Miracle-dz/UniFAR-FTUs huggingface dataset:
MEMS-Based Flexible Wearable Tri-Polar Concentric Ring Electrode Array With Self-Adhesive Graphene Gel for EEG Monitoring

Electroencephalography (EEG) is widely used to study brain activity and diagnose brain diseases due to its low cost and non-invasiveness. EEG has an excellent temporal resolution, but it does not provide good spatial resolution. The blurring effects of the head volume conductor are considered to be the main reason for the low spatial resolution. Concentric ring electrodes have been shown to provide significantly better spatial resolution than conventional electrodes which usually used silver or gold as contact conductors with the scalp. However, the metallic interfaces have high impedance. Herein, we designed a tri-polar concentric ring electrode (TCRE) array to precisely analyze the EEG signal and report a flexible self-adhesive graphene gel to reduce contact impedance. The electrodes are made of flexible material and are comfortable to wear. The electrode-scalp contact impedance was reduced to below 10 $\text{k}\Omega $ at 10 Hz and the EEG signal of alpha oscillations was successfully recorded. The average coherence between the original signals recorded by TCRE and the commercial Ag/AgCl gel electrode reached 0.913. The TCRE also shows significantly less mutual information between positions than the disk electrodes, showing high spatial resolution.
Characterization and classification of soils of the Rivers State University Teaching and Research Farm, Port Harcourt, Southern Nigeria

This study was conducted to characterize and classify the soils of the Teaching and Research Farm, Rivers State University, Port Harcourt, covering 30 hectares of land area. A rigid grid soil survey method at a very detailed level (100 × 100) m² (1 ha) with two mapping units identified and delineated. Each of the mapping unit was represented by a soil profile described from the lowest end to the upper part of the profiles to avoid contamination. Soil samples were collected for laboratory analysis from the various horizons identified. The results obtained, indicated that the soils were of Inceptisols/ Cambisol order, Udepts at the suborder level, Eutrudepts Great group level and Typic Eutrudepts (subgroup level). Thus, the drainage, parent materials, climate (rainfall), and vegetation of the area along with the geologic material, formed from the sedimentary rocks that were weathered into coastal plain sands and buried under alluvium at various degrees at different locations in the study area, greatly affected the soils of Teaching and Research Farm, Rivers State University, Port Harcourt, which are primarily Inceptisols/ Cambisols.
An adjoint‐based design methodology for CFD problems

A complete CFD design methodology is presented. The main components of this methodology are a general edge‐based compressible/incompressible flow solver; a continuous adjoint formulation for the gradient computations; a steepest descent technique for the change of design variables; evaluation of the gradient of the discretized flow equations with respect to mesh by finite differences; a CAD‐free pseudo‐shell surface parametrization, allowing every point on the surface to be optimized to be used as a design parameter; and a level type scheme for the movement of the interior points. Several examples are included to demonstrate the methodology developed.
Assessment of Selected Structural Properties of High-Speed Friction Welded Joints Made of Unalloyed Structural Steel

Commonly used S235JR structural steel, generally associated with good weldability, was joined by high-speed friction welding (HSFW). The friction welding tests were performed with a rotational speed of n = 8000 rpm and four different values of the unit pressure in the friction phase (pf) in the range of 64–255 MPa. The obtained joints were subjected to metallographic observations using an optical microscope; in selected zones of friction joints the average grain size was specified in accordance with the EN ISO 643:2012 standard; the hardness of friction joints was measured using the Vickers method. The friction-welded joint with the highest pf was EBSD-investigated. The obtained friction-welded joints resembled an hourglass, and the microstructure of individual zones of the joints differed depending on the height (axis, radius) of the observations. The generated joining conditions resulted in a significant refinement of the microstructure in the friction weld—the average grain size is about 1 µm2 (for base material it was 21 µm2). The highest increase in hardness above 340 HV0.1 was recorded in the friction weld of the welded joint with the lowest used value pressure in the friction phase. Such a sharp increase in hardness can make the resulting friction-welded joint become sensitive to dynamic or fatigue loads. The electron backscatter diffraction (EBSD) investigation confirmed the strong refinement of the microstructure in the friction-welded joint and the occurrence of the phenomenon of dynamic recrystallization (DRX). The friction weld was also characterized by a large share of high-angle boundaries (HAGBs) >80%. These results may indicate that during high-speed friction welding it is possible to create conditions like those obtained during the High-Pressure Torsion (the method used to produce UFG materials) process.
Multiresolution image fusion scheme based on fuzzy region feature

