Miracle-dz/UniFAR-FTUs huggingface dataset:
Intrinsic Image Decomposition via Structure-Preserving Image Smoothing and Material Recognition

Decoupling shading and reflectance from complex scene-images is a long-standing problem in computer vision. We introduce a framework for decomposing an image into the product of an illumination component and a reflectance component. Due to the ill-posed nature of the problem, prior information on shading and reflectance is mandatory. The proposed method adopts the premise that pixels in a region with similar chromaticity values should have the same reflectance. This assumption was used to minimize the l2 norm of the local per-pixel reflectance gradients to extract the shading and reflectance components. To obtain smooth chromatic regions, texture was treated in a new style. Texture was removed in the first step of the algorithm and the smooth image was processed for intrinsic decomposition. In the final step, texture details were added to the intrinsic components based on the material of each pixel. In addition, user-assistance was used to further refine the results. The qualitative and quantitative evaluation on the MIT intrinsic dataset indicated that the quality of intrinsic image decomposition was improved in comparison with previous methods.
The structure of postsynaptic densities isolated from dog cerebral cortex: II. characterization and arrangement of some of the major proteins within the structure

An attempt was made to identify some of the proteins of the postsynaptic density (PSD) fraction isolated from dog cerebral cortex. The major protein has been tentatively labeled "neurofilament" protein, on the basis of its 51,000 mol wt correspondence to a protein found in neurofilament preparations. Other proteins are akin to some dog myofibrillar proteins, on the basis if immunological crossreaction and equal sodium dodecyl sulfate (SDS)-gel electrophoretic mobilities. While a protein similar to dog muscle myosin is not present in the PSD fraction, a major protein present is actin, as evident from reactivity with antiactin serum, from SDS-gel mobility, and from amino acid composition. Only very little tubulin may be present in the PSD fraction, as determined by gel electrophoresis. Various treatments of the PSD fraction were attempted in order to extract some proteins, as revealed by gel electrophoresis, and to observe the structural changes of the PSD fraction residue after extraction of these proteins. The PSD is remarkably resistant to various extraction conditions, with only 4 M guanidine being found to extract most of the proteins, except the 51,000 mol wt protein. Disulfide reducing agents such as dithiothreitol (DTT), blocking agents such as p-chloromercuribenzoate (PCMB) (both in the presence of deoxycholate [DOC]), a Ca++ extractor, ethylene glycol-bis (beta- aminoethyl ether) N,N,N',N'-tetraacetate (EGTA), and guanidine caused an opening up of the native dense PSD structure, revealing approximately 10-nm filaments, presumably consisting of "neurofilament" protein. Both DTT-DOC and PCMB-DOC removed chiefly actin but also some other proteins. EGTA, in greatly opening up the structure, as observed in the electron microscope, revealed both 10-nm and 3- to 5-nm filaments; the later could be composed of actin, since actin was still in the residue after the treatment. EGTA removed a major 18,000 mol wt component and two minor proteins of 68,000 and 73,000 mol wt. Based on the morphological and biochemical evidence, a picture is presented of the PSD as a structure partly made up of 10-nm and 3- to 5-nm filaments, held together through Ca++ interaction and by bonds amendable to breakage by sulfhydrylblocking and disulfide-reducing reagents; either removal of Ca++ and/or rupture of these disulfide bonds opens up the structure. On the basis of the existence of filamentous proteins and the appearance of the PSD after certain treatments as a closed or open structure, a theory is presented with envisages the PSD to function as a modulator in the conduction of the nerve impulse, by movements of its protein relative.
Development of a Flying Robot With a Pantograph-Based Variable Wing Mechanism

