Miracle-dz/UniFAR-FTUs huggingface dataset:
Cardiac-Specific Overexpression of Human Stem Cell Factor Promotes Epicardial Activation and Arteriogenesis After Myocardial Infarction

Background—The adult epicardium is a potential source of cardiac progenitors after myocardial infarction (MI). We tested the hypothesis that cardiomyocyte-specific overexpression of membrane-associated human stem cell factor (hSCF) enhances epicardial activation, epicardium-derived cells (EPDCs) production, and myocardial arteriogenesis post MI. Methods and Results—Wild-type and the inducible cardiac-specific hSCF transgenic (hSCF/tetracycline transactivator) mice were subjected to MI. Wilms tumor-1 (Wt1)–positive epicardial cells were higher in hSCF/tetracycline transactivator compared with wild-type mice 3 days post MI. Arteriole density was significantly higher in the peri-infarct area of hSCF/tetracycline transactivator mice compared with wild-type mice 5 days post MI. In cultured EPDCs, adenoviral hSCF treatment significantly increased cell proliferation and growth factor expression. Furthermore, adenoviral hSCF treatment in wild-type cardiomyocytes significantly increased EPDC migration. These effects of hSCF overexpression on EPDC proliferation and growth factor expression were all abrogated by ACK2, a neutralizing antibody against c-kit. Finally, lineage tracing using ROSAmTmG;Wt1CreER mice showed that adenoviral hSCF treatment increased Wt1+ lineage–derived EPDC migration into the infarcted myocardium 5 days post MI, which was inhibited by ACK2. Conclusions—Cardiomyocyte-specific overexpression of hSCF promotes epicardial activation and myocardial arteriogenesis post MI.
Interactive Sketch‐Driven Image Synthesis

We present an interactive system for composing realistic images of an object under arbitrary pose and appearance specified by sketching. Our system draws inspiration from a traditional illustration workflow: The user first sketches rough ‘masses’ of the object, as ellipses, to define an initial abstract pose that can then be refined with more detailed contours as desired. The system is made robust to partial or inaccurate sketches using a reduced‐dimensionality model of pose space learnt from a labelled collection of photos. Throughout the composition process, interactive visual feedback is provided to guide the user. Finally, the user's partial or complete sketch, complemented with appearance requirements, is used to constrain the automatic synthesis of a novel, high‐quality, realistic image.
An empirical comparison of several recent epistatic interaction detection methods

MOTIVATION Many new methods have recently been proposed for detecting epistatic interactions in GWAS data. There is, however, no in-depth independent comparison of these methods yet. RESULTS Five recent methods-TEAM, BOOST, SNPHarvester, SNPRuler and Screen and Clean (SC)-are evaluated here in terms of power, type-1 error rate, scalability and completeness. In terms of power, TEAM performs best on data with main effect and BOOST performs best on data without main effect. In terms of type-1 error rate, TEAM and BOOST have higher type-1 error rates than SNPRuler and SNPHarvester. SC does not control type-1 error rate well. In terms of scalability, we tested the five methods using a dataset with 100 000 SNPs on a 64 bit Ubuntu system, with Intel (R) Xeon(R) CPU 2.66 GHz, 16 GB memory. TEAM takes ~36 days to finish and SNPRuler reports heap allocation problems. BOOST scales up to 100 000 SNPs and the cost is much lower than that of TEAM. SC and SNPHarvester are the most scalable. In terms of completeness, we study how frequently the pruning techniques employed by these methods incorrectly prune away the most significant epistatic interactions. We find that, on average, 20% of datasets without main effect and 60% of datasets with main effect are pruned incorrectly by BOOST, SNPRuler and SNPHarvester. AVAILABILITY The software for the five methods tested are available from the URLs below. TEAM: http://csbio.unc. edu/epistasis/download.php BOOST: http://ihome.ust. hk/~eeyang/papers.html. SNPHarvester: http://bioinformatics.ust. hk/SNPHarvester.html. SNPRuler: http://bioinformatics.ust. hk/SNPRuler.zip. Screen and Clean: http://wpicr.wpic. pitt.edu/WPICCompGen/. CONTACT wangyue@nus.edu. sg.
Relationship Between Body Composition Parameters and Metabolic Syndrome in Young Thai Adults

