Miracle-dz/UniFAR-FTUs huggingface dataset:
Computer Science Research Proposal Automated Statistical Abstraction of Programs

The application of automated theorem proving to program verification is increasingly being used in real-world situations, most of which are concerned with proving safety properties of code. For example, the Berkeley Lazy Abstraction Software Verification Tool [4] (Blast), and Microsoft r ©’s SLAM Toolkit [1] are applied to the verification of safety properties in drivers. Such use entails considering all possible execution paths, so that a property can be verified to hold in all circumstances. This approach therefore deals mainly with the processing of situations that do not commonly arise in practice, hence are not captured by conventional testing. On the other hand, the issue of modelling computer systems is primarily concerned with statistical properties of a system, and therefore the common case execution paths. An example of such an application is seen in network modelling; that is to say inferring the statistical behaviour of data flows on a network. Currently, such modelling is done either by simulation, or by use of statistical frameworks such as queueing theory. While the latter may allow a sophisticated analysis of global properties, one has to be cautious of the assumptions made of the underlying physical system. The challenge here lies in relating the model of a system to its actual implementation, and therefore in the interface between the ‘bottom-up’ approach taken by program verification, and the ‘top-down’ approach taken by behavioural modelling. The proposed research is to investigate the extent to which the two processes may be unified. For example, it should be possible, when provided with suitable data regarding the use of a procedure (such as the implementation of a queue), to derive statistical properties, such as the probability of a queue being full on a request to push more data onto it, given a distribution of arrival times. Conversely, one might like to generate approximations to the service time distribution of a queue, based on the implementation itself, in the context of normal operating parameters. There are two related problems here; that of verification that a queue corresponds (within specified bounds) to a service time distribution, and that of deriving the distribution itself. Any work of this nature would be required to deal with the language used in real-world implementations; namely C. Despite the issues observed due to lack of type safety and pointer related mishaps, substantial work has already been undertaken to address these problems. Most notable is the CCured [8] system, developed at Berkeley, which performs transformations on C code, in order to enforce type-safety in existing programs. Although this deals with just a subset of the language, it is noted that the majority of code does not take advantage of the more esoteric capabilities of C, and therefore may be readily analysed. CCured performs its
Error correction via smoothed L0-norm recovery

Channel coding has been considered as a classical approach to overcome corruptions occurring in some elements of input signal which may lead to loss of some information. Proper redundancies are added to the input signal to improve the capability of detecting or even correcting the corrupted signal. A similar scenario may happen dealing with real-field numbers rather than finite-fields. This paper considers a way to reconstruct an exact version of a corrupted signal by using an encoded signal with proper number of redundancies. The proposed algorithm uses Graduated Non-Convexity method beside using a smoothed function instead of ℓ0-norm to correct all the corrupted elements. Simulations show that our proposed algorithm substantially improves the probability of exact recovery in comparison to previous algorithms.
Microleakage in Resin Composite Restoration following Antimicrobial Pre-treatments with 2% Chlorhexidine and Clearfil Protect Bond

Aim: To evaluate microleakage in resin composite restorations after antimicrobial pre – treatments Materials and Methods: Forty freshly extracted non carious human premolars were procured. In all forty premolar specimens, class V preparation of standard dimension were prepared and were randomly divided into three experimental and one control group. In all control and experimental groups the class V preparations were restored with FILTEK Z350 composite restorative material. The experimental groups included different self etching primers and 2% Chlorhexidine gluconate. The control group included Xeno III and no antimicrobial pre-treatment was done for the control group. Thereafter these specimens were thermocycled, dried and sealed with nail varnish, leaving 1mm around the restoration and immersed in 0.5% basic fuchsin for 24 hours and then the specimens were subjected for microleakage evaluation. The results were statistically analyzed by Kruskal Wallis Test and Mann Whitney ‘U’ test. Results: Results indicate that group II (2% chlorhexidine gluconate group) had the minimum mean value (15.05) and group III(Clearfil protect Bond group) and IV(control group) had the maximum mean microleakage at the enamel margin (23.00). At the gingival margin the lowest mean microleakage values were obtained with group I (Clearfil SE bond group) and group II (2% chlorhexidine gluconate) (20.25) and highest with group III and group IV (20.85). The difference was not statistically significant both at the enamel margin and the dentin margin (p>0.05). Interpretation & Conclusions: Within the limitations of this in-vitro study, we conclude that: None of the materials tested in this study completely eliminated microleakage at the enamel and at the gingival margin. All of the tested materials provided better sealing at the enamel margin than at the gingival margin.
A new technique to reduce false sharing in parallel irregular codes based on distance functions

