Miracle-dz/UniFAR-FTUs huggingface dataset:
Causal Evidence for Neural Oscillations in Cognition

Author(s): Riddle, Justin | Advisor(s): D'Esposito, Mark T | Abstract: Since early recordings of the human brain, rhythmic electric fields have been observed emanating from regions involved in the specific information processing demands of which the human subject is engaged. Different oscillatory frequencies have been associated with different types of information processing. Neuroscience in the 21st century has seen a revival in research studying the neural basis of oscillatory activity that has deepened our understanding of the complex network level coordination of brain regions. However, causal evidence for the mechanistic role of neural oscillations is sparse, yet provides vital implications for the neural basis of cognition.The first experiment examines the specific role of beta (15-30 hertz) and gamma (30-50 hertz) frequency oscillations in top-down and bottom-up attention. By applying rhythmic transcranial magnetic stimulation (TMS), the purported cognitive contributions of beta and gamma oscillations are analyzed with respect to a visual search task that varies the level of top-down attention required for optimal performance.The second experiment examines the specific role of theta (3-8 hertz) and alpha (8-12 hertz) frequency neural oscillations in the reactivation and suppression of working memory representations. Rhythmic TMS in a retro-cued delayed match-to-sample task causally tested previously reported oscillatory neural signatures for their mechanistic contributions to working memory. The degree to which subjects engaged the regions targeted by TMS in functional magnetic resonance imaging (fMRI) predicted the frequency specific effect of rhythmic TMS.Simultaneous TMS and fMRI offers a unique opportunity to causally test the communication through coherence proposed with neural oscillations. By stimulating a single brain region in multiple frequency bands, the frequency-by-network specific spread of activation can be quantified. Towards this end, the third experiment develops the methodology of concurrent TMS-fMRI with a proof of principle experiment demonstrating the spread of TMS effects through a functional network. In sum, these projects test for the causal role of neural oscillations in cognition and pave the way for future research to study the network level organization of the brain via neural oscillations.
Deep Learning-Aided Iterative Detector for Massive Overloaded MIMO Channels

The paper presents a deep learning-aided iterative detection algorithm for massive overloaded MIMO channels. The proposed algorithm is based on the iterative soft thresholding algorithm for sparse signal recovery. The notable feature of the proposed scheme is that the detector has a reasonably low computational cost and contains trainable parameters which can be optimized with standard deep learning techniques. The number of trainable parameters is constant to the channel size, which promotes fast and stable training processes for the detector. The numerical simulations show that the proposed detector achieves a comparable detection performance to the state-of-the-art IW-SOAV detector for massive overloaded MIMO channels.
Pragma-Dialectical Argumentative Studies on International Court of Arbitration for Sport

: From pragma-dialectical argumentation theory, model of critical discussion and triangle of strategic maneuvering can deal with argumentative discourse normatively and descriptively, which remains logical framework and offers effective and flexible space for strategic maneuvering. Argumentative reconstruction under pragma-dialectical perspective provides the language approach of pragmatic trace of argumentative participants to further explore interactive principles, argumentative strategies and persuasive effects of rhetorical generation mechanism of International Court of Arbitration for Sports (ICAS) judicial language, which reflects paradoxical, independent and flexible institutional features of ICAS. Further, it has been discovered that there are sub-optimal settings both in trial discourse and arbitration text. Argumentative moves in sub-optimal settings are not into reasonable judgement of pragma-dialectical argumentation theory but it is still persuasive with operation of triangle of strategic maneuvering powered by the stimulus of strategic maneuvering.
Study on interfacial leakage characteristics of rubber sealing under temperature cycle conditions in PEM fuel cell

The amount of leakage is the only direct indicator of the sealing performance of a proton exchange membrane fuel cell (PEMFC). In this work, a predictive model is developed to quantitatively evaluate the variation of leakage for a PEMFC under temperature cycling conditions. The method first uses the Lattice-Boltzmann method to simulate the gas flow within the contact interfacial gap at various heights. Then the finite element method is used to analyze the local and macroscale contact state of the sealing interface and to clarify the effect of contact stresses on the interfacial gap height. Finally, the generalized Maxwell model, which considers time-temperature transfer and stiffness growth, is used to calculate the interfacial contact stresses under temperature cycling. The validity of the model was verified by comparison with experimental data from the available literature. Further analysis showed that reduced start-up temperature exacerbated the stress relaxation effect and decreased the service life of the seal material. When the start-up temperature is reduced from 25 °C to −20 °C, the model predicts that the service life of the PEMFC will be reduced by 100 temperature cycles or more. The leakage variation in a cycle was also discussed, and it was found that the leakage fluctuation became more and more significant as the number of cycles increased, weakening system reliability.
Constraints on heavy dark matter annihilation and decay from electron and positron cosmic ray spectra

