Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Temporal Gene Expression during Bacillus subtilis Spore Germination and Outgrowth

ABSTRACT Bacillus subtilis forms dormant spores upon nutrient depletion. Under favorable environmental conditions, the spore breaks its dormancy and resumes growth in a process called spore germination and outgrowth. To elucidate the physiological processes that occur during the transition of the dormant spore to an actively growing vegetative cell, we studied this process in a time-dependent manner by a combination of microscopy, analysis of extracellular metabolites, and a genome-wide analysis of transcription. The results indicate the presence of abundant levels of late sporulation transcripts in dormant spores. In addition, the results suggest the existence of a complex and well-regulated spore outgrowth program, involving the temporal expression of at least 30% of the B. subtilis genome.
Monocle: dynamic, fine-grained data plane monitoring

Ensuring network reliability is important for satisfying service-level objectives. However, diagnosing network anomalies in a timely fashion is difficult due to the complex nature of network configurations. We present Monocle --- a system that uncovers forwarding problems due to hardware or software failures in switches, by verifying that the data plane corresponds to the view that an SDN controller installs via the control plane. Monocle works by systematically probing the switch data plane; the probes are constructed by formulating the switch forwarding table logic as a Boolean satisfiability (SAT) problem. Our SAT formulation quickly generates probe packets targeting a particular rule considering both existing and new rules. Monocle can monitor not only static flow tables (as is currently typically the case), but also dynamic networks with frequent flow table changes. Our evaluation shows that Monocle is capable of finegrained monitoring for the majority of rules, and it can identify a rule suddenly missing from the data plane or misbehaving in a matter of seconds. Also, during network updates Monocle helps controllers cope with switches that exhibit transient inconsistencies between their control and data plane states.
Scanner: An Efficient and Accurate Trimming Tool for Illumina Next Generation Sequencing Reads

Recent advances in High-Throughput Sequencing (HTS) technology have greatly facilitated the researches in bioinformatics field. With the ultra-high sequencing speed and improved base-calling accuracy, Illumina Genome Analyzer is currently the most widely used platform in the field. To use the raw reads generated from the sequencing machine, the 3’ adapter sequence attached to the real read in the process of ligation needs to be correctly trimmed. This is often done by some inhouse scripts or different packages with various parameters. They either use the Smith-Waterman algorithm or search for an exact match of the 3’ adapter sequence. In this report, I investigated methodologies as well as the strengths and weaknesses of five representative mainstream adapter trimming tools in order to suggest a direction for other researchers. Furthermore, four sets of detailed analysis were performed to evaluate the performances of these tools. I demonstrated that my adapter trimming method is flexible, accurate and efficient for Next Generation Sequencing (NGS) analysis. Type of Report: MS Project Report Department of Computer Science & Engineering Washington University in St. Louis Campus Box 1045 St. Louis, MO 63130 ph: (314) 935-6160 Master’s Project Report LCScanner: An Efficient and Accurate Trimming Tool for Illumina Next Generation Sequencing Reads by Xiang Zhou Master of Engineering in Computer Science Washington University in St. Louis, 2012 Research Advisor: Professor Weixiong Zhang
Can quantum mechanics help distributed computing?

We present a brief survey of results where quantum information processing is useful to solve distributed computation tasks. We describe problems that are impossible to solve using classical resources but that become feasible with the help of quantum mechanics. We also give examples where the use of quantum information significantly reduces the need for communication. The main focus of the survey is on communication complexity but we also address other distributed tasks.
Using Principal Component Scores to Enhance the Validity and Reliability of Big Five Personality Measures

Varimax rotated principal component scores (VRPCS) have previously been offered as a possible solution to the non-orthogonality of scores for the Big Five factors. However, few researchers have examined the reliability and validity of VRPCS. To address this gap, we use a lab study and a field study to investigate whether using VRPCS increase orthogonality, reliability, and criterion-related validity. Compared to the traditional unit-weighting scoring method, the use of VRPCS enhanced the reliability and discriminant validity of the Big Five factors, although there was little improvement in criterion-related validity. Results are discussed in terms of the benefit of using VRPCS instead of traditional unit-weighted sum scores.
Optimal Placement of Piezoelectric Torsional Actuator Based on Genetic Algorithm

