Miracle-dz/UniFAR-FTUs huggingface dataset:
Negation in Spatial Reasoning A Computational Approach

In recent years a lot of research has been done in order to determine factors of complexity in spatial relational reasoning, like the number of models, the wording of conclusion or the influence of rela- tional complexity. But research so far focused on affirmative statements only, i. e. negated expressions have not yet been investigated. In spatial reasoning and in human machine interaction, however, negation plays a fundamental role. Central questions are: How are negated statements represented? What happens in multiple-model cases? Which effects have different reference frames? We conducted three experiments to show that humans (i) negate a relation by using the opposite relation, (ii) construct preferred mental models and use an economic principle, and (iii) have more difficulties in reasoning with negated relations. The goal is to ex- tend our cognitive and computational model - the SRM.
Power coupling characteristics between FBG and back-scattering signals

The property and compatibility between fiber Bragg grating (FBG) and back-scattering signals are investigated by employing optical time domain reflectometry. We compare the power spectrums of spontaneous Brillouin scattering (SpBS), simultaneous Brillouin scattering (SBS) and Rayleigh scattering (RS), and coupling mechanism between FBG and back-scattering signal is explored. Experimental results show that the region of FBG contributes to the backscatter power and causes the desired reflection, and the power peak of FBG in SBS power spectrum is the sharpest among back-scattering light power spectrums and broadens with the decrease of spatial resolution. Moreover, the FBG-based method is used to find the location of temperature or stain event for scatter-based distributed sensors.
Spurious resonance free bulk acoustic wave resonators

In this paper a device structure eliminating the spurious modes arising from lateral standing Lamb waves is presented. The operating principle behind the device is described with the use of a simple model. Experimental results of ZnO and AlN based resonators in SMR configuration are given. Laser interferometer measurements are presented that confirm applicability of the idea.
Discontinuous Petrov-Galerkin methods with optimal test spaces for convection dominated convection-diffusion equations

In this thesis, Discontinuous Petrov-Galerkin (DPG) finite element methods are developed for convection-diffusion equations. In particular, this thesis focuses on the use of optimal test spaces. A convection-diffusion equation is a singularly perturbed problem. That is, the nature of the problem changes when the diffusion term vanishes, which makes it challenging to solve numerically for small diffusion values, i.e. when convection dominates. Standard finite element methods give very unsatisfactory results, producing approximations that exhibit spurious oscillations and other nonphysical behavior. Recently, a class of finite element methods has been developed, in which optimal test spaces are used. These spaces guarantee that one gets the best approximation from the trial space in which the solution is sought. The methods are examples of least-squares methods, with the special property that one can choose the norm in which the residual is minimized. This freedom of choice allows us to control the norm in which the best approximation is obtained. The new approach in this thesis is that the variational formulation associated with the convection-diffusion problem also gives a well-posed variational formulation of the limit convection problem if the diffusion term vanishes. This is necessary in order to retain stability, and to make sure that the computational cost does not grow, when the diffusion term decreases. Special attention is paid to the transport problem which, besides being the limit problem for vanishing diffusion, also has other applications. A new method is introduced that outperforms existing methods in convergence rates, but also in reducing the smearing of discontinuities of solutions. The theory developed in this thesis is illustrated by various numerical results.
Phenomenological model of dielectric properties for PMN-PT

ABSTRACT The temperature behavior of the dielectric properties of PMN-PT has been considered in the framework of phenomenological theory of phase transitions in the systems with defects. The results are presented for the region of the diffuse phase transition, where dynamics of the charge localization on defects affects the dielectric properties. The consideration has been performed on the basis of simple thermodynamic ideas.
Ex situ and in situ sensitized quantum dot solar cells