Annihilation or decay of dark matter (DM) could contribute to the electron and positron cosmic-ray flux, allowing for constraints on DM parameters from its measurement. CALET is directly measuring the energy spectrum of electron+positron cosmic rays up into the TeV region most important for studying heavy DM, while AMS-02 provides a positron-only spectrum below the TeV range. Limits on DM annihilation and decay well into the TeV mass range have been derived from a combined analysis of both data-sets with an astrophysical background model including pulsars as the origin of the positron excess and individual nearby supernova remnant sources.
Effects of compaction on embankment breach due to overtopping

ABSTRACT Despite many embankment failures worldwide, data on such failures are limited. An understanding of the embankment failure and the dominant parameters affecting the failure are crucial for predicting and modelling the breach process. Laboratory experiments are conducted on overtopping of embankments consisting of uniform homogenous sand and constructed with different levels of compaction. The temporal changes in the embankment surface profiles and the downstream discharge are measured. Two dimensionless equations are developed for the variation of crest height and embankment bottom length with time as a function of embankment-material dry density. A simple model assuming triangular shape is proposed for the development of breach shape for different compaction levels. Except during the initial stage of the failure, proposed model prediction and the observed data match satisfactorily. The proposed model for the crest height satisfactorily predicts the failure of a laboratory test and three dam failures in SC.
Core stability status classification based on mediolateral head motion during rhythmic movements and functional movement tests

Objective Core stability assessment is paramount for the prevention of low back pain, with core stability being considered as the most critical factor in such pain. The objective of this study was to develop a simple model for the automated assessment of core stability status. Methods To assess core stability—defined as the ability to control trunk position relative to the pelvic position - we used an inertial measurement unit sensor embedded within a wireless earbud to estimate the mediolateral head angle during rhythmic movements (RMs) such as cycling, walking, and running. The activities of muscles around the trunk were analyzed by an experienced, highly trained individual. Functional movement tests (FMTs) were performed, including single-leg squat, lunge, and side lunge. Data was collected from 77 participants, who were then classified into good and poor core stability groups based on their Sahrmann core stability test scores. Results From the head angle data, we extrapolated the symmetry index (SI) and amplitude of mediolateral head motion (Amp). Support vector machine and neural network models were trained and validated using these features. In both models, the accuracy was similar across three feature sets for RMs, FMTs, and full, and support vector machine accuracy (∼87%) is greater than neural network (∼75%). Conclusion The use of this model, trained with head motion-related features obtained during RMs or FMTs, can help to accurately classify core stability status during activities.
Functional Overlay Model of Persistent Post-Concussion Syndrome

Persistent post-concussion syndrome (PPCS) is a complex and debilitating condition that can develop after head concussions or mild traumatic brain injury (mTBI). PPCS is characterized by a wide range of symptoms, including headaches, dizziness, fatigue, cognitive deficits, and emotional changes, that can persist for months or even years after the initial injury. Despite extensive research, the underlying mechanisms of PPCS are still poorly understood; furthermore, there are limited resources to predict PPCS development in mTBI patients and no established treatment. Similar to PPCS, the etiology and pathogenesis of functional neurological disorders (FNDs) are not clear neither fully described. Nonspecific multifactorial interactions that were also seen in PPCS have been identified as possible predispositions for FND onset and progression. Thus, we aimed to describe a functional overlay model of PPCS that emphasizes the interplay between functional and structural factors in the development and perpetuation of PPCS symptoms. Our model suggests that the initial brain injury triggers a cascade of physiological and psychological processes that disrupt the normal functioning of the brain leading to persistent symptoms. This disruption can be compounded by pre-existing factors, such as genetics, prior injury, and psychological distress, which can increase the vulnerability to PPCS. Moreover, specific interventions, such as cognitive behavioral therapy, neurofeedback, and physical exercise can target the PPCS treatment approach. Thus, the functional overlay model of PPCS provides a new framework for understanding the complex nature of this condition and for developing more effective treatments. By identifying and targeting specific functional factors that contribute to PPCS symptoms, clinicians and researchers can improve the diagnosis, management, and ultimately, outcomes of patients with this condition.
Model Predictive Direct Motion Control for Distributed Drive Electric Vehicles

