Miracle-dz/UniFAR-FTUs huggingface dataset:
A Markov random field model for network-based analysis of genomic data

MOTIVATION A central problem in genomic research is the identification of genes and pathways involved in diseases and other biological processes. The genes identified or the univariate test statistics are often linked to known biological pathways through gene set enrichment analysis in order to identify the pathways involved. However, most of the procedures for identifying differentially expressed (DE) genes do not utilize the known pathway information in the phase of identifying such genes. In this article, we develop a Markov random field (MRF)-based method for identifying genes and subnetworks that are related to diseases. Such a procedure models the dependency of the DE patterns of genes on the networks using a local discrete MRF model. RESULTS Simulation studies indicated that the method is quite effective in identifying genes and subnetworks that are related to disease and has higher sensitivity and lower false discovery rates than the commonly used procedures that do not use the pathway structure information. Applications to two breast cancer microarray gene expression datasets identified several subnetworks on several of the KEGG transcriptional pathways that are related to breast cancer recurrence or survival due to breast cancer. CONCLUSIONS The proposed MRF-based model efficiently utilizes the known pathway structures in identifying the DE genes and the subnetworks that might be related to phenotype. As more biological networks are identified and documented in databases, the proposed method should find more applications in identifying the subnetworks that are related to diseases and other biological processes.
Impact of Long-Term Proton Pump Inhibitor Therapy on Gut Microbiota in F344 Rats: Pilot Study

Background/Aims To evaluate changes in gut microbiota composition following long-term proton pump inhibitor (PPI) treatment. Methods Twenty-four-week-old F344 rats were fed diets with (n=6) or without (n=5) lansoprazole for 50 weeks. Profiles of luminal microbiota in the terminal ileum were then analyzed. Pyrosequencing of the 16S rRNA gene was performed using an FLX genome sequencer (454 Life Sciences/Roche). Results Rats treated with lansoprazole showed significantly reduced body weights compared to controls (lansoprazole-treated rats and controls, 322.3±15.3 g vs 403.2±5.2 g, respectively, p<0.001). However, stool frequencies and consistencies did not differ between the two groups. The composition of the gut microbiota in lansoprazole-treated rats was quite different from that of the controls. In the controls, the microbiota profiles obtained from the terminal ileum showed a predominance of Proteobacteria (93.9%) due to the abundance of Escherichia and Pasteurella genera. Conversely, lansoprazole-treated rats showed an elevated population of Firmicutes (66.9%), which was attributed to an increased ratio of Clostridium g4 to Lactobacillus genera. Conclusions This preliminary study suggests that long-term administration of PPI may cause weight loss and changes to the microbiota in the terminal ileum.
Efficient Design Methodology of RF-MEMS based Tuner

This paper describes a design methodology specifically developed for RF-MEMS based tuner, which translates into optimal performances in terms of both impedance coverage of the Smith Chart and |GammaMAX| value. The design methodology is moreover associated with an RF-MEMS technology developed for medium power (in the watt range) applications and exhibiting a design robustness regarding the capacitive RF-MEMS contact quality. A tuner has been designed thanks to this efficient procedure, fabricated and measured. The circuit exhibits excellent measured RF-performances: a wide impedance coverage is reached from the first test with a value of |GammaMAX| of 0.82 at 14 GHz.
Subthreshold Frequency Synthesis for Implantable Medical Transceivers

