Miracle-dz/UniFAR-FTUs huggingface dataset:
Competition and Facilitation in the Capuchin–Squirrel Monkey Relationship

In Guyana, the range of the brown capuchin, Cebus apella, meets the range of its congener, the wedge‐capped capuchin, C. olivaceus, with the two species exhibiting a mutually exclusive patchy distribution. Squirrel monkeys, Saimiri sciureus, and C. apella form ubiquitous interspecific associations, but the reason remains debatable. With a large biogeographic field study, we tested the degree to which the distribution and abundance of Cebus and S. sciureus is determined by habitat type, fruit availability, and geography (i.e., determinants of the fundamental niche) relative to interspecific interactions, such as competition and facilitation (i.e., the realized niche). We used the competition between the two capuchin monkeys as a natural experiment that subjected S. sciureus to C. apella and C. olivaceus ‘treatments’. Using spatial regression models and principal components analysis, we found that S. sciureus was associated with seasonally flooded forests, and was correlated with fruit abundance and diversity (fundamental niche), but was also correlated with C. apella density even when accounting for habitat and fruit availability (realized niche). Saimiri sciureus density was unrelated to C. olivaceus density. Cebus apella was associated with a variety of forest types, but particularly included disturbed and edge habitats such as logged forests, seasonally flooded forests, and upland savanna, in addition to mature forest. Cebus apella was also positively correlated with S. sciureus density and negatively correlated with the density of C. olivaceus. In contrast, C. olivaceus avoided riparian areas and was associated with mixed‐height forests on sloped mountainous terrain. In sum, interspecific interactions such as competition between species of Cebus and facilitation between C. apella and S. sciureus were as important as habitat and fruit availability in determining the distribution and abundance of these primates.
A Risk-Based Maintenance Decision-Making Approach for Railway Asset Management

This paper presents a risk-based maintenance decision making modeling methodology for railway asset maintenance optimization, which takes risk and maintenance cost objectives into consideration in the decision making process. A bottom-up risk analysis approach has been developed by using fuzzy reasoning approach (FRA) and fuzzy-analytical hierarchy process (Fuzzy-AHP) to produce a risk model. A total cost model has also been developed to estimate repair/renewal, maintenance and performance review costs. A risk-based maintenance decision making support model has then been developed by integrating the risk model with cost model in which multi-criteria decision making (MCDM) techniques are employed to process the proposed risk-based maintenance decision making support model. An illustrative example on a section of a track system maintenance decision selection is used to demonstrate the application of the proposed methodology. The results show that by using the proposed methodology the qualitative and quantitative risk data and information with maintenance costs associated with railway assets can be evaluated efficiently and effectively, which provide very useful information to railway engineers, managers, and decision makers.
Developmental Transactions Between Self-Regulation and Academic Achievement Among Low-Income African American and Latino Children.

This study examined the development of emerging self-regulation (SR) skills across the preschool years and relations to academic achievement in kindergarten and first grade. SR skills of 403 low-income African American and Latino children were measured at 2&1/2, 3&1/2, and 5 years (kindergarten). Reading and math skills were measured at 5 and 6 years (first grade) using the Woodcock-Johnson. Transactional relations between SR skills and achievement outcomes were estimated with latent difference score models. Increases in set shifting predicted prospective increases in reading, but not math scores. Increases in simple response inhibition predicted prospective increases in math, but not reading scores. Application of these findings to early intervention programming and needed supports for school readiness and achievement are discussed.
Energy-Per-Bit Performance Analysis of Relay-Assisted Power Line Communication Systems