This paper proposes a novel region based image fusion scheme based on multiresolution analysis. The low frequency band of the image multiresolution representation is segmented into important regions, sub-important regions and background regions. Each feature of the regions is used to determine the region’s degree of membership in the multiresolution representation, and then to achieve multiresolution representation of the fusion result. The final image fusion result can be obtained by using the inverse multiresolution transform. Experiments showed that the proposed image fusion method can have better performance than existing image fusion methods.
Automatic segmentation improvement based on parameter-free spectral matting

In this study, we propose a parameter-free spectral matting technique to automatically achieve essential matting components from the smallest eigenvectors of a Laplacian matrix that accomplish good segmentation results in photography. The proposed scheme is based on discarding alpha components before grouping alpha mattes for high accuracy and better performance in segmentation and compositing. The scheme’s emphasis is on finding the best alpha components of the foreground through opacity estimation in natural photographs without any required user input. The said parameter-free spectral matting technique gives us better performance in terms of seamless boundaries than the existing segmentation techniques. We have compared our scheme with the state-of-the-art interactive segmentation and matting techniques, that is, GrabCut, Graph Cut, and Bayesian Matting, etc. The results of the proposed parameter-free spectral matting scheme are promising and affirm the effectiveness of our method.
Separability measures for error estimation of two normally distributed classes

In pattern classification and remote sensing, the Gaussian ML classifier is most widely used because of its speed and robustness. In this paper, we propose to use two separability measures, Bhattacharyya distance and divergence to estimate the classification error of the Gaussian ML classifier. In the proposed method, we try to find empirical relationship between the separability measures and the classification error. In order to find such relationship, we generate two classes with normal distribution and compute the separability measures and classification error between the classes. Although there are infinite number of possibilities that two classes can have, we systematically search the whole mean-covariance space. From this exhaustive search, we are able to estimate the classification error accurately using the Bhattacharyya distance and divergence. It is observed that the error estimation using both the Bhattacharyya distance and divergence does not give a significant improvement over the error estimation using the Bhattacharyya distance only.
Can cochlear mechanics contribute to amplitude modulation perception

Amplitude modulation (AM) detection has been successfully used as a psychophysical measure of auditory temporal processing. Our understanding of the role of the auditory periphery in processing AM signals is emerging through physiological and psychophysical studies. Unfortunately, direct physiological estimates of the cochlea’s mechanical response to AM signals are not obtainable in humans. This study tries to fill this critical gap in knowledge by exploring the relationship between perception (through psychophysical AM detection) and mechanics (through otoacoustic emissions). Psychometric function for AM perception was measured for a 2-kHz carrier frequency and 10-Hz modulation frequency (fm). Distortion product otoacoustic emissions (DPOAEs) were recorded with amplitude-modulated f1 with fm = 10 Hz and steady-state f2. The frequencies of f1 and f2 were chosen to yield a 2f1 − f2 DPOAE around 2 kHz near a peak in the fine structure. The ratio between the DPOAE pressure at 2f1 − f2 and that of the sidebands separated by fm (AMOAE depth) was calculated as a function of different modulation depths. Results indicate that there might be a correlation between AM perception performance and AMOAE magnitude, suggesting that cochlear mechanics might play a role for AM perception. [Work supported by the Knowles Hearing Center and Northwestern University. ]
Nutritional Composition of Castor Genotypes and its Influence On Growth Attributes of Eri Silkworm (Philosamia ricini)

