Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic diversity of three ornamental reef fishes ( Families Pomacanthidae and Chaetodontidae ) from the Brazilian coast Affonso , PRAM

Reef fishes of the families Pomacanthidae (angelfish) and Chaetodontidae (butterflyfish) are popular ornamental species, intensively harvested for the aquarium trade. The impacts of such activity on intra-specific diversity and reef ecosystems are still poorly understood in the south Atlantic. In the present work, a fine-scale genetic analysis using RAPD markers was performed in distinct samples of the queen angelfish (Holacanthus ciliaris), French angelfish (Pomacanthus paru), and banded butterflyfish (Chaetodon striatus) along the Brazilian coast. Most of the genetic variation in the three species was related to intra-population diversity. However, AMOVA results demonstrated that H. ciliaris presents a subtle population structure (φ st = 0.132, P = 0.003), while P. paru and C. striatus present low genetic differentiation, especially remarkable in the latter (φ st = 0.090, P = 0.001 and φ st = 0.041, P = 0.028, respectively). Gene flow (Nm) was also higher in C. striatus than in the angelfish species. The reported patterns of genetic differentiation contrast with the similar pelagic stage of the selected species, suggesting that larval dispersal per se is a poor predictor of population structure in these reef fishes. Ecological features coupled with biogeographic history and distinct local selective pressures might play a major role on the genetic composition of each species. Although preliminary, the present results provide a baseline for monitoring the genetic variability in these reef species. These differences in the genetic structure among co-occurring species should be taken into consideration for the conservation of eventual evolutionary units along the Brazilian Province.
Reconstructing Thin Structures of Manifold Surfaces by Integrating Spatial Curves

The manifold surface reconstruction in multi-view stereo often fails in retaining thin structures due to incomplete and noisy reconstructed point clouds. In this paper, we address this problem by leveraging spatial curves. The curve representation in nature is advantageous in modeling thin and elongated structures, implying topology and connectivity information of the underlying geometry, which exactly compensates the weakness of scattered point clouds. We present a novel surface reconstruction method using both curves and point clouds. First, we propose a 3D curve reconstruction algorithm based on the initialize-optimize-extend strategy. Then, tetrahedra are constructed from points and curves, where the volumes of thin structures are robustly preserved by the Curve-conformed Delaunay Refinement. Finally, the mesh surface is extracted from tetrahedra by a graph optimization. The method has been intensively evaluated on both synthetic and real-world datasets, showing significant improvements over state-of-the-art methods.
The Brazilian stock market of the new millennium: an efficiency test

According to the Hypothesis of Efficient Market - HME, proposed by Fama (1970), in its weak form, an investor doesn’t get to predict the stock returns based on historical returns and thus doesn’t get abnormal returns in a consistent way. This paper is concerned verifying HME, in the weak form, in the Brazilian stock market by the analysis of fifty more negotiated stocks in BOVESPA since 2000 until 2007. The methodology was used based in the ARIMA models of time series and serial correlation tests of returns to prove or not the random behavior of the stock returns. The results had shown that Brazilian capital market did not evidence characteristics of an efficient market, in the weak form, in the considered period.
Tihonov theory and center manifolds for inhibitory mechanisms in enzyme kinetics

Abstract In this paper we study the chemical reaction of inhibition, determine the appropriate parameter ε for the application of Tihonov's Theorem, compute explicitly the equations of the center manifold of the system and find sufficient conditions to guarantee that in the phase space the curves which relate the behavior of the complexes to the substrates by means of the tQSSA are asymptotically equivalent to the center manifold of the system. Some numerical results are discussed.
Bayesian clustering algorithms ascertaining spatial population structure: a new computer program and a comparison study

