Miracle-dz/UniFAR-FTUs huggingface dataset:
Text-Based Automatic Personality Recognition: a Projective Approach

This paper provides a new TB-APR approach, using a projective test to build a corpus. The research of Personality Computing shows that it is possible to recognize personality automatically from texts (TB-APR), using paradigms of supervised learning. As concerns these paradigms, texts need to be labeled by psychometric instruments and, in order to realize this task, personality inventories are used. Personality inventories display great facilities for application and correction, but they do not evince efficient ways of controlling intentional or non-conscious omissions of undesired personality characteristics by the individual, which may explain the low correlations found in literature regarding TB-APR models. In this article, we propose the labeling of a textual corpus using the Z-test projective instrument, in order to mitigate the limitations of inventories, since it is very sensitive and offers the possibility of collective application. The proposed model used bag-of-words techniques, with some state of art machine learning inductors. The results are promising, with AUC-ROC on 0.85 average.
Theoretical studies on heats of formation for polynitrocubanes using the density functional theory B3LYP method and semiempirical MO methods

The heats of formation (HOFs) have been calculated for 21 polynitrocubane compounds using semiempirical MO methods (MINDO/3, MNDO, AM1 and PM3) and for eight of 21 polynitrocubanes containing one to four nitro groups using the density functional theory method at the B3LYP/6-31G* level by means of designed isodesmic reactions. The cubane cage skeletons in the polynitrocubane molecules have been kept in setting up the isodesmic reactions to produce more accurate and reliable results. It is found that there is a good linear relationship between the HOFs of eight polynitrocubanes calculated using the B3LYP/6-31G* and PM3 methods, but not for the other methods, and the linear correlation coefficient equals 0.9971. Subsequently, accurate HOFs at the B3LYP/6-31G* level of the other 13 polynitrocubanes containing four to eight nitro groups were obtained by systematically correcting their PM3-calculated HOFs. All 21 polynitrocubane compounds have high HOFs, implying that they can be very powerful energetic materials. The relationship between the HOFs and molecular structures for polynitrocubanes is discussed. Copyright © 2001 John Wiley & Sons, Ltd.
Potencial de água do solo e adubação com boro no crescimento e absorção do nutriente pela cultura da soja

A soja e uma cultura exigente em boro (B), entretanto, e estreita a faixa entre o nivel adequado e o toxico para esse nutriente no solo; dessa forma, a dose a ser recomendada deve ser bem definida. As condicoes hidricas do solo tambem e um aspecto importante relacionado diretamente com a disponibilidade de B para as plantas. Nesse contexto, este trabalho teve como objetivo avaliar o efeito da aplicacao de fontes e doses de B no crescimento da soja (Glycine max) em um Latossolo Vermelho eutroferrico de textura arenosa, submetido a diferentes tensoes de agua. O experimento foi conduzido em casa de vegetacao em vasos com 5 dm3 de solo. Utilizou-se o delineamento experimental em parcelas subdivididas, em esquema fatorial 5 x 2 x 3, sendo cinco doses de B (0,0; 0,25; 0,5; 1,0; e 2,0 mg dm-3); duas fontes (acido borico e colemanita) e tres tensoes de agua no solo (0,01; 0,03; e 0,10 MPa), com quatro repeticoes. Os resultados indicaram que o crescimento da soja nao e influenciado quando se mantem o nivel de tensao de agua no solo ate 0,1 MPa. O crescimento do sistema radicular foi interferido negativamente com a aplicacao de doses de B ate 2 mg dm-3, em solo com teor inicial de 0,32 mg dm-3. Os teores de B no solo e no tecido foliar da soja aumentaram linearmente com as doses do nutriente aplicado no solo, sendo observado na maior dose (2 mg dm-3 de B) sintomas de tipicos de toxidez de B nas folhas da cultura da soja.
Remote Physical Frailty Monitoring–The Application of Deep Learning-Based Image Processing in Tele-Health

