Miracle-dz/UniFAR-FTUs huggingface dataset:
Particle swarm optimization particle filtering for dual estimation

A new method for the dual estimation in state-space dynamic model was described, with a focus on sequential Bayesian learning about time-varying state and static parameters simultaneously. The new algorithm combines auxiliary particle filtering (APF) with particle swarm optimization (PSO) to achieve computational efficiency and stability. By properly choosing the fitness function of PSO, the algorithm produces the recursive maximum-likelihood estimation of the parameters. It is shown that the PSO can be integrated with APF in the simulation-based sequential frame for dual estimation. The algorithm is tested on Markov switching stochastic volatility model with promising results.
Controlling Dynamic Guests in a Virtual Computing Utility

Virtual Machine (VM) technology is rapidly emerging as a new foundation for server resource sharing and application service delivery. Virtual machines are instantiated from images containing initial file system state and software for the machine. VM images are a convenient vehicle for delivering virtual appliances with prepackaged software components for a specific purpose or application. An image may be instantiated in a guest VM on server hardware at a server hosting provider. VCL systems are an important example, but the provider could also be a data center managed by enterprise virtual utility software (e.g., VMware or XenSource), a virtual grid site such as Globus Workspaces [Keahey et al. 2006], or an open computing utility such as Amazon’s EC2. This paper summarizes some recent work on Orca , an open-source architecture for virtual computing utilities that host dynamic guest environments on a shared server substrate. The hosted environments (guests) on an Orca substrate may range from single-user personal computing systems (e.g., a virtual desktop service) to distributed applications, experimental network environments, or programming platforms for distributed computing, such as “personal compute clouds”. New guests (such as cloud computing environments or multi-tier Web services) may be deployed in an Orca system as plug-in extensions, without modifications to the Orca software itself. We designed Orca to be “guest-neutral”: it exports protocols and programmatic interfaces with a clean separation of guest-specific logic from a common underlying virtual computing platform. The software for a guest is packaged as one or more virtual appliances, which are instantiated on demand in VMs and configured or “contextualized” to perform their intended functions within the guest application or service. Each guest is governed by an external programmatic guest controller that uses Orca protocols to acquire, configure, and release server resources at resource providers (virtual computing utility sites). The controller instantiates and configures the guest and monitors its behavior, making adjustments according to its policy. Dynamic guests may add or remove VMs or other shared resources on the fly as their needs change. We focus on two issues for dynamic guests with pluggable controllers:
Reciprocity in the Developmental Regulation of Aquaporins 1, 3 and 5 during Pregnancy and Lactation in the Rat

Milk secretion involves significant flux of water, driven largely by synthesis of lactose within the Golgi apparatus. It has not been determined whether this flux is simply a passive consequence of the osmotic potential between cytosol and Golgi, or whether it involves regulated flow. Aquaporins (AQPs) are membrane water channels that regulate water flux. AQP1, AQP3 and AQP5 have previously been detected in mammary tissue, but evidence of developmental regulation (altered expression according to the developmental and physiological state of the mammary gland) is lacking and their cellular/subcellular location is not well understood. In this paper we present evidence of developmental regulation of all three of these AQPs. Further, there was evidence of reciprocity since expression of the rather abundant AQP3 and less abundant AQP1 increased significantly from pregnancy into lactation, whereas expression of the least abundant AQP5 decreased. It would be tempting to suggest that AQP3 and AQP1 are involved in the secretion of water into milk. Paradoxically, however, it was AQP5 that demonstrated most evidence of expression located at the apical (secretory) membrane. The possibility is discussed that AQP5 is synthesized during pregnancy as a stable protein that functions to regulate water secretion during lactation. AQP3 was identified primarily at the basal and lateral membranes of the secretory cells, suggesting a possible involvement in regulated uptake of water and glycerol. AQP1 was identified primarily at the capillary and secretory cell cytoplasmic level and may again be more concerned with uptake and hence milk synthesis, rather than secretion. The fact that expression was developmentally regulated supports, but does not prove, a regulatory involvement of AQPs in water flux through the milk secretory cell.
Multiple sliding surface control for systems with mismatched uncertainties

This paper proposes a new method for sliding mode control of systems with mismatched uncertainties. The proposed method employs a multiple sliding surface (MSS) approach combined with inertial delay control (IDC) for estimating unmatched disturbances. It has the advantage of tackling constant as well as time-variant and state dependent disturbances/uncertainties. The proposed method is validated by simulation and compared with traditional sliding mode control (SMC) and integral sliding mode control (I-SMC) method.
Development of a magnetic diagnostic suitable for the ITER radiation environment

