Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating the integration of eye-tracking and motion capture technologies: Quantifying the accuracy and precision of gaze measures

Integrating mobile eye tracking and optoelectronic motion capture enables point of gaze to be expressed within the laboratory co-ordinate system and presents a method not commonly applied during research examining dynamic behaviors, such as locomotion. This paper examines the quality of gaze data collected through the integration. Based on research suggesting increased viewing distances are associated with reduced data quality; the accuracy and precision of gaze data as participants (N = 11) viewed floor-based targets at distances of 1–6 m was investigated. A mean accuracy of 2.55 ± 1.12° was identified, however, accuracy and precision measures (relative to targets) were significantly (p < .05) reduced at greater viewing distances. We then consider if signal processing techniques may improve accuracy and precision, and overcome issues associated with missing data. A 4th-order Butterworth lowpass filter with cut-off frequencies determined via autocorrelation did not significantly improve data quality, however, interpolation via Quintic spline was sufficient to overcome gaps of up to 0.1 s. We conclude the integration of gaze and motion capture presents a viable methodology in the study of human behavior and presents advantages for data collection, treatment, and analysis. We provide considerations for the collection, analysis, and treatment of gaze data that may help inform future methodological decisions.
Bibliometric Analysis of Information Theoretic Studies

Statistical information theory is a method for quantifying the amount of stochastic uncertainty in a system. This theory originated in communication theory. The application of information theoretic approaches has been extended to different fields. This paper aims to perform a bibliometric analysis of information theoretic publications listed on the Scopus database. The data of 3701 documents were extracted from the Scopus database. The software used for analysis includes Harzing’s Publish or Perish and VOSviewer. Results including publication growth, subject areas, geographical contributions, country co-authorship, most cited publications, keyword co-occurrence analysis, and citation metrics are presented in this paper. Publication growth has been steady since 2003. The United States has the highest number of publications and received more than half of the total citations from all 3701 publications. Most of the publications are in computer science, engineering, and mathematics. The United States, the United Kingdom, and China have the highest collaboration across countries. The focus on information theoretic is slowly shifting from mathematical models to technology-driven applications such as machine learning and robotics. This study highlights the trends and developments of information theoretic publications, which helps researchers to understand the state of the art of information theoretic approaches for future contributions in this research domain.
Physical, Rheological and Mechanical Properties of Alkali Activated Hydrogels Based on Nanofibrillated Cellulose

ABSTRACT Hydrogels are classified as a three-dimensional network system, capable of retaining large amounts of water while preserving their shape and dimensional stability. Due to their natural origin and biocompatibility with human tissue, cellulose nanofibrils are often considered to be promising candidates for bioactive hydrogels preparation. For such applications, their responsiveness under different types of mechanical load, including multiple cyclic compressions, is of crucial importance. In the present study, cellulose nanofibril-based hydrogels were initiated though a simple alkali neutralization treatment. Structural, rheological and compressive features were investigated as a function of elevated NaOH concentration and physical gelling conditions. It was found that a sufficiently concentrated alkaline solution allows the formation of mechanically robust cellulose nanofibril hydrogels, which can be dried to the state of ultralight material, aerogel, of low density (0.057 g cm −3), superior porosity (96.2%), super water absorbant capacity (1200%), and exceptional shear and compressive load resilience with elasticity modulus of 9.3 kPa. These outstanding characteristics can be predominantly attributed to the polymorphic conversion of cellulose I to cellulose II, which results from the mercerization of cellulose nanofibrils and creates a stable and firm hydrogels texture.
The Use of New Waste-Based Plasticizer Made from Modified Used Palm Oil for Non-Glutinous Thermoplastic Starch Foam

A novel waste-based plasticizer derived from modified used palm oil (mUPO) was successfully developed and has been used as a new plasticizer to non-glutinous thermoplastic starch foam to improve their properties. The molecular weight and hydroxyl number of the mUPO was 3150 g/mol and 192.19 mgOH/g, respectively. The effects of mUPO content ranging from 0 to 9 phr were investigated. The results revealed that the optimal mUPO content as an additive was 6 wt%. The addition of mUPO had a direct effect on the mechanical properties and thermal properties. The impact strength increased from 1.30 to 4.55 J/m, while the glass transition temperature (Tg) decreased from 70.83 to 66.50 °C by increasing mUPO from 0 phr to 6 phr in the thermoplastic starch foam. The mUPO, on the other hand, has also the potential to reduce shrinkage from 33.91 to 21.77% and moisture absorption from 5.93 to 1.73% by increasing the content from 0 phr to 6 phr in starch foam. Furthermore, the mUPO helps the forming of the foam structure as measured by SEM, and the mUPO utilization of waste-based material could be a promising green alternative plasticizer for starch components, especially starch foam applications.
Meeting the Moment: Addressing Barriers and Facilitating Clinical Adoption of Artificial Intelligence in Medical Diagnosis.