This paper provides a comprehensive analysis of the energy efficiency performance for different relaying schemes over the non-Gaussian power line communication (PLC) channel. Specifically, amplify-and-forward (AF), decode-and-forward (DF), selective DF (SDF) and incremental DF (IDF) relaying systems are investigated. For a more realistic scenario, the power consumption profile of the PLC modems is assumed to consist of both dynamic and static power. For each system, we derive accurate analytical expressions for the outage probability and the minimum energy-per-bit performance. For the sake of comparison and completeness as well as to quantify the achievable gains, we also analyze the performance of a single-hop PLC system. Monte Carlo simulations are provided throughout this paper to validate the theoretical analysis. Results reveal that AF relaying over the non-Gaussian PLC channel does not always enhance the performance and that the IDF PLC system offers the best performance compared to all other schemes considered. It is also shown that increasing the channel variance, which is related to the PLC network branching, and impulsive noise probability can considerably deteriorate the system performance. Furthermore, when the end-to-end distance is relatively small, it is found that the single-hop PLC approach can perform better than AF relaying.
The Cool Cucumber System at the 2017 TAC KBP BeSt Evaluation

The 2017 BeSt Evaluation is an evaluation of targeted belief and sentiment detection. It seeks to answer the question “ who has what mental attitude towards whom/what? ”. Our team participated in the sentiment evaluation for English, starting from known mentions of entities, relations and events. In this situation, the diﬃculty lies in part in determining the pairs that carry sentiment from the multitude of potential pairs that can be created by combining all the known mentions. To deal with this issue, we propose a two-stage classiﬁer to (1) eliminate objective pairs (i.e., pairs that do not have sentiment) and (2) predict sentiment polarity values for the predicted-subjective pairs.
Event‐based distributed robust synchronization control for multiple Euler‐Lagrange systems without relative velocity measurements

This paper focuses on the event‐based distributed robust leaderless synchronization control for multiple Euler‐Lagrange systems with directed communication topology that contains a directed spanning tree. Update frequency of the system is reduced by taking advantages of the event‐triggered approach, which can help extend the service life of the controller. Robust control theory is employed to guarantee the synchronization stability of the networked Euler‐Lagrange systems when unmodeled dynamics occur. The cost on the distributed synchronization protocol design can be saved due to the relaxation of the requirement on relative velocity measurements. Furthermore, our results are more practical because unknown disturbance is taken into consideration. In addition, it can be rigorously analyzed that each agent can exclude the undesired Zeno behavior. Some simulation examples are provided in the end to demonstrate the effectiveness of the proposed event‐based distributed robust control algorithm.
The Effect of School-based Exercise Practices of 9-11 Year Old Girls Students on Obesity and Health-related Quality of Life

This study was planned to determine the effects of school-based exercise practices (SBEP) on obesity and health-related quality of life (HRQL) in 9-11 year old girls. Participants consist of girls students from 9-11 years old in two state schools in Kars. Intervention Group (n: 85) courses of games and physical activities (CGPA) and SBEP (Basketball, Handball, Volleyball, Badminton, Table Tennis) and Control Group (n: 85) were formed as only CGPA. The exercise program; intervention groups was made subject to a training load of 60-70% and repetitions making up 3 days a week for 60 minutes a day, whereas the control group is a compulsory lesson 45 minutes three days a week in the gym or playground. Health-Related Quality of Life Scale (Kid-KINDL) was used in order to define the girl student quality of life before and after SBEP while Exercise Self-Efficacy Scale (ESS) was used for determining their exercise levels. According to the findings; Intervention group was found to be significant at p<. 001 level according to the height, weight and body mass index control group of girl students. 4 months after intervention, the proportion of obesity in the intervention group was 25.2% and the rate of overweight was 14.2% while it was observed that the control group had a statistically insignificant decrease in BMI. Intervention group's scores of sub-dimensions of total quality of life, physical well-being, emotional well-being, self-esteem, family as well as exercise self-efficacy levels (ESL) were observed significantly high (p<0.001) compared to control group. A positive relationship (p<0.01; p<0.05) at the level of r=. 361; r=. 305; r=. 219 was found between ESL and the sub-dimensions of physical well-being, emotional well-being and self-esteem of HRQL of intervention group while a significant relationship (p<0.05) at the level of r=. 230 was determined between ESL and the sub-dimension of friends of HRQL Scale of control group. Consequently, Female students have a positive effect on ESL and HRQL. Obesity rate decreases as ESL increases and HRQL levels also increase significantly. SBEP participation should be increased at the point of increasing HRQL in children's daily lives and educational settings.
Acetyl‐CoA production from pyruvate is not necessary for preservation of myelin

