Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparing the Efficacy of Two School-Based Approaches of Neurocognitive Training for Enhancing Executive Functions

Neurocognitive training has been shown to improve a range of cognitive/executive functions and behavior in children. Delivering this training in a school context may enhance its ecological validity and improve training outcomes. The current study examined the efficacy of two school-based neurocognitive training approaches for enhancing executive functions (EF) in typically developing children: neurocognitive training with no teacher positive feedback (NCT), and neurocognitive training with teacher positive feedback (NCT-TPF). Using a randomized control design, 45 children were randomly allocated to the no-training control, NCT, or NCT-TPF group and completed pre- and post-training assessments on the core executive function (EF) domains of inhibitory control, working memory, and task switching. Teachers’ subjective acceptance of the two training protocols was investigated to explore potential ecological validity. The two training groups completed six sessions of training in a kindergarten over a 3-week period. The results showed significant post-training improvements in an untrained inhibitory control task for both training groups when compared with the control group. Different effects were found for each group for the untrained task switching task. While reduced reaction time (RT) in correct Color and Shape trials at Time 2 were reported for the NCT-TPF group, there was no difference compared to the control group for the NCT group. The NCT group showed increased RT in Switch trials but reduced Shape errors compared to controls at Time 2, while these effects were not significant for the NCT-TPF group. An unexpected outcome was that children in both training conditions did not show a significant improvement in an untrained working memory task. Teachers’ subjective acceptance consistently supported including positive feedback as part of NCT. While further research is needed, these results support use of neurocognitive training and/or neurocognitive training with teacher positive feedback for typically developing children in a school context.
GLOBAL ENERGETICS OF SOLAR FLARES. I. MAGNETIC ENERGIES

We present the first part of a project on the global energetics of solar flares and coronal mass ejections that includes about 400 M- and X-class flares observed with Atmospheric Imaging Assembly (AIA) and Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO). We calculate the potential (Ep), the nonpotential (Enp) or free energies (Efree = Enp − Ep), and the flare-dissipated magnetic energies (Ediss). We calculate these magnetic parameters using two different NLFFF codes: the COR-NLFFF code uses the line-of-sight magnetic field component Bz from HMI to define the potential field, and the two-dimensional (2D) coordinates of automatically detected coronal loops in six coronal wavelengths from AIA to measure the helical twist of coronal loops caused by vertical currents, while the PHOT-NLFFF code extrapolates the photospheric three-dimensional (3D) vector fields. We find agreement between the two codes in the measurement of free energies and dissipated energies within a factor of ≲ 3. The size distributions of magnetic parameters exhibit powerlaw slopes that are approximately consistent with the fractal-diffusive self-organized criticality model. The magnetic parameters exhibit scaling laws for the nonpotential energy, , for the free energy, and , for the dissipated energy, and , and the energy dissipation volume, . The potential energies vary in the range of Ep = 1 × 1031–4 × 1033 erg, while the free energy has a ratio of Efree/Ep ≈ 1%–25%. The Poynting flux amounts to Fflare ≈ 5 × 108–1010 erg cm−2 s−1 during flares, which averages to FAR ≈ 6 × 106 erg cm−2 s−1 during the entire observation period and is comparable with the coronal heating rate requirement in active regions.
Conceptual Radiation Shielding Design of Superconducting Tokamak Fusion Device by PHITS (Selected Papers of the Joint International Conference of Supercomputing in Nuclear Applications and Monte Carlo : SNA + MC 2010)

A 3D neutron and photon transport analysis by Monte Carlo transport code system PHITS (Particle and Heavy Ion Transport code System) has been performed for superconducting tokamak fusion device such as JT-60 Super Advanced (JT-60SA). It is possible to make use of PHITS in the port streaming analysis around the devices for the tokamak fusion device, the duct streaming analysis in the building where the device is installed, and the sky shine analysis for the site boundary. The neutron transport analysis by PHITS makes it clear that the shielding performance of the superconducting tokamak fusion device with the cryostat has been improved by the graphical results. From the standpoint of the port and duct streaming, it is necessary to estimate by 3D Monte Carlo code such as PHITS for the neutronics analysis of superconducting tokamak fusion device.
Pesticide-Free Robotic Control of Aphids as Crop Pests

