Miracle-dz/UniFAR-FTUs huggingface dataset:
MOROKOSHI: Transcriptome Database in Sorghum bicolor

In transcriptome analysis, accurate annotation of each transcriptional unit and its expression profile is essential. A full-length cDNA (FL-cDNA) collection facilitates the refinement of transcriptional annotation, and accurate transcription start sites help to unravel transcriptional regulation. We constructed a normalized FL-cDNA library from eight growth stages of aerial tissues in Sorghum bicolor and isolated 37,607 clones. These clones were Sanger sequenced from the 5′ and/or 3′ ends and in total 38,981 high-quality expressed sequence tags (ESTs) were obtained. About one-third of the transcripts of known genes were captured as FL-cDNA clone resources. In addition to these, we also annotated 272 novel genes, 323 antisense transcripts and 1,672 candidate isoforms. These clones are available from the RIKEN Bioresource Center. After obtaining accurate annotation of transcriptional units, we performed expression profile analysis. We carried out spikelet-, seed- and stem-specific RNA sequencing (RNA-Seq) analysis and confirmed the expression of 70.6% of the newly identified genes. We also downloaded 23 sorghum RNA-Seq samples that are publicly available and these are shown on a genome browser together with our original FL-cDNA and RNA-Seq data. Using our original and publicly available data, we made an expression profile of each gene and identified the top 20 genes with the most similar expression. In addition, we visualized their relationships in gene co-expression networks. Users can access and compare various transcriptome data from S, bicolor at http://sorghum.riken. jp.
Choice Based Revenue Management for Parallel Flights

This paper describes a revenue management problem of a major airline that operates in a very competitive market involving two major hubs and having more than 30 parallel daily flights. We consider choice based stochastic assortment optimization problems to maximize the expected revenue for the airline. The inputs include models of booking arrival rates, competitor assortment selection probabilities, customers' booking choices among the airline's own flights as well as competitors' flights, booking-to-ticketing conversion probabilities, and go-show and no-show probabilities. We build a variety of booking choice models to incorporate unobserved heterogeneous customer preferences for different departure times. The way departure time preferences are modeled dramatically affects price sensitivity estimates, and therefore the modeling of heterogeneous departure time preferences matters. We also show that customer choice behavior exhibits discontinuities, with much greater demand for the cheapest alternative than for the second cheapest alternative even when the price difference is small, and much greater demand for fully refundable tickets than almost fully refundable tickets. We formulate a deterministic (fluid) optimization problem corresponding to each of the booking choice models, and we show that in some cases these problems can be solved efficiently even when the discontinuities cause violation of the independence from irrelevant alternatives property. The resulting solutions are used to determine assortment selection policies for the stochastic problem. Simulation studies show that several of these policies generate significantly more revenue than the airline's existing policy, and that the improved performance of these policies is robust with respect to misspecification errors as well as with respect to errors in parameter estimates.
Evaluating the Coverage and Potential of Imputing the Exome Microarray with Next-Generation Imputation Using the 1000 Genomes Project

Next-generation genotyping microarrays have been designed with insights from large-scale sequencing of exomes and whole genomes. The exome genotyping arrays promise to query the functional regions of the human genome at a fraction of the sequencing cost, thus allowing large number of samples to be genotyped. However, two pertinent questions exist: firstly, how representative is the content of the exome chip for populations not involved in the design of the chip; secondly, can the content of the exome chip be imputed with the reference data from the 1000 Genomes Project (1KGP). By deep whole-genome sequencing two Asian populations that are not part of the 1KGP, comprising 96 Southeast Asian Malays and 36 South Asian Indians for which the same samples have also been genotyped on both the Illumina 2.5 M and exome microarrays, we discovered the exome chip is a poor representation of exonic content in our two populations. However, up to 94.1% of the variants on the exome chip that are polymorphic in our populations can be confidently imputed with existing non-exome-centric microarrays using the 1KGP panel. The coverage further increases if there exists population-specific reference data from whole-genome sequencing. There is thus limited gain in using the exome chip for populations not involved in the microarray design. Instead, for the same cost of genotyping 2,000 samples on the exome chip, performing whole-genome sequencing of at least 35 samples in that population to complement the 1KGP may yield a higher coverage of the exonic content from imputation instead.
Primitive Operations for Prioritized Data Reduction in Wireless Sensor Network Nodes

