Miracle-dz/UniFAR-FTUs huggingface dataset:
Review of N . Cartwright “ Hunting Causes and Using Them ”

Nancy Cartwright’s recent book “Hunting Causes and Using Them” comes to causality in an interesting stage of her stormy, century-old courtship with economics. A survey article by Kevin Hoover (2004, “Lost causes”) counts the frequency of causal terminology in econometrics articles and asks, “Where have all the causes gone? ” Hoover notes a steady decline from the 1930’s to the early 1980’s, a period of over half a century, followed by two decades of sluggish recovery, to be followed by a marked upsurge of usage in the year 2000. This pattern is both enigmatic and pathological considering that the central aim of econometrics is to provide a methodology for understanding and controlling economical phenomena, and that the founding fathers of econometrics were the ones who developed the basic mathematical tools for causal analysis, in the form of structural equation models (Haavelmo (1943), Marschak (1950), and Strotz and Wold (1960)). The decline of causal understanding in econometrics has in fact been so severe, that in 1995, while I was working on my book Causality [Pearl, 2000a], Jim Heckman had difficulty naming a single econometric textbook that adequately treats causality.1 Given this state of affairs, it is not surprising that philosophers of science, intrigued by the enigma, would avail themselves to offer clarity and guidance to a field that has let statistical dogma trample its glorious past. I was keenly curious therefore to read Cartwright’s take on the current state of causality in economics, and to learn how she proposes to reconcile economics tradition with modern advances in causal analysis, primarily those based on causal diagrams and the logic of counterfactuals.
Topology Prediction of Membrane Proteins Based on a Modified "Positive-Inside" Rule

It is difficult to determine the 3D structure of integral membrane proteins by experimental techniques. However, theoretical prediction of the secondary structures from amino acid sequences appears much easier for intrinsic membrane proteins than soluble proteins, because of steric constraints from membrane structure and weak hydrophobic interaction within the lipid bilayer. Then, the next step is to predict their transmembrane topology. It has been established that positively-charged amino acids (Lys and Arg) tend to be more prevalent in the cytoplasmic region of membrane proteins than in the external regions, which is called a positive-inside rule. In order to improve the accuracy of the topology prediction, we have incorporated another generally accepted rule to the problem, in which long loop-segments of membrane proteins tends to be in the extra-cytoplasmic space rather than in the cytoplasmic space (say, the long-loop-outside rule). In previous works [1,2], loops and tails longer than 60 residues were excluded, since they do not conform to the positive-inside rule. As a complementary approach, we have normalized the magnitude of positive charges by the total length of loops and tails. As a result, a score as good as 95% for the topology prediction was achieved by calculating the composition of positively charged residues (Lys and Arg) of the protein segments exposed at each side of the membrane, for the criterion (See, Methods). In the dataset, 81 out of 120 membrane protein sequences have actually longer extra-cytoplasmic segments, in total, than cytoplasmic ones.
Multi-Objective Genetic Algorithm Optimisation Approach for the Geometrical Design of an Active Noise Control Systems

This paper focuses on the geometrical design of active noise control (ANC) in free- field propagation medium. The development and performance assessment uses genetic optimisation techniques to arrange system components so as to satisfy several performance requirements, such as physical extent of cancellation, controller design restriction and system stability. The ANC system design can be effectively addressed if it is considered as multi – objective optimisation problems. The multi-objective genetic algorithms (MOGAs) are well suited to the design of an ANC system and the approach used for it is based on a multi - objective method, with which the physical extent of cancellation and relative stability assessment are dealt with simultaneously.
Early Transcriptomic Response to LDL and oxLDL in Human Vascular Smooth Muscle Cells