Objective: The aim of this study was to evaluate the relationship between body composition parameters, i.e. waist circumference, android fat mass (AFM), gynoid fat mass (GFM), android to gynoid fat mass ratio (AG ratio) and metabolic syndrome (MS) risk components in young Thai adults. Methods: This was a cross-sectional study conducted among 391 adolescents (174 male, 217 female). The body mass index (BMI), waist circumference, blood pressure, triglyceride, high-density lipoprotein (HDL) cholesterol and glucose levels were determined. AFM, GFM and AG ratio were assessed by dual-energy X-ray absorptiometry (DXA). Linear regression analysis was done to assess the relationship of waist circumference, AFM, GFM and AG ratio with MS risk components’ score, separately. Results: Among 391 young adults aged 18.5-21.8 years, MS was found in 5.9%. Participants with MS (n=23) had a significantly higher weight, height and BMI than those without MS. There was no statistically significant difference in bone mineral density between the two groups. At univariable linear regression analysis, waist circumferences, AFM, GFM and AG ratio showed significant relationship with MS risk components’ score. However, after adjusting for gender, birth weight and BMI, AG ratio demonstrated greater relationship with MS risk components’ score (β 1.89, 95%CI 1.096-2.978) than waist circumference (β 0.046, 95%CI 0.033-0.058) and AFM (β 0.979, 95%CI 0.667-1.290). No significant association was observed between GFM and MS risk components’ score (β 0.077, 95%CI -0.089-0.243). Conclusion: The results from this study indicated that AG ratio is a stronger predictor of MS than waist circumference and AFM in young Thai adults. The role of AG ratio for the diagnosis of MS needs to be further investigated.
An analysis of decay-usage scheduling in multiprocessors

Priority-ageing or decay-usage scheduling is a time-sharing scheduling policy capable of dealing with a workload of both interactive and batch jobs by decreasing the priority of a job when it acquires CPU time, and by increasing its priority when it does not use the (a) CPU. In this paper we deal with a decay-usage scheduling policy in multiprocessor systems modeled after widely used systems. The priority of a job consists of a base priority and a time-dependent part based on processor usage. Because the priorities in our model are time dependent, a queueing-theoretic analysis, for instance for the mean response time, seems impossible. Still, it turns out that as a consequence of the scheduling policy, the shares of available CPU time obtained by jobs converge, and a deterministic analysis for these shares is feasible: for a fixed set of jobs with very large (infinite) processing demands, we derive the relation between their base priorities and their steady-state shares. In addition, we analyze the relation between the values of the parameters of the scheduler and the level of control it can exercise over the steady-state shares. We validate the model by simulations and by measurements of actual systems.
Deletion of EphA4 enhances deafferentation‐induced ipsilateral sprouting in auditory brainstem projections

Axonal selection of ipsilateral and/or contralateral targets is essential for integrating bilateral sensory information and for coordinated movement. The molecular processes that determine ipsilateral and contralateral target choice are not fully understood. We examined this target selection in the developing auditory brainstem. Ventral cochlear nucleus (VCN) axons normally project to the medial nucleus of the trapezoid body (MNTB) only on the contralateral side. However, after unilateral removal of cochlear input in neonates, we found that axons from the unoperated VCN sprout and project to MNTB bilaterally. We found that EphA4 is expressed in the mouse auditory brainstem during development and during a sensitive period for ipsilateral sprouting, so we hypothesized that deletion of the Eph receptor EphA4 would impair target selection in these auditory pathways. Lipophilic dyes were used to evaluate quantitatively the brainstem projections in wild‐type and EphA4‐null mice. VCN‐MNTB projections in EphA4‐null mice were strictly contralateral, as in wild‐type mice. However, after deafferentation, EphA4‐null mice had a significant, threefold increase in the proportion of axons from the intact VCN that sprouted into ipsilateral MNTB compared with wild‐type mice. Heterozygous mice had a twofold increase in these projections. These results demonstrate that EphA4 influences auditory brainstem circuitry selectively in response to deafferentation. Although this axon guidance molecule is not by itself necessary for appropriate target choice during normal development, it is a strong determinant of ipsilateral vs. contralateral target choice during deafferentation‐induced plasticity. J. Comp. Neurol. 504:508–518, 2007. © 2007 Wiley‐Liss, Inc.
Development of the first Thai-made S-Band antenna system for THAICHOTE satellite control ground station