For the motion of distributed drive electric vehicles, this paper deigns a novel motion control strategy based on model predictive control, which can control the longitudinal and lateral motion simultaneously. Different with traditional strategies containing one vehicle controller and four motor controllers, this strategy treats the vehicle and its in-wheel motors as one control object and uses only one controller to realize motion control, so that control costs are reduced and the handling performance is improved. First, an improved unified model of the vehicle and in-wheel motors is established to predict future states. Considering different time constants in vehicle dynamic system and motor electrical system, coupling predictions are analyzed in detail and a linear model is proposed to simplify the complex computation. Then, based on the fact that inverters of in-wheel-motor systems have discrete and finite voltage vectors, a model predictive direct motion control strategy is proposed. A cost function is designed to find out optimal voltage vectors which make vehicle follow the desired motion and meet constrains. Finally, to deal with huge amount of calculation and over-actuation problem caused by four in-wheel-motor systems, a deadbeat solution is applied to optimize the optimal voltage vectors calculation. Simulations under the proposed and traditional strategies are carried out, in which that the proposed strategy can realize the vehicle motion control well in different directions, and improve the vehicle handling performance. A practical implementation method is also provided experimentally to realize the strategy on four-motor system.
Neo-R1000: A Fast And Efficient Compact Spectrograph For Emission Line Objects Study At Bosscha Observatory

In 2015, the Institute Teknologi Bandung (ITB) signed a Memorandum of Understanding with Sangyou Kyoto University (KSU). One realization of collaboration between ITB and KSU is observational program of Novae using a compact spectrograph NEO-R1000 (Novae and Emission line Objects with Resolution of 1000). This spectrograph is mounted at the Celestron C-11 (F/10.0) reflector and supported by a Losmandy G-11 equatorial mounting inside the GAO-ITB sliding roof building, Bosscha observatory, Lembang. The unique configuration of this spectrograph is the employment of mirror collimator and camera lens with focal length ratio of 3:1. This makes it has high speed characteristics. A slit width of 6.5 μm (4.7” @ C-11 reflector ) is combined with a fixed transmission grating of 600 grooves/mm and equipped with a ST-8 XME CCD camera (9 μm per pixel, 1530 × 1024 pixels), resulting in a resolution of R≈ 1000 at a wavelength of 5800 Å with effective spectrum wavelength coverage Δl 4000-8000 Å. NEO-R1000 spectrograph has additional peripherals such as a Fe-Ne-Ar hollow cathode tube (HTC) which is used as a comparison source. We take flat-field spectrum by using an acrylic board and a halogen lamp. The main primary aim of this spectrograph is to observe the Classical Novae in the southern sky as part of Collaborative Spectroscopic Observations for the Detection of Molecules in Classical Novae. This spectrograph can also be used to observe other emission line objects such as Planetary Nebulae, Comets, P Cygni star type, WR stars and Be stars. In June 2015, this spectrograph was successfully used to observe Nova Sgr 2015 no 2. Further developments of this spectrograph includes constructing a rotator to be attached to the flange of telescope to ensure high flexibility in observation of extended objects. In the future, a fiber optic connecting output pupil with the entrance slit of the spectrograph will be deployed to improve observational effectivity while reducing the load of spectrograph on telescope.
Design and implementation of a dual polarised L-band parabolic dish antenna for NeXtRAD

Research into multi-static, multi-band networked radar has led to the development of the NeXtRAD radar system. This dissertation will investigate the design and implementation of a dual polarised L-Band prime focus dish antenna with a centre frequency of 1.3 GHz and a HPBW of 10° in the azimuth plane. The antenna is required to handle a peak power of 1.5 kW over a 50 MHz bandwidth and be able to withstand environmental factors such as wind while mounted on a tripod. This dissertation forms part of the larger NeXtRAD project and as such, the antenna design requirements have been set based on the wider system specifications. Previous investigations into the feasibility of various antenna designs have concluded that a prime focus parabolic dish antenna would be the most appropriate to meet the design requirements. The dissertation details the design and manufacturing process followed. All antenna parameters have been simulated using a combination of FEKO v7 and CST 2014 to compare and verify the designs and simulations. Due to manufacturing limitations, the optimal antenna design could not be manufactured and, as a result, compromises had to be made in order for an antenna prototype to be manufactured and tested. These tests include, amongst others, characterisation of the return loss, cross polarisation, gain, beamwidth and beam pattern of the antenna in both planes of polarisation. These results have been recorded, analysed and compared to those found through simulations. It has been shown that the measured results correspond well with the simulated results, therefore illustrating that with adequate manufacturing facilities, the optimally designed and manufactured antenna will meet the system specifications. The built antenna prototype has been found to have an azimuth HPBW of 13.9° and 12.4° when horizontally and vertically polarised respectively. The prototype antenna meets all bandwidth and power requirements while maintaining a relatively compact size. The results have shown that using a prime focus parabolic dish antenna to meet the strict requirements is both feasible and practical.
Effect of Biopipe Total Flowrate on Venturi Aerator Performance

