Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring Evidence Aggregation Methods and External Expansion Sources for Medical Record Search

Abstract : This paper describes and analyzes experiments we performed for the Medical Records track in the 2012 Text REtrieval Conference (TREC). We mainly investigated three research problems: 1. Evidence Aggregation: In last year's track there were two different methods in general for obtaining a visit ranking out of reports (smaller document units), i.e., (A) using reports as indexing and retrieval units and then converting a report ranking into a visit ranking, and (B) using visits as indexing and retrieval units by concatenating reports at the very first stage and then obtain a visit ranking directly. Method A avoids the potential problem of varying visit document length, while Method B naturally aggregates evidence scatter over multiple reports and easily obtains a visit ranking. It is unclear which method is better based on all reported results. Thus, we compared the two approaches, tried various score aggregation methods for (A), and combined both approaches in a way that further improved the system performance. 2. Expansion Sources: We tested a variety of external collections (ranging from general web datasets to domain-specific thesauri, and from Megabyte datasets to Terabyte datasets) for query expansion, compared their effectiveness, and obtained useful insights into the data. 3. Retrieval Models: We tested several statistical IR models (proven to be effective on news and web collections) on this medical collection, and explored ways to combine these models to address different aspects of task. For instance, we used MRF model to model term proximity since most medical concepts are phrases. We also used a mixture of relevance models to obtain various relevant expansion terms covered by different expansion collections respectively, which is expect to significantly alleviate the vocabulary mismatch between medical terminologies.
Joint Depth and Color Camera Calibration with Distortion Correction

We present an algorithm that simultaneously calibrates two color cameras, a depth camera, and the relative pose between them. The method is designed to have three key features: accurate, practical, and applicable to a wide range of sensors. The method requires only a planar surface to be imaged from various poses. The calibration does not use depth discontinuities in the depth image, which makes it flexible and robust to noise. We apply this calibration to a Kinect device and present a new depth distortion model for the depth sensor. We perform experiments that show an improved accuracy with respect to the manufacturer's calibration.
ADN-Classifier:Automatically Assigning Denotation Types to Nominalizations

This paper presents the ADN-Classifier, an Automatic classification system of Spanish Deverbal Nominalizations aimed at identifying its semantic denotation (i.e. event, result, underspecified, or lexicalized). The classifier can be used for NLP tasks such as coreference resolution or paraphrase detection. To our knowledge, the ADN-Classifier is the first effort in acquisition of denotations for nominalizations using Machine Learning.We compare the results of the classifier when using a decreasing number of Knowledge Sources, namely (1) the complete nominal lexicon (AnCora-Nom) that includes sense distictions, (2) the nominal lexicon (AnCora-Nom) removing the sense-specific information, (3) nominalizations context information obtained from a treebank corpus (AnCora-Es) and (4) the combination of the previous linguistic resources. In a realistic scenario, that is, without sense distinction, the best results achieved are those taking into account the information declared in the lexicon (89.40% accuracy). This shows that the lexicon contains crucial information (such as argument structure) that corpus-derived features cannot substitute for.
Introducing buggy 2 − 5 and buggy s 2 − 5

This paper presents a brief introduction to two solvers, buggy2−5 and buggys2−5, which I have submitted to the binary extensional and binary intensional categories of the Second International CSP Solver Competition. Both solvers are a combination of preprocessing followed by mac search. The preprocessing consists of domain squashing and enforcing weak k-singleton arc consistency.
Ciphertext-Policy Hierarchical Attribute-based Encryption for Fine-Grained Access Control of Encryption Data

