Miracle-dz/UniFAR-FTUs huggingface dataset:
Structure and Distribution of Organelles and Cellular Location of Calcium Transporters in Neurospora crassa

ABSTRACT We wanted to examine the cellular locations of four Neurospora crassa proteins that transport calcium. However, the structure and distribution of organelles in live hyphae of N. crassa have not been comprehensively described. Therefore, we made recombinant genes that generate translational fusions of putative organellar marker proteins with green or red fluorescent protein. We observed putative endoplasmic reticulum proteins, encoded by grp-78 and dpm, in the nuclear envelope and associated membranes. Proteins of the vacuolar membrane, encoded by vam-3 and vma-1, were in an interconnected network of small tubules and vesicles near the hyphal tip, while in more distal regions they were in large and small spherical vacuoles. Mitochondria, visualized with tagged ARG-4, were abundant in all regions of the hyphae. Similarly, we tagged the four N. crassa proteins that transport calcium with green or red fluorescent protein to examine their cellular locations. NCA-1 protein, a homolog of the SERCA-type Ca2+-ATPase of animal cells, colocalized with the endoplasmic reticulum markers. The NCA-2 and NCA-3 proteins are homologs of Ca2+-ATPases in the vacuolar membrane in yeast or in the plasma membrane in animal cells. They colocalized with markers in the vacuolar membrane, and they also occurred in the plasma membrane in regions of the hyphae more than 1 mm from the tip. The cax gene encodes a Ca2+/H+ exchange protein found in vacuoles. As expected, the CAX protein localized to the vacuolar compartment. We observed, approximately 50 to 100 μm from the tip, a few spherical organelles that had high amounts of tagged CAX protein and tagged subunits of the vacuolar ATPase (VMA-1 and VMA-5). We suggest that this organelle, not described previously in N. crassa, may have a role in sequestering calcium.
Quality of Service in mobile ad hoc networks: a survey

To support multimedia applications, it is desirable that an ad hoc network has a provision of Quality of Service (QoS). However, the provision of QoS in a mobile ad hoc network is a challenging task. In this paper, we present a review of the current research related to the provision of QoS in an ad hoc environment. We examine issues and challenges involved in providing QoS in an ad hoc network. We discuss methods of QoS provisioning at different levels including those at the levels of routing, Medium Access Control (MAC), and cross layer. Also, we discuss schemes for admission control and scheduling that are proposed in the literature for the provision of QoS. We compare salient features of various solutions and approaches and point out directions for future work.
Investigating the differential mobility experiences of Chinese cross-border students

Abstract Recent migration studies have adopted the lens of mobility to examine the stratifying effects of border policies, but few investigate the differential mobility of migrant families and children. This paper aims to contribute to the migration literature by considering the interplay between border policies, family configurations, and differential mobility. We apply the lens of differential mobility to the experiences of Chinese cross-border pupils – young child migrants with Hong Kong permanent residency who reside in Shenzhen, China, and cross the border to attend school. We begin by describing shifts in Hong Kong’s border and immigration policies since 1997, which have created a typology of families differentiated by mixed status, citizenship rights, and mobility. We then turn to four case studies of students with unequal border-crossing experiences to elucidate how border control constrains or promotes family mobility and perpetuates inequalities.
Structure learning of probabilistic logic programs by searching the clause space

Abstract Learning probabilistic logic programming languages is receiving an increasing attention, and systems are available for learning the parameters (PRISM, LeProbLog, LFI-ProbLog and EMBLEM) or both structure and parameters (SEM-CP-logic and SLIPCASE) of these languages. In this paper we present the algorithm SLIPCOVER for “Structure LearnIng of Probabilistic logic programs by searChing OVER the clause space. ” It performs a beam search in the space of probabilistic clauses and a greedy search in the space of theories using the log likelihood of the data as the guiding heuristics. To estimate the log likelihood, SLIPCOVER performs Expectation Maximization with EMBLEM. The algorithm has been tested on five real world datasets and compared with SLIPCASE, SEM-CP-logic, Aleph and two algorithms for learning Markov Logic Networks (Learning using Structural Motifs (LSM) and ALEPH++ExactL1). SLIPCOVER achieves higher areas under the precision-recall and receiver operating characteristic curves in most cases.
ON THE USE OF METAL GRATINGS TO REDUCE DIFFRACTION FROM A FINITE GROUND PLANE IN CIRCULARLY-POLARIZED MICROSTRIP ARRAYS