On the basis of simulated data, this study compares the relative performances of the Bayesian clustering computer programs STRUCTURE, GENELAND, GENECLUST and a new program named TESS. While these four programs can detect population genetic structure from multilocus genotypes, only the last three ones include simultaneous analysis from geographical data. The programs are compared with respect to their abilities to infer the number of populations, to estimate membership probabilities, and to detect genetic discontinuities and clinal variation. The results suggest that combining analyses using TESS and STRUCTURE offers a convenient way to address inference of spatial population structure.
Enhanced 5G Cognitive Radio Networks Based on Spectrum Sharing and Spectrum Aggregation

In this paper, new enhanced cognitive radio networks (E-CRNs) based on spectrum sharing (SS) and spectrum aggregation (SA) are proposed for fifth generation (5G) wireless networks. The E-CRNs jointly exploit the licensed spectrum shared with the primary user (PU) networks and the unlicensed spectrum aggregated from the industrial, scientific, and medical bands. The PU networks include TV systems in TV white space and different incumbent systems in the long term evolution time division duplexing bands. The harmful interference from the E-CRNs to the PU networks are delicately controlled. Furthermore, the coexistence between the E-CRNs and other unlicensed systems, such as WiFi, is studied. The E-CRNs framework including dynamic spectrum management (DSM) is designed for the key parameters of licensed SS and unlicensed SA. The essential tradeoff between sharing efficiency and aggregation efficiency for the E-CRNs is discussed. Based on this tradeoff, a spectrum lean-management scheme is proposed to fulfill the DSM. Moreover, a water-filling algorithm is designed to dynamically access the available spectrum. Numerical results demonstrate that the proposed E-CRNs can significantly improve the system performance in terms of data rate, outage probability, and spectrum efficiency. In particular, the E-CRNs framework provides a spectrum usage prototype for 5G wireless communication networks.
Applying Rule-Based Maximum Matching Approach for Verb Phrase Identification and Translation ( Myanmar to English )

Phrase Identification is one of the most critical and widely studied in Natural Language processing (NLP) tasks. Verb Phrase Identification within a sentence is very useful for a variety of application on NLP. One of the core enabling technologies required in NLP applications is a Morphological Analysis. This paper presents the Myanmar Verb Phrase Identification and Translation Algorithm and develops a Markov Model with Morphological Analysis. The system is based on Rule-Based Maximum Matching Approach. In Machine Translation, Large amount of information is needed to guide the translation process. Myanmar Language is inflected language and there are very few creations and researches of Lexicon in Myanmar, comparing to other language such as English, French and Czech etc. Therefore, this system is proposed Myanmar Verb Phrase identification and translation model based on Syntactic Structure and Morphology of Myanmar Language by using MyanmarEnglish bilingual lexicon. Markov Model is also used to reformulate the translation probability of Phrase pairs. Experiment results showed that proposed system can improve translation quality by applying morphological analysis on Myanmar Language.
The TH17/Treg Imbalance in Rheumatoid Arthritis and Relation to Disease Activity

Objectives: T regulatory cells (Treg) and proinflammatory TH17 cells are newly identified T lymphocyte subsets, which have significant effects on autoimmunity and inflammation. Tregs play key role in the maintenance of self-tolerance. TH17/Treg disturbed balance has been reported to contribute to several autoimmune diseases.Our aim was to assess the Treg/TH17 pattern and TH17 related cytokines, in peripheral blood of Egyptian rheumatoid arthritis patients, and their relation to disease activity score (DAS). Analyzing IL17A and IL23 as indicators of TH17 function, was to study the effect of TH17 in RA.Methods: 100 Egyptian rheumatoid arthritis patients, divided into Group I (14), Group II (48), Group III (38), with low 5.1, activity DAS score respectively; and 50 healthy age and sex matched controls were enrolled. Peripheral blood TH17 and Treg (CD4+CD25+Foxp3+) frequencies were analyzed by flowcytometry, and the serum levels of interleukins (IL17A), (IL23) were determined by ELISA.Results: Active RA patients (groups II and III) revealed an obvious increase in peripheral TH17 frequencies, and levels of TH17-related cytokines, and a significant decrease in Treg (CD4+CD25+Foxp3+) frequencies in group III, when compared to healthy controls. TH17/Treg ratios were positively correlated with serum concentrations of IL17A and IL23 cytokines. Frequencies and levels showed statistical significant correlation with DAS scoring.Conclusions: Our study indicated that TH17/Treg balance was disturbed in peripheral blood of RA patients, leading to an increase of proinflammatory cytokines, correlating with DAS, and suggesting an important role in the development of RA.
Wakes-Ship Removal on High-Resolution Optical Images based on Histograms in HSV Color Space

