Miracle-dz/UniFAR-FTUs huggingface dataset:
CNS-Derived Interleukin-4 Is Essential for the Regulation of Autoimmune Inflammation and Induces a State of Alternative Activation in Microglial Cells

Regulation of inflammation in the CNS is essential to prevent irreversible cellular damage that can occur in neurodegenerative diseases such as multiple sclerosis (MS). We investigated the role of interleukin-4 (IL-4) in regulating CNS inflammation using the animal model of MS, experimental autoimmune encephalomyelitis (EAE). We found that CNS-derived IL-4 was a critical regulator because mice with a deficiency in IL-4 production in the CNS, but not the periphery, had exacerbated EAE associated with a significant increase in the absolute number of infiltrating inflammatory cells. We also found that CNS-resident microglial cells in both the resting and activated state produced the protein Ym1, which is a marker of alternatively activated macrophages (aaMΦs), in an IL-4-dependent manner. This aaMΦ phenotype extended to the lack of nitric oxide (NO) production by activated microglial cells, which is a marker of classically activated macrophages. We also show that IL-4 induced the expression of Ym1 in peripheral infiltrating macrophages, which also produce NO. Thus, macrophages that migrate into the CNS exhibit a dual phenotype. These data indicate that IL-4 production in the CNS is essential for controlling autoimmune inflammation by inducing a microglial cell aaMΦ phenotype. Macrophages that have undergone alternative activation have been shown to be important in tissue repair; thus, our results suggest a new role for microglial cells in the regulation of inflammation in the CNS.
A Novel Quantum Signature Scheme with Quantum LDPC Codes

This paper presents a novel quantum signature scheme by using quantum quasi-cyclic low density parity check (QC-LDPC) codes and quantum hash function. We construct quantum public keys by using quantum QC-LDPC Codes. Decoding general linear codes is NP-complete problem. The security of our scheme relies on the fact that NP-complete problem can not be solved on quantum Turing machines. Based on this public-key, this paper also gives a numerical simulation and proves the scheme security.
Title : Retroviral origins of the Caenorhabditis elegans orphan gene F 58 H 7 . 5

This work describes the results of the genome-scale analysis of endogenous retrovirus insertions in two C. elegans isolates: the prototype N2 (Bristol) and CB4856 (Hawaii). In total thirteen, identification of potentially replication competent, endogenous retroviral elements is described. Ten elements were identified as conserved between N2 and CB4856 by the reciprocal match of paired LTRs. The description focuses on the particular endogenous retrovirus insertion wich is identified on the proximal arm of the chromosome IV (located at positions IV: 912,948 – 921,658 and IV: 899,767 – 908,485 of the N2 and CB4856 respectively). In both isolates the inserted provirus is flanked by the predicted long terminal repeats (LTR)s of the length of 415 bp and of identical sequence. Provided the absolute LTR sequence identity this particular provirus represents insertion acquired prior to split from the common ancestor, suggesting this insertion event is evolutionary recent. The identified insertion of the endogenous retrovirus embeds the orphan gene F58H7.5, specific to C. elegans lineage. This unprecedented example establishes that in the evolutionary past C. elegans, had acquired the gene of the retroviral origins presumably via mechanisms involving the RNA intermediate. CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi. org/10.1101/073510 doi: bioRxiv preprint first posted online Sep. 5, 2016;
Robustness of the tuning functions adaptive backstepping design for linear systems

A new approach to adaptive control of linear systems which abandons the certainty-equivalence principle has been recently developed in the ideal case, that is, in the absence of unmodeled dynamics and bounded disturbances. In this paper the authors address the question of robustness and asymptotic performance of this adaptive scheme. The authors show that using a switching /spl sigma/-modification in the parameter update law, the closed loop system states are uniformly ultimately bounded with a region of attraction inversely proportional to the "size" of the unmodeled dynamics. The tracking error is shown to be proportional to the size of the uncertainties.
A comparison of parallelization techniques for irregular reductions

A large class of scientific applications are comprised of irregular reductions on large data sets. On shared-memory multiprocessors these reductions are typically parallelized by computing partial results into replicated buffers, then combining the values into shared data using synchronization. Recently, a number of alternative techniques have been developed based on selective privatization, local writes, and synchronized writes. In this paper, we present a more efficient version of the local write algorithm which is 56% faster on average. We then experimentally compare the performance of each technique using a number of representative kernels. Results show speedups vary greatly depending on application characteristics such as connectivity, locality, and adaptivity. In general, we find the local write technique provides the best performance, particularly when applications display good locality.
VP35 Knockdown Inhibits Ebola Virus Amplification and Protects against Lethal Infection in Mice