We develop a flying robot with a new pantograph-based variable wing mechanism for horizontal-axis rotorcrafts (cyclogyro rotorcrafts). A key feature of the new mechanism is to have a unique trajectory of variable wings that not only change angles of attack but also expand and contract according to wing positions. As a first step, this paper focuses on demonstrating the possibility of the flying robot with this mechanism. After addressing the pantograph-based variable wing mechanism and its features, a simulation model of this mechanism is constructed. Next, we present some comparison results (between the simulation model and experimental data) for a prototype body with the proposed pantograph-based variable wing mechanism. Both simulation and experimental results show that the flying robot with this new mechanism can generate enough lift forces to keep itself in the air. Furthermore, we construct a more precise simulation model by considering rotational motion of each wing. As a result of optimizing design parameters using the precise simulation model, flight performance experimental results demonstrate that the robot with the optimal design parameters can generate not only enough lift forces but a 155 gf payload as well.
Evidence for a preferential targeting of 3′-UTRs by cis-encoded natural antisense transcripts

Although both the 5′- and 3′-untranslated regions (5′- and 3′-UTRs) of eukaryotic mRNAs may play a crucial role in posttranscriptional gene regulation, we observe that cis-encoded natural antisense RNAs have a striking preferential complementarity to the 3′-UTRs of their target genes in mammalian (human and mouse) genomes. A null neutral model, evoking differences in the rate of 3′-UTR and 5′-UTR extension, could potentially explain high rates of 3′-to-3′ overlap compared with 5′-to-5′ overlap. However, employing a simulation model we show that this null model probably cannot explain the finding that 3′-to-3′ overlapping pairs have a much higher probability (>5 times) of conservation in both mouse and human genomes with the same overlapping pattern than do 5′-to-5′ overlaps. Furthermore, it certainly cannot explain the finding that overlapping pairs seen in both genomes have a significantly higher probability of having co-expression and inverse expression (i.e. characteristic of sense–antisense regulation) than do overlapping pairs seen in only one of the two species. We infer that the function of many 3′-to-3′ overlaps is indeed antisense regulation. These findings underscore the preference for, and conservation of, 3′-UTR-targeted antisense regulation, and the importance of 3′-UTRs in gene regulation.
Book Reviews: Extended Finite State Models of Language

In spite of the wide availability of more powerful (context free, mildly context sensitive, and even Turing-equivalent) formalisms, the bulk of the applied work on language and sublanguage modeling, especially for the purposes of recognition and topic search, is still performed by various finite state methods. In fact, the use of such methods in research labs as well as in applied work actually increased in the past five years. To bring together those developing and using extended finite state methods to text analysis, speech/OCR language modeling, and related CL and NLP tasks with those in AI and CS interested in analyzing and possibly extending the domain of finite state algorithms, a workshop was held in August 1996 in Budapest as part of the European Conference on Artificial Intelligence (ECAI'96).
A weighted pattern recognition algorithm for short-term traffic flow forecasting

The k-nearest neighbor (k-NN) nonparametric regression is a classic model for single point short-term traffic flow forecasting. The traffic flows of the same clock time of the days are viewed as neighbors to each other, and the neighbors with the most similar values are regarded as nearest neighbors and are used for the prediction. In this method, only the information of the neighbors is considered. However, it is observed that the “trends” in the traffic flows are useful for the prediction. Taking a sequence of consecutive time periods and viewing the a sequence of “increasing”, “equal” or “decreasing” of the traffic flows of two consecutive periods as a pattern, it is observed that the patterns can be used for prediction, despite the patterns are not from the same clock time period of the days. Based on this observation, a pattern recognition algorithm is proposed. Moreover, empirically, we find that the patterns from different clock time of the days can have different contributions to the prediction. For example, if both to predict the traffic flow in the morning, the pattern from the morning can lead to better prediction than same patterns from afternoon or evening. In one sentence, we argue that both the pattern and the clock time of the pattern contain useful information for the prediction and we propose the weighted pattern recognition algorithm (WPRA). We give different weights to the same patterns of different clock time for the prediction. In this way, we take both virtues of the k-NN method and the PRA method. We use the root mean square error (RMSE) between the actual traffic flows and the predicted traffic flows as the measurement. By applying the results to actual data and the simulated data, about 20% improvement compare with the PRA is obtained.
Fast Training of Nonlinear Embedding Algorithms

