Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification and experimentation of an industrial robot operating in varying-impedance environments

It is well-known that iff the robot with its end-effector force control is passive, the closed loop system consisting of the robot and an arbitrary passive environment is asymptotically stable. Passive robot control, however, limits the achievable robot impedance reduction. Recently, [1] investigated what performance can be achieved with non-passive control when uncertainty bounds for the environment are known. The question of stability margins neglected in [1] is treated in our companion paper [2].
Efficient Constraint Evaluation Algorithms for Hierarchical Next-Best-View Planning

We recently proposed a new and efficient next-best- view algorithm for 3D reconstruction of indoor scenes using active range sensing. We overcome the computation difficulty of evaluating the view metric function by using an adaptive hierarchical approach to exploit the various spatial coherences inherent in the acquisition constraints and quality requirements. The impressive speedups have allowed our NBV algorithm to become the first to be able to exhaustively evaluate a large set of 3D views with respect to a large set of surfaces, and to include many practical acquisition constraints and quality requirements. The success of the algorithm is greatly dependent on the implementation efficiency of the constraint and quality evaluations. In this paper, we describe the algorithmic details of the hierarchical view evaluation, and present efficient algorithms that evaluate sensing constraints and surface sampling densities between a view volume and a surface patch instead of simply between a single view point and a surface point. The presentation here provides examples for the design of efficient algorithms for new sensing constraints.
Comparison of hydrogen silsesquioxane development methods for sub-10 nm electron beam lithography using accurate linewidth inspection

There is presently considerable interest in determining the resolution limits of hydrogen silsesquioxane as a negative tone electron beam resist. Various techniques for improving the resolution and contrast have been reported in the literature. These include the use of concentrated tetramethyl ammonium hydroxide, hot development, sodium hydroxide, salty development, and the use of dilute hydrofluoric acid dips. One difficulty in comparing the results from different research groups is that measurements are made using different electron microscopes working at various beam energies. Different groups frequently use different resist thickness and a variety of electron beam lithography tools operating at differing beam energies. These variations mean that useful comparisons at the nanometer scale are often not possible. This paper compares different development techniques using a unified inspection regime and a high contrast backscattered electron detector. The paper also considers important issues such as resi.
Atomic-scale Deformation Kinematics for Bicrystal Grain Boundaries under Shear Loading

This research utilizes a method for calculating an atomic-scale deformationgradient within the framework of continuum mechanics using atomisticsimulations to examine bicrystal grain boundaries subjected to shear loading. Wecalculate the deformation gradient, its rotation tensor from polar decomposition,and estimates of lattice curvature and vorticity for thin equilibrium bicrystalgeometries deformed at low temperature. These simulations reveal pronounceddeformation fields that exist in small regions surrounding the grain boundary, anddemonstrate the influence of interfacial structure on mechanical behavior for thethin models investigated. Our results also show that more profound insight isgained concerning inelastic grain boundary phenomena by analyzing thedeformed structures with regard to these continuum mechanical metrics.
Induction of optical density waves and chemotactic cell movement in Dictyostelium discoideum by microinjection of cAMP pulses.

The development of most multicellular organisms involves coordinated cell movement. The early aggregation of Dictyostelium cells has been shown to be mediated by chemotactic movement to propagating waves of cAMP. We have proposed that propagating waves of a chemoattractant, most likely cAMP, also control the movement of cells in mounds and slugs. We have now used periodic pressure injection of pulses of cAMP in the extracellular space of aggregation streams, mounds, and slugs to investigate whether these signals can be relayed and control cell movement, using quantitative digital time-lapse microscopy. Our major findings are (1) short (0.1 s) pulses of cAMP (10(7) molecules) were able to elicit optical density (OD) waves in fields of aggregating amoebae. They propagate from the micropipet outward and interact with endogenous OD waves. (2) Periodic injection of cAMP pulses into aggregation streams blocked the pulses coming from the center and led to the rapid accumulation of cells downstream of the pipet around the pipet. (3) Injection of pulses of cAMP into mounds elicited OD waves, which propagated from the pipet outward and interacted with the endogenous waves, indicating that the same propagator carries them. (4) Periodic microinjection of cAMP in the prespore zone of slugs led to accumulation of anterior-like cells around the micropipet followed by tip formation. Furthermore, the cAMP signal could control the spacing of the endogenous sorting pattern. These results strongly support the hypothesis that the optical density waves observed during early development up to the mound stage represent propagating cAMP waves. They suggest furthermore that cAMP is the morphogen that controls cell movements in slugs.
Noncooperative dynamic games for inventory applications: A consensus approach