Julia Adler-Milstein, PhD, University of California-San Francisco; Nakul Aggarwal, BS, University of Wisconsin-Madison; Mahnoor Ahmed, MEng, National Academy of Medicine; Jessica Castner, PhD, RN-BC, Castner Incorporated; Barbara J. Evans, PhD, JD, University of Florida; Andrew A. Gonzalez, MD, JD, MPH, Regenstrief Institute; Cornelius A. James, MD, University of Michigan; Steven Lin, MD, Stanford University; Kenneth D. Mandl, MD, MPH, Boston Children’s Hospital; Michael E. Matheny, MD, MS, MPH, Vanderbilt University Medical Center and Veterans Affairs; Mark P. Sendak, MD, MPP, Duke University; Carmel Shachar, JD, MPH, Harvard University; and Asia Williams, MPH, National Academy of Medicine
A research agenda proposal on the influence of ApexBrasil on export, internationalisation and foreign trade

Objective: The present technical report aimed at presenting a research agenda regarding the influence of the Brazilian Trade and Investment Promotion Agency (ApexBrasil) on academic research about export, internationalisation, and foreign trade for academia, policymakers, practitioners, and other stakeholders. Method: We pursued a case study approach divided in a two-stage process. Firstly, we systematically reviewed 35 articles related to ApexBrasil’s influence on scientific research. Secondly, we analysed official documents and conferences, besides consulting a panel of specialists from ApexBrasil, in order to propose the research agenda. Main Results: Firstly, the results suggested that the knowledge about ApexBrasil’s influence on scientific research is scattered in different journals, researchers, and themes; furthermore, many studies do not have an impact on the international academy. Secondly, based on the data analysed, we propose a research agenda that might narrow the gap between ApexBrasil, academia, and other stakeholders. Relevance / Originality: The findings suggest unique insights about how and to what extent ApexBrasil’s influence is reported by scientific research and show which themes for future investigations are aligned with the agency’s interests, as well as the interests of its stakeholders in a scenario affected by the COVID-19 pandemic. Theoretical / Methodological Contributions: Our main contributions consist in a research agenda proposal based on theoretical and practical perspectives developed as a technical report. By doing so, we seek to raise awareness of academia, practitioners, and policymakers about ApexBrasil’s influence and potential relevance for international business studies, whilst pointing out important research gaps in the literature and potential new research avenues.
Herbarium Specimens May Provide Biased Flowering Phenology Estimates for Dioecious Species

Premise of research. Measuring phenology from herbarium specimens has become a widely used, powerful method for investigating the effects of climate change on plants across space, time, and phylogeny. However, it is not known whether and how biases in plant collecting might affect conclusions, particularly for dioecious species. Methodology. We examined the effects of spring temperature and latitude on the flowering phenology of male and female blunt-lobed spicebush (Lindera obtusiloba Blume) plants from across East Asia using 88 herbarium specimens and digitized photographs collected from 1918 to 2018. Pivotal results. Temperature and latitude did not affect the flowering phenology of either sex when analyzed separately. Surprisingly, however, female flowering plants were collected on average 25 d later than male plants. This difference is likely due to male plants being preferentially collected during the flowering season (with showy but more ephemeral flowers) and female plants being collected after the peak flowering season (with nonreceptive flowers persisting later into the season). Conclusions. Researchers investigating phenology using herbarium specimens need to be aware of possible collecting bias in dioecious species and species with persistent flowers. Herbarium collectors and photographers should sample both male and female plants.
Performance Analysis on Non-Clustering Routing
Techniques for Homogeneous and Heterogeneous Wireless
Sensor Networks

Wireless sensor network typically consists of a large number of low power and multiple functions-based sensor nodes that are spread in environment area. These sensor nodes are small/tiny is size but have sensing, computation and wireless transmission abilities. Different types of routing protocols invented for WSNs where energy efficiency saving is main concern for whole network. The performance of WSN depends on the types of routing technique, where it has been implemented. This paper gives comprehensive survey between existing non-cluster-based routing protocols of WSN. Initially in this paper we explain the routing and design challenges for WSN and later on focus on the comprehensive review of different routing protocols. Division of the routing protocols into non-cluster and cluster-based routing protocols for both homogeneous as well as heterogeneous networks. The tabular representation for different parameters for non-clustering routing protocols is explained in this paper.
A Thermal-Hydraulic-Gas-Mechanical Coupling Model on Permeability Enhancement in Heterogeneous Shale Volume Fracturing

