (10 studies), and prophylactic, curative, or suppressive therapy (10 studies). Community-level interventions had multiple impact targets, and 2 interventions used multiple modalities. Only 1 intervention showed efficacy against sexual transmission of HIV, but 22 (53.7%) showed effectiveness against other STIs. CONCLUSION Although many interventions have been found to be effective against STIs, few have been replicated, widely implemented, or carefully evaluated for effectiveness in other settings.
AN INTRODUCTION TO O-MINIMAL GEOMETRY

Preface These notes have served as a basis for a course in Pisa in Spring 1999. A parallel course on the construction of o-minimal structures was given by A. Macintyre. The content of these notes owes a great deal to the excellent book by L. van den Dries [vD]. Some interesting topics contained in this book are not included here, such as the Vapnik-Chervonenkis property. Part of the material which does not come from [vD] is taken from the paper [Co1]. This includes the sections on the choice of good coordinates and the triangulation of functions in Chapter 4 and Chapter 5. The latter chapter contains the results on triviality in families of sets or functions which were the main aim of this course. The last chapter on smoothness was intended to establish property " DC k-all k " which played a crucial role in the course of Macintyre (it can be easily deduced from the results in [vDMi]). It is also the occasion to give a few results on tubular neighborhoods. I am pleased to thank Francesca Acquistapace, Fabrizio Broglia and all colleagues of the Dipartimento di Matematica for the invitation to give this course in Pisa and their friendly hospitality. Also many thanks to Antonio Ponchio for reading these notes and correcting mistakes.
User Archetypes for Effective Information Privacy Communication Completed Research

In an information systems context, information privacy communication will only work if information systems meet the information needs of their users. Since the needs are neither static nor uniform, a promising approach avoiding inadequacies of ignoring differences in users’ information needs and more practical than dedicated attention to each individual user is to target information privacy communication to user archetypes. To identify such archetypes, we conduct a survey eliciting users’ information needs and apply hierarchical clustering to derive a hierarchical model of user archetypes with respect to their information privacy information needs. We identify a total of 13 archetypes on two hierarchy levels. In contrast to extant research on information privacy user archetypes focusing on information privacy attitudes, the identified information privacy user archetypes are based on information system characteristics desired by users as elicited through our survey. Thus, they yield clear input for enhancing information system design with respect to information privacy. Our research highlights differences and similarities between archetypes and enriches it with an interpretatively derived characterization of the different archetypes. The resulting archetype hierarchy serves as foundation for future research aiming to improve communication of information privacy practices.
Joint optimization of delivery constraint and capacity adjustment for electronic component production system

To keep competitive in the new dynamic market having more requirements in product various and delivery date, manufacturing companies need to make systems that not only response to market rapidly but also ensure delivery on time. Reconfigurable manufacturing system is a new paradigm to enhance the ability to response to the market rapidly and improve the performance rate. Capacity scalability is an important feature for reconfigurable manufacturing system. The effectiveness of an RMS depends on production scheduling and the time to reconfigure. According to the theory of constrains, bottleneck is the main factor to hinder the development of a manufacturing system. So the schedule and the adjustment of production capacity for bottleneck are really important in improving a manufacturing system performance. This paper focuses on the scheduling of bottleneck which can adjust production capacity and develops a model to solve this type problem. An adaptive genetic algorithm is used to solve the model. The aim of the problem is to find out the best schedule and device production capacity. Finally, an example is used to validate the results of the model and its solution procedure.
CRF-based semantic labeling in miniaturized road scenes

This paper presents an approach for the automatic pixelwise labeling of road scenes using a Probabilistic Graphical Model (PGM). The learning stage is based upon Conditional Random Fields (CRFs) and the inference of the semantic classes is relies on Tree-Reweighted Belief Propagation (TRW). The employment of miniaturized images based on superpixels is proposed and validated to achieve real time classification, which is of interest for the integration of scene understanding capabilities into ADAS and autonomous vehicles. The evaluation is carried out using the KITTI ROAD dataset achieving top results in roads with multiple marked lanes and it is publicly ranked among the state of the art.
Eye-to-hand coordination: a coarse-calibrated approach

