Miracle-dz/UniFAR-FTUs huggingface dataset:
Image super-resolution based on patches structure

Due to compression sensing wide research, sparse representation was well applied in super-resolution. At present, super-resolution via sparse representation is performed on the all patches of the image, but it is high time-consuming and its results are not perfect sometime. Considering the difference in the structure of the image patches, we proposed a super-resolution based on image patches structure feature. The method classifies the patches into smooth region and non-smooth region based on gray variance of the patch, and high-resolution and low-resolution dictionaries, for super-resolution via sparse representation, are obtained based on patches structure, and then bicubic interpolation and super-resolution via sparse representation are used to smooth region and non-smooth region respectively. Experiments show that this method can obtain better results and the run-time of image super-resolution is reduced comparison with the Yang et al. [9] method.
Validation of qualitative models of genetic regulatory networks by model checking: analysis of the nutritional stress response in Escherichia coli

MOTIVATION The modeling and simulation of genetic regulatory networks have created the need for tools for model validation. The main challenges of model validation are the achievement of a match between the precision of model predictions and experimental data, as well as the efficient and reliable comparison of the predictions and observations. RESULTS We present an approach towards the validation of models of genetic regulatory networks addressing the above challenges. It combines a method for qualitative modeling and simulation with techniques for model checking, and is supported by a new version of the computer tool Genetic Network Analyzer (GNA). The model-validation approach has been applied to the analysis of the network controlling the nutritional stress response in Escherichia coli. AVAILABILITY GNA and the model of the stress response network are available at http://www-helix.inrialpes. fr/gna.
Improved layout-driven area-constrained timing optimization by net buffering

With the advent of deep sub-micron technologies, interconnect loads and delays have become significant, and layout-driven synthesis has become the need of the day. However, due to the tight layout constraints (e.g., area availability, congestion), only layout-friendly logic transforms such as net buffering and gate resizing can be used effectively. In this paper, we address the problem of minimizing the delay of a mapped, roughly-placed and globally-routed design by buffer insertion and/or deletion without violating the local area constraints imposed by the layout. To the best of our knowledge, only one earlier work has addressed this problem (Murgai, 2000). Although the algorithm presented by Murgai (2000) is optimum for a single net, it has worst-case exponential run-time and is not suitable for large nets. In this paper, we present techniques to make this algorithm practical by improving the run-time without sacrificing the quality. We present a condition called ONPRB, which, if satisfied by the net, improves the worst case runtime complexity to quadratic, without causing a loss in optimality. A study of industrial designs showed that up to 80% of the critical nets satisfied the ONPRB condition. To further reduce the run-time, we propose a technique to convert a net into one that satisfies this condition. Experiments on industrial designs show that the proposed scheme gives up to 12.5 times speed-up over (Murgai, 2000), without sacrificing the design quality (i.e., final delay and area).
Describing MIMO designs for rapid prototyping in the BEE environment

Designing VLSI circuits for efficient stream processing implementations requires the designer to simultaneously consider both algorithmic and hardware architectural trade-offs. Rapid prototyping for such applications implies not only short design time but also satisfying certain design constraints, such as timing and silicon area. Direct-mapping is a method for reasoning about these issues and describing them unambiguously. The BEE (Berkeley Emulation Engine) with its rapid prototyping flow provides the platform for emulating a class of these systems in real-time.
Visualizing the Semantic Structure in Classical Music Works

A major obstacle in the appreciation of classical music is that extensive training is required to understand musical structure and compositional techniques toward comprehending the thoughts behind the musical work. In this paper, we propose an innovative visualization solution to reveal the semantic structure in classical orchestral works such that users can gain insights into musical structure and appreciate the beauty of music. We formulate the semantic structure into macrolevel layer interactions, microlevel theme variations, and macro-micro relationships between themes and layers to abstract the complicated construction of a musical composition. The visualization has been applied with success in understanding some classical music works as supported by highly promising user study results with the general audience and very positive feedback from music students and experts, demonstrating its effectiveness in conveying the sophistication and beauty of classical music to novice users with informative and intuitive displays.
The Equiprobability Bias from a Mathematical and Psychological Perspective

The equiprobability bias (EB) is a tendency to believe that every process in which randomness is involved corresponds to a fair distribution, with equal probabilities for any possible outcome. The EB is known to affect both children and adults, and to increase with probability education. Because it results in probability errors resistant to pedagogical interventions, it has been described as a deep misconception about randomness: the erroneous belief that randomness implies uniformity. In the present paper, we show that the EB is actually not the result of a conceptual error about the definition of randomness. On the contrary, the mathematical theory of randomness does imply uniformity. However, the EB is still a bias, because people tend to assume uniformity even in the case of events that are not random. The pervasiveness of the EB reveals a paradox: The combination of random processes is not necessarily random. The link between the EB and this paradox is discussed, and suggestions are made regarding educational design to overcome difficulties encountered by students as a consequence of the EB.
Development of functional ectopic compound eyes in scarabaeid beetles by knockdown of orthodenticle

