Miracle-dz/UniFAR-FTUs huggingface dataset:
Phonon Dispersions as Indicators of Dynamic Symmetry Reduction in Superconductors

Strong correlations between phonon energies and superconducting transition temperatures can be extracted from phonon dispersion calculations using density functional theory for a range of superconducting materials. These correlations are robust and consistent with experimental data for key external conditions including isotope effects, elemental substitutions and pressure variations. Changes in the electronic band structure also correlate with transitions to/from superconductivity but, in general, are less sensitive and less obvious than phonon behaviour. A computational approach that considers both phonons and electrons and the presence or absence of a phonon anomaly works well for conventional superconducting materials with hexagonal, cubic or tetragonal symmetries. Superconductivity in these compounds often involves symmetry reduction in an original non-superconducting parent compound induced, for instance, by substitution or by a dynamic reduction in symmetry shown in electron density distributions and Raman spectra. Such symmetry reduction is effectively modelled with super-lattice constructs which link Raman spectra with key superconducting parameters.
Diffracted Beams from Metasurfaces: High Chiral Detectivity by Photothermal Deflection Technique

Measurements of difference in optical interactions between circularly polarized excitations of opposite handedness (circular dichroism) are highly important for both natural and artificial chiral structures. Here the photothermal deflection technique is proposed as a method to detect the optical chirality of a metasurface, analyzing the diffracted beams by the metasurface itself. Two metasurfaces are investigated, based on Au and Ag. The samples are fabricated by nanosphere lithography, with a tilted deposition of thin metal layer, which produces symmetry‐breaking. The unit cell periodicity of these metasurfaces allows for multiple order diffraction in the 450–520 nm range, which encompasses the emission lines of an Ar laser. The metasurfaces are placed on a mirror and excited by an Ar pump beam at different orientations, laser wavelengths, and circular polarization degree; the probe beam scans the absorption of the diffraction orders back‐reflected from the underlying mirror. In this way, the chiral investigation is simplified by placing the scanning of absorption‐induced thermal effect into the metasurface plane, thus avoiding the transmission/reflection measurements of a specific order, which are done by angular placement of detector. Theoretical and numerical approaches are further developed to reconstruct both thermal and optical behavior of the chirality at the nanoscale.
Metabolic Response of ‘Topaz’ Apple Fruit to Minimal Application of Nitrogen during Cell Enlargement Stage

Nitrogen is an integral element of foliar sprays during apple fruit formation. However, in red cultivars, the application may have adverse effects on color in the second stage of fruit development. The effect of a low-dose foliar application of urea was monitored on ‘Topaz’ apple pomometric (fruit mass, firmness, total solids, starch content, skin color) and biochemical traits (primary metabolites, phenolic compounds, and assimilatory pigments). Three applications (17 July, 27 July, and 18 August) of two different urea doses (N1 = 1.4 kg N ha−1; N4 = 4 kg N ha−1) and control (N0, only sprayed with water) were used. Low doses of urea did not affect flesh firmness, total soluble, solid, and starch content, but individual fruit mass was significantly higher in N1 treatment compared to the other two treatments. Significantly lower a* parameters and a lower content of anthocyanins were measured on apples subject to N4 treatment. Many secondary metabolites (phenolic acids, flavan-3-ols, flavonols, and chalcones) were also negatively affected by low-dose urea application. Conversely, urea treatments significantly increased total assimilatory pigments in apple skin. Even minor levels of nitrogen, applied directly on the leaf at later stages of red apple fruit development, negatively altered color traits and the composition of metabolites.
Comparison of Different Herbal Additives on Immune Response and Growth Performance of Broiler Chickens

