Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive speed control for induction motor drives using neural networks

In this paper, the adaptive speed control of induction motor drives using neural networks is presented. To obtain good performances both in tracking and regulating characteristics, a digital two-degree-of-freedom (2DOF) controller and its quantitative design procedure are proposed. The parameters of the controller corresponding to various drive parameter sets are found off-line and stored as the training patterns. Under normal operation, the true drive parameters are real-time identified and they are converted into the controller parameters through multilayer forward computation by neural networks. In which, the connection weights of the multilayer feedforward network are estimated by backpropagation learning algorithm. <<ETX>>
LQR-trees: Feedback motion planning on sparse randomized trees

Recent advances in the direct computation of Lyapunov functions using convex optimization make it possible to efficiently evaluate regions of stability for smooth nonlinear systems. Here we present a feedback motion planning algorithm which uses these results to efficiently combine locally-valid linear quadratic regulator (LQR) controllers into a nonlinear feedback policy which probabilistically covers the reachable area of a (bounded) state space with a region of stability, certifying that all initial conditions that are capable of reaching the goal will stabilize to the goal. We carefully investigate the algorithm on a two-dimensional model system and discuss the potential for the control of more complicated underactuated control problems like bipedal walking.
Sensing Traffic Density Combining V2V and V2I Wireless Communications

Wireless technologies are making the development of new applications and services in vehicular environments possible since they enable mobile communication between vehicles (V2V), as well as communication between vehicles and infrastructure nodes (V2I). Usually, V2V communications are dedicated to the transmission of small messages mainly focused on improving traffic safety. Instead, V2I communications allow users to access the Internet and benefit from higher level applications. The combination of both V2V and V2I, known as V2X communications, can increase the benefits even further, thereby making intelligent transportation systems (ITS) a reality. In this paper, we introduce V2X-d, a novel architecture specially designed to estimate traffic density on the road. In particular, V2X-d exploits the combination of V2V and V2I communications. Our approach is based on the information gathered by sensors (i.e., vehicles and road side units (RSUs)) and the characteristics of the roadmap topology to accurately make an estimation of the instant vehicle density. The combination of both mechanisms improves the accuracy and coverage area of the data gathered, while increasing the robustness and fault tolerance of the overall approach, e.g., using the information offered by V2V communications to provide additional density information in areas where RSUs are scarce or malfunctioning. By using our collaborative sensing scheme, future ITS solutions will be able to establish adequate dissemination protocols or to apply more efficient traffic congestion reduction policies, since they will be aware of the instantaneous density of vehicles.
Stated product formulation preferences for HIV pre-exposure prophylaxis among women in the VOICE-D (MTN-003D) study

The effectiveness of HIV pre‐exposure prophylaxis (PrEP) requires consistent and correct product use, thus a deeper understanding of women's stated product formulation preferences, and the correlates of those preferences, can help guide future research. VOICE‐D (MTN‐003D), a qualitative ancillary study conducted after the VOICE trial, retrospectively explored participants’ tablet and gel use, as well as their preferences for other potential PrEP product formulations.
The use of preserved tissue in finite element modelling of fresh ovine vertebral behaviour

The aim of this study was to investigate whether the predicted finite element (FE) stiffness of vertebral bone is altered when using images of preserved rather than fresh tissue to generate specimen-specific FE models. Fresh ovine vertebrae were used to represent embalmed (n = 3) and macerated dry-bone (n = 3) specimens and treated accordingly. Specimens were scanned pre- and post-treatment using micro-computed tomography. A constant threshold level derived from these images was used to calculate the respective bone volume fraction (BV/TV) from which the conversion factor validated for fresh tissue was used to determine material properties that were assigned to corresponding FE models. Results showed a definite change in the BV/TV between the fresh and the preserved bone. However, the changes in the predicted FE stiffness were not generally greater than the variations expected from assignment of loading and boundary conditions. In conclusion, images of preserved tissue can be used to generate FE models that are representative of fresh tissue with a tolerable level of error.
Epidural Spinal Empyema and Vertebral Osteomyelitis in a Cat

ABST RACT A young adult neutered male domestic shorthair cat of unknown age was examined for a complaint of progressive hind limb paralysis. Neurologic examination revealed paraplegia with no deep pain sensation in both hind limbs and suggested a lesion localized between spinal cord segments T3 and L3. Survey radiography revealed at L2 multiple sites of lysis within the vertebra and a dense extradural soft tissue mass severely compressing the spinal cord. Computed tomography-guided needle aspiration was performed and a diagnosis of vertebral osteomyelitis and suspected spinal empyema was made. Emergency surgical decompression by pediculectomy exposed a firm, capsulated extradural tissue compressing the spinal cord. The abnormal tissue was removed and submitted to bacterial culture and sensitivity testing, resulting in isolation of Staphylococcus aureus. The cat was discharged ambulatory and eventually resumed normal gait. This is the first report of spinal epidural empyema and osteomyelitis and the third report of the former in cats. Computed tomographyguided fine needle aspiration from the vertebral lesion was helpful for diagnosing the cause of lesion and a rapid surgical decompression was beneficial.
Electromagnetic wave reflection by rough fractal surface of semiconductor materials