This paper presents a project based on an antenna system development for a ground station in Thailand. The “Wise Antenna of Transmission Execution & Receiving System” or WATERs is initiated with the aim to build ground station-related capacity within the country and attain sustainability in this technology. The development consists of Radio Frequency and Intermediate Frequency (RF/IF), tracking system and Monitoring and Control (M&C). This developed system is anticipated to replace the original system, which has been used for several years supporting THAICHOTE satellite communication. It will be applied to the following satellite systems such as THAICHOTE-2 and THAICHOTE-3. THAICHOTE is a sun synchronous near-polar LEO satellite. Therefore, tracking and ground station link system are essential. To develop a Thai-made system, GISTDA team must intensively study the original system.
SDCA without Duality

Stochastic Dual Coordinate Ascent is a popular method for solving regularized loss minimization for the case of convex losses. In this paper we show how a variant of SDCA can be applied for non-convex losses. We prove linear convergence rate even if individual loss functions are non-convex as long as the expected loss is convex.
Requirements Mean Decisions! – Research issues for understanding and supporting decision-making in Requirements Engineering

Requirements result from stakeholders’ decisions. These decisions are governed by hard issues such as the balance between cost and functionality, and soft issues such as social processes and organisational politics. The quality of the decision-making process is crucial as good-enough requirements is the foundation for a successful focusing of the available development resources. In this paper it is argued that research should focus more on Requirements Engineering (RE) as a decision-making process with focus on describing and understanding it, and on providing and evaluating methods to improve and support RE decisionmaking. There are many opportunities of fruitful interdisciplinary research when combining RE with areas such as decision theory, decision support systems, operations research and management science. A number of research issues are identified and several aspects of RE decisionmaking are described, with the aim of promoting research on methods which can better support requirements engineers in their decision-making.
A phrase-based approach based on morphological information for Japanese-Uighur statistical machine translation system

Japanese and Uighur language has many similarities. Uighur language belongs to Altaic language branch of Turkic language, the statistical translation approach of Japanese Uighur language in machine translation system is a blank. This paper analyses the approach of statistical machine translation system in Uighur language, discusses how to establishing of dictionary and parallel corpus and phrase based statistical machine translation system based on linguistic rules for Uighur language, and it presents the method of statistical machine translation system based on morphological information of Uighur, the rule base and the dictionary.
Experimental study on elevator using encoderless magnetic motion (ICCAS 2014)

A Elevator system composed of a permanent magnet linear synchronous motor (PMLSM) as a stator and a magnetic plate as a mover is proposed in this paper. Rather than using a conventional encoder or resolver, position is measured by adopting a vector control method using two Hall sensors for generating a rectangular wave signal. This method estimates the velocity and position of a mover using the quadrature of two hall sensor signals instead of an encoder signal. Vector control of the PMLSM using two Hall sensors for generating a rectangular wave is proved to control the system in a stable and efficient manner through simulations. Hardware experiments reveal that the position control performance is within the range of 30~50μm with an accuracy of 10~20μm, a two-fold improvement over the conventional method. The proposed method exhibits an economical efficiency and practical usefulness. The vector control technique using two Hall sensors can be installed in a narrow place. Accordingly, the proposed method can be implemented in applications where conventional encoders or resolvers cannot operate.
Trust oriented resource allocation using bidding