This experiment was conducted to compare the effects of four commercial herbal additives (Noviherb®, Bioessence®, Biostrong®, and Novigrow®), and a commercial antibiotic (virginiamycin) on growth performance, carcass yield, visceral organs weight, thyroid hormones, and humoral immune responses of broiler chickens. Nine hundred day-old Ross 308 male broiler chicks were reared in litter-covered floor cages and distributed into five experimental groups with six replicates of 30 birds. Five dietary treatments tested were diets supplemented with Noviherb®, Bioessence®, Biostrong® (each of them 100g/ton of diet), Novigrow® (1000g/ton of diet), and virginiamycin (100g/ton of diet) as a positive control. Feed intake, body weight, mortality, feed conversion ratio, European broiler index, and feed cost per kilogram of body weight were measured during the experiment. Antibody titers against sheep red blood cells (SRBC), immunoglobulin G, immunoglobulin M, and plasma concentrations of thyroxine (T4) and triiodothyronine (T3) were evaluated at the age of 42 days. Then, four birds per replicate were killed to determine the relative weight of carcass and organs. The GLM procedures of SAS software and Duncan’s multiple range test were applied to analyze data in a completely randomized design with five treatments and six replicates of 30 birds per each. The effects of herbal additives on productive traits feed cost per kilogram of body weight and relative weight of organs were not significant in comparison with antibiotic treatment. Dietary inclusion of Noviherb®, Biostrong®, and Novigrow® significantly decreased feed cost per kilogram of carcass compared with Bioessence® or antibiotic treatments (p<0.05). The titers of IgG in Noviherb® and virginiamycin were significantly higher (p<0.05) than in Biostrong® and Novigrow® fed groups. The plasma concentration of triiodothyronine was significantly decreased (p<0.05) by dietary inclusion of Noviherb® and Novigrow® compared to the antibiotic. In conclusion, all the evaluated herbal additives could act as a substitute for the growth-promoting antibiotic.
Electromechanical-Mode Coupling Model and Failure Prediction of CFRP under Three-Point Bending

Carbon fiber reinforced polymer materials (CFRP) cause CFRP to bend or fail when subjected to external loads or impacts. In the case of static three-point bending, using the conductive properties of the carbon fiber inside the CFRP, the overall damage detection and failure prediction can be carried out by electromagnetic methods. The eddy current coil is used to realize real-time monitoring of damage, and the measured voltage value can be mapped to obtain the load of the sample. This paper conducts theoretical analysis and experimental verification, and obtains the relationship between CFRP stress damage and spatial conductivity change, and proposes a CFRP electromechanical coupling model under quasistatic three-point bending. Combined with the theory of electrically ineffective length, the CFRP three-point bending electromechanical coupling model was revised. Experimental results prove that the revised model can describe the load-conductivity change trend of three-dimensional braided CFRP more accurately, which provides a theoretical basis for monitoring the structural health of CFRP through electromagnetic methods.
Water Chemistry During Baseflow Helps Inform Watershed Management: A Case Study of the Lake Wister Watershed, Oklahoma

Nonpoint source (NPS) pollution from agricultural and urban development is a primary source of nutrients and decreased water quality in aquatic systems. Installation of best management practices (BMPs) within critical source areas of the watershed can be helpful at reducing the transport of nutrients to waterbodies; however, prioritizing these areas may be difficult. The objective of this study was to develop several potential frameworks for prioritizing subwatersheds using baseflow water chemistry data in relation to a simple human development index (HDI; total percent agriculture and urban development). At a monthly interval, samples were collected at 26 sites throughout the Oklahoma portion of the Lake Wister Watershed (LWW) and analyzed for total nitrogen, total phosphorus, total suspended solids, and chlorophyll a. Changepoint analysis for each parameter found significant thresholds for each of the parameters ranging from 20 to 30% HDI. Changepoint analysis summary statistics were used to develop prioritization frameworks for the LWW that could be used to target subwatersheds where BMP installation would have the greatest effect at improving water quality. Additionally, regression models developed from the relationships between water quality parameters and HDI values serve as realistic targets for improving water quality, with the modeled line representing the target concentration for a given HDI value. After BMPs have been implemented, baseflow monitoring should continue at the subwatershed scale to track changes in water quality. Focusing monitoring efforts at the subwatershed scale will provide an earlier indication of the effectiveness of BMPs, as it may take several decades to detect improvements in water quality at the larger watershed scale.
Potential of Fermented Sweet Corn Stover as a Substitute for Corncob in Mushroom (Flammulina velutipes) Substrate

