Miracle-dz/UniFAR-FTUs huggingface dataset:
Legume Consumption and Colorectal Adenoma Risk: A Meta-Analysis of Observational Studies

Background The anticancer effects of legumes have been explored extensively, but evidence from epidemiologic studies on colorectal adenoma is controversial. We performed a meta-analysis to assess these issues. Methods A systemic search of several databases was conducted for relevant studies evaluating the relationship between legume intake and adenoma risk, with no language restriction, from January 1, 1966, to April 1, 2013. Results Three cohort and eleven case control studies with 8,380 cases and a total of 101,856 participants were included in the analysis; the pooled odds ratio (95% confidence interval) for the highest vs. lowest consumption categories was 0.83 (0.75–0.93), with moderate level of heterogeneity (I 2 = 25.9% and P = 0.146) based on a random effects model. A decreased risk of adenoma was also observed in most of our subgroup meta-analyses. Conclusions Higher intake of legumes significantly reduced the risk of colorectal adenoma in our meta-analysis. Nevertheless, due to possible confounders and bias, further investigations are warranted to confirm this relationship.
Overstretching B-DNA: The Elastic Response of Individual Double-Stranded and Single-Stranded DNA Molecules

Single molecules of double-stranded DNA (dsDNA) were stretched with force-measuring laser tweezers. Under a longitudinal stress of ∼65 piconewtons (pN), dsDNA molecules in aqueous buffer undergo a highly cooperative transition into a stable form with 5.8 angstroms rise per base pair, that is, 70% longer than B-form dsDNA. When the stress was relaxed below 65 pN, the molecules rapidly and reversibly contracted to their normal contour lengths. This transition was affected by changes in the ionic strength of the medium and the water activity or by cross-linking of the two strands of dsDNA. Individual molecules of single-stranded DNA were also stretched giving a persistence length of 7.5 angstroms and a stretch modulus of 800 pN. The overstretched form may play a significant role in the energetics of DNA recombination.
A new equivalence class based approach for discretizing quantitative data using Point Shift Mechanism

Different data mining techniques are utilized for knowledge discovery in modern real-world databases. Such techniques quite often require discretization of values. The task of discretization of items in a database is basically, a kind of transformation of continuous values to a simpler form of comprehension. Discretization has far reaching effects on the entire knowledge discovery process and interestingly, at certain times these effects may be adverse. Association Rule Mining (ARM) in quantitative databases exploit discretization of quantitative attributes to generate reasonable intervals for mining meaningful association rules. But, there are several issues related to interval generation that originate due to inefficient discretization which ultimately degrade the quality of discovered association rules. In this paper, we discuss such issues inherent in some of the existing discretization techniques and highlight how they may affect the task of ARM in quantitative databases. We also propose a new discretization technique that tries to nullify the adverse effects of inefficient discretization. Experimental results reveal that the proposed technique outperforms several existing ones in terms of reasonable interval generation.
Alternative splicing and molecular characterization of splice site variants: BRCA1 c.591C>T as a case study.

BACKGROUND Deleterious mutations in BRCA1 (breast cancer 1, early onset; MIM 113705) increase breast and ovarian cancer [B(O)C] risk; however, many variants cannot be readily classified as deleterious or neutral. Unclassified variants (UVs) pose serious problems in genetic counseling. RNA-splicing analysis is essential for the assessment of many UVs. METHODS Denaturing gradient gel electrophoresis was used to genotype the BRCA1 c.591C>T variant in 685 index cases of B(O)C families, 326 sporadic breast cancer cases, and 450 healthy controls from Spain. In silico tools were used to predict the effect of the c.591C>T variant on splicing. In vitro splicing analysis was performed in 7 c.591C>T carriers and 10 noncarriers. cDNAs were PCR-amplified with primers designed to detect BRCA1 alternative splicing isoforms. The products were analyzed by capillary electrophoresis. Peak areas were used to quantify the relative abundance of each isoform. Sequencing through exonic single-nucleotide polymorphisms (SNPs) enabled us to discriminate wild-type and variant transcripts. RESULTS c.591C>T was detected in B(O)C families (1.5%), breast cancer cases (0.3%), and controls (0.9%). c.591C>T induced BRCA1 exon 9 skipping and modified the relative expression of Delta(9,10), Delta(9,10,11B), Delta11B, and full-length isoforms. The mean ratio of Delta(9,10) to the full-length isoform increased from 0.25 in noncarriers to 1.5 in carriers. The mean Delta(9,10,11B)/Delta11B ratio increased from 0.2 to 4. Overall expression levels of c.591C>T and wild-type alleles were similar. CONCLUSIONS Our data support a nonpathogenic role for the BRCA1 c.591C>T variant. Naturally occurring alternative splicing isoforms need to be considered when assessing the role of BRCA1 UVs on splicing.
Performance Evaluation of Uplink Multiple Access Techniques in LTE Mobile Communication System