We focus on a finite horizon noncooperative dynamic game where the stage cost of a single player associated to a decision is a monotonically nonincreasing function of the total number of players making the same decision. For the single-stage version of the game, we characterize Nash equilibria and derive a consensus protocol that makes the players converge to the unique Pareto optimal Nash equilibrium. Such an equilibrium guarantees the interests of the players and is also social optimal in the set of Nash equilibria. For the multi-stage version of the game, we present an algorithm that converges to Nash equilibria, unfortunately not necessarily Pareto optimal. The algorithm returns a sequence of joint decisions, each one obtained from the previous one by an unilateral improvement on the part of a single player. The sequence with which the players act is chosen a priori and may influence the Nash equilibrium to which the path converges. We also specialize the game to a multi-retailer inventory system, where competing retailers aim at coordinating their supply strategies in order to minimize their local costs.
Protective coatings for mechanical aluminum–magnesium joints

AZ31 alloy is used as a lightweight material for structural application in the automobile and aircraft production. However, alloy AZ31 is known to have poor corrosion resistant due to high electrochemical activity. In this study, the possibility of improving the corrosion resistance by applying protective coatings deposited by the low pressure cold spray process was investigated. The relative performance of each cold sprayed corrosion preventive coatings was assessed in accordance with American Society for Testing and Materials standards. The data for the bare AZ31 alloy were initially obtained and used as a reference point to compare the corrosion protective performance of different preventive coatings. Electrochemical behaviour of each coating composition was analyzed after a given time period of the accelerated corrosion test. Microstructure and mechanical properties of the deposited preventive coatings are also discussed. The cold sprayed preventive coatings provide sufficient protection to substantially reduce the corrosion rate of alloy AZ31.
Spatial Data Preparation for Knowledge Discovery

There is a well known necessity to extract knowledge from spatial databases. Dozens of algorithms for data mining and knowledge discovery are reported in the specific literature to supply this necessity. However, these algorithms have some general drawbacks. Some consider only spatial data and others, only non-spatial data. Most are pseudo-codes, which are usually not implemented in toolkits, and need inputs in a specific representation. These inputs are often in unusual formats, and if these formats are easily obtainable in real databases is normally not mentioned nor considered. Therefore, outside academic institutions, data mining practice in real spatial databases is rare. This research proposes a methodology to prepare spatial data for data mining, as well as an interoperable software architecture to implement the methodology. Experiments with different input data formats were achieved with different data mining toolkits in order to validate the methodology. The software architecture was implemented in a data preparation toolkit and applied to artificial and real spatial databases.
Optimum location of sensors used for mould parameters estimation

Heat transfer processes proceeding in the system casting-mould-environment are considered. In particular, the inverse problem connected with the estimation of thermal conductivity and volumetric specific heat of mould material is presented. To estimate the parameters, the additional information concerning the temperature history at the points selected from domain considered is necessary. The essential problem is a proper choice of sensors localization. The application of sensitivity analysis assures the increase of identification efficiency and this problem is here presented. In the final part of the paper the examples of computations are shown.
Efficient antibacterial silver nanoparticles composite using lignin as a template

