Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Sparsifying Transforms for Image Reconstruction in Electrical Impedance Tomography

Electrical Impedance Tomography (EIT) is a fast and non-invasive imaging technology that reconstructs the internal electrical properties of a subject. However, its functionality is limited by low spatial resolution arising from an ill-posed and ill-conditioned inverse problem. Several sparsity-promoting regularization methods have been applied to improve the quality of EIT image reconstruction, including various ℓ0 and ℓ1-based analytical models (TV, TwIST, etc.), and a patch-based sparse representation via a learned dictionary (using the K-SVD algorithm), dubbed CS-EIT. To further exploit the potential of compressed sensing in Electrical Impedance Tomography, this paper incorporates the recent novel method of transform learning for EIT image reconstruction. We propose a blind compressed sensing algorithm, dubbed TL-EIT, which simultaneously optimizes the sparsifying transform and updates the reconstructed image. We demonstrate using both synthetic and in vivo data that the proposed TL-EIT is more effective than other sparsity-based algorithms for reconstructing high-quality EIT images. In addition, TL-EIT also accelerates the reconstruction process in comparison to other learning-based algorithms like CS-EIT.
Rate-Distortion Optimized Motion Estimation for on-the-Sphere Compression of 360 Videos

On-the-sphere compression of omnidirectional videos is a very promising approach. First, it saves computational complexity as it avoids to project the sphere onto a 2D map, as classically done. Second, and more importantly, it allows to achieve a better rate-distortion tradeoff, since neither the visual data nor its domain of definition are distorted. In this paper, the on-the-sphere compression [1] for omnidirectional still images is extended to videos. We first propose a complete review of existing spherical motion models. Then we pro-pose a new one called tangent-linear+t. We finally propose a rate-distortion optimized algorithm to locally choose the best motion model for efficient motion estimation/compensation. For that purpose, we additionally propose a finer search pattern, called spherical-uniform, for the motion parameters, which leads to a more accurate block prediction. The novel algorithm leads to rate-distortion gains compared to methods based on a unique motion model.
Maximum a Posteriori Estimator for Convolutive Sound Source Separation with Sub-Source Based NTF Model and the Localization Probabilistic Prior on the Mixing Matrix

In this paper we present a method for the separation of sound source signals recorded using multiple microphones in a reverberant room. In particular, we propose a maximum a posteriori (MAP) estimator based on the multichannel nonnegative tensor factorization (NTF) model with the localization prior distribution on the mixing matrix, in which the latent data consists of the so-called sub-sources for an improved performance in a reverberant environment. For the proposed MAP estimator, we derive the sub-source based expectation maximization (EM) algorithm with the multiplicative update rules (MU) and the localization prior distribution (LP) on the mixing matrix (SSEM-MU-LP). We then perform several experiments for speech and instrumental sound sources recorded using two microphones, in determined and under-determined scenarios, and with different types of initialization of the model parameters. The results of these experiments clearly indicate a significant improvement of the proposed algorithm with the localization prior over the state-of-the-art NTF-based source separation algorithms, which can reach up to 50% in the signal-to-distortion ratio.
Multivariate Non-Negative Matrix Factorization with Application to Energy Disaggregation

Non-Intrusive Load Monitoring aims to extract multiple unknown variables, i.e. device signatures, from a single observation, thus it can be considered as a single-channel source separation problem. Source separation methods and especially Non-negative Matrix Factorization have been utilized to solve the Non-Intrusive Load Monitoring problem. However, due to the restrictions of Non-negative Matrix Factorization being only applicable for utilization of one feature only active power signals have been used as features and multivariate signals, i.e. active and reactive power have not been used. In the proposed architecture the baseline Non-negative Matrix Factorization approach is expanded utilizing multi-variate signals. The proposed approach was evaluated on the AMPds2 dataset reporting performance improvements up to 21.7% when being compared with other source separation approaches reported in the literature.
Blind Extraction of Moving Sources via Independent Component and Vector Analysis: Examples

