Miracle-dz/UniFAR-FTUs huggingface dataset:
How to Optimize the Utilization of Image Quality Metrics in Computer Vision?

In this paper, we propose to show the importance to consider the image quality in Computer Vision (CV) applications. We also describe a proposed framework that not only take into account the quality but rather permits to select the more adapted measure for a given CV application. Here, the selection of the image quality metric is based on a degradation identification step using a Linear Discriminant Analysis (LDA) method. The proposed framework has been applied to a Full-Reference approach where the reference image is supposed to be available and for No-Reference approach where only the captured image is accessible. The method has been tested using the TID 2008 database, which is composed of 17 degradation types.
Wideband small-signal input dq admittance modeling of six-pulse diode rectifiers

This paper studies the wideband small-signal input dq admittance of six-pulse diode rectifiers. Considering the frequency coupling introduced by ripple frequency harmonics of d-and q-channel switching function, the proposed model successfully predicts the small-signal input dq admittance of six-pulse diode rectifiers in high frequency regions that existing models fail to explain. Simulation and experimental results verify the accuracy of the proposed model.
Learning Slowly To Learn Better: Curriculum Learning for Legal Ontology Population

In this paper, we present an ontology population approach for legal ontologies. We exploit Wikipedia as a source of manually annotated examples of legal entities. We align YAGO, a Wikipedia-based ontology, and LKIF, an ontology specifically designed for the legal domain. Through this alignment, we can effectively populate the LKIF ontology, with the aim to obtain examples to train a Named Entity Recognizer and Classifier to be used for finding and classifying entities in legal texts. Since examples of annotated data in the legal domain are very few, we apply a machine learning strategy called curriculum learning aimed to overcome problems of overfitting by learning increasingly more complex concepts. We compare the performance of this method to identify Named Entities with respect to batch learning as well as two other baselines. Results are satisfying and foster further research in this direction.
Hughes Beyond evidence-based interventions : implementing an integrated approach to promoting pupil mental wellbeing in schools with Pyramid club A

rising tide of psychological distress among children and young people, coupled with extensive spending cuts to Child and Adolescent Mental Health Services (CAMHS), has created a treatment gap with increasing numbers of pupils presenting with mental health and behaviour difficulties in schools (Taggart et al., 2014). The crucial role of schools in providing early intervention to pupils with psychological difficulties is recognised, with some authors insisting that mental health should be part of the ‘core business’ of schools (e.g. Bonell et al., 2014). This sentiment is incorporated within a settingsbased approach to health (World Health Organisation, 1986), integrating sectors from the wider social system (e.g. schools, public health, local authorities and social care): it builds on the principles of community participation, partnership, empowerment and equity. A strategic framework for mental health that reduces risk and increases protective factors for children is imperative (Department of Health (DH), 2015) and couched within a settings-based model, places schools in a pivotal position to offer socio-emotional interventions. A political shift marked by decentralisation has given schools the capacity to influence the services that are commissioned by feeding information on the mental health needs of their pupils into local transformation plans. Moreover, they can contract services directly, working with local providers to support mental health promotion and deliver early interventions according to individual school needs. This article discusses school as an ‘ideal’ setting for promoting mental wellbeing, but goes on to argue that demonstrably effective interventions are not on their own sufficient to deliver positive health outcomes. Pyramid club is an established UK socioemotional intervention. The Pyramid model is introduced here and the challenge of reconciling process issues through an integrated approach to pupil mental wellbeing is explored.
Cholecystokinin-Mediated RhoGDI Phosphorylation via PKCα Promotes both RhoA and Rac1 Signaling

RhoA and Rac1 have been implicated in the mechanism of CCK-induced amylase secretion from pancreatic acini. In all cell types studied to date, inactive Rho GTPases are present in the cytosol bound to the guanine nucleotide dissociation inhibitor RhoGDI. Here, we identified the switch mechanism regulating RhoGDI1-Rho GTPase dissociation and RhoA translocation upon CCK stimulation in pancreatic acini. We found that both Gα13 and PKC, independently, regulate CCK-induced RhoA translocation and that the PKC isoform involved is PKCα. Both RhoGDI1 and RhoGDI3, but not RhoGDI2, are expressed in pancreatic acini. Cytosolic RhoA and Rac1 are associated with RhoGDI1, and CCK-stimulated PKCα activation releases the complex. Overexpression of RhoGDI1, by binding RhoA, inhibits its activation, and thereby, CCK-induced apical amylase secretion. RhoA translocation is also inhibited by RhoGDI1. Inactive Rac1 influences CCK-induced RhoA activation by preventing RhoGDI1 from binding RhoA. By mutational analysis we found that CCK-induced PKCα phosphorylation on RhoGDI1 at Ser96 releases RhoA and Rac1 from RhoGDI1 to facilitate Rho GTPases signaling.
Design considerations for GaN transistor based synchronous rectification