Lignin was used as a template for the first time to in situ synthesize lignin-based silver nanoparticles composites using sodium borohydride or ascorbic acid as a reducing agent. The lignin-based silver nanoparticles composites were characterized by means of X-ray diffraction, scanning electron microscopy, transmission electron microscopy and thermogravimetric analysis. The scanning electron microscopy and transmission electron microscopy studies confirmed that silver nanoparticles with good dispersibility were well anchored onto the surface of lignin and the nanoparticles had pseudospherical shape with size mostly in 45–55 nm. Moreover, the antibacterial activity of the composites was studied against E. coli. A headspace gas chromatographic technique was used to monitor the bacterial growth by measuring the CO2 released by the bacteria. The results showed that the lignin-based silver nanoparticles composites can be used as potential antimicrobial agents.
A 16-element phased-array receiver IC for 60-GHz communications in SiGe BiCMOS

A 0.12-µm SiGe phased-array Rx IC for beam-steered wireless communication in the 60-GHz band is described. It has 16 RF phase-shifting front-ends with 11° digital phase resolution and hybrid passive-active RF signal combining. It achieves 7.4–7.9 dB NF (not including 12-dB array gain) over the 4 IEEE channels. The IC has a double-conversion superheterodyne Rx core with a maximum of 72 dB of power gain in 1-dB steps, and the on-chip synthesizer achieves ≪ −90 dBc/Hz Rx phase noise at 1MHz offset. The IC draws 1.8 W at 2.7 V with a die area of 38 mm2. It has been packaged with 16 antennas in a 288-pin organic BGA and phased-array beamsteering has been demonstrated, along with 5+ Gb/s wireless links using 16-QAM OFDM.
A Platform for Ubiquitous Sensor Deployment in Occupational and Domestic Environments

In this paper, we introduce the "Plug" sensor network, a ubiquitous networked sensing platform ideally suited to broad deployment in environments where people work and live. The backbone of the Plug sensor network is a set of 35 sensor-, radio-, and computation-enabled power strips distributed throughout the third floor of the MIT Media Lab. A single Plug device fulfills all the functional requirements of a normal power strip (i.e., four 120 V, 60 Hz electrical outlets; surge protector circuit; standard electrical connector to a US-style wall socket), and can be used without special training. Additionally, each Plug has a wide range of sensing modalities (e.g., sound, light, electrical current and voltage, vibration, motion, and temperature) for gathering data about how it is being used and its nearby environment. To our knowledge, the Plug sensor network is the first to embody the idea of designing sensor nodes to seamlessly become a part of their environment, rather than play the role of alien, if unobtrusive, observers. We argue this design principle is essential for sensor networks to succeed in the realm of ubiquitous computing. In this paper, we present an overview of the Plug hardware and software architectures, look at specific usage scenarios of a single Plug, and show example data taken across the entire Plug network to give a sense of the pulse of the building over a span of days. Finally, we present ongoing work interfacing heterogeneous devices with the Plug network for a variety of applications and discuss possible future work.
Collapsed Variational Dirichlet Process Mixture Models

Nonparametric Bayesian mixture models, in particular Dirichlet process (DP) mixture models, have shown great promise for density estimation and data clustering. Given the size of today's datasets, computational efficiency becomes an essential ingredient in the applicability of these techniques to real world data. We study and experimentally compare a number of variational Bayesian (VB) approximations to the DP mixture model. In particular we consider the standard VB approximation where parameters are assumed to be independent from cluster assignment variables, and a novel collapsed VB approximation where mixture weights are marginalized out. For both VB approximations we consider two different ways to approximate the DP, by truncating the stick-breaking construction, and by using a finite mixture model with a symmetric Dirichlet prior.
Crystallization behavior of poly(ϵ‐caprolactone)/Tio2 nanocomposites obtained by in situ polymerization