Heat treatment on shale reservoirs can promote the development of secondary fractures in a matrix on the basis of hydraulic fracturing, forming multi-scale gas–water seepage channels and strengthening the gas desorption. Experimental evidence shows that heat treatment can enhance gas recovery in the same mining life. Heat treatment on a shale gas reservoir is a multi-physical and multi-phase coupling process. However, how the thermal stimulation interacts with nonlinear two-phase flow in heterogeneous shale volume fracturing has not been clear. In this paper, a fully coupled THGM model for heating-enhanced shale-gas recovery in heterogeneous shale reservoirs is proposed. First, the governing equations are formulated for the shale-reservoir deformation involving both gas adsorption and thermal expansion, the permeability evolution model for the cracking process of fractured shale, the gas–water two-phase continuity equation considering the effects of gas solubility and the heat transfer equation for heat conduction and convection. The interactions among stress, temperature and seepage in a heterogeneous shale reservoir were studied. Secondly, a test on shale permeability after 50 °C temperature treatment was conducted. The evolution of temperature, capillary pressure, water and gas saturation and the permeability of shale during the heat treatment of the reservoir were numerically analyzed. Finally, the gas production from a shale gas reservoir was numerically simulated with this THGM model. The numerical results indicated that the thermal-induced fracturing, gas desorption and separation from water make predominant contributions to the evolution of permeability. The heat treatment can enhance cumulative gas production by 58.7% after 27.4 years of heat injection through promoting gas desorption and matrix diffusion.
A Disjoint Samples-Based 3D-CNN With Active Transfer Learning for Hyperspectral Image Classification

Convolutional neural networks (CNNs) have been extensively studied for hyperspectral image classification (HSIC). However, CNNs are critically attributed to a large number of labeled training samples, which outlays high costs in terms of time and resources. Moreover, CNNs are trained on some samples and have been tested on the entire HSI. Perhaps, the entire HSI is taken into account at test time to appropriately generate the ground-truth maps. To obtain a higher accuracy while considering the limited availability of training samples and disjoint validation and test samples, this work proposes a fast and compact 3-D CNN-based active learning (AL) for HSIC that integrates both deep transfer learning and AL into a unified framework. In the proposed methodology, a 3-D CNN model is trained with very few training samples (i.e., 5%, only) and in the next phase, the most informative and heterogeneous samples are queried from the validation set (candidate set) based on the fuzziness, mutual information, and breaking ties of the trained model. The 3-D CNN model is later fine-tuned (rather than retraining from scratch) with the new training samples (i.e., 200 samples are selected in each iteration) to reduce the computational cost. The proposed method has been compared with the state-of-the-art traditional and deep models proposed for HSIC. Experimental results proved the superiority of our proposed method on several benchmark HSI datasets with significantly fewer labeled samples. MATLAB demo can be accessed on GitHub: github.com/mahmad00
Performance Evaluation of Nano-RTD VCO Devices for On-Body THz Nano-Communication Applications

The constant miniaturization of devices and the insatiable demand for higher bandwidth are driving the development of ultra-compact THz systems. This work proposes a nano-RTD VCO operating at the THz region for on-body nano-communication systems. A semi-analytical tool for evaluating the performance of a transmitter based on the nano-RTD VCO considering different carrier-less modulations is developed. Results show that the device can operate in the H-band (220-325 GHz) while having ultra-low power consumption down to 160 nW at 0.11 Tb/s for reaches up to 25 mm. The device may enable a plethora of applications, including sensing, monitoring, and medical diagnosis.
Design and Performance of High Voltage Chip-Level Series-Connected SiC MOSFET Module

In medium voltage (MV) and high voltage (HV) applications, HV SiC mosfet with a single chip competes with series-connected low voltage (LV) SiC mosfet. The cost of the former is high due to immature process, and the parasitic inductance of the latter is large due to series-connected devices. In this article, a novel chip-level series-connected SiC mosfet module based on planar packaging is proposed to compromise cost and parasitic inductance. Several LV chips are connected in series through metal layers, and then packaged as a whole. Compared with HV module with a single chip, the proposed module has significant advantages in cost. Considering the effects of the buffer layer and direct bonded copper on the parasitic inductance, junction temperature, thermal stress, and electric field, electro-thermo-mechanical simulation is conducted to optimize the structure. Compared with existing series-connected structures, the parasitic inductance of the proposed module is reduced by at least 50.15%. Finally, 6.5 kV chip-level series-connected module with six 1.2 kV SiC mosfet is fabricated and tested. The results show the performance of the proposed module is comparable with that of HV module with a single chip, which means that the application of the proposed module in MV and HV conditions is promising.
Dual-plane Terahertz Hologram with Diffractive Optical Elements

A dual-plane terahertz hologram based on diffractive optical elements is presented. A 2D dielectric array THz hologram with elements comprised of various heights is designed by applying a nonlinear optimization method. The designed hologram masks are fabricated using 3D printing technology. Full-wave FDTD simulations and experimental results demonstrate that the designed hologram can achieve dual-plane imaging, which has the potential to be used in displays and data storage.
Estudo de métodos numéricos para eliminação de ruídos em imagens digitais

