Miracle-dz/UniFAR-FTUs huggingface dataset:
Advances in Pediatrics and Neonatal Care

This paper pursues a simple analysis of a static relationship between national income and income distribution, and obesity/overweight and undernutrition in African countries. From intuition, a relation between national income (GDP/Capita) and malnutrition is expected. Countries that have higher income are expected to have higher prevalence of obesity/overweight. Likewise, countries with higher income should have lower levels of undernutrition. This paper tests this hypothesis using macroeconomic data. The paper also analyses the role of income inequality, as measured by the GINI coefficient, as a potential driver of malnutrition. In this case, countries that have high levels of income inequality are expected to have coexistent high levels of both obesity and undernourishment. Results of this analysis show that there is a correlation between income and malnutrition. This relationship is insignificant, with a correlation coefficient of less than 50% for both undernourishment and overweight/ obesity. The signs are as expected, even when running a simple regression of the variables. Higher national income has a positive relationship with obesity and negative relationship with undernourishment. From the regression, only the coefficient on undernourishment is significant at 5% level of significance. No significant relationship was found between income distribution and malnourishment, even on the extended logistic model. These finding are not realistically surprising. Higher income does not guarantee good nutrition, although poorer countries are expected to have high level of undernourishment. Also, there is a friction in the response of undernutrition to growth in GDP. Given the low-income elasticity of demand for food, higher income is not expected to be strongly linked to obesity. This could also be an explanation for the low response of malnutrition to income inequalities, although this latter relationship needs to be tested further with data sets of longer duration, in a time series approach. As such, it is important to lobby governments to mainstream food and nutrition security in other initiatives that increase national income, and to promote direct interventions that reduce the prevalence of undernourishment as part of meeting the Sustainable Development Goals (SDGs). This will ensure that high national income translates to reduction in malnutrition prevalence across countries.
Marital commitment as a function of marital satisfaction, marital investment and marital alternatives among working women in Malaysia

Research on marriage, its correlates and consequences, has been mostly done in the Western countries and often the dependent variable links with the subjective evaluation on the quality of the marriage. Marital instability has been steadily included as one of the outcome variables which may imply the lack of commitment towards sustaining the relationship. Considering the increased trend in number of recorded divorce cases among the Malays in Malaysia, this study utilized Rusbult's Investment Model to examine the relationships between marital satisfaction, alternatives, investment and commitment toward marriage among married working women. The model postulates that an increases in satisfaction, decreases in quality of alternative, and increases in investment size would increase one's commitment in the marital relationship, hence, hindering marital dissolution. Using data on three hundred fifteen (n=315) married women from dual-earner couples in Malaysia, this study aims to determine the relationships between the aforementioned variables. Significant bivariate relationships between all independent variables and marital commitment were established. Findings of multiple regression analyses on the relevant variables for the model revealed that alternatives in marriage served as the strongest predictor of marital commitment, followed by marital satisfaction and marital investment. This model explained 65% of variance of marital commitment of the respondents in the study. However, controlling for selected socio-demographic variables, the findings indicated that married working women who perceived low quality of alternatives, with lower family income and higher marital satisfaction tended to have greater marital commitment. This additional analysis which explains only 45% of variance of marital commitment of the respondents also revealed that marital investment was not one of the significant predictors. Findings of the study lend support for the hypotheses derived from the model. Embracing contextual variables in the analysis explains the role of family income, and highlights variation in the role of marital investment as a predictor for marital commitment. The insignificant role of marital investment may imply that the inclination to weigh on marriage in terms of gain and lost may not be perceived as critical among the respondents. Confounding roles of cultural elements, economic interdependence and its associated variables may need to be further explored in future studies.
MULTISCALE TERRAIN ANALYSIS FOR THE IDENTIFICATION OF EROSION SUSCEPTIBLE AREAS AN EXAMPLE OF LEBANESE TERRITORIES