Significance From both evolutionary and biomedical perspectives, ectopic organ development is a promising paradigm to investigate the emergence and integration of novel complex structures outside their normal biological context. However, the best known examples of ectopic organ induction require genetic techniques only available for a few model systems. Here, we report the ectopic induction of complex and functional organs, compound eyes, by down-regulation of a single transcription factor through RNAi, a technique known to work well across a broad taxonomic range. These results provide a remarkable example of the ability of developmental systems to channel massive perturbations toward orderly and functional outcomes and open the use of ectopic eyes as an accessible paradigm of ectopic organ development. Complex traits like limbs, brains, or eyes form through coordinated integration of diverse cell fates across developmental space and time, yet understanding how complexity and integration emerge from uniform, undifferentiated precursor tissues remains limited. Here, we use ectopic eye formation as a paradigm to investigate the emergence and integration of novel complex structures following massive ontogenetic perturbation. We show that down-regulation via RNAi of a single head patterning gene—orthodenticle—induces ectopic structures externally resembling compound eyes at the middorsal adult head of both basal and derived scarabaeid beetle species (Onthophagini and Oniticellini). Scanning electron microscopy documents ommatidial organization of these induced structures, while immunohistochemistry reveals the presence of rudimentary ommatidial lenses, crystalline cones, and associated neural-like tissue within them. Further, RNA-sequencing experiments show that after orthodenticle down-regulation, the transcriptional signature of the middorsal head—the location of ectopic eye induction—converges onto that of regular compound eyes, including up-regulation of several retina-specific genes. Finally, a light-aversion behavioral assay to assess functionality reveals that ectopic compound eyes can rescue the ability to respond to visual stimuli when wild-type eyes are surgically removed. Combined, our results show that knockdown of a single gene is sufficient for the middorsal head to acquire the competence to ectopically generate a functional compound eye-like structure. These findings highlight the buffering capacity of developmental systems, allowing massive genetic perturbations to be channeled toward orderly and functional developmental outcomes, and render ectopic eye formation a widely accessible paradigm to study the evolution of complex systems.
Food microbiota diversity

Meat fermentation and fermented sausage manufacturing are ancient processes in Europe, and typical preparations based on fermentations driven by indigenous microflora are still produced by local meat factories or artisanal producers without the use of starter cultures (Rantsiou et al., 2005a; Urso et al., 2006). LAB (Lactic Acid Bacteria) and CNC (Coagulase Negative Cocci) are the two main groups of bacteria with technological value determining the several biochemical and physical reactions taking place during the fermentation and ripening of sausages (Rantsiou & Cocolin 2006). Interest in preserving the biodiversity of microorganisms involved in the fermentation of food products has been reported (EC 1999; Aymerich et al., 2006). As a consequence, and also taking into consideration the technological and economic importance of these microorganisms, the availability of methodologies able to unequivocally characterise single species, potentially right up to strain level, is called for. Identification of species, particularly within the genus Lactobacillus, using phenotypic methods such as sugar fermentation or other biochemical traits, may produce ambiguous results and be complicated because of the presence of several LAB species with similar characteristics (Quere et al., 1997). Molecular methods are nowadays increasingly employed to clarify the taxonomy of microbiota from sausages. The largest number of works is based on RAPD (Random Amplified Polymorphic DNA), (Rebecchi et al., 1998; Rantsiou et al., 2005a), 16S rDNA sequencing (Rantsiou et al., 2005a), PCR-DGGE (Denaturing Gradient Gel Electrophoresis) analysis (Cocolin et al., 2001a; Cocolin et al., 2001b; Comi et al., 2005; Urso et al., 2006), and REA-PFGE (Restriction Endonucleases Analysis Pulsed Field Gel Electrophoresis) analysis (Psoni et al., 2006). The above DNA-based methodologies, with the exception of REA-PFGE, are easy, fast, and provide an accurate identification at species level, but are not as informative when it comes to characterisation of the bacterial population at strain level. Random amplification of polymorphic DNA is useful for performing identification at strain level, but the lack of reproducibility and the lack of complex band patterns, are the main limiting factors. Restriction endonucleases analysis and pulse field gel electrophoresis is a powerful method
Visual context processing in bipolar disorder: a comparison with schizophrenia