The User Equipments (UE) nowadays are able to provide various internet applications and services that raise the demand for high speed data transfer and Quality of Service (QoS). Accordingly, next generation mobile communication systems driven by these demands are expected to provide higher data rates and better link quality compared to the existing systems. Orthogonal Frequency Division Multiple Access (OFDMA) and Single Carrier Frequency Division Multiple Access (SC-FDMA) are strong multiple access candidates for the uplink of the International Mobile Telecommunications-Advanced (IMT-Advanced). These multiple access techniques in combination with other promising technologies such as multi-hops transmission and Multiple-Input-Multiple-Output (MIMO) will be utilized to reach the targeted IMT-Advanced system performance. In this thesis, OFDMA and SC-FDMA are adopted and studied in the uplink of Long Term Evolution (LTE). Two transmission scenarios are considered, namely the single hop transmission and the relay assisted transmission (two hops). In addition, a hybrid multiple access technique that combines the advantages of OFDMA and SC-FDMA in term of low Peak-to-Average Power Ratio (PAPR) and better link performance (in terms of Symbol Error Rate (SER)) has been proposed in relay assisted transmission scenario. Simulation results show that the proposed hybrid technique achieves better end-to-end link performance in comparison to the pure SC-FDMA technique and maintains the same PAPR value in access link. In addition, a lower PAPR is achieved compared to OFDMA case, which is an important merit in the uplink transmission due to the UE’s power resources constraint (limited battery power).
Inter-Subject Synchronization of Prefrontal Cortex Hemodynamic Activity During Natural Viewing

Hemodynamic activity in occipital, temporal, and parietal cortical areas were recently shown to correlate across subjects during viewing of a 30-minute movie clip. However, most of the frontal cortex lacked between-subject correlations. Here we presented 12 healthy naïve volunteers with the first 72 minutes of a movie (“Crash”, 2005, Lions Gate Films) outside of the fMRI scanner to involve the subjects in the plot of the movie, followed by presentation of the last 36 minutes during fMRI scanning. We observed significant between-subjects correlation of fMRI activity in especially right hemisphere frontal cortical areas, in addition to the correlation of activity in temporal, occipital, and parietal areas. It is possible that this resulted from the subjects following the plot of the movie and being emotionally engaged in the movie during fMRI scanning. We further show that probabilistic independent component analysis (ICA) reveals meaningful activations in individual subjects during natural viewing.
External Knowledge Sources for Question Answering

MIT CSAIL’s entries for the TREC Question Answering track (Voorhees, 2005) focused on incorporating external general-knowledge sources into the question answering process. We also explored the effect of document retrieval on factoid question answering, in cooperation with a community focus on document retrieval. For the new relationship task, we present a new passage-retrieval based algorithm emphasizing synonymy, which performed best among automatic systems this year. Our most prominent new external knowledge source is the Wikipedia1, and its most useful component is the synonymy implicit in its subtitles and redirect link structure. Wikipedia is also a large new source of hypernym information. The main task included factoid questions, for which we modified the freely available Web-based Aranea question answering engine; list questions, for which we used hypernym hierarchies to constrain candidate answers; and definitional ‘other’ questions, for which we combined candidate snippets generated by several previous definition systems using a new novelty-based reranking method inspired by (Allan et al., 2003). Our factoid engine, Aranea2 (Lin and Katz, 2003), uses the World Wide Web to find candidate answers to the given question, and then projects its best candidates onto the newspaper corpus, choosing the one best sup-
Nonparametric Tests for the Gap Time Distributions of Serial Events Based on Censored Data