Background Although nowadays it is well known that the human transcriptome can importantly vary according to external or environmental condition, the reflection of this concept when studying oxidative stress and its direct relationship with gene expression profiling during the process of atherogenesis has not been thoroughly achieved. Objective The ability to analyze genome-wide gene expression through transcriptomics has shown that the genome responds dynamically to diverse stimuli. Here, we describe the transcriptome of human vascular smooth muscle cells (hVSMC) stimulated by native and oxidized low-density lipoprotein (nLDL and oxLDL respectively), with the aim of assessing the early molecular changes that induce a response in this cell type resulting in a transcriptomic transformation. This expression has been demonstrated in atherosclerotic plaques in vivo and in vitro, particularly in the light of the oxidative modification hypothesis of atherosclerosis. Approach and Results Total RNA was isolated with TRIzol reagent (Life Technologies) and quality estimated using an Agilent 2100 bioanalyzer. The transcriptome of hVSMC under different experimental conditions (1,5 and 24 hours for nLDL and oxLDL) was obtained using the GeneChip Human Gene 1.0 ST (Affymetrix) designed to measure gene expression of 28,869 well-annotated genes. A fixed fold-change cut-off corresponding to ± 2 was used to identify genes exhibiting the most significant variation and statistical significance (P< 0.05), and 8 genes validated by qPCR using Taqman probes. Conclusions 10 molecular processes were significantly affected in hVSMC: Apoptosis and cell cycle, extracellular matrix remodeling, DNA repair, cholesterol efflux, cGMP biosynthesis, endocytic mechanisms, calcium homeostasis, redox balance, membrane trafficking and finally, the immune response to inflammation. The evidence we present supporting the hypothesis for the involvement of oxidative modification of several processes and metabolic pathways in atherosclerosis is strengthen by the fact that gene expression patterns obtained when hVSMC are incubated for a long period of time in the presence of nLDL, correspond very much the same as when cells are incubated for a short period of time in the presence of chemically modified oxLDL. Our results indicate that under physiological conditions and directly related to specific environmental conditions, LDL particles most probably suffer chemical modifications that initially serve as an alert signal to overcome a harmful stimulus that with time might get transformed to a pathological pattern and therefore consolidate a pathological condition.
Collaboration: the Key to Establishing Community Networks in Regional Australia

Despite the promise of community involvement, cohesion and empowerment offered by local community networks (CN) using Internet Technologies, few communities in regional Australia have been able to demonstrate sustainable and vibrant CN which demonstrate increased social, cultural or self-reliance capital. The Faculty of Informatics and Communication at Central Queensland University (CQU) and a local council have established a formal alliance to establish the COIN (Community Informatics) projects to research issues around this topic. This paper presents the initial findings from this work and draws conclusions for possible comparison with other international experience. The research focuses attention on community understanding and cohesion, local government priorities in a community with relatively low diffusion of the Internet and the competing demands in a regional university between traditional service provision in an increasingly competitive market and the needs of establishing outreach research for altruistic, industry establishment and commercial rationale.
Improving Pairwise Learning Classification in Fuzzy Rule Based Classification Systems Using Dynamic Classifier Selection

Classification based on the One-vs-One decomposition strategy has shown a high quality for addressing those problems with multiple classes, even if the learning model enables the discrimination among several concepts. The main phase of the pairwise learning is the decision process, where the outputs of the binary classifiers are combined to give a single output. Recently, it has been shown that standard decision techniques do not take into account the influence of the non-competent classifiers, i.e. those that were not trained using the class of the query example, and this can deteriorate the performance of the model. In accordance with the former, a “Dynamic Classifier Selection” for the Onevs-One approach was proposed to alleviate this issue. It basically consists of finding those classifiers whose outputs are closest to the input example, and thus remove those ones which are not related with it. In this work, we want to analyse the goodness for the former approach using a fuzzy-type baseline classifier. Experimental results show that there is in fact a significant leap in the global performance when this model is applied, both versus the standard fuzzy rule based classification system, and the One-vs-One learning approach.
Visualizing the activity of a web-based collaborative platform

This paper describes a prototype that offers visualization features for monitoring a Web-based collaborative platform. The data displayed supports workplace awareness by providing an overview of the activities carried out on the platform. The prototype focuses on the information structured as hierarchical data. Three views are included: a classic vertical tree, a treemap view and an original new layout called ellimap. The system has been implemented on a real case in the domain of the support to innovation.
A brief review of surface meshing in medical images for biomedical computing and visualization

A visual representation of the interior of a body is important for clinical analysis and medical intervention. The technique, process and art of creating this visual representation are called medical imaging. The images produced from medical imaging need to be analyses by using Finite Element Method (FEM) especially for intraoperative registration and biomechanical modeling of the tissues. This medical model ranges from the smallest vascular to bones and the complex brain. In order to use FEM, the images need to go through surface meshing generator. Although numerous mesh generation methods have been described to date, there is a few which can deal with medical data input. In this paper, a briefing review of surface meshing that can deal in medical images is presented especially in biomedical computing and visualization. Some automatic mesh generators software used in medical imaging is also discussed such as ScanIP, MIMICS, TETGEN, NetGen, BioMesh3D,CUBITMesh and Gmsh.
Beating the Direct Sum Theorem in Communication Complexity with Implications for Sketching