The objective of this paper was to develop multiscale models for the identification of erosion susceptible areas, exploring the potential of different spatial resolution open source Digital Elevation Models (DEM), (MERIT, SRTM, ALOS AW3D, and ALOS PALSAR). Topography and terrain derivative parameters that have the greater impact on erosion were calculated in Geographical Information System based on geomorphometry algorithms and fuzzy logic functions proposed for theevaluation of each parameter on erosion risk in Lebanese territories. The objective of this research was to develop based on topography parameters (slope and dissection index) and based on terrain derivatives (LS factor, profile curvature, stream power index and topography wetness index) four different models for assessing the susceptible areas of erosion on the Lebanese territories, exploring the potential of DEMs of different spatial resolutions. Topography parameters and terrain derivatives were computed fromthe DEM ́s elevation, and some fuzzy logic functions were proposed toevaluate the influence of each parameter on erosion risk. The results showed that DEM useis relatively easy, an uncostly method to identify, in a qualitative way, the erosion susceptible areas (ESA) varies with the spatial resolution (scale) and related to the DEM way of interpolation. From this study, we can conclude that in digital erosion modeling the correlation vary with the type and resolution of the database used and influence on the shape and geometry of the Erosion Susceptible Areas.
Chirality: The Key to Specific Bacterial Protease-Based Diagnosis?

markdownabstractAbstract Bacterial proteases play an important role in a broad spectrum of processes, including colonization, proliferation and virulence. In this respect, bacterial proteases are potential biomarkers for bacterial diagnosis and targets for novel therapeutic protease inhibitors. To investigate these potential functions, the authors designed and used a protease substrate fluorescence resonance energy transfer (FRET)-library comprising 115 short D- and L-amino-acid-containing fluorogenic substrates as a tool to generate proteolytic profiles for a wide range of bacteria. Bacterial specificity of the D-amino acid substrates was confirmed using enzymes isolated from both eukaryotic and prokaryotic organisms. Interestingly, bacterial proteases that are known to be involved in housekeeping and nutrition, but not in virulence, were able to degrade substrates in which a D-amino acid was present. Using our FRET peptide library and culture supernatants from a total of 60 different bacterial species revealed novel, bacteria-specific, proteolytic profiles. Although in-species variation was observed for Pseudomonas aeruginosa, Porphyromonas gingivalis and Staphylococcus aureus. Overall, the specific characteristic of our substrate peptide library makes it a rapid tool to high-throughput screen for novel substrates to detect bacterial proteolytic activity.
A Novel Multi Source Electrical Energy System

The paper presents the new scheme of green energy systems using solarand wind-energy systems in order to reduce the pollution in the grid. The opportunity of a large wind and solar power production is being explored and also discusses different power electronics circuits and control methods to link the renewable energy to the national grid. This paper recommends some of the modern power electronic converters applicable to hybrid power energy systems which have improved significantly in solar and wind energy technologies to improve the quality of power. A new system configuration of the frontend rectifier stage for a hybrid wind/photovoltaic energy system allows the two sources to supply the load separately or simultaneously depending on the availability of the energy sources. The inherent nature of this Cuk-SEPIC fused converter, additional input filters are not necessary to filter out high frequency harmonics. Harmonic content is detrimental for the generator lifespan, heating issues, and efficiency. The fused multi input rectifier stage also allows Maximum Power Point Tracking (MPPT) to be used to extract maximum power from the wind and sun whenever it is available. An adaptive MPPT algorithm is used for the wind system and a standard perturb and observe method is used for the PV system. Operational analysis and the simulation results are given to highlight the merits of the proposed circuit.
Substrate Integrated Waveguide Based Millimeter Wave Antennas

