Miracle-dz/UniFAR-FTUs huggingface dataset:
Image-based detection and classification of allergenic pollen

The correct classification of airborne pollen is relevant for medical treatment of allergies, and the regular manual process is costly and time consuming. An automatic processing would increase considerably the potential of pollen counting. Modern computer vision techniques enable the detection of discriminant pollen characteristics. In this thesis, a set of relevant image-based features for the recognition of top allergenic pollen taxa is proposed and analyzed. The foundation of our proposal is the evaluation of groups of features that can properly describe pollen in terms of shape, texture, size and apertures. The features are extracted on typical brightfield microscope images that enable the easy reproducibility of the method. A process of feature selection is applied to each group for the determination of relevance.Regarding apertures, a flexible method for detection, localization and counting of apertures of different pollen taxa with varying appearances is proposed. Aperture description is based on primitive images following the Bag-of-Words strategy. A confidence map is built from the classification confidence of sampled regions. From this map, aperture features are extracted, which include the count of apertures. The method is designed to be extended modularly to new aperture types employing the same algorithm to build individual classifiers.The feature groups are tested individually and jointly on of the most allergenic pollen taxa in Germany. They demonstrated to overcome the intra-class variance and inter-class similarity in a SVM classification scheme. The global joint test led to accuracy of 98.2%, comparable to the state-of-the-art procedures.
Penetapan Kadar Vitamin B1 Pada Kacang Kedelai dan Tempe Yang Beredar di Pasar Raya Padang Secara Spektrofotometri Visibel

It has been the research about determination level of vitamin B 1 in soy bean and tempe. The determination level of vitamin B 1 was measured by spectrophotometry visible method. The result is level of vitamin B 1 in soy bean higher than level of vitamin B 1 in tempeh. Which level of vitamin B 1 in soy bean and tempeh is about 1.0213 % ±0.0188% and 0.2960 % ±0.0095%. It show that the proces manufacturing, like washing, bathing, boiling can affect the level of vitamin B 1 . Statistic analyze anova one way by using SPSS 17 program shows there are significant different (p<0.05) in the level from each sample.
Measurement of azimuthal anisotropy of muons from charm and bottom hadrons in Pb+Pb collisions at with the ATLAS detector

Azimuthal anisotropies of muons from charm and bottom hadron decays are measured in Pb+Pb collisions at √ s NN = 5 . 02 TeV. The data were collected with the ATLAS detector at the Large Hadron Collider in 2015 and 2018 with integrated luminosities of 0 . 5 nb − 1 and 1 . 4 nb − 1 , respectively. The kinematic selection for heavy-ﬂavor muons requires transverse momentum 4 < p T < 30 GeV and pseudorapidity | η | < 2 . 0. The dominant sources of muons in this p T range are semi-leptonic decays of charm and bottom hadrons. These heavy-ﬂavor muons are separated from light-hadron decay muons and punch-through hadrons using the momentum imbalance between the measurements in the tracking detector and in the muon spectrometers. Azimuthal anisotropies, quantiﬁed by ﬂow coeﬃcients, are measured via the event- plane method for inclusive heavy-ﬂavor muons as a function of the muon p T and in intervals of Pb+Pb collision centrality. Heavy-ﬂavor muons are separated into contributions from charm and bottom hadron decays using the muon transverse impact parameter with respect to the event primary vertex. Non-zero elliptic ( v 2 ) and triangular ( v 3 ) ﬂow coeﬃcients are extracted for charm and bottom muons, with the charm muon coeﬃcients larger than those for bottom muons for all Pb+Pb collision centralities. The results indicate substantial modiﬁcation to the charm and bottom quark angular distributions through interactions in the quark-gluon plasma produced in these Pb+Pb collisions, with smaller modiﬁcations for the bottom quarks as expected theoretically due to their larger mass. correlated between and
Aspects of Phytoplankton Chlorophyll A Carbon-Specific Growth Rates, and the Distributions of Chlorophyll A and Primary Productivity in Relation to Water Column Structure in the Eastern North Atlantic Ocean

