Miracle-dz/UniFAR-FTUs huggingface dataset:
Sar1 promotes vesicle budding from the endoplasmic reticulum but not Golgi compartments

Two new members (Sar1a and Sar1b) of the SAR1 gene family have been identified in mammalian cells. Using immunoelectron microscopy, Sar1 was found to be restricted to the transitional region where the protein was enriched 20-40-fold in vesicular carriers mediating ER to Golgi traffic. Biochemical analysis revealed that Sar1 was essential for an early step in vesicle budding. A Sar1-specific antibody potently inhibited export of vesicular stomatitis virus glycoprotein (VSV-G) from the ER in vitro. Consistent with the role of guanine nucleotide exchange in Sar1 function, a trans-dominant mutant (Sar1a[T39N]) with a preferential affinity for GDP also strongly inhibited vesicle budding from the ER. In contrast, Sar1 was not found to be required for the transport of VSV-G between sequential Golgi compartments, suggesting that components active in formation of vesicular carriers mediating ER to Golgi traffic may differ, at least in part, from those involved in intra-Golgi transport. The requirement for novel components at different stages of the secretory pathway may reflect the recently recognized differences in protein transport between the Golgi stacks as opposed to the selective sorting and concentration of protein during export from the ER.
A Module Analysis Approach to Investigate Molecular Mechanism of TCM Formula: A Trial on Shu-feng-jie-du Formula

At the molecular level, it is acknowledged that a TCM formula is often a complex system, which challenges researchers to fully understand its underlying pharmacological action. However, module detection technique developed from complex network provides new insight into systematic investigation of the mode of action of a TCM formula from the molecule perspective. We here proposed a computational approach integrating the module detection technique into a 2-class heterogeneous network (2-HN) which models the complex pharmacological system of a TCM formula. This approach takes three steps: construction of a 2-HN, identification of primary pharmacological units, and pathway analysis. We employed this approach to study Shu-feng-jie-du (SHU) formula, which aimed at discovering its molecular mechanism in defending against influenza infection. Actually, four primary pharmacological units were identified from the 2-HN for SHU formula and further analysis revealed numbers of biological pathways modulated by the four pharmacological units. 24 out of 40 enriched pathways that were ranked in top 10 corresponding to each of the four pharmacological units were found to be involved in the process of influenza infection. Therefore, this approach is capable of uncovering the mode of action underlying a TCM formula via module analysis.
Asymptotic properties of false discovery rate controlling procedures under independence

We investigate the performance of a family of multiple comparison procedures for strong control of the False Discovery Rate ($\mathsf{FDR}$). The $\mathsf{FDR}$ is the expected False Discovery Proportion ($\mathsf{FDP}$), that is, the expected fraction of false rejections among all rejected hypotheses. A number of refinements to the original Benjamini-Hochberg procedure [1] have been proposed, to increase power by estimating the proportion of true null hypotheses, either implicitly, leading to one-stage adaptive procedures [4, 7] or explicitly, leading to two-stage adaptive (or plug-in) procedures [2, 21]. We use a variant of the stochastic process approach proposed by Genovese and Wasserman [11] to study the fluctuations of the $\mathsf{FDP}$ achieved with each of these procedures around its expectation, for independent tested hypotheses. We introduce a framework for the derivation of generic Central Limit Theorems for the $\mathsf{FDP}$ of these procedures, characterizing the associated regularity conditions, and comparing the asymptotic power of the various procedures. We interpret recently proposed one-stage adaptive procedures [4, 7] as fixed points in the iteration of well known two-stage adaptive procedures [2, 21].
Nonnegative Mixed-Norm Convex Optimization for Mitotic Cell Detection in Phase Contrast Microscopy

This paper proposes a nonnegative mix-norm convex optimization method for mitotic cell detection. First, we apply an imaging model-based microscopy image segmentation method that exploits phase contrast optics to extract mitotic candidates in the input images. Then, a convex objective function regularized by mix-norm with nonnegative constraint is proposed to induce sparsity and consistence for discriminative representation of deformable objects in a sparse representation scheme. At last, a Support Vector Machine classifier is utilized for mitotic cell modeling and detection. This method can overcome the difficulty in feature formulation for deformable objects and is independent of tracking or temporal inference model. The comparison experiments demonstrate that the proposed method can produce competing results with the state-of-the-art methods.
Extreme Habitability: Formation of Habitable Planets in Systems with Close-in Giant Planets and/or Stellar Companions