Aiming at placement optimization of a piezoelectric torsional actuator bonded onto a thin-wall bar, a profound torsional vibration investigation was performed. Dynamic equations of the thin-wall bar-actuator system was theoretically derived using Lagrange equation and assumed mode method, and the state-space expression of the dynamic system was developed. The thin-wall bar was divided into several position units, the controllability Grammian was chosen as the objective function, and optimal placement of piezoelectric torsional actuator was obtained using genetic algorithm. At last, feedback control was performed, and the first three closed-loop frequency response of the angular displacement of the free end was obtained. The results show that the procured optimal placement is feasible. The actuator is bonded onto this position for control where the system has the best controllability, and significant torsional vibration suppression is obtained
VCGG: a varying cone distributed topology-control algorithm for wireless ad hoc networks

In order to increase node lifetime and system throughput, the topology of wireless Ad Hoc networks can be controlled by changing the transmission power at each node. In this paper, we propose an energy-efficient distributed topology-control algorithm, Varying Cone on Gabriel Graph (VCGG). By selecting logical neighbor nodes through deleting the farthest node, VCGG builds a degree-bounded, power spanner and planar sub-graph using the merits of a varying cone. The simulation results show that our proposed VCGG outperforms the existing SΘGG and SYaoGG algorithms in terms of power efficiency, the number of communication neighbors and interference reduction.
A Spinal Cord Window Chamber Model for In Vivo Longitudinal Multimodal Optical and Acoustic Imaging in a Murine Model

In vivo and direct imaging of the murine spinal cord and its vasculature using multimodal (optical and acoustic) imaging techniques could significantly advance preclinical studies of the spinal cord. Such intrinsically high resolution and complementary imaging technologies could provide a powerful means of quantitatively monitoring changes in anatomy, structure, physiology and function of the living cord over time after traumatic injury, onset of disease, or therapeutic intervention. However, longitudinal in vivo imaging of the intact spinal cord in rodent models has been challenging, requiring repeated surgeries to expose the cord for imaging or sacrifice of animals at various time points for ex vivo tissue analysis. To address these limitations, we have developed an implantable spinal cord window chamber (SCWC) device and procedures in mice for repeated multimodal intravital microscopic imaging of the cord and its vasculature in situ. We present methodology for using our SCWC to achieve spatially co-registered optical-acoustic imaging performed serially for up to four weeks, without damaging the cord or induction of locomotor deficits in implanted animals. To demonstrate the feasibility, we used the SCWC model to study the response of the normal spinal cord vasculature to ionizing radiation over time using white light and fluorescence microscopy combined with optical coherence tomography (OCT) in vivo. In vivo power Doppler ultrasound and photoacoustics were used to directly visualize the cord and vascular structures and to measure hemoglobin oxygen saturation through the complete spinal cord, respectively. The model was also used for intravital imaging of spinal micrometastases resulting from primary brain tumor using fluorescence and bioluminescence imaging. Our SCWC model overcomes previous in vivo imaging challenges, and our data provide evidence of the broader utility of hybridized optical-acoustic imaging methods for obtaining multiparametric and rich imaging data sets, including over extended periods, for preclinical in vivo spinal cord research.
The Role of Executive Control Deficits in Cognitive Correlates of Dysphoria