In the ciphertext-policy attribute based encryption (CP-ABE) scheme, a private key holder is related with a set of attributes while the data is encrypted under an access structure deﬁned by the data provider. In most proposed schemes, the characteristics of the attributes are treated as same level. While in the real world circum-stance, the attributes are always in the diﬀerent levels. In this paper, In this paper, a scheme is proposed under a diﬀerent hierarchy of attributes with the name of ciphertext-policy hierarchical attribute based encryption. The CP-HABE scheme is proved to be secure under the decisional q -parallel bilinear Diﬃe-Hellman exponent assumption, which can be considered as the generalization of the traditional CP-ABE.
Globally Optimal Short-Time Dynamic Time Warping, Application to Score to Audio Alignment

Dynamic time warping (DTW) finds the best global match or alignment between two sequences by 'time' warping them optimally. Since the algorithm uses the whole sequences, it can be very demanding in calculation cost and memory. In particular, this limits the size of the sequences which can be aligned. In this paper a novel algorithm is presented, short-time dynamic time warping (STDTW), which requires much less memory because optimization is done iteratively on portions of the sequences. The very remarkable property of the algorithm is that under some weak hypothesis, it produces the same globally optimal solution as the classical DTW. As an example, STDTW is applied to score to audio alignment which links events in a musical score and points on the audio performance time axis
The project of license plate recognition system in graduate course research-oriented final project

License plate automatic recognition is realized by Matlab in the paper, which is applied in toll payment, guard monitor, et al, and has promising future in the control and management of the traffic. The system can be divided into three modules that are license plate orientation, license plate character segmentation and recognition. In the process, it involves image processing, color dimensional conversion, gray transform, morphologic and so on. Each part is analyzed and discussed directly with corresponding results. The recognition is accurate and clear. At last, the shortage and future direction is given for following research. This project is the course final project of the graduate course of “Image Analysis and Recognition”. Through the training of this project, graduate students can improve their knowledge of image processing, at the same time, they have a better gain in the solving real problem and innovative abilities.
Central Proliferation and Neurogenesis Is Impaired in Type 2 Diabetes and Prediabetes Animal Models

Type 2 diabetes (T2D) is an important risk factor to suffer dementia, including Alzheimer’s disease (AD), and some neuropathological features observed in dementia could be mediated by T2D metabolic alterations. Since brain atrophy and impaired neurogenesis have been observed both T2D and AD we analyzed central nervous system (CNS) morphological alterations in the db/db mice (leptin receptor KO mice), as a model of long-term insulin resistance and T2D, and in C57Bl6 mice fed with high fat diet (HFD), as a model of diet induced insulin resistance and prediabetes. Db/db mice showed an age-dependent cortical and hippocampal atrophy, whereas in HFD mice cortex and hippocampus were preserved. We also detected increased neurogenesis and cell proliferation rates in young db/db mice when compared with control littermates. Our study shows that metabolic parameters serve as predictors of both atrophy and altered proliferation and neurogenesis in the CNS. Moreover in the cortex, atrophy, cell proliferation and neurogenesis were significantly correlated. Our data suggest that T2D may underline some of the pathological features observed in the dementia process. They also support that blood glucose control in elderly patients could help to slow down dementia evolution and maybe, improve its prognosis.
User Interface for Automatic Service Composition

In this paper, a user interface for Automatic Service Composition (ASC) is described. ASC solves general real-life problems more intelligently. Recently, research on the structure of ASC is evolving rapidly. Utilization of ASC is approaching by the favor day by day. However, when utilization is considered, in order even for the best system to be widely used by the general user, UI which is easy to use is required.
The Transformation of the Workers' Party in Brazil, 1989-2009

1. Introduction: understanding the normalization of the Workers' Party 2. Strategic change or institutional persistence? : Evolution of the Workers' Party 3. Opposition politics: the PT in the Chamber of Deputies 4. The PT in municipal government: the pragmatic face of the party 5. Striving for the presidency: from opposition to government 6. New challenges and opportunities: the PT in government, 2003-9 7. Final reflections: analytical implications and comparative perspectives.
Misspecification and Heterogeneity in Binary Choice Models