Eri silkworm (Philosamia ricini) is one of the most exploited, domesticated, and commercialized Vanya silkworms. Eri silk yield and productivity depend heavily on the feeds ingested by Eri silkworms, which will vary depending on the feed sources. A study was undertaken to evaluate different castor genotypes viz., GCH 4, GCH 7, DCH 519, TMV 5, along with local variety for the nutritional composition and its influence on the growth and economic attributes of Eri silkworm. The treatments were laid out in a Completely Randomized Design (CRD) with three replications. The performance of eri silkworm viz., growth attributes, and economic parameters were studied by feeding them with the leaves of five castor genotypes separately in the tray rearing method. The genotypes showed significant differences in growth and economic parameters of eri silkworm. Among the various genotypes, GCH 4 genotypes showed superior among all the other genotypes on nutritional composition, growth attributes, and economic parameters, followed by genotype DCH 519.
Review of WEC-Sim development and applications

WEC-Sim (Wave Energy Converter Simulator) is an open-source code for simulating wave energy converters, which has been actively developed and applied to simulate a wide variety of device archetypes, and has become a popular tool since its release. This paper reviewed the development efforts and the usage of WEC-Sim. The publications considered in this study have been broken down into six topic areas, namely feature development, experimental validation, device modeling, control modeling, PTO and grid modeling, and novel applications, which even includes some non-wave energy applications. This review paper has also attempted to recognize the contributions of the broader WEC-Sim development effort, meaning not only the internal WEC-Sim development team but also the external efforts from the academia researchers and technology developers around the world. The growing trend of external applications of WEC-Sim has demonstrated the broader acceptance of the open-source code, and how WEC-Sim has been used in a certain topic area also highlights the potential future development needs.
Clade 2.3.4.4b H5N8 Subtype Avian Influenza Viruses Were Identified from the Common Crane Wintering in Yunnan Province, China

The seasonal migration of wild aquatic birds plays a critical role in the maintenance, transmission, and incursion of the avian influenza virus (AIV). AIV surveillance was performed during 2020–2021 in two national nature reserves with abundant wild bird resources in Yunnan, China. Four H5N8 AIVs isolates from the common crane were identified by next-generation sequencing. Phylogenetic analysis demonstrated that all eight gene segments of these H5N8 AIVs belonged to clade 2.3. 4.4b high-pathogenic AIV (HPAIV) and shared high nucleotide sequence similarity with the strains isolated in Hubei, China, and Siberia, Russia, in 2020–2021. The H5N8 HPAIVs from common cranes were characterized by both human and avian dual-receptor specificity in the hemagglutinin (HA) protein. Moreover, possessing the substitutions contributes to overcoming transmission barriers of mammalian hosts in polymerase basic 2 (PB2), polymerase basic protein 1 (PB1), and polymerase acid (PA), and exhibiting the long stalk in the neck region of the neuraminidase (NA) protein contributes to adaptation in wild birds. Monitoring AIVs in migratory birds, at stopover sites and in their primary habitats, i.e., breeding or wintering grounds, could provide insight into potential zoonosis caused by AIVs.
Congruent evaporation temperature of molecular beam epitaxy grown GaAs (001) determined by local droplet etching

The congruent evaporation temperature Tc of GaAs (001) is critical for many technological processes and is fundamental to the control and stability of Ga droplets for quantum structure fabrication. We apply the technique of local droplet etching (LDE) to measure Tc for technologically important molecular beam epitaxy (MBE) grown GaAs (001). Below Tc, Ga droplets deposited on the surface shrink and form nanoholes via LDE and thermal widening. Above Tc, droplets grow by capturing excess Ga. From the transition between both regimes, we determine Tc = 680 ± 10 °C. Additionally, we find that the nanohole/droplet densities follow an Arrhenius-type temperature dependence with an activation energy of 1.31 eV. The method probes the stability of pre-existing droplets formed by deposition and so avoids the complication of nucleation barriers and readily allows the measurement of Tc for technologically important planar GaAs surfaces in any standard MBE system.
Lytic polysaccharide monooxygenase increases cellobiohydrolases activity by promoting decrystallization of cellulose surface