With more than 260 extrasolar planetary systems discovered to-date, the search for habitable planets has found new grounds. Unlike our solar system, the stars of many of these planets are hosts to eccentric or close-in giant bodies. Several of these stars are also members of moderately close ($<$40 AU) binary or multi-star systems. The formation of terrestrial objects in these "extreme" environments is strongly affected by the dynamics of their giant planets and/or their stellar companions. These objects have profound effects on the chemical structure of the disk of planetesimals and the radial mixing of these bodies in the terrestrial regions of their host stars. For many years, it was believed that such effects would be so destructive that binary stars and also systems with close-in giant planets would not be able to form and harbor habitable bodies. Recent simulations have, however, proven otherwise. I will review the results of the simulations of the formation and long-term stability of Earth-like objects in the habitable zones of such "extreme" planetary systems, and discuss the possibility of the formation of terrestrial planets, with significant amounts of water, in systems with hot Jupiters, and also around the primaries of moderately eccentric close binary stars.
Adverse Selection, Moral Hazard and the Term Structure of Default

This paper estimates the term structure of the hazard rate to default by using two hazard models - one ignoring and another allowing unobserved heterogeneity and annual shocks to the hazard rate. Diamond (1989) predicts a declining hazard rate to default due to adverse selection and moral hazard. The adverse selection effect is confirmed. Without controlling for adverse selection the hazard rate decreases over time. After controlling for adverse selection, the hazard rate shows to be increasing over time and hence the moral hazard effect cannot be confirmed. The paper contributes also to the credit risk literature by providing new stylized facts and by providing a tool to gap between the immediate and long-term default probabilities.
A Novel Approach Based on Logistic Regression and Bayesian for Relevance Feedback in Content-Based Image Retrieval

This paper presents a new relevance feedback (RF) method for image retrieval in content-based image retrieval (CBIR). The main conception of the method gives two aspects: First logistic regression adjusts the weight of each element in features extracted from the images in database with the preferences of the user. Then following a Bayesian methodology, which yields the posteriori of the images in the database and used to show to the user a new set of images. The retrieval system is repeating until he/she is satisfied or the target image has been found. Experimental results show the superiority of the proposed method.
IOS and supply chain process innovation

Taking China's two successful IOS cases as study object, this paper investigated inter-firm business process transformation enabled by IOS from four aspects, namely, integration, transfer, elimination and creation of inter-firm business processes. This study argues that IOS must be seen as the enabler of organizational structure and business process changes rather than a mere implementation tool for existing organizations and processes inside enterprises and between enterprises. Enterprises should focus on their core capability, collaborate with each other with IOS and actively achieve inter-firm business process integration and innovation.
Beyond DNA: An Integrated and Functional Approach for Classifying Germline Variants in Breast Cancer Genes

Genetic testing for hereditary breast cancer is an integral part of individualized care in the new era of precision medicine. The accuracy of an assay is reliant on not only the technology and bioinformatics analysis utilized but also the experience and infrastructure required to correctly classify genetic variants as disease-causing. Interpreting the clinical significance of germline variants identified by hereditary cancer testing is complex and has a significant impact on the management of patients who are at increased cancer risk. In this review we give an overview of our clinical laboratory's integrated approach to variant assessment. We discuss some of the nuances that should be considered in the assessment of genomic variants. In addition, we highlight lines of evidence such as functional assays and structural analysis that can be useful in the assessment of rare and complex variants.
Skyline Computation Algorithms - A Study

A skyline query operator is designed to find the set of interesting data points (objects) over a large dimensional data collection, satisfying a set of possibly contradicting conditions. In this paper, we provide an in-depth coverage of skyline algorithms. The paper consists of three parts. First, skyline operator with one of its application is discussed. Second, we represent history of skyline algorithms developed till date along with their pros and cons. Finally, we present the efficiency of skyline query processing algorithms on the basis of time complexities over high dimensional large datasets.
Requirements Management in Global Software Development : Preliminary Findings from a Case Study in a SW-CMM context

The requirements analysis is an important phase in the software development process. In geographically distributed environments (Global Software Development), requirements management becomes critical due to the characteristics of the distributed development (physical distance, cultural differences, trust, communication, etc). The objective of this paper is to analyze the requirements management in geographically distributed environments, identifying the main challenges. The results are based on a case study carried in a multinational organization that has offshore software development centers in Brazil, India and Russia, and was recently certified in SW-CMM Model level 2 in the Brazilian unit. The results suggest the necessity to adapt the requirements management to the distributed software development environment, addressing the main existing challenges. The problems and the solutions adopted are presented, aiming to relate these solutions to the organization distribution level, considering the project team, users and customers.
Reassessing FHA Risk