Although quantum dot‐sensitized solar cells (QDSCs) prepared with in situ sensitized wide‐band gap semiconductor nanorods are commonly reported, very few examples of the ex situ sensitization of these nanorods are known. They usually result in poor solar cell performance parameters. In this work, we have tested the photovoltaic application of both ex situ and in situ sensitized ZnO nanorods by linker‐assisted attachment and by the successive ionic layer adsorption and reaction (SILAR) technique, respectively. For the ex situ sensitization, instead of classical spherical QDs, we used quasi two‐dimensional CdSe nanoplatelets (NPLs) of controlled thicknesses, the photovoltaic application of which has never been reported before. Regarding the in situ sensitization, the photoanodes were characterized by XRD, UV–VIS absorption, and Raman spectroscopy during deposition, which helped to better understand the formation of CdSe QDs nanostructured ZnO surface. Devices incorporating in situ sensitized ZnO nanorods demonstrated superior performance compared to the best measured efficiencies of QDSCs prepared with ex situ sensitization, and their J–V characteristics were more reproducible.
Low power NiN-based resistive switching memory device using Ti doping

In this study, we investigated the properties of Ti-doped NiN-based resistive switching random access memories (ReRAMs) in comparison with both Al-doped and conventional NiN-based samples. The Ti dopants form metallic TiN particles in the nitride film, which induce local electric fields during the forming process causing filaments to form close to the TiN clusters. The TiN components in the filaments reduce the current level for the high resistive switching state (HRS) and low resistive switching state (LRS). In our testing, the Ti-doped sample had a current of 10 nA in the HRS and 23 μA in the LRS with a high on/off ratio (>103). This implies that the Ti doping effect enabled the sample to operate at low power. Furthermore, the Ti-doped samples also exhibited highly uniform operating parameters. In terms of reliability, the retention was measured to be >106 s at 85 °C, and the endurance was found to be at least 107 cycles. These results indicate that Ti-doped NiN-based ReRAM devices have significant adva.
The interplay among various durational units in Japanese stop quantity distinction

This talk gives a summary of several studies that examined native speakers’ production and perception of singleton and geminate stops in Japanese, focusing on the use of duration. Although the major acoustic correlate and perceptual cue to this distinction is known to be duration of stop closure, there have been various ideas as to what is the single speech unit to which the closure duration relates most reliably in distinguishing this stop quantity. Candidates for such a unit that emerged as results of different production and perception experiments have been: the preceding vowel, the preceding mora, the following vowel, the disyllable, and the word of any length. How should we interpret these seemingly different results? Do these units stand stable against durational variability such as different speakers, speaking rates, segmental composition, and length of words?
Tissue dissection using a 1470-nm diode laser and laparoscopic prototype

A continuous-wave, 40 Watt, 1470 nm laser was explored for rapid and precise dissection of porcine mesentery fascia and liver tissues, ex vivo. Laser energy was delivered through a 550-μm-core optical fiber inside a 5-mm-OD, laparoscopic probe, with detachable, 2 mm, sapphire ball rolling tip. Fascia tissue was cleanly dissected with scanning rates from 2.0 - 4.5 mm/s using 16 - 31W. Fascia collateral thermal damage measured as low as 180 ± 50 μm at 4.5 mm/s scan speed. Porcine liver ablation crater depth measured up to 1010 ± 220 μm with 30 W at 2.0 mm/s or as shallow as 80 ± 30 μm with 10 W at 10 mm/s. Peak temperatures reached 130 °C at ball tip and 75 °C on metal jaws. The 1470-nm laser and probe show promise for laparoscopic tissue cutting and coagulation.
A sublethal concentration of chitosan oligosaccharide suppresses the population growth of the wheat aphid, Rhopalosiphum padi (Linnaeus)