Substrate Integrated Waveguide Based Millimeter Wave Antennas Dhruva Kumar Chandrappa Concordia University, October 2019 Antennas those operating at millimeter-wave (mm-wave) frequencies (30 300 GHz) are more advantageous than operating at less than 6 GHz, due to a reduction in antenna physical dimensions, an increase in the data transfer rate, and reduction in latency. However, the electromagnetic waves propagating in free-space at mm-wave frequencies experience significant propagation path loss due to the atmospheric absorption and rain attenuation. Therefore, high-gain antennas are preferred to compensate for path loss and to increase the range of wireless communication. Also, transmission lines such as microstrip, and coplanar waveguides incur high radiation losses at mm-wave frequencies. Hence, to minimize losses, a planar waveguide known as a substrate integrated waveguide (SIW) is preferred. Besides, at mm-wave frequencies, circularly polarized (CP) waves are preferred over linearly polarized (LP) waves as these waves reduce multi-path effects at the receiver. The objectives of this thesis are to design high-gain linearly, and circularly polarized antennas based on SIW at the mm-wave frequency 30 GHz. The proposed antenna models were designed, simulated, and analyzed using CST software. The antenna prototypes were fabricated and measured for the reflection coefficient, gain, and principal plane radiation patterns. In this thesis, we are proposing two single element antennas, a linear to circular wave polarizer, and an array antenna. At first, we present, a planar, cylindrical sector-substrate integrated waveguide (CSSIW) narrow slot antenna. The impedance bandwidth of this antenna is 10.87% which is approximately equivalent to 4 GHz of bandwidth at 30 GHz, and the antenna gain ranges from 8.33 to 8.84 dB within the impedance bandwidth. Further, to improve the gain, an engineered substrate is constructed on top of the CS-SIW slot antenna. The impedance bandwidth of the modified antenna is 10.42% also, the gain ranges from 10.5 to 11.44 dB over the impedance bandwidth, which implies an increase in the gain from 2.1 to 2.7 dB when compared with the gain of CS-SIW slot antenna. Also, we propose a three-layered meander-line polarizer at 30 GHz which transforms linearly polarized waves to circularly polarized waves for the CS-SIW slot antenna.
THREE NEW GENERA, A NEW SUBGENUS AND A NEW SPECIES OF LEPTOPHLEBIIDAE (EPHEMEROPTERA) FROM AUSTRALIA

Austrophlebioides gen. n. is described for A. pusillus (Harker), comb. n. , which is redescribed and designated as type species, and A. unguicularis (Ulmer), comb. n. Garinjuga gen. n. is described as monotypic for G. maryannae sp. n. and Koorrnonga gen. n. is described for K. inconspicua (Eaton), comb. n. (type species), K. fusca (Ulmer), comb, n. , K. simillima (Ulmer), comb. n. , K. brunnea (Tillyard), comb. n. , K. parva (Harker), comb. n. and K. pilosa (Suter), comb. n. Australonousia subgen. n. is described within Nousia Navás for two Australian species: N. (A.) fuscula (Tillyard), comb. n. (type species) and N. (A.) delicatula (Tillyard), comb. n. ,
Hormonal treatments for preventing recurrence of endometriomas

Endometriosis is a chronic condition determined by the presence of ectopic endometrial glands and stroma. The disease affects approximately 10% of women of reproductive age and 35-50% of women with chronic pelvic pain and/or infertility. Transvaginal ultrasonography is a very sensitive and specific instrument for the diagnosis of endometrioma. Surgical and/or medical therapies for endometriomas aim to control symptoms (in particular, chronic pelvic pain and dysmenorrhea) and prevent cyst growth; medical therapy may be employed to reduce recurrence rate after surgery. After surgical approach, the reported postoperative recurrence rate of endometriomas is high, ranging from 30% to 40%; therefore, several hormonal therapies, such as oral contraceptives (OC), progestins (PG), GnRH analogs (GnRHa), and antagonists, danazol, aromatase inhibitors, selective estrogen receptor modulators (SERMs) and selective progesterone receptor modulators (SPRMs), have been employed in order to prevent disease recurrence. The objective of this systematic review is to assess the impact of the adjuvant use of hormonal treatment on endometrioma recurrence. Two evaluators extracted from MEDLINE, EMBASE, and Cochrane Library and reviewed published studies on this topic, following pre-determined selection criteria. Finally, data were extracted from 16 selected prospective or retrospective studies, of which 8 were randomized controlled trial and 8 were cohort studies. Most of them reported a beneficial impact on endometrioma recurrence by the usage of OC, PG, and GnRH analogs (GnRHa); however, conflicting results exist in the current literature about this topic. The duration of adjuvant therapy seems to have a crucial role in this context, but it is still not clear which type of postoperative hormonal treatment represents the best choice.
IRON LOSS COMPUTATION OF A PERMANENT MAGNET MOTOR: FEA-BASED COMPARATIVE STUDY BETWEEN DIFFERENT MODELS