Conjunction of massive amount of idle computers or resources that may be loosely coupled, heterogeneous and geographically dispersed to reach a common goal leads to a virtual computing platform for sharing resources across the world. Resource management, application development and usage models in these environments has some dilemma in undertaking resources due to resource providers with multiple administrative domains having their own policies and terms. A ditch in the Grid computing environment is how to coordinate the distributed resources amongst a dynamic set of individuals and organizations where the requesters and providers are allowed to join and leave Grid environment at any time. Bidding model prevents single point of failure and server overload problems of match making model while minimizing turnaround time by using some set of deterministic and probabilistic selection heuristics where resource requesters and resource providers were given the privilege to take autonomous decisions regarding resource selection. Autonomous decision making is enabled via peer-to-peer decentralized scheduling frame work. In decentralized environment, lack of global information is a key challenge to facilitate optimum decision making which can lead to greedy selection of the best provider. Therefore some probabilistic selection is used to reduce the fairness deviation among processors while minimizing the turnaround time. Currently just various level of information about providers has been concentrated to minimize the turnaround time. Simply concentrating on various level of information may also leads to failure due to rejection factor resulted by number of failures occurred at provider. However by merging trust oriented mechanisms along with various level of information, rejection factor can also be minimized along with minimization of the turnaround time.
Exploration of Interstate College and Post-Graduation Migration in the United States

Using national data, the present study first investigated interstate college migration. Unlike existing studies of interstate college migration, this study also tracked students to college graduation to explore their post-graduation migration, such as leaving to other states after graduating from instate institutions and returning to home states after graduating from out-of-state institutions. While a single equation approach has been widely used in migration research, this study used multi-level logistic regression that is rather new in the area of institutional research. In addition to state‟s economic conditions, certain institutional characteristics were found to influence differently depending of types of migration.
The Study of Multidimensional-Data Flow of Fishbone Applied for Data Mining

Data Mining Driven Fishbone, which is whole a new term, is an enhancement of abstractive conception of multidimensional-data flow of fishbone applied for data mining to optimize the process and structure of data mining. End-to-end DMDF diagram includes complex dataflow and different processing component and improvements for numerous aspects in multiply level. DMDF provides integrated platform and mixed methodology to support the whole life cycle of data mining with comprehensive methodology. Data preprocessing, data Classification, Association rule mining and Prediction are the foundation and linkage of the whole data mining process life cycle. DMDF supports combination of different mining component from strategy level, tactical level to abstractive level, and then re-engineered data mining process into execution system to realize reasonable architecture. DMDF is a new direction of the structure of data mining process.
A MULTI-BAND SPECTRAL SUBTRACTION METHOD FOR SPEECH ENHANCEMENT APPROVED BY SUPERVISORY COMMITTEE:

v ACKNOWLEDGEMENTS I would like to thank my adviser, Dr. Philipos Loizou, for his guidance in my studies and my work. He has offered me many helpful suggestions on conducting research and writing technical documents. Thanks are also in order to Dr. Emily Tobey for providing me with the opportunity to work with her wonderful team at the Callier Institute of Communication Disorders / UTD. I would like to thank Paul Dybala and Amanda Labue for conducting the subject test. I would like to take this opportunity to express my deepest gratitude to Dr. Neeraj Magotra of Texas Instruments – Dallas for the invaluable support and guidance he has given me in every aspect of my student and personal life. I am especially thankful for the wholehearted confidence that he has shown in my abilities. And finally to my wife, Sanmati, I would like to acknowledge my deepest appreciation for her love and caring, for her timely encouragements, for being my driving force and standing by me through thick and thin. The corruption of speech due to presence of additive background noise causes severe difficulties in various communication environments. This thesis addresses the problem of reduction of additive background noise in speech. The proposed approach is a frequency-dependent speech enhancement method based on the proven spectral subtraction method. Most implementations and variations of the basic spectral subtraction technique advocate subtraction of the noise spectrum estimate over the entire speech spectrum. However, real world noise is mostly colored and does not affect the speech signal uniformly over the entire spectrum. This thesis explores a Multi-Band Spectral Subtraction (MBSS) approach with suitable pre-processing of the speech data. Speech is processed into) 8 1 (≤ ≤ N N frequency bands and spectral subtraction is performed independently on each band using band-specific over-subtraction factors. This method provides a greater degree of flexibility and control on the noise subtraction levels that reduces artifacts in the enhanced speech, resulting in improved speech quality. The effect of the number of frequency band and the vii type of filter spacing (linear, logarithmic or mel) was investigated. Results showed that the proposed MBSS method with four linear-spaced frequency bands outperformed the conventional spectral subtraction method with respect to speech quality and reduced musical noise.
Performance Measurements of Mote Sensor Networks