In the present study, with a final goal of using spent mushroom substrates as roughage for cattle, mushroom cultivation experiment has been conducted on Flammulina velutipes using fermented sweet corn stover (FS) cut at the length of 13mm and 30mm as a substrate material (FS13 and FS30, respectively), and productivity and eating quality of fruiting bodies were evaluated. A total of nine substrates were prepared: control (composed mainly of ground corncob and rice bran), four FS13 groups (24, 48, 73 and 100% of rate of replacement with corncob, on dry matter basis) and four FS30 groups (the same replacement rates as in FS13 groups). The cultivation period increased in FS13 groups comparing with FS30 groups (P<0.05) and did with increasing replacement rate (P<0.01). Fruiting body yield was not affected by the length of FS, but increased gradually with increasing replacement rate, although decreased values were found when the rate was reached to 100%. Eating quality of the fruiting bodies was affected neither by length of FS nor by replacement rate. In conclusion, corncob can be replaced up to 73% with FS without showing any negative effect on productivity of F. velutipes. 
Enhancing Alzheimer’s Disease Diagnosis via Hierarchical 3D-FCN with Multi-Modal Features

Alzheimer’s disease (AD) is an incurable, progressive neurological disorder of the human brain related to loss of memory, commonly seen in the elderly population. Accurate detection of AD can help with proper treatment and prevent brain function damage. Existing CNN-based methods need to predetermine informative locations in sMRI, which means the stage of distinguishing lesions is separated from the later stages of feature extraction and classifier construction. In this paper, a novel “two-stage” framework based on a hierarchical 3D fully convolutional network (H-3D-FCN) is proposed to automatically identify discriminative local patches and regions in the sMRI. We further optimize the diagnosis performance by constructing a multi-layer perceptron (MLP) model which combines the multi-modal features (e.g., MMSE score, age, gender, APOE 4) with the risk probability maps (RPMs) generated from the H-3D-FCN model. Experiments on three typical AD datasets, namely, ADNI, AIBL, and NACC, show that our method achieves state-of-the-art performance as compared with recent baselines.
Inclusion of Citrullus colocynthis Seed Extract into Diets Induced a Hypolipidemic Effect and Improved Layer Performance

Citrullus colocynthis (CC) has been known as a natural medicinal plant with wide biological activities, including antioxidant, anti-inflammatory, and antilipidemic effects. The aim of this study was to investigate the effect of inclusion of the ethanolic extract of CC seeds (ECCs) into layer diets on the lipid profile, stress indicators, and physiological and productive performance of laying hens. A total of 216 forty-week-old commercial Hy-Line brown laying hens were randomly assigned into four equal groups (3 birds × 18 replicates per group) that received a basal diet supplemented with 0, 0.5, 1.0, and 2.0 g/kg of ECCs for 12 consecutive weeks. The first group served as a control. The results showed that ECCs at 1.0 and 2.0 g/kg significantly (p < 0.05) improved the productive and physiological performance compared to the other groups. In addition, stress indicators examined in the laying hens, including lipid peroxidation (malondialdehyde (MDA)), corticosterone hormone (CORT), tumor necrosis factor alpha (TNFα), and heat shock protein 70 (HSP70), were significantly alleviated after inclusion of ECCs into layer diets at the three levels compared to the control group. Furthermore, all ECC levels induced a significant reduction in plasma triglyceride (TG) and cholesterol (CH) levels in the plasma, liver, and egg yolk, whereas the highest levels were obtained with 2.0 g/kg of ECCs. Particularly important, a high linear correlation (R2 = 0.60–0.79) was observed between increasing doses of ECCs and MDA, liver CH, and egg yolk CH concentrations and egg weight, feed intake, and feed conversion ratio; moreover, the correlation was extremely high (R2 = 0.80–0.100) with the level of TG, CH, low-density lipoprotein CH, high-density lipoprotein CH, and CORT. These results indicated that dietary supplementation with 2.0 g/kg of ECCs could be considered a successful nutritional approach to producing healthier, lower-cholesterol eggs for consumers, in addition to enhancing the physiological and productive performance of laying hens by alleviating the stress of intensive commercial production.
Inadequacies in the SES–Achievement model: Evidence from PISA and other studies

