Miracle-dz/UniFAR-FTUs huggingface dataset:
Atomic Transition Probabilities for Forbidden Lines of the Iron Group Elements: (A Critical Data Compilation for Selected Lines)

Atomic transition probabilities for about 750 forbidden spectral lines for elements of the iron group, specifically V, Cr, Mn, Fe, Co, and Ni, have been critically evaluated and compiled using all available literature sources. The selection of the spectra and elements has been made primarily according to their astrophysical importance. The data are presented in separate tables for each element and stage of ionization, and for each ion the data are arranged according to multiplets. For each line within a multiplet the transition probability for spontaneous emission is listed along with the standard spectroscopic designation, the wavelength, the statistical weights, and the energy levels of the upper and lower states. In addition, the estimated accuracy and the source are indicated. In short introductions which precede the individual tables for the ions the main justifications for the choice of the adopted data and for the accuracy rating are discussed. A general introduction contains a detailed discussion .
Conditional Independence Structures Over Four Discrete Random Variables Revisited: Conditional Ingleton Inequalities

The paper deals with linear information inequalities valid for entropy functions induced by discrete random variables. Specifically, the so-called conditional Ingleton inequalities are in the center of interest: these are valid under conditional independence assumptions on the inducing random variables. We discuss five inequalities of this particular type, four of which has appeared earlier in the literature. Besides the proof of the new fifth inequality, simpler proofs of (some of) former inequalities are presented. These five information inequalities are used to characterize all conditional independence structures induced by four discrete random variables.
Growth and fermentation kinetics of a mixed culture of Saccharomyces cerevisiae var. bayanus and Williopsis saturnus var. saturnus at different ratios in longan juice (Dimocarpus longan Lour.)

Summary Cofermentation of longan juice by mixed cultures of Saccharomyces cerevisiae var. bayanus EC-1118 and Williopsis saturnus var. saturnus CBS254 at two inoculation ratios (EC-1118:CBS254 = 1:100 and 1:1000 cfu mL−1) was performed to ascertain their impact on longan wine aroma compound formation. The results showed improved aroma compound profiles in the longan wine fermented with mixed yeasts in comparison with the longan wines fermented with single yeasts in terms of increased production of acetate esters, fatty acid ethyl esters, alcohols and carboxylic acids. The impact of cofermentation on longan wine aroma formation was affected by the ratio of S. cerevisiae EC-1118 to W. saturnus CBS254 with 1:100 cfu mL−1 being more effective. This research suggests that the inoculation ratio of mixed yeasts may be used as an effective means of manipulating longan wine aroma.
Molecular dynamics simulation of dynamic response of beryllium.

The response of beryllium to dynamic loading has been extensively studied, both experimentally and theoretically, due to its importance in several technological areas. We use a MEAM empirical potential to examine the melt transition. MD simulations of equilibrated two-phase systems were used to calculate the HCP melting curve up to 300 GPa. This was found to agree well with previous ab initio calculations. The Hugoniostat method was used to examine dynamic compression along the two principal orientations of the HCP crystal. In both directions, the melting transition occurred at 230 GPa and 5000 K, consistent with the equilibrium melting curve. Direct NEMD simulations of uniaxial compression show a transition to an amorphous material at shocked states that lie below the equilibrium melt curve.
Identifying challenges towards practical quantum advantage through resource estimation: the measurement roadblock in the variational quantum eigensolver

Recent advances in Noisy Intermediate-Scale Quantum (NISQ) devices have brought much attention to the potential of the Variational Quantum Eigensolver (VQE) and related techniques to provide practical quantum advantage in computational chemistry. However, it is not yet clear whether such algorithms, even in the absence of device error, could achieve quantum advantage for systems of practical interest and how large such an advantage might be. To address these questions, we have performed an exhaustive set of benchmarks to estimate number of qubits and number of measurements required to compute the combustion energies of small organic molecules to within chemical accuracy using VQE as well as state-of-the-art classical algorithms. We consider several key modifications to VQE, including the use of Frozen Natural Orbitals, various Hamiltonian decomposition techniques, and the application of fermionic marginal constraints. Our results indicate that although Frozen Natural Orbitals and low-rank factorizations of the Hamiltonian significantly reduce the qubit and measurement requirements, these techniques are not sufficient to achieve practical quantum computational advantage in the calculation of organic molecule combustion energies. This suggests that new approaches to estimation leveraging quantum coherence, such as Bayesian amplitude estimation [arXiv:2006.09350, arXiv:2006.09349], may be required in order to achieve practical quantum advantage with near-term devices. Our work also highlights the crucial role that resource and performance assessments of quantum algorithms play in identifying quantum advantage and guiding quantum algorithm design.
The effects of irrigation, nitrogen fertilizer and grain size on Hagberg falling number, specific weight and blackpoint of winter wheat