We propose a nonparametric approach for estimating single-index, binarychoice models when parametric models such as Probit and Logit are potentially misspecified. The new approach involves two steps: first, we estimate index coefficients using sliced inverse regression without specifying a parametric probability function a priori; second, we estimate the unknown probability function using kernel regression of the binary choice variable on the single index estimated in the first step. The estimated probability functions for different demographic groups indicate that the conventional dummy variable approach cannot fully capture heterogeneous effects across groups. Using both simulated and labor market data, we demonstrate the merits of this new approach in solving model misspecification and heterogeneity problems.
Fault Tolerant Design for Magnetic Memories

This study presents a Fault Tolerant memory cores based on the property of Component Reusability, a method for Fault Tolerance for content addressable memories. The memories used in the design are 256, 512, 1024 and 2048 bytes. The fault is injected into the circuitry operation by using Automatic Test Pattern Generators (ATPGs). The design has been implemented in Cadence 90 nm technology and tested with Fault Injection Circuits and ATPG effectiveness was found out to be 100% at a frequency of 500 MHZ.
Evolutionary Trends of the Transposase-Encoding Open Reading Frames A and B (orfA and orfB) of the Mycobacterial IS6110 Insertion Sequence

Background The IS6110 insertion sequence, a member of the IS3 family of insertion sequences, was found to be specific to the Mycobacterium tuberculosis complex (MTBC). Although IS6110 has been extensively characterized as a transposable genetic marker, the evolutionary history of its own transposase-encoding sequence has not, to the best of our knowledge, been investigated. Methodology/Principal Findings Here we explored the evolution of the IS6110 sequence by analysing the genetic variability and the selective forces acting on its transposase-encoding open reading frames (ORFs) A and B (orfA and orfB). For this purpose, we used a strain collection consisting of smooth tubercle bacilli (STB), an early branching lineage of the MTBC, and present-day M. tuberculosis strains representing the full breadth of genetic diversity in Tunisia. In each ORF, we found a major haplotype that dominated over a flat distribution of rare descendent haplotypes, consisting mainly of single- and double-nucleotide variant singletons. The predominant haplotypes consisted of both ancestral and present-day strains, suggesting that IS6110 acquisition predated the emergence of the MTBC. There was no evidence of recombination and both ORFs were subjected to strict purifying selection, as demonstrated by their dN/dS ratios (0.29 and 0.51, respectively), as well as their significantly negative Tajima’s D statistics. Strikingly, the purifying selection acting on orfA proved much more stringent, suggesting its critical role in regulating the transpositional process. Maximum likelihood analyses further excluded any possibility of positive selection acting on single amino acid residues. Conclusions/Significance Taken together our data fit with an evolutionary scenario according to which the observed variability pattern of the IS6110 transposase-encoding ORFs is generated mainly through random point mutations that accrued on a functionally optimal IS6110 copy, whose acquisition predated the emergence of the MTBC complex. Background selection acting against deleterious mutations led to an excess of low-frequency variants.
Replication of KCNJ11 (p.E23K) and ABCC8 (p.S1369A) Association in Russian Diabetes Mellitus 2 Type Cohort and Meta-Analysis

The genes ABCC8 and KCNJ11 have received intense focus in type 2 diabetes mellitus (T2DM) research over the past two decades. It has been hypothesized that the p.E23K (KCNJ11) mutation in the 11p15.1 region may play an important role in the development of T2DM. In 2009, Hamming et al. found that the p.1369A (ABCC8) variant may be a causal factor in the disease; therefore, in this study we performed a meta-analysis to evaluate the association between these single nucleotide polymorphisms (SNPs), including our original data on the Siberian population (1384 T2DM and 414 controls). We found rs5219 and rs757110 were not associated with T2DM in this population, and that there was linkage disequilibrium in Siberians (D’=0.766, r2= 0.5633). In addition, the haplotype rs757110[T]-rs5219[C] (p.23K/p.S1369) was associated with T2DM (OR = 1.52, 95% CI: 1.04-2.24). We included 44 original studies published by June 2014 in a meta-analysis of the p.E23K association with T2DM. The total OR was 1.14 (95% CI: 1.11-1.17) for p.E23K for a total sample size of 137,298. For p.S1369A, a meta-analysis was conducted on a total of 10 studies with a total sample size of 14,136 and pooled OR of 1.14 [95% CI (1.08-1.19); p = 2 x 10-6]. Our calculations identified causal genetic variation within the ABCC8/KCNJ11 region for T2DM with an OR of approximately 1.15 in Caucasians and Asians. Moreover, the OR value was not dependent on the frequency of p.E23K or p.S1369A in the populations.
Research Proposal A. Proposed Study a Framework for Wireless Sensor Networks in Manufacturing Environments 2. Background