A series of time course labeling experiments were performed over a latitudinal gradient extending from 65°N to 8~, in August, 1988. Experiments were performed during the National Oceanic and Atmospheric Administration (NOAA) Global Change Expedition in the Eastern North Atlantic Ocean to investigate physiological and methodological aspects of phytoplankton growth estimated by the chlorophyll a labeling technique. The objectives were to evaluate the short-term kinetics of the labeling time of natural phytoplankton populations in different oceanic regions, determine the variability of apparent equilibration time in relation to environmental conditions, and compare growth rates from chl a labeling to independent physiological indicators of gX;0wth. The chl a carbon-specific activity (R*) increased during the day at all stations despite differences in daylength, integrated radiation and/or the commencement time of an experiment. The rate of change in R* increased a~ a ,. 38%) in the integrated total photosynthetically available radiation (PAR) received between samples. Overestimates in the specific growth rate observed at these stations were explained by the hypothesis that rapid increases in the quantity of PAR received by a phytoplankton cell may result in a disequilibrium between the
Efficient Feed Port Modeling of Patch or Microstrip Antennas in a Finite-Element Method

The modeling of antennas driven by a microstrip line requires a source or feed model. The most accurate one is the coaxial cable but it increases the burden of mesh generation. Simplified feed models have been proposed for the method of moments (MoM). Regarding the finite-element method (FEM) that, unlike the MoM, easily handles an anisotropic and/or highly inhomogeneous environment, a wire feed line can be modeled by a voltage source in the finite-width feed-gap. The input impedance is then obtained from the circulation of the magnetic field on a line around this gap. We show that this method cannot be used for a strip feed line and propose a novel and simple technique to compute the antenna impedance that can be straightforwardly implemented in an FEM numerical code. This technique can also be used for a wire feed line modeled as a strip provided that the wire radius is small enough. The pertinence and efficiency of this model is numerically evaluated on three types of antenna: dipole, patch, and microstrip.
Geographical distribution and detection of two potyviruses occurring in Momordica charantia (Cucurbitaceae) in Puerto Rico

Transmission dynamics of viruses within and among cultivated plant species are often well known. Much less studied, especially in the tropics, is the dynamic of virus exchange between cultivated and nearby wild or weedy species, even though such exchanges are known to occur. To develop the best strategies for crop protection and general disease control, spatial distribution of viruses in non-cultivated plants needs to be understood. This research focuses on the potyviruses that infect Momordica charantia (Cucurbitaceae), an alien naturalized invasive vine in Puerto Rico. A total of 390 symptomatic and asymptomatic plants were sampled throughout Puerto Rico, including adjacent islands of Culebra and Vieques. Samples were subjected to an enzyme linked immunosorbent assay (ELISA) for general potyvirus screening, and to ELISAs specific for Papaya ringspot virus (PRSV) and Zucchini yellow mosaic virus (ZYMV). The species distribution model algorithm MaxEnt was used to predict suitable environments for the potential presence of potyvirus symptoms, potyvirus, PRSV or ZYMV in M. charantia. Almost half of the samples of M. charantia tested positive for ZYMV, PRSV or both viruses. Twice as many samples were positive for PRSV (39%) than for ZYMV (21%). About 14% of samples were positive for both potyviruses. Plants that tested positive for PRSV were three times more likely to be positive for ZYMV than were plants that were negative for PRSV. Plants that tested positive using the general potyvirus ELISA were much more likely to exhibit symptoms than plants testing negative for potyvirus. In comparison, PRSV and ZYMV samples testing positive or negative were equally likely to exhibit virus-like symptoms. When we classified samples according to habitat (agricultural, rural-nonagricultural, or urban), the presence/absence of symptoms and test results for potyvirus, PRSV and ZYMV were not dependent on habitat classification. By contrast, a MaxEnt model using 20 environmental variables was able to predict areas of Puerto Rico where environmental conditions are favorable for the potential presence of virus symptoms, potyvirus, PRSV or ZYMV in M. charantia. Conditions predicted by our model to be moderately to strongly suitable for the presence of PRSV in M. charantia covered a much larger area of Puerto Rico than they did for ZYMV. The vegetable growing region in the central to eastern south coast was predicted to have highly suitable environmental conditions for the presence of both potyviruses in M. charantia.
Classification of Two-Dimensional Gas Chromatography Data

