Miracle-dz/UniFAR-FTUs huggingface dataset:
Anger and Aggression among Youth: An Empirical Investigation

Anger is usually considered to be one of the core human emotions. The presumed link between anger and aggression is most evident in biologically oriented theory and research. Aggression is by no means a new concern in human society, especially in youth. Aggressive behaviors in the young people are complex, heterogeneous with diverse etiologies and consequences. The current study examines anger and aggression in a group of youths. The measures used were the Clinical Anger Scale (Snell, 2002) and Aggression Questionnaire (Buss & Perry, 1992). The group comprised of 60 students pursuing Engineering from different colleges of Noida City. There were 30 boys and 30 girls. The age range of the sample was from 18 to 25 years. The scales were administered on 60 participants using convenience sampling method. Independent t-test and Pearson Correlation Coefficient were used for statistical analysis of data. Results revealed that there was significant difference in aggression, anger, physical aggression and humility. All the variables have been found to be significantly correlated except physical aggression and verbal aggression.
Computer-Simulated UWB VHF SAR Targets Based on Statistics of Real Data

—In this paper, we performed a statistical study of the targets of wavelength-resolution synthetic aperture radar (SAR) images and addressed the problem of limited training samples. Based on suitable statistical models for the real targets of the evaluated SAR image, we considered a sample generator method to create computer-simulated targets. For such, well-known statistical models, namely, Burr, Gamma, Gaussian, Log-normal, Rayleigh, Rician, and Weibull, are considered for the Anderson-Darling (AD) goodness-of-ﬁt test. This test is a statistical non-parametric hypothesis test generally used to investigate whether a given probability distribution yields a good ﬁt for a given data set. The images used in this study were obtained from the Swedish ultrawideband (UWB) very-high-frequency (VHF) SAR CARABAS II system whose consists of 24 magnitude single-look SAR images. The obtained computer-simulated targets followed similar statistical characteristics when compared to the real ones.
Examination of the polymorphs and particle size of calcium carbonate precipitated using still effluent (i.e., CaCl2 + NaCl Solution) of soda ash manufacturing process

The precipitation of calcium carbonate was studied by adding the sodium carbonate solution to a mixed system such as Still effluent (i.e., CaCl2 + NaCl solution) of the soda ash manufacturing (Solvay) process, and the effects of controlling factors on calcium carbonate polymorphs were investigated. The products were characterized with scanning electron microscopy (SEM), Fourier transform infrared (FTIR) spectroscopy, and powder X-ray diffraction analysis. The particle size distribution of products was determined as dry powder using laser diffraction technique. It was found that the dilute solutions of the reactants favor the aragonite formation without affecting much the particle size. The formation of calcite is favored with the increase in sodium carbonate concentration. The reaction temperature has no significant effect on polymorphism as well as particle size of calcium carbonate precipitated from solutions having concentration 1.25 M Ca2+ and 1.25 M CO32- and reaction time of 30 min. However, the mod.
ANTI-VATAIREA GUIANENSIS LECTIN IGY ANTIBODIES PRODUCED IN IMMUNIZED CHICKEN EGGS: PRODUCTION, ISOLATION AND CHARACTERIZATION

Lectins are a group of carbohydrate-binding proteins found in all organisms. Among these proteins, a species that stands out for having several biological activities is Vatairea guianensis lectin (VGL). Techniques involving antibodies can range from classic immunochemistry assays to advanced microscopy techniques. Thus, they can become valuable biotechnological tools since they are able to specifically recognize epitopes of the target molecules. Immunoglobulins are proteins whose main function is to bind with antigens foreign to the individual, in order to neutralize them. In the case of birds, the main class of immunoglobulins Y (IgYs) can be found not only in blood but also in egg yolks. This fact allows for quick and efficient purification of these molecules, facilitating their use as biotechnological tools. This work aimed to produce antibodies against VGL in chickens, implementing a methodology for the production biotechnological tools for the study of lectins. For that purpose, laying hens were immunized with VGL for 15 weeks at 10-day intervals. Collected eggs had the IgY purified and the produced antibody was able to recognize VGL as observed by western blotting. In this sense, the IgYs produced in this work constitute a powerful biotechnological tool available for future studies.
Einkristalline Gasturbinenschaufeln aus Nickelbasis‐Legierungen. Teil I: Herstellung und Mikrogefüge