Recent research has suggested that deficits in executive control, especially impairments in cognitive inhibition, as well as rumination, negative involuntary memories, and reduced autobiographical memory specificity could play key roles in the development and exacerbation of depressive symptoms. In the present study, participants completed the Negative Affective Priming (NAP) task, the Ruminative Responses Scale (RRS), the Continuous Word Association Task (CWAT), the Autobiographical Memory Task (AMT), and the Center for Epidemiologic Studies Depression Scale Revised (CESD-R) to examine the relationship between deficits in executive control and dysphoria that may be mediated by ruminative thinking, negative involuntary memory retrieval, and autobiographical memory specificity. Executive control deficits and greater ruminative tendencies were found in the dysphoric sample relative to controls, although there was no evidence to support differences in involuntary memory retrieval or memory specificity. Furthermore, rumination, especially brooding rumination, was found to mediate the relationship between executive control deficits and dysphoria. Although the NAP task seems to measure some aspect of executive control, the results suggested that the task itself warrants further scrutiny.
Luminosity functions of LMXBs in different stellar environments

Aims. Based on the archival data from the Chandra observations of nearby galaxies, we study different sub populations of lowmass X-ray binaries (LMXBs) ‐ dynamically formed systems in globular clusters (GCs) and in the nucleus of M31 and (presumably primordial) X-ray binaries in the fields of galaxies. Our aim is to produce accurate luminosity distributions of X-ray bi naries in different environments, suitable for quantitative comparison with each other and with the output of population synthesis calculations. Methods. Our sample includes seven nearby galaxies (M31, Maffei 1, Centaurus A, M81, NGC 3379, NGC 4697, and NGC 4278) and the Milky Way, which together provide relatively uniform coverage down to the luminosity limit of 10 35 erg/s. In total we have detected 185 LMXBs associated with GCs, 35 X-ray sources in the nucleus of M31, and 998 field sources of which ∼ 365 are expected to be background AGN. We combine these data, taking special care to accurately account for X-ray and optical incompleteness corrections and the removal of the contamination from the cosmic X-ray background sources, to produce luminosity distributions of X-ray binaries in different environments to far greater accuracy than has been obtained previously. Results. We found that luminosity distributions of GC and field LMXBs d iffer throughout the entire luminosity range, the fraction of faint (log(LX) < 37) sources among the former being∼ 4 times less than in the field population. The X-ray luminosit y function (XLF) of sources in the nucleus of M31 is similar to that of GC sources at the faint end but differs at the bright end, with the M31 nucleus hosting significantly fewer bright sources. We discuss the p ossible origin and potential implications of these results .
Comparison on Neural Network based acoustic model in Mongolian speech recognition

Deep Neural Networks (DNNs) beat the Gaussian Mixture Models (GMMs), and become the state-of-the-art techniques for acoustic model. Then various neural networks based acoustic models are proposed to make the speech recognition systems better and better. However these successes are not adopted in the researches of Mongolian speech recognition. This study fills in this gap. We study a series of neural networks based acoustic models, apply them in the Mongolian speech recognition systems, and compare their performance. We find out the Long Short-Term Memory (LSTM) is the best model among them. Finally, by using the LSTM acoustic model together with data augmentation technique, which uses various combinations of Vocal Tract Length Normalization (VTLN) warping factor and time-warping factor to artificially expand the amount of data, we refresh the recode of the Mongolian speech recognition. Compared with the best DNN-based speech recognition system, we cut the Word Error Rate (WER) nearly by half.
Extended line emission around seven radio-loud quasars at redshift z ∼ 2

We present near-infrared spectra of seven radio-loud quasars with a median redshift of 2.1, five of which were previously known to have Lyα nebulae. Extended [O iii] λ5007 and Hα emission are evident around six objects, at the level of a few times 10−16 erg cm−2 arcsec−2 s−1 within ≃2 arcsec of the nucleus (≡16 kpc in the adopted cosmology). Nuclear [O ii] λ3727 is detected in three of the five quasars studied at this wavelength and clearly extended in one of them. The extended [O iii] tends to be brighter on the side of the nucleus with the stronger, jet-like radio emission, indicating at least that the extranuclear gas is distributed anisotropically. It is also typically redshifted by several hundred km s−1 from the nuclear [O iii], perhaps because of the latter being blueshifted from the host galaxy's systemic velocity. Alternatively, the velocity shifts could be due to infall (which is suggested by linewidths ∼1000 km s−1 FWHM) in combination with a suitable dust geometry. Lyα/Hα ratios well below the case B value suggest that some dust is present. Photoionization modelling of the [O iii]/[O ii] ratios in the extended gas suggests that its pressure is around or less than a few times 107 cm−3 K; any confining intracluster medium is thus likely to host a strong cooling flow. A comparison with lower redshift work suggests that there has been little evolution in the nuclear emission-line properties of radio-loud quasars between redshifts 1 and 2.
Discovery of eleven new ZZ Ceti stars