Poly(ϵ-caprolactone) (PCL)/titanium dioxide (TiO2) nanocomposites were prepared by in situ polymerization of ϵ-caprolactone in the presence of modified-TiO2 nanoparticles as initiators. The molecular weight of PCL matrix was dependent on the amount of the TiO2 fillers. The incorporation of TiO2 did not significantly affect the crystalline structure of PCL. Moreover, a tendency of the nanoparticles to form aggregates was observed, especially at higher fillers contents. The analysis of the crystallization process showed that the addition of TiO2 nanoparticles accelerated the crystallization rate of PCL, and the crystallization rates increased by increasing the filler content. The crystallization activation energy dependence on the filler content observed here is probably the consequence of the two competing factors. The tendency of activation energy obtained by nonisothermal crystallization is similar to that of isothermal crystallization. POLYM. ENG. SCI., 2012. © 2011 Society of Plastics Engineers
Consumption calculation of vehicles using OBD data

The European type approval procedure, based on a fixed driving cycle for all vehicles, is not representative of their real on-road usage: the driving style and its influence on consumption and emissions cannot be neglected and their real-world environmental impact is not simple to measure. The objective of this work is to develop a methodology to calculate in real-time the energy and environmental impact of spark ignition and diesel vehicles. An on-board instrumentation capable to communicate with the electronic system of the vehicle (OBD/CAN) have been developed to collect all the sensor data available (rpm, vehicle speed, engine load, lambda sensor voltage, catalyst temperature, intake airflow, pressure and temperature etc.) and use them as input for power and consumption models. The models have been applied on several vehicles and validated on a dynamometer chassis running NEDC and ARTEMIS cycles. Consumption has been measured with the CVS and with a portable emission analyzer (HORIBA OBS-1300). A calibration procedure has been also developed in which 3 tests on a dynamometer chassis are needed: the maximum power curve, the curve at idle and a curve at fixed rpm varying the engine load. For spark ignition engines, an additional test should be needed to calibrate a coefficient that takes into account of the enrichment during accelerator pedal gradients, but this coefficient is not much variable for different vehicles (~10). All the vehicles show a difference between measurements and models never greater than 4% so this can be an accurate methodology to calculate the power and consumption of vehicles during their real use.
Semantic Forcing in Disjunctive Logic Programs

We propose a semantics for disjunctive logic programs, based on the single notion of forcing. We show that the semantics properly extends, in a natural way, previous approaches. A fixpoint characterization is also provided. We also take a closer look at the relationship between disjunctive logic programs and disjunctive‐free logic programs. We present certain criteria under which a disjunctive program is semantically equivalent with its disjunctive‐free (shifted) version.
Comparison of predictor approaches for longitudinal binary outcomes: application to anesthesiology data

Longitudinal data with binary repeated responses are now widespread among clinical studies and standard statistical analysis methods have become inadequate in the answering of clinical hypotheses. Instead of such conventional approaches, statisticians have started proposing better techniques, such as the Generalized Estimating Equations (GEE) approach and Generalized Linear Mixed Models (GLMM) technique. In this research, we undertook a comparative study of modeling binary repeated responses using an anesthesiology dataset which has 375 patient data with clinical variables. We modeled the relationship between hypotension and age, gender, surgical department, positions of patients during surgery, diastolic blood pressure, pulse, electrocardiography and doses of Marcain-heavy, chirocaine, fentanyl, and midazolam. Moreover, parameter estimates between the GEE and the GLMM were compared. The parameter estimates, except time-after, Marcain-Heavy, and Fentanyl from the GLMM, are larger than those from GEE. The standard errors from the GLMM are larger than those from GEE. GLMM appears to be more suitable approach than the GEE approach for the analysis hypotension during spinal anesthesia.
Molecular characterization of FrpB, the 70-kilodalton iron-regulated outer membrane protein of Neisseria meningitidis

The structural gene encoding the 70-kDa outer membrane protein FrpB of Neisseria meningitidis was cloned and sequenced. A mutant lacking FrpB was constructed. No difference in iron utilization between the mutant and the parental strain was observed. A minor effect of the mutation on serum resistance was observed. A topology model for FrpB in the outer membrane is proposed.
Hemostatic management of patients undergoing ear-nose-throat surgery