Der Beitrag gibt einen Uberblick uber die zur Herstellung hochbeanspruchter Gasturbinenschaufeln heute ubliche Einkristalltechnologie. Nach einem kurzen Abris der Anforderungen an Gasturbinenschaufeln mit dem sich daraus ergebenden Zwang zur Verbesserung der Nickelbasis-Legierungen und nach einer kurzen Definition des “technischen” Einkristalls werden im vorliegenden Teil I das Verfahrensprinzip der gerichteten Erstarrung, die realisierbaren Erstarrungsfrontmorphologien und die Methoden der Kornselektion beschrieben. Am Beispiel der Legierung SRR99 wird der fur industrielle Produktion sinnvolle Giesparameterbereich fixiert. Die fur Einkristallbauteile aus Nickelbasis-Legierungen wesentlichen Mikrostrukturmerkmale “Kristallorientierung, Mikroporositat, Morphologie der γ′-Hartungsphase, dendritische Seigerung und Resteutektikum” werden vorgestellt. Nach dem Abgus befindet sich die Mikrostruktur in einer fur die Gebrauchseigenschaften nicht optimierten Form. Daher ist eine Warmebehandlung erforderlich. In Teil II wird beschrieben, wie durch die Warmebehandlung Resteutektikum aufgelost, Seigerungen ausgeglichen und die Morphologie der γ′-Phase optimiert werden konnen. Abschliesend wird das mechanische Verhalten behandelt. Bei den elastischen und plastischen Eigenschaften werden der dominante Einflus der Anisotropie gezeigt und beim Kriechverhalten die Wechselwirkung mit der γ′-Morphologie, bei der Schwingfestigkeit der Zusammenhang mit der Mikroporositat hervorgehoben.
-dependent biofilm formation by Vibrio fischeri

Vibrio fischeri is the exclusive symbiont residing in the light organ of the squid Euprymna scolopes . To understand the genetic requirements for this association, we searched a library of V. fischeri transposon insertion mutants for those that failed to colonize E. scolopes . We identified four mutants that exhibited severe defects in initiating colonization. Sequence analysis revealed that the strains contained insertions in four different members of a cluster of 21 genes oriented in the same direction. The predicted gene products are similar to proteins involved in capsule, exopolysaccharide or lipopolysaccharide biosynthesis, including six putative glycosyltransferases. We constructed mutations in five additional genes and found that they also were required for symbiosis. Therefore, we have termed this region syp , for symbiosis polysaccharide. Homologous clusters also exist in Vibrio parahaemolyticus and Vibrio vulnificus , and thus these genes may represent a common mechanism for promoting bacteria–host interactions. Using lacZ reporter fusions, we observed that transcription of the syp genes did not occur under standard laboratory conditions, but could be induced by multicopy expression of sypG , which encodes a response regulator with a predicted s 54 interaction domain. This induction depended on s 54 , as a mutation in rpoN abolished syp transcription. Primer extension analysis supported the use of putative s 54 binding sites upstream of sypA , sypI and sypM as promoters. Finally, we found that multicopy expression of sypG resulted in robust biofilm formation. This work thus reveals a novel group of genes that V. fischeri controls through a s 54 -dependent response regulator and uses to promote symbiotic colonization.
One novel Variable-speed wind energy system based on PMSG and super sparse matrix converter

