Miracle-dz/UniFAR-FTUs huggingface dataset:
Kickstarting Deep Reinforcement Learning

We present a method for using previously-trained 'teacher' agents to kickstart the training of a new 'student' agent. To this end, we leverage ideas from policy distillation and population based training. Our method places no constraints on the architecture of the teacher or student agents, and it regulates itself to allow the students to surpass their teachers in performance. We show that, on a challenging and computationally-intensive multi-task benchmark (DMLab-30), kickstarted training improves the data efficiency of new agents, making it significantly easier to iterate on their design. We also show that the same kickstarting pipeline can allow a single student agent to leverage multiple 'expert' teachers which specialize on individual tasks. In this setting kickstarting yields surprisingly large gains, with the kickstarted agent matching the performance of an agent trained from scratch in almost 10x fewer steps, and surpassing its final performance by 42 percent. Kickstarting is conceptually simple and can easily be incorporated into reinforcement learning experiments.
Impact of mild to moderate COPD on feasibility and prognosis in non-small cell lung cancer patients who received chemotherapy

Background Non-small cell lung cancer (NSCLC) is the predominant cause of death in patients with COPD, and the severity of COPD in NSCLC patients is classified mainly as mild to moderate. Most advanced NSCLC patients with mild to moderate COPD are treated with chemotherapy; however, the feasibility for and prognosis after chemotherapy of these patients are not well understood. The aim of this study was to elucidate the impact of mild to moderate COPD on the feasibility for and prognosis after chemotherapy in NSCLC patients. Patients and methods A retrospective review was performed on 268 NSCLC patients who received first-line chemotherapy from 2009 to 2014 in our institution. Finally, 85 evaluable patients were included in this study. The clinical characteristics, toxicity profile, objective response rate, and prognosis were analyzed and compared between patients with mild to moderate COPD and those without COPD (non-COPD). Results Forty-three patients were classified as COPD (27 cases mild and 16 cases moderate) and 42 patients as non-COPD. The COPD group were older and had fewer never-smokers than the non-COPD group. The objective response rate did not differ between groups (p=0.14). There was no significant difference in overall survival between COPD and non-COPD groups (15.0 and 17.0 months, log-rank test p=0.57). In the multivariate Cox’s proportional hazard model, the adjusted hazard ratio (HRadj) was statistically significant for male sex (HRadj =5.382, 95% CI: 1.496–19.359; p=0.010), pathological diagnosis of adenocarcinoma (HRadj =0.460, 95% CI: 0.223–0.948; p=0.035), and epithelial growth factor receptor negative mutation (HRadj =6.040, 95% CI: 1.158–31.497; p=0.033), but not for the presence of COPD (HRadj =0.661, 95% CI: 0.330–1.325; p=0.24). Toxicity profile in COPD group was favorable, as in the non-COPD group. Conclusion Mild to moderate COPD did not have a significant deleterious impact on toxicity and prognosis in NSCLC patients.
Superplasticity of Metallic Alloys: Some Current Findings and Open Questions

Superplasticity of metallic alloys has been widely investigated for many years but despite numerous studies, some important questions regarding superplastic behavior of metals can be considered as still open. Among others, one can mention the role of grain boundary sliding as contributing mechanism of deformation, the microstructural requirements for getting superplasticity in metallic alloys or the link between mechanisms of deformation and mechanisms of damage. Interesting information were recently obtained by the use of new experimental techniques. One can mention for instance the development of fine grids allowing more detailed studies of the respective contributions of intra-and inter-granular strains in superplastic alloys or fast X-ray micro tomography allowing in situ 3D damage studies. The aim of this paper is to give information about current findings related to superplastic deformation of metallic alloys and to suggest some perspectives for future.
Methodological challenges in research on sexual risk behavior: I. Item content, scaling, and data analytical options