This paper is devoted to the recently proposed mixing model with constant separating vector (CSV) for Blind Source Extraction of moving sources using the FastDIVA algorithm, which is an extension of the famous FastICA and FastIVA for static mixtures. The benefits due to the CSV model and FastDIVA are demonstrated in three new applications. First, the extraction of a moving speaker in a noisy reverberant environment using a dense array of 48 MEMS microphones is considered. Second, a case study on the blind extraction of moving brain activity from visually evoked potentials in electroencephalogram is reported. Third, a simulation of block-by-block online extraction of a moving source is demonstrated. In these examples, the CSV and FastDIVA show their new potential and good performance in handling the blind moving source extraction problem.
Beaded stream-like CoSe2 nanoneedle array for efficient hydrogen evolution electrocatalysis

The development of earth-abundant and efficient electrocatalysts for the hydrogen evolution reaction (HER) is one of the keys to success for future green energy systems using hydrogen fuel. Nanostructuring of electrocatalysts is a promising way to enhance their electrocatalytic performance in the HER. In this study, pure pyrite-type beaded stream-like cobalt diselenide (CoSe2) nanoneedles are directly formed on flexible titanium foils through treating a cobalt oxide (Co3O4) nanoneedle array template with selenium vapor. The beaded stream-like CoSe2 nanoneedle electrode can drive the HER at a current density of 20 mA cm−2 with a small overpotential of 125 mV. Moreover, the beaded stream-like CoSe2 nanoneedle electrode remains stable in an acidic electrolyte for 3000 cycles and continuously splits water over a period of 18 hours. The enhanced electrochemical activity is facilitated by the unique three-dimensional hierarchical structure, the highly accessible surface active sites, the improved charge transfer kinetics and the highly attractive force between water and the surface of the nanoneedles that exceeds the surface tension of water.
Comparison Of Sorption Isotherms Of Mono- and Disaccharides Relevant To Oligosaccharide Separations For Na, K, And Ca Loaded Cation Exchange Resins

Abstract Oligosaccharides (OS) are applied as a functional food and feed ingredient. OS are produced as mixtures of different types of carbohydrates, and further separation is required for most applications. An example of separation is the removal of monosaccharides in order to decrease the amount of calories and the sweet taste. The work presented here focuses on finding an optimized poly(styrene-co-divinylbenzene) cation exchange resin as the sorbent for the chromatographic removal of monosaccharides, mainly glucose, from OS. The influence of Ca2+, Na+, and K+ as the cations of Dowex 50WX4-400 was investigated by determination of isotherms under relevant industrial conditions (temperature 60°C and sugar concentrations up to 400 g/L). Both the static desorption method and the dynamic frontal analysis method were used for isotherm measurement. The two methods mentioned give slightly different isotherms, which may be attributed to the assumption of no shrinking of the resin. It was shown experimentally that K+ loaded resin has a stronger adsorption of sugars than the Na+ loaded resin. The observed isotherm order is: fructose ≈ galactose > glucose > lactose > sucrose. The lower isotherms of the disaccharides are explained by the size exclusion mechanism. The order of the monosaccharide isotherms is in line with the number of equatorial-axial oriented sugar OH groups for complexation with the cation. The observed selectivity for glucose/lactose is independent of the cations considered and about 1.3, but capacity is highest for K+ loaded resin. The selectivity for fructose over sucrose is 2.4 for Ca2+ loaded resin and is clearly higher than for Na+ and K+. Therefore, based on selectivity and capacity, the K+ ion seems the most suitable cation for separation of glucose from OS and the Ca2+ cation is the best choice for removal of fructose from OS. No mass transfer effects were included in the comparison.
Laplacian Regularized Tensor Low-Rank Minimization for Hyperspectral Snapshot Compressive Imaging

