Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular Phylogeny of the Acanthocephala (Class Palaeacanthocephala) with a Paraphyletic Assemblage of the Orders Polymorphida and Echinorhynchida

Acanthocephalans are attractive candidates as model organisms for studying the ecology and co-evolutionary history of parasitic life cycles in the marine ecosystem. Adding to earlier molecular analyses of this taxon, a total of 36 acanthocephalans belonging to the classes Archiacanthocephala (3 species), Eoacanthocephala (3 species), Palaeacanthocephala (29 species), Polyacanthocephala (1 species) and Rotifera as outgroup (3 species) were analyzed by using Bayesian Inference and Maximum Likelihood analyses of nuclear 18S rDNA sequence. This data set included three re-collected and six newly collected taxa, Bolbosoma vasculosum from Lepturacanthus savala, Filisoma rizalinum from Scatophagus argus, Rhadinorhynchus pristis from Gempylus serpens, R. lintoni from Selar crumenophthalmus, Serrasentis sagittifer from Johnius coitor, and Southwellina hispida from Epinephelus coioides, representing 5 new host and 3 new locality records. The resulting trees suggest a paraphyletic arrangement of the Echinorhynchida and Polymorphida inside the Palaeacanthocephala. This questions the placement of the genera Serrasentis and Gorgorhynchoides within the Echinorhynchida and not the Polymorphida, necessitating further insights into the systematic position of these taxa based on morphology.
Long Term Effect of Curcumin in Regulation of Glycolytic Pathway and Angiogenesis via Modulation of Stress Activated Genes in Prevention of Cancer

Oxidative stress, an important factor in modulation of glycolytic pathway and induction of stress activated genes, is further augmented due to reduced antioxidant defense system, which promotes cancer progression via inducing angiogenesis. Curcumin, a naturally occurring chemopreventive phytochemical, is reported to inhibit carcinogenesis in various experimental animal models. However, the underlying mechanism involved in anticarcinogenic action of curcumin due to its long term effect is still to be reported because of its rapid metabolism, although metabolites are accumulated in tissues and remain for a longer time. Therefore, the long term effect of curcumin needs thorough investigation. The present study aimed to analyze the anticarcinogenic action of curcumin in liver, even after withdrawal of treatment in Dalton's lymphoma bearing mice. Oxidative stress observed during lymphoma progression reduced antioxidant enzyme activities, and induced angiogenesis as well as activation of early stress activated genes and glycolytic pathway. Curcumin treatment resulted in activation of antioxidant enzyme super oxide dismutase and down regulation of ROS level as well as activity of ROS producing enzyme NADPH:oxidase, expression of stress activated genes HIF-1α, cMyc and LDH activity towards normal level. Further, it lead to significant inhibition of angiogenesis, observed via MMPs activity, PKCα and VEGF level, as well as by matrigel plug assay. Thus findings of this study conclude that the long term effect of curcumin shows anticarcinogenic potential via induction of antioxidant defense system and inhibition of angiogenesis via down regulation of stress activated genes and glycolytic pathway in liver of lymphoma bearing mice.
How ecological networks evolve

Ecological networks represent the backbone of biodiversity. As species diversify over macro-evolutionary time-scales, the structure of these networks changes; this happens because species are gained and lost, and therefore add or remove interactions in their communities. The mechanisms underlying such dynamic changes in ecological network structure, however, remain poorly understood. Here we show that several types of ecological interactions share common evolutionary mechanisms that can be parametrised based on extant interaction data. In particular, we found that a model mimicking birth-death processes for species interactions describes the structure of extant networks remarkably well. Moreover, the various types of ecological interactions we considered—seed dispersal, herbivory, parasitism, bacteriophagy, and pollination—only differed in the position they occupy in the parameters’ multi-dimensional space. Notably, we found no clustering of parameters values between antagonistic and mutualistic interactions. Our results provide a common modelling framework for the evolution of ecological networks that we anticipate will contribute to the greater consideration of the explicit role played by species interactions in models of macro-evolution and adaptive radiations.
A Robust Control for TCSC Based on a Multiple Model Adaptive Control Strategy

