Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Higuchi, Katz and Multiresolution Box-Counting Fractal Dimension Algorithms for EEG Waveform Signals Based on Event-Related Potentials

Obtaining information through the measurement of brain signals recorded during different processes or physiological conditions is important for developing computer interfaces that translate electrical brain signals to computer control commands. Electroencephalography (EEG) records the electrical activity of the brain in response to its receipt of different external stimuli (potential events). Analysis of these signals makes it possible to identify and distinguish specific states of physiological brain function. The Fractal Dimension has been used as a tool for biomedical waveform analysis, in particular to measure the complexity of time series generated by EEG. This paper aims to analyze a database (HeadIT) of biomedical time series obtained by EEG for which the fractal dimension will be obtained by the Higuchi, Katz and multiresolution box-counting methods, showing the relationship between the method for obtaining the fractal dimension and the physiological condition of the brain event-related potentials.
Specific Tuning Parameter for Directed Random Walk Algorithm Cancer Classification

Accuracy of cancerous gene classification is a central challenge in clinical cancer research. Microarray-based gene biomarkers have proved the performance and its ability over traditional clinical parameters. However, gene biomarkers of an individual are less robustness due to litter reproducibility between different cohorts of patients. Several methods incorporating pathway information such as directed random walk have been proposed to infer the pathway activity. This paper discusses the implementation of group specific tuning parameter in directed random walk algorithm. In this experiment, gene expression data and pathway data are used as input data. Throughout this experiment, more significant pathway activities can be identified which increases the accuracy of cancer classification. The lung cancer gene is used as the experimental dataset, with which, the sDRW is used in determining significant pathways. More risk-active pathways are identified throughout this experiment.
A stabilization technique for coupled convection‐diffusion‐reaction equations

Partial differential equations having diffusive, convective, and reactive terms appear in the modeling of a large variety of processes in several branches of science. Often, several species or components interact with each other, rendering strongly coupled systems of convection‐diffusion‐reaction equations. Exact solutions are available in extremely few cases lacking practical interest due to the simplifications made to render such equations amenable by analytical tools. Then, numerical approximation remains the best strategy for solving these problems. The properties of these systems of equations, particularly the lack of sufficient physical diffusion, cause most traditional numerical methods to fail, with the appearance of violent and nonphysical oscillations, even for the single equation case. For systems of equations, the situation is even harder due to the lack of fundamental principles guiding numerical discretization. Therefore, strategies must be developed in order to obtain physically meaningful and numerically stable approximations. Such stabilization techniques have been extensively developed for the single equation case in contrast to the multiple equations case. This paper presents a perturbation‐based stabilization technique for coupled systems of one‐dimensional convection‐diffusion‐reaction equations. Its characteristics are discussed, providing evidence of its versatility and effectiveness through a thorough assessment.
Cepstral Analysis of Random Variables: Muculants

An alternative parametric description for discrete random variables, called muculants, is proposed. In contrast to cumulants, muculants are based on the Fourier series expansion, rather than on the Taylor series expansion, of the logarithm of the characteristic function. We utilize results from cepstral theory to derive elementary properties of muculants, some of which demonstrate behavior superior to those of cumulants. For example, muculants and cumulants are both additive. While the existence of cumulants is linked to how often the characteristic function is differentiable, all muculants exist if the characteristic function satisfies a Paley-Wiener condition. Moreover, the muculant sequence and, if the random variable has finite expectation, the reconstruction of the characteristic function from its muculants converge. We furthermore develop a connection between muculants and cumulants and present the muculants of selected discrete random variables. Specifically, it is shown that the Poisson distribution is the only distribution where only the first two muculants are nonzero.
Direct bandgap cross-over point of Ge1-ySny grown on Si estimated through temperature-dependent photoluminescence studies