Oligodendrocytes and Schwann cells not only form myelin in the central and peripheral nervous system, but also provide metabolic and trophic support to the axons they ensheathe. Acetyl‐CoA is potentially a key molecule in Schwann cells and oligodendrocytes because it is at the crossroads of cellular lipid biosynthesis and energy generation. The main route for acetyl‐CoA production is the oxidation of pyruvate by the pyruvate dehydrogenase complex (PDC). PDC deficiency in humans results in neurodegeneration and developmental impairments in both white and gray matter structures. To address the importance of PDC in myelinating glia, we deleted Pdha1 gene specifically in oligodendrocytes and Schwann cells. Surprisingly, sciatic and optic nerve morphology and the motor performance of Pdha1f/Y; CnpCre/+ mice are undistinguishable from those of controls at 1 month of age. In addition, myelin is stably maintained for at least 10 months. However, Pdha1f/Y; CnpCre/+ mice showed reduced fiber density and signs of axonal degeneration in both sciatic and optic nerves from 6 months of age. In contrast, 10 month‐old mice bearing a floxed Pdha1 gene with either P0‐Cre (expressed only by Schwann cells) or NG2‐CreER (expressed in oligodendrocyte precursor cells) do not show any sign of axonal pathology or alterations in myelin structure or thickness. This indicates that the axonopathy is specific to the Pdha1f/Y; CnpCre/+ mice. Taken together, these results suggest that acetyl‐CoA derived from pyruvate is not necessary for myelin maintenance and, thus, myelin‐forming cells are not likely to contribute to the pathophysiology of PDC deficiency.
Image colourisation by non-local total variation method in the CB and YIQ colour spaces

Colourisation is a process of adding colour to greyscale images. In this study, the authors propose two new colourisation models based on non-local total variation regularisation in the chromaticity and brightness (CB) colour space and the YIQ colour space. Lagrange multiplier method is used to handle the sphere constraint of chromaticity in the CB colour space. By introducing an extra variable and using the dual version of non-local total variation, they split the proposed colourisation problems into two subproblems with closed-form solutions and get two iterative algorithms. Experimental results and comparisons demonstrate that the advantage of the proposed methods is that they can preserve the colour edges better than the closely related existing methods, especially the total variation methods.
Optimization of Transfer Learning for Sign Language Recognition Targeting Mobile Platform

The target of this research is to experiment, iterate and recommend a system that is successful in recognition of American Sign Language (ASL). It is a challenging as well as an interesting problem that if solved will bring a leap in social and technological aspects alike. In this paper, we propose a real-time recognizer of ASL based on a mobile platform, so that it will have more accessibility and provides an ease of use. The technique implemented is Transfer Learning of new data of Hand gestures for alphabets in ASL to be modelled on various pre-trained high- end models and optimize the best model to run on a mobile platform considering the various limitations of the same during optimization. The data used consists of 27,455 images of 24 alphabets of ASL. The optimized model when ran over a memory-efficient mobile application, provides an accuracy of 95.03% of accurate recognition with an average recognition time of 2.42 seconds. This method ensures considerable discrimination in accuracy and recognition time than the previous research.
Short Schedules for Fast Flow Rerouting