Linear TCSC damping controller is bad in adaptability and robustness, but its control strategy is simple and easy to be implemented; on the contrary, the nonlinear TCSC damping controller has the better adaptability and robustness, but its control strategy is too complicated. A multiple model adaptive control strategy for robust damping of interarea oscillation in power system is put forward in this thesis. Based on the recursive Bayes theorem, the weight for each model is calculated and final output of the controller is synthesized by the weights. A more satisfied performance in adaptive and robust for the new model is proofed by the simulation result. KeywordsBayesian approach; Inter-area oscillations; multiple model adaptive control (MMAC); robustness; Thyristor controlled series compensator (TCSC). The Project Supported by Tian Jin Natural Science Foundation(08JCZDJC18600 09JCZDJC23900), Tian Jin Science and technology Project (07ZHRDCG04500), University Science and Technology Development Foundation of Tianjin 2006ZD32
Multimodal Translation System Using Texture-Mapped Lip-Sync Images for Video Mail and Automatic Dubbing Applications

We introduce a multimodal English-to-Japanese and Japanese-to-English translation system that also translates the speaker's speech motion by synchronizing it to the translated speech. This system also introduces both a face synthesis technique that can generate any viseme lip shape and a face tracking technique that can estimate the original position and rotation of a speaker's face in an image sequence. To retain the speaker's facial expression, we substitute only the speech organ's image with the synthesized one, which is made by a 3D wire-frame model that is adaptable to any speaker. Our approach provides translated image synthesis with an extremely small database. The tracking motion of the face from a video image is performed by template matching. In this system, the translation and rotation of the face are detected by using a 3D personal face model whose texture is captured from a video frame. We also propose a method to customize the personal face model by using our GUI tool. By combining these techniques and the translated voice synthesis technique, an automatic multimodal translation can be achieved that is suitable for video mail or automatic dubbing systems into other languages.
KVBTree: A Key/Value Based Storage Structure for Large-Scale Electric Power Data

There are lots of data communications among subtasks in big data processing, especially those key pair intermediate data. Its a key point concerning big data analytic area to process those intermediate data efficiently. However state of the art big data systems rare put an eye on the optimization and effeicient management of those intermediate data. On one hand, intermediate data in MapReduce and other batch systems are stored sequentially in files. Those intermediate date cannot be merged automatically, extra shuffle phase is needed in MapReduce to aggregate values with the same key, which surely costs extra time. On the other hand, some distributed message management system such as stream data processing system can aggregate the intermediate messages effectively, but they are at a much higher-level abstraction. Those systems usually suffer from complicated structure, which may incur the performance degradation. In this paper, we propose a B+ tree based data structure, KVBTree, to manage the intermediate data effectively. An efficient cache strategy is then proposed to increase the storage capability of the KVBTree. We also present the strategies for the querying, inserting and traversing of the data elements in KVBTree. We evaluate the time complexity and the space complexity of KVBTree in the final part of this paper. The experimental results show that KVBTree is able to play an effective role concerning the electric power data.
Integration of Physics Based Simulation with Haptic Interfaces for VR Applications

We present a novel approach to integrate physics based simulation with haptic interfaces for virtual reality applications. Proposed approach categorizes rigid bodies into two set of the visual and haptic rendering groups. Dynamic states of most objects which belong to the visual rendering group are simulated according to the visual rendering update rate which is typically 60 Hz. Only the objects in the haptic rendering group are simulated in a higher update rate which is required for the stable haptic interaction. In our case, dynamic states of the haptic rendering group are updated 1KHz. In the sense that collision and contact responses for each group can be efficiently handled with respective simulation algorithms (the penalty vs. analytic methods), our approach does not only save the computational cost but improves the simulation stability. As a case study, we apply our approach to CAVE like environment.
SandScout: Automatic Detection of Flaws in iOS Sandbox Profiles

Recent literature on iOS security has focused on the malicious potential of third-party applications, demonstrating how developers can bypass application vetting and code-level protections. In addition to these protections, iOS uses a generic sandbox profile called "container" to confine malicious or exploited third-party applications. In this paper, we present the first systematic analysis of the iOS container sandbox profile. We propose the SandScout framework to extract, decompile, formally model, and analyze iOS sandbox profiles as logic-based programs. We use our Prolog-based queries to evaluate file-based security properties of the container sandbox profile for iOS 9.0. 2 and discover seven classes of exploitable vulnerabilities. These attacks affect non-jailbroken devices running later versions of iOS. We are working with Apple to resolve these attacks, and we expect that SandScout will play a significant role in the development of sandbox profiles for future versions of iOS.
The Preference Learning Toolbox

Preference learning (PL) is a core area of machine learning that handles datasets with ordinal relations. As the number of generated data of ordinal nature is increasing, the importance and role of the PL field becomes central within machine learning research and practice. This paper introduces an open source, scalable, efficient and accessible preference learning toolbox that supports the key phases of the data training process incorporating various popular data preprocessing, feature selection and preference learning methods.
Genetic basis of delay discounting in frequent gamblers: examination of a priori candidates and exploration of a panel of dopamine-related loci

