Miracle-dz/UniFAR-FTUs huggingface dataset:
Haplotyping as perfect phylogeny: conceptual framework and efficient solutions

The next high-priority phase of human genomics will involve the development of a full Haplotype Map of the human genome [12]. It will be used in large-scale screens of populations to associate specific haplotypes with specific complex genetic-influenced diseases. A prototype Haplotype Mapping strategy is presently being finalized by an NIH working-group. The biological key to that strategy is the surprising fact that genomic DNA can be partitioned into long blocks where genetic recombination has been rare, leading to strikingly fewer distinct haplotypes in the population than previously expected [12, 6, 21, 7]. In this paper we explore the algorithmic implications of the key (and now realistic) "no-recombination in long blocks" observation, for the problem of inferring haplotypes in populations. We observe that the no-recombination assumption is very powerful. This assumption, along with the standard population-genetic assumption of infinite sites [23, 14] imposes severe combinatorial constraints on the permitted solutions to the haplotype inference problem, leading to an efficient deterministic algorithm to deduce all features of the permitted haplotype solution(s) that can be known with certainty. The technical key is to view haplotype data as disguised information about paths in an unknown tree, and the haplotype deduction problem as a problem of reconstructing the tree from that path information. This formulation allows us to exploit deep theorems and algorithms from graph and matroid theory to efficiently find one permitted solution to the haplotype problem; it gives a simple test to determine if it is the unique solution; if not, we can implicitly represent the set of all permitted solutions so that each can be efficiently created.
Human Computation : Charting The Growth Of A Burgeoning Field

The rapid growth of human computation within research and industry has produced many novel ideas aimed at organizing web users to do great things. However, the growth is not adequately supported by an overarching framework with which to understand each new system in the context of the old. We give a human computation classification system that can help identify parallels between different systems and reveal “holes” in the existing work as opportunities for new research. Since human computation is often confused with “crowdsourcing” and other terms, we explore the precise position of human computation with respect to other related topics. Author
Identifying User eXperiencing Factors along the Development Process: A Case Study

Currently there are many evaluation methods that can be used to assess the user interface at different phases of the development process. However, the comparison of results obtained from methods employed in early phases (e.g. requirement engineering) and late phases (e.g. user testing) of the development process it is not straightforward. This paper reports how we have treated this problem during the development process of a mobile application called Ubiloop aimed at supporting incident reporting in cities. For that purpose we have employed semi-directive requirement interviews, model-based task analysis, survey of existing systems and user testing with high fidelity prototypes. This paper describes how we have articulated the results obtained from these different methods. Our aim is to discuss how the triangulation of methods might provide insights about the identification of UX factors. Author
SINE Retrotransposons Cause Epigenetic Reprogramming of Adjacent Gene Promoters

Almost half of the human genome and as much as 40% of the mouse genome is composed of repetitive DNA sequences. The majority of these repeats are retrotransposons of the SINE and LINE families, and such repeats are generally repressed by epigenetic mechanisms. It has been proposed that these elements can act as methylation centers from which DNA methylation spreads into gene promoters in cancer. Contradictory to a methylation center function, we have found that retrotransposons are enriched near promoter CpG islands that stay methylation-free in cancer. Clearly, it is important to determine which influence, if any, these repetitive elements have on nearby gene promoters. Using an in vitro system, we confirm here that SINE B1 elements can influence the activity of downstream gene promoters, with acquisition of DNA methylation and loss of activating histone marks, thus resulting in a repressed state. SINE sequences themselves did not immediately acquire DNA methylation but were marked by H3K9me2 and H3K27me3. Moreover, our bisulfite sequencing data did not support that gain of DNA methylation in gene promoters occurred by methylation spreading from SINE B1 repeats. Genome-wide analysis of SINE repeats distribution showed that their enrichment is directly correlated with the presence of USF1, USF2, and CTCF binding, proteins with insulator function. In summary, our work supports the concept that SINE repeats interfere negatively with gene expression and that their presence near gene promoters is counter-selected, except when the promoter is protected by an insulator element. Mol Cancer Res; 10(10); 1332–42. ©2012 AACR.
Generating Rules with Common Knowledge: A Framework for Sentence Information Extraction

There are many nature language processing applications. A typical example is information extraction whose target is a sentence. Various rules are often used in this kind of applications. However, automated processing is not accurate enough in some cases. This is because it is easy to construct syntax rules of a sentence but difficult to semantic rules. On the other hand, the knowledge representation community paid much attention to common knowledge. It is insightful to use rules based on this sense on common things in nature language processing. Therefore, we propose an approach to combine the common knowledge and the nature language processing rules. It first applied the name entity reorganization technology and then generated rules based on a specific common knowledge database. As a result, this approach can be a framework for many (but not all) nature language processing applications. In our experimental example, this approach performed well.
Performance evaluation with a Comparative analysis of mimo channel on The basis of doppler shift and other Probabilistic parameters in fading Environment