In this paper we investigate the performance of mica2 and mica2dot Berkeley motes by means of an extensive experimental analysis. This study is aimed at analyzing the main elements that characterize the performance of a sensor network, e.g., power consumption in different operating conditions, impact of weather conditions, interference between neighboring nodes, etc. Even if the analysis is related to a specific technology it provides some general useful information. Specifically, we found that the transmission range of mote sensor nodes decreases significantly in the presence of fog or rain. We also investigate the interference between neighboring nodes and, based on the experimental results, we propose a channel model for mote sensor nodes. This model is very similar to the channel model of IEEE 802.11 networks.
Constructing Hierarchies for Triangle Meshes

We present a method to produce a hierarchy of triangle meshes that can be used to blend different levels of detail in a smooth fashion. The algorithm produces a sequence of meshes M/sub 0/, M/sub 1/, M/sub 2/. , M/sub n/, where each mesh M/sub i/ can be transformed to mesh M/sub i+1/ through a set of triangle-collapse operations. For each triangle, a function is generated that approximates the underlying surface in the area of the triangle, and this function serves as a basis for assigning a weight to the triangle in the ordering operation and for supplying the points to which the triangles are collapsed. The algorithm produces a limited number of intermediate meshes by selecting, at each step, a number of triangles that can be collapsed simultaneously. This technique allows us to view a triangulated surface model at varying levels of detail while insuring that the simplified mesh approximates the original surface well.
Action Detection by Fusing Hierarchically Filtered Motion with Spatiotemporal Interest Point Features

This chapter addresses the problem of action detection from cluttered videos. In recent years, many feature extraction schemes have been designed to describe various aspects of actions. However, due to the difficulty of action detection, e.g., the cluttered background and potential occlusions, a single type of features cannot effectively solve the action detection problems in cluttered videos. In this chapter, we propose a new type of features, Hierarchically Filtered Motion (HFM), and further investigate the fusion of HFM with Spatiotemporal Interest Point (STIP) features for action detection from cluttered videos. In order to effectively and efficiently detect actions, we propose a new approach which combines Gaussian Mixture Models (GMMs) with Branch-and-Bound search to locate interested actions in cluttered videos. The proposed new HFM features and action detection method have been evaluated on the classical KTH dataset and the challenging MSR Action Dataset II which consists of crowded videos with moving people or vehicles in background. Experiment results demonstrate that the proposed method significantly outperforms existing techniques especially for action detection in crowded videos.
Checking Applications using Security APIs with JOANA

JOANA is a tool for software security analysis, checking up to 100kLOC of full multithreaded Java. JOANA is based on sophisticated program analysis techniques and very precise. JOANA includes a new algorithm guaranteeing probabilistic noninterference, named RLSOD. JOANA needs few annotations, is open source, and was applied in several case studies. The current extended abstract discusses the analysis of security APIs using JOANA. In particular, we practically demonstrate a method which guarantees that code using a cryptographic API does not contain confidentiality leaks. The method is backed by a theorem from Küsters [6].