Aim to reduce the cost of wind energy conversion system and improve its performance, a novel Variable-speed wind energy generation scheme which is based on the combination of PMSG and super sparse matrix converter (SSMC) is presented in this paper. The whole physical system including SSMC is modeled. Coordinate transformation, active power conservation principle and singular perturbation theory are applied to simplify the control law for SSMC. To design a global stable and robust controller, Feedback Linearization theory and H-infinity control are used. The stability of zero dynamics of the system is analyzed in detail. Based on the analysis of operation condition of SSMC, the limitations (reactive capability at both sides of SSMC) of the system are presented. It will be helpful to design the out-loop control strategy such as reactive power optimization control, maximum torque control of PMSG. The proposed generation system is not only able to realize maximum power tracking, but also reduce torque pulsation due to the distorted stator current in PMSM. At last, simulation results verify the feasibility of the proposed method.
Tug of Perspectives: Mobile App Users vs Developers

—Billions of apps are published each year in the mobile application distribution market. However, a large number of these apps are unsuccessful due to poor user attention and satisfaction as reﬂected by low ratings on the distribution markets. Recent studies have investigated the app popularity from users’ perspectives, but none of the studies have compared it from a developer’s perspective. To ﬁll this gap, we analyzed the user ratings and reviews with the software characteristics: ratings, issue report contents, number of bugs and enhancements, and developers’ team structure. In order to do this, we examined 274 apps on the Apple App Store that also had their source code available on GitHub. We collected 19,655 app reviews and 13,193 issue reports from both platforms. Generally, app users’ satisfaction and reviews on App Store did not reﬂect the developers’ preferences and issue report contents on GitHub. Furthermore, results suggested larger team sizes and the presence of subteams of developers had a signiﬁcant impact on ratings. Our ﬁndings may have implications for practitioners to improve their mobile app development practices.
Die Cardenolide von Parquetina nigrescens (AFZEL.) BULLOCK. Glykoside und Aglykone, 270. Mitteilung [1]

Six crystalline (A, C, E, H, J and K) and six amorphous (α, γ, A1, D, D′, and G) but paperchromatographically homogenous cardenolides were isolated from the wood of Parquetina nigrescens (AFZEL.) BULLOCK (= Periploca nigrescens AFZEL.) after fermentation with glucosidases. The presence of twelve more cardenolides was observed in paperchromatograms. Three of the mentioned compounds could be identified with known substances: A = strophanthidin (already isolated by SCHENKERet al. [3] from similar material), H = strophadogenin = 16β-hydroxystrophanthidin and J = convallatoxin. A1, C, D, E, and K are new compounds whose structures will be reported in the following publication. The structures of α, γ, D′ and G are as yet unknown.
Reduced-Rank Tensor-on-Tensor Regression and Tensor-Variate Analysis of Variance

Fitting regression models with many multivariate responses and covariates can be challenging, but such responses and covariates sometimes have tensor-variate structure. We extend the classical multivariate regression model to exploit such structure in two ways: first, we impose four types of low-rank tensor formats on the regression coefficients. Second, we model the errors using the tensor-variate normal distribution that imposes a Kronecker separable format on the covariance matrix. We obtain maximum likelihood estimators via block-relaxation algorithms and derive their computational complexity and asymptotic distributions. Our regression framework enables us to formulate tensor-variate analysis of variance (TANOVA) methodology. This methodology, when applied in a one-way TANOVA layout, enables us to identify cerebral regions significantly associated with the interaction of suicide attempters or non-attemptor ideators and positive-, negative- or death-connoting words in a functional Magnetic Resonance Imaging study. Another application uses three-way TANOVA on the Labeled Faces in the Wild image dataset to distinguish facial characteristics related to ethnic origin, age group and gender. A R package totr implements the methodology.
Spectral Reflectance Estimation Using Projector with Unknown Spectral Power Distribution

A lighting-based multispectral imaging system using an RGB camera and a projector is one of the most practical and low-cost systems to acquire multispectral observations for estimating the scene's spectral reflectance information. However, existing projector-based systems assume that the spectral power distribution (SPD) of each projector primary is known, which requires additional equipment such as a spectrometer to measure the SPD. In this paper, we present a method for jointly estimating the spectral reflectance and the SPD of each projector primary. In addition to adopting a common spectral reflectance basis model, we model the projector's SPD by a low-dimensional model using basis functions obtained by a newly collected projector's SPD database. Then, the spectral reflectances and the projector's SPDs are alternatively estimated based on the basis models. We experimentally show the performance of our joint estimation using a different number of projected illuminations and investigate the potential of the spectral reflectance estimation using a projector with unknown SPD.
Self-supervised Learning with Fully Convolutional Networks