Magnetic diagnostics of the ITER tokamak must fulfill demanding specifications, because their accuracy and reliability affects margins to the machine engineering limits and there-fore operational flexibility. This paper describes the challenging issues related to the implementation of the magnetic diagnostics in a tokamak environment. We focus on nuclear radiations as they can significantly affect the measurement through Radiation Induced Electromotive Force (RIEMF) or Thermally Induced Electromotive Force (TIEMF). Thermal modeling of magnetic sensors and associated design studies are also reported as the thermal gradient in the sensors must be reduced to avoid TIEMF. Alter-native magnetic sensors such as fiber optic current sensors (FOCS) or steady state magnetic field sensors are also discussed because they serve as a backup to the usual inductive magnetic measurements. We conclude by a brief review of the development needs for magnetic diagnostics‥
Glycocalyx modulation is a physiological means of regulating cell adhesion.

Here we present experimental evidence that phagocytic cells use modulation of specific components of their glycocalyx to regulate their binding capacity. Particles coated with antibodies specific for the CD32 medium affinity IgG receptor were driven along human monocytic THP-1 cells (expressing CD32) in a flow chamber operated at low shear rate. Surprisingly, only minimal adhesion was observed. However, when cells were activated by exposure to fibronectin-coated surfaces and/or soluble &ggr; interferon, adhesion efficiency was dramatically increased, whereas the apparent glycocalyx thickness displayed 20% decrease, and the surface density of CD43/leukosialin carbohydrate epitopes displayed 30-40% decrease on activated cells. The existence of a causal link between adhesion increase and glycocalyx alteration was strongly supported by the finding that (i) both phenomena displayed similar kinetics, (ii) an inverse relationship between THP-1 cell binding capacity and glycocalyx density was demonstrated at the individual cell level, and (iii) adhesion enhancement could not be ascribed to an increased binding site density or improved functional capacity of activated cells. Additional experiments revealed that cell-to-particle adhesion resulted in delayed (i.e. more than a few minutes) egress of CD43/leukosialin from contact areas. Since the time scale of particle attachment was less than a second, surface mobility should not affect the potential of CD43 to impair the initial step of adhesion. Finally, studies performed with fluorescent lectins suggested that THP-1 cell activation and increased adhesive potential were related to a decrease of O-glysosylation rather than N-glycosylation of surface glycoproteins.
Improved Scaling for Quantum Monte Carlo on Insulators

Quantum Monte Carlo (QMC) methods are often used to calculate properties of many body quantum systems. The main cost of many QMC methods, for example, the variational Monte Carlo (VMC) method, is in constructing a sequence of Slater matrices and computing the ratios of determinants for successive Slater matrices. Recent work has improved the scaling of constructing Slater matrices for insulators so that the cost of constructing Slater matrices in these systems is now linear in the number of particles, whereas computing determinant ratios remains cubic in the number of particles. With the long term aim of simulating much larger systems, we improve the scaling of computing the determinant ratios in the VMC method for simulating insulators by using preconditioned iterative solvers. The main contribution of this paper is the development of a method to efficiently compute for the Slater matrices a sequence of preconditioners that make the iterative solver converge rapidly. This involves cheap preconditioner updates, an effective reordering strategy, and a cheap method to monitor instability of incomplete LU decomposition with threshold and pivoting (ILUTP) preconditioners. Using the resulting preconditioned iterative solvers to compute determinant ratios of consecutive Slater matrices reduces the scaling of QMC algorithms from $O(n^3)$ per sweep to roughly $O(n^2)$, where $n$ is the number of particles, and a sweep is a sequence of $n$ steps, each attempting to move a distinct particle. We demonstrate experimentally that we can achieve the improved scaling without increasing statistical errors. Our results show that preconditioned iterative solvers can dramatically reduce the cost of VMC for large(r) systems.
A Unique Solution of Planet and Star Parameters from an Extrasolar Planet Transit Light Curve

There is a unique solution of the planet and star parameters from a planet transit light curve with two or more transits if the planet has a circular orbit and the light curve is observed in a bandpass where limb darkening is negligible. The existence of this unique solution is very useful for current planet transit surveys for several reasons. First, there is an analytic solution that allows a quick parameter estimate, in particular of Rp. Second, the stellar density can be uniquely derived from the transit light curve alone. The stellar density can then be used to immediately rule out a giant star (and hence a much larger than planetary companion) and can also be used to put an upper limit on the stellar and planet radius even considering slightly evolved stars. Third, the presence of an additional fully blended star that contaminates an eclipsing system to mimic a planet transit can be largely ruled out from the transit light curve given a spectral type for the central star. Fourth, the period can be estimated from a single-transit light curve and a measured spectral type. All of these applications can be used to select the best planet transit candidates for mass determination by radial velocity follow-up. To use these applications in practice, the photometric precision and time sampling of the light curve must be high (better than 0.005 mag precision and 5 minute time sampling for a two-transit light curve).
Aloha-Based MAC Protocols with Collision Avoidance for Underwater Acoustic Networks