Implantable medical devices (IMDs) have evolved greatly since the first pacemaker was designed in the 1950s. The current generation of IMDs are capable of replacing damaged or malfunctioning organs, and are designed for long-term patient care. Cochlear implants, which differ greatly from hearing aids, convert received audio signals to electrical impulses and are capable of bypassing damaged parts of the ear and interfacing directly with auditory nerves. Microstimulators for neuromuscular stimulation can restore functionality to paralysed limbs. Implantable drug administration devices can deliver precise amounts of a drug, such as insulin for diabetics, at particular intervals, replacing the need for regular injections. Wireless IMDs designed for biotelemetry applications include implantable ECG and EEG recording, intra-ocular pressure sensing and wireless endoscopy capsules. In order to address the unique design requirements of wireless IMDs, namely ultra-low power consumption to extend battery life, small form factor to make the device suitable for implantation, and reliability to ensure correct operation once implanted, circuit designers must use new topologies and design techniques when conventional designs fail to address these requirements. In this work, we propose several novel circuits for an integer-N frequency synthesizer operating in the 402 MHz to 405 MHz Medical Implant Communication Service (MICS).
MEASURING AEROSOL ABSORPTION FROM OMI NEAR UV OBSERVATIONS

An assessment of OMI retrievals of aerosol properties is presented. We compare OMI retrieved values of extinction and absorption optical depth, and aerosol single scattering albedo to AERONET ground-based measurements. An evaluation of the accuracy of the retrievals for a limited number of observations under cloud-free conditions shows a positive offset of about 0.03 in retrieved optical depth. This small offset is an indication of accurate sensor calibration to the 1% level. The retrieved SSA values agree well with RMS differences of 0.02-0.03 compared with the AERONET observations. This result shows that the UV technique is a very valuable tool for measuring aerosol absorption from space.
MOMENTUM: MetamOrphic malware exploration techniques using MSA signatures

Modern malware that are metamorphic or polymorphic in nature mutate their code by employing code obfuscation and encryption methods to thwart detection. Thus, conventional signature based scanners fail to detect these malware. In order to address the problems of detecting known variants of metamorphic malware, we propose a method using bioinformatics techniques effectively used for Protein and DNA matching. Instead of using exact signature matching methods, more sophisticated signature(s) are extracted using multiple sequence alignment (MSA). The results show that the proposed method is capable of identifying malware variants with minimum false alarms and misses. Also, the detection rate achieved with our proposed method is better compared to commercial antivirus products used in the study.
Activity Context-Aware System Architecture

We propose a reference architecture for intelligent contextaware natural speech-enabled systems delivering complex functionality, with direct access to information, simplifying business processes and activities while providing domainspecific and task-specific depth in interactive banking, insurance, wealth management, finance, clinical, legal, telecom customer service, operations, supply chain, connected living room, and personal assistants. This system understands not just words, but intentions, and context of the interaction. We accomplish this through a marriage of speech recognition with advanced natural language processing techniques, scalable inference and semantic technologies. This architecture is expected to dramatically improve the quality of proactive decision support provided by virtual agents by enabling them to seek explanations, make predictions, generate and test hypothesis and perform whatif-analyses. The system can provide extreme personalization (N=1) by inferring user intent, making relevant suggestions, maintaining context, carrying out cost-benefit analysis from multiple perspectives, finding similar cases from organization and personal episodic memory before they are searched for, finding relevant documents and answers, and issues resolved by experts in similar situations. The architecture enables meaningfully correlating, finding and connecting people and information sources through discovery of causal, temporal and spatial relations. We present examples of demonstrations of concept in banking and insurance that we are in the process of developing. Next Generation Digital Workspace
A revisit to MPC of discrete-time nonlinear systems

In this paper, model predictive control (MPC) of discrete-time nonlinear systems with guaranteed nominal stability is revisited. In general the optimal cost function of the optimization problem might be discontinuous in the state of the systems, though it is not valuable to be chosen as a candidate Lyapunov function. Compared with the existing results, in this paper the optimal cost function is only used to show the convergence of the system trajectory to its equilibrium. Instead stability is proven in terms of a candidate Lyapunov function which is locally twice continuously differentiable in a vicinity of the equilibrium. Furthermore, asymptotic stability is achieved by the stability of the considered systems together with the convergence of the system trajectory to its equilibrium. In the end, locally robustly asymptotic stability of model predictive control is proven based on the locally continuous Lyapunov funciton. That is, locally inherent robustness of MPC of nonlinear systems with respect to input constraints, state constraints and terminal constraints is proven.
Latency Reduction in Contemporary DRAM Memories 83 2 Related Works

