Miracle-dz/UniFAR-FTUs huggingface dataset:
Genome-Wide Screen of DNA Methylation Changes Induced by Low Dose X-Ray Radiation in Mice

Epigenetic mechanisms play a key role in non-targeted effects of radiation. The purpose of this study was to investigate global hypomethylation and promoter hypermethylation of particular genes induced by low dose radiation (LDR). Thirty male BALB/c mice were divided into 3 groups: control, acutely exposed (0.5Gy X-rays), and chronic exposure for 10 days (0.05Gy/d×10d). High-performance liquid chromatography (HPLC) and MeDIP-quantitative polymerase chain reaction (qPCR) were used to study methylation profiles. DNMT1 and MBD2 expression was determined by qPCR and western blot assays. Methylation and expression of Rad23b and Ddit3 were determined by bisulfate sequencing primers (BSP) and qPCR, respectively. The results show that LDR induced genomic hypomethylation in blood 2 h postirraditaion, but was not retained at 1-month. DNMT1 and MBD2 were downregulated in a tissue-specific manner but did not persist. Specific hypermethylation was observed for 811 regions in the group receiving chronic exposure, which covered almost all key biological processes as indicated by GO and KEGG pathway analysis. Eight hypermethylated genes (Rad23b, Tdg, Ccnd1, Ddit3, Llgl1, Rasl11a, Tbx2, Scl6a15) were verified by MeDIP-qPCR. Among them, Rad23b and Ddit3 gene displayed tissue-specific methylation and downregulation, which persisted for 1-month postirradiation. Thus, LDR induced global hypomethylation and tissue-specific promoter hypermethylation of particular genes. Promoter hypermethylation, rather than global hypomethylation, was relatively stable. Dysregulation of methylation might be correlated with down-regulation of DNMT1 and MBD2, but much better understanding the molecular mechanisms involved in this process will require further study.
An incremental compilation algorithm for the Java programming language

The compiler transforms source code into object code. The incremental compiler is smarter than the batch compiler. When the programmer changes some source code files in the project. It does not need to recompile all source code files in the project and only needs to recompile changed source code files and all source code files directly and indirectly dependent on the changed source code files. This paper proposes an incremental compilation algorithm for the Java programming language. It overcomes the shortcomings of the make tool. It does not need to construct and maintain the makefile manually. The incremental compilation algorithm automatically collects and maintains the dependency rules. It also analyzes the effect of change types and eliminates unnecessarily recompilation process.
Obfuscation-Resilient , Efficient , and Accurate Detection and Family Identification of Android Malware

The number of Android malware apps are increasing very quickly. Simply detecting and removing malware apps is insufficient, since they can damage or alter other files, data, or settings; install additional applications; etc. To determine such behavior, a security engineer can significantly benefit from identifying the specific family to which an Android malware belongs. Techniques for detecting Android malware, and determining their families, lack the ability to deal with obfuscations (i.e., transformations of application to thwart detection). Moreover, some of the prior techniques are highly inefficient, making them inapplicable for real-time detection of threats. To address these limitations, we present a novel machine learning-based Android malware detection and family identification approach, RevealDroid, that provides selectable features. We assess RevealDroid to determine a selection of features that enable obfuscation resiliency, efficiency, and accuracy for detection and family identification. We assess RevealDroid’s accuracy and obfuscation resilience on an updated dataset of malware from a diverse set of families, including malware obfuscated using various transformations, and compare RevealDroid against an existing Android malware-family identification approach and another Android malware detection approach.
An Improved Presentation Method for Relevance Feedback in a Content-Based Image Retrieval System

Content-based image retrieval (CBIR) has been adopted as a complementary technique to the keyword-based image search. Relevance feedback (RFB) is considered as an effective means to bridge the gap between the designated features and the run-time semantics on a CBIR system. Like many other interactive system, a good user interface, which in RFB is mainly the presentation of the query results, is an important factor that affects the quality of feedbacks. By incorporating the multidimensional scaling (MDS) and the outlier detection techniques, we propose a method of presenting multiple image icons in this paper. It preserves the high-dimensional distance information and shows the selected images at proper 2D locations. Viewing the matched images with distance cues, users are able to give effective and productive feedbacks. We design and implement this presentation system and show some subjective results at the end.
Autonomous Mini-UAV for indoor flight with embedded on-board vision processing as navigation system