Summary. This article deals with the problem of comparing two populations with respect to the distribution of the gap time between two successive events when each subject can experience a series of events and when the event times are potentially right censored. Several families of nonparametric tests are developed, all of which allow arbitrary distributions and dependence structures for the serial events. The asymptotic and small‐sample properties of the proposed tests are investigated. An illustration with data taken from a colon cancer study is provided. The related problem of testing the independence of two successive gap times is also studied.
The role of human tissue kallikreins 7 and 8 in intracranial malignancies

Abstract Recent evidence suggests that many tissue kallikreins are implicated in carcinogenesis. Kallikrein 8 (KLK8) plays a role in the physiology of the central nervous system. Kallikrein 7 (KLK7) takes part in skin desquamation. Both show altered expression in ovarian and breast cancer. In this study, we examined the level of mRNA expression of the KLK7 and KLK8 genes in 73 intracranial tumors using qualitative RT-PCR. The results were correlated with clinical and histomorphological variables and patient outcome. The expression of both genes was also examined in the brain cancer cell lines U-251 MG, D54 and SH-SY5Y and the invasive capacity of glioblastoma cells U-251 MG overexpressing hK7 or hK8 was also investigated in an in vitro Matrigel assay. Follow-up analysis revealed that expression of KLK7 mRNA was associated with shorter overall survival (OS) compared to patients with no KLK7 expression, as determined by Cox proportional hazard regression analysis. Overexpression of hK7 protein by cultivated brain tumor cells significantly enhanced the invasive potential in the Matrigel invasion assay, in contrast to cells overexpressing hK8 protein. Our data suggest that hK7 protein overexpression is associated with a more aggressive phenotype in brain cancer cells.
Visual Analysis of Station Usage Patterns in Public Bicycle System

Public Bicycle System(PBS) is a new kind of urban transportation infrastructure. Understanding the usage patterns of stations in PBS is crucial for bicycle dispatch and traffic resource optimization. In this paper, we propose a visual analytic system to explore the station usage patterns. A filter model is proposed firstly, which is used to filter out desired records under different conditions. Map view and station analysis view are presented to assist exploration in the context of geography and rental information. In the station analysis view, a table-like component is designed to sort and demonstrate data intuitively based on the filter model, which helps the users to inspect single/multiple stations hire patterns under different time granularity uniformly. We exemplify our approach with a real PBS dataset through case studies.
On the Newtonian limit and cut-off scales of isothermal dark matter haloes with cosmological constant

We examine isothermal dark matter haloes in hydrostatic equilibrium with a 'A-field', or cosmological constant A = Ω Λ ρ critc 2 , where Ω Λ ≃ 0.7 and ρ c r i t is the present value of the critical density with h ≃ 0.65. Modelling cold dark matter (CDM) as a self-gravitating Maxwell-Boltzmann gas, the Newtonian limit of general relativity yields equilibrium equations that are different from those arising by merely coupling an 'isothermal sphere' to the A-field within a Newtonian framework. Using the conditions for the existence and stability of circular geodesic orbits, the numerical solutions of the equilibrium equations (Newtonian and Newtonian limit) show the existence of: (i) an 'isothermal region' (0 ≤ r r 1 ) dominated by the A-field, where the Newtonian potential oscillates and circular orbits only exist in disconnected patches of the domain of r; (iii) a 'transition region' (r 2 ≤ r 0.008 M O . pc - 3 , in interesting agreement with rotation curve studies of dwarf galaxies. Because r 2 marks the largest radius of a stable circular orbit, it provides a characteristic boundary or 'cut-off' maximal radius for isothermal spheres in equilibrium with a A-field. For current estimates of ρ c and velocity dispersion of virialized galactic structures, this cut-off scale ranges from 90 kpc for dwarf galaxies, up to 3 Mpc for large galaxies and 22 Mpc for clusters. In a purely Newtonian framework, these length-scales are about 10 per cent smaller, although in either case r 2 is between five and seven times larger than the physical cut-off scales of isothermal haloes, such as the virialization radius or the critical radius for the onset of Antonov instability. These results indicate that the effects of the A-field can be safely ignored in studies of virialized structures, but could be significant in the study of structure formation models and the dynamics of superclusters still in the linear regime or of gravitational clustering at large scales (r 30 Mpc).
PAPR Reduction in DFT-Spread OFDMA using Companding Transform