Gas chromatography (GC) is a popular tool for chemical analysis. Some samples are so complex that a single column does not have enough power to separate all of the analytes. In this instance a higher resolution GC method, known as comprehensive two-dimensional gas chromatography (GCxGC), is used. DSTL want to be able to use data from GCxGC to attribute samples to a particular region or cultivar. However, the nature of the data means that several difficulties must be overcome before being able to do this: noise from sample, peak mis-alignment, and low quantity of samples. In this report, we investigate several methods to overcome such difficulties, and then classify the data. We are very successful in telling apart blanks from seeds, but obtain limited success when trying to classify between seeds. The method that shows the most promise is k-Nearest Neighbours classification by Wasserstein distance. However, this is still quite sensitive to the noise created by the solvent in the sample. Thus, we suggest that more blank runs be obtained, so that the ‘ground truth’ behaviour of the solvent is better understood, allowing us to remove the effect of the solvent from seed data. We also hope that the methods explored here will be more successful on the full raw data than they were on the limited ‘peaks’ data available to us for the purpose of this study.
COVID-19 detection using machine learning and fusion-based deep learning models

The COVID-19 pandemic has been one of the most challenging crises attacking the world in the last three years. Many systems have been introduced in the field of COVID-19 detection. In this research, machine learning and deep learning models for the detection of COVID-19 with a probability of the presence of COVID-19 are proposed. In the machine learning scenario, the COVID-19 dataset is split into 70% training and 30% testing, and a segmentation process is applied to the CT images in order to get the lung ROI only. The features of CT images are then extracted using Gabor-Wavelet and deep-based features. The SVM classifier is then trained and evaluated. For the deep learning model, the CT images are fed into the model without feature extraction, and three different DL models (CNN, GoogleNet, and ResNet50) are trained and evaluated. Other scenarios are proposed in which the SVM Gabor-Wavelet and deep features are fused, and the three deep learning models are also fused to get better performance. The experiments show that the best model is the deep-based fusion model by which the system achieved 96.4156%, 96.1905%, and 96.1905% for accuracy, precision, and recall, respectively.
Healthcare Experience of Pediatric Patients with Autism Spectrum Disorders in Saudi Arabia: A Cross-Sectional Study

Children with autism spectrum disorder (ASD) face several challenges in the healthcare setting. This study defines the challenges experienced by children with autism in hospitals in Saudi Arabia. A cross-sectional study was conducted using a questionnaire for guardians of autistic children in outpatient clinics, autism support groups, and rehabilitation centers. A total of 199 participants were included. The medical procedures causing the most anxiety to children were injections and getting their blood drawn (68.3%), vital sign measurement (41.6%), and height and weight measurement (37.8%). Long waiting hours (44.1%), increased sensory stimuli (33.2%), and overcrowding of hospital staff (27.9%) were stress-inducing in the healthcare environment. The guardians recommended that loud noises (44.7%), crowdedness (41.2%), and long waiting hours (42.1%) be avoided. The nonverbal children experienced significantly higher levels (p < 0.001) of agitation, irritability, and outbursts during doctor visits than their verbal counterparts. The children with intellectual disabilities were more tense and unresponsive during doctor visits (33.3%) than their intellectually able counterparts, who more frequently were calm and responsive (44.9%) during visits. Most patients with ASD face hardships during hospital visits. Nonverbal patients and those with intellectual disabilities have a higher tendency for hospital setting anxiety-induced outbursts, which may be eased by avoiding loud noise and overcrowding.
Single-Layered Broadband Magnetoelectric Dipole Antenna for New 5G Application