At this present scenario, the demand of the system capacity is very high in wireless network. MIMO technology is used from the last decade to provide this requirement for wireless network antenna technology. MIMO channels are mostly used for advanced antenna array technology. But it is most important to control the error rate with enhanced system capacity in MIMO for present-day progressive wireless communication. This paper explores the frame error rate with respect to different path gain of MIMO channel. This work has been done in different fading scenario and produces a comparative analysis of MIMO on the basis of those fading models in various conditions. Here, it is to be considered that modulation technique as QPSK to observe these comparative evaluations for different Doppler frequencies. From the comparative analysis, minimum amount of frame error rate is viewed for Rician distribution at LOS path Doppler shift of 0 Hz. At last, this work is concluded with a comparative bit error rate study on the basis of singular parameters at different SNR levels to produce the system performance for uncoded QPSK modulation.
A Novel SNP Associated with Nighttime Pulse Pressure in Young-Onset Hypertension Patients Could Be a Genetic Prognostic Factor for Cardiovascular Events in a General Cohort in Taiwan

Background Pulse pressure (PP) is a risk factor for cardiovascular disease. It has been reported that ambulatory blood pressure (BP) and nighttime BP parameters are heritable traits. However, the genetic association of pulse pressure and its clinical impact remain undetermined. Method and Results We conducted a genome-wide association study of PP using ambulatory BP monitoring in young-onset hypertensive patients and found a significant association between nighttime PP and SNP rs897876 (p = 0.009) at chromosome 2p14, which contains the predicted gene FLJ16124. Young-onset hypertension patients carrying TT genotypes at rs897876 had higher nighttime PP than those with CT and CC genotypes (TT, 41.6±7.3 mm Hg; CT, 39.1±6.0 mm Hg; CC, 38.9±6.3 mm Hg; p<0.05,). The T risk allele resulted in a cumulative increase in nighttime PP (β = 1.036 mm Hg, se. = 0.298, p<0.001 per T allele). An independent community-based cohort containing 3325 Taiwanese individuals (mean age, 50.2 years) was studied to investigate the genetic impact of rs897876 polymorphisms in determining future cardiovascular events. After an average 7.79±0.28 years of follow-up, the TT genotype of rs897876 was independently associated with an increased risk (in a recessive model) of coronary artery disease (HR, 2.20; 95% CI, 1.20–4.03; p = 0.01) and total cardiovascular events (HR, 1.99; 95% CI, 1.29–3.06; p = 0.002), suggesting that the TT genotype of rs897876C, which is associated with nighttime pulse pressure in young-onset hypertension patients, could be a genetic prognostic factor of cardiovascular events in the general cohort. Conclusion The TT genotype of rs897876C at 2p14 identified in young-onset hypertensive had higher nighttime PP and could be a genetic prognostic factor of cardiovascular events in the general cohort in Taiwan.
Multiple distribution data description learning method for novelty detection

Current data description learning methods for novelty detection such as support vector data description and small sphere with large margin construct a spherically shaped boundary around a normal data set to separate this set from abnormal data. The volume of this sphere is minimized to reduce the chance of accepting abnormal data. However those learning methods do not guarantee that the single spherically shaped boundary can best describe the normal data set if there exist some distinctive data distributions in this set. We propose in this paper a new data description learning method that constructs a set of spherically shaped boundaries to provide a better data description to the normal data set. An optimisation problem is proposed and solving this problem results in an iterative learning algorithm to determine the set of spherically shaped boundaries. We prove that the classification error will be reduced after each iteration in our learning method. Experimental results on 23 well-known data sets show that the proposed method provides lower classification error rates.
Vertical Product Di erentiation, Network Externalities, and Compatibility Decisions

We analyse the subgame perfect equilibrium of a four stage game in a model of vertical product di erentiation, where the consumer's evaluation of a product depends on its inherent quality and on its network's size. First, two rms choose their product's inherent quality. Then they may mutually agree on providing an adapter before competing in prices. Finally, consumers buy. We nd that, despite the high quality rm's preference for incompatibility, an adapter is always provided in equilibrium. Social welfare is greater than without an adapter and can be improved by regulating compatibility only in those cases where qualities are di erentiated too much. JEL classi cation: L13, L15, D43
On the elegibilty grounds of CP-QFSK for mobile radio systems

In this paper we review a class of the Continuous Phase modulation (CPM), namely, the Quaternary Frequency Shift Keying (CP-QFSK) signaling and investigate its suitability for the application in mobile radio systems. This type of modulation renders its self as a spectrally efficient scheme that is currently used in a wide variety of applications ranging from communications systems to sonar, geophysics, and biomedicine, etc. It is exhibited herein that this scheme outperforms its MSK and QPSK counterparts in terms of bandwidth occupancy due to its spectral containment. An extensive survey of research material is provided and some of the CP-QFSK system applications in various realms are highlighted. It is concluded that this signaling scheme due to its spectral efficiency is a viable and promising modulation scheme particularly in the multichannel systems of communications.
Selective data acquisition for probabilistic K-NN query