Remote screening physical frailty (PF) may assist in triaging patients with chronic obstructive pulmonary disease (COPD) who are in clinical priorities to visit a clinical center for preventive care. Conventional PF assessment tools have however limited feasibility for remote patient monitoring applications. To improve the safety of PF assessment, we previously developed and validated a quick and safe PF screening tool called Frailty Meter (FM). FM works by quantifying weakness, slowness, rigidity, and exhaustion during a 20-second repetitive elbow flexion/extension task using a wrist-worn sensor and generates a frailty index (FI) ranging from zero to one; higher values indicate progressively greater severity of frailty. However, the use of wrist-sensor limits its applications in telemedicine and remote patient monitoring. In this study, we developed a sensor-less FM based on deep learning-based image processing, which can be easily integrated into mobile health and enables remote assessment of physical frailty. The sensor-less FM extracts kinematic features of the forearm motion from the video of 20-second elbow flexion and extension recorded by a tablet camera, and then calculates frailty phenotypes and FI. To test the validity of sensor-less FM, 11 COPD patients admitted to a Telehealth pulmonary rehabilitation clinic and 10 healthy young volunteers (controls) were recruited. All participants completed the test indicating high feasibility. Strong correlations (0.72 < r < 0.99) were observed between the sensor-based FM and sensor-less FM to extract all frailty phenotypes and FI. After adjusting with age and body mass index(BMI), sensor-less FM enables distinguishing COPD group from controls (p < 0.050) with the largest effect sizes observed for weakness (Cohen’s effect size d=2.24), frailty index (d=1.70), and slowness (d=1.70). These pilot findings suggest feasibility and proof of concept validity of this sensor-less FM toward remote assessment of PF in COPD patients.
Application of Pore Size Analyzers in Study of Chinese Angelica Slices Drying

The objective of this article is to study the influence of pore size and distribution in plant tissue on drying behavior of plant materials using Chinese Angelica slices as an example. By using an automatic mercury injection apparatus and automatic surface area–porosity analyzer, the study compares the pore size distribution inside the matrix of a sample dried by 200 W microwave and 60°C hot air. The study also characterizes the matrix microstructure by scanning electronic microscopy (SEM) and discusses the drying dynamics of the sample, as well as the rehydration property of the dried sample. This work may be helpful for further investigation of the optimization of drying technology focused on micromechanisms and the quality of dried products.
Multi-Climate Factors and the Preceding Growth Stage of Vegetation Co-Regulated the Variation of the End of Growing Season in Northeast Inner Mongolia, China

The end of growing season (EOS) is an effective indicator of annual vegetation growth. Previous studies have revealed the dynamics of the EOS with climate change, while the influence of vegetation growth in preceding stage and peak of growing season (POS) on the EOS has not been thoroughly documented. In this study, we used four smoothing methods to obtain EOS dates from the Normalized Difference Vegetation Index (NDVI) in northeast Inner Mongolia (NIM) between 2001–2017, assessed the differences in the spatiotemporal variations of the EOS obtained by the four smoothing methods, and then investigated the impacts of climate factors, summer/ autumn vegetation growth and POS on the EOS. The results showed that the EOS dates obtained with different smoothing methods were broadly consistent in terms of their spatial patterns and temporal trends. In terms of climate factors, the EOS was driven mainly by preseason precipitation for the majority of vegetation types and advanced with increasing precipitation. For the steppe, both minimum temperature (Tmin) and relative humidity (RHU) played the most important roles in regulating the variation of EOS which was delayed with an increase in Tmin and reduction in RHU. Furthermore, our study found an earlier POS and vigorous vegetation growth in summer would jointly advance the steppe EOS, but these relationships were the opposite of each other in meadow and forest regions. Interestingly, the EOS of NIM was more related with vegetation growth in the most recent period before the EOS. This study highlights the importance of ecological processes in the preceding growth stage for understanding the dynamics of EOS.
Numerical Analysis of Temperature Distribution in Ellipsoidal Tumors in Magnetic Fluid Hyperthermia