It is shown that metal gratings can be used to improve the cross polarization of circularly-polarized aperture-coupled microstrip antennas. The metal gratings reduce edge difiraction from the flnite- size grounded dielectric slab on which the antennas are printed. The edge difiraction is due to surface waves that can propagate in the grounded dielectric slab. The design of the metal grating is based on an analytical model, which results in a flrst-order estimation for the design of the metal grating structure. The model provides physical insight and appears to be accurate enough for the application. Using this model, a prototype was developed, consisting of a circularly-polarized 2 £ 2 microstrip array with associated feeding network. Measurements show that the axial ratio can be reduced down to 1.75dB within the beam width of the antenna.
Stages of Sexual Grooming: Recognizing Potentially Predatory Behaviors of Child Molesters

ABSTRACT It has been proposed that sexual grooming behaviors of child molesters are not easily identified prior to the abuse. The present study investigated whether participants could recognize grooming behaviors, and if so, identify which stages of the process were most easily identified. Participants were randomly assigned to read one of six vignettes describing the stages of the grooming process. Results revealed no differences in likelihood ratings that the person in the vignette was a child molester and would commit sexual abuse between any of the conditions, suggesting that people may be unable to identify potentially predatory behaviors of child molesters prospectively.
Onboard Adaptive Learning for Planetary Surface Rover Control in Rough Terrain

Current and future NASA robotic missions to planetary surfaces are tending toward longer duration and are becoming more ambitious for rough terrain access. For a higher level of autonomy in such missions, the rovers will require behavior that must also adapt to declining rover health and unknown environmental conditions. The MER (Mars Exploration Rovers) called Spirit and Opportunity have both passed 350 days of life on the Martian surface, with possible extensions to 450 days and beyond depending on rover health. Changes in navigational planning due to degradation of the drive motors as they reach their lifetime are currently done on Earth for the Spirit rover. The upcoming 2009 MSL (Mars Science Laboratory) and 2013 AFL (Astrobiology Field Laboratory) missions are planned to last 300-500 days, and will possibly involve traverses on the order of multiple kilometers over challenging terrain. This paper presents an adaptive control algorithm for onboard learning of weights within a free flow hierarchy (FFH) behavior framework for autonomous control of planetary surface rovers that explicitly addresses the issues of rover health and rough terrain access. We also present the results of some laboratory and field studies.
Intelligent Agents for Proactive Fault Detection

As the Internet becomes a critical component of our society, a key challenge is to maintain network availability and reliability. Intelligent processing agents that reside at network nodes use an adaptive learning method to detect abnormal network behavior before a fault actually occurs. In a test at Rensselaer Polytechnic Institute, an agent on a router detected a file server failure 12 minutes before it occurred.
‘Alcohol short-circuits important part of the brain’: Swedish newspaper representations of biomedical alcohol research

Abstract The media has a central role in communicating and constructing health knowledge, including communicating research findings related to alcohol consumption. However, research on news reporting about alcohol is still a relatively small field; in particular, there are few studies of the reporting of biomedical alcohol and drug research, despite the assumed increasing popularity of biomedical perspectives in public discourse in general. The present article addresses the representational ‘devices’ used in Swedish press reporting about biomedical alcohol research, drawing on qualitative thematic analysis of the topics, metaphors, and optimist versus critical frames used in presenting biomedical research findings. In general, the press discourse focuses on genetic factors related to alcohol problems, on the role of the brain and the reward system in addiction, and on medication for treating alcohol problems. Metaphors of ‘reconstruction’ and ‘reprograming’ of the reward system are used to describe how the brain’s function is altered in addiction, whereas metaphors of ‘undeserved reward’ and ‘shortcuts’ to pleasure are used to describe alcohol’s effects on the brain. The study indicates that aspects of the Swedish press discourse of biomedical alcohol research invite reductionism, but that this result could be understood from the point of view of both the social organization of reporting and the intersection of reporting, science, and everyday understandings rather than from the point of view of the news articles only. Moreover, some characteristics of the media portrayals leave room for interpretation, calling for research on the meanings ascribed to metaphors of addiction in everyday interaction.
Local Two-Dimensional Canonical Correlation Analysis

Recently, two-dimensional canonical correlation analysis (2DCCA) has been proposed for image analysis. 2DCCA seeks linear correlation based on images directly. It fails to identify nonlinear correlation between two sets of images. In this letter, we present a new manifold learning method called local 2DCCA (L2DCCA) to identify the local correlation. Different from 2DCCA in which images are globally equally treated, L2DCCA weights images differently according to their closeness. That is, the correlation is measured locally, which makes L2DCCA more accurate in finding correlative information. Computationally, L2DCCA is formulated as solving generalized eigenvalue equations tuned by Laplacian matrices. Like 2DCCA, the implementation of L2DCCA is straightforward. Experiments on FERET and UMIST face databases show the effectiveness of the proposed method.
SwiftLib: rapid degenerate-codon-library optimization through dynamic programming

