Miracle-dz/UniFAR-FTUs huggingface dataset:
Cell Cycle-independent Role of Cyclin D3 in Host Restriction of Influenza Virus Infection

To identify new host factors that modulate the replication of influenza A virus, we performed a yeast two-hybrid screen using the cytoplasmic tail of matrix protein 2 from the highly pathogenic H5N1 strain. The screen revealed a high-score interaction with cyclin D3, a key regulator of cell cycle early G1 phase. M2-cyclin D3 interaction was validated through GST pull-down and recapitulated in influenza A/WSN/33-infected cells. Knockdown of Ccnd3 by small interfering RNA significantly enhanced virus progeny titers in cell culture supernatants. Interestingly, the increase in virus production was due to cyclin D3 deficiency per se and not merely a consequence of cell cycle deregulation. A combined knockdown of Ccnd3 and Rb1, which rescued cell cycle progression into S phase, failed to normalize virus production. Infection by influenza A virus triggered redistribution of cyclin D3 from the nucleus to the cytoplasm, followed by its proteasomal degradation. When overexpressed in HEK 293T cells, cyclin D3 impaired binding of M2 with M1, which is essential for proper assembly of progeny virions, lending further support to its role as a putative restriction factor. Our study describes the identification and characterization of cyclin D3 as a novel interactor of influenza A virus M2 protein. We hypothesize that competitive inhibition of M1-M2 interaction by cyclin D3 impairs infectious virion formation and results in attenuated virus production. In addition, we provide mechanistic insights into the dynamic interplay of influenza virus with the host cell cycle machinery during infection.
Formability Discussion in Dieless Drawing of Stainless Steel Tubes

Stainless steel tubes are widely used in various fields, such as electrode tubes, probe tubes, electronic parts, painless injection needles, and micro-nozzles etc. In this study, a self-developed prototype dieless drawing machine is used to explore the formability of the dieless drawing process of SUS304 stainless steel tubes. The critical process parameters of the forming temperature, drawing velocity, the drawing accelerations and area reduction are investigated. A commercial finite element code of DEFORM 3D is used to simulate the temperature, stress, strain distributions and drawing velocity limit in the dieless drawing process of the stainless steel tubes. The maximum area reduction obtained can reach 50% and the better forming temperatures are between 1000°C and 1100 °C.
New Mutants of Phycomyces blakesleeanus for (beta)-Carotene Production

The accumulation of (beta)-carotene by the zygomycete Phycomyces blakesleeanus is increased by mutations in the carS gene. The treatment of spores of carS mutants with N-methyl-N(prm1)-nitro-N-nitrosoguanidine led to the isolation, at very low frequencies, of mutants that produced higher levels of (beta)-carotene. Strain S556 produced about 9 mg of (beta)-carotene per g of dry mass when it was grown on minimal agar. Crosses involving strain S556 separated the original carS mutation from a new, unlinked mutation, carF. The carF segregants produced approximately as much carotene as did carS mutants, but they were unique in their ability to produce zygospores on mating and in their response to agents that increase carotenogenesis in the wild type. The carotene contents of carF segregants and carF carS double mutants were increased by sexual interaction and by dimethyl phthalate but were not increased by light or retinol. Mixed opposite-sex cultures of carF carS mutants contained up to 33 mg of (beta)-carotene per g of dry mass. Another strain, S444, produced more (beta)-carotene than did S556 but was marred by slow growth, defective morphology, and bizarre genetic behavior. In all the strains tested, the carotene concentration was minimal during the early growth phase and became higher and constant for several days in older mycelia.
Loose Hamilton Cycles in Regular Hypergraphs

We establish a relation between two uniform models of random k-graphs (for constant k ⩾ 3) on n labelled vertices: ℍ (k) (n,m), the random k-graph with exactly m edges, and ℍ (k) (n,d), the random d-regular k-graph. By extending the switching technique of McKay and Wormald to k-graphs, we show that, for some range of d = d(n) and a constant c > 0, if m ~ cnd, then one can couple ℍ (k) (n,m) and ℍ (k) (n,d) so that the latter contains the former with probability tending to one as n → ∞. In view of known results on the existence of a loose Hamilton cycle in ℍ (k) (n,m), we conclude that ℍ (k) (n,d) contains a loose Hamilton cycle when d ≫ log n (or just d ⩾ C log n, if k = 3) and d = o(n 1/2).
Information visualization using 3D interactive animation