With improved electrical characteristics, GaN transistors have demonstrated superior performance in numerous hard-switching, soft-switching, and resonant power applications. In this paper, we will focus on the evaluation of GaN transistors as synchronous rectifiers and discuss design considerations unique for low voltage (<100 V), high frequency GaN transistor based synchronous rectification applications. Two experimental prototypes, operating from V<inf>in</inf>=48 V to V<inf>out</inf>=12 V and f<inf>sw</inf>=300–1000 kHz and V<inf>in</inf>=12 V to V<inf>out</inf>=1.8 V at f<inf>sw</inf>=10 MHz are used for evaluation.
Quantum causal modelling

Causal modelling provides a powerful set of tools for identifying causal structure from observed correlations. It is well known that such techniques fail for quantum systems, unless one introduces ‘spooky’ hidden mechanisms. Whether one can produce a genuinely quantum framework in order to discover causal structure remains an open question. Here we introduce a new framework for quantum causal modelling that allows for the discovery of causal structure. We define quantum analogues for core features of classical causal modelling techniques, including the causal Markov condition and faithfulness. Based on the process matrix formalism, this framework naturally extends to generalised structures with indefinite causal order.
Some Bullies Are More Equal than Others: Peer Relationships Modulate Altruistic Punishment of Bullies after Observing Ostracism.

current study presents a novel experimental design to examine how real-life peer relationships modulate altruistic punishment of bullies and compensation of victims after observed ostracism. Twenty-four participants (age 20) were invited to an experimental session in groups of three classmates and two unfamiliar peers, where they engaged in online interactions with one another. They played a series of virtual ball-tossing games (Cyberball) where they observed the ostracism of a classmate by another classmate and an unfamiliar bully. In between the Cyberball sessions, participants played economic exchange games where they could invest money to increase or decrease the payoffs of the players from the preceding Cyberball session. Participants punished classmate bullies and compensated victims more when they liked the victim more than the bully. Importantly, participants punished familiar bullies less severely than unfamiliar bullies when the familiar bully was better liked than the victim.
RADIATIVE TRANSFER: A NEW LOOK OF THE OLD THEORY

This tutorial paper discusses electromagnetic scattering by random many-particle groups and summarizes the microphysical approach to radiative transfer and coherent backscattering. It provides a detailed discussion of the exact meaning of such fundamental concepts as single and multiple scattering and explains how the theories of radiative transfer and coherent backscattering originate in the macroscopic Maxwell equations. It also exposes and corrects certain misconceptions of the traditional phenomenological approach to radiative transfer.
ROVIBRATIONALLY RESOLVED DIRECT PHOTODISSOCIATION THROUGH THE LYMAN AND WERNER TRANSITIONS OF H2 FOR FUV/X-RAY-IRRADIATED ENVIRONMENTS

Using ab initio potential curves and dipole transition moments, cross-section calculations were performed for the direct continuum photodissociation of H2 through the B1Σ+u ← X1Σ+g (Lyman) and C1Πu ← X1Σ+g (Werner) transitions. Partial cross-sections were obtained for wavelengths from 100 Å to the dissociation threshold between the upper electronic state and each of the 301 bound rovibrational levels v″J″ within the ground electronic state. The resulting cross-sections are incorporated into three representative classes of interstellar gas models: diffuse clouds, photon-dominated regions, and X-ray-dominated regions (XDRs). The models, which used the cloudy plasma/molecular spectra simulation code, demonstrate that direct photodissociation is comparable to fluorescent dissociation (or spontaneous radiative dissociation, the Solomon process) as an H2 destruction mechanism in intense far-ultraviolet or X-ray-irradiated gas. In particular, changes in H2 rotational column densities are found to be as large as 20% in the XDR model with the inclusion of direct photodissociation. The photodestruction rate from some high-lying rovibrational levels can be enhanced by pumping from H Lyβ due to a wavelength coincidence with cross-section resonances resulting from quasi-bound levels of the upper electronic states. Given the relatively large size of the photodissociation data set, a strategy is described to create truncated, but reliable, cross-section data consistent with the wavelength resolving power of typical observations.
Optimization Method for Developing Spectral Controlling Cosmetics: Application for Thermal Barrier Cosmetic

