Miracle-dz/UniFAR-FTUs huggingface dataset:
Motion generation and adaptive control method of automated guided vehicles in road following

Dynamics of automated guided vehicles (AGVs) are described by a nonlinear nonholonomic model with two inputs: the rear axle torque and the steering angle torque. This model uses integrated longitudinal and lateral behavior. The first part of this paper is concerned with motion generation, taking into account kinodynamics and motor's constraints. Usual kinematics constraints are not always sufficient to provide feasible trajectories; thus, we focus on velocity limitation and the motor's current and slew rate constraints. Optimal velocity is determined for AGVs along a specified path with a known curvature. The main result concerns the realistic situation when the parameters of the model describing the movement of the vehicle are not well known. A nonlinear strategy is proposed to ensure control of the vehicle even if the knowledge of the AGV's constant parameters is not perfect. The proof of the main result is based on the Lyapunov concept and the proposed results are illustrated by simulations and some comments.
Detection of Mass Increase in a Fan Impeller With a Frequency Converter

Fan systems are often responsible for the ventilation of contaminated air, such as exhaust gases. Contaminants can build up on the fan impeller eventually causing a mechanical imbalance, which may lead to the fan breakdown and shutdown of production processes. Usually, the contamination buildup can be detected by visual inspection or from increased vibrations caused by the imbalance on the fan impeller. If the contamination buildup could be detected before the imbalance occurs, the unscheduled maintenance or even the failure of the fan system could be avoided. In this paper, a novel method is presented that can be used to detect the contamination buildup on the fan impeller. The method uses the capability of the frequency converter controlling the fan motor to estimate the rotational speed of the motor and the capability to control the motor torque. The presented method is validated by laboratory measurements.
Functional parcellation of memory related brain networks by spectral clustering of EEG data

In this study, we investigate the clustering information of alpha band brain networks during memory load task. For this purpose, short time memory task which includes memory load varieties is implemented to the subjects. To calculate mutual information, time and frequency information is both taken into consideration due to Cohen class time-frequency distribution (TFD) formulation. Cohen class based mutual information helps us to integrate adjacency matrices based on the similarity information of individual electrode pairs. In addition, essential frequency bins are selected from the TFD with respect to the default alpha frequency (8 - 12Hz) intervals. Moreover, graph based spectral clustering algorithm is used to parcellate memory related circuits on the brain. From the calculated adjacency matrices, the N-cut algorithm is used for node wise clustering between nodes. After node wise clustering information, subject wise clustering is applied with respect to the similarities of node information over all subjects.
Deregulation of DNA Damage Signal Transduction by Herpesvirus Latency-Associated M2

ABSTRACT Infected cells recognize viral replication as a DNA damage stress and elicit a DNA damage response that ultimately induces apoptosis as part of host immune surveillance. Here, we demonstrate a novel mechanism where the murine gamma herpesvirus 68 (γHV68) latency-associated, anti-interferon M2 protein inhibits DNA damage-induced apoptosis by interacting with the DDB1/COP9/cullin repair complex and the ATM DNA damage signal transducer. M2 expression constitutively induced DDB1 nuclear localization and ATM kinase activation in the absence of DNA damage. Activated ATM subsequently induced Chk activation and p53 phosphorylation and stabilization without eliciting H2AX phosphorylation and MRN recruitment to foci upon DNA damage. Consequently, M2 expression inhibited DNA repair, rendered cells resistant to DNA damage-induced apoptosis, and induced a G1 cell cycle arrest. Our results suggest that γHV68 M2 blocks apoptosis-mediated intracellular innate immunity, which might ultimately contribute to its role in latent infection.
Learning to Perceive the World as Probabilistic or Deterministic via Interaction With Others: A Neuro-Robotics Experiment