Investigation of sexual behavior involves many challenges, including how to assess sexual behavior and how to analyze the resulting data. Sexual behavior can be assessed using absolute frequency measures (also known as counts) or with relative frequency measures (e.g., rating scales that range from never to always). We discuss these 2 assessment approaches in the context of research on HIV risk behavior. We conclude that these 2 approaches yield nonredundant information and, more important, that only data yielding information about the absolute frequency of risk behavior have the potential to serve as valid indicators of HIV contraction risk. However, analyses of count data may be challenging because of non-normal distributions with many outliers. Therefore, we identify new and powerful data analytical solutions that have been developed recently to analyze count data and discuss limitations of’acommonly appliedmethod(viz., analysis of covariance using baseline scores as covariates).
PERFORMANCE OF RECYCLED HOT MIX ASPHALT MIXTURES

This research project was undertaken to evaluate the performance of recycled pavements in comparison to virgin (control) asphalt pavements. Five projects, each consisting of a recycled section and a control section, were subjected to detailed evaluation. In-situ mix properties (such as percent air voids, resilient modulus and indirect tensile strength), recovered asphalt binder properties (such as penetration, viscosity, G*/sino and G*sino), and laboratory recompacted mix properties (such as Gyrator Stability Index and confined dynamic creep modulus) were measured. A paired t-test statistical analysis indicated no significant differences between these properties of virgin and recycled mix pavements which have been in service from 1 1/2 to 2 1/4 years. Ten additional virgin mix pavements and 13 additional recycled pavements were also evaluated as two independent groups. No statistically significant differences were found between the recovered asphalt properties (penetration and viscosity) of these virgin and recycled pavements in service. The current Georgia Department of Transportation recycling specifications and mix design procedures appear to be satisfactory based on the results of this study.
Mapping Urban Impervious Surface by Fusing Optical and SAR Data at the Decision Level

The proliferation of impervious surfaces results in a series of environmental issues, such as the decrease of vegetated areas and the aggravation of the urban heat island effects. The mapping of impervious surface and its spatial distributions is of significance for the ecological study of urban environment. Currently, the integration of optical and synthetic aperture radar (SAR) data has shown advantages in accurately characterizing impervious surface. However, the fusion mainly occurs at the pixel and feature levels which are subject to influences of data noises and feature selections, respectively. In this paper, an innovative and effective method was developed to extract urban impervious surface by synergistically utilizing optical and SAR images at the decision level. The objective of this paper was to obtain an accurate urban impervious surface map based on the random forest classifier and the evidence theory and to provide a detailed uncertainty analysis accompanying the fused impervious surface maps. In this study, both the GaoFen (GF-1) and Sentinel-1A imagery were first used as independent data sources for mapping urban impervious surfaces. Then additional spectral features and texture features were extracted and integrated with the original GF-1 and Sentinel-1A images in generating impervious surfaces. Finally, based on the Dempster-Shafer (D-S) theory, impervious surfaces were produced by fusing the previously estimated impervious surfaces from different datasets at the decision level. Results showed that impervious surfaces estimated from the combined use of original images and features yielded a higher accuracy than those from the original optical or SAR data. Further validations suggested that optical data was better than SAR data in separating impervious surfaces from non-impervious surfaces. The fused impervious surfaces at the decision level had a higher overall accuracy than those produced independently by optical or SAR data. It was also highlighted that the fusion of GF-1 and Sentinel-1A images reduced the amount of confusions among the low reflectance of impervious surface and water, as well as for low reflectance of bare land. An overall accuracy of 95.33% was achieved for extracting urban impervious surfaces by fused datasets. The spatial distributions of uncertainties provided by the evidence theory displayed a confidence level of at least 75% for the impervious surfaces derived from the fused datasets.
A Novel Architecture for FPGA Implementation of Otsu's Global Automatic Image Thresholding Algorithm