Wireless sensor networks (WSNs) are a collection of many tiny sensor devices termed sensor nodes or motes that form connected networks once deployed. Because sensor nodes are relatively cheap, a typical sensor network normally consists of hundreds, if not thousands, of sensor nodes, with each capable of sensing data from its environment and relaying the sensed data through other sensor nodes, in an ad-hoc fashion to a centralized location or sink [19]. Of late, there have been much research interests in WSNs as they pose many interesting challenges in designing optimal WSN frameworks for many different applications. WSNs can be used as a tool in an array of different industries such as agriculture, marine, military, medical, and the focus of our research, manufacturing. In manufacturing, the use of WSNs can reduce costs associated with machine faults and network maintenance, prevent safety hazards, and improve production quality, all at a low deployment cost [23, 8, 33, 13]. In most contexts of WSN, the design framework must optimize all performance metrics by sustaining energy-efficiency, memory-efficiency, self-organization, and network performance; this is no exception in manufacturing. Sensor nodes are battery powered devices and replacement or re-charge of a sensor node’s battery is often not feasible due to its low cost, hence
Glycemic Index and Glycemic Load of Selected Staples Based on Rice, Yam and Cassava Commonly Consumed in Côte d'Ivoire

Integrating information on the glycemic index (GI) and the glycemic load (GL) of diet is limited in Cote d’Ivoire because of the lack of data. Thus, this study was undertaking for the local management and prevention of diabetes mellitus and its complications based on nutritional data (GI and GL values). The study included ten healthy subjects with 7 males, 3 females (28 ± 2 years on average age and 20.5 ± 1.7 on average BMI). Participants tested three different meals with equal carbohydrate load (50 g). Blood samples were obtained at 0, 15, 30, 45, 60, 90 and 120 min before and after consumption for glucose levels determination. GIs were determined using a standard method with glucose as reference food and data were used for GLs calculating. Data showed that GIs value of pounded yam with eggplant sauce and cassava paste with granulates palm nut sauce were high ranging to 94 to 86 respectively while rice with groundnut sauce, have a low GI (GI = 45). Nevertheless, the GLs of the all the test foods are high with the values of 47, 43 and 23 (g) for pounded yam with eggplant sauce, cassava paste with granulates palm nut sauce and rice with groundnut sauce respectively. According to GIs and GLs data, the three test foods must be consumed moderately in a diet. So, it is important to associate GL data to GI data of Ivorian traditional foods for the management and the prevention of diabetes mellitus in Cote d’Ivoire and in others countries sharing the same food tradition.
the L-Selectin and ICAM-1 Pathways Requires Overlapping Interactions Between Leukocyte Entry into Sites of Inflammation