Epitaxial Ge1-ySny (y = 0%–7.5%) alloys grown on either Si or Ge-buffered Si substrates by chemical vapor deposition were studied as a function of Sn content using temperature-dependent photoluminescence (PL). PL emission peaks from both the direct bandgap (Γ-valley) and the indirect bandgap (L-valley) to the valence band (denoted by ED and EID, respectively) were clearly observed at 125 and 175 K for most Ge1-ySny samples studied. At 300 K, however, all of the samples exhibited dominant ED emission with either very weak or no measureable EID emission. At 10 K, ED is dominant only for Ge1-ySny with y > 0.052. From the PL spectra taken at 125 and 175 K, the unstrained indirect and direct bandgap energies were calculated and are plotted as a function of Sn concentration, the results of which show that the indirect-to-direct bandgap transition occurs at ∼6.7% Sn. It is believed that the true indirect-to-direct bandgap cross-over of unstrained Ge1-ySny might also take place at about the same Sn content at roo.
Living Alone, Environmental Hazards, and Falls Among U.S. Older Adults

Abstract Background and Objectives Physical conditions of living environments can affect the incidence of falls; however, prior work has focused typically on 1 domain at a time—either neighborhood or home, capturing limited environmental boundaries of older adults. We examined how neighborhood together with the home environment affect the incidence of falls over time and whether living arrangement modifies the influence of the environmental risks on falls. Research Design and Methods Using the 2012–2020 waves of the Health and Retirement Study (HRS; N = 1,893), we fitted logistic regression to estimate the incidence of falls over an 8-year study period. We used the neighborhood and housing data that are collected systematically by trained observers in the HRS to assess environmental hazards. Sidewalk quality, neighborhood disorder, and the presence of green space were measured to capture outdoor environmental hazards. Indoor environmental hazards included the presence of housing decay and poorly maintained stairways. All models were stratified by living arrangement. Results Neighborhood and housing environment were independently associated with the odds of falls net of demographic characteristics and preexisting health conditions, and effects were significant for people living alone only. The presence of green space and poorly maintained stairways were associated with greater odds of falling, net of covariates during 8 years of follow-up (odds ratios = 2.10 and 2.65, p < .05, respectively). None of the environmental risk factors were significant for those living with others. Discussion and Implications Falls in old age may be determined in part by a combination of outdoor and indoor risk factors. More research is needed to understand pathways that lead to greater vulnerability among older adults living alone to environmental hazards.
Antenna-coupled graphene Josephson-junction THz/mm-wave detector

Highly-sensitive broadly-tunable detectors are needed for future multi-domain sensing and quantum-information systems. Layered graphene with “magic” twist-angle between 2 - 4 sheets is superconducting below 2 K. Demonstrated Josephson junctions in this material feature very high dynamic resistance at the maximum zero-voltage current. Biased at this current, a small microwave voltage across the junction shifts the voltage-current step, which results in a large DC output voltage. A suitable antenna driven by external radiation can source the desired AC voltage across the junction. As a non-thermal mechanism, such detectors may in principle be fast, as well as sensitive. Additionally, there is a bolometric response, whose temperature coefficient of resistance we estimate to be 300%/K. Design, fabrication, response, and twist-angle tolerance for antenna-coupled, superconducting-graphene, Josephson-junction detectors of mm-wave and THz radiation are discussed.
Performance Influencing Factors of Convolutional Neural Network Models for Classifying Certain Softwood Species

This study aims to verify the wood classification performance of convolutional neural networks (CNNs), such as VGG16, ResNet50, GoogLeNet, and basic CNN architectures, and to investigate the factors affecting classification performance. A dataset from 10 softwood species consisted of 200 cross-sectional micrographs each from the total part, earlywood, and latewood of each species. We used 80% and 20% of each dataset for training and testing, respectively. To improve the performance of the architectures, the dataset was augmented, and the differences in classification performance before and after augmentation were compared. The four architectures showed a high classification accuracy of over 90% between species, and the accuracy increased with increasing epochs. However, the starting points of the accuracy, loss, and training speed increments differed according to the architecture. The latewood dataset showed the highest accuracy. The epochs and augmented datasets also positively affected accuracy, whereas the total part and non-augmented datasets had a negative effect on accuracy. Additionally, the augmented dataset tended to derive stable results and reached a convergence point earlier. In the present study, an augmented latewood dataset was the most important factor affecting classification performance and should be used for training CNNs.
IoT-based framework for agile supply chain in FMCG indus-tries – a solution for (post-)pandemic times