The purpose of this work is to present a study on the application of numerical methods for the resolution of model considered by Barcelos, Boaventura and Silva Jr [7], for image denoising through a partial differential equation, and to consider a stability analysis of an iterative method usually applied to this model. A comparative analysis among various considered methods is carried out through experimental results for synthetic and real images. Key-words: Numerical methods, partial differential equation, stability, image restoration.
The Mediation Role of Self-Control in the Association of Self-Efficacy and Physical Activity in College Students

Global COVID-19 lockdown measures have led to an apparent decrease in physical activity. This study aimed to explore the explanatory function of self-control’s mediating role between self-efficacy and physical activity among college students. The analysis used the data of 1627 university students (aged 19.41 ± 0.66, range 17–28, 40.5% males) at Shanghai Jiao Tong University. Self-efficacy, self-control, and physical activity were tested, respectively, by the general self-efficacy scale, the new brief self-control scale, and the International Physical Activity Questionnaire (IPAQ) scale, which were analyzed by SPSS software. Correlation analysis showed that self-efficacy, self-control, and physical activity were related in pairs. Comparing the two dimensions of self-control, we found that self-discipline mediated the relationship between self-efficacy and PA, and impulse control did not mediate the relationship. Regarding the gender difference according to multi-group analysis, findings showed that females need higher self-discipline from the path of self-efficacy to physical activity improvement than males.
Cosmological singularities in Born-Infeld determinantal gravity

The Born-Infeld determinantal gravity has been recently proposed as a way to smooth the Big Bang singularity. This theory is formulated on the Weitzenbock space-time and the teleparallel representation is used instead of the standard Riemannian representation. We find that although this theory is shown to be singularity-free for certain region of the parameter space in which the divergence of the Hubble rate at the high energy regime is substituted by a de-Sitter stage or a bounce in a Friedmann-Lemaitre-Robertson-Walker universe, cosmological singularities such as Big Rip, Big Bang, Big Freeze, and Sudden singularities can emerge in other regions of the configuration space of the theory. We also show that all these singular events exist even though the Universe is filled with a perfect fluid with a constant equation of state.
Using Superimposed Coding Of N-Gram Lists For Efficient Inexact Matching

N-gram encoding for strings provides good inexact matching performance, but pays a large storage penalty. We describe a method for superimposed N-gram coding that provides more than a 40-60% reduction in the storage space required over the typical N-gram implementation while giving good speed and matching performance. Our system uses bit vectors to represent the occurrence of sets of N-grams in lexicon strings. The space savings comes from the notion of superimposing sets of N-grams onto single bit vectors. We also discuss an extension of the superimposed coding idea which encodes every N-gram with an ensemble of bit vectors in such a way as to yield even greater space savings.
Combined Machine Learning Techniques For Characteristics Classification and Threshold Voltage Extraction of Transistors

We present an autonomous 2-step Machine Learning based approach for characteristics classification and key parameter extraction for transistors. The first step is a multi-model ensemble, composed of Machine Learning, more particularly a Convolutional Neural Network (CNN) approach to enable fast classification of transistor characteristics. The second step is another CNN model to extract the threshold voltage parameters that enable us to measure the performance of ultra-scaled MOSFETs. Our CNN-based classifier has demonstrated accuracy above 90% with an execution time significantly faster than that of the current human expert-based methods while our Vth extractor has demonstrated less than 8mV error rate in the filtered dataset that comes from the classifier. The proposed techniques which do not incorporate hard-coded domain knowledge, and are also tested with input data coming from 16nm-node FinFET technology and evaluated by a consensus of experts to prove the universality of the models using the same parameters.
Dynamical evolution of supernova remnants breaking through molecular clouds

We carry out three-dimensional hydrodynamic simulations of the supernova remnants (SNRs) produced inside molecular clouds (MCs) near their surface using the HLL code (Harten et al. 1983). We explore the dynamical evolution and the X-ray morphology of SNRs after breaking through the MC surface for ranges of the explosion depths below the surface and the density ratios of the clouds to the intercloud media (ICM). We find that if an SNR breaks out through an MC surface in its Sedov stage, the outermost dense shell of the remnant is divided into several layers. The divided layers are subject to the Rayleigh-Taylor instability and fragmented. On the other hand, if an SNR breaks through an MC after the remnant enters the snowplow phase, the radiative shell is not divided to layers. We also compare the predictions of previous analytic solutions for the expansion of SNRs in stratified media with our onedimensional simulations. Moreover, we produce synthetic X-ray surface brightness in order to research the center-bright X-ray morphology shown in thermal composite SNRs. In the late stages, a breakout SNR shows the center-bright X-ray morphology inside an MC in our results. We apply our model to the observational results of the X-ray morphology of the thermal composite SNR 3C 391.