This paper describes the development of an Unmanned Aerial Vehicle (UAV) with the aid of a vision processing system for indoor navigation. A co-axial radio-controlled (RC) helicopter is upgraded with a customized on-board avionics system which include two Gumstix Linux computer systems as the on-board processors. A camera module is used to capture real time video during the flight to perform real time image processing. High level control commands are sent to the avionics system such that the UAV could perform simple indoor navigation by tracking the colored tracks on the ground. Important data such as attitude, velocity and acceleration of the UAV, together with the real time video will be feedback to the ground station via communication links for giving commands and monitoring purposes. Flight tests have been carried out to verify the results of the vision processing system and to ensure the robustness of the controller in the UAV.
The Influence of Between-Farm Distance and Farm Size on the Spread of Classical Swine Fever during the 1997–1998 Epidemic in The Netherlands

As the size of livestock farms in The Netherlands is on the increase for economic reasons, an important question is how disease introduction risks and risks of onward transmission scale with farm size (i.e. with the number of animals on the farm). Here we use the epidemic data of the 1997–1998 epidemic of Classical Swine Fever (CSF) Virus in The Netherlands to address this question for CSF risks. This dataset is one of the most powerful ones statistically as in this epidemic a total of 428 pig farms where infected, with the majority of farm sizes ranging between 27 and 1750 pigs, including piglets. We have extended the earlier models for the transmission risk as a function of between-farm distance, by adding two factors. These factors describe the effect of farm size on the susceptibility of a ‘receiving’ farm and on the infectivity of a ‘sending’ farm (or ‘source’ farm), respectively. Using the best-fitting model, we show that the size of a farm has a significant influence on both farm-level susceptibility and infectivity for CSF. Although larger farms are both more susceptible to CSF and, when infected, more infectious to other farms than smaller farms, the increase is less than linear. The higher the farm size, the smaller the effect of increments of farm size on the susceptibility and infectivity of a farm. Because of changes in the Dutch pig farming characteristics, a straightforward extrapolation of the observed farm size dependencies from 1997/1998 to present times would not be justified. However, based on our results one may expect that also for the current pig farming characteristics in The Netherlands, farm susceptibility and infectivity depend non-linearly on farm size, with some saturation effect for relatively large farm sizes.
Contextual Control Policy SelectionJe erson

Every autonomous agent operating in realistic settings must deal with incomplete state information. Sensory limitations, due to hardware constraints and/or limited interpretation algorithms, introduce hidden states which can prevent the acquisition of optimal control policies for a given task. This paper addresses this problem within the dynamical systems framework. The idea is to treat the agent in its environment as a dynamical system, and augment the original state space using contextual cues extracted empirically as the agent exercises existing control policies. Contex-tual cues are provided by the correlation between dynamic features of the agent-environment interaction and agent performance. In principle, the augmented state space allows the agent to learn to exploit control policies whenever they are likely to succeed, gather more information if the agent's context is ambiguous , and explore control alternatives in unfavorable contexts. Initial experiments involving an agent with impoverished sensing capabilities in a simulated, dynamic environment suggest that this approach might ooer a relatively simple way to extract meaningful context information from dynamical systems, and to enhance the agent's performance.
An Application of Markov Chain Monte Carlo to Community Ecology

Act 1. In 1975 Jared Diamond, who has since become famous as the Pulitzer Prizewinning author of Guns, Germs, and Steel, published a paper based mainly on a big matrix of Os and is [4]. Each row of Diamond's matrix' corresponded to a bird species; each column corresponded to an island in the New Hebrides (now Vanuatu). The Is and Os recorded the presence or absence of the species on the islands. In his paper, Diamond proposed a set of seven "community assembly rules" that he had inferred from the patterns in his co-occurrence matrix. These rules, said Diamond, govern the way species organize themselves into communities.
Asymmetry in the dynamic conditional correlation of gold returns and stock returns

The purpose of this thesis is to explore the possibility of asymmetry in the dynamic conditional correlation of stock returns and gold returns. We hypothesize that this asymmetry might be different for large and small firms, as a result of size specific characteristics that may influence firm profitability and risk following negative market shocks. We investigate this on three different sized U.S. stock indices during a twenty two year long period by using the dynamic conditional correlation model and the asymmetric generalized dynamic conditional correlation model. Our results show that there is asymmetry in the dynamic conditional correlation of these stock indices and gold. Furthermore, we find that the asymmetric effect is not the same for large and small firms.
The motivators that contribute to the migration of African American educators from suburban school districts to urban school districts