In recent decades, with the growth of sustainable development, supply chain agility has become very important as a strategy for competitiveness in the business environment, and supply chain stakeholders expect the role of digital developments and efficient tools in these developments in the supply chain to be considered. One of the most important transformational solutions in today's world is the Internet of Things (IoT). It can accelerate activity in the supply chain and create value in the organization. Due to environmental issues and the increasing speed of changes in customer needs in various industries, such as critical industries where agility has a high impact on people's health, these industries have undergone many changes with the emergence of innovation. Therefore, the whole supply chain path requires im-plementing strategies such as agile and green supply chain and achieving smartness. Thus, emerging technologies such as the Internet of Things play a significant role in the agility and greenness of the en-tire path of the supply chain. Given the importance of the FMCG industry and its impact on people's dai-ly lives, this qualitative study aims to provide a framework for agile supply chain sustainability in the FMCG industry and draw possible implications for a post-pandemic period. This framework embedding the IoT into agility in supply chains can effectively guide FMCG companies in using the Internet of Things to streamline the supply chain.
Religious Values in the Rowa Traditional Ceremony in Manggarai Communities in Flores

: This study aims to investigate religious values in the traditional Rowa ceremony or funeral ceremony for the Manggarai community in Flores. The Rowa traditional ceremony is a series of ceremonies for the death of a person starting from the ceremony of bathing the body, fixing the coffin, releasing and burial of the body. The utterances at the Rowa traditional ceremony are a means of presenting themselves to the Manggarai people before each other, their ancestors and God. The traditional speech in the Rowa traditional ceremony is in the form of a poem called torok tae. As a poem, torok tae has a variety of traditional languages, connotative word choices and has a special semantic meaning. This study used qualitative research methods. Data was collected using the listening and speaking method and perfected by the observing and speaking technique involving speaking, taking notes and recording the entire series of Rowa traditional ceremonies. The results of the study prove that the utterances in the Rowa traditional ceremony have religious values which include the values of trust, reconciliation and safety. The value of belief states belief in the Highest Being (God) in cultural terms addressed Mori, Mori Dewa, Dewa Mori Ngaran Jari, Jari Dewa Mori Ngaran, Mori Ngaran and anthropomorphic greeting Ende Wa. Belief in the existence of wakar souls, ase kae which revive humans and the existence of life after death. The value of reconciliation states the restoration of the vertical relationship between God the Creator and humans as His creations. The value of salvation is a form of recognition by the Manggarai people for God's holiness, God's protection and new life after death.
Design of a 1 mw, 280 Ghz gyrotron oscillator

The design of a 1 MW, 280 GHz gyrotron suitable for ECR heating is complete and under construction at MIT. A highly overmoded cylindrical cavity with linear tapers at each end will operate in the whispering gallery mode; TE42,7,1. The magnetron injection gun (MIG) was optimized to produce a 90 kV, 50 A annular electron beam with an α = υ/υ|| =1.6 and a perpendicular velocity spread of approximately 5 %. The MIG and a 12 Tesla superconducting magnet with a 5 inch warm bore are presently under construction. Initial operation is planned for early next year.
Bandwidth efficient channel estimation method for airborne hyperspectral data transmission in sparse doubly selective communication channels

