Miracle-dz/UniFAR-FTUs huggingface dataset:
Development and Evaluation of an Outdoor Multisensory AR System for Cultural Heritage

Enhancing tourist visits to cultural heritage sites by making use of mobile augmented reality has been a tendency in the last few years, presenting mainly audiovisual experiences. However, these explorations using only visuals and sounds, or narratives, do not allow users to be presented with, for example, a particular smell that can be important to feel engaged or to better understand the history of the site. This article pursues the goal of creating an experience that puts the user in a scene planned to evoke several stimuli with SensiMAR prototype – a Multisensory Augmented Reality system that aims to be used in cultural heritage outdoors. When using SensiMAR, the user will be involved with visual reconstructions, surrounded by the soundscape of ancient times, and is exposed to a particular smell very common that time. Given the novelty of this proposal, ascertaining the usability of such a system was raised as a foremost demand. Thus, in addition to its development and implementation specifications, an experimental study was conducted to evaluate the usability of the system in end-users’ perspective. The results obtained from random visitors of an archaeological site were analysed according to their sex, age, previous experience with augmented reality technology, and provided condition – audiovisual condition, and multisensory condition, with visual, audio, and smell stimuli. Results were collected from a total of 67 participants and show that this multisensory prototype achieved good usability results across all groups. No statistically differences were found, demonstrating good usability of the SensiMAR system regardless of their sex, age, previous experience with the technology or provided condition.
A Simplified LSTM Neural Networks for One Day-Ahead Solar Power Forecasting

In recent years, exploration and exploitation of renewable energies are turning a new chapter toward the development of energy policy, technology and business ecosystem in all the countries. Distributed energy resources (DERs) are being largely interconnected to electrical power grids. This dispersed and intermittent generational mixes bring technical and economic challenges to the power systems in terms of operations, stability, reliability, interoperability and the policy making. In additional, DERs cause the significant impacts to the operation of traditional centralized generation power plants and the dispatch control centers. Under such circumstances, the accuracy of DERs power forecasting is one of the critical problems for TSO and DSO such as unit commitment, smooth fluctuations, peak load shifting, demand response, etc. In this paper, a simplified LSTM algorithm built over the architecture of Machine Learning methodology to forecast one day-ahead solar power generation is introduced. Through the machine learning processes of data processing, model fitting, cross validation, metrics evaluation and hyperparameters tuning, the result shows that the proposed simplified LSTM model outperform the MLP model. Moreover, the forecast of LSTM model can successfully capture intra-hour ramping on different weather scenarios. The average RMSE is 0.512 which is quite promising to inspire that the proposed methodology and architecture can best fit the short-term solar power forecasting applications.
Evidence against redox regulation of energy homoeostasis in humans at high altitude.

The present study examined if free radicals and associated inflammatory sequelae influenced metabolic biomarkers involved in the neuro-endocrinological regulation of energy homoeostasis at high altitude. Sixteen mountaineers (11 males/five females) were matched for physical fitness and caloric intake and assigned in a double-blind manner to either antioxidant (n = 8) or placebo (n = 8) supplementation, which was enforced for 7 days a: sea level and during an 11-day ascent to 4780 m. Enteral prophylaxis incorporated a daily bolus dose of I g of L-ascorbate, 400 international units of D,L-α-tocopherol acetate and 600 mg of α-lipoic acid. EPR (electron paramagnetic resonance) spectroscopic detection of PBN (a-phenyl-tert-butylnitrone) adducts confirmed an increase in the venous concentration of carbon-centred radicals at high altitude in the placebo group, whereas a decrease was observed in the antioxidant group (P < 0.05 compared with that at sea level). EPR detection of DMSO/A○ - (DMSO-supplemented ascorbate free radical) demonstrated that the increase in carbon-centred radicals at high altitude was associated with a decrease in ascorbate (r2 = 0.63; P < 0.05). Ascent to high altitude (pooled placebo + antioxidant groups) also increased the expression of pro-inflammatory cytokines (P < 0.05 compared with that at sea level) and biomarkers of skeletal tissue damage (P < 0.05). Despite a general decrease in leptin, insulin and glucose at high altitude (pooled placebo + antioxidant groups; P < 0.05 compared with that at sea level), persistent anorexia resulted in a selective loss of body fat (P < 0.05). In conclusion, antioxidant prophylaxis decreased the concentration of carbon-centred radicals at high altitude (P < 0.05 compared with the placebo group), but did not influence markers of inflammation, appetite-related peptides, ad libitum nutrient intake or bocy composition. Thus free radicals do not appear to be involved in the inflammatory response and subsequent control of eating behaviour at high altitude.
Preschool Anger, Activity Level, Inhibitory Control, and Behavior Problems: A Family Study Approach