Recently, management of uncertain data draws lots of attention to consider the granularity of devices and noises in collection and delivery of data. Previous works directly model and handle uncertain data to find the required results. However, when data uncertainty is not small or limited, users are not able to obtain useful insights and thereby tend to provide more resources to improve the solution, by reducing the uncertainty of data. In light of this issue, this paper formulates a new problem of choosing a given number of uncertain data objects for acquiring their attribute values to improve the solutions of Probabilistic k-Nearest-Neighbor (k-PNN) query. We prove that solutions must be better after data acquisition, and we devise algorithms to maximize expected improvement. Our experiment results demonstrate that the probability can be significantly improved with only a small number of data acquisitions.
Non-host Plant Resistance against Phytophthora capsici Is Mediated in Part by Members of the I2 R Gene Family in Nicotiana spp.

The identification of host genes associated with resistance to Phytophthora capsici is crucial to developing strategies of control against this oomycete pathogen. Since there are few sources of resistance to P. capsici in crop plants, non-host plants represent a promising source of resistance genes as well as excellent models to study P. capsici – plant interactions. We have previously shown that non-host resistance to P. capsici in Nicotiana spp. is mediated by the recognition of a specific P. capsici effector protein, PcAvr3a1 in a manner that suggests the involvement of a cognate disease resistance (R) genes. Here, we have used virus-induced gene silencing (VIGS) and transgenic tobacco plants expressing dsRNA in Nicotiana spp. to identify candidate R genes that mediate non-host resistance to P. capsici. Silencing of members of the I2 multigene family in the partially resistant plant N. edwardsonii and in the resistant N. tabacum resulted in compromised resistance to P. capsici. VIGS of two other components required for R gene-mediated resistance, EDS1 and SGT1, also enhanced susceptibility to P. capsici in N. edwardsonii, as well as in the susceptible plants N. benthamiana and N. clevelandii. The silencing of I2 family members in N. tabacum also compromised the recognition of PcAvr3a1. These results indicate that in this case, non-host resistance is mediated by the same components normally associated with race-specific resistance.
Low-Latency Polling Schemes for Long-Reach Passive Optical Networks

The increased propagation delay of future long-reach passive optical networks (LR-PONs) may lead to a significantly increased idle time and delay if optical network units (ONUs) use conventional report-grant mechanisms. Sophisticated and efficient bandwidth allocation mechanisms are required to cope with the imposed propagation delay in LR-PONs. In this study, we evaluate three dynamic bandwidth allocation (DBA) frameworks in terms of frame (packet) delay; namely, we consider conventional (interleaved) polling for traditional PON and two recently introduced scheduling paradigms for next generation LR-PON, i.e., multi-thread polling (MT-P) and real-time polling (RT-P). We enhance MT-P and RT-P by applying the just-in-time framework. Next, we provide an analytical framework for evaluating the end-to-end frame delay in our enhanced MT-P and RT-P frameworks. We compare their performance with conventional polling and double-phase polling and investigate their shortcomings and advantages in an LR-PON setting. The simulation results closely match the analysis for this framework. Also, our results indicate that RT-P significantly reduces frame delay in LR-PONs compared to MT-P and conventional polling frameworks.
Converging Evidence of Ubiquitous Male Bias in Human Sex Perception

Visually judging the sex of another can be achieved easily in most social encounters. When the signals that inform such judgements are weak (e.g. outdoors at night), observers tend to expect the presence of males–an expectation that may facilitate survival-critical decisions under uncertainty. The present aim was to examine whether this male bias depends on expertise. To that end, Caucasian and Asian observers targeted female and male hand images that were either the same or different to the observers’ race (i.e. long term experience was varied) while concurrently, the proportion of targets changed across presentation blocks (i.e. short term experience change). It was thus found that: (i) observers of own-race stimuli were more likely to report the presence of males and absence of females, however (ii) observers of other-race stimuli–while still tending to accept stimuli as male–were not prone to rejecting female cues. Finally, (iii) male-biased measures did not track the relative frequency of targets or lures, disputing the notion that male bias derives from prior expectation about the number of male exemplars in a set. Findings are discussed in concert with the pan-stimulus model of human sex perception.
Encoding Categorical and Coordinate Spatial Relations Without Input-Output Correlations: New Simulation Models