A direct sum theorem for two parties and a function f states that the communication cost of solving k copies of f simultaneously with error probability 1/3 is at least k · R1/3(f), where R1/3(f) is the communication required to solve a single copy of f with error probability 1/3. We improve this for a natural family of functions f, showing that the 1-way communication required to solve k copies of f simultaneously with probability 2/3 is Ω(k · R1/k(f)). Since R1/k(f) may be as large as Ω(R1/3(f) · log k), we asymptotically beat the direct sum bound for such functions, showing that the trivial upper bound of solving each of the k copies of f with probability 1 -- O(1/k) and taking a union bound is optimal! In order to achieve this, our direct sum involves a novel measure of information cost which allows a protocol to abort with constant probability, and otherwise must be correct with very high probability. Moreover, for the functions considered, we show strong lower bounds on the communication cost of protocols with these relaxed guarantees; indeed, our lower bounds match those for protocols that are not allowed to abort. In the distributed and streaming models, where one wants to be correct not only on a single query, but simultaneously on a sequence of n queries, we obtain optimal lower bounds on the communication or space complexity. Lower bounds obtained from our direct sum result show that a number of techniques in the sketching literature are optimal, including the following: • (JL transform) Lower bound of
The statistical approach to machine translation and a roadmap for speech translation

During the last few years, the statistical approach has found widespread use in machine translation, in particular for spoken language. In many comparative evaluations of automatic speech translation, the statistical approach was found to be signiﬁcantly superior to the existing conventional approaches. The paper will present the main components of a statistical machine translation system (such as alignment and lexicon models, training procedure, generation of the target sentence) and summarize the progress made so far. We will conclude with a roadmap for future research on spoken language translation.
Research of pseudo frame skip technology applied in H.264

In extreme low bit rate environment, there are much more distortions in the video stream produced by present H.264 reference software model. This paper proposes a new rate control method using pseudo frame skip technology. The method takes advantage of H.264 syntax element and mode selection mechanism and prevents frame skipping under bit rate controlled. The experiment results indicated that the proposed method make the bit allocation more reasonable and enhance the visual quality of the coded video sequence.
Collision prediction among polygons with arbitrary shape and unknown motion

Collision prediction is a fundamental operation for planning motion in dynamic environment. Existing methods usually exploit complex behavior models or use dynamic constraints in collision prediction. However, these methods all assume simple geometries, such as disc, which significantly limit their applicability. This paper proposes a new approach that advances collision prediction beyond disc robots and handles arbitrary polygons. Our new tool predicts collision by assuming that obstacles are adversarial. Comparing to an online motion planner that replans periodically at fixed time interval and planner that approximates obstacle with discs, our experimental results provide strong evidences that the new method significantly reduces the number of replans while maintaining higher success rate of finding a valid path. Our geometric-based collision prediction method provides a tool to handle highly complex shapes and provides a complimentary approach to those methods that consider behavior and dynamic constraints of objects with simple shapes.
Cancer Epithelia Protease Results in Its Secretion by Prostate and Prostate Catalytic Cleavage of the Androgen-regulated TMPRSS 2 Updated Version

We identified TMPRSS2as a gene that is down-regulated in androgenindependent prostate cancer xenograft tissue derived from a bone metastasis. Using specific monoclonal antibodies, we show that the TMPRSS2encoded serine protease is expressed as a Mr 70,000 full-length form and a cleavedMr 32,000 protease domain. Mutation of Ser-441 in the catalytic triad shows that the proteolytic cleavage is dependent on catalytic activity, suggesting that it occurs as a result of autocleavage. Mutational analysis reveals the cleavage site to be at Arg-255. A consequence of autocatalytic cleavage is the secretion of the protease domain into the media by TMPRSS2-expressing prostate cancer cells and into the sera of prostate tumor-bearing mice. Immunohistochemical analysis of clinical specimens demonstrates the highest expression of TMPRSS2 at the apical side of prostate and prostate cancer secretory epithelia and within the lumen of the glands. Similar luminal staining was detected in colon cancer samples. Expression was also seen in colon and pancreas, with little to no expression detected in seven additional normal tissues. These data demonstrate that TMPRSS2 is a secreted protease that is highly expressed in prostate and prostate cancer, making it a potential target for cancer therapy and diagnosis.
A Holistic Paradigm for Schema Matching ∗

Schema matching is a critical problem for integrating heterogeneous information sources. Traditionally, the problem of matching multiple schemas has essentially relied on finding pairwise-attribute correspondence. In contrast, we propose a new matching paradigm, holistic schema matching, to holistically match many schemas at the same time and find all the matchings at once. By handling a set of schemas together, we can explore their context information that reflects the semantic correspondences among attributes, which is not available when schemas are matched only in pairs. As the realizations of the holistic paradigm, we developed two alternative approaches recently. This article takes an initial step to unify those two approaches and further contrasts their strength and weakness. Specifically, we develop two alternative methods for realizing holistic schema matching: lobal evaluationand local evaluation. Global evaluation exhaustively assesses all the possible models, where a modelexpresses all attribute matchings. In particular, we propose the MGS framework for such global evaluation with the hypothesis of the existence of generative models. On the other hand, local evaluation independently assesses every single matching to incrementally construct the model. In particular, we develop theDCM framework for such local evaluation with the observation that co-occurrence patterns across schemas often reveal the complex relationships of attributes. We apply our approaches on matching Web query interfaces on the deep Web. The result shows the effectiveness of both the MGS andDCM approaches, which together demonstrate the promise of the holistic paradigm for schema matching.
Cross Talk between Neuroregulatory Molecule and Monocyte: Nerve Growth Factor Activates the Inflammasome