This paper studies the fundamental problem of how to reroute $k$ unsplittable flows of a certain demand in a capacitated network from their current paths to their respective new paths, in a congestion-free manner and fast. This scheduling problem has applications in traffic engineering in communication networks and has recently received much attention in software-defined networks, in which updates are distributed over an asynchronous network by a software controller. However, existing algorithms for this problem either have a super-polynomial runtime or only compute feasible schedules, which do not provide any guarantees on the length of the rerouting schedule. This paper presents the first polynomial-time algorithm for computing shortest update schedules to reroute flows in a congestion-free manner. We contribute an almost tight characterization of the polynomial-time tractability of the problem: We present the first polynomial-time solution for this problem for two flows, but also show that even the question whether a feasible update schedule exists, is already NP-hard for six flows. In fact, the presented algorithm runs in linear time and is hence not only optimal in terms of scheduling but also asymptotically optimal in terms of runtime.
Fully discrete FEM-BEM method for a class of exterior nonlinear parabolic-elliptic problems in 2 D

We considered a nonlinear parabolic equation in a bounded domain of R2 coupled with the Laplace equation in the corresponding exterior region. This kind of problems appears in the modelling of quasi-stationary electromagnetic fields. We chose a regular artificial boundary containing the nonlinear region in its interior. Then, we applied a symmetric FEM-BEM coupling procedure including a parameterization of the artificial boundary. We used the backward Euler method for the time discretization and an exact triangulation of the finite element domain. Assuming that the nonlinear operator is strongly monotone and Lipschitz-continuous, we proved convergence and obtained optimal error estimates for the solution of the discrete problem. Finally, we proposed a fully discrete scheme with quadrature formulas of low order and, under some additional conditions on the nonlinearity, proved that the order of convergence remains optimal.
Fraud Detection in Banking Sector using Data mining

: In present scenario when the term fraud comes into a discussion, banking fraud clicks to mind until now. In recent years banking fraud has increasing extremely. Every year fraud in banking is rising. Fraud presents significant cost to our economy. For customer segmentation and productivity, most of the banks are using data mining, and also for credit scores and approval, predicting payment default, marketing, detecting fraudulent transactions, etc. This paper provides an overview of the concept of Data Mining and different frauds in Banking. The banking sector consists of public sector, private sector and foreign banks, apart from smaller regional and cooperative banks. IT-based banking products, services and solutions are available in market. Phone Banking; ATM facility; Credit, Debit and Smart Cards; Internet Banking & Mobile Banking; SWIFT Network & INFINET Network are most common in banking.
Self-Organized Cell Outage Detection Architecture and Approach for 5G H-CRAN

An attractive architecture called heterogeneous cloud radio access networks (H-CRAN) becomes one of the important components of 5G networks, which can provide ubiquitous high-bandwidth services with flexible network construction. However, massive access nodes increase the risk of cell outages, leading to negative impact on user-perceived QoS (Quality of Service) and QoE (Quality of Experience). Thus, cell outage management (COM) became a key function proposed in SON (Self-Organized Networks) use cases. Based on COM, cell outage detection (COD) will be resolved before cell outage compensation (COC). Currently few studies concentrate on COD for 5G H-CRAN, and we propose self-organized COD architecture and approach for it. We firstly summarize current COD solutions for LTE/LTE-A HetNets and then introduce self-organized architecture and approach suitable for H-CRAN, which includes COD architecture and procedures, and corresponding key technologies for it. Based on the architecture, we take a use case with handover data analysis using modified LOF (Local Outlier Factor) detection approach to detect outage for different kinds of cells in H-CRAN. Results show that the proposed approach can identify the outage cell effectively.
Bridging Languages through Images with Deep Partial Canonical Correlation Analysis

We present a deep neural network that leverages images to improve bilingual text embeddings. Relying on bilingual image tags and descriptions, our approach conditions text embedding induction on the shared visual information for both languages, producing highly correlated bilingual embeddings. In particular, we propose a novel model based on Partial Canonical Correlation Analysis (PCCA). While the original PCCA finds linear projections of two views in order to maximize their canonical correlation conditioned on a shared third variable, we introduce a non-linear Deep PCCA (DPCCA) model, and develop a new stochastic iterative algorithm for its optimization. We evaluate PCCA and DPCCA on multilingual word similarity and cross-lingual image description retrieval. Our models outperform a large variety of previous methods, despite not having access to any visual signal during test time inference.
Invasive Pulmonary Aspergillosis Following In luenza: Report of Two Cases