Orthogonal Frequency Division Multiplexing (OFDM) is an efficient transmission technique for high data rate communication systems. The major problem of OFDM system is Peak to Average Power Ratio (PAPR) which reduces the efficiency of the system and increases the system complexity. In this paper, the two different techniques are combined together, so as to give the effective reduction in PAPR for OFDM, namely, DFT spreading and Two Piece-wise Companding (TPWC). DFT spread OFDM (DFTS-OFDM) has been selected as the uplink transmission scheme for long-term 3G evolution (LTE) and TPWC transform can provide significant PAPR reduction with low computational complexity, which is similar to other existing linear transforms. TPWC is proposed so as to compress large signal amplitudes and expand small ones with two different linear functions.
Texture characterization and compression based on human perception in the JPEG2000 framework

Over the last decade perceptually based image compression has gained significant importance. This is because it relies on Human Visual Perception (HVP) in measuring the reconstruction quality in the compression process, as humans are the end users for images. Visual data that is perceived by humans can be characterized in terms of three parameters. Magnitude, Phase and Orientation of the spatial frequency content. While existing perceptually based image compression techniques exploits the first parameter, the novel contribution of this paper is its focus on the use of phase data for perceptually based texture compression. In this paper a HVS based texture characterization approach is applied to measure the perceived (by humans) phase coherence in the image. Then images are more compressed after removing the unperceived phase redundancy. Finally subjective tests are performed to measure the reconstruction quality of the proposed compression approach. The proposed compression algorithm has been applied in the JPEG2000 framework. Simulation results that demonstrate the efficiency of the proposed approach are presented.
Performance Comparison of Diierent Class-and-drop Treatment of Data and Acknowledgements in Diiserv Ip Networks Performance Comparison of Diierent Class-and-drop Treatment of Data and Acknowledgements in Diiserv Ip Networks

In diierentiated services IP networks the sender of a TCP connection determines the class of data packets he emits. The receiver chooses the class of the acknowledgements sent back, independently of the received class. In this work, we examine the impact of diierent drop precedence in a class and the assignment of diierent classes for data and acknowledgements. The results show that the throughput of a TCP connection depends not only on the data class, but also on the right choice for the acknowledgements. Some combinations of classes for data and ACKs could even lead to an \unfair" use of bandwidth. On the other hand, for a high throughput the selection of the drop precedence is in most cases only important for data packets.
HABITAT SAMPLING AND HABITAT SELECTION BY FEMALE WILD TURKEYS: ECOLOGICAL CORRELATES AND REPRODUCTIVE CONSEQUENCES

ABST,Acr. --Habitat sampling can allow much more effective habitat selection for longterm activities such as nesting and may be directly linked to fitness. We studied the process of habitat sampling and selection in female Wild Turkeys (Meleagris gallopavo) in the Arkansas Ozarks. In particular, we tested the prediction that movements prior to selecting nesting habitat correlate with the quality of selected habitat. Our results supported the prediction that greater habitat sampling (as reflected by greater area covered prior to nesting) allows acquisition of better nesting habitat; greater movements were correlated with choice of better nesting sites with more cover that allow higher nest survival. Attributes of individual birds and habitat dispersion influenced movement patterns and access to quality habitats. In addition, extent of habitat sampling early in the season correlated with reproductive performance by affecting renesting. Distance between subsequent nest locations was inversely related to the movements early in the season and also depended upon length of incubation before nest predation. Females that sampled larger areas after depredation of their first nest and did so outside of their prenesting range were more successful than other females. Received 11 August 1995, accepted 10 November 1995. HABITAT USE can influence reproduction and survival and, thus, affect the evolution of many aspects of a species' biology (Whitham 1980, Cody 1985, Martin 1993). In particular, variation in habitat quality should favor individuals that choose habitats that yield the greatest reproductive success and survival (Fretwell and Lucas 1970, Fretwell 1972, Whitham 1980, Mar
k-k Routing, k-k Sorting, and Cut-Through Routing on the Mesh