The goal of the present work is to examine via computer simulations how the shape of a tumor, deviating from ideal spherical to an ellipsoidal one, affects the temperature distribution inside the tumor and on its surface, during magnetic fluid hyperthermia (MFH). The temperature distribution is modeled using the Pennes bio-heat equation. The magnetic nanoparticles (MNPs) are assumed to be homogeneously distributed throughout the cancerous region. The analysis is quantified in terms of the tumor sphericity, a morphological descriptor that describes how far the assumed tumor shape diverges from that of a perfect sphere. The results indicate that, under the same heating conditions, tumors with low sphericity diffuse temperature to the surrounding healthy tissue in a non-uniform manner, which suggests that ellipsoidal tumors may be more difficult to treat clinically as compared to ideally spherical ones.
A pilot study on carbon quantum dots for bioimaging of muscle myoblasts

Carbon quantum dots (CQD) are fluorescent nanoparticles that show potential in bioimaging as biocompatible fluorescent dye replacements. Even though numerous precursors and various fabrication processes are reported, the use of corrosive chemicals is widespread during most of the process. Recently, researchers have focused on green synthesis techniques for CQDs used in biological studies. In this work, we report on CQDs fabricated from prevalent carbon sources, namely paper and bread, using a facile chemical-free technique. This green synthetic route facilitated the production of luminescent CQDs with a broad emission range between 380 – 600 nm. The photoluminescence of the CQDs was analyzed, and a suitable candidate for bioimaging was identified. The CQDs obtained from bread exhibited comparatively high fluorescent and low cytotoxicity. Moreover, these CQDs were well internalized by C2C12 muscle myoblast cells and clearly luminescent in differentiated myotubes. The results will potentially aid in disease and intervention studies using C2C12 cell model systems.
Lattice dynamics investigation of different transition behaviors of cubic BaTiO3 and SrTiO3 by first-principles calculations

The lattice dynamics of cubic BaTiO3 and SrTiO3 at different crystal lattice volumes were investigated using first-principles density functional theory calculation. The computational results indicate that the Ti–O and A–O (A = Sr or Ba) interactions are responsible for the unstable ferroelectric Γ15 and antiferrodistortive R25 phonons, respectively. With decreasing volume, the Γ15 phonon behaviors of cubic SrTiO3 and BaTiO3 show a similar trend and the Ti–O repulsions are significantly enhanced, leading to the disappearance of ferroelectric instability. However, for BaTiO3 the large ionic radius of Ba with respect to Sr results in a repulsive Ba–O interaction and thereby the disappearance of the R25 instability, while the long-range characteristic of Sr–O pair are crucial for the antiferrodistortive instability of cubic SrTiO3. By analyzing the real-space interatomic force constants, it can be confirmed that the different antiferrodistortive behaviors of the two compounds are dictated by different short-range repulsions of A–O pairs. Moreover, owing to the smaller ionic radius of Sr relative to Ba, the lattice constant of SrTiO3 can be significantly reduced, leading to the absence of ferroelectric instability for SrTiO3. The substitution and different crystal volumes make the phase transitions of the two compounds entirely different.
Investigating the feasibility of combining EEG and EMG for controlling a hybrid human computer interface in patients with spinal cord injury

Objective. Human-computer interfaces (HCI) are potential tools for assisting (movement replacement) and rehabilitating (movement restoration) individuals with spinal cord injury (SCI). HCIs based on electroencephalography (EEG) have limited accuracy and hence control options; this could be improved by exploiting potential residual muscle activity (electromyography, EMG). The study objectives were to determine if combined EEG and EMG improves offline single-trial movement classification. Furthermore, the effect of number of classes and detection latency on the accuracies was investigated. Methods. Ten able-bodied and eight SCI subjects performed elbow flexion/extension at three force levels while EEG and EMG were recorded. Temporal and spectral features were extracted from the EEG and Hudgins time domain features were extracted from the EMG in 1-second time windows. The time window was shifted (200-ms shift) over 5second epochs around the movement onset. Each segment was classified in three scenarios (2, 3 or 7 classes) using linear discriminant analysis. Results. The accuracies obtained with EEG (51.2%) was outperformed by EMG (95.5%) and combined EMG and EEG (96.2%). Immediately after the EMG onset, the accuracies increased and rapidly reached a plateau. High accuracies were obtained for the different number of classes. Conclusion and Significance. EMG was crucial for obtaining high accuracies, and potential residual EMG should be exploited in HCIs to improve the performance. Force proved to be a viable option for SCI subjects with residual EMG to increase the number of classes for HCI control. These findings could assist design considerations of HCIs for SCI individuals.
Equivalent Surface Impedances for Below-Cutoff Propagation in Circular Waveguides