This paper aims to investigate iron losses in a surface mounted permanent magnet motor. For this, an overview of common iron loss models has been initially presented. Then, three different loss models have been applied for the computation of iron losses in the studied machine. The reason of testing several loss models is to discuss their advantages and disadvantages and to discuss their applicability, stability and efficiency. To perform this study, finite element method is used. Indeed, a considerable attention has been paid to the dynamic modeling of the rotating machine. Afterward, the employed models have been incorporated into the finite element analysis. Finally, the obtained results are compared and analyzed. Based on the obtained results, on one hand, it is revealed that traditional technique is fast and stable while the hysteresis models necessitates a lot of time and requires an adequate iterative procedure. On the other hand, it is shown that traditional technique is simplistic unlike the hysteresis models which are more general and accurate.
Learning dynamical systems from data: a simple cross-validation perspective

Regressing the vector field of a dynamical system from a finite number of observed states is a natural way to learn surrogate models for such systems. We present variants of cross-validation (Kernel Flows [31] and its variants based on Maximum Mean Discrepancy and Lyapunov exponents) as simple approaches for learning the kernel used in these emulators.
Localized Motion Artifact Reduction on Brain MRI Using Deep Learning with Effective Data Augmentation Techniques

In-scanner motion degrades the quality of magnetic resonance imaging (MRI) thereby reducing its utility in the detection of clinically relevant abnormalities. We collaborate with doctors from NYU Langone's Comprehensive Epilepsy Center and apply a deep learning-based MRI artifact reduction model (DMAR) to correct head motion artifacts in brain MRI scans. Specifically, DMAR employs a two-stage approach: in the first, degraded regions are detected using the Single Shot Multibox Detector (SSD), and in the second, the artifacts within the found regions are reduced using a convolutional autoencoder (CAE). We further introduce a set of novel data augmentation techniques to address the high dimensionality of MRI images and the scarcity of available data. As a result, our model was trained on a large synthetic dataset of 225,000 images generated using 375 whole brain T1-weighted MRI scans from the OASIS-1 dataset. DMAR visibly reduces image artifacts when validated using real-world artifact-affected scans from the multi-center ABIDE study and proprietary data collected at NYU. Quantitatively, depending on the level of degradation, our model achieves a 27.8%-48.1% reduction in RMSE and a 2.88-5.79 dB gain in PSNR on a 5000-sample set of synthetic images. For real-world data without ground-truth, our model reduced the variance of image voxel intensity within artifact-affected brain regions ($\mathrm{p}=0.014$).
Affine Non-negative Collaborative Representation Based Pattern Classification

During the past decade, representation-based classification methods have received considerable attention in pattern recognition. In particular, the recently proposed non-negative representation based classification (NRC) method has been reported to achieve promising results in a wide range of classification tasks. However, NRC has two major drawbacks. First, there is no regularization term in the formulation of NRC, which may result in unstable solution and misclassification. Second, NRC ignores the fact that data usually lies in a union of multiple affine subspaces, rather than linear subspaces in practical applications. To address the above issues, this paper presents an affine non-negative collaborative representation (ANCR) model for pattern classification. To be more specific, ANCR imposes a regularization term on the coding vector. Moreover, ANCR introduces an affine constraint to better represent the data from affine subspaces. The experimental results on several benchmarking datasets demonstrate the merits of the proposed ANCR method. The source code of our ANCR is publicly available at this https URL.
Phylogenetic Revision of the Late Ordovician Orthid Brachiopod Genera Plaesiomys and Hebertella from Laurentia