In the given work the rough surface of semiconductor is modeling by 2D fractal Wierstrass function. On the basis of the Kirchhoff scalar theory the scattering indicatrices for the some types od scattering surfaces are present. On the basis of numerical accounts average scattering coefficient the diagrams of dependence for various fractal semiconductor surfaces was constructed.
Generating Minimal Definite Descriptions

The incremental algorithm introduced in (Dale and Reiter, 1995) for producing distinguishing descriptions does not always generate a minimal description. In this paper, I show that when generalised to sets of individuals and disjunctive properties, this approach might generate unnecessarily long and ambiguous and/or epistemically redundant descriptions. I then present an alternative, constraint-based algorithm and show that it builds on existing related algorithms in that (i) it produces minimal descriptions for sets of individuals using positive, negative and disjunctive properties, (ii) it straightforwardly generalises to n-ary relations and (iii) it is integrated with surface realisation.
Simple and Efficient Traversal Methods for Quadtrees and Octrees

Abstract Quadtrees and octrees are used extensively throughout computer graphics and in many other diverse fields such as computer vision, robotics, and pattern recognition. Managing information stored in quadtrees and octrees requires basic tree traversal operations such as point location, region location, and neighbor searches. This paper presents simple and efficient methods for performing these operations that are inherently nonrecursive and reduce the number of comparisons with poor predictive behavior. The methods are table-free, thereby reducing memory accesses, and generalize easily to higher dimensions. Source code is available online.
Rhythm modeling, visualizations and applications

People use their awareness of others' temporal patterns to plan work activities and communication. This paper presents algorithms for programatically detecting and modeling temporal patterns from a record of online presence data. We describe analytic and end-user visualizations of rhythmic patterns and the tradeoffs between them. We conducted a design study that explored the accuracy of the derived rhythm models compared to user perceptions, user preference among the visualization alternatives, and users' privacy preferences. We also present a prototype application based on the rhythm model that detects when a person is "away" for an extended period and predicts their return. We discuss the implications of this technology on the design of computer-mediated communication.
Immunization with reverse-genetics-produced H5N1 influenza vaccine protects ferrets against homologous and heterologous challenge.

BACKGROUND Multiple cases of transmission of avian H5N1 influenza viruses to humans illustrate the urgent need for an efficacious, cross-protective vaccine. METHODS Ferrets were immunized with inactivated whole-virus vaccine produced by reverse genetics with the hemagglutinin (HA) and neuraminidase genes of A/HK/213/03 virus. Ferrets received a single dose of vaccine (7 or 15 microg of HA) with aluminum hydroxide adjuvant or 2 doses (7 microg of HA each) without adjuvant and were challenged with 10(6) 50% egg infectious doses of A/HK/213/03, A/HK/156/97, or A/Vietnam/1203/04 virus. RESULTS One or 2 doses of vaccine induced a protective antibody response to the vaccine strain. All immunization regimens completely protected ferrets from challenge with homologous wild-type A/HK/213/03 virus: no clinical signs of infection were observed, virus replication was significantly reduced (P<.05) and was restricted to the upper respiratory tract, and spread of virus to the brain was prevented. Importantly, all vaccinated ferrets were protected against lethal challenge with the highly pathogenic strain A/Vietnam/1203/04. The 2-dose schedule induced higher levels of antibodies that were cross-reactive to antigenically distinct H5N1 viruses. CONCLUSIONS H5N1 vaccines may stimulate an immune response that is more cross-protective than what might be predicted by in vitro assays and, thus, hold potential for being stockpiled as "initial" pandemic vaccines.
ICI Canceling Space-Frequency Block Code for MISO-OFDM in Fast Fading Channels

An intercarrier interference (ICI) canceling technique for multiple-input single-output (MISO) orthogonal frequency division multiplexing (OFDM) systems in fast fading channels is proposed. The proposed scheme consists of a linear space-frequency block code (SFBC) at the transmitter and a receive frequency block code (RFBC) at the receiver. The code design is based on the upper bound of pairwise error probability (PEP) which is derived under assumptions and approximations stated. Specifically, the proposed code is designed to minimize the upper bound of the PEP. The simulation results demonstrate that the proposed technique outperforms the conventional methods in fast fading environments.
Financial model-base construction for flexible model manipulation of models and solvers