Background Increasing evidence points to a role for the extra-neuronal nerve growth factor (NGF) in acquired immune responses. However, very little information is available about its role and underlying mechanism in innate immunity. The role of innate immunity in autoimmune diseases is becoming increasingly important. In this study, we explored the contribution of pleiotropic NGF in the innate immune response along with its underlying molecular mechanism with respect to IL-1β secretion. Methods Human monocytes, null and NLRP3 deficient THP-1 cell lines were used for this purpose. We determined the effect of NGF on secretion of IL-1β at the protein and mRNA levels. To determine the underlying molecular mechanism, the effect of NGF on NLRP1/NLRP3 inflammasomes and its downstream key protein, activated caspase-1, were evaluated by ELISA, immunoflorescence, flow cytometry, and real-time PCR. Results In human monocytes and null THP-1 cell line, NGF significantly upregulates IL-1β at protein and mRNA levels in a caspase-1 dependent manner through its receptor, TrkA. Furthermore, we observed that NGF induces caspase-1 activation through NLRP1/NLRP3 inflammasomes, and it is dependent on the master transcription factor, NF-κB. Conclusions To best of our knowledge, this is the first report shedding light on the mechanistic aspect of a neuroregulatory molecule, NGF, in innate immune response, and thus enriches our understanding regarding its pathogenic role in inflammation. These observations add further evidence in favor of anti-NGF therapy in autoimmune diseases and also unlock a new area of research about the role of NGF in IL-1β mediated diseases.
Thresholding in edge detection: a statistical approach

Many edge detectors are available in image processing literature where the choices of input parameters are to be made by the user. Most of the time, such choices are made on an ad-hoc basis. In this article, an edge detector is proposed where thresholding is performed using statistical principles. Local standardization of thresholds for each individual pixel (local thresholding), which depends upon the statistical variability of the gradient vector at that pixel, is done. Such a standardized statistic based on the gradient vector at each pixel is used to determine the eligibility of the pixel to be an edge pixel. The results obtained from the proposed method are found to be comparable to those from many well-known edge detectors. However, the values of the input parameters providing the appreciable results in the proposed detector are found to be more stable than other edge detectors and possess statistical interpretation.
Secure and Robust Localization in a Wireless Ad Hoc Environment

We study the problem of accurate localization of static or mobile nodes in a wireless ad hoc network using the distance estimates of a group of untrusted anchors within the communication range of the nodes. Some of the anchors may be malicious and may independently lie about the distance estimate. The malicious anchors may also collude to lie about the distance estimates. In both cases, accurate node localization may be seriously undermined. We propose a scheme that performs accurate localization of the nodes in the network despite the presence of such malicious anchors. We also show how to identify most of these malicious anchors. In the case where measurements are error free, we derive a critical threshold B for the number of malicious anchors that can be tolerated in the localization process without undermining accuracy. We also show how to correctly localize a node and identify all the malicious anchors in this setting. In the presence of measurement errors, we propose a convex optimization-based localization scheme that can accurately localize a node, as long as the number of malicious anchors in its communication range is no more than B. Simulation results show that our schemes are very effective. When the measurements are error prone and the number of malicious anchors is no more than B , our scheme localizes a node with an error less than 8% and is also able to identify a significant number of malicious anchors. Our schemes guarantee that a true anchor is not identified as malicious.
Approximate Soft Shadows win an Image‐Space Flood‐Fill Algorithm

Most former soft shadow algorithms have either suffered from restricted self‐shadowing capabilities, been too slow for interactive applications, or could only be used with a limited types of geometry. In this paper, we propose an efficient image‐based approach for computing soft shadows. Our method is based on shadow mapping and provides the associated benefits. We use pixel‐based visibility computations for rendering penumbra regions directly into the screen‐space. This is accomplished by using a modified flood‐fill algorithm which enables us to implement the algorithm using programmable graphics hardware. Even though the resulting images are most often high quality, we do not claim that the proposed method is physically correct. The computation time and memory requirements for soft shadows depend on image resolution and the number of lights, not geometric scene complexity.