In this paper a technique to deal with the problem of poor locality and false sharing in irregular codes on shared memory multiprocessors (SMPs) is proposed. This technique is based on the locality model for irregular codes previously developed and extensively proven by the authors on monoprocessors and multiprocessors. In the model, locality is established in run-time considering parameters that describe the structure of the sparse matrix which characterizes the irregular accesses. As an example of irregular code with false sharing a particular implementation of the sparse matrix-vector product (SpM/spl times/V) was selected. The problem of increasing locality and decreasing false sharing for a irregular problem is formulated as a graph. An adequate distribution of the graph among processors followed by a reordering of the nodes inside each processor produces the solution. The results show important improvements in the behavior of the irregular accesses: reductions in execution time and an improved program scalability.
EqnMaster : Evaluating Mathematical Expressions with Generative Recurrent Networks

In this project, we seek to use computational models to infer mathematical structure from purely symbolic inputs. Though there are existing systems for parsing mathematical expressions, there have been only limited approaches to apply learning-based algorithms to this inherently subtle task. This project therefore proposes an integrated methodology that applies various conﬁgurations of neural networks to analyze sequences of mathematical language. We deﬁne both a discriminative task – in which we pursue the veriﬁcation of a given equation – and a generative task – where we predict the evaluation of an input mathematical expression. We test our models on a novel dataset, and gain insight into the workings of our models by learning underlying representations of our data.
SPARC Fusion Protein Induces Cellular Adhesive Signaling

Secreted protein, acidic and rich in cysteine (SPARC) has been described as a counteradhesive matricellular protein with a diversity of biological functions associated with morphogenesis, remodeling, cellular migration, and proliferation. We have produced mouse SPARC with a FLAG-tag at the N-terminus of SPARC (Flag-SPARC, FSP) in a Bac-to-Bac baculoviral expression system. After affinity purification, this procedure yields SPARC of high purity, with an electrophoretic mobility of ∼44 kDa under reducing conditions, and ∼38–39 kDa under non-reducing conditions. Unexpectedly, FSP adsorbed to plastic supported cell attachment and spreading, in a calcium-dependent manner. The adhesive activity of native FSP was inhibited by prior incubation with anti-SPARC IgG. Cell adhesion to FSP induced the formation of filopodia and lamellipodia but not focal adhesions that were prominent on cells that were attached to fibronectin. In addition, FSP induced the tyrosine phosphorylation of FAK and paxillin in attached epithelial cells. Erk1/2 and Rac were also activated in cells attached to FSP, but at a lower level in comparison to cells on fibronectin. This study provides new insight into the biological functions of SPARC, a matricellular protein with important roles in cell-extracellualr matrix interactions.
New Researches and Application Progress of Commonly Used Optical Molecular Imaging Technology

Optical molecular imaging, a new medical imaging technique, is developed based on genomics, proteomics and modern optical imaging technique, characterized by non-invasiveness, non-radiativity, high cost-effectiveness, high resolution, high sensitivity and simple operation in comparison with conventional imaging modalities. Currently, it has become one of the most widely used molecular imaging techniques and has been applied in gene expression regulation and activity detection, biological development and cytological detection, drug research and development, pathogenesis research, pharmaceutical effect evaluation and therapeutic effect evaluation, and so forth, This paper will review the latest researches and application progresses of commonly used optical molecular imaging techniques such as bioluminescence imaging and fluorescence molecular imaging.
Diet × genotype interactions in hepatic cholesterol and lipoprotein metabolism in Atlantic salmon (Salmo salar) in response to replacement of dietary fish oil with vegetable oil

The present study investigates the effects of genotype on responses to alternative feeds in Atlantic salmon. Microarray analysis of the liver transcriptome of two family groups, lean or fat, fed a diet containing either a fish oil (FO) or a vegetable oil (VO) blend indicated that pathways of cholesterol and lipoprotein metabolism might be differentially affected by the diet depending on the genetic background of the fish, and this was further investigated by real-time quantitative PCR, plasma and lipoprotein biochemical analysis. Results indicate a reduction in VLDL and LDL levels, with no changes in HDL, when FO is replaced by VO in the lean family group, whereas in fat fish fed FO, levels of apoB-containing lipoproteins were low and comparable with those fed VO in both family groups. Significantly lower levels of plasma TAG and LDL-TAG were measured in the fat group that was independent of diet, whereas plasma cholesterol was significantly higher in fish fed the FO diet in both groups. Hepatic expression of genes involved in cholesterol homeostasis, β-oxidation and lipoprotein metabolism showed relatively subtle changes. A significantly lower expression of genes considered anti-atherogenic in mammals (ATP-binding cassette transporter A1, apoAI, scavenger receptor class B type 1, lipoprotein lipase (LPL)b (TC67836) and LPLc (TC84899)) was found in lean fish, compared with fat fish, when fed VO. Furthermore, the lean family group appeared to show a greater response to diet composition in the cholesterol biosynthesis pathway, mediated by sterol-responsive element-binding protein 2. Finally, the presence of three different transcripts for LPL, with differential patterns of nutritional regulation, was demonstrated.
Structure of TRPV1 channel revealed by electron cryomicroscopy