Stochastic neighbor embedding (SNE) and related nonlinear manifold learning algorithms achieve high-quality low-dimensional representations of similarity data, but are notoriously slow to train. We propose a generic formulation of embedding algorithms that includes SNE and other existing algorithms, and study their relation with spectral methods and graph Laplacians. This allows us to define several partial-Hessian optimization strategies, characterize their global and local convergence, and evaluate them empirically. We achieve up to two orders of magnitude speedup over existing training methods with a strategy (which we call the spectral direction) that adds nearly no overhead to the gradient and yet is simple, scalable and applicable to several existing and future embedding algorithms.
Involving patients and the public: how to do it better. Second edition

Climate affects the abundance and distribution of many species of wildlife. Nevertheless, the potential effects of climate on dispersive behaviour remain unstudied. Here, I combine data from (i) a long-term Black-winged Stilt (Himantopus himantopus) monitoring program, (ii) a capture-recapture marking program in Doñana, and (iii) reports from the Rare Birds Committee in the United Kingdom to analyse at different geographical scales the relationship between climate, survival, philopatry, and dispersive behaviour. Black-winged Stilt populations varied in size in consonance with changes in both the North Atlantic Oscillation (NAO) and local rainfall during the breeding season. Changes in population size are related to changes in philopatry and increases in dispersal beyond the traditional range of the species. The results indicate that climatic conditions influence the dispersive behaviour of individual birds, explaining rapid changes in the local population of this species breeding in unstable Mediterranean wetlands.
Mukamel Using hierarchical modeling to measure ICU quality

Electronic Supplementary Material Supplementary Material is available in the online version of this article at http://dx.doi. org/10.1007/s00134-003-1959-9 Abstract Objective: To determine whether hierarchical modeling agrees with conventional logistic regression modeling on the identity of ICU quality outliers within a large multiinstitutional database. Design: Retrospective database analysis. Setting and patients: Subset of the Project IMPACT database consisting of 40,435 adult patients admitted to surgical, medical, and mixed surgicalmedical ICUs (n =55) between 1997 and 1999 who met inclusion criteria for SAPS II. Measurements and results: The SAPS II score was customized to this database using conventional logistic regression and using a hierarchical (random coefficients) model. Both models exhibited excellent discrimination (C statistic) and calibration (Hosmer-Lemeshow statistic). The hierarchical and nonhierarchical models had C statistics of . 870 and . 865, and HL statistics of 3.71 (p>.88, df=8) and 8.94 (p>.35, df=8), respectively. Since the random effects component of the hierarchical model accounts for between-hospital variability, only the fixed-effects coefficients were used to calculate the expected mortality rate based on the hierarchical model. The ratio and 95% confidence intervals of the observed to expected mortality rate were calculated using both models for each ICU. ICUs whose observed/expected ratio was either less than 1 or greater than 1, and whose 95% confidence interval did not include 1 were labeled as either highperformance or low-performance outliers, respectively. Analysis using κ statistic revealed almost perfect agreement between the two models (nonhierarchical vs. hierarchical) on the identity of ICU quality outliers. Conclusions: Models obtained by customizing SAPS II using a nonhierarchical and a hierarchical approach exhibit excellent agreement on the identity of ICU quality outliers.
Genetic and Physiological Improvement of Rice for SubmergenceTolerance

Submergence stress is a major problem in Tamil Nadu during the monsoons. Every year paddy production is greatly affected due to flash floods. A major QTL on chromosome 9, Sub1 has provided the opportunity to apply Marker Assisted Backcrossing (MAB) to develop submergence tolerant versions of rice cultivars that are widely grown in the region. Present study was at aimed at marker assisted introgression of Sub1 locus controlling submergence tolerance from FR 13A into the background of CO 43, a popularly grown rice variety in the cauvery delta region. Molecular markers that were tightly linked with Sub1, flanking Sub1, and unlinked to Sub1 were used for foreground, recombinant, and background selection, respectively, in backcrosses between a submergence tolerant donor, FR 13A and the widely grown recurrent parent, CO 43. Polymorphic markers for foreground and background selection were identified. Genotyping and phenotyping of BC1F1 and F2 generations revealed the superiority of the plants introgressed with Sub1 locus. By the BC2F2 and BC3F3 generations a submergence tolerant plant was identified that possessed 100% CO 43 genome with Sub1 locus. These backcross progenies were evaluated for their tolerance against flooding. All the plants were able to survive 11 days of complete flooding.
A* based joint segmentation and classification of dialog acts in multiparty meetings