Because our civilization has relied on pesticides to fight weeds, insects, and diseases since antiquity, the use of these chemicals has become natural and exclusive. Unfortunately, the use of pesticides has progressively had alarming effects on water quality, biodiversity, and human health. This paper proposes to improve farming practices by replacing pesticides with a laser-based robotic approach. This study focused on the neutralization of aphids, as they are among the most harmful pests for crops and complex to control. With the help of deep learning, we developed a mobile robot that spans crop rows, locates aphids, and neutralizes them with laser beams. We have built a prototype with the sole purpose of validating the localization-neutralization loop on a single seedling row. The experiments performed in our laboratory demonstrate the feasibility of detecting different lines of aphids (50% detected at 3 cm/s) and of neutralizing them (90% mortality) without impacting the growth of their host plants. The results are encouraging since aphids are one of the most challenging crop pests to eradicate. However, enhancements in detection and mainly in targeting are necessary to be useful in a real farming context. Moreover, robustness regarding field conditions should be evaluated.
Metacognitive Scales: Assessing Metacognitive Knowledge in Older Adults Using Everyday Life Scenarios

The multidimensional effect of aging on cognition and its interference with daily functioning is well reported by many studies. Therefore, the ability to detect age-related cognitive changes is of great importance for older adults to help compensate for cognitive decline. For that, metacognition and its course of change across the lifespan of a person have attracted considerable scientific interest. The aim of the present study is to present three new self-report questionnaires, developed to measure older adults’ metacognitive knowledge for everyday memory (MKEM), metacognitive knowledge for everyday attention (MKEA), and metacognitive knowledge for everyday executive functions (MKEEFs). The questionnaires were tested for structural validity and reliability. A sample size of 171 community-dwelling adults of advancing age (97 females and 74 males) voluntarily participated in this study and their ages ranged from 50 to 82 years (mean = 59.32, SD = 7.39). Exploratory factor analysis using principal component analysis with varimax rotation was applied to examine structural validity. The results revealed a one-factor structure for the MKEM with high internal consistency (α = 0.88), a two-factor structure for the MKEA, that reflected “divided and shifted attention” (α = 0.74) and “concentration” (α = 0.75), and a two-factor structure for the MKEEFs that reflected “planning” (α = 0.70) and “inhibition” (α = 0.65). The variables created for each factor respectively showed significant positive correlations between each other.
Contribution of Common Modulation Spectral Features to Vocal-Emotion Recognition of Noise-Vocoded Speech in Noisy Reverberant Environments

In one study on vocal emotion recognition using noise-vocoded speech (NVS), the high similarities between modulation spectral features (MSFs) and the results of vocal-emotion-recognition experiments indicated that MSFs contribute to vocal emotion recognition in a clean environment (with no noise and no reverberation). Other studies also clarified that vocal emotion recognition using NVS is not affected by noisy reverberant environments (signal-to-noise ratio is greater than 10 dB and reverberation time is less than 1.0 s). However, the contribution of MSFs to vocal emotion recognition in noisy reverberant environments is still unclear. We aimed to clarify whether MSFs can be used to explain the vocal-emotion-recognition results in noisy reverberant environments. We analyzed the results of vocal-emotion-recognition experiments and used an auditory-based modulation filterbank to calculate the modulation spectrograms of NVS. We then extracted ten MSFs as higher-order statistics of modulation spectrograms. As shown from the relationship between MSFs and vocal-emotion-recognition results, except for extremely high noisy reverberant environments, there were high similarities between MSFs and the vocal emotion recognition results in noisy reverberant environments, which indicates that MSFs can be used to explain such results in noisy reverberant environments. We also found that there are two common MSFs (MSKTk (modulation spectral kurtosis) and MSTLk (modulation spectral tilt)) that contribute to vocal emotion recognition in all daily environments.
A Novel Approach for Emotion Recognition Based on EEG Signal Using Deep Learning