The effects of irrigation and nitrogen (N) fertilizer on Hagberg falling number (HFN), specific weight (SW) and blackpoint (BP) of winter wheat (Triticum aestivum L) were investigated. Mains water (+50 and +100 mm month(-1), containing 44 mg NO3- litre(-1) and 28 mg SO42- litre(-1)) was applied with trickle irrigation during winter (17 January-17 March), spring (21 March-20 May) or summer (24 May-23 July). In 1999/2000 these treatments were factorially combined with three N levels (0, 200, 400 kg N ha(-1)), applied to cv Hereward. In 2000/01 the 400 kg N ha(-1) treatment was replaced with cv Malacca given 200 kg N ha(-1). Irrigation increased grain yield, mostly by increasing grain numbers when applied in winter and spring, and by increasing mean grain weight when applied in summer. Nitrogen increased grain numbers and SW, and reduced BP in both years. Nitrogen increased HFN in 1999/2000 and reduced HFN in 2000/01. Effects of irrigation on HFN, SW and BP were smaller and inconsistent over year and nitrogen level. Irrigation interacted with N on mean grain weight: negatively for winter and spring irrigation, and positively for summer irrigation. Ten variables derived from digital image analysis of harvested grain were included with mean grain weight in a principal components analysis. The first principal component ('size') was negatively related to HFN (in two years) and BP (one year), and positively related to SW (two years). Treatment effects on dimensions of harvested grain could not explain all of the effects on HFN, BP and SW but the results were consistent with the hypothesis that water and nutrient availability, even when they were affected early in the season, could influence final grain quality if they influenced grain numbers and size. (C) 2004 Society of Chemical Industry
Improved Convergence Rates for Non-Convex Federated Learning with Compression

Federated learning is a new distributed learning paradigm that enables efficient training of emerging large-scale machine learning models. In this paper, we consider federated learning on non-convex objectives with compressed communication from the clients to the central server. We propose a novel first-order algorithm (\texttt{FedSTEPH2}) that employs compressed communication and achieves the optimal iteration complexity of $\mathcal{O}(1/\epsilon^{1.5})$ to reach an $\epsilon$-stationary point (i.e. $\mathbb{E}[\|\nabla f(\bm{x})\|^2] \leq \epsilon$) on smooth non-convex objectives. The proposed scheme is the first algorithm that attains the aforementioned optimal complexity with compressed communication and without using full client gradients at each communication round. The key idea of \texttt{FedSTEPH2} that enables attaining this optimal complexity is applying judicious momentum terms both in the local client updates and the global server update. As a prequel to \texttt{FedSTEPH2}, we propose \texttt{FedSTEPH} which involves a momentum term only in the local client updates. We establish that \texttt{FedSTEPH} enjoys improved convergence rates under various non-convex settings (such as the Polyak-\L{}ojasiewicz condition) and with fewer assumptions than prior work.
Behavior of Silica-Supported Manganese Oxides in Hydrometallurgical Separations

Abstract The properties of nanoporous manganese oxides for metal uptake from hydrometallurgical solutions were studied. Layer-structured OL-1 and tunnel-structured OMS-1 were synthesized by means of a hydrothermal route and then supported on silica. Competitive uptake of metals and acid was studied using equilibrium, batch kinetic, and fixed-bed measurements. The experimental data were correlated with a dynamic model, which also accounts for the dissolution of the framework manganese. Results show that silica–supported OMS materials can be utilized to separate copper from nickel and cadmium. Behavior of the composites can be explained reasonably well with the presented model and the parameters estimated from the data of the unsupported oxides.
Quantification and characterization of anthocyanins in Balaton Tart cherries