Leukocyte interactions with vascular endothelium during inﬂammation depend on cascades of adhesion molecule engagement, particularly during selectin-mediated leukocyte rolling. Leukocyte rolling is also facilitated by members of the integrin and Ig families. Speciﬁcally, leukocyte rolling velocities during inﬂammation are signiﬁcantly increased in ICAM-1-deﬁcient mice, with ICAM-1 expression required for optimal P- and L-selectin-mediated rolling. Elimination of ICAM-1 expression in L-selectin-deﬁcient mice signiﬁcantly reduces leukocyte rolling. Whether disrupted leukocyte rolling in L-selectin and ICAM-1 double-deﬁcient (L-selectin/ICAM-1 2 / 2 ) mice affects leukocyte entry into sites of inﬂammation in vivo was assessed in the current study by using experimental models of inﬂammation; thioglycollate-induced peritonitis, chemokine-induced neutrophil migration to the skin, delayed-type hypersensitivity responses, rejection of allogeneic skin grafts, and septic shock. In many cases, the loss of both L-selectin and ICAM-1 expression dramatically reduced leukocyte migration into sites of inﬂammation beyond what was observed with loss of either receptor alone. In fact, the effects from loss of both L-selectin and ICAM-1 effectively eliminated multiple chronic inﬂammatory responses in L-selectin/ICAM-1 2 / 2 mice. By contrast, the combined loss of L-selectin and ICAM-1 expression had minimal effects on the generation of Ag-speciﬁc T cell responses or humoral immunity. Thus, members of the selectin and Ig families function synergistically to mediate optimal leukocyte rolling and entry into tissues, which during thioglycollate-induced peritonitis, IL-8-induced neutrophil migration to the skin, contact hypersensitivity reactions, skin graft rejection, and LPS-induced septic shock. The results further conﬁrm that the selectins and ICAM-1 have overlapping functions essential for optimal leukocyte rolling and entry into in vivo sites of inﬂammation.
Can a machine think ? In Newman JR The World of Mathematics

The study of DHCP has improved DHCP, and current trends suggest that the analysis of sensor networks will soon emerg e. In fact, few systems engineers would disagree with the explo ration of systems. We concentrate our efforts on demonstrat ing that public-private key pairs can be made encrypted, reliab l , and stochastic.
Evaluation of Underwater IEEE 802.11 Networks at VHF and UHF Frequency Bands using Software Defined Radios

Radio Frequency (RF) communications suffer high attenuation underwater, limiting the range of standard IEEE 802.11 networks to a few centimeters underwater. The usage of custom RF solutions at lower frequencies to increase range entails high development costs, and proprietary hardware. This paper evaluates the performance of cost-effective, mass-market IEEE 802.11 networks underwater at different frequencies in the sub-GHz bands using Software Defined Radio platforms. Optimizations to the gr-ieee802.11 implementation, together with custom designed antennas, allowed the testing of frequencies in the 70-700 MHz range, in a large-scale freshwater tank, and in real-world, seawater conditions in Tagus river estuary. Results show a frequency-dependent communications range up to 5 m in freshwater and 1.8 m in seawater, with bitrates up to 550 kbit/s and delay under 45 ms. This proves the feasibility of IEEE 802.11 networks in the sub-GHz bands for applications such as video streaming from an autonomous underwater vehicle and underwater sensors.
Title : Selection on heterozygosity drives adaptation in intra-and interspecific hybrids Running title : Adaptation in hybrids

1Department of Genome Sciences, University of Washington, Seattle, Washington, United States of America 2Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America 3Howard Hughes Medical Institute and Department of Embryology, Carnegie Institution, Baltimore, Maryland, United States of America 4Department of Biology, Johns Hopkins University, Baltimore, Maryland, United States of America #aCurrent address: Exelixis, Dallas, Texas, United States of America #bCurrent address: BioNano Genomics, San Diego, California, United States of America #cCurrent address: Wall High School, Wall Township, New Jersey, United States of America #dCurrent address: Nanostring, Seattle, Washington, United States of America
Combining Equity Premium Forecasts

In this paper, we provide techniques for combining different experts' opinions of the forward looking equity premium to resolve questions about the future value of an equity index tracker fund. By exploiting the fact that the survey data is approximately gamma distributed, we either use numerical methods or derive closed form solutions depending on the exact question posed. The practical significance of our results is shown to be highly sensitive to assumptions about the independence of each individual forecast.