Degenerate codon (DC) libraries efficiently address the experimental library-size limitations of directed evolution by focusing diversity toward the positions and toward the amino acids (AAs) that are most likely to generate hits; however, manually constructing DC libraries is challenging, error prone and time consuming. This paper provides a dynamic programming solution to the task of finding the best DCs while keeping the size of the library beneath some given limit, improving on the existing integer-linear programming formulation. It then extends the algorithm to consider multiple DCs at each position, a heretofore unsolved problem, while adhering to a constraint on the number of primers needed to synthesize the library. In the two library-design problems examined here, the use of multiple DCs produces libraries that very nearly cover the set of desired AAs while still staying within the experimental size limits. Surprisingly, the algorithm is able to find near-perfect libraries where the ratio of amino-acid sequences to nucleic-acid sequences approaches 1; it effectively side-steps the degeneracy of the genetic code. Our algorithm is freely available through our web server and solves most design problems in about a second.
HiPerData: An autonomous large-scale model building and management platform for big data analytics

Data mining is a difficult task that relies on an exploratory and analytic process of processing large quantities of data in order to discover meaningful patterns for valuable insights. The increasing heterogeneity and complexity of data requires expert knowledge on how to combine multiple data mining techniques to process and analyze the data in an effective and efficient way. This paper presents a distributed architecture, HiPerData, for automated data processing and mining using large-scale computational resource management, model building and selection, and predictive and inference analysis. We illustrate two data mining tasks in which we automate the data mining knowledge flow construction based on the use of standards that have been defined in both data mining and automated-planning communities.
Discharging arcs in commutation motors

Electromagnetic interference (EMI) in electric motors with mechanic commutators consists of two phenomena: commutating electromagnetic interference, just due to the changes in motor magnetic energy, and switching electromagnetic interference due to mechanical performance of the commutators as switches. The first phenomenon does not cause commutator wear, but the second causes both: the excessive EMI especially by voltage spikes and discharging arcs, which additionally could reignite drawn arcs, and further on, causing the severe commutator wear. This reignited drawn arc makes progress from the short one to the longer one, being more severe due to material transfer jagging edges and surfaces of commutator bars and brushes. Preventing the overvoltage spikes, and so far the ignition of the discharging arc results, besides reducing EMI, in avoidance of the drawn arc reignition and minimizing also the commutator wear. The paper gives also a method of determining a quenching capacitance value.
Identification of Salt Tolerance Genes in Rice from Microarray Data using SVM-RFE

Salt tolerance is an important agriculture character in Oryza sativa (rice). This paper proposed a framework of Support Vector Machine Recursive Feature Elimination (SVM-RFE) for analysing Oryza sativa microarray data from GEO. Through preliminary selection using t-test and iterative feature selection by SVM-RFE, we obtained 541 candidate genes. We analysed top 10 genes, which may play highly important roles in response to salt stress. The obtained results shed some light on the mechanism of salt tolerance in plants.
Clinical effectiveness of CBT-based self-help for symptoms of fatigue in multiple sclerosis

The second page of the manuscript must contain only the abstract, which should be of no more then 200 words and must be clearly written and comprehensive to readers before they have to read the paper. The abstract should be structured according to the following sub headings: Background, Objective, Methods, Results and Conclusion. Abbreviations should be avoided and reference citations are not permitted. Any manuscripts submitted without a structured abstract will be returned to the author immediately without peer review, thus delaying the evaluation process of the manuscript. Introduction The introduction should assume that the reader is knowledgeable in the field and be as brief as possible. Materials and Methods Methods that have been published in detail elsewhere should not be described in detail. Avoid unnecessary detailed descriptions of widely used techniques. SI Units should be used throughout the text. Reports of experiments involving patients and healthy volunteers must describe the steps taken to obtain consent and to maintain confidentiality. Experiments involving animals must conform to accepted ethical standards.
Primitive recursion on higher types

A revision of the basic concepts of type, function (called here operation), and relation is proposed. A simple generic method is presented for constructing operations and types as concrete finite structures parameterized by natural numbers. The method gives rise to build inductively so called Universe intended to contain all what can be effectively constructed. For any (higher order) type A the operation of type RecA : (N;(N → (A → A))) → (A → A) is constructed that corresponds to primitive recursion of Grzegorzyk [1] and Girard [2].
A review and classification of various VANET Intrusion Detection Systems

The use of wireless links renders a vehicular ad-hoc network (VANET) vulnerable to malicious attacks such as Denial of Service, blackhole attack, Sybil attack, selective forwarding and altering routing information. In wired networks the attacker needs to gain access to the physical media to make an attack. In wireless networks the scenario is much different, there are no firewalls and gateways in place hence attacks can take place from any location within radio coverage area. Each mobile node in ad-hoc network is an autonomous unit in itself free to move independently. This means a node with not adequate physical protection is very much susceptible to be compromised. It is difficult to track down a single compromised node in a large network, attacks stemming from a compromised node are far more detrimental and much harder to detect.
Optimal design of energy-efficient HetNets: joint precoding and load balancing