Abstract:The temperament dimensions of anger, activity level (AL), and inhibitory control (IC) are representative of Rothbart’s negative affectivity, surgency, and effortful control factors, and are consistently related to child behavioral problems. Using parent and observer ratings of child temperament, we investigated links between anger, AL, IC, behavior problems (attention-deficit hyperactivity disorder [ADHD], aggression, and externalizing) and maternal characteristics in 201 preschoolers and their parents. Anger, AL, and IC were associated with one another and the three behavior problems in the expected directions. Parent-rated temperament was associated with all behavioral problems across analyses. However, in more rigorous regression analyses, observer-rated AL and IC were linked with ADHD, anger was associated with aggression, and hyperactivity was linked with externalizing problems, showing some specificity. Maternal education moderated the relationship between observed anger and externalizing problems. Results indicate that multimethod assessment approaches enable a more contextualized interpretation of early child temperament and behavior-problem research.
Microdetermination of Heavy Metal Chelates by High-Performance Liquid Chromatography

Abstract Adsorption chromatography of diethyldithiocarbamate chelates of heavy metals is described. Determination of heavy metals including Hg (II), Cd (II), Pb (II), Cr (VI), Bi (III) and Cu (II) in micro to nano gram order is successfully carried out with good accuracy and reproducibility by a deactivated silica gel column. Separative microdetermination of these chelates is accomplished within 12 min, and selective determination is also possible by choosing the detection wavelength of a UV detector.
The Protective Role of Parent Positive Personality and Emotional Availability in Toddler Problem Behavior

Abstract:This study examined the mediating role of emotional availability in the relation between parent positive personality and toddler problem behavior. The sample comprised 654 twins at 12 and 32 months. Primary caregivers (>95% mothers) completed six measures indexing parent positive personality assessed at 12 months, and emotional availability and toddler problem behaviors assessed at both times. Parent positive personality was positively associated with emotional availability and negatively associated with problem behavior. The indirect path from parent positive personality to problem behavior through emotional availability was significant, and parent positive personality was no longer significantly related to problem behavior, suggesting full mediation. Although problem behaviors were heritable, over half of the variance was due to the shared environment, pointing to early childhood as a time when parent characteristics and behaviors may have maximum influence. Parental emotional responsiveness could serve to reduce problem behaviors in young children.
Effect of microwave‐assisted extraction on the release of polyphenols from ginger (Zingiber officinale)

The significance of different variables viz. temperature, time and solvent at constant power in microwaveassisted extraction (MAE) process of ginger was studied and compared with conventional method. Aqueous ethanol (50%) provided higher yields of extract as well as the highest release of total polyphenols (TPP) than alcoholic solvents. The reason could be the high dielectric constant of aqueous ethanol as compared to alcohols. Microwave heating being a volumetric process, an exposure time of 1 min was found to be sufficient. The better penetration of microwaves and greater solubility at higher temperature resulted in higher yield of TPP and [6]-gingerol. The resultant extract showed higher radical scavenging activity (RSA) values. Thus, MAE allowed higher recoveries compared to conventional extraction process, with improvement in the quantity and quality of extract in very short period of time.
Theoretical Analysis and Novel Simulation for Single Shunt Rectifiers

Rectifiers are essential for microwave wireless power transfer (MWPT). RF-DC conversion efficiency must be improved for the practical use of MWPT. The focus of this research is related to single shunt rectifiers. Former research explained the operations of single shunt rectifiers in the frequency domain. Currently, we are using a harmonic balance method for the circuit simulations. These analyses focus on the frequency domain and transient phenomena were not directly analyzed. Also, the differences between experiments and their simulations are still issues in designing rectifiers. Therein, we analyzed an ideal rectifier with transient analysis and simulation. We also propose a novel simulation for single shunt rectifiers. Our simulation method is based on simple theories focusing on the steady-state condition of transient phenomena. In our analysis method, the output DC voltage is a fixed parameter and the DC current with the voltage is calculated. Therefore, this method is suitable for analyzing I-V characteristics. First, theoretical solutions are compared with Advanced Design System (ADS) simulations and they show the good agreement. Next, we created the novel simulation with our analysis method. Their results are also compared with ADS simulations. These analyses showed good agreement. Therefore, our novel method is consistent with former researches and commercial simulations. As a result, this research shows a novel analysis method for single shunt rectifiers and its consistency.
Sensitivity Assessment of Spatial Resolution Difference in DEM for Soil Erosion Estimation Based on UAV Observations: An Experiment on Agriculture Terraces in the Middle Hill of Nepal