We suggest that different behavior generation schemes, such as sensory reflex behavior and intentional proactive behavior, can be developed by a newly proposed dynamic neural network model, named stochastic multiple timescale recurrent neural network (S-MTRNN). The model learns to predict subsequent sensory inputs, generating both their means and their uncertainty levels in terms of variance (or inverse precision) by utilizing its multiple timescale property. This model was employed in robotics learning experiments in which one robot controlled by the S-MTRNN was required to interact with another robot under the condition of uncertainty about the other’s behavior. The experimental results show that self-organized and sensory reflex behavior—based on probabilistic prediction—emerges when learning proceeds without a precise specification of initial conditions. In contrast, intentional proactive behavior with deterministic predictions emerges when precise initial conditions are available. The results also showed that, in situations where unanticipated behavior of the other robot was perceived, the behavioral context was revised adequately by adaptation of the internal neural dynamics to respond to sensory inputs during sensory reflex behavior generation. On the other hand, during intentional proactive behavior generation, an error regression scheme by which the internal neural activity was modified in the direction of minimizing prediction errors was needed for adequately revising the behavioral context. These results indicate that two different ways of treating uncertainty about perceptual events in learning, namely, probabilistic modeling and deterministic modeling, contribute to the development of different dynamic neuronal structures governing the two types of behavior generation schemes.
SWEEP: evaluating computer system energy efficiency using synthetic workloads

Energy efficiency is a key design concern in contemporary processor and system design, in the embedded domain as well as in the enterprise domain. The focus on energy efficiency has led to a number of power benchmarking methods recently. For example, EEMBC released EnergyBench and SPEC released SPECpower to quantify a system's energy efficiency; also academics have proposed power benchmarks, such as JouleSort. A major limitation for each of these proposals is that they are tied to a specific benchmark, and hence, they provide limited insight with respect to why one system may be more energy-efficient than another. This paper proposes SWEEP, Synthetic Workloads for Energy Efficiency and Performance evaluation, a framework for generating synthetic workloads with specific behavioral characteristics. We employ SWEEP to generate a wide range of synthetic workloads while varying the instruction mix, ILP, memory access patterns, and I/O-intensiveness; and we use SWEEP to evaluate the energy efficiency of commercial computer systems across the workload space and learn about how the energy efficiency of a computer system is tied to its workload's characteristics. This paper also presents the Energy-Delay Diagram (EDD), a novel method for visualizing energy efficiency. The EDD clearly illustrates the energy versus performance trade-off, and provides more intuitive insight than the traditionally used EDP and ED2P metrics.
Estrogen Protects Against Intracranial Aneurysm Rupture in Ovariectomized Mice

Clinical observations suggest that postmenopausal women have a higher incidence of aneurysmal rupture than premenopausal women. We hypothesize that a relative deficiency in estrogen may increase the risks of aneurysmal growth and subarachnoid hemorrhage in postmenopausal women. We assessed the effects of estrogen and selective estrogen receptor subtype agonists on the development of aneurysmal rupture in ovariectomized female mice. We used an intracranial aneurysm mouse model that recapitulates the key features of human intracranial aneurysms, including spontaneous rupture. Ten- to 12-week-old ovariectomized female mice received treatment with estrogen, nonselective estrogen receptor antagonist, estrogen receptor-&agr; agonist, or estrogen receptor-&bgr; agonist starting 6 days after aneurysm induction so that the treatments affected the development of aneurysmal rupture without affecting aneurysmal formation. Estrogen significantly reduced the incidence of ruptured aneurysms and rupture rates in ovariectomized mice. Nonselective estrogen receptor antagonist abolished the protective effect of estrogen. Although estrogen receptor-&agr; agonist did not affect the incidence of ruptured aneurysms or rupture rates, estrogen receptor-&bgr; agonist prevented aneurysmal rupture without affecting the formation of aneurysms. The protective role of estrogen receptor-&bgr; agonist was abolished by the inhibition of nitric oxide synthase. We showed that estrogen prevented aneurysmal rupture in ovariectomized female mice. The protective effect of estrogen seemed to occur through the activation of estrogen receptor-&bgr;, a predominant subtype of estrogen receptor in human intracranial aneurysms and cerebral arteries.
Effects of knowledge management on unit performance: examining the moderating role of tacitness and learnability