The bird cherry‐oat aphid Rhopalosiphum padi (L.) (Hemiptera: Aphididae) is a key pest of wheat in China. Chitosan oligosaccharide (COS) has been widely used due to its biocompatibility, antibacterial activity, environmental friendliness and convenient extraction. This study was aimed at determining the acute toxicity of COS on R. padi and transgenerational effects of sublethal concentrations of COS on the biological characteristics of R. padi. The results indicated that COS possessed acute toxicity against R. padi after 48 h of exposure (LC50: 1227.35 mg/L). The sublethal concentration of COS (LC15: 260 mg/L) induced a decrease in adult longevity, adult prereproductive period and fecundity in the first filial generation (F1). Moreover, in F1 progeny, nymphal (1st–3rd), preadult and total prereproductive period significantly enhanced due to sublethal dose. Moreover, finite rate of increase (λ), the intrinsic rate of increase (r) and net reproductive rate (R0) of F1 progeny were significantly decreased, whereas a sublethal COS concentration exposure significantly increased the mean generation time (T) of F1 progeny. Overall, the study shows that sublethal concentration of COS can significantly suppress population growth of R. padi F1 generation, showing the potential of COS as a biorational option to manage aphids.
Regularized Least Square Approach for Remote Sensing Image Denoising using Wavelet Filters

Noise in remote sensing images (aerial and satellite) is caused due to various reasons such as atmospheric interference or lack of quality in sensors used to capture them. Removal of noise in an efficient way is a big challenge for researchers. In this paper, one dimensional signal denoising based on weighted regularized least square method is mapped to two dimensional image de noising. Objectives: This paper introduces a novel image denoising technique based on least square weighted regularization. Methods/Statistical Analysis: The proposed technique for image denoising based on Least Square (LS) approach is experimented on five different satellite and aerial images corrupted by gaussian noise with varying noise levels and regularization parameter lambda (λ) for different wavelet filter coefficients such as ‘haar’, ‘symlet’, ‘daubechies’ and coiflet. The effectiveness of the proposed method of image denoising is compared against the existing second order filter [based on LS] and conventional wavelet based image denoising technique based on the standard metric called Peak Signal to Noise Ratio (PSNR). Findings: From the experimental result analysis obtained it is inferred that the wavelet filters outperforms the second order filter and the conventional wavelet based image denoising. The complexity of the mathematics is low in our proposed method for image denoising. Applications/Improvements: The proposed denoising technique can be adopted as a faster pre-processing step in most of the image processing applications.
Classification ascendante hiérarchique des grands ensembles de données : un algorithme rapide fondé sur la construction des voisinages réductibles

© Les cahiers de l’analyse des données, Dunod, 1978, tous droits réservés. L’accès aux archives de la revue « Les cahiers de l’analyse des données » implique l’accord avec les conditions générales d’utilisation (http: //www.numdam.org/conditions). Toute utilisation commerciale ou impression systématique est constitutive d’une infraction pénale. Toute copie ou impression de ce fichier doit contenir la présente mention de copyright.
IoTSafe: Detecção de Ataques Baseada em Redes Neurais Profundas

O uso massivo da Internet das Coisas (IoT), em ambientes urbanos, expõe sistemas de naturezas diversas a ataques. São recorrentes, na literatura, propostas de autenticação e criptografia ou sistemas de detecção de ataques, IDS (Intrusion Detection System). Entretanto, faltam soluções que consigam unir, eficientemente, essas duas táticas de segurança, principalmente se inseridas em arquiteturas de computação de borda. Este artigo propõe uma solução para detecção de ataques como complemento aos mecanismos de criptografia e autenticação da IoTSafe, apresentados em um trabalho anterior. O novo modulo, de detecção, é baseado em deep learning e implementa uma rede neural profunda para identificação de ataques. Especializado em comunicação via MQTT (Message Queuing Telemetry Transport), o módulo é implantado na camada fog da arquitetura. Para avaliar o módulo e a arquitetura IoTSafe completa, testes em três ambientes foram realizados, com indicativos de consumo de recursos em cada um. Um estudo de caso mostrou que a IoTSafe funciona com todos os mecanismos, módulos e camadas propostos. O desempenho do novo módulo evidencia a sua eficácia, tendo obtido uma acurácia de 99,57% e precisão de 99,66% na detecção de ataques.
Determinación de precisión de la eritrosedimentación y su relación con otros parámetros hematológicos y bioquímicos en bóvidos Determining the precision of the erythrosedimentation and its relation with other hematologic and biochemical parameters in bovines