Abstract The orthidine brachiopod genera Plaesiomys and Hebertella are significant constituents of Late Ordovician benthic marine communities throughout Laurentia. Species-level phylogenetic analyses were conducted on both genera to inform systematic revisions and document evolutionary relationships. Phylogenetic analyses combined discrete and continuous characters, from which character states were determined using a statistical approach, and utilized both cladistic and Bayesian methodologies. Plaesiomys cutterensis, P. idahoensis, and P. occidentalis are herein recognized as distinct species rather than subspecies of P. subquadratus. Similarly, Hebertella montoyensis and H. prestonensis are recognized as distinct species separate from H. occidentalis, and H. richmondensis is recognized as a distinct species rather than a geographical variant of H. alveata. Hebertella subjugata is removed from its tentative synonymy with H. occidentalis and revalidated. The development of species-level evolutionary hypotheses for Plaesiomys and Hebertella provides a detailed framework for assessing evolutionary and paleobiogeographic patterns of Late Ordovician brachiopods from Laurentia. The geographic range of Hebertella expanded throughout Laurentia during the Richmondian into both intracratonic and marginal basins. Plaesiomys subquadratus participated in the Late Ordovician Richmondian Invasion. The recovered phylogenetic topology for Plaesiomys suggests that P. subquadratus may have migrated into the Cincinnati region from a basin situated to the paleo-northeast.
ESTIMATION OF DOUBLY FED INDUCTION GENERATOR BASED WIND ENERGY CONVERSION SYSTEM WITH HAMMERSTEIN-WIENER MODEL

The aim of this paper is to estimate the parameters such as real power, reactive power, DC link voltage and generator torque of the doubly fed induction generator based wind energy conversion system with HammersteinWiener models. The Hammerstein-Wiener models are developed for the complete wind energy conversion system and the parameters of Hammerstein-Wiener models are estimated with different procedures such as piecewise linear, sigmoid network, saturation, dead zone, wavelet network and one dimensional polynomial. Wavelet network and sigmoid network are found to be the techniques which produce the best fit percentage for all the parameters except for the generator torque in the low wind speed region and real power of medium wind speed region. Dead zone technique produces the best fit percentage for generator torque in low wind speed region. Similarly, saturation technique produces the best fit percentage for real power of doubly fed induction generator in medium wind speed region. The stability is analyzed with transient response, frequency response and pole-zero maps of the appropriate models.
Single-particle level access to hydrodynamic and frictional coupling between spheres in dense colloidal suspensions

The rotational Brownian motion of colloidal spheres in dense suspensions reflects local hydrodynamics and friction, both key to non-linear rheological phenomena such as shear-thickening and jamming, and transport in crowded environments, including intracellular migration and blood flow. To fully elucidate the role of rotational dynamics experimentally, it is crucial to measure the translational and rotational motion of all spheres simultaneously. Here, we develop compositionally uniform colloidal spheres with an off-centre, fully embedded core with a different fluorophore to the particle body, allowing access to rotational motion for all particles at the single-particle level. We reveal interparticle hydrodynamic rotational coupling in charged colloidal crystals. We also find that higher local crystallinity in denser crystals enhances rotational diffusivity, and that nearly arrested particles exhibit a stick-slip rotational motion due to frictional coupling. Our method sheds new light on the largely-unexplored local rotational dynamics of spherical particles in dense colloidal materials.
In Response to COVID-19: Configuration Model of the Epidemic Spreading

A configuration model for epidemic spread, based on a scale-free network, is introduced. We obtain the analytical solutions describing both unstable and stable dynamics of the epidemic spreading, and demonstrate how these regimes can interchange during the epidemic. We apply the model to the COVID-19 case and demonstrate the predictive features of our model.