ABSTRACT Phosphorodiamidate morpholino oligomers (PMO) are a class of uncharged single-stranded DNA analogs modified such that each subunit includes a phosphorodiamidate linkage and morpholine ring. PMO antisense agents have been reported to effectively interfere with the replication of several positive-strand RNA viruses in cell culture. The filoviruses, Marburg virus and Ebola virus (EBOV), are negative-strand RNA viruses that cause up to 90% lethality in human outbreaks. There is currently no commercially available vaccine or efficacious therapeutic for any filovirus. In this study, PMO conjugated to arginine-rich cell-penetrating peptide (P-PMO) and nonconjugated PMO were assayed for the ability to inhibit EBOV infection in cell culture and in a mouse model of lethal EBOV infection. A 22-mer P-PMO designed to base pair with the translation start site region of EBOV VP35 positive-sense RNA generated sequence-specific and time- and dose-dependent inhibition of EBOV amplification in cell culture. The same oligomer provided complete protection to mice when administered before or after an otherwise lethal infection of EBOV. A corresponding nonconjugated PMO, as well as nonconjugated truncated versions of 16 and 19 base residues, provided length-dependent protection to mice when administered prophylactically. Together, these data suggest that antisense PMO and P-PMO have the potential to control EBOV infection and are promising therapeutic candidates.
Vibrations, quanta and biology

Abstract Quantum biology is an emerging field of research that concerns itself with the experimental and theoretical exploration of non-trivial quantum phenomena in biological systems. In this tutorial overview we aim to bring out fundamental assumptions and questions in the field, identify basic design principles and develop a key underlying theme – the dynamics of quantum dynamical networks in the presence of an environment and the fruitful interplay that the two may enter. At the hand of three biological phenomena whose understanding is held to require quantum mechanical processes, namely excitation and charge transfer in photosynthetic complexes, magneto-reception in birds and the olfactory sense, we demonstrate that this underlying theme encompasses them all, thus suggesting its wider relevance as an archetypical framework for quantum biology.
Endowing e-Learning Systems with Emotion Awareness

The consideration of emotion in learning has been in the research agenda for quite long time and literature is offering a variety of studies that are evaluating the role of emotions in various learning contexts (class, test and exams, during studying at home, etc). In the current paper we first appose a critical review of prominent emotion taxonomies, affect detection and feedback strategies and then we propose the design of a system that is endowed with students' emotion aware capabilities. An emotion taxonomy that originates from the basic emotions of fear and affection is put forward. Social-Emotional Learning Theory and Practice can be exploited to feed the necessary theoretical background that is lacking of empirical data.
Testing Temporal Correctness of Real-Time Systems by Means of Genetic Algorithms

The development of real-time systems is an essential industrial activity. Dynamic testing is the most important analytical method to assure the quality of real-time systems. It is the only method that examines the run-time behavior, based on an execution in the application environment. An investigation of existing software test methods shows that they mostly concentrate on testing for functional correctness. They are not specialized in the examination of temporal correctness that is essential to real-time systems. Therefore, existing test procedures must be supplemented by new methods that concentrate on determining whether the system violates its specified timing constraints. In general, a violation means that outputs are produced too early or their computation takes too long. The task of the tester is to find the inputs with the longest or shortest execution times to check whether they produce a temporal error. If the search for such inputs is interpreted as a problem of optimization, genetic algorithms can be used to find the inputs with the longest or shortest execution times automatically. The fitness function is the measured execution time. Experiments using genetic algorithms on a number of programs with up to 1511 LOC and 843 input parameters have successfully identified new longer and shorter execution times than those that had been found using random testing and systematic testing. Genetic algorithms therefore seem to be well-suited for checking the temporal correctness of real-time software. A combination of genetic optimization with systematic testing offers further opportunities to improve the test quality and could lead to an effective test strategy for real-time systems.
Distributed Intrusion Detection Framework based on Autonomous and Mobile Agents

Implementation of intrusion detection systems with agent technology is one of the new paradigms for intrusion detection for computer systems. In this paper, we propose a distributed intrusion detection framework based on autonomous and mobile agents. In this framework, the mobile agent platform "aglets" is utilized. The system has five types of agents: administrator agents, analyzer agents, connection agents, crisis agents, and update behavior agents. These agents interact with each other to perform the detection task. We also discuss the implementation issues about our system
Influence of voltage vectors of a NPC inverter on torque and flux variations of a DTC drive considering different load and speed conditions