Purpose This paper aims to examine and test the moderating influence of the type of knowledge underlying work – known as the knowledge in practice (KIP) perspective – on the relationship between knowledge management (KM) activities and unit performance. KIP proposes that the knowledge underlying work varies according to two dimensions: tacitness and learnability. This theory proposes that aligning KM activities with tacitness and learnability results in increased performance. However, to the authors’ knowledge, there exists no direct empirical tests of these propositions outlined in KIP theory. This study examines the empirical support for the theoretical predictions outlined by KIP. Design/methodology/approach The study uses a multiple survey, multiple respondent survey design to measure KM activity sets, the tacitness and learnability involved in work contexts and unit performance. Regression analysis is used to test the hypotheses. Findings In line with previous research, the authors find support for a direct relationship between some KM activity sets and unit performance. Surprisingly, the authors did not find support for the predictions offered by KIP theory. Specifically, the degree of tacitness or learnability did not moderate the relationship between KM activity sets and unit performance. Research limitations/implications The lack of findings to support the moderating effects of tacitness and learnability on the relationship between KM activity sets and unit performance challenges the adequacy of existing formulations of KIP theory. The authors discuss several important future research directions to examine this puzzling finding. Practical implications This paper reinforces the suggestion that managers at all levels of organizations should engage in KM activities to increase performance. These findings also suggest that considering the type of knowledge underlying a unit’s work should not be a consideration in implementing KM activities. Originality/value This is the first study to empirically test a KIP perspective. That is, how the type of knowledge involved in work moderates the relationships between KM activity sets and unit performance.
AGI and Reflexivity

We define a property of intelligent systems, which we call Reflexivity. In human beings, it is one aspect of consciousness, and an element of deliberation. We propose a conjecture, that this property is conditioned by a topological property of the processes which implement this reflexivity. These processes may be symbolic, or non symbolic e.g. connexionnist. An architecture which implements reflexivity may be based on the interaction of one or several modules of deep learning, which may be specialized or not, and interconnected in a relevant way. A necessary condition of reflexivity is the existence of recurrence in its processes, we will examine in which cases this condition may be sufficient. We will then examine how this topology and this property make possible the expression of a second property, the deliberation. In a final paragraph, we propose an evaluation of intelligent systems, based on the fulfillment of all or some of these properties.
Impaired catecholaminergic signalling of B lymphocytes in patients with chronic rheumatic diseases

OBJECTIVE To investigate further the influence of the autonomic nervous system on chronic rheumatic diseases. METHODS The density and affinity of β2 adrenergic receptors (β2R) on CD19+ lymphocytes in patients with rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), and systemic sclerosis (SSc), as well as intracellular cAMP levels in patients with RA and SLE, were determined. Human peripheral blood mononuclear cells were separated from venous blood of patients and healthy controls by Ficoll-Hypaque density centrifugation. CD19+ lymphocytes were purified by magnetic cell sorting, and β2R were determined by a radioligand binding assay with [125I]iodocyanopindolol. Intracellular cAMP levels and β2R agonist induced cell death were measured by a radioimmunoassay and flow cytometry using annexin-V binding, respectively. Systemic disease activity of the patients was evaluated using multifactorial scoring systems. RESULTS The density of β2R on peripheral CD19+ lymphocytes was significantly decreased in patients with RA, SLE, and SSc compared with healthy controls. In patients with RA and SSc β2R density was negatively correlated with systemic disease activity. Furthermore, although basal intracellular cAMP levels were raised in patients with RA and SLE, the increase of cAMP upon stimulation of β2R was significantly reduced in these patients compared with control subjects. Preliminary data suggest that β2R agonist induced cell death is diminished in patients with RA exhibiting decreased β2R densities. CONCLUSIONS The results of this study show a reduction of β2R densities on B lymphocytes mirrored by an impaired intracellular cAMP generation in patients with chronic rheumatic diseases, indicating a decreased influence of the autonomic nervous system on B cells in these conditions.
Multiple Cayley-Klein metric learning