Abstract. A channel estimation (CE) method based on compressed sensing (CS) is proposed to estimate the sparse and doubly selective (DS) channel for hyperspectral image transmission from unmanned aircraft vehicles to ground stations. The proposed method contains three steps: (1) the priori estimate of the channel by orthogonal matching pursuit (OMP), (2) calculation of the linear minimum mean square error (LMMSE) estimate of the received pilots given the estimated channel, and (3) estimate of the complex amplitudes and Doppler shifts of the channel using the enhanced received pilot data applying a second round of a CS algorithm. The proposed method is named DS-LMMSE-OMP, and its performance is evaluated by simulating transmission of AVIRIS hyperspectral data via the communication channel and assessing their fidelity for the automated analysis after demodulation. The performance of the DS-LMMSE-OMP approach is compared with that of two other state-of-the-art CE methods. The simulation results exhibit up to 8-dB figure of merit in the bit error rate and 50% improvement in the hyperspectral image classification accuracy.
An adaptive quadrature-based factorization method for inverse acoustic scattering problems

ABSTRACT We propose a novel adaptive algorithm, which generates nonuniform sampling points that automatically concentrate near the boundary of an unknown scatterer, to dramatically speed up Kirsch’s factorization method for inverse acoustic scattering problems. Built upon the widely used adaptive Simpson quadrature method, our proposed adaptive algorithm approximates the integral of an indicator function over the search domain and yields reliable and accurate reconstructions significantly faster than the standard factorization method. Numerical experiments are performed to validate the effectiveness of our proposed algorithm and make comparisons with the established multilevel linear sampling method.
Theory of regularly and rapidly varying functions on time scales and its application to dynamic equations

V Kapitole 2 připomeneme teorii regularni a rychle variace pro spojitý a diskretni připad, teorii na casových skalach, teorii dynamických rovnic a zakladni teorii $q$-kalkulu a $q$-diferencnich rovnic; tyto temata uzce souviseji s obsahem prace. Dale vybudujeme teorii regularni a rychle variace na casových skalach. Rozlisujeme nasledujici dva připady. V Kapitole 3 studujeme tuto teorii pro obecnou casovou skalu se zrnitosti $\mu(t)=o(t)$ (vyjimecně, v některých specialnich připadech je „povolena“ zrnitost $\mu(t)=O(t)$). V Kapitole 4 je vybudovana odpovidajici teorie, t.j. teorie $q$-regularni a $q$-rychle variace pro důležitou casovou skalu $\mathbb{T}=q^{\mathbb{N}_0}$, $q>1$, ktera ma zrnitost $\mu(t)=(q-1)t$, a (jak ukažeme) memůže být studovana s předchozim (obecným) připadem soucasně. Ve druhe casti Kapitoly 3, resp. Kapitoly 4, aplikujeme obdrženou teoroii regularni a rychle, resp. $q$-regularni a $q$-rychle variace na výzkum asymptotickeho chovani řeseni pololinearni dynamicke rovnice $$[\Phi(y^{\Delta })]^\Delta - p(t)\Phi(y^{\sigma})=0,$$ resp. $q$-diferencni rovnice $$D_q[\Phi(D_qy(t))] - p(t)\Phi(y(qt))=0. $$ Tež se uvažuji a studuji jejich specialni linearni tvary. Ve vsech připadech předpokladame, že koeficient $p$ je kladný. Konecně, Kapitola 5 je věnovana tak-zvanemu „teleskopickemu principu“ sloužicimu k zjisťovani oscilacnich vlastnosti pololinearni dynamicke rovnice $$[r(t)\Phi(y^{\Delta })]^\Delta + p(t)\Phi(y^{\sigma})=0. $$ Tento princip nam umožni zkonstruovat mnoho nových oscilatorických rovnic. Narozdil od předchozich praci zabývajicich se teleskopickým principem, formulujeme jiste oscilacni výsledky za slabsiho předpokladu $r(t)\not=0$ (misto $r(t)>0$).
Key Exchange Over Particular Algebraic Closure Ring

Abstract In this paper, we propose a new method of Diffie-Hellman key exchange based on a non-commutative integral closure ring. The key idea of our proposal is that for a given non-commutative ring, we can define the secret key and take it as a common key to encrypt and decrypt the transmitted messages. By doing, we define a new non-commutative structure over the integral closure OL of sextic extension L, namely L is an extension of ℚ of degree 6 in the form ℚ(α, β), which is a rational quadratic and monogenic extension over a non-pure and monogenic cubic subfield K = ℚ(β).
Comparative analysis of SH2 domain structures