Emotion can be defined as a voluntary or involuntary reaction to external factors. People express their emotions through actions, such as words, sounds, facial expressions, and body language. However, emotions expressed in such actions are sometimes manipulated by people and real feelings cannot be conveyed clearly. Therefore, understanding and analyzing emotions is essential. Recently, emotion analysis studies based on EEG signals appear to be in the foreground, due to the more reliable data collected. In this study, emotion analysis based on EEG signals was performed and a deep learning model was proposed. The study consists of four stages. In the first stage, EEG data were obtained from the GAMEEMO dataset. In the second stage, EEG signals were transformed with both VMD (variation mode decomposition) and EMD (empirical mode decomposition), and a total of 14 (nine from EMD, five from VMD) IMFs were obtained from each signal. In the third stage, statistical features were obtained from IMFs and maximum value, minimum value, and average values were used for this. In the last stage, both binary-class and multi-class classifications were made. The proposed deep learning model is compared with kNN (k nearest neighbor), SVM (support vector machines), and RF (random forest). At the end of the study, an accuracy of 70.89% in binary-class classification and 90.33% in multi-class classification was obtained with the proposed deep learning method.
Structural Heterogeneity of the GABAergic Tripartite Synapse

The concept of the tripartite synapse describes the close interaction of pre- and postsynaptic elements and the surrounding astrocyte processes. For glutamatergic synapses, it is established that the presence of astrocytic processes and their structural arrangements varies considerably between and within brain regions and between synapses of the same neuron. In contrast, less is known about the organization of astrocytic processes at GABAergic synapses although bi-directional signaling is known to exist at these synapses too. Therefore, we established super-resolution expansion microscopy of GABAergic synapses and nearby astrocytic processes in the stratum radiatum of the mouse hippocampal CA1 region. By visualizing the presynaptic vesicular GABA transporter and the postsynaptic clustering protein gephyrin, we documented the subsynaptic heterogeneity of GABAergic synaptic contacts. We then compared the volume distribution of astrocytic processes near GABAergic synapses between individual synapses and with glutamatergic synapses. We made two novel observations. First, astrocytic processes were more abundant at the GABAergic synapses with large postsynaptic gephyrin clusters. Second, astrocytic processes were less abundant in the vicinity of GABAergic synapses compared to glutamatergic, suggesting that the latter may be selectively approached by astrocytes. Because of the GABA transporter distribution, we also speculate that this specific arrangement enables more efficient re-uptake of GABA into presynaptic terminals.
Flow Instability of a Liquid Through a Small-Scale Channel During a Flow Evaporation

Finite volume analysis of two-dimensional model has been performed to study of the influence of heat flux and mass flux on two phase heat transfer through microchannel during water flow boiling. The channel dimensions were (5×5××50) m3. The inlet boundary conditions were (1.63, 3.32, 4.9, 6.65, 8.16) . The supplied heat fluxes were 24.8 , 33.2 , 46.13 , 51 and 69 for nucleate boiling while 33.3 , 50 , 66.7 , 83.3 , and 100 for dryout condition. The inlet temperature was 30oC. It was shown that the highest heat transfer coefficient occurs at beginning of onset of nucleate boiling (ONB) after that the it will drop due the changing of the flow patterns. According to supplied heat flux, the patterns were bubble flow, dispersed bubbles, churn flow, annular flow, and then dry out condition occurs. For the mass flux 1.63kg/ the highest heat transfer coefficient was 9.5 kW/ while for the mass flux 8.16 kg/ the highest heat transfer coefficient was 20kW/ . For the mass flux 1.63kg/ the highest value of vapour quality was 0.09 while for the mass flux 8.16 kg/ the highest value was 0.15. There is a sharp pressure drop when starts to nucleate and the highest value occurs at dryout condition. This study gave an understanding of the heat exchange flow behaviour during water boiling through a single microchannel.
Characterization and Expression Analysis of Mollusk-like Growth Factor: A Secreted Protein Involved in Pacific Abalone Embryonic and Larval Development