Wireless Sensor Networks have evolved into complex deployments where their nodes can have a full network protocol stack, database systems, etc. The main rationed resource in such a deployment is energy. Having power usage tightly managed ensures a long operational life for the node in cases where replenishments (either via recharge or battery change) are difficult or impossible. The basic deployment of Wireless Sensor Networks consists of sensing nodes as well as a relay node (i.e., sink) which collects sensory data to be relayed via a reliable network. The sink node can become unreachable due to malfunction, scheduled uptime or, in the case of mobile sink nodes, due to being out of the sensor nodes’ reach. In addition, the sensor nodes may decide against relaying data for some period. In these cases, optimal use of sensor node memory space also becomes critical. In this article, we classify data types and establish a set of node level approaches that can be taken to make the most of limited data storage via a prioritized data reduction. We conclude that such a methodology enables the node to be useful by collecting data beyond the point where its data storage size would otherwise allow.
Pedestrian tracking using thermal infrared imaging

This paper describes an experimental study of the use of thermal infrared (8 - 12μm) imaging applied to the problem of pedestrian tracking. Generally it was found that infrared images enable better image segmentation, but their tracking performance with current algorithms is poorer. Simple fusion of both types of images has produced some improvement in the segmentation step of the tracking algorithms. In addition to the specific experimental results, this paper also provides a useful set of practical factors that need to be taken into account when using thermal infrared imaging for surveillance applications under real-world conditions.
USB Device Drivers: A Stepping Stone into Your Kernel

The widely–used Universal Serial Bus (USB) exposes a physical attack vector which has received comparatively little attention in the past. While most research on device driver vulnerabilities concentrated on wireless protocols, we show that USB device drivers provide the same potential for vulnerabilities but offer a larger attack surface resulting from the universal nature of the USB protocol. To demonstrate the effectiveness of fuzzing USB device drivers, we present our prototypical implementation of a mutation–based, man-in-the-middle USB fuzzing framework based on an emulated environment. We practically applied our framework to fuzz the communication between an Apple iPod device and a WindowsXP system. This way, we found several potential vulnerabilities. This supports our claim that the USB architecture exposes real attack vectors and should be considered when assessing the physical security of computer systems in the future.
A Novel Control Method for Transformerless H-Bridge Cascaded STATCOM With Star Configuration

This paper presents a transformerless static synchronous compensator (STATCOM) system based on multilevel H-bridge converter with star configuration. This proposed control methods devote themselves not only to the current loop control but also to the dc capacitor voltage control. With regards to the current loop control, a nonlinear controller based on the passivity-based control (PBC) theory is used in this cascaded structure STATCOM for the first time. As to the dc capacitor voltage control, overall voltage control is realized by adopting a proportional resonant controller. Clustered balancing control is obtained by using an active disturbances rejection controller. Individual balancing control is achieved by shifting the modulation wave vertically which can be easily implemented in a field-programmable gate array. Two actual H-bridge cascaded STATCOMs rated at 10 kV 2 MVA are constructed and a series of verification tests are executed. The experimental results prove that H-bridge cascaded STATCOM with the proposed control methods has excellent dynamic performance and strong robustness. The dc capacitor voltage can be maintained at the given value effectively.
Discovering Feature Weights for Feature-based Indexing of Q-tables

In this paper we propose an approach to address the old problem of identifying the feature conditions under which a gaming strategy can be effective. For doing this, we will build on previous work on CBRetaliate, a system that combines case-based reasoning and reinforcement learning to play team-based First Person Shooter Games. In CBRetaliate, cases are pairs (features, Q-table), where the Q-table associates a utility with each state-action pair, which is used to select an appropriate action in a given state. CBRetaliate learns cases as it plays against opponents. We propose to cluster cases in the case-base using a novel definition of similarity between their Q-tables; cases will be grouped in the same cluster if they have similar Q-tables. We propose to use standard information gain formulas and use the clusters as the classification to assign feature weights. We expect that this approach would lead to identifying features that are crucial to select which Q-table to reuse in a given situation. In addition, we propose to use the same notions of Qtable similarity to find substrategies that are common to every or nearly every case in the case base.
Stereoscopic image transforms to autostereoscopic multiplexed image

Recently, 3D display system are getting considerable attentions not only from theater but also from home. 3D multimedia content is revolutionizing visual entertainment which people can feel more real and fun than color and sound of 2D. Lenticular autostereoscopic display is one of the 3D-TV that consists of following advantages. It improve 3D viewing experience, support wider viewing angles and multiple viewers, and no need for special glasses. In this paper we describe a new technique for generating Autostereoscopic multiplexed content. First, the feature points detector Speeded-Up Robust Features (SURF) was used to match the corresponding pixels between stereo image, and we integrated the Epipolar Line property with detecting process to measure the accuracy of result and scale the matching range down; these corresponding pair, moreover, could be applied to estimate the depth of point which will be used to establish the depth map of image through interpolation of segmentation. Second, in order to obtain the optimized result of disoccluded regions caused by wrapping, we pre-process the depth map through Gaussian filter and mean filter. Finally, we proposed a new method based on DIBR to fill the disoccluded regions with more accurately. The experimental results of our system showed an impressive quality of rendering with Lenticular autostereoscopic display.
Optimizing existential queries in stratifiable deductive databases