Src Homology 2 (SH2) is the compact globular domains, which is involved in intra-cellular signaling pathways and play an important role in mediating specific protein-protein interactions. It consists of about 100 amino acids and include sevens β -sheets and two α -helices. The SH2 domains comprise two highly conservative parts of binding pocket – pTyr and pTyr +3. The knowledge of the protein complexes structure is an important step forward to understanding of the mechanisms of their functioning. The binding site of SH2 domains and surrounding to binding site sequences were analyzed by using in silico methods. All SH2 domains were divided into the groups by sequence similarity. The parts of sequences which are common to all domains and the unique parts of certain domains were found within the framework of conservation and similarity analysis of SH2 domains. Furthermore, the surface area analysis displays that the highly conservative structures occupy the smallest area. These results indicate the ability of the SH2 domains to recognize not only linear phosphopeptide sequences. It opens new insights on the interpretation of possible mechanisms of interaction between SH2 domains and ligands/protreins (e. g. possibility of binding between protein or ligand with SH2 domain not only within binding site area).
Opportunities and Areas for Improvement in Public Library Makerspaces for Adults with Disabilities

Makerspaces are now a common feature in many public libraries in the United States. However, there has been little research into how these spaces function for adults with disabilities. In this study, qualitative data were collected from patrons with disabilities and public librarians through online focus groups, interviews, and an online survey to address this gap in knowledge. Findings speak to the needs of a significant subset of public library patrons, describe current practices in public library makerspaces, and suggest areas for implementing more inclusive practices.
Improving Sri Lankan Buildings' Energy Efficiency Through Bioclimatic Classification and Potential Assessment

As a result of lifestyle changes, the energy requirement for thermal comfort has increased. To increase energy efficiency and reduce global warming, building design should consider the climate. An energy-efficient building code has been developed with the goal of reducing energy demand by 25%–40%. However, the code cannot be used because different stakeholders have different perspectives. Climate zones, which are required for building structures that are both energy-efficient and climate-responsive, do not exist in the country. From 1989 to 2019, hourly weather data has been collected for district headquarters. This research focuses on the bioclimatic classification of Sri Lankan buildings and passive design methods. Degree days have been calculated for various base temperatures using Hitchin's, Erb's, Schoenau and Kehring's, ASHRAE, UKMO, and Hourly methods. The degree-day maps for Sri Lanka were created using ArcGIS. The bioclimatic classification for Sri Lanka was developed by combining climate and degree-day data. Sri Lanka is divided into three bioclimatic zones: cold, hot, and intermediate. The design potential of each bioclimatic zone was calculated using BcChart V2.0. Natural ventilation is an effective passive design technique for increasing indoor comfort. In the cold, hot, and intermediate zones, its potential is 72%, 62%, and 80%, respectively.
Emergent Hypotrochoidal and Epitrochoidal Formations in a Swarm of Agents

This article proposes a decentralized controller for a swarm of agents that generates hypotrochoidal and epitrochoidal curves in a 3-D space. The dynamics of the agents is modeled as a double integrator where the control input, i.e., the acceleration profile, contains two terms that account for the interactions between the agents in terms of position and velocity, respectively. The term related to the interaction between velocities is weighted by a skew-symmetric matrix responsible for coupling the velocities displacements. Such a matrix defines an axis of rotation centered on the centroid of the swarm, around which the swarm organizes itself to generate the desired trajectories, which can be selected by properly setting two free parameters of the model. In particular, the motion of each agent is analyzed by separating its dynamics along the rotation axis from that in the perpendicular plane. It is shown that the agents achieve consensus or periodic motion along the axis of rotation while performing the desired evolutions in the perpendicular plane. Numerical simulations are presented to illustrate the proposed framework.