Miracle-dz/UniFAR-FTUs huggingface dataset:
Mining Frequent Patterns Using Queues In Large Databases

The proposed model helps mining frequent patterns in large databases by implementing queue data structure. The whole database is scanned only once and the data is compressed in the form of patterns in the queue structure. The frequent patterns are mined from this compressed database of queue structure. This queue approach brings efficiency in mining as the number of database scans is effectively less than two. Appropriate mathematical operations are designed and performed on queue data structure to achieve this efficiency. KeywordsQueue, Transactions, Itemsets, Frequent Patterns, Data Mining, Large Databases, Association Rule Mining.
The Regulation of IGF-1 Gene Transcription and Splicing during Development and Aging

It is commonly known that the insulin-like growth factor-I gene contains six exons that can be differentially spliced to create multiple transcript variants. Further, there are two mutually exclusive leader exons each having multiple promoter sites that are variably used. The mature IGF-I protein derived from the multiplicity of transcripts does not differ suggesting a regulatory role for the various transcript isoforms. The variant forms possess different stabilities, binding partners, and activity indicating a pivotal role for the isoforms. Research has demonstrated differential expression of the IGF-I mRNA transcripts in response to steroids, growth hormone, and developmental cues. Many studies of different tissues have focused on assessing the presence, or putative action, of the transcript isoforms with little consideration of the transcriptional mechanisms that generate the variants or the translational use of the transcript isoforms. Control points for the latter include epigenetic regulation of splicing and promoter usage in response to development or injury, RNA binding proteins and microRNA effects on transcript stability, and preferential use of two leader exons by GH and other hormones. This review will detail the current knowledge of the mechanical, hormonal, and developmental stimuli regulating IGF-1 promoter usage and splicing machinery used to create the variants.
Dynamic object tracking system

In this paper, we describe a moving object tracking system for a personal mobility platform designed to improve the mobility of handicapped and older people. The system consists of two steps for continuously detecting a certain target. To be specific, the first step is to designate a person as a target. In this step, if an object is locate within the certain area of near the vehicle, the system will perceive it as a target. Next step is to calculate the distance and direction between the vehicle and the target. When those information is provided to the tracking system, the vehicle has to follow the object for the purpose of keeping constant distance between them. The vehicle is equipped with two LiDAR sensors located on the front and left side of that, respectively. The function of the former sensor (HOKUYO-UTM30lx) is to find a target located in the front area of the vehicle, and that of the latter one(HOKUYO-URG04lx) is to discover a target located in the left area of that. In order to prove the effectiveness of the system, we conduct several experiments in indoor and outdoor environments. In the case of an indoor experiment, the vehicle detect a certain person as a target, and continuously follow in the place where people are crowded. In outdoor, vehicle platooning is performed by means of the system in three vehicles.
NAC-1, a Rat Brain mRNA, Is Increased in the Nucleus Accumbens Three Weeks after Chronic Cocaine Self-Administration

Chronic cocaine use leads to biochemical and behavioral changes that can persist for weeks to months after drug administration is discontinued. Alterations in gene expression in the mammalian CNS may contribute to these long-term neural consequences of cocaine abuse. A combined in situ transcription–PCR amplification strategy was used to isolate a novel mRNA, NAC-1, from the nucleus accumbens of rats 3 weeks after discontinuing 3 weeks of intravenous cocaine self-administration. In rats that self-administered cocaine, levels of NAC-1 were increased ∼50% in the nucleus accumbens but not in the dorsal striatum or hippocampus, when compared with levels from yoked-saline controls. In situ hybridization analysis demonstrated increased numbers of NAC-1-expressing cells in the nucleus accumbens of rats who had self-administered cocaine. NAC-1 mRNA exists as one form, ∼4400 nucleotides (nt) in size, and also is present at much lower amounts in non-neural tissues. A full-length cDNA clone was isolated from a whole brain library. The predicted polypeptide sequence contains a POZ domain in the first 120 amino acids; the same POZ domain sequence mediates protein–protein interactions among some transcriptional regulators. NAC-1 mRNA levels were also increased in the nucleus accumbens 1 week after 6 d of noncontingent cocaine treatments. Regulation of NAC-1 mRNA in the nucleus accumbens demonstrates a long-term effect of cocaine use on cellular function that may be relevant in behavioral sensitization or cocaine self-administration.
Pseudo-finite hard instances for a student-teacher game with a Nisan-Wigderson generator