Anomalous perception has been investigated extensively in schizophrenia, but it is unclear whether these impairments are specific to schizophrenia or extend to other psychotic disorders. Recent studies of visual context processing in schizophrenia (Tibber et al., 2013; Yang et al., 2013) point to circumscribed, task-specific abnormalities. Here we examined visual contextual processing across a comprehensive set of visual tasks in individuals with bipolar disorder and compared their performance with that of our previously published results from schizophrenia and healthy participants tested on those same tasks. We quantified the degree to which the surrounding visual context alters a center stimulus' appearance for brightness, size, contrast, orientation and motion. Across these tasks, healthy participants showed robust contextual effects, as indicated by pronounced misperceptions of the center stimuli. Participants with bipolar disorder showed contextual effects similar in magnitude to those found in healthy participants on all tasks. This result differs from what we found in schizophrenia participants (Yang et al., 2013) who showed weakened contextual modulations of contrast but intact contextual modulations of perceived luminance and size. Yet in schizophrenia participants, the magnitude of the contrast illusion did not correlate with symptom measures. Performance on the contrast task by the bipolar disorder group also could not be distinguished from that of the schizophrenia group, and this may be attributed to the result that bipolar patients who presented with greater manic symptoms showed weaker contrast modulation. Thus, contrast gain control may be modulated by clinical state in bipolar disorder. Stronger motion and orientation context effects correlated with worse clinical symptoms across both patient groups and especially in schizophrenia participants. These results highlight the complexity of visual context processing in schizophrenia and bipolar disorder.
Motivating factors for physician ordering of factor V Leiden genetic tests.

BACKGROUND The factor V Leiden (FVL) genetic test is used by many physicians despite its uncertain clinical utility. METHODS We investigate whether self-reported motivations and behaviors concerning FVL genetic testing differ between 2 groups of primary care physicians defined by frequency of previous FVL test use. In January 2007, 112 physicians (60 frequent and 52 infrequent FVL test users) at Group Health, a large health care delivery system, were surveyed. Survey content areas included primary reasons and motivating factors for ordering the FVL test, the likelihood of ordering the FVL test for hypothetical patients, potential barriers to genetic testing, and practices and skills regarding FVL test ordering. RESULTS Responses between groups agreed concerning most clinical- and patient-related factors. Frequent-FVL physicians were more likely than infrequent-FVL physicians to report ordering the FVL test for hypothetical patients with mesenteric venous thrombosis (adjusted odds ratio, 4.57; 95% confidence interval, 1.55-13.53) or venous thrombosis after hospital discharge (adjusted odds ratio, 3.42; 95% confidence interval, 1.30-8.95). Frequent-FVL physicians were also less likely to identify several items on the survey as barriers to genetic testing and were more likely to report high confidence in interpreting and explaining FVL test results. CONCLUSIONS Generally, both physician groups reported similar motivating factors for ordering FVL tests, and reported behaviors were consistent with existing guidelines. More striking differences were observed for measures such as barriers to and confidence in using genetic tests. Although additional research is necessary to evaluate the impact of these results, they inform several knowledge-to-practice translation issues that are important for the successful integration of genetic testing into primary care.
On the monodromy at infinity of a polynomial map, II

In the last years a lot of work has been concentrated on the study of the behaviour at infinity of polynomial maps. This behaviour can be very complicated, therefore the main idea was to find special classes of polynomial maps which have, in some sense, nice properties at infinity. In this paper, we completely determine the complex algebraic monodromy at infinity for a special class of polynomial maps (which is complicated enough to show the nature of the general problem).
Adaptation and maladaptation of the heart in diabetes: Part I: general concepts.

Diabetes mellitus (type 2 diabetes) is as much a disease of modern lifestyle as it is a disease of genetic predisposition. Worldwide, there are about 143 million patients with diabetes, almost 5 times more than estimates of 10 years ago.1,2⇓ Heart disease, often presenting as cardiomyopathy, is the leading cause of death among patients with diabetes mellitus (Figure 1). 3 Like diabetes, the prevalence of heart failure also continues to rise in Western countries.4 Diabetes, in turn, is the largest comorbidity of patients with heart failure and adversely affects outcomes of cardiovascular disease.5 The trend is unmistakable; both insulin resistance and heart failure have emerged as major worldwide epidemics. It is therefore timely to take a fresh look at the effects of diabetes on the heart. Figure 1. Multiple Risk Factor Intervention Trial (MRFIT). Age-adjusted cardiovascular disease death rates (per 10 000 person-years) by presence of number of risk factors in men with and without diabetes. Reproduced with permission from Stamler et al.3 Copyright 1993 American Diabetes Association ( Diabetes Care . 1993;16:434–444). Reprinted with permission from the American Diabetes Association. The difficulties in making a causal connection between diabetes and heart failure are formidable. Some simple definitions remain elusive. For example, the distinction between the insulin-deficient (type 1) and insulin-resistant (type 2) forms of diabetes on the one hand, and the distinction between systolic and diastolic dysfunction as causes of heart failure, on the other hand, are hard to define. The known trophic and hemodynamic effects of insulin in healthy individuals,6 the well-described endothelial dysfunction, the deposition of advanced glycation end products, and an accelerated progression of atherosclerosis in patients with diabetes add further complexities to the clinical picture of heart failure in diabetes. Nonetheless, diabetes as a primary cause for heart failure …
Disorder Concept Identification from Clinical Notes: an Experience with the ShARe/CLEF 2013 Challenge