Although deep learning based methods have achieved great success in many computer vision tasks, their performance relies on a large number of densely annotated samples that are typically difficult to obtain. In this paper, we focus on the problem of learning representation from unlabeled data for semantic segmentation. Inspired by two patch-based methods, we develop a novel self-supervised learning framework by formulating the Jigsaw Puzzle problem as a patch-wise classification process and solving it with a fully convolutional network. By learning to solve a Jigsaw Puzzle problem with 25 patches and transferring the learned features to semantic segmentation task on Cityscapes dataset, we achieve a 5.8 percentage point improvement over the baseline model that initialized from random values. Moreover, experiments show that our self-supervised learning method can be applied to different datasets and models. In particular, we achieved competitive performance with the state-of-the-art methods on the PASCAL VOC2012 dataset using significant fewer training images.
Representation-Free Model Predictive Control for Dynamic Motions in Quadrupeds

This article presents a novel representation-free model predictive control (RF-MPC) framework for controlling various dynamic motions of a quadrupedal robot in three-dimensional (3-D) space. Our formulation directly represents the rotational dynamics using the rotation matrix, which liberates us from the issues associated with the use of Euler angles and quaternion as the orientation representations. With a variation-based linearization scheme and a carefully constructed cost function, the MPC control law is transcribed to the standard quadratic program form. The MPC controller can operate at real-time rates of 250 Hz on a quadruped robot. Experimental results including periodic quadrupedal gaits and a controlled backflip validate that our control strategy could stabilize dynamic motions that involve singularity in 3-D maneuvers.
Trying Bilinear Pooling in Video-QA

Bilinear pooling (BLP) refers to a family of operations recently developed for fusing features from different modalities predominantly developed for VQA models. A bilinear (outer-product) expansion is thought to encourage models to learn interactions between two feature spaces and has experimentally outperformed `simpler' vector operations (concatenation and element-wise-addition/multiplication) on VQA benchmarks. Successive BLP techniques have yielded higher performance with lower computational expense and are often implemented alongside attention mechanisms. However, despite significant progress in VQA, BLP methods have not been widely applied to more recently explored video question answering (video-QA) tasks. In this paper, we begin to bridge this research gap by applying BLP techniques to various video-QA benchmarks, namely: TVQA, TGIF-QA, Ego-VQA and MSVD-QA. We share our results on the TVQA baseline model, and the recently proposed heterogeneous-memory-enchanced multimodal attention (HME) model. Our experiments include both simply replacing feature concatenation in the existing models with BLP, and a modified version of the TVQA baseline to accommodate BLP we name the `dual-stream' model. We find that our relatively simple integration of BLP does not increase, and mostly harms, performance on these video-QA benchmarks. Using recently proposed theoretical multimodal fusion taxonomies, we offer insight into why BLP-driven performance gain for video-QA benchmarks may be more difficult to achieve than in earlier VQA models. We suggest a few additional `best-practices' to consider when applying BLP to video-QA. We stress that video-QA models should carefully consider where the complex representational potential from BLP is actually needed to avoid computational expense on `redundant' fusion.
Sorting in Memristive Memory