Ship detection on optical remote sensing images is getting great attention; however, some images called wakes-ship have not been taken into account yet. Current works in ship detection are focusing on in-shore detection where ships are in calm; furthermore, their methods get high Intersection Over Union (IoU), above 70%, but when computing IoU using only wakes-ship images the ratio is 22%. In this paper, it is presented a new framework to improve ship segmentation on wakes-ship images. In order to achieve this goal, it was considered HSV color space and histograms. First, ship detection was done using state-of-the-art ship detection methods. Second, bin histograms in HSV color space was used to get the colors that rely on wakes. Finally, the removal of wakes from ships was done using some discriminative properties. In this way, the increase of the IoU performance at wake-ship segmentation goes from 22% to 63%, which is an improvement of 186%.
Limitations of using bags of complex features: Hierarchical higher-order filters fail to capture spatial configurations

One common method of representing images is to reduce an image to a collection of features. Many simple features have been proposed, such as pixel intensities and wavelet responses, but these choices are fundamentally unsuitable for capturing the configural relations of objects and object parts, as spatial information associated with each feature is lost. Another recent strategy, known as “feature-hierarchy” modeling, involves the use of overlapping, redundant features. These features are obtained by processing an image across a hierarchy of units tuned to progressively more complex properties. An open question is whether such approaches produce data structures rich enough for implicitly capturing configural relations. We implemented three experiments and several computer simulations to address this issue. Our method involved the use of four classes of objects, each derived from the simple spatial relationships present in classic Vernier and bisection acuity tasks. All human observers achieved near perfect categorization performance after relatively few exposures to each stimulus class. This ability also transferred across several dimensions, including orientation and background context. By contrast, simulations on a featurehierarchy model revealed poor performance for this class of models. Furthermore, the moderate categorization accuracy achieved did not transfer across even the simplest of dimensions. These results indicate that this approach to image representation lacks a fundamental property necessary for encoding the spatial configurations of object parts.
An Experimental Investigation of Vagueness on the Left Side of Balance Sheet

We investigated through experiments vagueness among property, plant, and equipment (PPE), intangible asset and inventory accounts. To semantic vagueness among items, epistemic vagueness is added in relation to liquidity order classification. Traditional dichotomy current/non-current classification of balance sheet items seems to have been used as a straitjacket, where inventories are current assets, and PPE and intangibles are non-current assets. While gray zone is ignored, items that lay on that are swept under the rug, i.e. arbitrarily classified in one way or another, hence, information asymmetry persists, and is neglected by auditors and standard setters. Literature suggests that the increase of information about underling economic transactions mitigate vagueness. Through the configurational approach, we identified five arrangements according to the intensity of property rights transference. Information about those five arrangements was provided to subjects. Evidences from between-subjects experiments (subjects were 93 MBA students enrolled on Accounting courses) suggest that the argued vagueness is acknowledge by financial statements users.
Answering What If, Should I, and Other Expectation Exploration Queries Using Causal Inference over Longitudinal Data