This paper integrates different novel concepts to perform eye-to-hand coordination and manipulation to realise a working robot named COERSU. One of the salient features of our system is that it is not highly dependent to the camera-robot calibrations. Our coarse-calibrated eye-to-hand visual servoing uses monocular vision and primitive tactile information to extract 3D information of the scene. A robust genetic tuner is briefly presented to optimise the parameters of the image segmentation and edge detection. Some simple methods for scene classification, pose detection and final verification were also implemented to perform intelligent grasping. Experimental results from COERSU in a table-top scenario to manipulate some soft objects (fruit and egg) are also provided to validate these methods (snapshots and videoclip). Figure 1. COERSU and a table-top scenario
A temperature-aware global router

In this paper, we present a temperature-aware global router that considers the reliability of interconnects by improving a state-of-the-art global router, NTHU-Route 2.0, with the following enhancements: (1) a temperature-aware L-shaped routing method employed during initial routing, (2) two temperature-aware cost functions employed during rip-up and reroute, and (3) three implementation techniques for memory reduction. The experimental results show that under two different types of thermal profiles our router solves 12 of 16 ISPD08 benchmarks without causing any overflow, which is as good as NTHU-Route 2.0. For the other 4 benchmarks, our router can generate results with comparable overflows. Furthermore, our router significantly reduces the number of net segments located in hot spots and thus enhances the chip reliability. Finally, our router averagely reduces 45% memory usage of NTHU-Route 2.0.
Echoes from an irradiated disc in GRO J1655–40

We demonstrate correlated rapid variability between the optical/UV and X-ray emission for the first time in a soft X-ray transient, GRO J1655–40: Hubble Space Telescope (HST) light curves show similar features to those seen by the Rossi X-ray Timing Explorer (RXTE), but with mean delay of up to 10–20 s. We interpret the correlations as the result of reprocessing of X-rays into optical and UV emission, with a delay owing to finite light travel time, and thus perform echo mapping of the system. The time-delay distribution has a mean of 14.6 ± 1.4 s and dispersion (i.e. the standard deviation of the distribution) of 10.5 ± 1.9 s at binary phase 0.4. Hence we identify the reprocessing region as the accretion disc rather than the mass donor star.
Uncertainty Models of Vision Sensors in Mobile Robot Positioning

This paper discusses how uncertainty models of vision-based positioning sensors can be used to support the planning and optimization of positioning actions for mobile robots. Two sensor types are considered: a global vision with overhead cameras, and an on-board camera observing artificial landmarks. The developed sensor models are applied to optimize robot positioning actions in a distributed system of mobile robots and monitoring sensors, and to plan the sequence of actions for a robot cooperating with the external infrastructure supporting its navigation.
High-frequency error recovery in JPEG XR coded images

Image data compressed with JPEG XR when transmitted over error-prone channels is severely distorted. In fact, due to the adaptive coding strategies used by the codec, even a single bit error causes a mismatch in the alignment of the reading position from the bitstream, leading to completely different images at the decoder side. We propose an extension to the JPEG XR algorithm, consisting in an error recovery process enabling the decoder to realign itself to the right bitstream position and to correctly decode the most part of the image. We have performed several experiments using different encoder parameter and different error probabilities while image distortion is measured by PSNR objective metric. The simplicity of the proposed algorithm adds very little computational overhead and seems very promising as confirmed by objective image quality results in experimental tests.
Towards an (Even More) Natural Probabilistic Interpretation of Fuzzy Transforms (and of Fuzzy Modeling)

In many practical applications, it turns out to be useful to use the notion of fuzzy transform: once we have functions A1(x) ≥ 0, . ,An ≥ 0, with Σi=1n Ai(x) = 1, we can then represent each function f (x) by the coefficients Fi = (∫ f (x) ċAi(x)dx)/(∫ Ai(x)dx). Once we know the coefficients Fi, we can (approximately) reconstruct the original function f(x) as Σi=1n Fi ċ Ai(x). The original motivation for this transformation came from fuzzy modeling, but the transformation itself is a purely mathematical transformation. Thus, the empirical successes of this transformation suggest that this transformation can be also interpreted in more traditional (nonfuzzy) mathematics as well. Such an interpretation is presented in this paper. Specifically, we show that the 2002 probabilistic interpretation of fuzzy modeling by Sanchez et al. can be modified into a natural probabilistic explanation of fuzzy transform formulas.
Quantitative aspects of chemical carcinogenesis and tumor promotion in liver.