Efficient depolymerization of crystalline cellulose requires cooperation between multiple cellulolytic enzymes. Through biochemical approaches, molecular dynamics (MD) simulation, and single-molecule observations using high-speed atomic force microscopy (HS-AFM), we quantify and track synergistic activity for cellobiohydrolases (CBHs) with a lytic polysaccharide monooxygenase (LPMO) from Phanerochaete chrysosporium. Increasing concentrations of LPMO (AA9D) increased the activity of a glycoside hydrolase family 6 CBH, Cel6A, whereas the activity of a family 7 CBH (Cel7D) was enhanced only at lower concentrations of AA9D. MD simulation suggests that the result of AA9D action to produce chain breaks in crystalline cellulose can oxidatively disturb the crystalline surface by disrupting hydrogen bonds. HS-AFM observations showed that AA9D increased the number of Cel7D molecules moving on the substrate surface and increased the processivity of Cel7D, thereby increasing the depolymerization performance, suggesting that AA9D not only generates chain ends but also amorphizes the crystalline surface, thereby increasing the activity of CBHs.
Combined Time and Frequency-Domain Modelling of Electromagnetic Radiation From Apertures On Resonant Cavities By Fdtd-Mom Method

A combined method is presented for wideband analysis of electromagnetic radiation through apertures on a resonant cavity. The aperture has size comparable with the wavelength. An interior and an exterior problem are solved by FDTD and MoM, respectively. The aperture field is expanded on an entire domain basis whose time-dependent coefficients are processed by extrapolation techniques and a one-dimensional discrete Fourier transform. As a consequence of the segmentation, a partial reuse of computed electromagnetic data is possible. The method enables a compression of data to be stored and a reduction of computation time.
Fukaya categories and the minimal model program: Creation

We prove that small blow-ups or reverse flips (in the sense of the minimal model program) of rational symplectic manifolds with trivial centers create Floer-non-trivial Lagrangian tori. We give examples of explicit mmp runnings and descriptions of Floer non-trivial tori in the case of toric manifolds, polygon spaces, and moduli spaces of flat bundles on punctured two-spheres (moduli of parabolic bundles). These results are part of a conjectural description of generators for the Fukaya category of a compact symplectic manifold with an orbifold running of the minimal model program.
Foundations for Envelope Models and Methods

Envelopes were recently proposed by Cook, Li and Chiaromonte as a method for reducing estimative and predictive variations in multivariate linear regression. We extend their formulation, proposing a general definition of an envelope and a general framework for adapting envelope methods to any estimation procedure. We apply the new envelope methods to weighted least squares, generalized linear models and Cox regression. Simulations and illustrative data analysis show the potential for envelope methods to significantly improve standard methods in linear discriminant analysis, logistic regression and Poisson regression. Supplementary materials for this article are available online.
Parent-Metabolite Pharmacokinetic Modeling of Formononetin and Its Active Metabolites in Rats after Oral Administration of Formononetin Formulations