We participated in both tasks 1a and 1b of the ShARe/CLEF 2013 NLP Challenge, where 1a was on detecting disorder concept boundaries and 1b was on assigning concept IDs to the entities from 1a. An existing NLP system developed at Kaiser Permanente was modified to output concepts that were close to the disorder definition of the Challenge. The core pipeline involved deterministic section detection, tokenization, sentence chunking, probabilistic POS tagging, rule-based phrase chunking, terminology look-up (using UMLS 2012AB), rule-based concept disambiguation and post-coordination. The system originally identifies findings (both normal and abnormal), procedures, anatomies, etc., and therefore a post-filter was created to subset the concepts with the source (SNOMED) and semantic types expected by the Challenge. A list of frequency-ranked CUIs was extracted from the training corpus to help break ties when multiple concepts were proposed on a single set of span. However, no retraining/customization was made to meet the boundary annotation preference specified in the challenge guidelines. Our best settings achieved an F-score of 0.503 (was 0.684 with relaxed boundary penalty) in task 1a, and best accuracy of 0.443 (was 0.865 on relaxed boundaries) in task 1b.
Sparse linear modeling of next-generation mRNA sequencing (RNA-Seq) data for isoform discovery and abundance estimation

Since the inception of next-generation mRNA sequencing (RNA-Seq) technology, various attempts have been made to utilize RNA-Seq data in assembling full-length mRNA isoforms de novo and estimating abundance of isoforms. However, for genes with more than a few exons, the problem tends to be challenging and often involves identifiability issues in statistical modeling. We have developed a statistical method called “sparse linear modeling of RNA-Seq data for isoform discovery and abundance estimation” (SLIDE) that takes exon boundaries and RNA-Seq data as input to discern the set of mRNA isoforms that are most likely to present in an RNA-Seq sample. SLIDE is based on a linear model with a design matrix that models the sampling probability of RNA-Seq reads from different mRNA isoforms. To tackle the model unidentifiability issue, SLIDE uses a modified Lasso procedure for parameter estimation. Compared with deterministic isoform assembly algorithms (e.g., Cufflinks), SLIDE considers the stochastic aspects of RNA-Seq reads in exons from different isoforms and thus has increased power in detecting more novel isoforms. Another advantage of SLIDE is its flexibility of incorporating other transcriptomic data such as RACE, CAGE, and EST into its model to further increase isoform discovery accuracy. SLIDE can also work downstream of other RNA-Seq assembly algorithms to integrate newly discovered genes and exons. Besides isoform discovery, SLIDE sequentially uses the same linear model to estimate the abundance of discovered isoforms. Simulation and real data studies show that SLIDE performs as well as or better than major competitors in both isoform discovery and abundance estimation. The SLIDE software package is available at https://sites.google. com/site/jingyijli/SLIDE.zip.
Safe Exploration in Continuous Action Spaces

We address the problem of deploying a reinforcement learning (RL) agent on a physical system such as a datacenter cooling unit or robot, where critical constraints must never be violated. We show how to exploit the typically smooth dynamics of these systems and enable RL algorithms to never violate constraints during learning. Our technique is to directly add to the policy a safety layer that analytically solves an action correction formulation per each state. The novelty of obtaining an elegant closed-form solution is attained due to a linearized model, learned on past trajectories consisting of arbitrary actions. This is to mimic the real-world circumstances where data logs were generated with a behavior policy that is implausible to describe mathematically; such cases render the known safety-aware off-policy methods inapplicable. We demonstrate the efficacy of our approach on new representative physics-based environments, and prevail where reward shaping fails by maintaining zero constraint violations.
Underactuated finger mechanism for natural motion and self-adaptive grasping towards bionic partial hand

This paper presents an underactuated finger mechanism enabling both self-adaptive grasping and natural motion such as flexion and extension. It has three degrees-of-freedom mechanism composed of one actuator and a couple of passive components including torsional springs and mechanical stoppers. In detail, the proposed mechanism consists of two five-bar and one four-bar linkages. Since each five-bar linkage contains passive components, it is allowed to have adaptive grasping as well as natural motion for human finger-like behavior. Kinematics and static force analysis are performed to reveal the operational principle of the proposed mechanism. Finally both simulation and experiments are conducted to show the design feasibility of the proposed mechanism.