Case Summary: (Case 1) A 45-year-old man of chronic obstructive pulmonary disease (COPD) had dyspnea. He was admitted to the intensive care unit (ICU) with ventilator support due to worsening pneumonia and severe hypoxemia. In luenza A (H1N1) DNA in the nasopharynx sample remained positive after 5 days of oseltamivir therapy. Peramivir was therefore used for additional 5 days. Voriconazole had been used for 2 weeks for Aspergillus infection due to high index (4.96) of Aspergillus galactomannan (GM) antigen in the blood sample. Imipenem and colistin were used for Klebsiella pneumoniae bacteremia and that sputum cultures yielded Pseudomonas aeruginosa and Acinetobacter baumannii. We used high frequency oscillatory ventilation for severe refractory hypoxemia. The response was poor and he died one month after admission. (Case 2) A 76-year-old man was admitted due to in luenza B with dyspnea. He was treated with zanamivir and cefuroxime. As respiratory failure with interstitial in iltration over right lung, he was transferred to the ICU. Piperacillin and levo loxacin were used. Zanamivir (5days) followed by oseltamivir (10days) were used for persistent recovery of in luenzaB DNA in the throat samples. Sputum culture yielded Aspergillus species and blood Aspergillus GM antigen index was 2.25 (positive, > 0.5). He received intravenous voriconazole (14 days) followed by oral form (21 days). Then Aspergillus GM antigen became 0.38. He was discharged after 6 weeks of hospital stay. As lung ibrosis with dyspnea affecting his daily activity, he needed oxygen therapy at home.
Development and internal evaluation of speech-to-speech translation technology at BBN

Speech-to-speech translation (S2S) technology holds out the promise of allowing spoken communication across language barriers. Recently, there has been a great deal of progress in S2S technology, much of it under the sponsorship of DARPA's TransTac program. In this paper, we present BBN's S2S system, "TransTalk", whose development has been funded under the TransTac program. We also present various performance metrics, and the result of detailed performance analyses, using the TransTalk system.
An Annotation Language for Semantic Search of Legal Sources

While formalizing legal sources is an important challenge, the generation of a formal representation from legal texts has been far less considered and requires considerable expertise. In order to improve the uniformity, richness, and efﬁciency of legal annotation, it is necessary to experiment with annotations and the annotation process. This paper reports on a ﬁrst experiment, which was a campaign to annotate legal instruments provided by the Scottish Government’s Parliamentary Counsel Ofﬁce and bearing on Scottish smoking legislation and regulation. A small set of elements related to LegalRuleML was used. An initial guideline manual was produced to annotate the text using annotations related to these elements. The resulting annotated corpus is converted into a LegalRuleML XML compliant document, then made available via an online visualisation and query tool. In the course of annotating the documents, a range of important interpretive and practical issues arose, highlighting the value of a focused study on legal text annotation.
A real-time chaotic encryption for multimedia data and application to secure surveillance framework for IoT system

Video surveillance is becoming more and more popular in our life. It is widely deployed in many kinds of monitoring application such as healthcare and industrial environment. However, there are many security requirements such as privacy, authentication, and confidentiality. To tackle this issue, we address chaotic systems, which have been suggested as a good promising direction with desired properties in a real-time application. Furthermore, our major contributions are two-fold. First, we discuss the properties of chaotic systems in order to encrypt multimedia data. Second, we propose a secure surveillance framework for healthcare application by intelligent integration of the efficient chaotic map to extract data in the monitored scene using a visual sensor (camera). We show that our proposed framework fulfills the security requirements for surveillance applications.