Unlike terrestrial networks that mainly rely on radio waves for communications, underwater networks utilize acoustic waves, which have comparatively lower loss and longer range in underwater environments. However, the use of acoustic waves pose a new research challenge in the networking area. While existing network schemes for terrestrial sensor networks are mainly designed for negligible propagation delay and high data rate, underwater acoustic communications are characterized by high propagation delay and low data rate. These terrestrial schemes, when directly applied to the underwater channel, will under-utilize its already limited capacity. We investigate how the underwater channel's throughput may be enhanced via medium access control (MAC) techniques that consider its unique characteristics. Specifically, we study the performance of Aloha-based protocols in underwater networks, and propose two enhanced schemes, namely, Aloha with collision avoidance (Aloha-CA), and Aloha with advance notification (Aloha-AN), which are capable of using the long propagation delays to their advantage. Simulation results have shown that both schemes can boost the throughput by reducing the number of collisions, and, for the case of Aloha-AN, also by significantly reducing the number of unproductive transmissions.
Data Falsification Attacks on Consensus-Based Detection Systems

This paper considers the problem of signal detection in distributed networks in the presence of data falsification (Byzantine) attacks. Detection approaches considered in the paper are based on fully distributed consensus algorithms, where all of the nodes exchange information only with their neighbors in the absence of a fusion center. For such networks, we first characterize the negative effect of Byzantines on the steady state and transient detection performance of conventional consensus-based detection algorithms. To avoid performance deterioration, we propose a distributed weighted average consensus algorithm that is robust to Byzantine attacks. We show that, under reasonable assumptions, the global test statistic for detection can be computed locally at each node using our proposed consensus algorithm. We exploit the statistical distribution of the nodes’ data to devise techniques for mitigating the influence of data falsifying Byzantines on the distributed detection system. Since some parameters of the statistical distribution of the nodes’ data might not be known a priori, we propose learning based techniques to enable an adaptive design of the local fusion or update rules. Numerical results are presented for illustration.
Synthesizing dance performance using musical and motion features

This paper proposes a method for synthesizing dance performance synchronized to played music and our method presents a system that imitates dancers' skills in performing their motion while they listen to the music. Our method consists of a motion analysis, a music analysis, and a motion synthesis based on results of the analyses. In these analysis steps, motion and music features are acquired. These features are derived from motion keyframes, motion intensity, music intensity, musical beats, and chord changes. Our system also constructs a motion graph to search similar poses from given dance sequences and to connect them as possible transitions. In the synthesis step, the trajectory that provides the best correlation between music and motion features is selected from the motion graph, and the resulting motion is generated. Our experimental results indicate that our proposed method actually creates dance as the system "hears" the music
Quality-based framework for requirement analysis in data warehouse

Data warehouse (DW) integrates data from external and internal sources not only for storage purposes but also for analythical query processing. As this information is to be used for business intelligent, it makes the design of DW difficult task. Requirements analysis is the foundation for the development of a DW. Ensuring quality in requirements analysis is an importance task to minimize the risk of failure in a DW project. However, quality issues in DW requirements analysis have not given much attention in the literature. In this paper we have advocated the integration of quality and multi-driven approach (goal-driven, user-driven, data-driven, process-driven and external-driven) as an explicit stage in the DW development to reduce failure risk of DW.
Precise indoor localization of multiple mobile robots with adaptive sensor fusion using odometry and vision data

Abstract An accurate, reliable and a cost effective localization is the key feature of self-navigation of autonomous mobile robots. The position and orientation, together known as pose, of the mobile robot can be determined by using certain localization systems. In this work we use the mobile robot system Robotino – a practice-orientated educational and training system offered by Festo Didactic GmbH. For the Robotinos, position determination can be provided by laser scanner for Robotino or Robotino® Northstar System (Festo Didactic GmbH). These existing systems are quite expensive and localization accuracy in certain field dimensions is quite low. In this paper we provide a relatively inexpensive and a more accurate localization system, which combines the strengths of odometry and vision-based localization. The fusion of odometry and vision-based localization data is accomplished with the use of the Extended Kalman Filter (EKF). The resulting localization system delivers better accuracy and more frequent pose information of the mobile robots on the test field.
Design and Analysis of Electrical Resistance Feedback for Automated Patch Clamp on Adherent Cells