We reconsider query evaluation in stratifiable deductive databases using Magic Sets. On the basis of the soft stratification approach, a new solution to the problem of optimizing existential queries in a set-oriented database language like Datalog is presented. To this end, the query answering process is optimized in such a way that after the generation of one appropriate answer fact with respect to a (derived) existential query, the redundant computations of alternative answer facts are avoided. The same technique can be employed for avoiding the generation of subsumed answers and sub-queries as well. It is shown that in presence of recursion or stratified negation this may considerably reduce the total number of facts generated.
Distributed SLAM system using particle swarm optimized particle filter for mobile robot navigation

The distributed SLAM system is a value method for mobile robot navigation. But particle impoverishment is inevitably because of the random particles prediction and resampling applied in generic particle filter, especially in SLAM problem that involve a large number of dimensions. In this paper, the distributed particle swarm optimized particle filter was developed to improve the SLAM system. The Quantum-behaved particle swarm optimized particle filter was used to replace the local filters in distributed SLAM system. The detailed process of the improved distributed SLAM system was described. And the analysis and prove for the optimized distributed SLAM system was finished. The simulation experiment was finished using the experiment data come from an experiment that taken at Victoria Park. And the experiment results show that the proposed algorithm improved the virtue of the DPF-SLAM system in isolate faults and enabled the system has a better tolerance and robustness.
The Rise of New Urban Middle Classes in Southeast Asia: What is its national and regional significance?

Middle classes in East Asia are a product of regional economic development which has taken place in waves under an American informal empire, over half a century, first in Japan, then in NIEs, then in Thailand, Malaysia, Indonesia and the Philippines and now in China. They are a product of developmental states and their politics of economic growth. Their life styles have been shaped in complex ways by their appropriation of things American, Japanese, Chinese, Islamic, and others. Though created in one generation, they nationally occupy different social, political and cultural positions: Thai middle classes are coherent socially, hegemonic culturally and intellectually and ascendant politically; their counterparts in Malaysia and Indonesia are socially divided, dependent on the state, and unable to shape politics in any significant way; and in the Philippines, middle classes are socially coherent, less dependent on the state, culturally ascendant, but politically weak. Yet there is no question that new urban middle classes are there as important forces in all these countries. Their emergence as social and cultural formation is significant for the East Asian region making in three respects. First, being a product of financial globalization and regionalization of production, they have vital stakes in their countries remaining open for those forces. Second, they provide regional markets for MNCs. Whether in fashion, life style, music, or other businesses, firms successful in capturing regional markets thrive. The novelty of the familiar is the key to capturing regional markets or their segments. And third, regional middle class markets open up the possibility for the construction of market-mediated national and regional cultural identities. What remains to be seen is who produces what to further integrate the region economically and to construct an Asian identity for economic and political gains.
The Galaxy Proximity Effect in the Lyα Forest

Hydrodynamic cosmological simulations predict that the average opacity of the Lyα forest should increase in the neighborhood of galaxies because galaxies form in dense environments. Recent observations (Adelberger et al. [1]) confirm this expectation at large scales, but they show a decrease of absorption at comoving separations Δr ⩽ 1h−1 Mpc. We show that this discrepancy is statistically significant, especially for the innermost data point at Δr ⩽ 0.5h−1, even though this data point rests on three galaxy‐quasar pairs. Galaxy redshift errors of the expected magnitude are insufficient to resolve the conflict. Peculiar velocities allow gas at comoving distances ⩾ 1h−1 Mpc to produce saturated absorption at the galaxy redshift, putting stringent requirements on any “feedback” solution. Local photoionization is insufficient, even if we allow for recurrent AGN activity that keeps the neutral hydrogen fraction below its equilibrium value. A simple “wind” model that eliminates all neutral hydrogen in spheres ar.
SERS Substrates by the Assembly of Silver Nanocubes: High-Throughput and Enhancement Reliability Considerations

