Miracle-dz/UniFAR-FTUs huggingface dataset:
Oral Anti-CD3 Antibody Treatment Induces Regulatory T Cells and Inhibits the Development of Atherosclerosis in Mice

Background— Accumulating evidence suggests that several subsets of regulatory T cells that actively mediate immunologic tolerance play crucial roles in atherogenesis. Recently, orally administered anti-CD3 monoclonal antibody has been shown as an inducer of novel regulatory T cells expressing latency-associated peptide (LAP) on their surface, which potently prevents systemic autoimmunity. In the present study, we hypothesized that oral anti-CD3 antibody treatment may inhibit atherosclerosis in mice. Methods and Results— Six-week-old apolipoprotein E–deficient mice on a standard diet were orally given anti-CD3 antibody or control immunoglobulin G on 5 consecutive days, and atherosclerosis was assessed at age 16 weeks. Oral administration of anti-CD3 antibody significantly reduced atherosclerotic lesion formation and accumulations of macrophages and CD4+ T cells in the plaques compared with controls. We observed a significant increase in LAP+ cells and CD25+Foxp3+ cells in the CD4+ T-cell population in anti-CD3–treated mice, in association with increased production of the antiinflammatory cytokine transforming growth factor-β and suppressed T-helper type 1 and type 2 immune responses. Neutralization of transforming growth factor-β in vivo abrogated the preventive effect of oral anti-CD3 antibody. Conclusions— Our findings indicate the atheroprotective role of oral anti-CD3 antibody treatment in mice via induction of a regulatory T-cell response. These findings suggest that oral immune modulation may represent an attractive therapeutic approach to atherosclerosis.
Data Envelope Analysis Accounting for a Stochastic Component in the Data

Data Envelope Analysis, DEA, has become a standard tool in applied economics for estimating production frontiers and for assessing rms' technical e ciency. While the analysis is based on solid economic principles it does not take into account any stochastic component in the data. An alternative nonparametric method for estimating a production frontier and assessing technical e ciency which accounts for a stochastic component in the data is proposed here. The method uses nonparametric kernel regression to smooth the data, and then uses the results obtained from the regression to test the hypothesis that all rms are technically e cient. Unfortunately, this test is only powerful against a limited set of alternatives. An additional method is proposed to examine the relationship between the portion of variance accounted for by measurement error and the portion of ine cient rms in the sample. Research on this paper was done within the Sonderforschungsbereich 373 at Humboldt University Berlin and was printed using funds made available by the Deutsche Forschungsgemeinschaft.
Representing Uncertain Data: Uniqueness, Equivalence, Minimization, and Approximation

Many schemes have been proposed for representing uncertain data, where an uncertain database is defined as a set of {\em possible instances} for the database. Some important properties of representation schemes, such as {\em completeness} and {\em closure}, have already been considered. In this paper we identify several other interesting properties and obtain results for them with respect to a variety of different representation schemes. We first consider the {\em uniqueness} of representations, i.e., whether there is at most one representation for a set of possible instances in a particular representation scheme. For schemes that do not guarantee unique representations, we provide algorithms and complexity results for testing {\em equivalence} of representations. We also consider the problem of {\em minimizing} the size of the representation for a set of possible instances, obtaining a strong result for uncertainty schemes comprised of tuples and constraints: minimizing the number of tuples also minimizes the size of constraints. We show the NP-hardness of minimizing a representation, and study the more restricted problem of maintaining minimality when performing operations on the data. Next, we present several results on the problem of {\em approximating} an uncertain database when we wish to use a simple (incomplete) representation scheme. Finally, we give an interesting result relating closure and completeness for uncertain databases.
Shrink: a tool for failure diagnosis in IP networks

Faults in an IP network have various causes such as the failure of one or more routers at the IP layer, fiber-cuts, failure of physical elements at the optical layer, or extraneous causes like power outages. These faults are usually detected as failures of a set of dependent logical entities--the IP links affected by the failed components. We present Shrink, a tool for root cause analysis of network faults which, given a set of failed IP links, identifies the underlying cause of the faulty state. Shrink models the diagnosis problem as a Bayesian network. It has two main contributions. First, it effectively accounts for noisy measurement and inaccurate mapping between the IP and optical layers. Second, it has an efficient inference algorithm that finds the most likely failure causes in polynomial time and with bounded errors. We compare Shrink with two prior approaches and show that it substantially improves the performance.
A mechanism for brief glacial episodes in the Mesozoic greenhouse