Sorting data is needed in many application domains. Traditionally, the data is read from memory and sent to a general-purpose processor or application-specific hardware for sorting. The sorted data is then written back to the memory. Reading/writing data from/to memory and transferring data between memory and processing unit incur significant latency and energy overhead. In this work, we develop the first architectures for in-memory sorting of data to the best of our knowledge. We propose two architectures. The first architecture is applicable to the conventional format of representing data, i.e., weighted binary radix. The second architecture is proposed for developing unary processing systems, where data is encoded as uniform unary bit-streams. As we present, each of the two architectures has different advantages and disadvantages, making one or the other more suitable for a specific application. However, the common property of both is a significant reduction in the processing time compared to prior sorting designs. Our evaluations show on average 37 × and 138× energy reduction for binary and unary designs, respectively, compared to conventional CMOS off-memory sorting systems in a 45 nm technology. We designed a 3×3 and a 5×5 Median filter using the proposed sorting solutions, which we used for processing 64×64 pixel images. Our results show a reduction of 14× and 634× in energy and latency, respectively, with the proposed binary, and 5.6× and 152×103 in energy and latency with the proposed unary approach compared to those of the off-memory binary and unary designs for the 3 × 3 Median filtering system.
On the stability of Leidenfrost drop inner flows

E. Yim, A. Bouillant, D. Quéré, F. Gallaire LFMI, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland LadHyX, École polytechnique, 91128 Palaiseau, France PMMH, PSL-ESPCI, CNRS-UMR 7636, 75005 Paris, France Abstract Recent experimental observation by Bouillant et al. (Nat. Phys., vol. 14, 2018, 1188–1192) revealed that below a certain radius, a Leidenfrost water drop starts to self-rotate and propel. To better describe this internal mode transition, we study experimentally and numerically the global stability of a water drop in a Leidenfrost regime. In the experiment, the surface temperature and the internal flow fields of a drop with initial radius R ≈ 3.7 mm are measured using infrared camera and particle induced velocimetry, respectively, and show the existence of critical radii on successive azimuthal mode (of wavenumber m) transitions. Numerically, the steady base flow is computed assuming a non-deformable interface while the heat exchange on the boundary is modeled by an empirical correlation law. In absence of precise knowledge of the surface contamination properties, the surface tension gradient appears as the only tunable parameter to match experimental observations. The stability analysis of nominally axisymmetric base flow shows dominant unstable azimuthal mode transitions at radii close to the experimental observations. The unstable eigenvectors for the azimuthal wavenumber m = 3 and m = 2 are reminiscent to the experimental observations while the rolling mode is best described by the m = 1 eigenvector.
Spritz: general relativistic magnetohydrodynamics with neutrinos

We here present a new version of the publicly available general relativistic magnetohydrodynamic (GRMHD) code Spritz, which now includes an approximate neutrino leakage scheme able to handle neutrino cooling and heating. The leakage scheme is based on the publicly available ZelmaniLeak code, with a few modifications in order to properly work with Spritz. We discuss the involved equations, physical assumptions, and implemented numerical methods, along with a large battery of general relativistic tests performed with and without magnetic fields. Our tests demonstrate the correct implementation of the neutrino leakage scheme, paving the way for further improvements of our neutrino treatment and the first application to magnetized binary neutron star mergers. We also discuss the implementation in the Spritz code of high-order methods for a more accurate evolution of hydrodynamical quantities.
Voronoi Progressive Widening: Efficient Online Solvers for Continuous Space MDPs and POMDPs with Provably Optimal Components

Markov decision processes (MDPs) and partially observable MDPs (POMDPs) can effectively represent complex real-world decision and control problems. However, continuous space MDPs and POMDPs, i.e. those having continuous state, action and observation spaces, are extremely difficult to solve, and there are few online algorithms with convergence guarantees. This paper introduces Voronoi Progressive Widening (VPW), a general technique to modify tree search algorithms to effectively handle continuous or hybrid action spaces, and proposes and evaluates three continuous space solvers: VOSS, VOWSS, and VOMCPOW. VOSS and VOWSS are theoretical tools based on sparse sampling and Voronoi optimistic optimization designed to justify VPW-based online solvers. While previous algorithms have enjoyed convergence guarantees for problems with continuous state and observation spaces, VOWSS is the first with global convergence guarantees for problems that additionally have continuous action spaces. VOMCPOW is a versatile and efficient VPW-based algorithm that consistently outperforms POMCPOW and BOMCP in several simulation experiments.