For an NP ∩ coNP function g of the Nisan-Wigderson type and a string b outside its range we consider a two player game on a common input a to the function. One player, a computationally limited Student, tries to find a bit of g(a) that differs from the corresponding bit of b. He can query a computationally unlimited Teacher for the witnesses of the values of constantly many bits of g(a). The Student computes the queries from a and from Teacher’s answers to his previous queries. It was proved in [Kra11b] that if g is based on a hard bit of a one-way permutation then no Student computed by a polynomial size circuit can succeed on all a. In this paper we give a lower bound on the number of inputs a any such Student must fail on. Using that we show that there is a pseudo-finite set of hard instances on which all uniform students must fail. The hard-core set is defined in a non-standard model of true arithmetic and has applications in a forcing construction from [Kra11a].
Why European Entrepreneurs in the Water and Waste Management Sector Are Willing to Go beyond Environmental Legislation

Sustainability in the water sector in Europe is a major concern, and compliance with the current legislation alone does not seem to be enough to face major challenges like climate change or population growth and concentration. The greatest potential for improvement appears when companies decide to take a step forward and go beyond environmental legislation. This study focuses on the environmental responsibility (ER) of European small and medium-sized enterprises (SMEs) in the water and waste management sector and analyzes the drivers that lead these firms to the adoption of more sustainable practices. Our results show that up to 40% of European SMEs within this industry display environmental responsibility. Market pull has a low incidence in encouraging ER, while values and the strategic decisions of entrepreneurs seem decisive. Policy makers should prioritize subsidies over fiscal incentives because they show greater potential to promote the adoption of environmental responsibility among these firms.
IMMERSIVE WELL PATH PLANNING: THE ADDED VALUE OF INTERACTIVE IMMERSIVE VISUALIZATION

The final copy of this thesis has been examined by the signators, and we find that both the content and the form meet acceptable presentation standards of scholarly work in the above mentioned discipline. Immersive well path planning: The added value of interactive immersive visualization Thesis directed by Professor Clayton Lewis The benefits of immersive visualization are primarily anecdotal; there have been few controlled users studies that have attempted to quantify the added value of immersion for problems requiring the manipulation of virtual objects. This research quantifies the added value of immersion for a real-world industrial problem: oil well path planning. An experiment was designed to compare human performance between an immersive virtual environment (IVE) and a desktop workstation with stereoscopic display. This work consisted of building a cross-environment application, capable of visualizing and editing a planned well path within an existing oilfield, and conducting an user study on that application. This work presents the results of sixteen participants who planned the paths of four oil wells. Each participant planned two well paths on a desktop workstation with a stereoscopic display and two well paths in a CAVE TM-like IVE. Fifteen of the participants completed well path editing tasks faster in the IVE than in the desktop environment, which is statistically significant (p < 0.001). The increased speed in the IVE was complimented by an increase correct solutions. There was a statistically significant (p < 0.05) increase in correct solutions in the IVE. The results suggest that an IVE allows for faster and more accurate problem solving in a complex interactive three-dimensional domain. iv Acknowledgments Thanks to Clayton Lewis, my thesis advisor, for his support and guidance throughout this work; Touysinhthiphonexay for their help and guidance offered as members of my thesis committee; the staff at the B.P. Center for Visualization, for giving me the opportunity to conduct this research; Gwen Pech for working tirelessly to keep the system running in an effort to support my work; Jonathan Marbach for his countless contributions to this work, we spent many hours working together, laughing together and learning from each other; Jo Solonika and Michael Gruchalla for their fearless proofreading ; Michelle for her unwavering love, patience, and support; and finally, all the research participants for volunteering their time.
Exotic Grass Invasion Reduces Survival of Amblyomma americanum and Dermacentor variabilis Ticks (Acari: Ixodidae)

Abstract Exotic plants often invade areas of high human activity, such as along trails, roads, and forest edges, and in disturbed riparian areas. These same habitat types are also favored by ticks. This convergence suggests that habitat modifications caused by exotic plant invasions may mediate disease vector habitat quality, indirectly affecting human disease risk at the local spatial scale. We tested the hypothesis that experimental invasions of Japanese stiltgrass, Microstegium vimineum (Trin.) A. Camus, alter soil surface microclimate conditions, thereby reducing habitat quality for ticks. Microstegium is an exotic annual grass that is highly invasive throughout the eastern United States where the vector ticks Amblyomma americanum (Linnaeus) and Dermancentor variabilis (Say) occur. Ticks (n = 100 per species) were introduced into experimentally invaded and native vegetation control plots (n = 5 per treatment). D. variabilis mortality rate increased 173% and A. americanum mortality rate increased 70% in the invaded plots relative to those in control plots. Microstegium invasion also resulted in a 13.8% increase in temperature and an 18.8% decrease in humidity, which are known to increase tick mortality. We predict that areas invaded by Microstegium will have lower densities of host-seeking ticks and therefore reduced human disease risk. Our results emphasize the role of invasive species in mediating disease vector populations, the unpredictable consequences of biological invasions, and the need for integrative management strategies that can simultaneous address exotic plant invasions and vector-borne disease.
An approximate dynamic programming based non-myopic sensor selection method for target tracking