The erythrosedimentation is essential for a good hematologic study. The erythrosedimentation is not specific but important because it can be accelerated meanwhile other hematologic and/or biochemical parameters are not altered. The purpose of this work was to determine the precision of the erythrosedimentation and its behavior in front of other hematologic and/or biochemical parameters in samples of buffaloes and Carora cattle localized in the state of Merida-Venezuela. The erythrosedimentation was manually performed by using the methods and procedures suggested for human beings (Wintrobe and Westergreen). The hemoglobin, the hematocrit and the number of leucocytes were determined by the use of the IDEXX VetautoreadTM Hematology Analyzer. The fibrinogen concentration was determined by the use of a Bio-Bas coagulometer. The concentration of triglycerides and cholesterol was obtained in a Spectronic Genesys 20. The data obtained were processed by the statistical program Statistical Package for the Social Sciences version 10. Resulting the Wintrobe method in the buffaloes, an F test (p<0, 05) as the coefficient of variation <5%; and the Westergreen method for the Carora cattle in the second hour of erythrosedimentation, an F test (p<0, 05) as the coefficient of variation <5%. It can be concluded that, the erythrosedimentation presented precision by/in the Wintrobe method in buffaloes; meanwhile the Westergreen method presented the precision in the second hour in the Carora cattle. So that, we recommend that every locality REDVET. Revista electronica de Veterinaria 1695-7504 2010 Volumen 11 Numero 03 Determinacion de precision de la eritrosedimentacion y su relacion con otros parametros hematologicos y bioquimicos en bovidos http://www.veterinaria. org/revistas/redvet/n030310/031005.pdf 3 determine the values of the erythrosedimentation depending/based on the method and the bovine because the particular hematologic and biochemical variations of each specie have influence on the precision of the method.
Kinetic modelling of NH3 production in N2–H2 non-equilibrium atmospheric-pressure plasma catalysis

Detailed plasma kinetics modelling is presented of a low electron energy N2–H2 atmospheric-pressure discharge for ammonia synthesis. The model considers both electron and vibrational kinetics, including excited N2(X, ν) and H2(X, ν) species, and surface reactions such as those occurring by the Eley–Rideal and Langmuir–Hinshelwood mechanisms and dissociative adsorption of molecules. The predictions of the model are compared to the measured NH3 concentration produced in a packed-bed dielectric barrier discharge reactor as a function of process parameters such as input gas composition and applied voltage. Unlike typical low-pressure plasma processes, under the plasma conditions considered here (reduced electric field E/N in the range 30–50 Td, electron density of the order 108 cm−3), the influence of ions is not significant. Instead, the reactions between radicals and vibrationally-excited molecules are more important. The active species in surface reactions, such as surface-adsorbed atomic nitrogen N(s) or hydrogen H(s), are found to be predominantly generated through the dissociative adsorption of molecules, in contrast to previously proposed mechanisms for plasma catalysis under low-pressure, high-E/N conditions. It is found that NH radicals play an important role at the early stages of the NH3-generation process, NH in turn is produced from N and H2(ν). Electron kinetics is shown to play a critical role in the molecular dissociation and vibrational excitation reactions that produce these precursors. It is further found that surface-adsorbed atomic hydrogen H(s) takes a leading role in the formation of NH3, which is another significant difference from the mechanisms in conventional thermo-chemical processes and low-pressure plasmas. The applied voltage, the gas temperature, the N2:H2 ratio in the input gas mixture and the reactivity of the surface material are all found to influence the ammonia production. The calculated results reproduce the observed trends in the dependence of NH3 production on the N2/H2 ratio in the input gas mixture and the applied voltage.
Height estimation from single aerial imagery using contrastive learning based multi-scale refinement network