A relation between a metamaterial (MTM) liner for a circular waveguide and its equivalent surface impedance is made to allow for the replacement of the MTM liner with a metasurface (MTS). The equivalent surface impedance is found over a frequency range in a representative MTM-lined waveguide design. A below-cutoff backward-wave propagation region is successfully predicted by the MTS theoretical model.
Blind Image Deblurring via Local Maximum Difference Prior

Blind image deblurring is a well-known conundrum in the digital image processing field. To get a solid and pleasing deblurred result, reasonable statistical prior of the true image and the blur kernel is required. In this work, a novel and efficient blind image deblurring method which utilizes the Local Maximum Difference Prior (LMD) is presented. We find that the maximum value of the sum of the differences between the intensity of one pixel and its surrounding 8 pixels in the local image patch becomes smaller with motion blur. This phenomenon is an intrinsic feature of the motion blur process, we demonstrate it theoretically in this paper. By introducing a linear operator to compute LMD and adopting the $L_{1} $ norm constrain to the LMD involved term, an effective optimization scheme which makes use of a half-quadratic splitting strategy is exploited. Experimental results show that the presented method is more robust and outperforms the most advanced deblurring methods on both composite images and ground-truth scenes. Besides, this algorithm is more general because it does not require any heuristic edge selection steps or need too many extreme value pixels in the input image.
Different crystal forms of a rich hydrogen bond acceptor compound resulting from alternative C–H⋯O and orthogonal CO⋯CO molecular interaction patterns

The racemic compound 2,4,6,8-tetracarbomethoxybicyclo[3.3. 0]octa-2,6-diene-3,7-diol 3 is known to form a solvent-free crystal structure (Polymorph I) through repetition of a centrosymmetric dimeric unit that is constructed by concave face to concave face association of two shallow dish-shaped tetraester 3 molecules. Compounds employing such awkwardly shaped repeat units are known to be prone to yielding more than one crystal form. Systematic screening has now revealed a second solvent-free crystal form (Polymorph II), and also a family of essentially isostructural lattice inclusion compounds (Inclusion form I), of 3. The X-ray crystal structures of Polymorph II, and the p-xylene and cyclohexanol compounds of the inclusion crystal form, are described. The predominant weak interactions in all three crystal forms comprise C–H⋯O and orthogonal CO⋯CO attractive forces and their different arrangements are compared and contrasted.
EEG-based classification of visual and auditory monitoring tasks

Using EEG signals for mental workload detection has received particular attention in passive BCI research aimed at increasing safety and performance in high-risk and safety-critical occupations, like pilots and air traffic controllers. Along with detecting the level of mental workload, it has been suggested that being able to automatically detect the type of mental workload (e.g., auditory, visual, motor, cognitive) would also be useful. In this study, we developed a novel experimental protocol in which subjects performed a task involving one of two different types of mental workload (specifically, Auditory and Visual), each under two different levels of task demand (Easy and Difficult). The tasks were designed to be nearly identical in terms of visual and auditory stimuli, and differed only in the type of stimuli the subject was monitoring/attending to. EEG power spectral features were extracted and used to train linear discriminant classifiers. Preliminary results on three subjects suggested that the Auditory and Visual tasks could be distinguished from one another, and individually from a Baseline condition (which also contained nearly identical stimuli that the subject did not need to attend to), with accuracy significantly exceeding chance. This was true when classification was done within a workload level, and when data from the two workload levels was combined. Though further investigation is required, these preliminary results are promising, and suggest the feasibility of a passive BCI for detecting both type and level of mental workload.
High-temperature elasticity of polycrystalline orthoenstatite (MgSiO3)