In this paper, a method of optimizing a thermal barrier cosmetic and spectral selective cosmetic by controlling the particle size and material is proposed as a countermeasure to heatstroke. The radiative properties of single cosmetic particles of a wide range of particle sizes and wavelengths in non-absorbing air were calculated in this study based on the Mie theory. Al2O3, TiO2, Au, and Ag were used as the material of the cosmetic particle. The radiative property of a particle cloud in dependent scattering was calculated. The radiative transfer in the cosmetic layer was analyzed, and the spectral reflectance of the cosmetic layer on the human skin was calculated. A new parameter was defined to quantitatively evaluate the performance of the thermal barrier cosmetic and spectral selective cosmetic. For the thermal barrier cosmetic, the Al2O3 particle was determined to be suitable, and its size was optimized. For the spectral selective cosmetic, the Au particle was likewise determined to be suitable, and its size was optimized. Our cosmetics satisfied both aesthetic and thermal concerns.
Distributed Smart Home Architecture for Data Handling in Smart Grid

Smart homes form an integral part of smart grid infrastructure. Recently, large numbers of sensors have been added within smart homes to enhance home appliance automation and monitoring. This addition raises questions about where the data generated within the home should be processed. The data can be processed either by one central processor or through multiple distributed processors closer to the sensors. This paper proposes a smart home distributed architecture involving home sensors talking directly to a smart gateway installed within the home. The gateway then decides which data should be forwarded to the central processor for further analysis. A test bed is designed to highlight the advantages of this approach. An open data set is used to feed sensor data into the test setup. It is shown that the local processing of data can improve efficiency by effectively utilizing available network bandwidth. Furthermore, local processing is favorable for time-critical smart home applications, since local processing has a faster data communication round trip time as compared with that of central processing. Moreover, we argue that certain calculations, like energy usage prediction for home appliances, can effectively be done locally while the central processor can be used for coordination between different local processors.
Image Collection Pop-up: 3D Reconstruction and Clustering of Rigid and Non-rigid Categories

This paper introduces an approach to simultaneously estimate 3D shape, camera pose, and object and type of deformation clustering, from partial 2D annotations in a multi-instance collection of images. Furthermore, we can indistinctly process rigid and non-rigid categories. This advances existing work, which only addresses the problem for one single object or, if multiple objects are considered, they are assumed to be clustered a priori. To handle this broader version of the problem, we model object deformation using a formulation based on multiple unions of subspaces, able to span from small rigid motion to complex deformations. The parameters of this model are learned via Augmented Lagrange Multipliers, in a completely unsupervised manner that does not require any training data at all. Extensive validation is provided in a wide variety of synthetic and real scenarios, including rigid and non-rigid categories with small and large deformations. In all cases our approach outperforms state-of-the-art in terms of 3D reconstruction accuracy, while also providing clustering results that allow segmenting the images into object instances and their associated type of deformation (or action the object is performing).
Bounded subset selection with noninteger coefficients

The subset selection problem is known to be NP hard. It was recently shown that by relaxing the requirement that the reconstructed signal be equal to the original, one ends with a bounded error subset selection that admits a solution in polynomial time. In the bounded error subset selection problem, the reconstructed signal is allowed to differ from the original signal by a bounded error. This bounded error formulation is natural in many applications, such as coding. In this paper, we improve the accuracy and reduce the complexity of the previously proposed approach for solving the bounded error subset selection problem. In particular, unlike the previously proposed approach for solving the bounded error subset selection problem, our new algorithm accommodates cases where the coefficients of the closest sparse approximation to the underlying signal in the dictionary are not necessarily one. Our new algorithm is based on weighting the dictionary vectors by the minimum l2 norm solution and relaxing the integer constraint on the coefficients of the dictionary vectors. It is shown to guarantee high signal accuracy and sparsity. Compared with the Basis Pursuit and the Method of Frames (MoF) algorithms, the proposed algorithm has a better rate-distortion behavior.
Adaptive Control of Robotic Manipulators With Unified Motion Constraints

In this paper, we present an adaptive control of robotic manipulators with parametric uncertainties and motion constraints. Position and velocity constraints are considered and they are unified and converted into the constraint of the nominal input. An adaptive neural network control is developed to achieve trajectory tracking, while the problems of motion constraints are addressed by considering the saturation effect of the nominal input. The uniform boundedness of all closed-loop signals is verified through Lyapunov analysis. Simulation and experiment results on a 2-degree-of-freedom robotic manipulator demonstrate the effectiveness of the proposed method.
Interactivity Attributes for Expression-oriented Interaction Design

This study proposes a new way of conceptualizing and designing interactive artifacts that emphasizes the importance of articulating sophisticated qualities of interactivity for promoting the design of aesthetic interaction. To make this possible, we introduce a set of attributes that solely describe the quality of interactivity, which is dynamic and invisible unlike other visual properties of an interactive artifact, and we call them interactivity attributes. In order to examine and explore the effects of applying interactivity attributes in interaction design, we conducted a series of studies in which we observed design students designing a set of interactive artifacts with and without the introduced interactivity attributes. We found that sensitizing the design students with these attributes changed their ways of approaching the design of interactivity of the artifacts. Designs became more expressive, quality descriptions were more sophisticated, both input- and output-behavior concepts of the interactive artifacts were considered consciously, and new materials and interaction styles were considered and applied.
Early Effects of Salinity on Water Transport in Arabidopsis Roots. Molecular and Cellular Features of Aquaporin Expression1