Direct torque control (DTC) is one of the most effective vector control methods proposed for high performance drives of a wide variety of industrial applications. This control method becomes more attractive when applied on the Neutral Point Clamped (NPC) Inverter driven drives. While exploring accurate analytical equations of torque and flux variations, this paper investigates analytically the affecting characteristic of voltage vectors of a NPC converter on variations of stator flux and electromagnetic torque (decreasing or increasing) of medium voltage induction motor drives. The analytically obtained results show that the affecting characteristic of some voltage vectors depends not only on the flux sector in which the stator flux vector is located but also on the exact position of flux vector inside that sector. Besides the load and speed conditions of a machine can change the affecting characteristic of voltage vectors undesirably. The paper studies application of DTC method in NPC inverter driven induction motors and considers different load and speed conditions. It proposes a set of appropriate voltage vectors for accurate control of torque and flux variations considering degrees of freedom in voltage vector selection provided by NPC Inverter.
Reflections on remote reflection

The Java programming language provides both reflection and remote method invocation: reflection allows a program to inspect itself and its runtime environment, remote method invocation allows methods to be invoked transparently across a network. Unfortunately, the standard Java implementations of reflection and remote method invocation are incompatible: programmers cannot reflect on a remote application. We describe how Java systems can be extended to support Remote Reflection transparently by extending the standard Java API. Remote reflection can support remote debuggers, performance monitors, programming environments, application component servers such as Enterprise JavaBeans, and any other Java system that can be distributed across a network.
Adoption of Big Data Analytics in Healthcare: The Efficiency and Privacy

Big data analytics (BDA) has shown distinctive advantages on improving healthcare outcomes and reducing healthcare cost. While it also increases consumer’s privacy risk. We thus focus on the question that whether health IT providers should adopt BDA to increase healthcare efficiency in the presence of privacy concerns. We focus on the healthcare wearable device market due to its natural advantages and popularity in healthcare field. Since the consumers has various preferences on the products (horizontal differentiation) with different quality levels (vertical differentiation), we adopt a two-dimensional product differentiation model to investigate the effects of BDA’s efficiency-privacy tradeoff on the competition. Our results demonstrate that health IT providers should adopt BDA technology when their efficiency-privacy tradeoffs are large. Besides, when BDA cost on per unit benefit is small, or the investment has more unit benefit for itself than the rival, health IT providers also should adopt BDA. Our findings provide insights to business managers on how to optimize strategies of BDA adoption. Social planners are also guided to conduct better policies to improve health service quality by promoting BDA adoption in healthcare sector.
The Application of Hierarchical Tag Cluster in Multimedia Search

Generated by socialized identification on web pages, pictures, videos and etc by the mass Internet users, tag is an unique meta data comprised of words on Internet. As a new data resource, it offers a new way to produce, manage and obtain Internet information. This paper will try to explore and utilize the characteristics of tag, start from hierarchical tag relation definition, integrate the knowledge of informatics and probability theory, and provide a easy and quick picture search method with relatively accurate data for users.
Design and implementation of a content filtering firewall

A firewall is a system for enforcing access control policy between two networks and is one of the most important measures to protect against network attacks. Firewalls traditionally protect the internal network from outside threats. But there has been increasing need for preventing the misuses of the network by the internal users which most previous firewalls overlook. In this paper, we propose a method of adding content filtering functionality to the firewall and describe its implementation. We also show a new attack that combines JAVA Applet and XML to get around the content filtering firewall, hence showing the need for clear usage policy for software and systems.
A Copy Number Variant on Chromosome 20q13.3 Implicated in Thinness and Severe Obesity

Background/Objectives. To identify copy number variants (CNVs) which are associated with body mass index (BMI). Subjects/Methods. CNVs were identified using array comparative genomic hybridization (aCGH) on members of pedigrees ascertained through severely obese (BMI ≥ 35 kg/m2) sib pairs (86 pedigrees) and thin (BMI ≤ 23 kg/m2) probands (3 pedigrees). Association was inferred through pleiotropy of BMI with CNV log⁡2 intensity ratio. Results. A 77-kilobase CNV on chromosome 20q13.3, confirmed by real-time qPCR, exhibited deletions in the obese subjects and duplications in the thin subjects (P = 2.2 × 10−6). Further support for the presence of a deletion derived from inference by likelihood analysis of null alleles for SNPs residing in the region. Conclusions. One or more of 7 genes residing in a chromosome 20q13.3 CNV region appears to influence BMI. The strongest candidate is ARFRP1, which affects glucose metabolism in mice.
DESRM: a disease extraction system for real-time monitoring

In this paper, we proposed a method that combines semantic rules and machine learning to extract infectious disease events in Vietnamese electronic news for a real-time monitoring system of spreading status. Our method includes two important steps: detecting disease events from unstructured text and extracting information of the disease event. The detection phrase uses semantic rules and machine learning to detect a disease event; in the later step, named entity recognition NER, rules, and dictionaries are utilised to capture the events information. The performance of the two steps has F-score of 77.33% 2.36% better than the baseline's and 91.89% 4.31% better than the baseline's correspondingly. The promising results from the comparisons showed that our method is suitable for extracting disease events in Vietnamese text.
A new method to reduce overestimation of thresholds with observational network data