[1] The Mesozoic, perhaps the longest period of warmth during the Phanerozoic Earth history, has been repeatedly affected by short-lived cold interludes lasting about one million years. While the origin of these cold snaps has been classically attributed to a temporary atmospheric CO2 drawdown, quantified mechanisms explaining these instabilities of the carbon cycle are still lacking. Based on a climate carbon cycle model, we show that the general demise of carbonate platforms accompanying these short-lived cold interludes is a powerful mechanism capable of generating a fast atmospheric CO2 decrease and a moderate sea level drop associated with ice sheet buildup. The temporary nature of the carbonate production decline explains the relative short time of these cold events but makes it possible to account for ice sheet waxing and waning.
Strategies of qualitative research

Kvalitativna istraživanja razvila su se u mnogim znanstvenim disciplinama u primjenjenim drustveno-humanisticim znanostima. Kvalitativne metode se ne mogu promatrati odvojeno od istraživackog procesa i predmeta istraživanja. Osnovna svrha ovog rada je pronalaženje jednog sveobuvatnog spoznajno-teorijskog pristupa koji bi proucavanju socijalnih fenomena prisao s multidimenzionalne perspektive razvijajuci sve tri poznate strategije: hemeneuticko-povijesnu, empirijsko-analiticku i akcijsko-kriticku.
Mining Minimal Constrained Flow Cycles from Complex Transaction Data

Transaction data in domains such as trading records from online financial or other markets, logistics delivery registers, and many others, are being accumulated at an increasing rate. In this type of data each transaction has a complex format, being usually associated with attributes such as time, numerical quantity, parties involved, and so on. Performing data mining on trace record data of complex transactions may enable the extraction of knowledge about implicit relationships which will benefit the community in different ways, for example by improving market efficiency and oversight, or detecting scheduling bottlenecks. However, the size of data sets of this type is usually enormous, and therefore in order to perform searching or mining techniques considerations of efficiency are often more important than correctness. In this paper we develop a framework to embed different methods to speed up search algorithms with the goal of detecting cycles in trace record data that fit a given constraint predicate on the amount of transaction quantities that can flow in a direction. The method is shown to improve significantly on a naive approach, and suggests a number of directions for further work.
Research on Fault Tree Based Complex Electronic Device Fault Diagnosis Expert System

Quick and accurate diagnosis and maintenance on complex electronic devices important issue that needs to be resolved urgently. Based on the construction of some type complex electronic device fault tree model and calculation methods of minimal cut sets importance degree and top event probability, the paper introduced fault tree into fault diagnosis expert system and solved key issues related to the system design. The constructed system can solve the problems of poor commonly usability, low degree of automation and complex operation that of original test devices, which provides effective solution for fault diagnosis of complex electronic devices.
SEVENTH FRAMEWORK PROGRAMME ICT Priority Deliverable D3.7: “Neural Coding of Objects and Attention Control”

Dissemination Level PU Public X PP Restricted to other programme participants (including the Commission Services) RE Restricted to a group specified by the consortium (including the Commission Services) CO Confidential, only for members of the consortium (including the Commission Services) In the monthly work plan for Y4 (developed immediately after the Y3 review meeting) it was decided to reallocate the research time of KCL in Work Package 3 (Vision) to a number of tasks that would provide temporal integration of 2D object detection (CVUT) and 3D pose estimation (FORTH) results across consecutive vision frames in order to increase the stability and speed of vision processing which, for both the 2D and 3D vision systems, was executed for each frame individually. The WP3 research resources for KCL were originally planned for a system implementing " neural coding of objects and attentional control " (Task 3.8 in the DARWIN DoW). However, the neural system originally proposed by then Prof. John Taylor was deemed too complex for the robotic hardware and duplicated research efforts in other parts of the vision system. Reallocating these resources to provide improved integration over time between object detection and pose estimation results was decided by the consortium to be the best use of research effort, and subsequently turned out to be in line with the recommendation made by the Project Officer (in the decision letter of July 2014) to drop objective S10 (attention-based cognitive architecture). Originally submitted after month 40 of the project (when the temporal integration system was in early development), we would like to make use of the opportunity to update D3.7 with the latest state of the work. In the following pages we describe the approach taken, and demonstrate how the addition of temporal integration (" tracking ") of vision results has improved both the stability and speed of the overall vision system. The approach also allowed to introduce " functional " aspects of attention, such as managed allocation of computational resources, dealing with robot-induced occlusion of the scene, and integrating information about the task being executed through context-dependent information arriving from other parts of the cognitive system.
Management and Education of the Risk of Insider Threat (MERIT): Mitigating the Risk of Sabotage to Employers’ Information, Systems, or Networks