The transient receptor potential (TRP) family of ion channels participate in many signaling pathways. TRPV1 functions as a molecular integrator of noxious stimuli, including heat, low pH, and chemical ligands. Here, we report the 3D structure of full-length rat TRPV1 channel expressed in the yeast Saccharomyces cerevisiae and purified by immunoaffinity chromatography. We demonstrate that the recombinant purified TRPV1 channel retains its structural and functional integrity and is suitable for structural analysis. The 19-Å structure of TRPV1 determined by using single-particle electron cryomicroscopy exhibits fourfold symmetry and comprises two distinct regions: a large open basket-like domain, likely corresponding to the cytoplasmic N- and C-terminal portions, and a more compact domain, corresponding to the transmembrane portion. The assignment of transmembrane and cytoplasmic regions was supported by fitting crystal structures of the structurally homologous Kv1.2 channel and isolated TRPV1 ankyrin repeats into the TRPV1 structure.
Reducing information redundancy in search results

It is well-known that the web contains many duplicate and near-duplicate documents. Despite the efforts that have been put towards equipping search engines with duplicate detection algorithms, still there are cases where the documents retrieved in response to web queries contain redundant information. In this paper, we are concerned with effectively identifying and reducing redundant information in search results. In particular, we describe how we automatically detect content that is lexically and/or semantically duplicated across search results and we introduce a novel algorithm that upon the detection of significant (i.e., above a given threshold) content duplication, it filters out redundant information. Information filtering takes place in two-steps depending on whether we are dealing with documents of (nearly) identical lexical content or with documents of lexically distinct but semantically equivalent content. In the first case, our algorithm retains in the result list the document that is the most relevant to the query intention and removes duplicates. In the second case, our algorithm merges into a single text, which we call SuperText, the documents of redundant information in a way that every document contributes diverse semantic content to the generated SuperText. Additionally, the algorithm re-ranks the remaining documents based on their contextual relevance to the query intention. The experimental evaluation of our approach demonstrates that it is very effective in identifying lexical and semantic information redundancy across search results. In addition, we have found that our algorithm manages to filter out successfully content duplication from the results list and the SuperTexts it generates for reducing information redundancy are syntactically and semantically coherent texts.
Mid1/Mid2 expression in craniofacial development and a literature review of X‐linked opitz syndrome

Opitz syndrome (OS) is a genetic disorder that affects mainly the development of midline structures, including the craniofacial region, embryonic heart, and urogenital system. The manifestations of X‐linked OS are believed to be results of a malfunctioned gene, MID1, whose product has been shown to have ubiquitin E3 ligase activity and regulate the turnover of microtubular protein phosphatase 2Ac. MID2, a homolog of MID1, shares high structural and functional similarities with MID1. Identification of a missense mutation in MID2 in an Indian family causing overlapping phenotypes with OS provided the first evidence that MID2 might be involved in similar pathogenesis.
Scalable and privacy-respectful interactive discovery of place semantics from human mobility traces

Mobility diaries of a large number of people are needed for assessing transportation infrastructure and spatial development planning. Acquisition of personal mobility diaries through population surveys is a costly and error-prone endeavour. We examine an alternative approach to obtaining similar information from episodic digital traces of people’s presence in various locations, which appear when people use their mobile devices for making phone calls, accessing the Internet or posting georeferenced contents (texts, photos or videos) in social media. Having episodic traces of a person over a long time period, it is possible to detect significant (repeatedly visited) personal places and identify them as home, work or place of social activities based on temporal patterns of a person’s presence in these places. Such analysis, however, can lead to compromising personal privacy. We have investigated the feasibility of deriving place meanings and reconstructing personal mobility diaries while preserving the privacy of individuals whose data are analysed. We have devised a visual analytics approach and a set of supporting tools making such privacy-preserving analysis possible. The approach was tested in two case studies with publicly available data: simulated tracks from the VAST Challenge 2014 and real traces built from georeferenced Twitter posts.
Enhanced distance subset approximation using class-specific subspace kernel representation for kernel approximation