Correspondence Gary N. Marks, Social and Political Sciences, University of Melbourne, Parkville 3052, Victoria, Australia. Emails: gmarks@unimelb.edu. au; garymarks2030@gmail.com Abstract Students’ socioeconomic status (SES) is central to much research and policy deliberation on educational inequalities. However, the SES model is under severe stress for several reasons. SES is an illdefined concept, unlike parental education or family income. SES measures are frequently based on proxy reports from students; these are generally unreliable, sometimes endogenous to student achievement, only low to moderately intercorrelated, and exhibit low comparability across countries and over time. There are many explanations for SES inequalities in education, none of which achieves consensus among research and policy communities. SES has only moderate effects on student achievement, and its effects are especially weak when considering prior achievement, an important and relevant predictor. SES effects are substantially reduced when considering parent ability, which is causally prior to family SES. The alternative cognitive ability/genetic transmission model has far greater explanatory power; it provides logical and compelling explanations for a wide range of empirical findings from student achievement studies. The inadequacies of the SES model are hindering knowledge accumulation about student performance and the development of successful policies.
Speaker-Independent Lipreading By Disentangled Representation Learning

With the development of the deep learning technology, automatic lipreading based on deep neural network can achieve reliable results for speakers appeared in the training dataset. However, speaker-independent lipreading, i.e. lipreading for unseen speakers, is still a challenging task, especially when the training samples are quite limited. To improve the recognition performance in the speaker-independent scenario, a new deep neural network structure, named Disentangled Visual Speech Recognition Network (DVSR-Net), is proposed in this paper. DVSR-Net is designed to disentangle the identity-related features and the content-related features from the lip image sequence. To further eliminate the identity information that remained in the content features, a content feature refinement stage is designed in network optimization. By this way, the extracted features are closely related to the content information and irrelevant to the various talking style and thus the speech recognition performance for unseen speakers can be improved. Experiments on two widely used datasets have demonstrated the effectiveness of the proposed network in the speaker-independent scenario.
Transfer Learning Based Model for Pneumonia Detection in Chest X-ray Images

: Pneumonia is a lung infectious disease caused by viral bacteria. It damages one or both lungs in humans. Expert radiotherapists must evaluate chest X-ray to detect pneumonia. As a result, designing an automated system for detecting pneumonia would be valuable for quickly treating the disease, especially in remote areas. This paper introduces a convolutional neural network-based model for reliably detecting pneumonic lungs from chest X-rays. This model can be used by doctors to treat pneumonia in the real world. This study proposes a hybrid model of EfficientNetB0 as a transfer learning-based model and support vector machine (SVM) hinge loss. The functionality of the pre-trained EfficientNetB0 model is used as feature-extractors followed by SVM classifier for the classification of abnormal and normal chest X-Rays. The statistical findings show that using a pre-trained EfficientNetB0 model and supervised classifier algorithm to evaluate chest X-ray images, specifically to detect Pneumonia, can be very beneficial. The proposed model achieves higher classification accuracy, precision, recall, and AUC values outperforming other state of art models with an overall accuracy of 97%.
Coeffect of Air Pollution Control Devices on Trace Element Emissions in an Ultralow Emission Coal-Fired Power Plant