As a specific kind of non-Euclidean metric lies in projective space, Cayley-Klein metric has been recently introduced in metric learning to deal with the complex data distributions in computer vision tasks. In this paper, we extend the original Cayley-Klein metric to the multiple Cayley-Klein metric, which is defined as a linear combination of several Cayley-Klein metrics. Since Cayley-Klein is a kind of non-linear metric, its combination could model the data space better, thus lead to an improved performance. We show how to learn a multiple Cayley-Klein metric by iterative optimization over single Cayley-Klein metric and their combination coefficients under the objective to maximize the performance on separating inter-class instances and gathering intra-class instances. Our experiments on several benchmarks are quite encouraging.
Practical solutions for QoS-based resource allocation problems

The QoS based Resource Allocation Model (Q-RAM) proposed by R. Rajkumar et al. (1998) presented an analytical approach for satisfying multiple quality of service dimensions in a resource constrained environment. Using this model, available system resources can be apportioned across multiple applications such that the net utility that accrues to the end users of those applications is maximized. We present several practical solutions to allocation problems that were beyond the limited scope of Q-RAM. We show that the Q-RAM problem of finding the optimal resource allocation to satisfy multiple QoS dimensions is NP hard. We then present a polynomial solution for this resource allocation problem which yields a solution within a provably fixed and short distance from the optimal allocation. Secondly, Q-RAM dealt mainly with the problem of apportioning a single resource to satisfy multiple QoS dimensions. We study the converse problem of apportioning multiple resources to satisfy a single QoS dimension. In practice, this problem becomes complicated, since a single QoS dimension perceived by the user can be satisfied using different combinations of available resources. We show that this problem can be formulated as a mixed integer programming problem that can be solved efficiently to yield an optimal resource allocation. We also present the run times of these optimizations to illustrate how these solutions can be applied in practice. A good understanding of these solutions will yield insights into the general problem of apportioning multiple resources to satisfy simultaneously multiple QoS dimensions of multiple concurrent applications.
AUTOPILOT: A Distributed Planner for Air Fleet Control

Distributed planning requires both architectures for structuring multiple planners and techniques for planning, communication, and cooperation. We describe a family of systems for distributed control of multiple aircraft, in which each aircraft plans its own flight path and avoids collisions with other aircraft. AUTOPILOT, the kernel planner used by each aircraft, comprises several processing "experts" that share a common world model. These experts sense the world, plan and evaluate flight paths, communicate with other aircraft, and control plan execution. We discuss four architectures for the distribution of airspace management and planning responsibility among the several aircraft occupying the airspace at any point in time. The architectures differ in the extent of cooperation and communication among aircraft.
Mapping biomedical concepts onto the human genome by mining literature on chromosomal aberrations

Biomedical literature provides a rich but unstructured source of associations between chromosomal regions and biomedical concepts. By mining MEDLINE abstracts, we annotate the human genome at the level of cytogenetic bands. Our method creates a set of chromosomal aberration maps that associate cytogenetic bands to biomedical concepts from a variety of controlled vocabularies, including disease, dysmorphology, anatomy, development and Gene Ontology branches. The association between a band (e.g. 4p16.3) and a concept (e.g. microcephaly) is assessed by the statistical overrepresentation of this concept in the abstracts relating to this band. Our method is validated using existing genome annotation resources and known chromosomal aberration maps and is further illustrated through a case study on heart disease. Our chromosomal aberration maps provide diagnostics support to clinical geneticists, aid cytogeneticists to interpret and report cytogenetic findings and support researchers interested in human gene function. The method is available as a web application, aBandApart, at http://www.esat. kuleuven.be/abandapart/.
In Situ Synchrotron Measurement of Internal Stresses in Solid-Oxide Fuel Cell during Red-Ox Cycle