Snapshot Compressive Imaging (SCI) systems, including hyperspectral compressive imaging and video compressive imaging, are designed to depict high-dimensional signals with limited data by mapping multiple images into one. One key module of SCI systems is a high quality reconstruction algorithm for original frames. However, most existing decoding algorithms are based on vectorization representation and fail to capture the intrinsic structural information of high dimensional signals. In this paper, we propose a tensor-based low-rank reconstruction algorithm with hyper-Laplacian constraint for hyperspectral SCI systems. First, we integrate the non-local self-similarity and tensor low-rank minimization approach to explore the intrinsic structural correlations along spatial and spectral domains. Then, we introduce a hyper-Laplacian constraint to model the global spectral structures, alleviating the ringing artifacts in the spatial domain. Experimental results on hyperspectral image corpus demonstrate the proposed algorithm achieves average 0.8~2.9 dB improvement in PSNR over state-of-the-art work.
Speaker-Independent Brain Enhanced Speech Denoising

The auditory system is extremely efficient in extracting attended auditory information in the presence of competing speakers. Single-channel speech enhancement algorithms, however, greatly lack this efficacy. In this paper, we propose a novel deep learning method referred to as the Brain Enhanced Speech Denoiser (BESD), that takes advantage of the attended auditory information present in the brain activity of the listener to denoise a multi-talker speech. We use this information to modulate the features learned from the sound and the brain activity, in order to perform speech enhancement. We show that our method successfully enhances a speech mixture, without prior information about the attended speaker, using electroencephalography (EEG) signals recorded from the listener. This makes it a great candidate for realistic applications where no prior information about the attended speaker is available, such as hearing aids or cell phones.
Evaluation and Comparison of Three Source Direction-of-Arrival Estimators Using Relative Harmonic Coefficients

A spherical harmonics domain source feature called relative harmonic coefficients (RHC) has recently been applied to address the source direction-of-arrival (DOA) estimation problem. This paper presents a compact evaluation and comparison between two existing RHC based DOA estimators: (i) a method using a full grid search over the two-dimensional (2-D) directional space, (ii) a decoupled estimator which uses one-dimensional (1-D) search to separately localize the source's elevation and azimuth. We also propose a new estimator using a gradient descent search over the 2-D directional grid space. Extensive experiments in both simulated and real-life environments are conducted to examine and analyze the performance of all the underlying DOA estimators. Two objective metrics, including localization accuracy and algorithm complexity, are adopted for an evaluation and comparison between all estimators.
Determination of pH of soils by different methods : collaborative study

Fifty-three laboratories (including author's) from Canada, India, Israel, and the United States participated in a collaborative study for the measurement of pH of different types of soils. A method with 2 alternative procedures was used for pH measurements of mineral soils (alternative I for soils containing less than 17× organic carbon and alternative II for soils with variable salt content), a second method was used for saline-sodic soils, and a third method was used for organic soils (soils containing at least 17× organic carbon). The pH was measured potentiometrically. The methods were selected by the Soil Science Society of America, S889 Committee on Coordination of Official Methods of Soil Analysis. Each laboratory used all 4 procedures to analyze 10 blind duplicate samples per procedure. The repeatability relative standard deviation values (RSD,) were 1.45-7.80% for mineral soils tested by the alternative 1, 0.95-6.91% for mineral soils tested by the alternative 11, 0.74-7.09% for saline-sodic soils, and 0.73-4.66% for organic soils. The corresponding reproducibility relative standaad deviation (RSDR) values were 2.67-10.75%, 2.03-7.54%, 2.45-9.93%, and 2.15-6.32%. Repeatability and reproducibility data indicated that the results are within acceptable levels. The 3 methods for pH measurements of mineral, saline-sodic, and organic soils were adopted first action by AOAC INTERNATIONAL
A Solid-State Hybrid Solar Cell Made of nc-TiO2, CdS Quantum Dots, and P3HT with 2-Amino-1-methylbenzimidazole as an Interface Modifier