Small clusters of nanoparticles are ideal substrates for SERS measurements, but the SERS signal enhancement by a particular cluster is strongly dependent on its structural characteristics and the measurement conditions. Two methods for high-throughput assembly of silver nanocubes into small clusters at predetermined locations on a substrate are presented. These fabrication techniques make it possible to study both the structure and the plasmonic properties of hundreds of nanoparticle clusters. The variations in SERS enhancement factors from cluster to cluster were analyzed and correlated with cluster size and configuration, and laser frequency and polarization. Using Raman instruments with 633 nm and 785 nm lasers and linear clusters of nanocubes, an increase in the reproducibility of the enhancement and an increase in the average enhancement values were achieved by increasing the number of nanocubes in the cluster, up to 4 nanocubes per cluster. By examining the effect of cluster configuration, it is shown that linear clusters with nanocubes attached in a face-to-face configuration are not as effective SERS substrates as linear clusters in which nanocubes are attached along an edge.
Measuring Machine Translation Errors in New Domains

We develop two techniques for analyzing the effect of porting a machine translation system to a new domain. One is a macro-level analysis that measures how domain shift affects corpus-level evaluation; the second is a micro-level analysis for word-level errors. We apply these methods to understand what happens when a Parliament-trained phrase-based machine translation system is applied in four very different domains: news, medical texts, scientific articles and movie subtitles. We present quantitative and qualitative experiments that highlight opportunities for future research in domain adaptation for machine translation.
A Novel Approach for Pathway Inference Based on Network Flow ∗

Signal transduction pathways play important roles in various biological processes such as cell cycle, apoptosis, proliferation, differentiation and responses to the external stimuli. Efficient computational methods are of great demands to map signaling pathways systematically based on the interactome and microarray data in the post-genome era. In this study, we propose a novel approach to infer the pathways based on the network flow well studied in the operation research. We define a potentiality variable for each protein to denote the extent to which it belongs to the objective pathway. And the capacity on each edge is not a constant but a function of the potentiality variables of the corresponding two proteins. The total potentiality of all proteins is given an upper bound. The approach is formulated to a linear programming model and solved by the simplex method. Experiments on the yeast sporulation data suggest this novel approach recreated successfully the backbone of the MAPK signaling pathway with a low upper bound of the total potentiality. By increasing the upper bound, the approach successfully predicted all the members of the MAPK pathway responding to the pheromone. It also included the cross-talks between the MAPK pathway and the pathway controlling cell cycle which play important roles in the yeast sporulation. This simple but effective approach provides a very useful tool facilitating the biologists to mine the biological insight from the genomic data.
Issues in Cue Phrase Implicature

Knott's empirical study of cue phrases has resulted in a taxonomic classiication of some 150 cue phrases. The taxonomy can be viewed as a partial ordering on the set of phrases, and hence we can view cue phrase selection in terms of scalar implicature, following Hirschberg. We draw out some of the immediate consequences of this view, including the problematic status of the conventional/conversational distinction, and the proper treatment of high-level cue phrases. We conclude by considering how to test empirically some of the new predictions.
Analysis of longitudinal beam dynamics behavior and rf system operative limits at high-beam currents in storage rings

A dynamics simulation model is used to estimate limits of performance of the Positron-Electron Project (PEP-II). The simulation captures the dynamics and technical limitations of the Low Level Radio Frequency (LLRF) system, the high-power RF components and the low-order mode coupled bunch longitudinal beam dynamics. Simulation results showing the effect of non-linearities on the LLRF loops, and studies of the effectiveness of technical component upgrades are reported, as well as a comparison of these results with PEP-II measurements. These studies have led to the estimation of limits and determining factors in the maximum stored current that the Low Energy Ring/High Energy Ring (LER/HER) can achieve, based on system stability for different RF station configurations and upgrades. In particular, the feasibility of the PEP-II plans to achieve the final goal in luminosity, which required an increase of the beam currents to 4A for LER and 2.2A for HER, is studied. These currents are challenging in part because they would push the longitudinal low-order beam mode stability to the limit, and the klystron forward power past a level of satisfactory margin. An acceptable margin is defined in this paper, which in turn determines the corresponding klystron forward power limitation.
A Study on Burst Error Statistics and Error Modelling for MB-OFDM UWB Systems

Error models characterize the statistics of bursty error sequences encountered in digital wireless channels and are therefore, useful for the cross-layer design of wireless networks. In this paper, target error sequences are generated by computer simulations of multiband orthogonal frequency division multiplexing (MB-OFDM) ultra wideband (UWB) systems. A corresponding generative model is then developed based on a properly parameterized and sampled deterministic process followed by a threshold detector and two parallel mappers. Simulation results indicate that the developed deterministic process based generative model (DPBGM) enables us to approximate very closely the characteristics of target error sequences with respect to all the interested burst error statistics.