Aquaporins facilitate the uptake of soil water and mediate the regulation of root hydraulic conductivity (Lpr) in response to a large variety of environmental stresses. Here, we use Arabidopsis (Arabidopsis thaliana) plants to dissect the effects of salt on both Lpr and aquaporin expression and investigate possible molecular and cellular mechanisms of aquaporin regulation in plant roots under stress. Treatment of plants by 100 mm NaCl was perceived as an osmotic stimulus and induced a rapid (half-time, 45 min) and significant (70%) decrease in Lpr, which was maintained for at least 24 h. Macroarray experiments with gene-specific tags were performed to investigate the expression of all 35 genes of the Arabidopsis aquaporin family. Transcripts from 20 individual aquaporin genes, most of which encoded members of the plasma membrane intrinsic protein (PIP) and tonoplast intrinsic protein (TIP) subfamilies, were detected in nontreated roots. All PIP and TIP aquaporin transcripts with a strong expression signal showed a 60% to 75% decrease in their abundance between 2 and 4 h following exposure to salt. The use of antipeptide antibodies that cross-reacted with isoforms of specific aquaporin subclasses revealed that the abundance of PIP1s decreased by 40% as early as 30 min after salt exposure, whereas PIP2 and TIP1 homologs showed a 20% to 40% decrease in abundance after 6 h of treatment. Expression in transgenic plants of aquaporins fused to the green fluorescent protein revealed that the subcellular localization of TIP2;1 and PIP1 and PIP2 homologs was unchanged after 45 min of exposure to salt, whereas a TIP1;1-green fluorescent protein fusion was relocalized into intracellular spherical structures tentatively identified as intravacuolar invaginations. The appearance of intracellular structures containing PIP1 and PIP2 homologs was occasionally observed after 2 h of salt treatment. In conclusion, this work shows that exposure of roots to salt induces changes in aquaporin expression at multiple levels. These changes include a coordinated transcriptional down-regulation and subcellular relocalization of both PIPs and TIPs. These mechanisms may act in concert to regulate root water transport, mostly in the long term (≥6 h).
Statistical Analysis of the Non-stationarity of Neural Population Codes

Neural prosthetic technology has moved from the laboratory to clinical settings with human trials. The motor cortical control of devices in such settings raises important questions about the design of computational interfaces that produce stable and reliable control over a wide range of operating conditions. In particular, non-stationarity of the neural code across different behavioral conditions or attentional states becomes a potential issue. Non-stationarity has been previously observed in animals where the encoding model representing the mathematical relationship between neural population activity and behavioral variables such as hand motion changes over time. If such an encoding model is formed and learned during a particular training period, decoding performance (neural control) with the model may not be consistent during successive periods even when the same task is repeated. It is critical in both laboratory experiments and in clinical settings to be able to evaluate whether the representation of movement encoded by a neural population has changed or not. Such information can be used as a cue to retrain the system or as feedback to an adaptive decoding algorithm. To that end, we develop a statistical methodology to evaluate changes in the neural code over time using a generative probabilistic decoding model. The changes are evaluated by comparing the likelihoods of firing rates given similar distributions of 2D hand kinematics collected while a primate periodically performs a manual cursor control task. A comparison is performed by measuring a distance between probabilistic encoding models trained at different times. The statistical significance of the distance measurements are justified with a systematic statistical hypothesis test. The experimental results demonstrate that the likelihood changes over different periods with the change being greater when more distant periods are compared
Involvement of SPATA31 copy number variable genes in human lifespan

The SPATA31 (alias FAM75A) gene family belongs to the core duplicon families that are thought to have contributed significantly to hominoid evolution. It is also among the gene families with the strongest signal of positive selection in hominoids. It has acquired new protein domains in the primate lineage and a previous study has suggested that the gene family has expanded its function into UV response and DNA repair. Here we show that over-expression of SPATA31A1 in fibroblast cells leads to premature senescence due to interference with aging-related transcription pathways. We show that there are considerable copy number differences for this gene family in human populations and we ask whether this could influence mutation rates and longevity in humans. We find no evidence for an influence on germline mutation rates, but an analysis of long-lived individuals (> 96 years) shows that they carry significantly fewer SPATA31 copies in their genomes than younger individuals in a control group. We propose that the evolution of SPATA31 copy number is an example for antagonistic pleiotropy by providing a fitness benefit during the reproductive phase of life, but negatively influencing the overall life span.