Performances of DRAM memories are characterized by memory latency and bandwidth. Contemporary DRAM memories more successfully satisfy demands for higher bandwidth than lower latency. In this paper solutions, which may reduce latency of these memories, are investigated. These solutions are two new controller policies called ’Write-miss Only Close-Page’ and ’Write-miss Only Close-Page-Open previous Page’ as well as several address remapping schemes. ’Write-miss Only Close-Page’ policy is basically a combination of the policies ’Open-Page’ and ’ClosePage-Autoprecharge’. For all DRAM reads ’Open-Page’ policy is used. Also for all DRAM writes that cause row-buffer hits ’Open-Page’ policy is used. For all DRAM writes that cause row-buffer misses ’ClosePage-Autoprecharge’ policy is used. ’Write-miss Only Close-Page-Open previous Page’ policy is the same as ’Writemiss Only Close-Page’, except that after the precharge the previously open row is opened again. Simulations show improvements in using these combined policies. Permutation-based Page Interleaving scheme is known as an effective address remapping scheme for reducing row-buffer conflicts, which are consequence of conflict cache memory misses. This scheme is based on using xor circuits for changing bank indices of data blocks that fit into the same cache memory line set. We improve this scheme by proposing five similar schemes, with slightly better effectiveness. Three of the proposed schemes have approximately the same performances, but do not use xor circuits at all. Two of the proposed schemes use xor circuits but have slightly better performances.
Audio fingerprinting based on dynamic subband locating and normalized SSC

Audio fingerprint is a content-based compact feature that summarizes an audio clip. As same as we using human fingerprint to recognize people, audio fingerprint can be used to retrieval unknown audio clips. In this paper, we propose an algorithm which extracts audio fingerprint based on dynamic subband locating and normalized SSC (Spectral Subband Centroid). SSC has been found to be related the human sensation of the brightness of an audio signal. By using this algorithm, recognize an unknown audio clip efficient and highly robust in the presence of noise be possible. The preliminary result of our experiments shows prominent performance.
A Survey of Modern Data Classification Techniques

In this paper, we present an overview of existing data classification algorithms. All these algorithms are described more or less on their own. Classification is a very popular and computationally expensive task. We also explain the fundamentals of data classification. We describe today’s approaches for data classification. From the broad variety of efficient algorithms that have been developed we will compare the most important ones. We will systematize the algorithms and analyze their performance based on both their run time performance and theoretical considerations. Their strengths and weaknesses are also investigated. It turns out that the behavior of the algorithms is much more similar as to be expected.
Reliability and Validity of the Multidimensional Locus of Control IPC Scale in a Sample of 3668 Greek Educators

The Multidimensional Locus of Control IPC Scale (IPC LOC Scale) is an instrument for assessing the locus of control on adults. The aim of the present study is to translate the IPC LOC Scale and evaluate its reliability and validity in a sample of Greek teachers. Data were collected from a nationwide sample of 3668 educators of all levels and specialties. The Cronbach’s alpha coefficient was used to determine the internal consistency reliability. A confirmatory factor analysis (CFA) was conducted in order to test the construct validity of the questionnaire. Validity was further examined by investigating the correlation of the IPC LOC Scale with the Rosenberg self-esteem scale (RSES) and its association with several demographic and work-related data. Internal consistency reliability was satisfactory with a Cronbach’s alpha above 0.70 for all LOC dimensions. CFA confirmed that the items composing the three subscales of the IPC LOC Scale measure the same construct. Also, the root mean square error of approximation (RMSEA), the comparative fit index (CFI) and the goodness of fit index (GFI) values were 0.053, 0.951, and 0.937, respectively for the three-factor model, further confirming the manufacturer’s theory for the three latent variables, Internality, Powerful Others, and Chance. Intercorrelations and correlation coefficients between the IPC LOC Scale and the RSES were significant, while age and sex differences were also found. The Greek version of the IPC LOC Scale was found to have satisfactory psychometric properties and could be used to evaluate the locus of control in Greek teachers.
Dealing with the Functional Units Starvation in SMT