Chronic exposure of rodents to high dose levels of drugs, food additives and environmental chemicals frequently results in liver enlargement. Several of these compounds have been found to enhance the incidence of liver tumors in animals briefly exposed previously to hepatocarcinogens. Accordingly, it has been advanced that these agents act as tumor promoters. This contention has remained subject of controversy following reports that these substances may also cause liver tumors in noncarcinogen-treated rodents, particularly in those characterized by a relatively high incidence of "spontaneous" liver tumors. Since many of these chemicals are in common use, a crucial question would seem to be whether such effects are due to facilitation of the expression of pre-existing oncogenic potential, i.e., to tumor promotion, or to the synergistic action of weakly carcinogenic agents. As a result of mechanistic differences tumor promotion and syn-carcinogenesis must exhibit different dose-time-response characteristics, and, accordingly, it should be possible, in principle, to discriminate between these phenomena. However, since tumor manifestation periods in low-dose groups frequently exceed the animals average lifespan, this approach may not always yield conclusive data, unless a sensitive early marker of carcinogenic activity can be employed. There is evidence that enzyme-deficient preneoplastic areas in liver can be used for this purpose. A strong quantitative correlation between carcinogen dose, the extent of ATPase deficient areas, and the subsequent appearance of tumors has now been established for a number of hepatocarcinogens. Experimental data are consistent with the concept that two critical events (hits) are required for induction of ATPase deficiency in hepatocytes. The first hit is carcinogen-dependent, whereas the second hit would seem to be due to time-dependent event(s). Tumor-promoters, such as phenobarbital, were found to accelerate and increase formation of preneoplastic islets. This evidence, together with data indicating that the compound is devoid of carcinogenic potential, suggests that phenobarbital may be operative at relatively early stages of hepatocarcinogenesis by increasing the probability of the occurrence of the time-dependent second hit. Such effects are dose-dependent and appear to be related to the induction of liver enlargement. The changes in hepatocellular ploidy status and atypical nuclear figures observed during phenobarbital treatment and cessation thereof, suggest that this compound might induce abnormal redistributions of genetic material. It is postulated that these cytological changes may result in phenotypical manifestation of recessive oncogenic information.
Single image enhancement in various weather conditions using Intensity and Saturation Deterioration Ratio

Enhancing images that are plagued with weather related conditions; such as haze, fog and rain poses a challenging problem due to its ill-posed nature, which means the unknowns that need to be found are more than the equations that we have. To address such challenges, a fast yet robust method is proposed in this paper where unknowns in the light scattering model are estimated based on physically sound assumptions. Light scattering model describes the formation of those phenomena in an image as a combination of airlight and the original scene, where this combination is controlled by how much transmission value present at the scene's point. The transmission value determines how much of the original scene's intensity were attenuated and how much airlight was added. The attenuation term of the light scattering model causes the reduction in contrast and the airlight term causes the effect of color shift. In this paper, Intensity Deterioration Ratio (IDR) and Saturation Deterioration Ratio (SDR) are proposed, where the former can be used to estimate the reduction of contrast and so gives a clue about the attenuation term, and the latter to estimate the reduction of chromaticity in a scene which gives a clue about the airlight term. IDR and SDR are therefore used to give us a new insight in using the light scattering model when enhancing images.
Influence of the low-frequency acoustic bypass on distance perception with hearing-aids

With the advent of new hearing-aid technology, more and more hearing-aid users wear their devices with an open fit, avoiding unwanted occlusion effects. Open fitting allows for the direct acoustic sound from the outside to pass through to the ear drum. But also for closed fitted hearing aids there is a part of the direct acoustic sound from the outside that can pass through the vent, especially at low frequencies, depending on vent size. Any sound from the outside that reaches the ear drum will be superposed to the sound played back by the hearing aid, thus allowing for effects such as comb filters that may deteriorate the perceived sound.
PROCEEDINGS of the HUMAN FACTORS AND ERGONOMICS SOCIETY 37th ANNUAL MEETING-1993 METACOGNITIVE STRATEGIES IN SUPPORT OF RECOGNITION