Simple Summary The Pacific abalone, Haliotis discus hannai, is a gastropod mollusk in high demand, which is extensively cultured in many Asian countries. The growth and development of Pacific abalone depend on the activation of growth factors and other growth-regulating proteins. Growth factors are secreted, biologically active molecules that stimulate cell growth through signal transduction pathways. The mollusk-like growth factor (MLGF) is a mollusk specific growth factor in the adenosine deaminase related growth factor subfamily having a conserved adenosine deaminase (ADA) domain. Molecular functions of this growth factor include adenosine deaminase activity, growth factor activity, and zinc binding activity. For this growth factor activity, enzymatic activity (ADA activity) that converts adenosine to inosine to stimulate cell growth is essential. As abalone aquaculture completely depends on hatchery-produced seed, proper embryonic and larval development is essential, and MLGF is one of the main growth factors that can regulate this activity. In Pacific abalone, higher expression of Hdh-MLGF mRNA in the embryonic and larval development stages is an indication of higher production of adenosine and increases the growth factor activity that stimulates embryonic and larval cell growth through signal transduction pathways. Abstract Growth factors are mostly secreted proteins that play key roles in an organism’s biophysical processes through binding to specific receptors on the cell surface. The mollusk-like growth factor (MLGF) is a novel cell signaling protein in the adenosine deaminase-related growth factor (ADGF) subfamily. In this study, the MLGF gene was cloned and characterized from the digestive gland tissue of Pacific abalone and designated as Hdh-MLGF. The transcribed full-length sequence of Hdh-MLGF was 1829 bp long with a 1566 bp open reading frame (ORF) encoding 521 amino acids. The deduced amino acid sequence contained a putative signal peptide and two conserved adenosine deaminase domains responsible for regulating molecular function. Fluorescence in situ hybridization localized Hdh-MLGF in the submucosa layer of digestive tubules in the digestive gland. The mRNA expression analysis indicated that Hdh-MLGF expression was restricted to the digestive gland in the adult Pacific abalone. However, Hdh-MLGF mRNA expressions were observed in all stages of embryonic and larval development, suggesting Hdh-MLGF might be involved in the Pacific abalone embryonic and larval development. This is the first study describing Hdh-MLGF and its involvement in the Pacific abalone embryonic and larval development.
Spatial Modelling of Peak Frequencies of Brain Signals

Spatial modelling of various phenomena has been undertaken in many diversified fields. In this project, we concentrate on the modelling of the peak frequencies of brain signals and the objective is to fit and illustrate spatial regression with Simultaneous Autoregressive (SAR) covariance structure. We found that the peak frequencies can be modelled appropriately as, β β β e = + + + 2 00 11 1 2 21 1 2 , i i
Signals of composite particles at the LHC

Composite particles generated by an unknown strong dynamics can be responsible for the ElectroWeak Symmetry Breaking (EWSB) and can substitute the Standard Model (SM) Higgs boson in keeping perturbative unitarity in the longitudinal WW scattering up to a cut-off \Lambda\approx 4\pi v. These new states can be sufficiently light to be observed at the Large Hadron Collider (LHC) and they can even be the first manifestation of new physics at the LHC. Their couplings among themselves and with the SM particles, can be described using reasonable effective Lagrangians and Chiral Perturbation Theory. In the first part of this thesis different possibilities for a strongly interacting EWSB are discussed in details with particular attention to the roles of unitarity in the longitudinal WW scattering and of ElectroWeak Precision Tests (EWPT). Higgsless models with composite vectors and scalars, based on the SU(2)_{L}\times SU(2)_{R}/SU(2)_{L+R} custodial symmetry, are discussed in the context of ElectroWeak Chiral Lagrangians and the phenomenology of the pair productions is studied for the high energy and high luminosity phase of the LHC. In the second part of the thesis the possible signals of single particle production at the early LHC, with 7 TeV of center of mass energy and 1-5 fb^{-1} of integrated luminosity, are treated with a phenomenological Lagrangian approach. The final states containing at least one photon emerge as the most promising channels for an early discovery already with tens of inverse picobarns of integrated luminosity. Finally, in the last part of this work, the role of a composite iso-singlet vector in Dark Matter models is discussed and the related LHC phenomenology is studied, giving particular attention to the Z\gamma final state.
Decoherence of nuclear spins in the frozen core of an electron spin