Otsu's global automatic image thresholding technique is widely used in various computer vision-based applications. This paper presents a resource-efficient architecture for the design of Otsu's thresholding algorithm and its implementation in field-programmable gate array (FPGA). The proposed architecture is implemented for a 640x480 size of input image that is captured by a real-time high-resolution analog camera and buffered in a DDR2 SDRAM memory. The computation of between-class variance in Otsu's algorithm requires the evaluation of a normalized cumulative histogram, mean and cumulative moments, which need single-cycle read-modify-write operations. These operations are achieved by incorporating the FPGA's slices, dual-port Block RAM memories and DSP slices with DDR2 SDRAM as a frame buffer. The data path of the architecture is fixed-point arithmetic based and it does not require any divider. The proposed design is implemented in Xilinx Virtex-5 xc5vfx70tffg1136-1 FPGA device, available on the Xilinx ML-507 platform. In order to develop the required hardware and software in an integrated method, the Xilinx Embedded Development Kit (EDK) design tool is used.
Deterministic Communication in Radio Networks

In this paper we improve the deterministic complexity of two fundamental communication primitives in the classical model of ad-hoc radio networks with unknown topology: broadcasting and wake-up. We consider an unknown radio network, in which all nodes have no prior knowledge about network topology, and know only the size of the network n, the maximum in-degree of any node Delta, and the eccentricity of the network D. For such networks, we first give an algorithm for wake-up, in both directed and undirected networks, based on the existence of small universal synchronizers. This algorithm runs in O((min{n,D*Delta}*log(n)*log(Delta))/(log(log(Delta)))) time, improving over the previous best O(n*log^2(n))-time result across all ranges of parameters, but particularly when maximum in-degree is small. Next, we introduce a new combinatorial framework of block synchronizers and prove the existence of such objects of low size. Using this framework, we design a new deterministic algorithm for the fundamental problem of broadcasting, running in O(n*log(D)*log(log((D*Delta)/n))) time. This is the fastest known algorithm for this problems, improving upon the O(n*log(n)*log*log(n))-time algorithm of De Marco (2010) and the O(n*log^2(D))-time algorithm due to Czumaj and Rytter (2003), the previous fastest results for directed networks, and is the first to come within a log-logarithmic factor of the Omega(n*log(D)) lower bound due to Clementi et al. (2003). Our results have also direct implications on the fastest deterministic leader election and clock synchronization algorithms in both directed and undirected radio networks, tasks which are commonly used as building blocks for more complex procedures.
Hysteroscopy in Abnormal Uterine Bleeding vs Ultrasonography and Histopathology Report in Perimenopausal and Postmenopausal Women.

INTRODUCTION Abnormal uterine bleeding is one of the most common morbidity landing women to attend medical attention in gynecology outpatient department. This study aims to evaluate the hysteroscopy finding in diagnosis of AUB and its correlation with ultrasonography finding and histopathological reports. METHODS This was a prospective comparative study in which ultrasonography was performed in fifty patients with abnormal uterine bleeding attending OPD then hysteroscopy was performed.After removing hysteroscopy dilation and curettage was done and sample sent for histopathology.At the end reports of hysteroscopy finding were compared with sonograhic and pathological results. RESULTS In the study women aged from 45 to 64 years with the symptoms duration of 15 days to 6 months. Post menopausal women seek medical attention more early then the menstruating women.Common symptoms are menorrhagia, metrorrhagia and postmenopausal bleeding. Most common abnormality was menorrhagia (32%) followed by post menopausal bleeding 28 %. Ultrasonography showed 46% of abnormal finding in which 17 (47%) menstruating women and 6 (43%) women were postmenopausal women. Among 50 women 17 (34%) had negative finding and 43 (66%) had abnormal finding in which most common finding of hyperplastic endometrium. Hysteroscopy correctly diagnose atrophic endometrium, polyp and endometrial Ca which is also confirmed by histopathology finding. CONCLUSIONS Hysteroscopy is reliable method for evaluating cases of AUB and it can be used as first line diagnostic method for benign lesions. Hysteroscopy guided biopsy has most accurate in diagnosing pathology.
Illegal captive lemurs in Madagascar: Comparing the use of online and in‐person data collection methods