Recent research on decision making has focused on complex real-world domains and experienced decision makers, in contrast to artificial tasks and novice subjects (e.g., Klein et al., 1993). This research has produced a revised view of decision making, one that stresses knowledge-based, recognitional processing rather than general-purpose, analytical methods. Nevertheless, a full understanding of recognitional processing and its implications for the design of decision aids has not yet been achieved. In particular, the active, controlled aspects of recognitional processing have not been fully accounted for in approaches that stress relatively automatic pattern recognition as the basis for responding. Early decision aids implemented formal, general-purpose methods for inference and choice. In inference, the ideal decision maker was thought of as generating a set of exhaustive and mutually exclusive hypotheses, making numerical assessments of the probabilistic relationships among prior beliefs, evidence, and hypotheses, and combining the numerical assessments to arrive at probabilities for the hypotheses. Once a hypothesis was accepted, the decision maker was thought of as generating all feasible options, assessing probabilities for each possible outcome of every option, evaluating each outcome in terms of every relevant evaluative dimension, and then combining the probabilities anc! values to arrive at a measure of the desirability of each option (e.g., Raiffa, 1968; Keeney & Raiffa, 1976). Many empirical studies focused on comparisons of actual behavior in artifi.cia1 tasks with formal models of this sort; the conclusion was often that human decision making is fundamentally flawed and irrational (Kahneman et al., 1982; Cohen, 1993). The most obvious decision aiding implication of this literature involved the attempt to reshape human reasoning directly in the mold of normative models, such as decision analysis (e.g., Edwards, 1968).
Two Seemingly Homologous Noncoding RNAs Act Hierarchically to Activate glmS mRNA Translation

Small noncoding RNAs (sRNA) can function as posttranscriptional activators of gene expression to regulate stress responses and metabolism. We here describe the mechanisms by which two sRNAs, GlmY and GlmZ, activate the Escherichia coli glmS mRNA, coding for an essential enzyme in amino-sugar metabolism. The two sRNAs, although being highly similar in sequence and structure, act in a hierarchical manner. GlmZ, together with the RNA chaperone, Hfq, directly activates glmS mRNA translation by an anti-antisense mechanism. In contrast, GlmY acts upstream of GlmZ and positively regulates glmS by antagonizing GlmZ RNA inactivation. We also report the first example, to our knowledge, of mRNA expression being controlled by the poly(A) status of a chromosomally encoded sRNA. We show that in wild-type cells, GlmY RNA is unstable due to 3′ end polyadenylation; whereas in an E. coli pcnB mutant defective in RNA polyadenylation, GlmY is stabilized and accumulates, which in turn stabilizes GlmZ and causes GlmS overproduction. Our study reveals hierarchical action of two well-conserved sRNAs in a complex regulatory cascade that controls the glmS mRNA. Similar cascades of noncoding RNA regulators may operate in other organisms.
Yesterday's Heroes: Compensation and Risk at Financial Firms

type="main"> Many believe that compensation, misaligned from shareholders’ value due to managerial entrenchment, caused financial firms to take risks before the financial crisis of 2008. We argue that, even in a classical principal-agent setting without entrenchment and with exogenous firm risk, riskier firms may offer higher total pay as compensation for the extra risk in equity stakes borne by risk-averse managers. Using long lags of stock price risk to capture exogenous firm risk, we confirm our conjecture and show that riskier firms are also more productive and more likely to be held by institutional investors, who are most able to influence compensation.
Latent Correlation Analysis of HMM Parameters for Speech Recognition

Correlation between HMM parameters has been utilized for various rapid speaker adaptation, e.g. eigenvoice adaptation. The covariance matrix of the supervector which is a concatenation of all the Gaussian means in HMM, is clearly a good measure of such parameter correlation. In this paper, we propose to treat the supervector as a latent variable under HMM, and perform estimation of the hidden supervector's covariance matrix directly from the acoustic frames using EM algorithm. In contrast to traditional methods which depend on using well-trained/adapted supervector samples, the proposed method is more theoretically sound and capable of dealing well with speaker-specific data sparseness. Moreover, the idea of conducting utterance-level correlation analysis, estimating utterance eigenvoices, and performing (unsupervised) utterance adaptation is explored. Experiments on the OGI Numbers database show that the proposed approach achieves better adaptation performance than the traditional methods, and the utterance-level correlation analysis is found to be useful.