The computational complexity of kernel methods grows at least quadratically with respect to the training size and hence low rank kernel approximation techniques are commonly used. One of the most popular approximations is constructed by sub-sampling the training data. In this paper, we present a sampling algorithm called Enhanced Distance Subset Approximation (EDSA) based on a novel kernel function called CLAss-Specific Kernel (CLASK), which applies the idea of subspace clustering to low rank kernel approximation. By representing the kernel matrix based on a class-specific subspace model, it is allowed to use distinct kernel functions for different classes, which provides a better flexibility compared to classical kernel approximation techniques. Experimental results conducted on various UCI datasets are provided in order to verify the proposed techniques.
How We Recognize Angry and Happy Emotion in People, Places, and Things

Darwin proposed and Ekman and Izard confirmed the presence of cross-cultural regularities in facial displays of emotion. Following their work, the author and his colleagues sought to find parallel mechanisms that would permit these displays to be decoded. A cross-cultural comparison of the display of anger and happiness in masks used in ritual social functions revealed that a set of geometric patterns, rather than actual facial features, conveyed these different emotional meanings. The power of nonrepresentational visual patterns to produce meaning was examined in a series of studies using materials that presented geometric shapes in a variety of line drawings, large-scale physical movement in classical ballet, and configurations among individuals in 17th-century Dutch art. Results across all studies suggested that for the emotions of anger and happiness, at least, meaning is carried in the geometric properties of the visual display.
Clustering Amelioration and Optimization with Swarm Intelligence for Color Image Segmentation

Cluster examination is data mining task for the assignment of collection a set of items in such a path, to the point that questions in the same gathering (called a cluster) are more like one another than to those in different gatherings (clusters). K-means grouping is a technique for group investigation which intends to parcel n perceptions into k groups in which every perception fits in with the cluster with the closest mean. This paper, decided the aftereffect of standard parameter estimations of shading picture division with k-means and the modified k-means with ABC and ACO algorithms. The paper demonstrates that division of color picture with modified k-mean consolidated with swarm Intelligence calculations for color image segmentation gives preferable results over simple k-means and Modified k-means with Ant colony optimization gives better results than modified k-means with Artificial bee colony .
MetaGrad: Faster Convergence Without Curvature in Online Convex Optimization

In online convex optimization it is well known that objective functions with curvature are much easier than arbitrary convex functions. Here we show that the regret can be significantly reduced even without curvature, in cases where there is a stable optimum to converge to. More precisely, the regret of existing methods is determined by the norms of the encountered gradients, and matching worst-case performance lower bounds tell us that this cannot be improved uniformly. Yet we argue that this is a rather pessimistic assessment of the complexity of the problem. We introduce a new parameter-free algorithm, called MetaGrad, for which the gradient norms in the regret are scaled down by the distance to the (unknown) optimum. So when the optimum is reasonably stable over time, making the algorithm converge, this new scaling leads to orders of magnitude smaller regret even when the gradients themselves do not vanish. MetaGrad does not require any manual tuning, but instead tunes a learning rate parameter automatically for the data. Unlike all previous methods with provable guarantees, its learning rates are not monotonically decreasing over time, but instead are based on a novel aggregation technique. We provide two versions of MetaGrad. The first maintains a full covariance matrix to guarantee the sharpest bounds for problems where we can afford update time quadratic in the dimension. The second version maintains only the diagonal. Its linear cost in the dimension makes it suitable for large-scale problems.
Attention and predictions: control of spatial attention beyond the endogenous-exogenous dichotomy

The mechanisms of attention control have been extensively studied with a variety of methodologies in animals and in humans. Human studies using non-invasive imaging techniques highlighted a remarkable difference between the pattern of responses in dorsal fronto-parietal regions vs. ventral fronto-parietal (vFP) regions, primarily lateralized to the right hemisphere. Initially, this distinction at the neuro-physiological level has been related to the distinction between cognitive processes associated with strategic/endogenous vs. stimulus-driven/exogenous of attention control. Nonetheless, quite soon it has become evident that, in almost any situation, attention control entails a complex combination of factors related to both the current sensory input and endogenous aspects associated with the experimental context. Here, we review several of these aspects first discussing the joint contribution of endogenous and stimulus-driven factors during spatial orienting in complex environments and, then, turning to the role of expectations and predictions in spatial re-orienting. We emphasize that strategic factors play a pivotal role for the activation of the ventral system during stimulus-driven control, and that the dorsal system makes use of stimulus-driven signals for top-down control. We conclude that both the dorsal and the vFP networks integrate endogenous and exogenous signals during spatial attention control and that future investigations should manipulate both these factors concurrently, so as to reveal to full extent of these interactions.