Simultaneous Multithreading(SMT) technology is designed for using the hardware resources more efficiently by implementing Thread Level Parallelism. Usually, an SMT processor fetches instructions from different threads each cycle and fulfills shared instruction queues. Hence, the quality of the instruction sequence which is mainly constructed by the fetch unit would heavily affect the SMT processor's performance. Recently, the fetch policy has attracted many scientists' attention, and also a lot of work has been done in this field. These new designed fetch policies concentrate on improving the throughput by monitoring the status of pipeline to decide which threads to be fetched, such as the instruction count and the cache miss rate. The goal of this paper is to involve the functional units resources into the fetch policy, which has never been carefully studied. We simplify the inefficient use problem of the functional units in SMT, propose a new metric to reflect the degree of the inefficient use and design a new fetch policy to increase the throughput by reliving it. Finally, we evaluate the new policy and the throughput can be improved up to 22% and 3.25% on average.
A Real-Time Soft Shadow Volume Algorithm

Rendering of shadows is a very important ingredient in three-dimensional graphics since they increase the level of realism and provide cues to spatial relationships. Area or volumetric light sources give rise to so called soft shadows, i.e., there is a smooth transition from no shadow to full shadow. For hard shadows, which are generated by point light sources, the transition is abrupt. Since all real light sources occupy an area or volume, soft shadows are more realistic than hard shadows. Fast rendering of soft shadows, preferably in real time, has been a subject for research for decades, but so far this has mostly been an unsolved problem. Therefore, this thesis, which is based on five papers, focuses on how to achieve real-time rendering of soft shadows. The first four papers constitute the foundation and evolution of a new algorithm, called the soft shadow volume algorithm, and the fifth paper provides an essential proof for correctness and generality of this and some previous shadow algorithms. The algorithm augments and extends the well-known shadow volume algorithm for hard shadows. Two passes are used, where the first pass consist of the classic shadow volume algorithm to generate the hard shadows (umbra). The second pass compensates to provide the softness (penumbra). This is done by generating penumbra wedges and rasterizing them using a custom pixel shader that for each rasterized pixel projects the hard shadow quadrilaterals onto the light source and computes the covered area. A result of the thesis is an algorithm capable of real-time soft shadows that utilizes programmable graphics hardware. The algorithm produce high-quality shadows for area light sources and volumetric light sources. It also handles textured light sources, which currently is a very rare capability among real-time soft shadow algorithms. Even video textures are allowed as light sources.
Alternative Estimates of the Effect of the Increase of Life Expectancy on Economic Growth

Until recently the literature has found evidence of a positive, significant, and sizable influence of life expectancy on economic growth. This view has been challenged by Acemoglu and Johnson (2007). They find no evidence that the large exogenous increase in life expectancy led to a significant increase in per capita economic growth. This paper takes up the modelling and estimation framework presented in Acemoglu and Johnson (2007), and presents alternative estimates on the impact of life expectancy on population, GDP, and GDP per capita by using alternative instrument, timeline, and country groups. The findings suggest that the results differ significantly from that provided in Acemoglu and Johnson (2007); that the generalization of the pessimistic outcomes with regards to the impact of life expectancy on income per capita requires caution; and the increase of life expectancy may have had a positive impact on income per capita growth.
Automatic Attendance and Mobile Learning System in Sensor-Enabled Heterogeneous and Dynamic University Environment.