Abstract Compressional and shear wave velocities of a polycrystalline specimen of MgSiO3 orthoenstatite have been measured by ultrasonic interferometry to 1373 K at 300 MPa in an internally heated gas-medium apparatus. The elastic wave velocities and bulk and shear moduli vary linearly with temperature to 1073 K. Below 1073 K, the temperature derivatives of the elastic moduli [(∂KS/∂T)P = -28.3(7) MPa/K and (∂G/∂T)P = -14.5(1) MPa/K, respectively] determined in this study are consistent with averages of single-crystal elastic constants measured using Brillouin spectroscopy by Jackson et al. (2007). The measured temperature dependence of elastic moduli, along with pressure dependence of elastic moduli, thermal expansion and calorimetric data have been assimilated into a finite-strain equation of state of the type proposed by Stixrude and Lithgow-Bertelloni (2005). This analysis suggests significant revisions to the optimal values of the zero-pressure Grüneisen parameter γ0 and its zero-pressure logarithmic volume derivative q0. The unusually high absolute values of (∂K/∂P)T and (∂K/∂T)P are related through the extrinsic part of the temperature derivative. Above 1073 K, a pronounced softening of the elastic wave velocities is observed, which is plausibly associated with a phase transformation for which there is microstructural evidence: The recovered specimen was found to have transformed to the low-pressure clinoenstatite polymorph.
Numerical Study on AC Loss Characteristics of Conductor on Round Core Cables Under Transport Current and Magnetic Field

This paper first introduced a conductor on round core (CORC) cable model using the finite-element method (FEM). Then, the AC loss dependent on transport current was studied, indicating the eddy current loss of the copper former. Finally, we calculated the generated loss under a simultaneous application of transport current and magnetic field, showing even a small magnetic field resulted in a significant increase in transport AC loss.
Power Reduction Estimation of 5G Active Antenna Systems for Human Exposure Assessment in Realistic Scenarios

Maximum power extrapolation techniques from measured data are usually employed to assess the compliance with standards of average fields radiated by base stations. However, such techniques provide an upper bound, which is not reached in real scenarios. This is particularly true in 5G Communications, where Active Antenna Systems allow a decrease of the average power density according to the adopted scheduling strategy. This paper is focused on the power reduction estimation in realistic scenarios. In particular a deterministic model of a communication system is used to obtain simple formulas only requiring the knowledge of the served area angular extension and of the Envelope Radiation Pattern of the antenna. The model, developed for beam steering and grid of beams antennas, is also extended to analyze the case of Multi User massive Multiple Input Multiple Output (MU-mMIMO) antennas with single layer per user, showing that under proper hypothesis on the beams of the antenna it is possible to estimate the reduction parameter without the explicit knowledge of the number of layers of MU-mMIMO systems. In spite of the simplicity of the approach, comparison with stochastic models and results reported in recent literature show that the formulas obtained using the model proposed in this paper allow to obtain a useful approximation of the power reduction factor, making the formulas suitable for a preliminary fast estimation of the Electromagnetic Field in 5G cells for human exposure assessment.
Picture completion reveals developmental change in representational drawing ability: An analysis using a convolutional neural network

Drawings of children may provide unique insights into their cognition. Previous research showed that children's ability to draw objects distinctively develops with increasing age. In recent studies, convolutional neural networks have been used as a diagnostic tool to show how the representational ability of children develops. These studies have focused on top-down task modifications by asking a child to draw specific objects. Object representations, however, are influenced by bottom-up visual perception as well as by top-down intentions. Understanding how these processing pathways are integrated and how this integration changes with development is still an open question. In this paper, we investigate how bottom-up modifications of the task affect the representational drawing ability of children. We designed a set of incomplete stimuli and asked children between two and eight years to draw on them without specific task instructions. We found that the higher layers of a deep convolutional neural network pretrained for image classification on objects and scenes well differentiated between different drawing styles (e.g. scribbling vs. meaningful completion), and that older children's drawings were more similar to adult drawings. By analyzing representations of different age groups, we found that older children adapted to variations in the presented stimuli in a more similar way to adults than younger children. Therefore, not only a top-down but also a bottom-up modification of stimuli in a drawing task can reveal differences in how children at different ages represent different concepts. This task design opens up the possibility to investigate representational changes independently of language ability, for example, in children with developmental disorders.