The Motivators that Contribute to the Migration of African American Educators from Suburban School Districts to Urban School Districts. (May 2012) Ostrova Dewayne McGary, B.A., Southeastern Louisiana University; M. Ed., Southeastern Louisiana University Chair of Advisory Committee: Dr. Gwendolyn Webb-Hassan The purpose of this qualitative study was to examine the perceived motivators contributing African American educators’ decision to migrate from a suburban school district to an urban school district. The case study approach was used in an effort to capture the participants’ voices and the motivators contributing to their decision to migrate to an urban school district after working as an educator in a suburban school district. The findings from this study will contribute to the existing body of literature by providing national policy makers, state policy makers, local school leaders and school district personnel information to create national, state, and local policy initiatives regarding African American educator personnel. The seven informants in this study were members of a large metropolitan area in the state of Texas and the suburban school districts bordering that metropolitan area. Since the enactment of the federal No Child Left Behind Act (2001), the achievement gap has been discussed and studied. However, few studies have
Accelerate data acquisition using Turbo Spin Echo and O-Space

Turbo Spin Echo (TSE) is a method of acquiring the echoes of a Cartesian readout in a T2-weighted echo train, resulting in a very fast imaging time. On the other hand, recent methods of spatial encoding with nonlinear magnetic fields have been studied by our group and others to reduce data acquisitions time, such as, PatLoc, O-Space, Null Space, 4D-RIO, etc. These efforts have focused on gradient echo imaging. In this paper, a novel method has been proposed to combine the benefits of both TSE acquisition and O-Space to accelerate the data acquisition for T2-weighted imaging. Because O-space acquires DC signal in at least some spatial location within each echo, modifications of the acquisition order and reconstruction method are required. We present simulations and experiments illustrating that the proposed method can further speed up data acquisition of an O-Space imaging sequence using spin echo trains.
Oberon with Gadgets - A Simple Component Framework

We present a simple component framework that, "in a nutshell", addresses many of the archetypal aspects of component-oriented software environments, with a particular emphasis on homogeneity and uni ed concepts. Some of the topics focussed upon are a fully hierarchic notion of compound objects, persistent object representation, interactive and descriptive tools for object composition and self-contained and mobile objects. Methodological highlights are (a) a novel kind of generic object interfaces in combination with a message protocol that strictly obeys the principle of parental control, (b) a multi-purpose concept of indexed object libraries and (c) an alternative approach (compared to the Java virtual machine) to portable code, accompanied by dynamic compilation. Our framework is based on and integrated into Oberon, a language and system in the heritage of Pascal and Modula that runs both natively on Intelbased PCs or on top of a commercial operating system. Of the many projects having made use of our framework so far, three applications of a pronounced interdisciplinary character shall be mentioned brie y.
Psychiatric symptoms in glioma patients: from diagnosis to management

Patients with primary intrinsic brain tumors can experience neurological, cognitive, and psychiatric symptoms that greatly affect daily life. In this review, we focus on changes in personality and behavior, mood issues, hallucinations, and psychosis, because these are either difficult to recognize, to treat, or are understudied in scientific literature. Neurobehavioral symptoms are common, often multiple, and causation can be multifactorial. Although different symptoms sometimes require a different treatment approach, we advise a comprehensive treatment approach, including pharmacological treatment and/or psychotherapy where appropriate. Further research is needed to obtain a better estimate of the prevalence of psychiatric symptoms in glioma patients, and the extent to which these affect everyday functioning and family life.
FAST: Fast annotation with synchronized threads

FAST is a multi-threaded, I/O optimized Seed-and-Extend alignment program. FAST is extensible to nucleotide sequences making it comparable to both BLASTn and BLASTp, and also features several new usage flags reporting only HSPs meeting user defined e-value cut-offs. FASTs threaded database construction allows fast, low memory database construction e.g., RefSeq (9.4GB) can be indexed in under 5 minutes using 20 threads. The threaded database construction gives users the ability to create custom databases on demand which is useful for tasks requiring self-alignment, such as network construction [30]. Finally, FAST supports incremental database construction enabling users to keep their databases up-to-date by adding sequences without suffering the cost of reformatting the entire database. The FAST source is freely available through GitHub https:// github.com/hallamlab/FAST and test datasets can be found on Dropbox https://www.dropbox. com/sh/xvvavweuzgqybc4/ AAAWCrRnol67ZsXi2qLQWUuOa?
Ontology-Driven Personalized Query Refinement