Abstract : The Insider Threat Study, conducted by the U.S. Secret Service and Carnegie Mellon University s Software Engineering Institute CERT Program, analyzed insider cyber crimes across U.S. critical infrastructure sectors. The study indicates that management decisions related to organizational and employee performance sometimes yield unintended consequences that increase risk of insider attack. The problem is exacerbated by a lack of tools for understanding insider threat, analyzing risk mitigation alternatives, and communicating results. The goal of Carnegie Mellon University's Management and Education of the Risk of Insider Threat (MERIT) project is to develop such tools. MERIT uses system dynamics to model and analyze insider threats and produce interactive learning environments. These tools can be used by policy makers, security officers, information technology and human resource personnel, and management. The tools help these users to understand the problem and assess risk from insiders based on simulations of policies, and on cultural, technical, and procedural factors. This technical note describes the MERIT insider threat model and simulation results.
User-environment based navigation algorithm for an omnidirectional passive walking aid system

This work introduces a new indoor navigation method for an omnidirectional passive walking aid system, called Omni RT Walker-II. Omni RT Walker II is the second version of a newly manufactured walking aid system with an omnidirectional platform which is controlled through merely control of MR rotary brakes and excludes actuators, aiming at higher safety and better functionality and maneuverability of the system. The proposed navigation method is unique in that it uses both environment information and human characteristics in order to provide its user with further freedom in handling the walker, and avoids abrupt movements of the system. The new method can assist the users with gait disorder and avoid turning over or falling while navigating the user to a destination. Experimental results are presented to evaluate the accuracy and quality of navigation.
General branching processes conditioned on extinction are still branching processes

It is well known that a simple, supercritical Bienayme-Galton-Watson process turns into a subcritical such process, if conditioned to die out. We prove that the corresponding holds true for general, multi-type branching, where child-bearing may occur at different ages, life span may depend upon reproduction, and the whole course of events is thus affected by conditioning upon extinction.
Coronary Artery Size and Dilating Capacity in Ultradistance Runners

Background. Increases in coronary artery size and dilating capacity have been observed in some animals after endurance training, and at autopsy, active men appear to have enlarged epicardial coronary arteries. This cross‐sectional study was designed to test the hypothesis that highly trained endurance runners have larger epicardial coronary arteries and greater dilating capacity than inactive men. Methods and Results. The subjects, ages 39‐66 years, included 11 male volunteers who had participated in ultradistance running during the past 2 years and 11 physically inactive men who had been referred for arteriography but had no visible coronary artery disease. The internal diameter of the proximal segments of each major epicardial coronary artery was measured before and after nitroglycerin administration using a computer‐based quantitative arteriographic analysis system. Measurements also included maximal oxygen uptake, plasma lipoprotein concentrations, body composition, and cardiac mass by echocardiography. Before nitroglycerin, the sum of the cross‐sectional areas for the proximal right, left anterior descending, and circumflex arteries was not different for the runners and the inactive men: 22.7±4.79 versus 21.0±7.97 mm2 (p=0.57), respectively. However, the increase in the sum of the cross‐sectional area for the proximal right, left anterior descending, and circumflex arteries in response to nitroglycerin was greater for the runners (13.20±4.76 versus 6.00±3.02 mm2; p=0.002). Left ventricular mass index (152±21 versus 116±41 g/m2; p<0.05) but not left ventricular mass (284±40 versus 246±91 g; p=0.22) was significantly greater for the runners. Among the runners, dilating capacity was positively correlated with aerobic capacity and negatively related to adiposity, resting heart rate, and plasma lipoprotein concentrations. Conclusions. Highly trained, middle‐aged endurance runners demonstrated a significantly greater dilating capacity of their epicardial coronary arteries in response to nitroglycerin compared with inactive men. The causes of this greater dilating capacity and its clinical significance need to be determined. (Circulation 1993;87:1076‐1082)
Conflict Detection for Arbitrary Constraint Propagation Algorithms

Existing conflict detection methods for CSP’s such as [de Kleer, 1989; Ginsberg, 1993 ] cannot make use of powerful propagation which makes them unusable for complex real-world problems. On the other hand, powerful constraint propagation methods lack the ability to extract dependencies or conflicts, which makes them unusable for many advanced AI reasoning methods that require conflicts, as well as for interactive applications that require explanations. In this paper, we present a non-intrusive conflict detection algorithm called QUICKXPLAIN that tackles those problems. It can be applied to any propagation or inference algorithm as powerful as it may be. Our algorithm improves the efficiency of direct non-intrusive conflict detectors by recursively partitioning the problem into subproblems of half the size and by immediately skipping those subproblems that do not contain an element of the conflict. Q UICKXPLAIN is used as explanation component of an advanced industrial constraint-based configuration tool.
Software Protection Mechanisms for Dependable Systems