In this letter, a new type of broadband magnetoelectric dipole antenna is investigated and implemented for millimeter-wave applications, particularly for new fifth-generation (5G) applications. The proposed antenna has broadband operating bandwidth and high front–back radiation level owing to its complementary antenna configuration. The antenna also features a single-layer structure to bring about ease of fabrication and low profile. The antenna covers an operating bandwidth of 50.4% (47.5–79.5 GHz), which thoroughly covers the new unlicensed band in the new 5G standard. The antenna yields advantages of broadband, low back-radiation level, and low fabrication cost.
Portuguese variety identification on broadcast news

This paper describes an accent identification system for Portuguese, that explores different type of properties: acoustic, phono tactic and prosodic. The system is designed to be used as a pre-processing module for the Portuguese automatic speech recognition system developed at INESC-ID. In terms of variety identification, the overall rate of correct identification is 69.0% if all 7 varieties are considered, and the best results are obtained for Brazilian Portuguese, also the variety that proved easiest to identify in perceptual experiments. When distinguishing between European, Brazilian and African Portuguese, the identification rate goes up to 94.7%. The fact that the prosodic system alone can achieve an identification rate of 77% is also worth investigating.
Spectrum Sharing Games on the Interference Channel

In this paper, we address the problem of spectrum sharing where competitive operators coexist in the same frequency band. First, we model this problem as a strategic non-cooperative game where operators simultaneously share the spectrum according to the Nash Equilibrium (N.E). Given a set of channel realizations, several Nash equilibria exist which renders the outcome of the game unpredictable. For this reason, the spectrum sharing problem is reformulated as a Stackelberg game where the first operator is already being deployed and the secondary operator follows next. The Stackelberg equilibrium (S.E) is reached where the best response of the secondary operator is taken into account upon maximizing the primary operator’s utility function. Finally, we assess the goodness of the proposed distributed approach by comparing its performance to the centralized approach.
A Low-Power Keyword Spotting System With High-Order Passive Switched-Capacitor Bandpass Filters for Analog-MFCC Feature Extraction

This paper presents a low-power high-accuracy key-word spotting (KWS) system based on analog passive switched-capacitor (SC) bandpass filters (BPF). The proposed system inno-vatively extracts the Mel-frequency cepstrum coefficient (MFCC) features with all-analog circuits, providing a better spotting performance than the present analog short-time amplitude or energy features under the same condition. At the circuit level, the analog-MFCC extraction includes the low-noise amplifier, BPF, squarer, integrator, and discrete cosine transformer. And thanks to the effective analog-MFCC features, the size of the fully-connected neural network (FCNN) classifier in our KWS system is enormously reduced. A high-order and fully-differential BPF is also proposed, achieving ultra-low power and high dynamic range by combining zero and pole generation stages rather than building stages separately in traditional ways. Fabricated in 0.18- $\mu \text{m}$ CMOS, our filterbank of eight BPFs is measured with a power consumption of 83.2 nW, with a 69.7 dB dynamic range at 5% THD, having advantages over other SC BPFs with similar functions. The total power consumption of our feature extractor is 661.7 nW, achieving an accuracy of 96.6% in two-keyword spotting by an FPGA-based, 15k bit parameter FCNN with a 9.6 $\mu \text{s}$ latency.
Utilization of Extraction Procedures for Evaluating Environmental Risk from Waste Materials