INTRODUCTION Information Visualization uses computer graphics and interactive animation to stimulate recognition of patterns and structure in information. It does so by exploiting the human perceptual system in ways similar to Scientific Visualization, which allows scientists to perceive patterns in large data collections. While Scientific Visualization typically works on data from simulations of physical processes, Information Visualization works on the structure of information inherent in large information spaces. This video shows a prototype system, called the Information Visualizer, and two information visualization techniques used to access information both by structure and by content. Cone Trees are used for visualizing hierarchical information structures. The Perspective Wall is used for visualizing linear information structures. Both techniques use 3D to maximize effective use of available screen space and enable visualization of the whole structure. Interactive animation is used to shift some of the user’s cognitive load to the human perceptual system. The video concludes with a series of examples from an application scenario, based on managing an organization.
Generation of high precision digital maps using circular arc splines

Digital maps can provide essential information for many advanced driver assistance systems (ADAS) dedicated to both safety and comfort applications. As the level of detail and global accuracy of state-of-the-art digital maps are not sufficient for a multitude of applications, we present methods and models for the generation of high precision maps. The proposed modeling includes 3D lane level information, road markings, landmarks and additional attributes with benefits for many ADAS. The extensive use of circular arc splines enables both adjustable accuracy and high efficiency as our cartographic methodology guarantees the minimum number of curve segments with respect to a given error threshold.
Modeling Form for On-line Following of Musical Performances

Automated musical accompaniment of human performers often requires an agent be able to follow a musical score with similar facility to that of a human performer. Systems described in the literature represent musical scores in a way that assumes no large-scale structural variation of the piece during performance. If the performer deviates from the expected path by skipping or repeating a section, the system may become lost. We describe a way to automatically generate a Markov model from a written score that models the score form, and an on-line algorithm to align a performance to a score. The resulting system can follow performances that take alternate paths through the score without losing its place. We compare the performance of our system to that of sequence-based score followers on a melodic corpus of 98 Jazz melodies. Results show that explicitly representing the branching structure of a score significantly improves score following when the branch a performer may take is unknown beforehand.
Binaural Noise Cue Preservation in a Binaural Noise Reduction System With a Remote Microphone Signal

A general binaural noise reduction system is considered that employs the multichannel Wiener filter with partial noise estimation (MWFη) allowing for an explicit tradeoff between noise reduction and binaural noise cue preservation. In this paper, it is assumed that along with the general binaural system, a remote microphone signal with a high input signal-to-noise ratio (SNR) is available for inclusion in the MWFη. The use of this remote microphone signal with a high input SNR allows for a simultaneous increase in both noise reduction performance and preservation of the binaural noise cues. To further increase the performance, a modification to the partial noise estimation (PNE) variable, η, is proposed which relies on exploiting the aforementioned trade-off by either constraining the output SNR or binaural noise cues to the same level before and after the addition of the remote microphone signal. The validity of the theoretical results are supplemented via simulations using a binaural setup with a single speech and noise source.
Evaluation for Warm-Mix Additive-Modified Asphalt Binders Using Spectroscopy Techniques

AbstractThe recent increased interest in “fingerprinting” or identifying commonly used construction materials such as asphalt binders is expected to continue in years to come. To capture the basic fingerprint of asphalt binders, spectroscopy devices can be handy and useful. In particular, this study evaluated the effects of two warm-mix asphalt (WMA) additives, Sasobit and aspha-min, on the chemical compositions of a performance grade binder (PG 64-22). Spectroscopy techniques including Fourier transform infrared (FTIR) spectroscopy, nuclear magnetic resonance (NMR), and X-ray photo electron spectroscopy (XPS) were used in this study. Mass precipitated asphaltenes and maltenes and straight-run asphalt binder samples were analyzed using these techniques, and test results were compared with the rheological data. The effectiveness of an antistripping agent (ASA), AD-here HP Plus, on a WMA-modified binder was also evaluated. Furthermore, the effects of aging on chemical compositions of the ASA-modified binder.
Statistical Inference of Accelerated Life Testing With Dependent Competing Failures Based on Copula Theory

Competing failure is an important reliability topic. Thus, the study of the statistical inference of accelerated life testing (ALT) with competing failures is of great significance. In contrast to the previous related studies that assumed that all competing failure modes were cross statistically independent, we study the statistical inference method for ALT considering the statistical dependence of the competing failure modes based on copula theory. With the copula function, we construct the statistically dependent relationship between the margin distributions of the competing failure modes and their joint distribution, and find the maximum likelihood estimation (MLE) model for the parameter estimations. We also present a simple engineering-based multi-dimensional copula construction method applied in the statistical inference for ALT with statistically dependent competing failure modes. The results and analysis of the case studies indicate that the statistical inference models and the multi-dimensional copula construction method derived in this article are not only correct and feasible but have good accuracy and universality. We have provided an effective, universally applicable method for the statistical inference of ALT in situations involving competing failures, statistically independent or dependent, which is of great significance to evaluating a product's lifetime in ALT.
Recognitionof shapesby morphological attributedrelationalgraphs