We report the discovery of eleven new ZZ Cetis using telescopes at OPD (Observatorio do Pico dos Dias/LNA) in Brazil, the 4.1 m SOAR (Southern Astrophysical Research) telescope at Cerro Pachon, Chile, and the 2.1 m Otto Struve telescope at McDonald observatory. The candidates were selected from the SDSS (Sloan Digital Sky Survey) and SPY (ESO SN Ia progenitor survey), based on their $T_{\mathrm{eff}}$ obtained from optical spectra fitting. This selection criterion yields the highest success rate of detecting new ZZ Cetis, above 90% in the $T_{\mathrm{eff}}$ range from 12 000 to 11 000 K. We also report on a DA not observed to vary, with a $T_{\mathrm{eff}}$ placing the star close to the blue edge of the instability strip. Among our new pulsators, one is slightly cooler than this star for which pulsations were not detected. Our observations are an important constraint on the location of the blue edge of the ZZ Ceti instability strip.
An Improved Algorithm of Bayesian Text Categorization

Text categorization is a fundamental methodology of text mining and a hot topic of the research of data mining and web mining in recent years. It plays an important role in building traditional information retrieval, web indexing architecture, Web information retrieval, and so on. This paper presents an improved algorithm of text categorization that combines the feature weighting technique with Naive Bayesian classifier. Experimental results show that using the improved Gini index algorithm to feature weight can improve the performance of Naive Bayesian classifier effectively. This algorithm obtains good application in the sensitive information recognition system.
Examining an Effective Communication Message to Promote Participation in Sports Activity: Applying the Extended Parallel Process Model

ABSTRACT The present study examined how a message based on the extended parallel process model can affect individuals’ attitudes and intention to participate in sports activity. A two by two between-subject experiment was conducted among 152 participants who were randomly assigned to one of the four different messages. Individuals’ threat perception was found to increase attitudes and intentions toward sports activity when they also had a high level of efficacy perception to participate in sports activity, supporting the hypothesis. Furthermore, for those with a high level of efficacy, the protective motivation mediated a positive relationship between perceived threat and attitudes, whereas for those with a low level of efficacy, the defensive motivation mediated the negative relationship between perceived threat and attitudes. Neither of the proposed mediators predicted the relationship between perceived threat and intentions. The present study suggests that a theory-based message can help increase campaign effects to promote sports.
Autonomous Navigation using a Real-Time 3 D Point Cloud

This paper presents a system for autonomous navigation of a mobile robot in an unknown environment based on the fusion of a continuously updated point cloud with proprioceptive sensors (IMU and encoders). A SICK LMS100 series laser is used to generate a wide field of view point cloud which is transmitted to a ground control station for visualisation during teleoperation. The point cloud is also used to generate an occupancy grid on which an efficient path planning algorithm is run in realtime. The advantages of this system are its efficiency, flexibility and quick coverage of a large unknown environment. Experiments show the ability of the system to map out a large area while navigating autonomously to a target position.
Photometric survey of the polar ring galaxy NGC 6822