Many questions come up when we think about the academic performance of students and the ways and means to ameliorate that. In today’s digital era we can use latest technologies to improve student performance and attendance. Class attendance, quizzes and assignments play a key role in academics. In this paper, we have defined a framework for improving class attendance based on GPS and face detection, and new learning environment where students can use devices like enabled devices, iPad, Tab, iPhone, blackberry, laptop etc. for class quizzes and assignments. We proposed an online as well off-line model for quizzes that will run on platform independent applications. Keywords : Heterogeneous, face recognition, GPS, Platform Independent application, mobile learning
Draft Genome Sequence of Methicillin-Resistant Staphylococcus epidermidis Strain ET-024, Isolated from an Endotracheal Tube Biofilm of a Mechanically Ventilated Patient

ABSTRACT Staphylococcus epidermidis strain ET-024 was isolated from a biofilm on an endotracheal tube of a mechanically ventilated patient. This strain is resistant to methicillin, and the draft genome sequence shares some characteristics with other nosocomial S. epidermidis strains (such as S. epidermidis RP62A).
Personal and Indoor PM2.5 Exposure from Burning Solid Fuels in Vented and Unvented Stoves in a Rural Region of China with a High Incidence of Lung Cancer

The combustion of biomass and coal is the dominant source of household air pollution (HAP) in China, and contributes significantly to the total burden of disease in the Chinese population. To characterize HAP exposure related to solid fuel use and ventilation patterns, an exposure assessment study of 163 nonsmoking female heads of households enrolled from 30 villages was conducted in Xuanwei and Fuyuan, two neighboring rural counties with high incidence of lung cancer due to the burning of smoky coal (a bituminous coal, which in health evaluations is usually compared to smokeless coal—an anthracite coal available in some parts of the area). Personal and indoor 24-h PM2.5 samples were collected over two consecutive days in each household, with approximately one-third of measurements retaken in a second season. The overall geometric means (GM) of personal PM2.5 concentrations in Xuanwei and Fuyuan were 166 [Geometric Standard Deviation (GSD):2.0] and 146 (GSD:1.9) μg/m3, respectively, which were similar to the indoor PM2.5 air concentrations [GM(GSD):162 (2.1) and 136 (2.0) μg/m3, respectively]. Personal PM2.5 was moderately highly correlated with indoor PM2.5 (Spearman r = 0.70, p < 0.0001). Burning wood or plant materials (tobacco stems, corncobs etc.) resulted in the highest personal PM2.5 concentrations (GM:289 and 225 μg/m3, respectively), followed by smoky coal, and smokeless coal (GM:148 and 115 μg/m3, respectively). PM2.5 levels of vented stoves were 34–80% lower than unvented stoves and firepits across fuel types. Mixed effect models indicated that fuel type, ventilation, number of windows, season, and burning time per stove were the main factors related to personal PM2.5 exposure. Lower PM2.5 among vented stoves compared with unvented stoves and firepits is of interest as it parallels the observation of reduced risks of malignant and nonmalignant lung diseases in the region.
Global Awareness Dialogue Project: Exploring Potential for Faculty Transformation Through a Professional Development Series

This article examines a faculty professional development program aimed at engaging faculty in an ongoing discussion about global awareness and the practices surrounding teaching and learning in a linguistically and culturally diverse classroom. The program is modeled on two key components: the engagement of undergraduate students and faculty in a structured dialogue outside the classroom and the contributions of experts to faculty discussions to locate and contextualize best practices. The initiative’s potential to affect faculty perspectives is explored through a transformative learning framework. Short-term and long-term assessments show that participants were motivated to improve and implement new instructional practices.
Compilation and Exploitation of the IJS-ELAN Parallel Corpus

With more and more text being available in electronic form, it is becoming relatively easy to obtain digital texts together with their translations. The paper presents the processing steps necessary to compile such texts into parallel corpora, an extremely useful language resource. Parallel corpora can be used as a translation aid for second-language learners, for translators and lexicographers, or as a datasource for various language technology tools. We present our work in this direction, which is characterised by the use of open standards for text annotation, the use of publicly available third-party tools and wide availability of the produced resources. Explained is the corpus annotation chain involving normalisation, tokenisation, segmentation, alignment, word-class syntactic tagging, and lemmatisation. Two exploitation results over our annotated corpora are also presented, namely a Web concordancer and the extraction of bi-lingual lexica.