Federal Housing Administration (FHA) insurance has doubled over the past two years and is projected to redouble to $1.5 trillion over the next five. Despite clear signs of strain in the FHA's Mutual Mortgage Insurance Fund, a recent actuarial review indicates that the FHA will not need any form of government support. We identify four risk factors that make such a funding request more likely; the review underestimates how many FHA borrowers are underwater and in economic distress; it uses measures of house values that lower loss estimates; it does not incorporate early-warning signals of future losses that are available from mortgage delinquency; and it ignores potential risks associated with recent down-payment assistant programs despite higher losses on previous programs of this type. We propose measures that could be taken to improve the predictive accuracy of FHA risk assessment.
An Alternative backup Route with a Loop Free Routing Table Short Distance in Ad hoc Wireless

In a mobile ad hoc wireless networks (MANET), nodes communicate with each other via packet radios. However, in a MANET network, the mobility of the nodes and power limitations lead to an increased loss of connectivity between the mobile nodes when changing the route between nodes, which requires the routing table to be frequently updated. Hence, routing protocol plays an important role in updating the routing table when the nodes move from one area to another. By pre-computing a backup routing table in advance, the source can pass traffic through it without needing to wait for the routing table to be updated from where the failure occurs. This paper proposes a new algorithm, ARTSD (Alternative Routing Table Short Distance), to improve the existing DSDV (Destination Sequenced Distance Vector) protocol by creating a mesh network with different numbers of nodes to provide multiple alternative routes. The ARTSD algorithm determines the adjacent nodes for each node on the primary path and then selects one of these adjacent nodes as the backup next hop according to the least numbers of hops to the destination. The results show that loss of data packets, throughput and end-to-end delay times between source and destination have been improved by avoiding loops on the network. The results show that the new protocol does not degrade network performance by sending extra messages to construct the new backup routing table. A simulation (using an NS2 simulator) was undertaken to demonstrate the difference between using a DSDV protocol with or without the proposed schema.
Genome analysis Osiris : an integrated promoter database for Oryza sativa L .

Summary: Rice (Oryza sativa L.) is an important model monocot and cereal crop. While the rice genome sequence has been published and annotated, relatively little is known about the transcriptional networks that regulate rice gene expression. For this reason, we have developed Osiris, a database containing promoter sequences, predicted transcription factor (TF) binding sites, gene ontology annotation and microarray expression data for 24 209 genes in the rice genome. These tools are seamlessly integrated in the Osiris web site, allowing the user to visualize TF binding sites in multiple promoters; analyze the statistical significance of enriched TF binding sites; query for genes containing similar promoter regulatory logic or gene function and visualize the microarray expression patterns of queried or selected gene sets. Availability: http://www.bioinformatics2. wsu.edu/Osiris Contact: jwyrick@wsu.edu Supplementary information: Supplementary data are available at Bioinformatics online.
Improving the energy efficiency of WSN by using application-layer topologies to constrain RPL-defined routing trees

The deployment of thousands of tiny devices inter-networked together and accessible through the Internet is the result of the increasing trend towards enabling the concepts of Internet-of-Things. As these devices may be scattered in a unplanned way, a routing protocol is needed. The RPL protocol is the IETF proposed standard protocol for IPv6-based multi-hop Wireless Sensor Networks (WSN). RPL requires that communication paths go through a central router which may provide suboptimal paths, making no distinction of the applications the nodes run. To address these issues, an Application-Driven extension to RPL is proposed which enables the increase of the WSN lifetime by limiting the routing and forwarding functions of the network mainly to nodes running the same application. This paper evaluates the proposed solution coded in ContikiOS by means of Cooja simulations, and compares it against regular RPL. Simulation results confirm that the proposed solution provides lower energy consumption, lower end-to-end delays, and lower total number of packets transmitted and received.
Preclinical and Clinical Assessment of Cannabinoids as Anti-Cancer Agents

Cancer is the second leading cause of death in the United States with 1.7 million new cases estimated to be diagnosed in 2016. This disease remains a formidable clinical challenge and represents a substantial financial burden to the US health care system. Therefore, research and development of novel therapeutics for the treatment of cancer is of high priority. Cannabinoids and their derivatives have been utilized for their medicinal and therapeutic properties throughout history. Cannabinoid activity is regulated by the endocannabinoid system (ECS), which is comprised of cannabinoid receptors, transporters, and enzymes involved in cannabinoid synthesis and breakdown. More recently, cannabinoids have gained special attention for their role in cancer cell proliferation and death. However, many studies investigated these effects using in vitro models which may not adequately mimic tumor growth and metastasis. As such, this article aims to review study results which evaluated effects of cannabinoids from plant, synthetic and endogenous origins on cancer development in preclinical animal models and to examine the current standing of cannabinoids that are being tested in human cancer patients.
Foveated nonlo cal self-si milarity