Conventional patch clamp techniques require complex manual work. Automated patch clamp systems have been recently developed to eliminate the need of manual handling, but these systems can only perform recordings on suspended cells and require cell dissociation for recordings on adherent cells. Here, we develop a systematic approach to apply electrical resistance feedback for automated patch clamp recording on adherent cells. By developing resistance thresholds in the electrical resistance feedback algorithm, the engaging condition of the adherent cell was automatically determined. We analyze the critical parameters that affect the performance of the automated patch clamp recording. By using the new algorithm for automated engaging and formation, the cell-attached and whole-cell recordings on adherent cells were performed in less than 5 min with the yield of over 70%. The system is designed to directly measure the adherent cells and so, cell dissociation (e.g., trypsin treatment and cell scrapers) can be avoided and the cell properties can be maintained. By using the system, the efficiency of performing the automated patch clamp on adherent cells can be improved, which is of great importance in electrophysiological studies of single cells.
Multiple reflection expansion and heat kernel coefficients

We propose the multiple reflection expansion as a tool for the calculation of heat kernel coefficients. As an example, we give the coefficients for a sphere as a finite sum over reflections, obtaining as a byproduct a relation between the coefficients for Dirichlet and Neumannboundary conditions. Further, we calculate the heat kernel coefficients for the most general matching conditions on the surface of a sphere, including those cases corresponding to the presence of delta and delta prime background potentials. In the latter case, the multiple reflection expansion is shown to be non-convergent.
Eating disorder public service announcements: Analyzing effects from an intergroup affect and stereotype perspective

Purpose – Previous studies have documented that exposure to stereotypical information about certain social groups leads to unfavorable perceptions and feelings toward that group. Integrating insights from the mental illness stigma and the social identity perspective literatures, the purpose of this paper is to explore the effects of eating disorder public service announcements (ED PSAs) that employ stigma formats through the lenses of the stereotype content model (SCM) and the Behaviors from Intergroup Affect and Stereotypes (BIAS) Map. Design/methodology/approach – The study followed an experimental control group design. Participants were exposed to either a stigmatizing or a non-stigmatizing PSA. Findings – Exposure to the stigmatizing PSA resulted in lower perceptions of warmth and competence being attributed to people who have an ED which further predicted greater feelings of contempt toward these individuals. The stigmatizing PSA also directly predicted greater feelings of contempt. Practical implications – The findings suggest that using stereotypes about EDs in PSAs aimed at preventing such diseases may elicit perceptions of low warmth and competence, further associated with increased feelings of contempt toward people who have an ED in healthy individuals. Social implications – The stereotyping effects of PSAs may reduce the social and emotional support that people with EDs receive and may exacerbate their emotional distress. Originality/value – From a theoretical point of view, these results extend the understanding of mental illness stereotypes from an intergroup, SCM and BIAS Map perspective as it applies to EDs. More importantly, this study draws attention to possible unintended consequences of PSAs, a matter that is rarely researched, but that can have severe implications.
Cognitive impairment and Alzheimer’s disease: Links with oxidative stress and cholesterol metabolism

Oxidative stress has been implicated in the progression of a number of neurodegenerative diseases, including Alzheimer’s disease (AD), Parkinson’s disease and amyotrophic lateral sclerosis. We carried out an in-depth study of cognitive impairment and its relationships with oxidative stress markers such as ferric-reducing ability of plasma (FRAP), plasma malondialdehyde and total antioxidative capacity (TAC), as well as cholesterol parameters, in two subsets of subjects, AD patients (n = 59) and a control group of neurologically normal subjects (n = 29), attending the University Hospital Salvador in Santiago, Chile. Cognitive impairment was assessed by a set of neuropsychological tests (Mini-Mental State Examination, Boston Naming Test, Ideomotor Praxia by imitation, Semantic Verbal Fluency of animals or words with initial A, Test of Memory Alteration, Frontal Assessment Battery), while the levels of those oxidative stress markers and cholesterol metabolism parameters were determined according with standard bioassays in fresh plasma samples of the two subgroups of patients. No significant differences were observed when the cholesterol parameters (low-, high-density lipoprotein, total cholesterol) of the AD group were compared with normal controls. Interestingly, a correlation was evidenced when the levels of cognitive impairment were analyzed with respect to the plasma antioxidant capacity (AOC) of patients. In this context, the subset of subjects exhibiting cognitive impairment were divided into two subgroups according with their Global Dementia Scale performance: a subgroup with mild AD and a subgroup with moderate to severe AD. Significant differences in AOC were found between subgroups. The different correlations between cognitive impairment of subgroups of subjects with the oxidative stress profile are discussed in the context of AD pathogenesis.