As financial markets are volatile and rapidly changing, preciseness and agility in price evaluation and risk assessment in the portfolios are more important and decision support systems containing diverse financial products and pricing algorithms have been adopted to support those quantitative analysis tasks. To effectively use the financial DSS, the trader should be able to know which algorithms are applicable to a specific product and to match flexibly the product with appropriate algorithms depending on his product-evaluation purposes. This paper proposes model-base construction mechanisms in a financial DSS that facilitates such mix-and-match operations between financial products (considered as models) and pricing algorithms (considered as solvers). As a conceptual framework for the model-base, we use the generic model concept for developing system constructs and procedures. The constructs and procedures of the model-base are represented as self-contained and well-modularized objects that can be applied to a wide variety of problem domains.
From Global to Local Similarities: A Graph-Based Contextualization Method using Distributional Thesauri

After recasting the computation of a distributional thesaurus in a graph-based framework for term similarity, we introduce a new contextualization method that generates, for each term occurrence in a text, a ranked list of terms that are semantically similar and compatible with the given context. The framework is instantiated by the definition of term and context, which we derive from dependency parses in this work. Evaluating our approach on a standard data set for lexical substitution, we show substantial improvements over a strong non-contextualized baseline across all parts of speech. In contrast to comparable approaches, our framework defines an unsupervised generative method for similarity in context and does not rely on the existence of lexical resources as a source for candidate expansions.
Strain analysis in advanced tool forming process with spline finite strip (SFS) method

Roll forming is one of the important advanced metal forming processes. Simulation is an effective method to study the geometrical and the mechanical character of the strip deformation between the rolls. The spline finite strip method (SFSM) has been developed to simulate the cold forming process. The solution procedures of SFSM are given. The forming processes of four types of sections: electrical resistance welded pipe, channel section, channel section with outer edge and non-symmetrical channel section, were simulated by SFSM. The transverse membrane strain, longitudinal membrane strain and displacement of the deformed strip were obtained.
Azemiopsin from Azemiops feae Viper Venom, a Novel Polypeptide Ligand of Nicotinic Acetylcholine Receptor

Background: Venoms from rare snake species may contain toxins of new structural or/and pharmacological types. Results: Amino acid sequence of the new polypeptide azemiopsin isolated from Azemiops feae viper venom was established, and its biological activity was determined. Conclusion: Azemiopsin is the first natural toxin that blocks nicotinic acetylcholine receptors and does not contain disulfide bridges. Significance: Azemiopsin is the first member of a new toxin group. Azemiopsin, a novel polypeptide, was isolated from the Azemiops feae viper venom by combination of gel filtration and reverse-phase HPLC. Its amino acid sequence (DNWWPKPPHQGPRPPRPRPKP) was determined by means of Edman degradation and mass spectrometry. It consists of 21 residues and, unlike similar venom isolates, does not contain cysteine residues. According to circular dichroism measurements, this peptide adopts a β-structure. Peptide synthesis was used to verify the determined sequence and to prepare peptide in sufficient amounts to study its biological activity. Azemiopsin efficiently competed with α-bungarotoxin for binding to Torpedo nicotinic acetylcholine receptor (nAChR) (IC50 0.18 ± 0.03 μm) and with lower efficiency to human α7 nAChR (IC50 22 ± 2 μm). It dose-dependently blocked acetylcholine-induced currents in Xenopus oocytes heterologously expressing human muscle-type nAChR and was more potent against the adult form (α1β1ϵδ) than the fetal form (α1β1γδ), EC50 being 0.44 ± 0.1 μm and 1.56 ± 0.37 μm, respectively. The peptide had no effect on GABAA (α1β3γ2 or α2β3γ2) receptors at a concentration up to 100 μm or on 5-HT3 receptors at a concentration up to 10 μm. Ala scanning showed that amino acid residues at positions 3–6, 8–11, and 13–14 are essential for binding to Torpedo nAChR. In biological activity azemiopsin resembles waglerin, a disulfide-containing peptide from the Tropidechis wagleri venom, shares with it a homologous C-terminal hexapeptide, but is the first natural toxin that blocks nAChRs and does not possess disulfide bridges.
SceneSeer: 3D Scene Design with Natural Language

Designing 3D scenes is currently a creative task that requires significant expertise and effort in using complex 3D design interfaces. This effortful design process starts in stark contrast to the easiness with which people can use language to describe real and imaginary environments. We present SceneSeer: an interactive text to 3D scene generation system that allows a user to design 3D scenes using natural language. A user provides input text from which we extract explicit constraints on the objects that should appear in the scene. Given these explicit constraints, the system then uses a spatial knowledge base learned from an existing database of 3D scenes and 3D object models to infer an arrangement of the objects forming a natural scene matching the input description. Using textual commands the user can then iteratively refine the created scene by adding, removing, replacing, and manipulating objects. We evaluate the quality of 3D scenes generated by SceneSeer in a perceptual evaluation experiment where we compare against manually designed scenes and simpler baselines for 3D scene generation. We demonstrate how the generated scenes can be iteratively refined through simple natural language commands.
Event tactic analysis based on player and ball trajectory in broadcast video

Most of existing approaches on sports video analysis are concentrated on semantic event detection which is general audience oriented and the extracted events are presented to the audience without further analysis from tactic perspective. In this paper, we propose a novel approach to extract the tactic information and recognize the tactic patterns from goal events in broadcast soccer video. We extract the goal events with far-view shots using the analysis and alignment of web-casting text and broadcast video. For a detected goal event, a multi-object detection and tracking algorithm is employed to obtain the players and ball trajectories. An effective tactic representation called aggregate trajectory are constructed based on multi-object trajectories using a novel analysis of temporal-spatial interaction among the players and ball. The interactive relationship of aggregate trajectory and the hypothesis testing of the trajectory temporal-spatial distribution are employed to discover the tactic patterns in a hierarchical coarse-to-fine framework. The experimental results on FIFA World Cup 2006 show that the proposed approach is more effective than our previous work.
Optimization of Slow Light in Slotted Photonic Crystal Waveguide With Liquid Infiltration

Slow light in slotted photonic crystal waveguide (SPCW) has been theoretically optimized with the post-fabrication technology of liquid infiltration. By choosing the refractive indices that infiltrated in the first and second rows of air holes adjacent to the slot, SPCW was optimized to possess wideband slow light with high group index and low dispersion. Simulation results showed that the slow light in SPCW for the same structure could be optimized with nearly constant group indices of 50, 82.5, 150, and 176 over 6.9 nm, 3.1 nm, 1.65 nm, and 1.15 nm bandwidths. Then, it was demonstrated that this method has the potential for realizing reconfigurable SPCW, in which the tunable slow light could be obtained. Besides, the capability to control the slow light properties after fabrication was interesting to compensate fabrication imperfections, and it was particularly interesting to realize temperature-stable SPCW devices. The preliminary results of this study have provided important theoretical basis for the potential application offered by the SPCW in future optical technologies.
Local Graph Clustering and Applications to Graph Partitioning

Today there exist innumerable applications which require the analysis of some type of large graph. Social networks useful to social scientists, protein interaction and neural networks arising in biological problems, as well as geometric meshes used in many diverse scientific applications, have grown, thanks to the availability and abundance of data, to tremendous proportions. Besides the sheer size of some of these datasets – the world wide web, for example, is estimated to contain at least 4.75 billion pages [11] – the analysis of even moderately large networks, on the order of tens of thousands of vertices, poses a significant challenge when researches need information beyond basic metrics such as the degree distribution. The NP-complete problem of finding an optimal clustering of vertices within one of these networks, for example, has been under investigation for over a decade by various scientific communities, including data mining, computational biology, and combinatorics.
Optimal Piecewise-Linear Approximation of the Quadratic Chaotic Dynamics

This paper shows the influence of piecewiselinear approximation on the global dynamics associated with autonomous third-order dynamical systems with the quadratic vector fields. The novel method for optimal nonlinear function approximation preserving the system behavior is proposed and experimentally verified. This approach is based on the calculation of the state attractor metric dimension inside a stochastic optimization routine. The approximated systems are compared to the original by means of the numerical integration. Real electronic circuits representing individual dynamical systems are derived using classical as well as integratorbased synthesis and verified by time-domain analysis in Orcad Pspice simulator. The universality of the proposed method is briefly discussed, especially from the viewpoint of the higher-order dynamical systems. Future topics and perspectives are also provided.
Distribution of Misfolded Prion Protein Seeding Activity Alone Does Not Predict Regions of Neurodegeneration

Protein misfolding is common across many neurodegenerative diseases, with misfolded proteins acting as seeds for "prion-like" conversion of normally folded protein to abnormal conformations. A central hypothesis is that misfolded protein accumulation, spread, and distribution are restricted to specific neuronal populations of the central nervous system and thus predict regions of neurodegeneration. We examined this hypothesis using a highly sensitive assay system for detection of misfolded protein seeds in a murine model of prion disease. Misfolded prion protein (PrP) seeds were observed widespread throughout the brain, accumulating in all brain regions examined irrespective of neurodegeneration. Importantly, neither time of exposure nor amount of misfolded protein seeds present determined regions of neurodegeneration. We further demonstrate two distinct microglia responses in prion-infected brains: a novel homeostatic response in all regions and an innate immune response restricted to sites of neurodegeneration. Therefore, accumulation of misfolded prion protein alone does not define targeting of neurodegeneration, which instead results only when misfolded prion protein accompanies a specific innate immune response.