In this paper, we study the non-myopic sensor selection problem for target tracking in wireless sensor networks based on quantized sensor data. Using the conditional posterior Cramér-Rao lower bound (C-PCRLB) as a sensor selection metric, we formulate and solve a non-myopic sensor selection problem using an approximate dynamic programming (A-DP) algorithm. Given a constraint on the total number of selected sensors allowed while observing the target over a time window, simulation results show that the proposed non-myopic sensor selection scheme based on A-DP is computationally very efficient and yields better tracking performance than the myopic sensor selection scheme.
Automated annotation of gene expression image sequences via non-parametric factor analysis and conditional random fields

Motivation: Computational approaches for the annotation of phenotypes from image data have shown promising results across many applications, and provide rich and valuable information for studying gene function and interactions. While data are often available both at high spatial resolution and across multiple time points, phenotypes are frequently annotated independently, for individual time points only. In particular, for the analysis of developmental gene expression patterns, it is biologically sensible when images across multiple time points are jointly accounted for, such that spatial and temporal dependencies are captured simultaneously. Methods: We describe a discriminative undirected graphical model to label gene-expression time-series image data, with an efficient training and decoding method based on the junction tree algorithm. The approach is based on an effective feature selection technique, consisting of a non-parametric sparse Bayesian factor analysis model. The result is a flexible framework, which can handle large-scale data with noisy incomplete samples, i.e. it can tolerate data missing from individual time points. Results: Using the annotation of gene expression patterns across stages of Drosophila embryonic development as an example, we demonstrate that our method achieves superior accuracy, gained by jointly annotating phenotype sequences, when compared with previous models that annotate each stage in isolation. The experimental results on missing data indicate that our joint learning method successfully annotates genes for which no expression data are available for one or more stages. Contact: uwe.ohler@duke.edu
Exploratory sequential data analysis for multi-agent occupancy simulation results

In this paper we apply the principles of Exploratory Sequential Data Analysis (ESDA) to simulation results analysis. We replicate a resource consumption simulation of occupants in a building and analyze the results using an open-source ESDA tool called UberTagger previously only used in the human-computer interaction (HCI) domain. We demonstrate the usefulness of ESDA by applying it to a hotel occupant simulation involving water and energy consumption. We have found that using a system which implements ESDA principles helps practitioners better understand their simulation models, form hypotheses about simulated behavior, more effectively debug simulation code, and more easily communicate their findings to others.
A Novel Trust Model for Peer-To-Peer Systems Using Sort Technique

Accessible and hidden nature of peer to peer system makes it an ideal forum for traducer to spread malignant content. Managing trust is a problem in peer to peer environment, so a novel trust model is built based on trust metrics. The trust metrics such as reputation, service trust, recommendation trust are defined to precisely measure trustworthiness of peers. A peer's trustworthiness is evaluated by considering provided services and given recommendations with service and recommendation contexts. An interaction is evaluated based on importance, recentness and three parameters: satisfaction, weight, fading effect, when evaluating recommendation, recommender's trustworthiness and confidence level about the information provided are also considered. Experiments on file sharing application demonstrate that peers with the highest trust value are considered and build the trust model in their contiguity and insulate malignant peers.
Heliod at TREC Legal 2011: Learning to Rank from Relevance Feedback for e-Discovery

We present the results of applying a learning to rank al-gorithm to the 2011 TREC Legal dataset. The learning to rank algo-rithm we use was designed to maximize NDCG, MAP, and AUC scores. We therefore examine our results using the AUC and hypothetical F1 scores. We ﬁnd query expansion and learning to rank improve scores beyond standard language model retrieval, however learning to rank does not outperform query expansion.
The role of combination therapy in managing pulmonary arterial hypertension

Pulmonary arterial hypertension (PAH) is a complex, progressive disease with several pathobiological mechanisms, including the endothelin, nitric oxide and prostacyclin pathways. Current treatments for PAH target one of these pathways and, in more severe cases or instances of disease worsening, may be combined with a view to target multiple pathways in parallel. Treatment combination is performed sequentially (as an intensification from initial monotherapy) or upfront (use of two or more therapies in treatment-naïve patients). Whilst combination therapy has been historically considered to be an option for the treatment of PAH, supporting evidence was typically limited to expert opinion, clinical experience and registry data. Data from randomised controlled trials on sequential combination therapy in particular has grown in recent years, resulting in a change in the level of recommendations in the latest update to the PAH treatment algorithm. However, short-term trials have shown inconsistent results, and have not been powered to assess morbidity/mortality outcomes. More recent data from long-term trials suggest a potential clinical benefit associated with sequential combination therapy. In this review we will introduce the concept of combination therapy, consider the latest evidence for both sequential and upfront combination therapy, and discuss additional considerations when initiating combination therapy in clinical practice.
Effects of Preterm Birth on Cortical Thickness Measured in Adolescence