When we gaze a scene, our visual acuity is maximal at the xation point (imaged by the fovea, the central part of the retina) and decreases rapidly towards the periphery of the visual eld. This phenomenon is known as foveation. We investigate the role of foveation in nonlocal image ltering, installing a di¤erent form of self-similarity: the foveated self-similarity. We consider the image denoising problem as a simple means of assessing the e¤ectiveness of descriptive models for natural images and we show that, in nonlocal image ltering, the foveated self-similarity is far more e¤ective than the conventional windowed self-similarity. To facilitate the use of foveation in nonlocal imaging algorithms, we develop a general framework for designing foveation operators, i.e., linear operators producing foveated patches by means of spatially variant blur. Within this framework, we construct several parametrized families of foveation operators, including anisotropic ones. Strikingly, the operators enabling the best denoising performance are the radial ones, in complete agreement with the orientation preference of the human visual system.
Mechanical and Aerospace Engineering Stability and Transition of Three-dimensional Boundary Layers

We are pleased to provide you a complimentary copy of our Annual Reviews article as a PDF file for your own personal use. Any further/multiple distribution, publication or commercial usage of this copyrighted material would require submission of a permission request addressed to the Annual Reviews Permissions Department, s Abstract The recent progress in three-dimensional boundary-layer stability and transition is reviewed. The material focuses on the crossflow instability that leads to transition on swept wings and rotating disks. Following a brief overview of instability mechanisms and the crossflow problem, a summary of the important findings of the 1990s is given.
The Metropolis-Hastings-Green Algorithm

1.1 Dimension Changing The Metropolis-Hastings-Green algorithm (as opposed to just MetropolisHastings with no Green) is useful for simulating probability distributions that are a mixture of distributions having supports of different dimension. An early example (predating Green’s general formulation) was an MCMC algorithm for simulating spatial point processes (Geyer and Møller, 1994). More widely used examples are Bayesian change point models and Bayesian model selection (Green, 1995). Abstractly, we are interested in a Markov chain having a state space that is a union of Euclidean spaces of different dimension. Let X denote the state space of the Markov chain. This is assumed to be a disjoint union
An exact word lattice generation method in the weighted finite-state transducer framework

As a multiple-candidate output format of speech recognition system, word lattice is essential for applications such as keyword spotting, confidence measure, multi-pass decoding and so on. This paper analyzes the problems of generating word lattice using Weighted Finite-State Transducer (WFST) decoders, such as word boundary decision, word position pushing and redundancy existed in the word lattice. We present an efficient word lattice generation method which is able to retain all the accurate word alignment information. Furthermore, a new word-level determinization algorithm that keeps the alignment information is described to completely remove the redundant paths in the word lattice. Experiments show that the proposed determinization algorithm is effective for improving the quality of the word lattice-based confidence measure and accuracy of keyword spotting.
Fast content independent playlist generation for streaming media

Playlist generation is an important part of online streaming media platforms. Different methods rely on different information to generate playlists. Approaches trained exclusively on previous playlists (interaction data) are content independent, thus they can work with playlists containing different content types. The data types, playlist generation methods and evaluation approaches are described in the first part of the paper. A novel method with similar performance to k Nearest Neighbour is proposed in second part. The method is based on random walk and returns tracks with the same probability distribution as a k Nearest Neighbour method would do with a special similarity metric and including all neighbours. As there is no need for neighbour search the runtime complexity is lower by orders of magnitude. The performance is comparable to playlist generation methods also incorporating artist meta-data (CAGH, SAGH).
Management of Agricultural Crop Insurance Contracts : a Theoretical Strategy

Agricultural economic literature shows the difficulties to manage insurance contracts that include systemic risk. The aim of the paper is to present an approach to overcome such difficulties. It is applied to a crop yield insurance contract but can be extended to other insurance contracts such as revenue or crop margin. The approach mixes the pooling technique usually used to manage insurance contracts and risk transfer to financial markets as used to manage systemic risks. The financial market model includes a crop yield futures contract, a price futures contract and a zerocoupon bond. It is shown in the theoretical approach that this strategy allows for an intermediation for a risk-free management of such a type of insurance contract.