Formononetin is a major isoflavone contained in propolis and is reported to exhibit various pharmacological effects. However, the use of formononetin in pharmaceutical industry is limited due to its low bioavailability and solubility. There had been several efforts on formononetin formulation development, but further study is required to acquire optimal formulation. The aim of this study is to conduct pharmacokinetic (PK) evaluations after the oral administration of three formononetin formulations (20 mg/kg) in male Sprague Dawley rats. Then, a parent-metabolite PK model for formononetin was developed and evaluated for the first time. To do this, a simultaneous analysis method for formononetin and its active metabolites, daidzein, dihydrodaidzein and equol in rat plasma was developed using ultra-performance liquid chromatography tandem mass spectrometry. The separation was performed using a gradient elution of water and acetonitrile and a Kinetex C18 column (2.1 mm × 100 mm, 1.7 µm particle size) at a temperature of 30 ± 5 °C. The simultaneous analytical method developed in this study was validated according to international guidance and was successfully applied for the pharmacokinetic study. The time-plasma concentrations of formononetin and daidzein were well described by a two-compartment model combined with a metabolite compartment. Additionally, plasma protein binding assay was conducted in male rat plasma. The findings from the study could be used as a fundamental for the future development of formononetin as a pharmaceutical product.
Diagnosis of Depression Based on Four-Stream Model of Bi-LSTM and CNN From Audio and Text Information

Recent development trends in artificial intelligence applications have seen increasing interest in the design of automated systems for depression detection and diagnosis among the affective computing community. Particularly, active research has been conducted in depression diagnosis, based on multi-modal approaches in deep learning technology, which enable utilization of various information through fusion of varied data types. This study proposes a four-stream-based depression diagnosis model consisting of Bidirectional Long Short-Term Memory (Bi-LSTM) and convolutional neural networks (CNN), using speech and text data. One-dimensional features of audio signals are extracted using Mel Frequency Cepstral Coefficients and Gammatone Cepstral Coefficients, and two-dimensional features are extracted from Bark, equivalent rectangular bandwidth, and Log-Mel spectrograms, based on time-frequency transform. The extracted features are applied to Bi-LSTM and CNN-based transfer learning models. Word encoding was used for mapping of text to sequences with numeric indices, and word embedding used for representation of all words in numeric dense vectors. These were applied to Bi-LSTM and n-gram-based CNN models. Finally, an ensemble of the softmax values output from the four deep learning models was used to perform depression diagnosis, based on the proposed four-stream model. Using the proposed model, experiments were performed with the Extended Distress Analysis Interview Corpus Wizard of Oz depression database and other datasets. Experimental results showed improved performance by 10.7% to 11.9% over two-stream-based state-of-the-art methods. This demonstrates that the proposed model is effective for depression diagnosis.
Extra-Basal Ganglia Brain Structures Are Related to Motor Reserve in Parkinson’s Disease

Background: The “motor reserve” is an emerging concept based on the discrepancy between the severity of parkinsonism and dopaminergic degeneration; however, the related brain structures have not yet been elucidated. Objective: We investigated brain structures relevant to the motor reserve in Parkinson’s disease (PD) in this study. Methods: Patients with drug-naïve, early PD were enrolled, who then underwent dopamine transporter (DAT) scan and diffusion tensor imaging (DTI). The severity of motor symptoms was evaluated with the Unified Parkinson’s Disease Rating Scale score of bradykinesia and rigidity on the more affected side and dopaminergic degeneration of DAT uptake of the more affected putamen. Individual motor reserve estimate (MRE) was evaluated based on the discrepancy between the severity of motor symptoms and dopaminergic degeneration. Using DTI and the Brainnetome atlas, brain structures correlated with MRE were identified. Results: We enrolled 193 patients with drug-naïve PD (mean disease duration of 15.6±13.2 months), and the MRE successfully predicted the increase of levodopa equivalent dose after two years. In the DTI analysis, fractional anisotropy values of medial, inferior frontal, and temporal lobes, limbic structures, nucleus accumbens, and thalamus were positively correlated with the MRE, while no brain structures were correlated with mean diffusivity. Additionally, degree centrality derived from the structural connectivity of the frontal and temporal lobes and limbic structures was positively correlated with the MRE. Conclusion: Our results show empirical evidence for MR in PD and brain structures relevant to MR, particularly, the extra-basal ganglia system including the limbic and frontal structures.