Soil erosion in the agricultural area of a hill slope is a fundamental issue for crop productivity and environmental sustainability. Building terrace is a very popular way to control soil erosion, and accurate assessment of the soil erosion rate is important for sustainable agriculture and environmental management. Currently, many soil erosion estimations are mainly based on the freely available medium or coarse resolution digital elevation model (DEM) data that neglect micro topographic modification of the agriculture terraces. The development of unmanned aerial vehicle (UAV) technology enables the development of high-resolution (centimeter level) DEM to present accurate topographic features. To demonstrate the sensitivity of soil erosion estimates to DEM resolution at this high-resolution level, this study tries to evaluate soil erosion estimation in the Middle Hill agriculture terraces in Nepal based on UAV derived high-resolution (5 × 5 cm) DEM data and make a comparative study for the estimates by using the DEM data aggregated into different spatial resolutions (5 × 5 cm to 10 × 10 m). Firstly, slope gradient, slope length, and topographic factors were calculated at different resolutions. Then, the revised universal soil loss estimation (RUSLE) model was applied to estimate soil erosion rates with the derived LS factor at different resolutions. The results indicated that there was higher change rate in slope gradient, slope length, LS factor, and soil erosion rate when using DEM data with resolution from 5 × 5 cm to 2 × 2 m than using coarser DEM data. A power trend line was effectively used to present the relationship between soil erosion rate and DEM resolution. The findings indicated that soil erosion estimates are highly sensitive to DEM resolution (from 5 × 5 cm to 2 × 2 m), and the changes become relatively stable from 2 × 2 m. The use of DEM data with pixel size larger than 2 × 2 m cannot detect the micro topography. With the insights about the influencing mechanism of DEM resolution on soil erosion estimates, this study provides important suggestions for appropriate DEM data selection that should be investigated first for accurate soil erosion estimation.
Generation of an EDS Key Based on a Graphic Image of a Subject's Face Using the RC4 Algorithm

Modern facial recognition algorithms make it possible to identify system users by their appearance with a high level of accuracy. In such cases, an image of the user’s face is converted to parameters that later are used in a recognition process. On the other hand, the obtained parameters can be used as data for pseudo-random number generators. However, the closeness of the sequence generated by such a generator to a truly random one is questionable. This paper proposes a system which is able to authenticate users by their face, and generate pseudo-random values based on the facial image that will later serve to generate an encryption key. The generator of a random value was tested with the NIST Statistical Test Suite. The subsystem of image recognition was also tested under various conditions of taking the image. The test results of the random value generator show a satisfactory level of randomness, i.e., an average of 0.47 random generation (NIST test), with 95% accuracy of the system as a whole.
Design Optimization of Water Distribution Networks through a Novel Differential Evolution

Optimization algorithms have proven to be a useful tool in different areas of water resource management including water distribution network (WDN), which may be modelled as a large scale, combinatorial problem subject to constraints with the typical objective of minimizing the cost. In this study, a fuzzy C-means adaptive differential evolution (FCADE) is proposed to solve three well-known WDN problems: the two-loop distribution network problem, the Hanoi distribution network problem, and New York tunnel distribution network problem. FCADE is integrated with a well-known simulation software EPANET to manage the pressure constraints requirement. A comparative analysis of results through various performance metrics indicate the competence of FCADE for solving complex WDN problems.
INet: Convolutional Networks for Biomedical Image Segmentation

Encoder–decoder networks are state-of-the-art approaches to biomedical image segmentation, but have two problems: i.e., the widely used pooling operations may discard spatial information, and therefore low-level semantics are lost. Feature fusion methods can mitigate these problems but feature maps of different scales cannot be easily fused because down- and upsampling change the spatial resolution of feature map. To address these issues, we propose INet, which enlarges receptive fields by increasing the kernel sizes of convolutional layers in steps (e.g., from $3\times 3$ to $7\times 7$ and then $15\times 15$ ) instead of downsampling. Inspired by an Inception module, INet extracts features by kernels of different sizes through concatenating the output feature maps of all preceding convolutional layers. We also find that the large kernel makes the network feasible for biomedical image segmentation. In addition, INet uses two overlapping max-poolings, i.e., max-poolings with stride 1, to extract the sharpest features. Fixed-size and fixed-channel feature maps enable INet to concatenate feature maps and add multiple shortcuts across layers. In this way, INet can recover low-level semantics by concatenating the feature maps of all preceding layers and expedite the training by adding multiple shortcuts. Because INet has additional residual shortcuts, we compare INet with a UNet system that also has residual shortcuts (ResUNet). To confirm INet as a backbone architecture for biomedical image segmentation, we implement dense connections on INet (called DenseINet) and compare it to a DenseUNet system with residual shortcuts (ResDenseUNet). INet and DenseINet require 16.9% and 37.6% fewer parameters than ResUNet and ResDenseUNet, respectively. In comparison with six encoder–decoder approaches using nine public datasets, INet and DenseINet demonstrate efficient improvements in biomedical image segmentation. INet outperforms DeepLabV3, which implementing atrous convolution instead of downsampling to increase receptive fields. INet also outperforms two recent methods (named HRNet and MS-NAS) that maintain high-resolution representations and repeatedly exchange the information across resolutions.
Discriminant Analysis of Voice Commands in the Presence of an Unmanned Aerial Vehicle