Solid-state hybrid solar cells have been constructed using nanocrystalline titania as an electron acceptor and transporter, CdS quantum dots as a sensitizer, and poly(3-hexylthiophene) as a hole transporter. Nanocrystalline titania consisted of a bottom compact layer about 340 nm thick and a top layer about 3.4 μm thick that formed an open structure. CdS quantum dots were deposited by successive ionic layer adsorption and reaction. Poly(3-hexylthiophene) was deposited on the top by spin-coating using a solution that also contained 2-amino-1-methylbenzimidazole. The latter greatly affected cell performance that reached an efficiency of 0.87%, which is among the highest values recorded with cells of the present combination. The above cells were very easy to assemble. All layers were applied at ambient conditions, including the top silver electrodes. Cells demonstrated a remarkable stability, even though they were neither sealed nor encapsulated.
Automated Optical Image Analysis of Iron Ore Sinter

Sinter quality is a key element for stable blast furnace operation. Sinter strength and reducibility depend considerably on the mineral composition and associated textural features. During sinter optical image analysis (OIA), it is important to distinguish different morphologies of the same mineral such as primary/secondary hematite, and types of silico-ferrite of calcium and aluminum (SFCA). Standard red, green and blue (RGB) thresholding cannot effectively segment such morphologies one from another. The Commonwealth Scientific Industrial Research Organization’s (CSIRO) OIA software Mineral4/Recognition4 incorporates a unique textural identification module allowing various textures/morphologies of the same mineral to be discriminated. Together with other capabilities of the software, this feature was used for the examination of iron ore sinters where the ability to segment different types of hematite (primary versus secondary), different morphological sub-types of SFCA (platy and prismatic), and other common sinter phases such as magnetite, larnite, glass and remnant aluminosilicates is crucial for quantifying sinter petrology. Three different sinter samples were examined. Visual comparison showed very high correlation between manual and automated phase identification. The OIA results also gave high correlations with manual point counting, X-ray Diffraction (XRD) and X-ray Fluorescence (XRF) analysis results. Sinter textural classification performed by Recognition4 showed a high potential for deep understanding of sinter properties and the changes of such properties under different sintering conditions.
Feasibility of a Geriatric Assessment to Detect and Quantify Sarcopenia and Physical Functioning in German Nursing Home Residents—A Pilot Study

Background: Entering into a nursing home leads to increased immobility and further reductions in physical and cognitive functioning. As a result, there is a risk of sarcopenia, which is characterized by loss of muscle strength, muscle mass and physical functioning. To our knowledge, the feasibility of sarcopenia screening has not yet been performed in the German nursing home setting. Methods: For sarcopenia screening, the specifications of EWGSOP2 were applied. The quantification of sarcopenia was performed according to the corresponding cut-off values. The collection of anthropometric data and the morbidity status were recorded. SARC-F, mini-mental state examination, Barthel Index, Short Physical Performance Battery and Timed Up and Go tests were implemented. Results: In one participant, severe sarcopenia could be identified. The quantification was not possible for four participants. A suspicion of sarcopenia was not confirmed in five participants. Only one person was able to perform all assessments. Conclusions: Sarcopenia screening according to EWGSOP2 presented satisfactory feasibility by nursing home residents. However, further tests to assess the physical functioning of the participants often could not be performed. Moreover, inconsistencies in individual assessments became apparent, leading to inconclusive analyses. The recording of sarcopenia prevalence in German nursing homes should be the goal of further research.
Managing Vineyard Topography and Seasonal Variability to Improve Grape Quality and Vineyard Sustainability

Topography may induce variability in meteorological conditions at the meso-scale level and could influence grape quality. Understanding the impact of topography on grape ripening allows for the development of sustainable management practices that include topographical influences in their consideration. This is also important for applying proactive strategies able to counter the expected changes of climate. This study was conducted on cv. Nebbiolo vineyards in North-West Italy. The topographic traits were performed in 17 vineyards within the region, which had previously been identified as belonging to different terroir units. An analysis of historical meteorological data series was also carried out to characterize the units from the meteorological point of view. The grape composition was investigated during 2012 and 2013. Based on the topography traits, a Cluster Analysis classified the 17 vineyards into four groups. Differences among groups mainly concerned insolation and heat accumulation. Topography influenced the individual components of grape quality differently depending on the seasonal weather trend. Interactions between topography and vintage were observed for a few parameters. Better understanding the grapevine reaction to external factors/site characteristics can allow for improved site and season-specific management decision making and can contribute to improving vineyard sustainability while maintaining winery objectives and wine typicity.
Running title: DIET OF ARTHROPODOPHAGOUS BATS FROM ARGENTINA Academy Section: ECOSYSTEMS