Several procedures for extracting content from different waste materials types were investigated, with the aim of evaluating their environmental impact. The waste materials consisted of wastes from bauxite ore processing by means of the Bayer process (red mud, Ajka, Hungary), bauxite ore using the sintering process followed by the Bayer process (brown-red mud, Žiar nad Hronom, Banská Bystrica region, Slovakia) and sulphide ores (metal-rich post-flotation tailing, Lintich, Slovakia). The extraction procedures were carried out with the aim of isolating “mobilizable” fractions using 0.05 M ethylenediaminetetraacetic acid (EDTA) and 0.43 M acetic acid (AA) (representing environmental risk during changes in normal environmental conditions) and “maximum potentially mobilizable” fractions using 2 M HNO3 (representing the total environmental risk). The content of chosen toxic heavy metals (THMs) (Cd, Cr, Cu, Pb, Ni, Zn) and Fe, Mn as metals creating Fe/Mn oxides in the extracts and solutions after microwave digestion was determined using high-resolution continuum source flame atomic absorption spectrometry (HR CS FAAS). On the basis of the results obtained in this study, it is possible to state that different origin of waste materials is reflected in different mobility of toxic heavy metals into the surrounding environment. From the point of view of toxic heavy metals mobility, disposal site of wastes after bauxite processing are much less of a threat to the environment than disposal site of flotation sludge after processing sulphide ores. The single extraction of 0.43 M AA is more effective than the extraction of 0.05 M EDTA for the purposes of determining the content of metals in the mobilizable fraction of tailing waste materials. The mobility of the studied toxic heavy metals in the Lintich tailing decreases in the direction from the lagoon to the dam, which may indicate the fact that the dam serves to a certain extent to inhibit the mobility of metals into the surrounding ecosystem.
: A Personalized Music Recommendation Method Combining TextCNN and Attention

To deal with the problems of occurring personalized music recommendation methods, for instance, low explanation, low accuracy of recommendation, and difficulty extracting information effectively, a personalized music recommendation method combining TextCNN and attention is proposed. Firstly, TextCNN model and BERT are combined to capture local music continuous features. Secondly, self-attention is introduced to solve the remaining omitted non-continuous features that are not paid attention by TextCNN. Finally, multi-headed attention mechanism is used to get features of hotspot music and user’s interest music, and cascading fusion method is used to achieve click prediction. Experimentally, the proposed model can effectively recommend personalized music, its MAE values on FMA and GTZAN datasets are 0.156 and 0.146, respectively, improving by at least 6.6% and 3.3% compared to other comparative models. And its RMSE result values on the FMA and GTZAN datasets are 0.185 and 0.164, respectively, improving by at least 12.4% and 5.2% compared to other comparative models.
Deep unfolding for hyper sharpening using a high-frequency injection module

The fusion of multi-source data with different spatial and spectral resolutions is a crucial task in many remote sensing and computer vision applications. Model-based fusion methods are more interpretable and. flexible than pure data-driven networks, but their performance depends greatly on the established fusion model and. the hand-crafted, prior. In this work, we propose an end-to-end trainable model-based. network for hyperspectral and panchromatic image fusion. We introduce an energy functional that takes into account classical observation models and. incorporates a high-frequency injection constraint. The resulting optimization function is solved by a forward-backward splitting algorithm and. unfolded into a deep-learning framework that uses two modules trained, in parallel to ensure both data observation fitting and constraint compliance. Extensive experiments are conducted, on the remote-sensing hyperspectral PRISMA dataset and on the CAVE dataset, proving the superiority of the proposed deep unfolding network qualitatively and quantitatively.
The Unicellular, Parasitic Fungi, Sanchytriomycota, Possess a DNA Sequence Possibly Encoding a Long Tubulin Polymerization Promoting Protein (TPPP) but Not a Fungal-Type One

The unicellular, parasitic fungi of the phylum Sanchytriomycota (sanchytrids) were discovered a few years ago. These unusual chytrid-like fungi parasitize algae. The zoospores of the species of the phylum contain an extremely long kinetosome composed of microtubular singlets or doublets and a non-motile pseudocilium (i.e., a reduced posterior flagellum). Fungi provide an ideal opportunity to test and confirm the correlation between the occurrence of flagellar proteins (the ciliome) and that of the eukaryotic cilium/flagellum since the flagellum occurs in the early-branching phyla and not in terrestrial fungi. Tubulin polymerization promoting protein (TPPP)-like proteins, which contain a p25alpha domain, were also suggested to belong to the ciliome and are present in flagellated fungi. Although sanchytrids have lost many of the flagellar proteins, here it is shown that they possess a DNA sequence possibly encoding long (animal-type) TPPP, but not the fungal-type one characteristic of chytrid fungi. Phylogenetic analysis of p25alpha domains placed sanchytrids into a sister position to Blastocladiomycota, similarly to species phylogeny, with maximal support.