The aim of this study was to perform discriminant analysis of voice commands in the presence of an unmanned aerial vehicle equipped with four rotating propellers, as well as to obtain background sound levels and speech intelligibility. The measurements were taken in laboratory conditions in the absence of the unmanned aerial vehicle and the presence of the unmanned aerial vehicle. Discriminant analysis of speech commands (left, right, up, down, forward, backward, start, and stop) was performed based on mel-frequency cepstral coefficients. Ten male speakers took part in this experiment. The unmanned aerial vehicle hovered at a height of 1.8 m during the recordings at a distance of 2 m from the speaker and 0.3 m above the measuring equipment. Discriminant analysis based on mel-frequency cepstral coefficients showed promising classification of speech commands equal to 76.2% for male speakers. Evaluated speech intelligibility during recordings and obtained sound levels in the presence of the unmanned aerial vehicle during recordings did not exclude verbal communication with the unmanned aerial vehicle for male speakers.
Linear stability analysis for flows over sinusoidal bottom topography

Abstract This is an ocean motivated study which investigates the impacts of sinusoidal bottom topography on baroclinic instability of zonal vertically sheared flows in the two-layer quasigeostrophic model. The corresponding linear stability problem is solved by assuming Fourier-mode solutions in both the zonal and meridional directions. In the presence of variable topographic features, the Fourier modes become coupled due to phase shifts in the wavevectors. The spectral discretisation method used in this work retains the primary relationship between different Fourier modes; thus, the linear stability eigenproblem can be solved for any periodic topography. Moreover, this method does not need any additional assumptions, such as considering small-amplitude or large-scale bottom irregularities, as in some previous studies. In this work, the eigenproblem is solved for a range of topographic amplitudes and wavenumbers, and their effects on the growth rates and shapes of the most unstable eigenmodes are discussed. In general, both the zonal and meridional variations in topography tend to suppress the baroclinic instability. However, it is found that only meridionally varying topography affects the magnitudes of the fastest growth rates. In this instance, unstable modes appear to form two clusters well separated in the zonal wavenumber axis and growth rate maxima occur at two distinct zonal wavenumbers. Dependencies of the characteristics of these clusters on the values of topography amplitude and ridge width are reviewed. Finally, doubly periodic numerical simulations are used to verify the results from the linear stability analysis.
Emotional responses to music: The need to consider underlying mechanisms

Research indicates that people value music primarily because of the emotions it evokes. Yet, the notion of musical emotions remains controversial, and researchers have so far been unable to offer a satisfactory account of such emotions. We argue that the study of musical emotions has suffered from a neglect of underlying mechanisms. Specifically, researchers have studied musical emotions without regard to how they were evoked, or have assumed that the emotions must be based on the "default" mechanism for emotion induction, a cognitive appraisal. Here, we present a novel theoretical framework featuring six additional mechanisms through which music listening may induce emotions: (1) brain stem reflexes, (2) evaluative conditioning, (3) emotional contagion, (4) visual imagery, (5) episodic memory, and (6) musical expectancy. We propose that these mechanisms differ regarding such characteristics as their information focus, ontogenetic development, key brain regions, cultural impact, induction speed, degree of volitional influence, modularity, and dependence on musical structure. By synthesizing theory and findings from different domains, we are able to provide the first set of hypotheses that can help researchers to distinguish among the mechanisms. We show that failure to control for the underlying mechanism may lead to inconsistent or non-interpretable findings. Thus, we argue that the new framework may guide future research and help to resolve previous disagreements in the field. We conclude that music evokes emotions through mechanisms that are not unique to music, and that the study of musical emotions could benefit the emotion field as a whole by providing novel paradigms for emotion induction.