Skeletonsrepresent a powerful tool for qualitativeshapematchingbecause they resume,synthesizeandhelptheunderstandingbothof theobjectshapeandof its topology. Theaimof thiswork is mainlyonusingthepotentialstrengthof skeletonof discreteobjectsin computervision andpatternrecognitionwherefeaturesof objects areneededfor classification.In this paperwe proposea methodto improvethetopological skeletonrepresentationof a binary shape.This allows to find a graphmodel characterizedby efficient andeffective attributes,leadingto a morecorrectdiscriminationbetweenshapesby anattributedgraphmatchingalgorithm.
Multisample Analysis of Multivariate Ordinal Categorical Variables

We study a multiple group model with ordinal categorical observed variables that are manifestations of underlying normal variables. When the objective of an analysis is to compare the locations and dispersions of the underlying continuous variables in different groups, traditional approaches use exact linear constraints on thresholds across groups to identify the model. Though the resultant model facilitates interpretation in multiple group analysis, in some cases the exact linear relationships on thresholds are not appropriate for describing the reality. However, these constraints must be imposed to identify the model. In view of this, we propose to apply across group stochastic constraints on thresholds to identify the model. Stochastic constraints are more practical and flexible than exact constraints, and subsume exact constraints as a special case, and therefore enable the structure of the data to be described in a more realistic way. Using stochastic constraints, we can achieve an identified model that allows the comparison of underlying continuous variables in different groups relatively, and at the same time accommodate the possible differences in thresholds. A Bayesian approach is employed to analyze the model, and prior knowledge can be incorporated into the analysis. It is demonstrated that the parameter estimates can be produced conveniently using the Mx software program, and an illustrative sample Mx input script is presented. A real data set is analyzed with the proposed approach, and results are compared to those obtained by using other prevailing approaches.
The impact of service quality, satisfaction, value and switching barrier on customer loyalty in Chinese airline industry

The Chinese airline industry is the most promising market both in terms of the huge opportunity. It has experienced fast grow rate and is now facing a restructured and private entry issue. Under the consideration the launching of the highway and high-railway, the industry is shifting its strategic focus away from price cutting for attracting new customers, towards retaining existing customers through consolidation of service quality and the promotion of customer loyalty. This paper investigates how perception of service quality and switching barriers directly and indirectly influence customer loyalty. An empirical example based on the frequent flyer program market in Chinese indicates support for role of main antecedents of customer loyalty. Managerial implications of the results are discussed
CNN and CRF for Semantic Image Segmentation

In this report, we experienced several ways to do semantic segmentation. First, we explored fully convolutional networks, which modified the fully connected layers in conventional CNN model to convolutional layers. And then we use conditional random field as a post-process method to improve the segmentation result. Finally, we also explored the deeplab segmentation model.
Finite Energy Survey Propagation for Constraint Satisfaction Problems

The Survey Propagation (SP) algorithm [1] has recently been shown to work well in the hard region for random K-SAT problems. SP has its origins in sophisticated arguments in statistical physics, and can be derived from an approach known as the cavity method, when applied at what is called the one-step replica symmetry breaking level. In its most general form, SP can be applied to general constraint satisfaction problems, and can also be used in the unsatisfiable region, where the aim is to minimize the number of violated constraints. In this paper, we formulate the SP-Y algorithm for general constraint satisfaction problems, applicable for minimizing the number of violated constraints. This could be useful, for example, in solving approximate subgraph isomorphism problems. Preliminary results show that SP can solve a few instances of induced subgraph isomorphism for which belief propagation failed to converge.
Insulin Secretion and Incretin Hormone Concentration in Women with Previous Gestational Diabetes Mellitus