Although it is illegal to capture, sell, and trade lemurs, the live capture of lemurs in Madagascar is ongoing and may have impacted over 28,000 lemurs between 2010 and 2013. Only one study has examined this trade and did so using in‐person interviews in northern Madagascar. The current study sought to expand this existing dataset and examine the comparability of online surveys to more traditional on‐location data collection methods. In this study, we collected data through a web‐based survey resulting in 302 sightings of 685 captive lemurs. We also collected data from 171 hotel and 43 restaurant websites and social media profiles. Survey submissions included sightings of 30 species from 10 genera, nearly twice as many species as identified via the in‐person interviews. Lemur catta, Varecia variegata, and Eulemur fulvus were the most common species sighted in captivity. Captive lemurs were reported in 19 of Madagascar's 22 administrative regions and most were seen in urban areas near their habitat ranges. This represents a wider geographic distribution of captive lemurs than previously found through in‐person interviews. The online survey results were broadly similar to those of the in‐person surveys though greater in species and geographic diversity demonstrating advantages to the use of online surveys. The online research methods were low in cost (USD $100) compared to on‐location data collection (USD $12,000). Identified disadvantages included sample bias; most of the respondents to the online survey were researchers and many captive sightings were near study sites. The results illustrate the benefits of incorporating a social science approach using online surveys as a complement to traditional fieldwork. Am. J. Primatol. 79:e22541, 2017. © 2016 Wiley Periodicals, Inc.
Computational Prediction of Intronic microRNA Targets using Host Gene Expression Reveals Novel Regulatory Mechanisms

Approximately half of known human miRNAs are located in the introns of protein coding genes. Some of these intronic miRNAs are only expressed when their host gene is and, as such, their steady state expression levels are highly correlated with those of the host gene's mRNA. Recently host gene expression levels have been used to predict the targets of intronic miRNAs by identifying other mRNAs that they have consistent negative correlation with. This is a potentially powerful approach because it allows a large number of expression profiling studies to be used but needs refinement because mRNAs can be targeted by multiple miRNAs and not all intronic miRNAs are co-expressed with their host genes. Here we introduce InMiR, a new computational method that uses a linear-Gaussian model to predict the targets of intronic miRNAs based on the expression profiles of their host genes across a large number of datasets. Our method recovers nearly twice as many true positives at the same fixed false positive rate as a comparable method that only considers correlations. Through an analysis of 140 Affymetrix datasets from Gene Expression Omnibus, we build a network of 19,926 interactions among 57 intronic miRNAs and 3,864 targets. InMiR can also predict which host genes have expression profiles that are good surrogates for those of their intronic miRNAs. Host genes that InMiR predicts are bad surrogates contain significantly more miRNA target sites in their 3′ UTRs and are significantly more likely to have predicted Pol II and Pol III promoters in their introns. We provide a dataset of 1,935 predicted mRNA targets for 22 intronic miRNAs. These prediction are supported both by sequence features and expression. By combining our results with previous reports, we distinguish three classes of intronic miRNAs: Those that are tightly regulated with their host gene; those that are likely to be expressed from the same promoter but whose host gene is highly regulated by miRNAs; and those likely to have independent promoters.
of Geophysical Research : Solid Earth Investigating Compaction by Intergranular Pressure Solution Using the Discrete Element Method