Cook (1995) criticized Kosslyn, Chabris, Marsolek & Koenig's (1992) network simulation models of spatial relations encoding in part because the absolute position of a stimulus in the input array was correlated with its spatial relation to a landmark; thus, on at least some trials, the networks did not need to compute spatial relations. The network models reported here include larger input arrays, which allow stimuli to appear in a large range of locations with an equal probability of being above or below a “bar,” thus eliminating the confound present in earlier models. The results confirm the original hypothesis that as the size of the network's receptive fields increases, performance on a coordinate spatial relations task (which requires computing precise, metric distance) will be relatively better than on a categorical spatial relations task (which requires computing above/below relative to a landmark).
The association between XRCC1 Arg399Gln polymorphism and risk of leukemia in different populations: a meta-analysis of case-control studies

Background Associations between Arg399Gln single-nucleotide polymorphism (SNP) in the XRCC1 gene and leukemia susceptibility have been studied extensively, however, the results are inconsistent. The aim of this study was to determine these associations using meta-analytical methods. Methods A meta-analysis was performed to examine the associations between XRCC1 Arg399-Gln SNP and leukemia risk. A literature search of PubMed and Web of Science databases was conducted to identify relevant studies published up to March 10, 2015. The references of the retrieved articles were also screened. All the statistical analyses were conducted using Review Manager software. Results The XRCC1 Arg399Gln SNP was found to be associated with increased childhood risk of acute lymphoblastic leukemia among Asians under the dominant (odds ratio [OR] 2.11, 95% confidence interval [CI] 1.50–2.97, P<0.0001), allele contrast (OR 1.72, 95% CI 1.33–2.23, P<0.0001), and homozygote contrast (OR 2.34, 95% CI 1.25–4.36, P=0.008) models. However, no association was found in Caucasians between the SNP and risk of either chronic myeloid leukemia or chronic lymphocytic leukemia under any contrast model. Conclusion The findings of the current meta-analysis indicate that the XRCC1 Arg399Gln SNP is a risk factor for childhood lymphoblastic leukemia in Asians.
Self Similar Source Modelling of VBR Packet-Video Traffic

Due to the rapid development of multimedia services efficient modelli ng of VBR sources is becoming a key research topic in the design of future broadband networks. Because of their abilit y in capturing the long term correlation of measured data, Self Similar models permit a reali stic parsimonious description of traffic processes in ATM networks. The fractal nature of video traffic is investigated in connection with different applications (video-telephony, videoconference, entertainment video) and the analysis of the queueing performances emphasises the effects of traffic burstiness on queueing delay and cell l oss probability.
Clinical Significance of Telomere Length and Associated Proteins in Oral Cancer

Purpose Telomere shortening is an important event during carcinogenesis. Although studies suggest role of multiple proteins in telomere length regulation, there is dearth of reports in oral cancer which is a leading malignancy in Asian countries especially in India. Thus the present study was carried out to study these mechanisms and explore the pathways involved in telomere—telomerase regulation and identify possible prognostic markers to understand the biology of oral tumors for better treatment approaches. Methods Telomere length was determined by Southern Hybridisation method, telomeric repeat binding factor (TRF) 1 and 2 expression was detected by Western blot method and telomerase activation by telomeric repeat amplification protocol. Statistical analysis was done using SPSS (Version 10) software. Results Significant shortening of telomeres was seen in the tumor tissues as compared to normal tissues. Poor prognosis was observed in the patients with higher telomere length in malignant tissue, higher tumor to normal telomere length ratio (T/N TRF LR). Expression of TRF-2 but not TRF-1 protein was significantly higher in the malignant tissues. We also observed telomerase activation in 75 malignant tissues. Conclusions Our results reveal significant clinical usefulness of telomere length, T/N TRF LR and telomerase activation in the prognosis of oral cancer patients. TRF-2 overexpression in malignant tissues appears to play an important role in telomere length shortening in oral cancer.
Active Social Capital: Tracing the Roots of Development and Democracy

1. Introduction: Can Social Capital Help Support Development and Democracy? 2. How Might Social Capital Matter? 3. Structure and Agency: New Political Entrepreneurs and the Rise of Village-Based Collective Action4. Measuring Social Capital5. Understanding Economic Development: Why Do Some Villages Develop Faster than Others? 6. Examining Community Harmony: Why Are Some Villages Peaceful and Others Not? 7. Democratic Participation in Rural North India: Social Capital and New Political Entrepreneurs8. ConclusionAppendices
Reactive Zoom Control while Tracking

This paper presents a method for automatically adjusting the zoom setting of an active camera undergoing pure rotation so that it maintains the ratio of projected areas in the scene and image around the fixation point. We restrict discussion to planar objects, and exploit the properties of the two different interimage transformations which are observed — the infinity homography describing correspondences between points projected into the rotating camera from the static background, and the regular plane-to-plane homography between views of the foreground plane which can both rotate and translate freely. Results are presented from real imagery captured from an active camera in both snapshot and real-time operation.