Background We examined the change in the levels of incretin hormone and effects of glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide 1 (GLP-1) on insulin secretion in women with previous gestational diabetes (pGDM). Methods A 75-g oral glucose tolerance test (OGTT) was conducted on 34 women with pGDM. In addition, 11 women with normal glucose tolerance, matched for age, height and weight, were also tested. The insulin, GIP, GLP-1, and glucagon concentrations were measured, and their anthropometric and biochemical markers were also measured. Results Among 34 women with pGDM, 18 had normal glucose tolerance, 13 had impaired glucose tolerance (IGT) and 1 had diabetes. No significant differences were found in GLP-1 concentration between the pGDM and control group. However, a significantly high level of glucagon was present in the pGDM group at 30 minutes into the OGTT. The GIP concentration was elevated at 30 minutes and 60 minutes in the pGDM group. With the exception of the 30-minute timepoint, women with IGT had significantly high blood glucose from 0 to 120 minutes. However, there was no significant difference in insulin or GLP-1 concentration. The GIP level was significantly high from 0 to 90 minutes in patients diagnosed with IGT. Conclusion GLP-1 secretion does not differ between pGDM patients and normal women. GIP was elevated, but that does not seem to induce in increase in insulin secretion. Therefore, we conclude that other factors such as heredity and environment play important roles in the development of type 2 diabetes.
Network Configuration and Flow Scheduling for Big Data Applications

This chapter focuses on network configuration and flow scheduling for Big Data applications. It highlights how the performance of Big Data applications is tightly coupled with the performance of the network in supporting large data transfers. Deploying high-performance networks in data centers is thus vital but configuration and performance management as well as the usage of the network are of paramount importance. This chapter starts by discussing the problem of virtual machine placement and its solutions considering the underlying network topology. It then provides an analysis of alternative topologies highlighting their advantages from the perspective of Big Data applications needs. In this context, different routing and flow scheduling algorithms are discussed in terms of their potential for using the network most efficiently. In particular, Software-Defined Networking relying on centralized control and the ability to leverage global knowledge about the network state is propounded as a promising approach for efficient support of Big Data applications.
Predictive Inverse Optimal Control in Large Decision Processes via Heuristic-based Search

Human behavior is much more structured than physical limitations require; variability in tasks ranging from manipulating an object (Castiello, 2005) to locomoting (Taga, 1995) is relatively small. For robots to efficiently interact with people, they must learn this structure to be able to predict human behavior (Ziebart et al., 2009) and be predictable themselves (Dragan et al., 2013). This will allow both robot and person to take complementary actions that efficiently realize shared objectives.
Brain imaging in awake infants by near-infrared optical topography

Studies of young infants are critical to understand perceptual, motor, and cognitive processing in humans. However, brain mechanisms involved are poorly understood, because the use of brain-imaging methods such as functional magnetic resonance imaging in awake infants is difficult. In the present study we show functional brain imaging of awake infants viewing visual stimuli by means of multichannel near-infrared spectroscopy, a technique that permits a measurement of cerebral hemoglobin oxygenation in response to brain activation through the intact skull without subject constraint. We found that event-related increases in oxyhemoglobin were evident in localized areas of the occipital cortex of infants aged 2–4 months in response to a brief presentation of a checkerboard pattern reversal while they maintained fixation to attention-grabbing stimuli. The dynamic change in cerebral blood oxygenation was qualitatively similar to that observed in the adult brain. This result introduces near-infrared optical topography as a method for investigating the functional development of the brain in early infancy.
An Image Matching Method on Photography Measurement

The image feature matching is a critical step in photography measurement and rebuilding. Based on the Characteristics of topography measurement, a new topography feature matching algorithm is presented in this paper. In the algorithm, the stereo images to be matched are partitioned, and then the region matching process is used to these partitioned image pairs. Based on the region matching, the corner feature matching operation is then processed, which involves relaxed iteration algorithm, zero-crossing method and least squares median algorithms to eliminate the ill matching points. Three groups of topography photography measurement images are used in image matching experiment, the experiment results shows that this algorithm can effectively improve the computation efficiency and matching accuracy, thus has a wide applications in the area based on the principle of stereo vision, such as: topography photography measurement, urban planning, etc.
A Case Study on Implementing Virtual 5D Torus Networks Using Network Components of Lower Dimensionality

Several of the most powerful supercomputers in the Top500 and the Graph500 lists continue choosing a torus topology to interconnect a large number of compute nodes. In some cases, a torus network with five or six dimensions is implemented, however, one notices that the costs of implementing an interconnection network increase with the node degree. In previous works we defined and characterized the nD Twin (nDT) torus topology in order to virtually increase the dimensionality of a torus. This new topology reduces the distances between nodes and therefore increases network performance. In this work, we present how to build a 5DT torus network using commercial 6-port network cards. The main issues of this approach are detailed, and we present solutions these problems. Moreover we show, using the same components, that the performance of the 5DT torus network is higher than the performance of the 3D torus network for the same number of compute nodes.