We investigate the use of the A* algorithm for joint segmentation and classification of dialog acts (DAs) of the ICSI Meeting Corpus. For the heuristic search a probabilistic framework is used that is based on DA-specific N-gram language models. Furthermore, two new metrics for performance evaluation are motivated and described and the influence of different metrics for performance evaluation is demonstrated. The proposed method is evaluated on both traditional and new metrics, and compared with our previous work on the same task
Dali server: conservation mapping in 3D

Our web site (http://ekhidna.biocenter.helsinki.fi/dali_server) runs the Dali program for protein structure comparison. The web site consists of three parts: (i) the Dali server compares newly solved structures against structures in the Protein Data Bank (PDB), (ii) the Dali database allows browsing precomputed structural neighbourhoods and (iii) the pairwise comparison generates suboptimal alignments for a pair of structures. Each part has its own query form and a common format for the results page. The inputs are either PDB identifiers or novel structures uploaded by the user. The results pages are hyperlinked to aid interactive analysis. The web interface is simple and easy to use. The key purpose of interactive analysis is to check whether conserved residues line up in multiple structural alignments and how conserved residues and ligands cluster together in multiple structure superimpositions. In favourable cases, protein structure comparison can lead to evolutionary discoveries not detected by sequence analysis.
Accelerated DNA Methylation Age: Associations With Posttraumatic Stress Disorder and Mortality.

OBJECTIVE Recently developed indices of cellular age based on DNA methylation (DNAm) data, referred to as DNAm age, are being used to study factors that influence the rate of aging and the health correlates of these metrics of the epigenetic clock. This study evaluated associations between trauma exposure, posttraumatic stress disorder (PTSD) symptoms, and accelerated versus decelerated DNAm age among military veterans. We also examined whether accelerated DNAm age predicted mortality over the course of a 6.5-year medical record review period. METHODS Three hundred thirty-nine genotype-confirmed white, non-Hispanic, middle-aged, trauma-exposed veterans underwent psychiatric assessment and genome-wide DNAm analysis. DNAm age was calculated using a previously validated algorithm. Medical records were available for a subset of 241 veterans and were reviewed approximately 6.5 years after DNA collection and PTSD assessment. RESULTS PTSD hyperarousal symptoms were associated with accelerated DNAm age (β = 0.20, p = .009) but trauma exposure and total PTSD severity were not. Accelerated DNAm age was also associated with 13% increased risk for all-cause mortality (hazard ratio = 1.13, 95% confidence interval = 1.01-1.26) during the medical record review period. CONCLUSIONS Findings of this study replicate the association between PTSD and accelerated DNAm age and suggest that this effect may be specific to the hyperarousal symptom cluster. Results point to the potential utility of DNAm age algorithms for identifying individuals who are aging at an accelerated rate and for determining the factors that influence this process.
Inositol 1, 4, 5-Trisphosphate Receptors and Human Left Ventricular Myocytes

Background— Little is known about the function of inositol 1,4,5-trisphosphate receptors (IP3Rs) in the adult heart experimentally. Moreover, whether these Ca2+ release channels are present and play a critical role in human cardiomyocytes remains to be defined. IP3Rs may be activated after G&agr;q-protein–coupled receptor stimulation, affecting Ca2+ cycling, enhancing myocyte performance, and potentially favoring an increase in the incidence of arrhythmias. Methods and Results— IP3R function was determined in human left ventricular myocytes, and this analysis was integrated with assays in mouse myocytes to identify the mechanisms by which IP3Rs influence the electric and mechanical properties of the myocardium. We report that IP3Rs are expressed and operative in human left ventricular myocytes. After G&agr;q-protein–coupled receptor activation, Ca2+ mobilized from the sarcoplasmic reticulum via IP3Rs contributes to the decrease in resting membrane potential, prolongation of the action potential, and occurrence of early afterdepolarizations. Ca2+ transient amplitude and cell shortening are enhanced, and extrasystolic and dysregulated Ca2+ elevations and contractions become apparent. These alterations in the electromechanical behavior of human cardiomyocytes are coupled with increased isometric twitch of the myocardium and arrhythmic events, suggesting that G&agr;q-protein–coupled receptor activation provides inotropic reserve, which is hampered by electric instability and contractile abnormalities. Additionally, our findings support the notion that increases in Ca2+ load by IP3Rs promote Ca2+ extrusion by forward-mode Na+/Ca2+ exchange, an important mechanism of arrhythmic events. Conclusions— The G&agr;q-protein/coupled receptor/IP3R axis modulates the electromechanical properties of the human myocardium and its propensity to develop arrhythmias.
Long-term survival in a child with severe encephalopathy, multiple respiratory chain deficiency and GFM1 mutations