Intergranular pressure solution creep is an important deformation mechanism in the Earth’s crust. The phenomenon has been frequently studied and several analytical models have been proposed that describe its constitutive behavior. These models require assumptions regarding the geometry of the aggregate and the grain size distribution in order to solve for the contact stresses and often neglect shear tractions. Furthermore, analytical models tend to overestimate experimental compaction rates at low porosities, an observation for which the underlying mechanisms remain to be elucidated. Here we present a conceptually simple, 3-D discrete element method (DEM) approach for simulating intergranular pressure solution creep that explicitly models individual grains, relaxing many of the assumptions that are required by analytical models. The DEM model is validated against experiments by direct comparison of macroscopic sample compaction rates. Furthermore, the sensitivity of the overall DEM compaction rate to the grain size and applied stress is tested. The effects of the interparticle friction and of a distributed grain size on macroscopic strain rates are subsequently investigated. Overall, we find that the DEM model is capable of reproducing realistic compaction behavior, and that the strain rates produced by the model are in good agreement with uniaxial compaction experiments. Characteristic features, such as the dependence of the strain rate on grain size and applied stress, as predicted by analytical models, are also observed in the simulations. DEM results show that interparticle friction and a distributed grain size affect the compaction rates by less than half an order of magnitude.
The Catechol-O-Methyltransferase (COMT) val158met Polymorphism Affects Brain Responses to Repeated Painful Stimuli

Despite the explosion of interest in the genetic underpinnings of individual differences in pain sensitivity, conflicting findings have emerged for most of the identified “pain genes”. Perhaps the prime example of this inconsistency is represented by catechol-O-methyltransferase (COMT), as its substantial association to pain sensitivity has been reported in various studies, but rejected in several others. In line with findings from behavioral studies, we hypothesized that the effect of COMT on pain processing would become apparent only when the pain system was adequately challenged (i.e., after repeated pain stimulation). In the present study, we used functional Magnetic Resonance Imaging (fMRI) to investigate the brain response to heat pain stimuli in 54 subjects genotyped for the common COMT val158met polymorphism (val/val = n 22, val/met = n 20, met/met = n 12). Met/met subjects exhibited stronger pain-related fMRI signals than val/val in several brain structures, including the periaqueductal gray matter, lingual gyrus, cerebellum, hippocampal formation and precuneus. These effects were observed only for high intensity pain stimuli after repeated administration. In spite of our relatively small sample size, our results suggest that COMT appears to affect pain processing. Our data demonstrate that the effect of COMT on pain processing can be detected in presence of 1) a sufficiently robust challenge to the pain system to detect a genotype effect, and/or 2) the recruitment of pain-dampening compensatory mechanisms by the putatively more pain sensitive met homozygotes. These findings may help explain the inconsistencies in reported findings of the impact of COMT in pain regulation.
Improving zero-training brain-computer interfaces by mixing model estimators

Objective. Brain-computer interfaces (BCI) based on event-related potentials (ERP) incorporate a decoder to classify recorded brain signals and subsequently select a control signal that drives a computer application. Standard supervised BCI decoders require a tedious calibration procedure prior to every session. Several unsupervised classification methods have been proposed that tune the decoder during actual use and as such omit this calibration. Each of these methods has its own strengths and weaknesses. Our aim is to improve overall accuracy of ERP-based BCIs without calibration. Approach. We consider two approaches for unsupervised classification of ERP signals. Learning from label proportions (LLP) was recently shown to be guaranteed to converge to a supervised decoder when enough data is available. In contrast, the formerly proposed expectation maximization (EM) based decoding for ERP–BCI does not have this guarantee. However, while this decoder has high variance due to random initialization of its parameters, it obtains a higher accuracy faster than LLP when the initialization is good. We introduce a method to optimally combine these two unsupervised decoding methods, letting one method’s strengths compensate for the weaknesses of the other and vice versa. The new method is compared to the aforementioned methods in a resimulation of an experiment with a visual speller. Main results. Analysis of the experimental results shows that the new method exceeds the performance of the previous unsupervised classification approaches in terms of ERP classification accuracy and symbol selection accuracy during the spelling experiment. Furthermore, the method shows less dependency on random initialization of model parameters and is consequently more reliable. Significance. Improving the accuracy and subsequent reliability of calibrationless BCIs makes these systems more appealing for frequent use.