Context. We have previously established, from a carbon star survey, that the Local Group dwarf irregular galaxy NGC 6822 is much larger than its central bright core. Aims. Four MegaCam fields are acquired to survey a 2$^\circ\times 2^\circ$ area centred on NGC 6822 to fully determine its extent and map its stellar populations. Methods. Photometry of over one million stars is obtained in the SDSS g' , r' , i' to three magnitudes below the TRGB. RGB stars, selected from their magnitudes and colours, are used to map the NGC 6822 stellar distribution up to a distance of 60 arcmin. Results. We map the reddening over the whole area. We establish that the stellar outer structure of NGC 6822 is elliptical in shape, with $\epsilon=0.36$ and a major-axis PA = 65°, contrasting with the orientation of the HI disk. The density enhancement can be seen up to a semi-major axis of $36'$ making NGC 6822 as big as the Small Magellanic Cloud. We fit two exponentials to the surface density profile of the spheroid, and identify a bulge with a scale length of $3.85'$ and an outer spheroid with a scale length of $10.0'$. We find intermediate-age C stars up to ${\sim}40'$ while demonstrating that the SDSS filters are unsuitable to identify extragalactic C stars. Conclusions. NGC 6822 is a unique Local Group galaxy with shape and structure suggesting a polar ring configuration. Radial velocities of carbon stars have indeed demonstrated that there are two kinematical systems in NGC 6822.
Path planning for mobile manipulation using probabilistic cell decomposition

In the field of autonomous robotics, manipulation planning is a problem of major significance. A very important component within a manipulation planner is a path planner that is able to connect two configurations by a feasible continuous path, provided that such a path exists. Recently, a new probabilistic path planning method, probabilistic cell decomposition (PCD), has been shown to perform well for, amongst other problems, motion planning for a robotic manipulator. In this paper we investigate how the performance of the general method can be further improved when used within the context of manipulation planning by incorporating knowledge of a specific manipulator. We propose pre-computation of a cell decomposition covering self-collision, adjustment of the cell splitting procedure to the articulated structure of the robot and tuning of distance metrics with respect to the robot. To evaluate the algorithms, we present simulations of a Puma 560 robot arm mounted on a Nomadic XR4000 mobile platform.
Iterative multiuser detection and error control code decoding in random CDMA

The combination of forward-error control (FEC) coding with code-division multiple access (CDMA) using random spreading sequences is considered. Such systems can be viewed as serially concatenated, and iterative (turbo) decoding principles can be applied. An analysis of the component systems is presented by studying variance input-output behaviors. Soft symbols are derived from the FEC decoders' extrinsic information outputs. A variance measure of the error of these soft symbols is used in a variance transfer (VT) analysis between component systems to give an accurate description of the convergence properties of the iterative joint decoder. This VT analysis is applied to three CDMA interference resolution component-systems: 1) simple interference cancellation; 2) per-user minimum-mean-square-error (MMSE) cancellation; and 3) a low-complexity multistage method that is proposed to approximate the complex MMSE filter. Closed-form equations for large-scale systems are presented for all three filters as the number of users K/spl rarr//spl infin/. It is shown that per-user MMSE filtering has a spectral advantage of 1+1//spl alpha/ over simple matched filtering, where /spl alpha/ is the system load supported by the latter, and the multistage filter can approach the MMSE performance with a few stages. Moreover, the number of filter stages to achieve a certain performance is independent of the number of users. The impact of the FEC systems is studied, and it is shown that for low signal-to-noise ratios (SNRs) powerful concatenated codes are required, while for higher SNRs, simple single-error control codes support higher system loads. FEC code examples and simulation results are presented and put in contrast with the capacity limits of the random CDMA channel.
Reverse Engineering Yeast Gene Regulatory Networks using Graphical Models

We investigate in this paper reverse engineering of gene regulatory networks from time series microarray data. We propose a dynamic Bayesian networks (DBNs) modeling and a full Bayesian learning scheme. The proposed DBN models directly the continuous expression levels and also is associated with parameters that indicate the degree as well as the types of regulations. To learn the network from data, we proposed a reversible jump Markov chain Monte Carlo (RJMCMC) algorithm. The RJMCMC algorithm can provide not only more accurate inference results than the deterministic alternative algorithms but also an estimate on the a posteriori probabilities (APPs) of the network topology. The estimated APPs provide useful information on the confidence of the inferred results and can also be used for efficient Bayesian data integration. The proposed approach was tested on yeast cell cycle microarray data and the results were compared with the KEGG pathway map