Zusammenfassung Das perioperative Hämostasemanagement gewinnt auch in der Otorhinolaryngologie zunehmend an Bedeutung. Die vorliegende Übersichtsarbeit fasst den aktuellen Stand der Literatur zusammen und erläutert das perioperative Hämostasemanagement. Mit Bezug auf die HNO-Heilkunde werden die allgemeinen Prinzipien der Risikobewertung, Thromboseprophylaxe, und der Überbrückung der Antikoagulation erläutert.
First principle study of electronic structure and mechanical properties of Zr doped Al2Cu

Abstract First principle calculations are adopted using the pseudopotential plane wave method scheme to investigate the electronic structure and mechanical properties of Zr doped Al–Cu intermetallic compounds Al2Cu. Replacing an Al atom or a Cu atom with a Zr atom, this compound forms the crystal structure of Al15Cu8Zr or Al16Cu7Zr. The results show that the structural stability and alloying ability of doped structures are larger than Al2Cu. Moreover, the structural stability and alloying ability of Al15Cu8Zr are higher than that of Al16Cu7Zr. This indicates that Zr is preferred to replace the position of Al. The mechanical properties of doped structures are increased, such as stiffness and plasticity. However, the ductility decreases, and the corresponding room temperature brittleness becomes larger. Theoretical analysis reveals that these two compounds have strong hybridisation between Al s, p states and Zr d states, which leads to intensify the atomic interaction. Therefore, chemical bonds show a character of covalent bond, and the ductility reduces.
Circadian clock of Aedes aegypti: effects of blood-feeding, insemination and RNA interference

Mosquitoes are the culprits of some of the most important vector borne diseases. A species’ potential as a vector is directly dependent on their pattern of behaviour, which is known to change according to the female’s physiological status such as whether the female is virgin/mated and unfed/blood-fed. However, the molecular mechanism triggered by and/or responsible for such modulations in behaviour is poorly understood. Clock genes are known to be responsible for the control of circadian behaviour in several species. Here we investigate the impact mating and blood-feeding have upon the expression of these genes in the mosquito Aedes aegypti . We show that blood intake, but not insemination, is responsible for the down-regulation of clock genes. Using RNA interference, we observe a slight reduction in the evening activity peak in the fourth day after dstim injection. These data suggest that, as in Drosophila , clock gene expression, circadian behaviour and environmental light regimens are interconnected in Ae. aegypti .
AlGaN/GaN sensors for direct monitoring of fluids and bioreactions

AlGaN/GaN based pH-sensors have been characterized and further developed for the in situ monitoring of cell reactions. Generally, good proliferation of different cell lines was observed on AlGaN and GaN surfaces without using any kind of thin films of organic material for improving of the cellular adhesion and biocompatibility. NG108-15 nerve cells were chosen for the investigation of the sensor response on cell activity. In an open setup with contact to normal atmosphere, the monitoring of the spontaneous cell activity (“breathing”) was recorded. By titration in complex electrolytes, it was demonstrated that these sensors are able to monitor complex cell reactions on different neuroinhibitors. Numerical simulations as well as simplified analytical calculations of ion fluxes give strong evidence that the signal in the cell-transistor coupling experiments is primarily generated by the Na+ flux. In conclusion, the AlGaN/GaN-ISFETs show stable operation under physiological conditions, exhibit a very good signal resolution and are suitable for long-time monitoring of cell reactions on different stimuli.
Adaptive predictive control system design with an adaptive output estimator

The predictive controls are one of the major control strategies in the process control. However, in general, an exact model of the controlled system is required in order to predict the system's outputs accurately. In this paper, we propose an adaptive predictive control using an adaptive output estimator with a simple structure for uncertain controlled systems. In the proposed method, the stability of the obtained adaptive predictive control system will be confirmed by setting a novel input constraint, “almost strictly positive real (ASPR) constraint”.