The diet of arthropodophagous bats can be infl uenced by several factors. Furthermore, its study is critical for understanding their role in the ecosystem as regulators of arthropod abundance. The aim of this study was to analyze the diet of 12 species beloging to two families of arthropodophagous bats from the Yungas Forests, Northwestern Argentina. We also evaluated differences in diet between well-preserved and disturbed sites, sexes, and seasons. The specimens were collected with mist nets in eight different localities, four well-preserved and four disturbed sites of the Yungas Forests. Through the analysis of feces, arthropod remains were identifi ed until the lowest possible taxonomic level. Volume and frequency of occurrence percentages for each food item and the niche breadth for the species were estimated. A total of 475 samples from 12 species were analyzed and their diet contained arthropods from eight orders and seven families; the highest number of consumed arthropod orders were registered for Eptesicus diminutus. A low niche breadth was recorded in general for all species. The diet was signifi cantly infl uenced by season and site characteristics only in E. diminutus and E. furinalis, respectively. This showed that bats could modify its diet according to the different habitats and seasons.
Effect of Addition of Tryptophan on Aggregation of Apo-α-Lactalbumin Induced by UV-Light

UV-B illumination facilitates aggregation of alpha-lactalbumin (α-LA) by intramolecular disulfide bond cleavage followed by intermolecular thiol-disulfide exchange reactions. However, long term exposure to UV-B illumination may induce undesired oxidative modifications of amino acid residues in the protein. The purpose of this study was to examine the effect of UV-induced aggregation of apo-α-LA (a calcium-depleted form of α-LA) under aerobic and anaerobic conditions and by addition of tryptophan (Trp) as a photosensitizer. The addition of Trp to apo-α-LA illuminated under anaerobic conditions facilitated the highest level of free thiol release and disulfide-mediated aggregation as compared to without addition of Trp under both anaerobic and aerobic conditions. Addition of Trp under aerobic condition resulted in the lowest level of free thiols and disulfide-mediated aggregation and the aerobic conditions caused oxidation of the free Trp with formation of kynurenine and 5-hydroxy-Trp. Minor levels of the Trp oxidation product, 3-hydroxy-kynurenine (2% converted from Trp), was formed in apo-α-LA with added Trp under both aerobic and anaerobic conditions after UV-B treatment.
Factors affecting the employability of private university graduates: an exploratory study on Bangladeshi employers

This paper aims to identify the factors that can affect the overall graduate employability (OGE) of the private university graduates of Bangladesh. The authors carefully selected six such employable factors after searching the existing literature. Those six factors: academic performance (AP), technical skills (TS), communication skills (CS), personality (PE), leadership & motivational skills (LMS); and teamwork and problem solving skills (TPSS), had been considered as the independent variables while OGE had been considered as the single dependent variable. ,The authors collected the primary data from a valid sample of 360 employers through a structured questionnaire working as the hiring managers. Those respondents were selected on a random basis. The authors used exploratory factor analysis to validate the items under those independent variables and structural equation modeling with AMOS (24) to test the hypothesized relationship between each independent variable and the dependent one. ,After proper statistical analysis, the results revealed that AP, PE, CS and TPSS can positively and significantly influence the OGE of Bangladeshi graduates while LMS and TS have positive but insignificant influence over OGE. ,Based on the findings, this paper can help scholars in further investigating the employability factors. ,This explorative study will guide the fresh graduates in developing their required employability skills while assisting the employers in recruiting suitable candidates with the required skills and performance. ,This is one of the few attempts that focused on the employability factors of private university graduates in Bangladesh. The authors are well confident that this empirical paper can shed some light on the fresh graduates’ employability and conducting further investigations on it.