Despite the extensive research into brain development after preterm birth, few studies have investigated its long-term effects on cortical thickness. The Stockholm Neonatal Project included infants between 1988 and 1993 with birth weight (BW) ≤1500 g. Using a previously published method, cortical thickness was estimated on T1-weighted 3D anatomical images acquired from 74 ex-preterm and 69 term-born adolescents (mean age 14.92 years). The cortex was significantly thinner in ex-preterm individuals in focal regions of the temporal and parietal cortices as indicated by voxel-wise t-tests. In addition, large regions around the central sulcus and temporal lobe as well as parts of the frontal and occipital lobes tended also to be thinner in the ex-preterm group. Although these results were not significant on voxel-wise tests, the spatially coherent arrangement of the thinning in ex-preterm individuals made it notable. When the group of ex-preterm individuals was divided by gestational age or BW, the thinning tended to be more pronounced in the anterior and posterior poles in those born nearer term or with a BW closer to 1500 g. These results support the notion that preterm birth is a risk factor for long-term development of cortical thickness.
AESOP : The Autoparallelizing Compiler for Shared Memory Computers

An automatic parallelizer is a tool that converts serial code in C, C++ and Fortran to parallel code. This is an important problem because most hardware today is parallel and manually rewriting the vast repository of serial code is tedious and error prone. We have developed an automatic parallelizing compiler for source code, AESOP targeting shared memory machines. AESOP leverages the LLVM infrastructure and presently works with LLVM-3.0. It targets parallelism for dense arraybased codes with affine-based analysis using traditional methods. The focus of AESOP is not to break new ground in parallelization theory, but to deliver a robust and fast compiler that can handle large programs while getting good speedups for large, real affine-function codes. It is unique among research compilers in the scope of programs parallelized, with programs totalling over 2 million lines of source code (LOC) being correctly handled including primarily the entire SPEC CPU 2006 suite. Smaller programs totalling a few thousand LOC from OMP 2001, NAS and Polybench benchmark suites are also parallelized. Of the tested programs, AESOP identified a subset of SPEC CPU 2006 benchmarks and most of the other programs with over 100,000 LOC in total that it was able to automatically get good speedups on. The fraction of benchmarks parallelized is small for SPEC CPU 2006 because SPEC benchmarks are predominantly serial programs with no exploitable affine parallelism. We have not seen speedup numbers on parallelizing the entire SPEC CPU 2006 benchmark suite (or any significant portion thereof) using affine methods in any other published work. In comparing with the leading open-source polyhedral-based compiler (Pluto), AESOP delivered significantly better speedups on Polybench benchmarks owing to its greater tolerance of different types of affine access patterns, and better affine-based cache optimizations. Pluto was not able to compile any of the larger benchmark suites we list above.
Research on midcourse maneuvering penetration guidance law of ballistic missile based on Genetic Algorithm

The maneuvering penetration guidance law in the middle-course flight of the strategic missile is developed by simulation method in this paper. A maneuvering penetration scheme based on detect system is presented and researched. Based on calculation to maneuvering penetration time with Genetic Algorithm, a new type of optimal penetration guidance law is presented. The optimal, earliest and latest maneuvering penetration time calculating optimization models are designed. Finally, the penetration- interception simulated system based on those models is built, the simulation experiments show the guidance law feasible and effective, and its results are analyzed.
ARGUMENTS FOR SEQUENCING THE GENOME OF THE SEA URCHIN STRONGYLOCENTROTUS PURPURATUS

Robert C. Angerer (University of Rochester) Lynne Angerer (University of Rochester) Roy J. Britten (California Institute of Technology) James A. Coffman (Stowers Institute for Medical Research) William H. Klein (M. D. Anderson Cancer Center) Donal Manahan (University of Southern California) David R. McClay (Duke University) Jonathan P. Rast (California Institute of Technology) Victor D. Vacquier (Scripps Institute of Oceanography)
Reinforcement learning method for energy efficient cooperative multiband spectrum sensing

Cognitive radios (CR) and dynamic spectrum access (DSA) attempt to exploit the underutilized radio spectrum by allowing secondary users to access the licensed frequencies in an opportunistic manner. In order to avoid collisions with the primary user the secondary users need to sense the spectrum, and to mitigate the effects of channel fading on sensing cooperative schemes have been proposed in the literature. In this paper a multiband spectrum sensing policy for coordinating cooperative sensing is proposed. The proposed policy employs the ∈-greedy reinforcement learning method to prioritize the sensing of different subbands and to assign those secondary users to sense them that are able to provide a desired level of miss detection probability. In order to improve the energy efficiency, the number of assigned sensors per subband is minimized.