Delay discounting is a behavioral economic index of impulsivity that reflects preferences for small immediate rewards relative to larger delayed rewards. It has been consistently linked to pathological gambling and other forms of addictive behavior, and has been proposed to be a behavioral characteristic that may link genetic variation and risk of developing addictive disorders (i.e., an endophenotype). Studies to date have revealed significant associations with polymorphisms associated with dopamine neurotransmission. The current study examined associations between delay discounting and both previously linked variants and a novel panel of dopamine‐related variants in a sample of frequent gamblers.
Esophageal pH and Combined Impedance-pH Monitoring in Children

Esophageal pH monitoring is considered the gold standard for the diagnosis of gastroesophageal reflux disease because of the normal ranges across the pediatric age range. However, this method can only detect acid reflux. Multichannel intraluminal impedance-pH (MII-pH) monitoring has recently been used for the detection of bolus reflux in infants and children. This method allows for the detection of liquid, gas or mixed reflux in addition to acid, weakly acidic or weakly alkaline reflux. MII-pH monitoring can record the direction of flow and the height of reflux, which are useful parameters to identify an association between symptoms and reflux. However, the technique is limited by its high cost and the lack of normative data of MII-pH in the pediatric population. Despite certain limitations, MII-pH monitoring will become more common and gradually replace pH monitoring in the future, because pH monitoring is part of MII-pH.
Techniques for location selection on a mobile device

In this paper we present techniques for selecting one's current location in mobile location-based systems. We present Locawe (Location-aware System Platform) and four alternative location selection techniques, which are physical selection using RFID technology, automatic selection based on GPS coordinates, selection from a mobile map with a stylus, and a textual selection technique involving a virtual keyboard and a selection list. These techniques have been tested in real mobile applications.
Building a Brazilian Portuguese Parallel Corpus of Original and Simplified Texts

In this paper we address the problem of building the necessary tools and resources for performing Brazilian Portuguese text simplification. We describe our efforts on the design and development of: (a) a XCES-based annotation schema, (b) an annotation edition tool, and (c) a portal to access parallel corpora of original-simplified texts. These contributions were intended to (i) allow the creation and public release of a corpus of original and simplified texts with two different versions of simplification (called here natural and strong), targeting two levels of functional illiteracy and (ii) register simplification decisions during the creation of such corpus. We also provide an analysis of the first corpus created using the resources presented here: 104 newspaper texts and their simplified versions, produced by an expert in text simplification.
Comparison of Artificial Neural Networks with Logistic Regression in Prediction of Kidney Transplant Outcomes

Predicting the outcome of a graft transplant with high level of accuracy is a challenging task. To answer the challenge, data mining can play a significant role. The goal of this study is to compare the performances and features of an Artificially Intelligent (AI)-based data mining technique namely Artificial Neural Network with Logistic Regression as a standard statistical data mining method to predict the outcome of kidney transplants over a 2-year horizon. The methodology employed utilizes a dataset made available to us from a kidney transplant database. The dataset embodies a number of important properties, which make it a good starting point for the purpose of this research. Results reveal that in most cases, the neural network technique outperforms logistic regression. This study highlights that in some situations, different techniques can potentially be integrated to improve the accuracy of predictions.
The impact of pet ownership on self esteem, life satisfaction and personality

The purpose of this quantitative study was to explore the effects of pet ownership on selfesteem, life satisfaction and personality in pet and non-pet owners. Participants were (N=100) in total with (N=71) females and (N=29) males. Participants were asked demographic questions along with three self-report measures. The Rosenberg Self Esteem Scale (RSE; Rosenberg, 1965) was used to measure participant’s self-esteem. The Satisfaction with Life Scale (SWLS; Diener, Emmons, Larsen & Griffin, 1985) was used to measure subject’s life satisfaction. The Big Five Inventory (BFI; John & Srivastava, 1999) was used to measure the personalities of participants. Independent sample t-tests found no significant differences between pet and non-pet owners in relation to levels of self-esteem as well as personality. In addition, a Mann Whitney U test showed no significance differences in life satisfaction between pet and non-pet owners. These findings and the implications of the findings are discussed in greater detail.
SOC verification infrastructure

The testing and verification technology for system HDL models, focused to the significant improvement of the quality of design components for digital systems on chips and reduction the development time (time-to-market) by using the simulation environment, testable analysis of the logical structure HDL-program and the optimal placement of assertion engine is proposed.
Use geographic ontology and web mining to enhance service quality of web map