Hybrid qubit systems combining electronic spins with nearby (``proximate'') nuclear spin registers offer a promising avenue towards quantum information processing, with even multispin error-correction protocols recently demonstrated in diamond. However, for the important platform offered by spins of donor atoms in cryogenically cooled silicon, decoherence mechanisms of $^{29}\mathrm{Si}$ proximate nuclear spins are not yet well understood. The reason is partly because proximate spins lie within a so-called ``frozen core'' region where the donor electronic hyperfine interaction strongly suppresses nuclear dynamics. We investigate the decoherence of a central proximate nuclear qubit arising from quantum spin baths outside, as well as inside, the frozen core around the donor electron. We consider the effect of a very large nuclear spin bath comprising many $(\ensuremath{\gtrsim}{10}^{8})$ weakly contributing pairs outside the frozen core (the ``far bath''). We also propose that there may be an important contribution from a few (of order 100) symmetrically sited nuclear spin pairs (``equivalent pairs''), which were not previously considered because their effect is negligible outside the frozen core. If equivalent pairs represent a measurable source of decoherence, nuclear coherence decays could provide sensitive probes of the symmetries of electronic wave functions. For the phosphorus donor system, we obtain ${T}_{2n}$ values of order 1 second for both the far-bath and equivalent-pair models, confirming the suitability of proximate nuclei in silicon as very-long-lived spin qubits.
Equity properties of the Shapley value as a power index

We study power indices for simple games whi ch have the following "uniform transfer property" : when only one los in g coali tion in a game beco mes winning, worths of all other coali t ions remaining unchanged, t he index in creases eq ually for all players in that coaliti on and decreases equa lly for all pl ayers not in that coali­ ti on. We show t hat both for superaddi t ive simple games and fo r all simple games there is only one such index: t he Shapley- Shubik index, the res triction of Shapley value to the cl ass of simple games. Moreover, the proof of this fact does not even req uire t he standard assumption of symmet ry of power indices whi ch can be replaced by a weaker equal t reatment condition. Keywor d s: simple game, power index , uni fo rm transfer, Shap­ ley value.
K63 Ubiquitination of P21 Can Facilitate Pellino-1 in the Context of Chronic Obstructive Pulmonary Disease and Lung Cellular Senescence

Chronic obstructive pulmonary diseases (COPD) is a kind of age-related, airflow-obstruction disease mostly caused by cigarette smoke. However, the relationship between COPD and lung cellular senescence is still not fully understood. Here, we found silencing Pellino-1 could inhibit the protein level of P21. Then, through constructing cell lines expressed ubiquitin-HA, we found that the E3 ubiquitin ligase Pellino-1 could bind to senescence marker p21 and modify p21 by K63-site ubiquitination by co-IP assays. Furthermore, we found that p21-mediated lung cellular senescence could be inhibited by silencing Pellino-1 in a D-galactose senescence mice model. Moreover, by constructing a COPD mouse model with shPellino-1 adenovirus, we found that silencing Pellino-1 could inhibit COPD and inflammation via reduction of SASPs regulated by p21. Taken together, our study findings elucidated that silencing E3 ligase Pellino-1 exhibits therapeutic potential for treatment to attenuate the progression of lung cellular senescence and COPD.
Linear analyses for the stability of radial and non-radial oscillations of massive stars

In order to understand the periodic and semiperiodic variations of luminous OBA-type stars, linear non-adiabatic stability analyses for radial and non-radial oscillations have been performed for massive evolutionary models (8―90 M ⊙ ). In addition to radial and non-radial oscillations excited by the kappa-mechanism and strange mode instability, we discuss the importance of low-degree oscillatory convection (non-adiabatic g ― ) modes. Although their kinetic energy is largely confined to the convection zone generated by the Fe-opacity peak near 2 x 10 5 K, the amplitude can emerge into the photosphere and should be observable in a certain effective temperature range. They have periods longer than those of the radial strange modes so that they seem to be responsible for some of the long-period microvariations of Luminous Blue Variables (LBVs; S Dor variables) and α Cyg variables. Moreover, monotonically unstable radial modes are found in some models whose initial masses are greater than or equal to 60 M ⊙ with Z = 0.02. The monotonic instability probably corresponds to the presence of an optically thick wind. The instability boundary roughly coincides with the Humphreys-Davidson limit.