Networks of interdependent nodes support phenomena such as epidemics, product adoption, cascading failure, ecosystem collapse, congestion, and bandwagon effects. We consider the problem of using observational data to estimate the sensitivity of individual nodes to the activation of their network neighbors. We prove that---in the case of binary activation decisions---activation thresholds are impossible to correctly measure for some nodes in virtually all contagion processes on complex networks. This result holds even when each step of the process is observed. Measurement error always produces an overestimate of a node's true activation threshold. We develop a condition for determining which node thresholds are correctly measured and demonstrate that modeling activation thresholds as a function of node-level factors reduces the error compared to existing approaches.
Online Route Prediction for Automotive Applications

An information and communication technology infrastructure is rapidly emerging that enables the delivery of location-based services to vast numbers of mobile users. Services will benefit from being aware of not only the user's location, but also the user's current destination and route towards the destination. This paper describes a component that enables the use of geocontext. Using GPS data, the component gathers a driver's routes and associates them with usage meta-data. Other services may then provide the component with a driver ID, the time of the day, and a location, in return obtaining the likely routes for the driver. For the covering abstract see ITRD E134653.
High-SNR Analytical Performance of Spatial Multiplexing MIMO Systems With CSI

In this paper, we investigate the average and outage performance of spatial multiplexing multiple-input multiple-output (MIMO) systems with channel state information at both sides of the link. Such systems result, for example, from exploiting the channel eigenmodes in multiantenna systems. Due to the complexity of obtaining the exact expression for the average bit error rate (BER) and the outage probability, we derive approximations in the high signal-to-noise ratio (SNR) regime assuming an uncorrelated Rayleigh flat-fading channel. More exactly, capitalizing on previous work by Wang and Giannakis, the average BER and outage probability versus SNR curves of spatial multiplexing MIMO systems are characterized in terms of two key parameters: the array gain and the diversity gain. Finally, these results are applied to analyze the performance of a variety of linear MIMO transceiver designs available in the literature.
Uncertainty Quantification in Dynamic Simulations of Large-scale Power System Models using the High-Order Probabilistic Collocation Method on Sparse Grids

This paper proposes a probabilistic collocation method (PCM) to quantify the uncertainties with dynamic simulations in power systems. The appraoch was tested on a single-machine-infinite-bus system and the over 15,000 -bus Western Electricity Coordinating Council (WECC) system. Comparing to classic Monte-Carlo (MC) method, the proposed PCM applies the Smolyak algorithm to reduce the number of simulations that have to be performed. Therefore, the computational cost can be greatly reduced using PCM. The algorithm and procedures are described in the paper. Comparison was made with MC method on the single machine as well as the WECC system. The simulation results shows that using PCM only a small number of sparse grid points need to be sampled even when dealing with systems with a relatively large number of uncertain parameters. PCM is, therefore, computationally more efficient than MC method.
The critical period and preservation of emerged vowel systems

The critical period for language acquisition is often assumed to be nothing more than a by-product of development. However, evolutionary computer simulations show that it can be explained as a result of biological evolution (Hurford, 1991). In the present study the aim is not to explain how and why this age sensitivity evolved but to investigate the consequences of this individual-level disadvantage on a culturally evolving vowel system as a whole. Using two different agent-based computer models it will be argued that a difference in learning ability between children and adults can improve the stabilization and preservation of complexity of vowel systems in a changing population. The first model is a re-implementation of the one described by de Boer and Vogt (1999), which consists of a population of agents that interact through imitation games using realistic mechanisms for production and perception of vowels. The agents have a vowel memory in which they store learned prototypes of vowels and in response to their interactions with other agents they update their memory and learn new sounds. Analogous to the results of de Boer and Vogt (1999) the model shows that a population in which new members are born and old members die, a critical period stabilizes vowel systems over the generations. In this case the adults provide the learners with a stable target facilitating the acquisition process. Figure 1 shows the difference in the changes of the vowel system after transmission in a population with or without age structure. The second model is a variation on the first which integrates the linguistic paradigm of Optimality Theory (OT). In this version of the model, the agents imitate each other using their own bidirectional stochastic OT grammar (Boersma & Hamann, 2008) consisting of a ranked set of articulatory and cue constraints. To produce or perceive a speech signal, a set of possible candidate forms is evaluated by the grammar. The candidate that violates the fewest highly ranked constraints is selected. In response to their interactions with other agents they learn by adjusting (a) No age structure (b) Age structure Figure 1. Emerged vowel systems in the first model. Initial vowel system in grey. the ranking values in their grammar. This new approach replicates the results of the stabilizing effect on the emerged vowel systems. The results suggest that the critical period might be more than just an unfortunate consequence of development since its influence …