This paper considers the downlink of a heterogeneous network, where multiple base stations (BSs) can serve the users by non-coherent multiflow beamforming. We assume imperfect channel state information at both BSs and users. The objective is to jointly optimize the precoding, load balancing, and BS operation mode (active or sleep) for improving the energy efficiency of the network. The considered problem is to minimize the weighted total power consumption (both circuit power and dynamic transmit power), while satisfying per-user quality of service constraints and per-BS transmit power constraints. This problem is non-convex, but we prove that for each combination of BS modes, the considered problem has a hidden convexity structure. Thus, the global optimal solution is obtained by an exhaustive search over all possible BS mode combinations. Furthermore, by iterative convex approximations of the non-convex power consumption functions, a heuristic algorithm is proposed to obtain a local optimal solution with low complexity. Simulation results illustrate that our proposed algorithms significantly reduce the total power consumption, compared to the scheme where all BSs are continuously active. This implies that putting a BS into sleep mode by proper load balancing is an important solution for energy savings in heterogeneous networks.
On the efficient indexing of ordered multidimensional tuples

Multidimensional data structures are applied in many areas, e.g. data mining, indexing multimedia data and text documents, and so on. Therefore many index data structures and algorithms have been proposed. These data structures provide efficient processing of many types of queries like point and range queries. There are some applications where the range query result must be ordered. A typical case is the result with tuples sorted according to values in one dimension defined by the ORDER BY clause of an SQL statement. If we use a common multidimensional data structure, the result set is sorted after the range query is processed. Since the sort operation must often be processed on tuples stored in the secondary storage, an external sorting algorithm must be utilized. Therefore, this operation is time consuming especially for a large result set. In this paper, we introduce a new data structure, a variant of the R-tree, supporting a storage of ordered tuples. In this way, the range query result is ordered without an application of any time consuming sort operation. Our experiments show an improvement of this data structure compared to the R-tree.
Support for Software Assisted Speculative Execution

Computer architects strive to improve machine performance by xploiting parallelism, but control flow and data dependences limit available parallelism. Spec ulative execution enhances parallelism by selectively ignoring the constraints of control flow and dat a dependences, thereby executing instructions before it it known whether they are needed or correct. Softwa re assisted speculative execution is a form of this tack where the running program directs the hardware i n what instructions should be speculatively executed and how. This report identifies and characterized t h fundamental architectural, implementation, and compiler issues of software assisted speculative execution. These issues serve as the basis for describing, comparing and contrasting proposed architect ur s from the literature.
Static Resiliency vs Churn-Resistance Capability of DHT-Protocols

During the last few years, the topic of peer-to-peer networking (P2P hereafter) has gained significant attention from the research community. The focus has mainly been on the design, implementation and evaluation of systems based on Distributed Hash Tables (DHTs), as these structures have potential to become a general purpose substrate for distributed applications. Nonetheless, there are still dimensions of this technology that just have been barely studied and require further investigation before the full potential of P2P technologies could be achieved. A specific aspect of this networking technology requiring attention relates to the dynamic nature of P2P overlay networks. The composition of overlay networks is typically highly dynamic and heterogeneous in multiple ways, thereby making difficult the task of providing guarantees for the performance metrics of the system. More specifically, the continuous arrival and departure of new (or returning) nodes, commonly referred to as churn, is a problem that has not been extensively studied, and remains a major problem to be tackled. A particular aspect of churn is its impact on the overall performance of P2P networks. This paper addresses the impact of churn on P2P networking performance and presents a framework to evaluate different aspects of P2P overlay networks. The focus of this paper is on structured, DHT-based overlay networks. The main contributions of this paper are a new insight into the impact of churn on P2P overlay network performance, a set of new evaluation criteria that captures the impact of churn on P2P performance, and a detailed set of experiments which uses these evaluation criteria to analyze the performance of multiple DHT architectures under churn.
Implementation of EEG based control of remote robotic systems

The paper provides a novel approach to control the motion and orientation of a mobile robot using an encoded sequence of arm movements, obtained from the motor imagery indicated by electroencephalographic measurements. The importance of the proposed scheme lies in maintaining secrecy and privacy in control or management of remote robotic systems, as the signals liberated from the user's brain is not accessible to any third party even during the execution phase of the command and hence can find applications in the defense sector. For our demonstration we have successfully differentiated six classes of limb movements from the raw EEG data, encoded the classified signals and used this to control the movements of a Khepera mobile robot. Experiments have been undertaken to study the suitability of the scheme, and the results are promising.