This paper discusses how to use geographic ontology to describe web map services and use geographic ontology and web mining to improve service quality of web map. For the users, the map is the efficient method of representing spatial information. But during the geographic information services, agents need be used to find and match all kinds of service. In the traditional map, the information is understood by the people, not by the agents. Therefore geographic ontology encodes the semantic information that people obtain from the map in a machine-readable manner. Second, present GIS lacks for the deduced competence, but geographic ontology can enhance the deduced competence because it has abundant semantic information. The improvement of query services of web map with the help of ontology and web mining can be described from two facets: discovering and extracting address information from the Web to extend geocoding database with the help of geographic ontology, enhancing the ability of query by spatial analyzing and reasoning on the extended address ontology database.
Evolutionary Ensemble Strategies for Heuristic Scheduling

An ensemble of single parent evolution strategies voting on the best way to construct solutions to a scheduling problem is presented. The ensemble technique applied is analogous to those described in the machine learning literature. A set of individuals vote on the best way to construct solutions and so collaborate with one another. An experimental study illustrates the superiority of the ensemble strategy over evolutionary strategies where individuals do not collaborate.
Transient fault characterization in dynamic noisy environments

Technology trends are increasing the frequency of serious transient (soft) faults in digital systems. For example, ICs are becoming more susceptible to cosmic radiation, and are being embedded in applications with dynamic noisy environments. We propose a generic framework for representing such faults and characterizing them on-line. We formally define the impact of a transient fault in terms of three basic parameters: frequency, observability and severity. We distinguish fault modes in systems whose noise environment changes dynamically. Based on these ideas, the problem of designing on-line architectures for transient fault characterization is formulated and analyzed for several optimization goals. Finally, experiments are described that determine transient fault impact and the corresponding tests for various simulated fault modes of the ISCAS-89 benchmark circuits
Exploring Patterns and Pathways of Dietary Change: Preferred Foods, Oral Health, and Stable Isotope Analysis of Hair from the Dani of Mulia, Papua, Indonesia

Interregional encounters frequently result in dietary, health, and cultural changes for participating groups. This paper investigates the patterns and pathways of dietary change among the Mulia Dani of highland western New Guinea, who at the time of data collection had been in contact with Christian missionaries and the global food market for 29 years. We explore three lines of data: food preferences (from survey responses), oral health (indicated by the percentage of carious and missing teeth), and dietary composition (from stable isotope ratios [δ13C and δ15N] of hair). We assess the results alongside categories of village affiliation, profession, age, and sex, finding that different demographic subsets within Mulia differentially adopted new foods and food preferences. Children and communities that had completely abandoned their traditional subsistence strategies appear to have been the segments of society most likely to exhibit dietary changes, and preferences for meat appear to have been influenced by the ability of a group to acquire animal products from the missionary settlement. Results of this study deepen our understanding of how new foods and ideas entered highland New Guinea and provide a model to understand processes of nutritional transitions in other times and regions.
The Impact of Cache Organization in Optimizing Microprocessor Power Consumption

In the recent years, power consumption has become increasingly an important design concern as silicon area and performance in modern computer systems design. Several factors have contributed to this trend. Perhaps the most visible have been the remarkable success and growth of Personal Digital Assistants (PDA’s), Cellular phones and pagers, etc . This work is an attempt to explore the impact of feature size shrinkage and cache configuration on optimizing power consumption in modern processors. The work studies two commercially known RISC microprocessors. The StrongARM and the Alpha-21064 microprocessors. The latter is the ancestor of the former and is therefore used here as the baseline in our analysis. Our analysis has illustrated quantitatively great power saving when technology is downsized and cache is well organized
The 2014 Mw 6.0 Napa earthquake, California: Observations from real‐time GPS‐enhanced earthquake early warning

Recently, progress has been made to demonstrate feasibility and benefits of including real‐time GPS (rtGPS) in earthquake early warning and rapid response systems. Most concepts, however, have yet to be integrated into operational environments. The Berkeley Seismological Laboratory runs an rtGPS‐based finite fault inversion scheme in real time. This system (G‐larmS) detected the 2014 Mw 6.0 South Napa earthquake in California. We review G‐larmS' performance during this event and 13 aftershocks and present rtGPS observations and real‐time modeling results for the main shock. The first distributed slip model and magnitude estimates were available 24s after the event origin time, which, after optimizations, was reduced to 14s (≈8s S wave travel time, ≈6s data latency). G‐larmS' solutions for the aftershocks (that had no measurable surface displacements) demonstrate that, in combination with the seismic early warning magnitude, Mw 6.0 is our current resolution limit.