Background: Mitochondrial diseases due to deficiencies in the mitochondrial oxidative phosphorylation system (OXPHOS) can be associated with nuclear genes involved in mitochondrial translation, causing heterogeneous early onset and often fatal phenotypes. Case report: The authors describe the clinical features and diagnostic workup of an infant who presented with an early onset severe encephalopathy, spastic-dystonic tetraparesis, failure to thrive, seizures and persistent lactic acidemia. Brain imaging revealed thinning of the corpus callosum and diffuse alteration of white matter signal. Genetic investigation confirmed two novel mutations in the GFM1 gene, encoding the mitochondrial translation elongation factor G1 (mtEFG1), resulting in combined deficiencies of OXPHOS. Discussion: The patient shares multiple clinical, laboratory and radiological similarities with the 11 reported patients with mutations involving this gene, but presents with a stable clinical course without metabolic decompensations, rather than a rapidly progressive fatal course. Defects in GFM1 gene confer high susceptibility to neurologic or hepatic dysfunction and this is, to the best of our knowledge, the first described patient who has survived beyond early childhood. Reporting of such cases is essential so as to delineate the key clinical and neuroradiological features of this disease and provide a more comprehensive view of its prognosis.
Combining Heterogenous Social and Geographical Information for Event Recommendation

With the rapid growth of event-based social networks (EBSNs) like Meetup, the demand for event recommendation becomes increasingly urgent. In EBSNs, event recommendation plays a central role in recommending the most relevant events to users who are likely to participate in. Different from traditional recommendation problems, event recommendation encounters three new types of information, i.e., heterogenous online+offline social relationships, geographical features of events and implicit rating data from users. Yet combining the three types of data for offline event recommendation has not been considered. Therefore, we present a Bayesian latent factor model that can unify these data for event recommendation. Experimental results on real-world data sets show the performance of our method.
Lnc2Meth: a manually curated database of regulatory relationships between long non-coding RNAs and DNA methylation associated with human disease

Abstract Lnc2Meth (http://www.bio-bigdata.com/Lnc2Meth/), an interactive resource to identify regulatory relationships between human long non-coding RNAs (lncRNAs) and DNA methylation, is not only a manually curated collection and annotation of experimentally supported lncRNAs-DNA methylation associations but also a platform that effectively integrates tools for calculating and identifying the differentially methylated lncRNAs and protein-coding genes (PCGs) in diverse human diseases. The resource provides: (i) advanced search possibilities, e.g. retrieval of the database by searching the lncRNA symbol of interest, DNA methylation patterns, regulatory mechanisms and disease types; (ii) abundant computationally calculated DNA methylation array profiles for the lncRNAs and PCGs; (iii) the prognostic values for each hit transcript calculated from the patients clinical data; (iv) a genome browser to display the DNA methylation landscape of the lncRNA transcripts for a specific type of disease; (v) tools to re-annotate probes to lncRNA loci and identify the differential methylation patterns for lncRNAs and PCGs with user-supplied external datasets; (vi) an R package (LncDM) to complete the differentially methylated lncRNAs identification and visualization with local computers. Lnc2Meth provides a timely and valuable resource that can be applied to significantly expand our understanding of the regulatory relationships between lncRNAs and DNA methylation in various human diseases.