Abstract In this paper we present randomized algorithms for k-k routing, k-k sorting, and cut-through routing on an n × n mesh connected computer (referred to simply as the mesh). The stated resource bounds hold with high probability. The algorithm for k-k routing runs in ( k /2) n + o ( kn ) steps. We also show that k-k sorting can be accomplished within ( k /2) n + 2 n + o ( kn ) steps, and cut through routing can be done in kn /2 + (3/2) n + o ( kn ) steps. kn /2 is a known lower bound for all three problems (which is the bisection bound), and hence our algorithms are very nearly optimal. All the above-mentioned algorithms have optimal queue length. These algorithms also extend to higher-dimensional meshes.
Extreme Learning Machine-Based Classification of ADHD Using Brain Structural MRI Data

Background Effective and accurate diagnosis of attention-deficit/hyperactivity disorder (ADHD) is currently of significant interest. ADHD has been associated with multiple cortical features from structural MRI data. However, most existing learning algorithms for ADHD identification contain obvious defects, such as time-consuming training, parameters selection, etc. The aims of this study were as follows: (1) Propose an ADHD classification model using the extreme learning machine (ELM) algorithm for automatic, efficient and objective clinical ADHD diagnosis. (2) Assess the computational efficiency and the effect of sample size on both ELM and support vector machine (SVM) methods and analyze which brain segments are involved in ADHD. Methods High-resolution three-dimensional MR images were acquired from 55 ADHD subjects and 55 healthy controls. Multiple brain measures (cortical thickness, etc.) were calculated using a fully automated procedure in the FreeSurfer software package. In total, 340 cortical features were automatically extracted from 68 brain segments with 5 basic cortical features. F-score and SFS methods were adopted to select the optimal features for ADHD classification. Both ELM and SVM were evaluated for classification accuracy using leave-one-out cross-validation. Results We achieved ADHD prediction accuracies of 90.18% for ELM using eleven combined features, 84.73% for SVM-Linear and 86.55% for SVM-RBF. Our results show that ELM has better computational efficiency and is more robust as sample size changes than is SVM for ADHD classification. The most pronounced differences between ADHD and healthy subjects were observed in the frontal lobe, temporal lobe, occipital lobe and insular. Conclusion Our ELM-based algorithm for ADHD diagnosis performs considerably better than the traditional SVM algorithm. This result suggests that ELM may be used for the clinical diagnosis of ADHD and the investigation of different brain diseases.
Provable Polylog Routing for Darknets

Darknets, anonymous and membership-concealing P2P networks, aim at providing censorship-resistance without relying on a central authority. An efficient routing algorithm is needed to create Darknets that offer an acceptable performance to a large number of users. Designing such an algorithm is hard due to the restricted topology of Darknets, which has not been modelled adequately up to now. We present such a model of Darknets by modifying Kleinberg's small-world model [1] and a new algorithm, NextBestOnce. It is shown analytically that NextBestOnce takes O(log2 n) steps on our model, simulations show that it performs better than existing Darknet routing algorithms such as the one used in the dark Freenet [2], especially with regard to the maximal path length which is bounded by O(log2 n) for NextBestOnce, but scales linearly in case of Freenet.
Multilingual Summary Generation in a Speech-To-Speech Translation System for Multilingual Dialogues

This paper describes a novel functionality of the VERBMOBIL system, a large scale translation system designed for spontaneously spoken multilingual negotiation dialogues. The task is the on-demand generation of dialogue scripts and result summaries of dialogues. We focus on summary generation and show how the relevant data are selected from the dialogue memory and how they are packed into an appropriate abstract representation. Finally, we demonstrate how the existing generation module of VERBMOBIL was extended to produce multilingual and result summaries from these representations.