Many people use web search engines for expectation exploration: exploring what might happen if they take some action, or how they should expect some situation to evolve. While search engines have databases to provide structured answers to many questions, there is no database about the outcomes of actions or the evolution of situations. The information we need to answer such questions, however, is already being recorded. On social media, for example, hundreds of millions of people are publicly reporting about the actions they take and the situations they are in, and an increasing range of events and activities experienced in their lives over time. Here, we show how causal inference methods can be applied to such data to generate answers for expectation exploration queries. This paper describes a system implementation for running ad-hoc online causal inference analyses. The analysis results can be used to generate pros/cons lists for decision support, timeline representations to show how situations evolve, and be embedded in many other decision support and planning applications. We discuss potential methods for evaluating the fundamental quality of inference results and judge the short-term and long-term usefulness of information for users.
Enhanced Textual Password Scheme for Better Security and Memorability

Traditional textual password scheme provides a large number of password combinations but users generally use a small portion of available password space. Complex textual passwords are difficult to remember, therefore most users choose passwords with small length and contain dictionary words. Due to the use of small password length and dictionary words, textual passwords become easy to crack through offline guessability attacks. Traditional textual passwords scheme is also weak against keystroke logger attacks because alphanumeric characters are directly inserted into the password field. In this paper, enhancements are proposed in the registration and login screen of the traditional textual password scheme for improving security against offline guessability attacks and keystroke logger attacks. The proposed registration screen also improve memorability of traditional textual passwords through visual cues or pattern-based approach. In the proposed login screen, passwords are indirectly inserted into the password field, to resist keystroke logger attacks. A comparative analysis between the passwords created in traditional and proposed pattern-based approach is presented. The testing results show that users create strong and high entropy passwords in the proposed pattern-based approach as compared to the traditional textual passwords approach.
Related Factors Associated with Quality of life Assessed Using a ChineseVersion of the MOS-HIV Health Survey in People with HIV/AIDS in China

Objectives: To evaluate the Chinese version of the 35-item Medical Outcomes Study HIV Health Survey (MOSHIV) in people living with HIV/AIDS (PLWHA) in mainland China and to study its relationship with socio-demographic characteristics and disease-related factors. Methods: 222 PLWHA recruited from outpatient clinics in Hunan province completed measures of quality of life and related factors. Results: Internal consistency of the overall score on the Chinese version of the MOS-HIV was high (α=0.95); internal consistency of the eight subscales was also high (α=0.79-0.91). Factor analysis of the MOS-HIV revealed a one-factor solution, accounting for 54.97% of the total variance. At linear regression analysis, all domains of quality of life (QOL) and Total Health Summary Score (THS) were correlated with KPS scores (r2 range 0.06-0.32), but only physical function and social function scores showed a significant correlation with CD4 cell count; the MOS-HIV however, did not distinguish between HIV disease stage. Using logistic regression analysis, KPS scores, as well as the variables of marriage, employment status, occupation before diagnosis, somebody to talk to, transmission modality of injection drug use and sex partner HIV positive showed statistically associated with a lower quality of life. Conclusions: This study presents the first evidence for the reliability and validity of the Chinese version of MOSHIV among PLWHA in mainland China. Lower scores of the MOS-HIV indicate that the QOL of the PLWHA in our study sample have been poor. This was irrespective of the stage of their disease and CD4 cell counts. This questionnaire has the potential to inform interventions aimed at enhancing and maintaining QOL of PLWHA.
Network-level allosteric effects are elucidated by detailing how ligand-binding events modulate utilization of catalytic potentials