In this study, distribution, partitioning concentration, balance rate, and removal efficiency of trace elements (TEs) in an ultralow emission coal-fired electric power plant (EPP) were investigated and evaluated. Results include determination of the TEs in flue gas, coal, fly ash, bottom ash, gypsum, limestone, makeup water, wet flue gas desulfurization (WFGD) wastewater, and wet electrostatic precipitator (WESP) wastewater. The results indicate that most of the TEs are distributed in the fly ash, with a smaller portion in the bottom ash. The concentration of TEs in the flue gas gradually decreases as the gas moves through the air pollution control devices (APCDs). Only a small amount of TEs is emitted from the stack (Be: 0.039 μg/m3, Cd: 0.019 μg/m3, Cr: 2.229 μg/m3, Ni: 0.350 μg/m3, Pb: 0.194 μg/m3, Sb: 0.017 μg/m3, Se: 0.307 μg/m3, and U: 0.029 μg/m3). The Se concentration in the liquid portion was high and thus significantly contributed to the material balance. The low-temperature economizer-electrost.
A novel miniature inverted-flame burner for the generation of soot nanoparticles

Abstract Lab-scale soot nanoparticle generators are used by the aerosol research community to study the properties of soot over a broad range of particle size distributions, and number and mass concentrations. In this study, a novel miniature inverted-flame burner is presented and its emitted soot particles were characterized. The burner consisted of two co-annular tubes for fuel and co-flow air and the flame was enclosed by the latter. The fuel used was ethylene. A scanning mobility particle sizer (SMPS) and an aerodynamic aerosol classifier (AAC) were used to measure mobility and aerodynamic size distribution of soot particles, respectively. Particle morphology was studied using transmission electron microscopy (TEM). The elemental carbon (EC) and organic carbon (OC) content of the soot were measured using thermal-optical analysis (TOA). The burner produced soot particles with mobility diameter range of 66–270 nm, aerodynamic diameter range of 56–140 nm, and total concentration range of 2 × 105–1 × 107 cm−3. TEM images showed that most soot particles were sub-micron soot aggregates. Some soot superaggregates, typically larger than 2 µm in length, were observed and their abundance increased with ethylene flow rate. TOA showed that the concentration of EC in the generated soot increased with ethylene flow rate, and the soot was observed to have high EC fraction at high ethylene flow rates. The miniature inverted-flame burner was demonstrated to produce soot nanoparticles over a range of concentrations and sizes with high EC content, making it a practical device to study soot nanoparticle properties in different applications. Copyright © 2019 American Association for Aerosol Research
Occupational inequalities in mortality in Korea: an analysis using nationally representative mortality follow-up data from the late 2000s and after

Many Korean and international studies have found higher mortality rates and poorer health conditions among manual workers than among non-manual workers. However, a recent study using unlinked data argued that since the economic crisis in Korea in the late 2000s, the mortality estimates of male Korean non-manual workers have been higher than those of manual workers. Our work using individually linked data from the late 2000s and after aimed to examine mortality inequality by occupational class. We analyzed Korea National Health and Nutrition Examination Survey data that were individually linked to cause-of-death data. Cox regression analysis was used to identify the hazard ratios for mortality by occupational class. Of 11,766 males aged between 35 and 64, 397 died between 2007 and 2018: 142 died from cancer, 68 from cardiovascular disease, 88 from external causes, and 99 from other causes. After controlling for age, the mortality estimates for manual workers were 1.85 times higher than those for upper non-manual workers (p<0.05). We observed no evidence of reversed mortality inequality among occupational classes in Korea since the 2000s; this previously reported finding might have been due to numerator-denominator bias arising from the use of unlinked data.
Beyond Surrogate Modeling: Learning the Local Volatility Via Shape Constraints

We explore the abilities of two machine learning approaches for no-arbitrage interpolation of European vanilla option prices, which jointly yield the corresponding local volatility surface: a finite dimensional Gaussian process (GP) regression approach under no-arbitrage constraints based on prices, and a neural net (NN) approach with penalization of arbitrages based on implied volatilities. We demonstrate the performance of these approaches relative to the SSVI industry standard. The GP approach is proven arbitrage-free, whereas arbitrages are only penalized under the SSVI and NN approaches. The GP approach obtains the best out-of-sample calibration error and provides uncertainty quantification.The NN approach yields a smoother local volatility and a better backtesting performance, as its training criterion incorporates a local volatility regularization term.