We expect that in future commodity hardware will be used in safety critical applications. But the used commodity microprocessors will become less reliable because of decreasing feature size and reduced power supply. Thus software-implemented approaches to deal with unreliable hardware will be required. As one basic step to software- implemented hardware-fault tolerance (SIHFT) we aim at providing failure virtualization by turning arbitrary value failures caused by erroneous execution into crash failures which are easier to handle. Existing SIHFT approaches either are not broadly applicable or lack the ability to reliably deal with permanent hardware faults. In contrast, Forin [7] introduced the Vital Coded Microprocessor which reliably detects transient and permanent hardware errors but is not applicable to arbitrary programs and requires special hardware. We discuss different approaches to generalize Forin's approach and make it applicable to modern infrastructures.
Scalable Bayesian Modelling of Paired Symbols

We present a novel, scalable and Bayesian approach to modelling the occurrence of pairs of symbols (i,j) drawn from a large vocabulary. Observed pairs are assumed to be generated by a simple popularity based selection process followed by censoring using a preference function. By basing inference on the well-founded principle of variational bounding, and using new site-independent bounds, we show how a scalable inference procedure can be obtained for large data sets. State of the art results are presented on real-world movie viewing data.
A Network-of-Networks Model for Electrical Infrastructure Networks

Modeling power transmission networks is an important area of research with applications such as vulnerability analysis, study of cascading failures, and location of measurement devices. Graph-theoretic approaches have been widely used to solve these problems, but are subject to several limitations. One of the limitations is the ability to model a heterogeneous system in a consistent manner using the standard graph-theoretic formulation. In this paper, we propose a {\em network-of-networks} approach for modeling power transmission networks in order to explicitly incorporate heterogeneity in the model. This model distinguishes between different components of the network that operate at different voltage ratings, and also captures the intra and inter-network connectivity patterns. By building the graph in this fashion we present a novel, and fundamentally different, perspective of power transmission networks. Consequently, this novel approach will have a significant impact on the graph-theoretic modeling of power grids that we believe will lead to a better understanding of transmission networks.
Honeyfiles: deceptive files for intrusion detection

This paper introduces an intrusion-detection device named honeyfiles. Honeyfiles are bait files intended for hackers to access. The files reside on a file server, and the server sends an alarm when a honey file is accessed. For example, a honeyfile named "passwords.txt" would be enticing to most hackers. The file server's end-users create honeyfiles, and the end-users receive the honeyfile's alarms. Honeyfiles can increase a network's internal security without adversely affecting normal operations. The honeyfile system was tested by deploying it on a honeynet, where hackers' use of honeyfiles was observed. The use of honeynets to test a computer security device is also discussed. This form of testing is a useful way of finding the faulty and overlooked assumptions made by the device's developers.
Syllable-based Language Models in Speech Recognition for English Spoken Document Retrieval

The spoken content of audio/visual collections such as TV or radio archives is an information resource of enormous potential. The challenge is to develop methods that will make it possible to browse or search these collections. The experimental results presented in this paper demonstrate that syllable-level transcripts provide an important supple- ment to conventional word-level transcripts for the task of unlimited vocabulary American English spoken document retrieval. Recognition is performed with syllable language models with vocabulary sizes 20k, 10k, 5k, 1k, and 500. The syllable recognition rates of the 10k and 5k models are comparable to that achieved by a baseline 100k word-based language model. A simple retrieval experiment involving a fuzzy full text search supplies proof-of-concept that syllable-based transcripts make it possible to retrieve spoken documents that contain query words not included in the 100k vocabulary of the word-based language model.
Research on resistor array non-uniformity correction with neural network

In order to make the imagery respond just as the real-world scenes do, nonuniformity correction of resistor array is necessary. Most of all, this paper proposed a new neural network algorithm for nonuniformity correction. It has simple neural network model, at the same time, not only can well compensated nonuniformity, also can fit the characteristic curves. In addition, we adopted piecewise linear method to approach the correspondence curve between the actual input voltage and the theoretical input voltage for the first time. This approach greatly reduces the storage space and makes the algorithm easily realized in hardware. Theoretical analysis of the improved neural network algorithm, the algorithm's implementation steps, piecewise linear approach of the corresponding curve, simulation results and considerations are given in the paper.