Allosteric regulation has traditionally been described by mathematically-complex allosteric rate laws in the form of ratios of polynomials derived from the application of simplifying kinetic assumptions. Alternatively, an approach that explicitly describes all known ligand-binding events requires no simplifying assumptions while allowing for the computation of enzymatic states. Here, we employ such a modeling approach to examine the “catalytic potential” of an enzyme—an enzyme’s capacity to catalyze a biochemical reaction. The catalytic potential is the fundamental result of multiple ligand-binding events that represents a “tug of war” among the various regulators and substrates within the network. This formalism allows for the assessment of interacting allosteric enzymes and development of a network-level understanding of regulation. We first define the catalytic potential and use it to characterize the response of three key kinases (hexokinase, phosphofructokinase, and pyruvate kinase) in human red blood cell glycolysis to perturbations in ATP utilization. Next, we examine the sensitivity of the catalytic potential by using existing personalized models, finding that the catalytic potential allows for the identification of subtle but important differences in how individuals respond to such perturbations. Finally, we explore how the catalytic potential can help to elucidate how enzymes work in tandem to maintain a homeostatic state. Taken together, this work provides an interpretation and visualization of the dynamic interactions and network-level effects of interacting allosteric enzymes.
Hierarchical Clustering better than Average-Linkage

Hierarchical Clustering (HC) is a widely studied problem in exploratory data analysis, usually tackled by simple agglomerative procedures like average-linkage, single-linkage or complete-linkage. In this paper we focus on two objectives, introduced recently to give insight into the performance of average-linkage clustering: a similarity based HC objective proposed by [Moseley and Wang, 2017] and a dissimilarity based HC objective proposed by [Cohen-Addad et al., 2018]. In both cases, we present tight counterexamples showing that average-linkage cannot obtain better than 1/3 and 2/3 approximations respectively (in the worst-case), settling an open question raised in [Moseley and Wang, 2017]. This matches the approximation ratio of a random solution, raising a natural question: can we beat average-linkage for these objectives? We answer this in the affirmative, giving two new algorithms based on semidefinite programming with provably better guarantees.
Low Delay Scheduling of Objects Over Multiple Wireless Paths

In this paper we consider the task of scheduling packet transmissions amongst multiple paths with uncertain, time-varying delay. We make the observation that the requirement is usually to transmit application layer objects (web pages, images, video frames etc) with low latency, and so it is the object delay rather than the per packet delay which is important. This has fundamental implications for multipath scheduler design. We introduce SOS (Stochastic Object-aware Scheduler), the first multipath scheduler that considers application layer object sizes and their relationship to link uncertainty. We demonstrate that SOS reduces the 95% percentile object delivery delay by 50-100% over production WiFi and LTE links compared to state-of-the art schedulers. We extend SOS to utilize FEC and to handle the scheduling multiple objects in parallel. We show that judicious priority scheduling of HTTP objects can lead to a 2-3x improvement in page load times
Robotic Lateral Pelvic Lymph Node Dissection after Neoadjuvant Chemoradiation: View from the West.

1119 DISEASES OF THE COLON & RECTUM VOLUME 61: 9 (2018) Neoadjuvant chemoradiation (nCRT) and total mesorectal excision (TME) are the current standard treatment for locally advanced rectal cancer in Western countries. However, lateral pelvic lymph node (LPLN) metastasis, beyond the TME plane, has increasingly become an important clinical problem. To solve this problem, Japanese surgeons have routinely performed lateral pelvic lymph node dissection (LPLND) and TME for low rectal cancer. In contrast, Western surgeons have not adopted this strategy because of a concern regarding technical difficulty and morbidity, especially in the more obese Western population. Recent data suggest that patients with clinically positive LPLN have a high risk of treatment failure with TME plus either nCRT or LPLND. In particular, the surgical management of residual macroscopically enlarged LPLN after nCRT is an important issue that remains unaddressed in Western series. In our institution, for patients with clinically involved LPLN, we utilize the combined strategy of nCRT and LPLND. This video demonstrates the technique of roboticassisted LPLND in a 38-year-old Western patient who has rectal cancer with the BMI = 29 kg/m. For clarification, we annotated the video with schematic anatomical descriptions (see Video, Supplemental Digital Content 1, http:// links.lww.com/DCR/A697). The dissection is performed along the embryological planes of the lateral compartment. The important anatomical landmarks are identified and the pelvic autonomic nerves are preserved. Meanwhile, all the nodal tissue within these following boundary structures are removed in an en bloc fashion: