Miracle-dz/UniFAR-FTUs huggingface dataset:
D G ] 1 6 Ju n 20 07 3-quasi-Sasakian manifolds

In the present paper we carry on a systematic study of 3-quasi-Sasakian manifolds. In particular we prove that the three Reeb vector fields generate an involutive distribution determining a canonical totally geodesic and Riemannian foliation. Locally, the leaves of this foliation turn out to be Lie groups: either the orthogonal group or an abelian one. We show that 3-quasi-Sasakian manifolds have a well-defined rank, obtaining a rank-based classification. Furthermore, we prove a splitting theorem for these manifolds assuming the integrability of one of the almost product structures. Finally, we show that the vertical distribution is a minimum of the corrected energy. 2000 Mathematics Subject Classification. 53C15, 53C25, 53C26.
An Evolutionary Connectionist Fuzzy System for Multispectral Data Classification

In this paper, numerical exemplars are used in a training method to find the structure of a fuzzy-neural network. After this structure learning, a genetic algorithm is applied to determine the initial weights of the neural network, thereby guiding the neural network to a nearoptimal initialization. These well-initialized networks are then trained with backpropagation algorithm. Using this proposed approach, the local minimum phenomenon, which may cause the learning process to stagnate, can be avoided. Overall learning performance is, thus, significantly improved. The proposed method has been implemented and tested on the Thematic Mapper sensor system (TM) data to get the fractional representation of each class within a pixel. Results show the potential of the proposed method for this kind of applications.
Seasonal variation of mono- and sesquiterpene emission rates of Scots pine

Abstract. The seasonal variation of mono-and sesquiterpene emission rates of Scots pine was measured from April to October in 2004. The emission rates were measured daily in the afternoons with the exception of weekends. Emissions were measured from two branches; one of them was debudded in May (branch A), while the other was allowed to grow new needles (branch B). The monoterpene emission pattern remained almost constant throughout the measurement period, Δ3-carene being the dominant monoterpene (50-70% of the VOC emission). The standard monoterpene emission potential (30°C) was highest during early summer in June (the average of the two branches 1.35 µg g-1h-1) and lowest during early autumn in September (the average of the two branches 0.20 µg g-1h-1. The monoterpene emission potential of branch A remained low also during October, whereas the emission potential of branch B was very high in October. The sesquiterpenes were mainly emitted during mid summer, the dominant sesquiterpene being β-caryophyllene. Branch A had a higher sesquiterpene emission potential than branch B and the emission maximum occurred concomitant with the high concentration of airborne pathogen spores suggesting a potential defensive role of the sesquiterpene emissions. The sesquiterpene emissions were well correlated with linalool and 1,8-cineol emissions, but not with monoterpenes. Sesquiterpene and 1,8-cineol emissions were equally well described by the temperature dependent and the temperature and light dependent algorithms. This is due to the saturation of the light algorithm as the measurements were always conducted during high light conditions.
A Clustering Algorithm Based on Symmetric Neighborhood of Micro-clusters

Clustering is an important task in data mining with numerous applications, including minefield detection, seismology, astronomy, etc. At present, the academic communities have introduced various clustering algorithms, and these methods have been widely applied to different fields according to their respective characteristics. In this paper, we propose a novel clustering algorithm based on symmetric neighborhood of micro-clusters in large database. Firstly we use k-means algorithm to produce micro-clusters which are introduced to compress the data, and then calculate both neighbors and reverse neighbors of micro-clusters to estimate their densities distribution, and gain the ultimate clustering result. The algorithm can discover arbitrary shape and different densities, and also it needs fewer input parameters than the existing clustering algorithms, such as, k-means algorithm. The efficiencies and effectiveness of the algorithm are validated through the test of IRIS testing dataset and synthetic dataset.
DFT implementation aspects and techniques suitable for VLSI implementation: A survey

This paper explains design essentials for VLSI implementation of DFT algorithms. For applications such as Asynchronous Digital Subscriber Line (ADSL), Digital Video Broadcasting (DVB), and Orthogonal Frequency Division Multiplexing (OFDM) digital signal processing algorithms are a necessity. Hardware designed has to align area, power and performance trade-off's. FFT (Fast Fourier Transform) is used for efficient evaluation of DFT (Discrete Fourier Transform). Paper surveys techniques such as pipelining, systolic architectures and CORDIC based architectures to achieve optimization in these FFT algorithms with respect to the applications.
A novel wireless inkjet-printed chipless sensor for moisture detection utilizing carbon nanotube

A new chipless sensor for water droplet detection is proposed. This concept is demonstrated by inkjet-printing a dual rhombic loop scatterer on a flexible substrate having a size of 4×2cm2 only. This sensor operates in the ISM band at 2.45 GHz. The scatterer is doped with a thin layer of carbon nanotube-based organic ink to enhance its sensitivity in the presence of water. Strong water molecule adsorption by the carbon nanotubes helps to detect and record when a water drop has been in contact with the sensor. The sensor's electromagnetic response is modified permanently so that a “water event” can be detected later. Simulation and wireless measurement results validate this new concept.
Conical-Beam Circularly-Polarized Microstrip Antenna Array for Ceiling Mount Doppler Sensors

—A conical-beam circularly-polarized microstrip antenna array composed of four square-shaped radiating elements has been proposed. In the presented antenna array all of radiating elements are fed with equal-amplitude and in-phase signals and the excitation signal is guided to the center of the array through the via, to achieve both appropriate polarization properties and the conical radiation pattern. The paper includes the design details as well as simulation and measurement results of the manufactured antenna array designated for ceiling mount Doppler sensors operating at 10.5 GHz.
Slow recovery from inactivation regulates the availability of voltage‐dependent Na+ channels in hippocampal granule cells, hilar neurons and basket cells

1 Fundamental to the understanding of CNS function is the question of how individual neurons integrate multiple synaptic inputs into an output consisting of a sequence of action potentials carrying information coded as spike frequency. The availability for activation of neuronal Na+ channels is critical for this process and is regulated both by fast and slow inactivation processes. Here, we have investigated slow inactivation processes in detail in hippocampal neurons. 2 Slow inactivation was induced by prolonged (10‐300 s) step depolarisations to ‐10 mV at room temperature. In isolated hippocampal dentate granule cells (DGCs), recovery from this inactivation was biexponential, with time constants for the two phases of slow inactivation τslow,1 and τslow,2 ranging from 1 to 10 s and 20 to 50 s, respectively. Both τslow,1 and τslow,2 were related to the duration of prior depolarisation by a power law function of the form τ(t) =a (t/a)b, where t is the duration of the depolarisation, a is a constant kinetic setpoint and b is a scaling power. This analysis yielded values of a= 0.034 s and b= 0.62 for τslow,1 and a= 24 s and b= 0.30 for τslow,2 in the rat. 3 When a train of action potential‐like depolarisations of different frequencies (50, 100, 200 Hz) was used to induce inactivation, a similar relationship was found between the frequency of depolarisation and both τslow,1 and τslow,2 (a= 0.58 s, b= 0.39 for τslow,1 and a= 3.77 s and b= 0.42 for τslow,2). 4 Using nucleated patches from rat hippocampal slices, we have addressed possible cell specific differences in slow inactivation. In fast‐spiking basket cells a similar scaling relationship can be found (a= 3.54 s and b= 0.39) as in nucleated patches from DGCs (a= 2.3 s and b= 0.48) and non‐fast‐spiking hilar neurons (a= 2.57 s and b= 0.49). 5 Likewise, comparison of human and rat granule cells showed that properties of ultra‐slow recovery from inactivation are conserved across species. In both species ultra‐slow recovery was biexponential with both τslow,1 and τslow,2 being related to the duration of depolarisation t, with a= 0.63 s and b= 0.44 for τslow,1 and a= 25 s and b= 0.37 for τslow,2 for the human subject. 6 In summary, we describe in detail how the biophysical properties of Na+ channels result in a complex interrelationship between availability of sodium channels and membrane potential or action potential frequency that may contribute to temporal integration on a time scale of seconds to minutes in different types of hippocampal neurons.
The Applied Research of Convolutional Turbo Code Based on WiMAX Protocol

Because most practical communication systems need possessing higher bandwidth efficiency, this article increases the bandwidth efficiency through the two aspects of code rate and modulation mode, that is, by combining CTC(convolutional turbo code) in WiMax protocol with MSK modulation and applying them in the practical communication systems. The simulation result shows the combination of CTC and MSK modulation possesses not only a stronger error correcting capability but also a higher bandwidth efficiency, i.e. , it's more applicable in the practical communication systems.
On the Use of SVMs to Detect Anomalies in a Stream of SIP Messages

Voice and multimedia communications are rapidly migrating from traditional networks to TCP/IP networks (Internet), where services are provisioned by SIP (Session Initiation Protocol). This paper proposes an on-line filter that examines the stream of incoming SIP messages and classifies them as good or bad. The classification is carried out in two stages: first a lexical analysis is performed to weed out those messages that do not belong to the language generated by the grammar defined by the SIP standard. After this first stage, a second filtering occurs which identifies messages that somehow differ - in structure or contents - from messages that were previously classified as good. While the first filter stage is straightforward, as the classification is crisp (either a messages belongs to the language or it does not), the second stage requires a more delicate handling, as it is not a sharp decision whether a message is semantically meaningful or not. The approach we followed for this step is based on using past experience on previously classified messages, i.e. a "learn-by-example" approach, which led to a classifier based on Support-Vector-Machines (SVM) to perform the required analysis of each incoming SIP message. The paper describes the overall architecture of the two-stage filter and then explores several points of the configuration-space for the SVM to determine a good configuration setting that will perform well when used to classify a large sample of SIP messages obtained from real traffic collected on a VoIP installation at our institution. Finally, the performance of the classification on additional messages collected from the same source is presented.
Satisfiability of Elastic Demand in the Smart Grid

We study a stochastic model of electricity production and consumption where appliances are adaptive and adjust their consumption to the available production, by delaying their demand and possibly using batteries. The model incorporates production volatility due to renewables, ramp-up and ramp-down time, uncertainty about actual demand versus planned production, delayed and evaporated demand due to adaptation to insufficient supply. We study whether threshold policies stabilize the system. The proofs use Markov chain theory on general state space.
Fair Information Practices: A Basic History - Version 2.20

This report offers a history of Fair Information Practices (FIPs) with a focus – but not an exclusive one – on activities in the United States. The text usually quotes key portions of source documents in order to allow for comparison of different versions of FIPs. For the most part, the analysis is neutral, with only limited interpretation, comment, and criticism. FIPs are a set of internationally recognized practices for addressing the privacy of information about individuals. Information privacy is a subset of privacy. FIPs are important because they provide the underlying policy for many national laws addressing privacy and data protection matters. The international policy convergence around FIPs as core elements for information privacy has remained in place since the late 1970s. Privacy laws in the United States, which are much less comprehensive in scope than laws in some other countries, often reflect some elements of FIPs but not as consistently as the laws of most other nations.
Design of a self-aligning 3-DOF actuated exoskeleton for diagnosis and training of wrist and forearm after stroke

Rehabilitation robotics provides a means of objectively quantifying patient condition before, during and after treatment. This paper describes the design and preliminary validation results of a novel rehabilitation device for the human wrist and forearm. The design features two key aspects: 1) it performs dynamical self-alignment to compensate for misalignment of the human limb and 2) it assists movements within almost the full natural range of motion. Self-alignment is performed by a linkage of parallelograms that allows torque-driven actuation. Advantages are decreased user-device interaction forces and lower don/doff-and setup-times. The full natural range of motion in Flexion/Extension, Radial/Ulnar-deviation and Pronation/Supination allows patients to perform ADL-like exercises during training. Furthermore, in the current design the hand and fingers remain free to perform grabbing activities and the open structure provides simple connection to the patients limb.
Ultrasound-Triggered Phase Transition Sensitive Magnetic Fluorescent Nanodroplets as a Multimodal Imaging Contrast Agent in Rat and Mouse Model

Ultrasound-triggered phase transition sensitive nanodroplets with multimodal imaging functionality were prepared via premix Shirasu porous glass (SPG) membrane emulsification method. The nanodroplets with fluorescence dye DiR and SPIO nanoparticles (DiR-SPIO-NDs) had a polymer shell and a liquid perfluoropentane (PFP) core. The as-formed DiR-SPIO-NDs have a uniform size of 385±5.0 nm with PDI of 0.169±0.011. The TEM and microscopy imaging showed that the DiR-SPIO-NDs existed as core-shell spheres, and DiR and SPIO nanoparticles dispersed in the shell or core. The MTT and hemolysis studies demonstrated that the nanodroplets were biocompatible and safe. Moreover, the proposed nanodroplets exhibited significant ultrasound-triggered phase transition property under clinical diagnostic ultrasound irradiation due to the vaporization of PFP inside. Meanwhile, the high stability and R2 relaxivity of the DiR-SPIO-NDs suggested its applicability in MRI. The in vivo T2-weighted images of MRI and fluorescence images both showed that the image contrast in liver and spleen of rats and mice model were enhanced after the intravenous injection of DiR-SPIO-NDs. Furthermore, the ultrasound imaging (US) in mice tumor as well as MRI and fluorescence imaging in liver of rats and mice showed that the DiR-SPIO-NDs had long-lasting contrast ability in vivo. These in vitro and in vivo findings suggested that DiR-SPIO-NDs could potentially be a great MRI/US/fluorescence multimodal imaging contrast agent in the diagnosis of liver tissue diseases.
Security analysis of the time-coding quantum key distribution protocols

We report on the security analysis of time-coding quantum key distribution protocols. The protocols make use of coherent single-photon pulses. The key is encoded in the photon time-detection. The use of coherent superposition of states allows to detect eavesdropping of the key. We give a mathematical model of a first protocol from which we derive a second, simpler, protocol. We derive the security analysis of both protocols and find that the secure rates can be similar to those obtained with the BB84 protocol. We then calculate the secure distance for those protocols over standard fibre links. When using low-noise superconducting single photon detectors, secure distances over 200 km can be foreseen. Finally, we analyse the consequences of photon-number splitting attacks when faint pulses are used instead of single photon pulses. A decoy states technique can be used to prevent such attacks.
Long Range Passive UHF RFID System Using HVAC Ducts

In this paper, the use of hollow metal heating, ventilating, and air-conditioning (HVAC) ducts as a potential communication channel between passive ultrahigh-frequency (UHF) radio-frequency identification (RFID) readers and tags is studied. HVAC ducts behave as electromagnetic waveguides with much lower signal attenuation compared to free-space propagation. This low-loss electromagnetic environment allows one to greatly increase the communication range of passive UHF RFID systems and build, for example, a long range passive sensor network spanning an entire infrastructure such as a large building. In this work, it is shown both theoretically and experimentally that the read range of passive UHF RFID systems can be increased by multiple times compared to operation in a free-space environment.
Concurrent dual-band 1.8/2.4 GHz LNA using miller effect of the gate-drain capacitor

Future wireless devices become multi-mode communication systems in order to handle different standards. This paper presents a concurrent dual-band 1.8 and 2.4GHz low noise amplifier (LNA) in response to the growing market demands for more effective LNA's with a low supply voltage and power consumption. The impedance matching of the proposed LNA targeting the Wireless Local Area Network (WLAN) frequencies was obtained using the Miller effect of the intrinsic gate-drain capacitor, and using a Particle swarm optimization (PSO) technique. A folded cascode topology structure and the implementation of a forward body biased technique were employed for the reduction of the supply voltage. The proposed LNA performed well under a supply voltage of 0.3V consuming only 1.4mW of power. The LNA exhibited a power gain of 22dB and 18dB and an input return loss of -25dB and -33dB at the 1.8 and 2.4GHz band frequencies, respectively. The noise figure was below the required 2dB in both frequency bands.
A statistical model of timbre perception

We describe a perceptual space for timbre, define an objective metric that takes into account perceptual orthogonality and measure the quality of timbre interpolation. We discuss two timbre representations and measure perceptual judgments on an equivalent range of timbre variety. We determine that a timbre space based on Mel-frequency cepstral coefficients (MFCC) is a good model for a perceptual timbre space.
Compliance and the Enforcement of EU Law

Introduction 1. Compliance and What EU Member States Make of It 2. The Governance of Compliance 3. Article 258/260 TFEU Infringement Procedures: The Commission Perspective in Environmental Cases 4. From the Velvet Glove to the Iron Fist: Criminal Sanctions for the Enforcement of Union Law 5. The Role of National Constitutional Courts in Issues of Compliance 6. The Role of National Courts in Inducing Compliance with International and European Law - A Comparison
Generating Textual Explanations of Psychological Expressions Using Support Vector Machines Insu

An explanation capability is crucial in securitysensitive domains such as medical applications. Although support vector machines (SVMs) have shown superior performance in a range of classification and regression tasks, SVMs like artificial neural networks (ANNs) lack an explanatory capability. There is a significant literature on obtaining human-comprehensible rules from SVMs and ANNs in order to explain “how” a decision was made or “why” a certain result was achieved, and this paper proposes a novel approach for SVM classifiers. The experiments describe a first attempt to generating textual explanations to “why” certain text contents are depressing or funny using a decompositional approach. Learned model parameters are analysed to select informative feature components and filtering is applied to select subsets of more relevant components. Explanation components are then used to rank basic conceptconstructs called predicates, which are generated and ranked using a commonsense database. The ranked predicates are then used to generate textual explanations of classification results. We show that the explanations are consistent and that the accuracy of SVM models are bounded by the accuracy of explanation components. In further experiments, generated explanation components are used to classify the sample data. The results show that the generated explanations display a high level of fidelity.
Silaffins of Diatoms: From Applied Biotechnology to Biomedicine

Silaffins are involved in the formation of the cell walls of diatoms. It is known that silaffins can precipitate silica in vitro, forming nano- and micro-particles in the shape of spheres and plates containing many pores. It is important to note that the deposition of silica and the particle morphology in the presence of silaffins affects chemical and physical agents (e.g., peptides, polyamines, phosphate, nitrogen, and the mechanical changes of the reaction mixture). It is believed that silaffins act as an organic matrix for silica-genesis and that silica pore size should reflect the pattern of a matrix. Here, biotechnology related to silaffins is discussed in the context of “a hypothesis of silaffin matrix” and “the LCPA-phosphate model”. We discuss the most promising area of silaffin biotechnology—the development of production methods for silicon structures with desired shapes and nanostructural properties that can be used to create biocompatible materials.
Discipline Reform: The Impact of a Statewide Ban on Suspensions for Truancy

Abstract Chronic absenteeism and truancy have been linked to a variety of undesirable outcomes for students including increased risk of dropout, lower test scores, lower educational and social engagement, juvenile delinquency, and substance abuse. One controversial response to truancy is the use of exclusionary discipline, such as out-of-school suspensions (OSS). Out of concern that such a practice is counter-intuitive and likely not effective at improving student engagement or academic outcomes, some states have recently banned this practice altogether. This analysis uses Arkansas as a case study to estimate the impact of a state-level ban on the use of OSS for truancy on attendance—an important measure related to student engagement and opportunity to learn. Using an eight-year panel of student-level data in a difference-in-differences framework, we find no evidence of improvement in attendance for truant students. Implications for policy design, implementation, and evaluation are discussed.