ABSTRACT Height map estimation from a single aerial image plays a crucial role in localization, mapping, and 3D object detection. Deep convolutional neural networks have been used to predict height information from single-view remote sensing images, but these methods rely on large volumes of training data and often overlook geometric features present in orthographic images. To address these issues, this study proposes a gradient-based self-supervised learning network with momentum contrastive loss to extract geometric information from non-labeled images in the pretraining stage. Additionally, novel local implicit constraint layers are used at multiple decoding stages in the proposed supervised network to refine high-resolution features in height estimation. The structural-aware loss is also applied to improve the robustness of the network to positional shift and minor structural changes along the boundary area. Experimental evaluation on the ISPRS benchmark datasets shows that the proposed method outperforms other baseline networks, with minimum MAE and RMSE of 0.116 and 0.289 for the Vaihingen dataset and 0.077 and 0.481 for the Potsdam dataset, respectively. The proposed method also shows around threefold data efficiency improvements on the Potsdam dataset and domain generalization on the Enschede datasets. These results demonstrate the effectiveness of the proposed method in height map estimation from single-view remote sensing images.
Out of equilibrium quantum dynamics and disordered systems in bosonic ultracold atoms

The fast progress of cold atoms experiments in the last decade has allowed to explore new aspects of strongly correlated systems. This thesis deals with two such general themes: the out of equilibrium dynamics of closed quantum systems, and the impact of disorder on strongly correlated bosons at zero temperature. Among the different questions about out of equilibrium dynamics, the phenomenon of dynamical transition is still lacking a complete understanding. The transition is typically signalled, in mean-field, by a singular behaviour of observables as a function of the parameters of the quench. In this thesis, a mean field method is developed to give evidence of a strong link between the quantum phase transition at zero temperature and the dynamical transition. We then study using field theory techniques a relativistic O($N$) model, and show that the dynamical transition bears similarities with a critical phenomenon. In this context, the dynamical transition also appears to be formally related to the dynamics of symmetry breaking. The second part of this thesis is about the disordered Bose-Hubbard model and the nature of its phase transitions. We use and extend the cavity mean field method, introduced by Ioffe and Mezard to obtain analytical results from the quantum cavity method and the replica trick. We find that the conventional transition, with power law scaling, is changed into an activated scaling in some regions of the phase diagram. Furthermore, the critical exponents are continuously varying along the conventional transition. These intriguing properties call for further investigations using different methods.
Structure-function clustering in multiplex brain networks

A key question in neuroscience is to understand how a rich functional repertoire of brain activity arises within relatively static networks of structurally connected neural populations: elucidating the subtle interactions between evoked “functional connectivity” and the underlying “structural connectivity” has the potential to address this. These structural-functional networks (and neural networks more generally) are more naturally described using a multilayer or multiplex network approach, in favour of standard single-layer network analyses that are more typically applied to such systems. In this letter, we address such issues by exploring important structure-function relations in the Macaque cortical network by modelling it as a duplex network that comprises an anatomical layer, describing the known (macro-scale) network topology of the Macaque monkey, and a functional layer derived from simulated neural activity. We investigate and characterize correlations between structural and functional layers, as system parameters controlling simulated neural activity are varied, by employing recently described multiplex network measures. Moreover, we propose a novel measure of multiplex structure-function clustering which allows us to investigate the emergence of functional connections that are distinct from the underlying cortical structure, and to highlight the dependence of multiplex structure on the neural dynamical regime.
SEMIPARAMETRIC EFFICIENCY FOR CENSORED LINEAR REGRESSION MODELS WITH HETEROSKEDASTIC ERRORS

Using a simplified approach developed by Severini and Tripathi (2001), we calculate the semiparametric efficiency bound for the finite-dimensional parameters of censored linear regression models with heteroskedastic errors. Under an additional identification at infinity type assumption, we propose an efficient estimator based on a novel result from Lewbel and Linton (2002). An extension to censored partially linear single-index models is also presented.
Complete words and superpatterns

This thesis surveys the most important results regarding complete words, by which we mean words containing as subsequences every permutation of some set, and then considers two variants of the problem of finding the shortest complete words. The first of these asks for the shortest superpattern, which is a complete word with some additional requirements, and the second asks for the expected number of timesteps before a particular random process generates