There is a vacuum created when water goes past a pipe constriction. Air may be pulled into the main flow by drilling a hole in the pipe near where the vacuum happens. Venturi aerator is an example of the application in action. A vacuum is formed at the suction holes of the Venturi tube when there is a small difference in pressure between the input and output sides. To demonstrate the link between total flow rate and Venturi aerator performance, a Venturi aerator (model 1584) was introduced at a specific point in a Biopipe system. For this purpose, a physical model on a pilot scale was constructed and installed in an existing sewage treatment plant. Dissolved oxygen concentrations were measured at four locations along the Biopipe at different values of wastewater flowrates. The study results showed that raising the total flow rate increased the amount of air injected by the Venturi aerator. When the total flow rate was less than 4 m3/hour, the Venturi aerator stops sucking air and produces negative consequences.
Bootstrap likelihood ratio test for Weibull mixture models fitted to grouped data

Abstract Weibull mixture models are widely used in a variety of fields for modeling phenomena caused by heterogeneous sources. We focus on circumstances in which original observations are not available, and instead the data comes in the form of a grouping of the original observations. We illustrate EM algorithm for fitting Weibull mixture models for grouped data and propose a bootstrap likelihood ratio test (LRT) for determining the number of subpopulations in a mixture model. The effectiveness of the LRT methods are investigated via simulation. We illustrate the utility of these methods by applying them to two grouped data applications.
Large scale arrays of four-state vortex domains in BiFeO3 thin film

Exotic domain states, like vortex, offer the promise of superior properties and the potential disclination strain is a key factor for their formation in ferroelectrics. Here we show that large scale arrays of four-state vortex domains can be obtained in rhombohedral BiFeO3 thin films grown on PrScO3 substrates by pulsed laser deposition. Cs-corrected scanning transmission electron microscopy demonstrates that each vortex domain is comprised of four ferroelectric variants with two 180° domain walls and two 109° domain walls. Atomic mappings of the lattice distortions unit cell by unit cell reveal that the cores of the vortex might be charged. The strains are mainly concentrated on domain walls. The formation mechanism of such large scale vortex-like states was discussed.
Text Classification using Bi-Gram Alphabet Document Vector Representation

Text classification TC is the process of assignment of text documents to appropriate categories based on their content. High dimensionality of feature space is a primary challenge in TC. The most common approach for TC is bag of words BOW which is limited due to the continuous increase in the number of features as the volume of vocabulary increases. Many investigators have addressed the issue of management of dimensionality by applying careful preprocessing techniques that include complex morphological phase, in particular for the high inflectional languages including Arabic. In the present study, term frequency of bi-gram alphabet is used to construct document vector. A main contribution of bi-gram alphabet approach is that feature terms are standard and separate from documents contents; this helps to reduce the high dimensionality associated with the increasing the volume of data. In addition, the classification process performs well on both Arabic and English collections without morphological preprocessing requirements. The proposed approach has proved high accuracy results and outperformed other Arabic TC systems.
Tools from Stochastic Analysis for Mathematical Finance: A Gentle Introduction

The idea of this document is to provide the reader with an intuitive, yet rigorous and comprehensive introduction to the main tools in stochastic analysis required in Finance to understand the modern modelling, pricing and hedging techniques. The most important models (Brownian motion, arithmetic and geometric Brownian motion, mean-reverting models, stochastic and jump processes) are considered and their properties illustrated with the help of Matlab codes and videos. We would like to emphasize that this document is very much work in progress and we would like to encourage readers to get in touch with us with feedback, comments, suggestions for additions and, of course, corrections of typos. All of these will be gratefully acknowledged in the future releases of this document.
Theory of Adaptation of Educators Teaching Technology-Based Courses

The need for resilience among educators has become a critical demand during the COVID-19 pandemic when in-person classes were restricted and were converted into distance learning and eventually shifted to blended learning as governments opened borders and health safety protocols eased down. Hence, this study focuses on understanding how educators of technology-based courses in public higher education across academic landscapes have navigated for continuous instructional delivery. This study utilizes the Straussian approach of Grounded Theory. This design uses a three-stage coding methodology: open, axial, and selective coding. The study generates the Theory of Educators Teaching Technology-Based Courses across academic landscapes, which postulates that educators in technology-based courses undergo phases of metamorphosis that include visioning, learning, rationalizing and doing, and modernizing, ultimately allowing them to become resilient and adaptive to the shifting landscapes of the academe caused by the COVID-19 pandemic.
Thresholding in high dimensional statistics: an application in testing and Cosmology

We review a family of model selection techniques called thresholding that assume the vector of parameters has few non-zero coefficients, and we show two applications of thresholding estimators. First, we derive a new class of statistical tests for generalized linear models. These tests can be employed whether the model includes more parameters than observations or not. We show through simulations that our tests have better control of the nominal level and higher power than existing tests. Second, we use a thresholding estimator to solve a cosmology problem that consists in recovering the 3D gas emissivity of a galaxy cluster from a 2D image taken by a telescope. We perform simulations in which we show how our methodology outperforms the current state-of-the-art approach in terms of mean squared errors, and how it has good coverage probability. We apply our methods to five different real telescope images and discuss the scientific findings.