The most popular way for finding information on the Web is go to a search engine, submit a query that describes an information need and receive a list of results that relate to the information sought. As more and more topics are being discussed over the Web and our vocabulary remains relatively stable, it is increasingly difficult for Web users to select queries that express their varying information needs in a distinguishable by the engine manner. Query refinement is the process of providing information seekers with alternative wordings for expressing their search intentions. Although refined queries may contribute to the improvement of retrieval results, nevertheless their realization is intrinsically limited in that they consider nothing about the preferences of the user issuing that query. One way to go about selecting suitable query alternatives is to account for the user interests in the query refinement process. This task involves two great challenges. First we need to be able to effectively identify the user preferences and build a profile for every user. Second, once such a profile is available, we need to identify among a set of candidate query alternatives those that match the user interests. In this article, we present our work towards a personalized query refinement technique and we discuss how we address both of these challenges. Since Web users are reluctant to provide explicit information on their personal preferences, for the first challenge we attempt to determine them based on the analysis of the users' click history. In particular, we leverage a topical ontology for estimating the user's topic preferences based on her past searches. For the second challenge, we have developed a query refinement mechanism that uses the learnt user preferences in order to disambiguate the user's current query and thereafter identify alternative query wordings that match both the initial query semantics and the user preferences. Our experiments show that user preferences can be learnt accurately through the use of the topical ontology and refined queries based on the user preferences yield significant improvements in the search quality over existing query improvement techniques.
PAX1/SOX1 DNA methylation and cervical neoplasia detection: a Taiwanese Gynecologic Oncology Group (TGOG) study

We aimed to determine whether PAX1/SOX1 methylation could be translated to clinical practice for cervical neoplasia detection when used alone and in combination with current cytology‐based Pap screening. We conducted a multicenter case–control study in 11 medical centers in Taiwan from December 2009 to November 2010. Six hundred seventy‐six patients were included in the analysis, including 330 in the training set and 346 in the testing set. Multiplex quantitative methylation‐specific polymerase chain reaction (PCR) was performed with a TaqMan probe system using a LightCycler 480 Real‐Time PCR System (Roche). The level of human papilloma virus (HPV) was analyzed using a Hybrid Capture 2 system (Digene). Receiver operating characteristic curves were generated to obtain the best cutoff values from the training data set. The sensitivities, specificities, and accuracies were validated in the testing set. The sensitivities for methylated (m) PAX1m and SOX1m and HPV testing for detecting CIN3+ lesions were 0.64, 0.71, and 0.89, and the specificities were 0.91, 0.77, and 0.68, respectively. Combined parallel testing of PAX1m/SOX1m tests with Pap smearing showed superior specificity (0.84/0.71 vs. 0.66, respectively) and similar sensitivity (0.93/0.96 vs. 0.97) to the combination of Pap smear results and HPV testing. Thus, combined parallel testing using Pap smears and PAX1 or SOX1 methylation tests may provide better performance than a combination of Pap smears with HPV testing in detection for cervical neoplasia.
SASLL: A System Annotating Semantic Label of Location

Nowadays GPS embedded in mobile device such as smartphones can easily identify people's physical locations. However, in daily life people are more concerned about semantic locations (such as dormitories, laboratories, shopping malls, etc.). Usually GPS positioning uses continuous sampling method, which results in a lot of semantically independent sample points. We call these points outliers. How to remove outliers from GPS data and thereby cluster meaningful semantic places is a research challenge in current field of pervasive computing. Aiming at the characteristics of this problem, we first propose a novel approach to add semantic annotations to newly discovered places every day. We use an unsupervised method to discover semantic places, which ensures accuracy of the results and reduces the amount of calculation. Secondly, we discuss the concept of outliers in GPS data collected in daily life, and then eliminate outliers using a density-based method. Moreover, we perform experiments to validate its effectiveness. Thirdly by taking advantage of rule-based inference and reverse geocoding we proposed an approach to calculate the probable semantic labels, which can help user annotate places and reduce the burden on users. Finally, we develop a local System Annotating Semantic Label of Location(SASLL) and by carrying out experiments we demonstrate the validity of our research.
IDENTIFYING CONTROL GROUPINGS AND MENU STRUCTURES FOR ADVANCED AUTOMOTIVE SYSTEMS USING PSYCHOLOGICAL CLUSTERING AND SCALING TECHNIQUES

In this paper, the authors describe two studies which use empirical psychological methods to identify users' conceptual organization of automotive system functions. The studies extend the use of formal clustering and scaling techniques to the design of more complex automotive systems offering a greater variety of features and functions. The results are intended to provide guidance in the layout of control and the structure of hierarchical menus in human/machine interface (HMIs) for two products.