The internal stress in solid-oxide fuel cells (SOFCs) was evaluated during the thermal, reduction and re-oxidation cycles by using high-energy X-ray synchrotron radiation of about 70 keV at Beam line BL02B1 of SPring-8. The oxidized cell has a compression of about 400 MPa in the c-ScSZ electrolyte and a tension of 50-100 MPa in the NiO-YSZ anode at room temperature. In-situ measurement during the thermal cycle in an air atmosphere, the internal stress decreased with increasing temperature, becoming approximately zero at 1000 K. After the thermal cycle, the internal stress returned to its initial value. In the measurement during the reduction cycle, the internal stress was smaller than that measured during the cooling cycle after the anode was reduced from NiO-YSZ to Ni-YSZ. In the re-oxidation cycle of a reduced cell, the internal stress in the electrolyte went into tension above 800 K when the anode was re-oxidized from Ni-YSZ to NiO-YSZ. This tensile stress is responsible for possible fracture of unit cells in SOFCs.
Airway and tissue responses to antigen challenge in sensitized brown Norway rats.

It has recently been shown in several species that lung tissue resistance increases after administration of exogenous bronchoconstrictors. This finding suggests the possibility that lung parenchymal tissues could be involved in the pathophysiology of pulmonary allergic responses. To test this hypothesis, we sensitized Brown Norway rats with ovalbumin (OA) and performed experiments in anesthetized, open-chested, mechanically ventilated (respiratory frequency [f] = 1 Hz, tidal volume [VT] = 9 ml/kg, positive end-expiratory pressure [PEEP] = 3 cm H2O) animals. We affixed alveolar capsules to the lungs to measure alveolar pressure and calculated the resistance of lung (RL), tissue (Rti), and airway (Raw) under control conditions and after aerosol administration of saline (S) (n = 10) or OA (n = 14). To assess lung morphometry during the late response, the lungs of six S and six OA animals were frozen with liquid nitrogen (PEEP = 3 cm H2O) and processed via freeze substitution. Airway constriction was assessed by measuring the ratio of the airway lumen (A) to the ideally relaxed airway (Ar). Tissue distortion was assessed by measuring the mean linear intercept between alveolar walls (Lm), an atelectasis index (ATI) derived by calculating the ratio of tissue/airspace, and the standard deviation (SD) of Lm and ATI. In the OA group, all animals demonstrated an early response (ER; RL, Rti, Raw = 183.5 +/- 7.7, 159.7 +/- 9.9, 232.5 +/- 17.2% baseline, respectively) and 11 animals showed a late response (LR; RL, Rti, Raw = 178.9 +/- 5.1, 191.3 +/- 11.5, 176.6 +/- 17.3% baseline, respectively). Neither ER nor LR were observed in the saline group. (ABSTRACT TRUNCATED AT 250 WORDS)
Network Monitoring with Imperfect Tests

System-level Diagnosis is a long standing theory that employs tests to determine which units of a given system are {\em faulty} and {\em fault-free}. Diagnosis has been applied to network fault management, including LAN, WAN, and wireless network monitoring. A common assumption of several diagnosis models is that a fault-free tester is capable of correctly determining whether the tested unit is faulty or fault-free. As most real systems are not synchronous, this assumption is actually hard to implement in practice, and thus results in a probabilistic solution. In this work we report our initial efforts to design a model to allow network monitoring with imperfect tests, i.e. a fault-free tester may not be able to correctly determine the state of the tested unit. We investigate our hypothesis through an implementation of a LAN monitoring system.
Underwater Target Tracking Algorithm Based on an Improved Color Matching

Owing to fuzzy detail and distortion of underwater image and complex changes of target, the underwater target tracking system requires accuracy and continuity of tracking, and expects that the size of tracking window can adapt to appearance change of target. According to the requirements mentioned above, the underwater target tracking algorithm based on an improved color matching is proposed, which finds the best location of target through tracking accuracy algorithm and calculates width of window on the basis of tracking window size variation algorithm. The experimental results show that this algorithm can adaptively track the real-time target and has higher accuracy than traditional color matching algorithm.