The anthocyanin contents of Balaton and Montmorency cherries were compared. The results indicate that both cherries contain identical anthocyanins. However, Balaton contains approximately six times more anthocyanins than does Montmorency. Also, hydrolysis of the total anthocyanins and subsequent gas chromatographic (GC) and nuclear magnetic resonance (NMR) experiments with the resulting products indicated that both varieties contain only one aglycon cyanidin. This observation contrasts with existing reports of the presence of peonidin glycosides in Montmorency cherry. Results of the present study suggest that the anthocyanins in Balaton and Montmorency cherries are anthocyanin 1 [3-cyanidin 2‘‘-O-β-d-glucopyranosyl-6‘‘-O-α-l-rhamnopyranosyl-β-d-glucopyranoside], anthocyanin 2 [3-cyanidin 6‘‘-O-α-l-rhamnopyranosyl-β-d-glucopyranoside], and anthocyanin 3 [3-cyanidin O-β-d-glucopyranoside]. Keywords: Prunus cerasus; fruit; Balaton; Montmorency; anthocyanin; cyanidin; cyanidin glucoside; quantification and ch.
Combining Machine Learning and Human Experts to Predict Match Outcomes in Football: A Baseline Model

In this paper, we present a new application-focused benchmark dataset and results from a set of baseline Natural Language Processing and Machine Learning models for prediction of match outcomes for games of football (soccer). By doing so we give a baseline for the prediction accuracy that can be achieved exploiting both statistical match data and contextual articles from human sports journalists. Our dataset is focuses on a representative time-period over 6 seasons of the English Premier League, and includes newspaper match previews from The Guardian. The models presented in this paper achieve an accuracy of 63.18% showing a 6.9% boost on the traditional statistical methods.
Analyzing Finite Neural Networks: Can We Trust Neural Tangent Kernel Theory?

Neural Tangent Kernel (NTK) theory is widely used to study the dynamics of infinitely-wide deep neural networks (DNNs) under gradient descent. But do the results for infinitely-wide networks give us hints about the behaviour of real finite-width ones? In this paper we study empirically when NTK theory is valid in practice for fully-connected ReLu and sigmoid networks. We find out that whether a network is in the NTK regime depends on the hyperparameters of random initialization and network's depth. In particular, NTK theory does not explain behaviour of sufficiently deep networks initialized so that their gradients explode: the kernel is random at initialization and changes significantly during training, contrary to NTK theory. On the other hand, in case of vanishing gradients DNNs are in the NTK regime but become untrainable rapidly with depth. We also describe a framework to study generalization properties of DNNs by means of NTK theory and discuss its limits.
Dynamic analysis of a microbial process: A systems engineering approach

A general mathematical model of the chemostat system is developed in order to define an experimental program of dynamic testing. A glucose‐limited culture ofSaccharomyces cerevisiae was grown in a chemostat using chemically defined medium. The chemostat was perturbed from an initial steady state by changes in input glucose concentration, dilution rate, pH, and temperature. Dynamic responses of cell mass, glucose, cell number, RNA, and protein concentrations were measured. A number of simulation techniques were used in developing a dynamic mathematical model and in comparing the developed model with experimental data as well as the Monod model. The resulting model was found to be quantitatively accurate and superior to the Monod model. The developed model was interpreted in the light of cell physiology. Adjustment of intracellular RNA fraction was found to be rate limiting in acceleration of cell specific growth rate.
Comparison of Atom Representations in Graph Neural Networks for Molecular Property Prediction

Graph neural networks have recently become a standard method for analysing chemical compounds. In the field of molecular property prediction, the emphasis is now put on designing new model architectures, and the importance of atom featurisation is oftentimes belittled. When contrasting two graph neural networks, the use of different atom features possibly leads to the incorrect attribution of the results to the network architecture. To provide a better understanding of this issue, we compare multiple atom representations for graph models and evaluate them on the prediction of free energy, solubility, and metabolic stability. To the best of our knowledge, this is the first methodological study that focuses on the relevance of atom representation to the predictive performance of graph neural networks.
Studies on physical properties of red and black soil pedons in Kavalur-1 micro-watershed, Karnataka

The physical properties of soil pedons of Kavalur-1 micro-watershed of northern dry zone (Zone -3) of Karnataka were investigated during 2016-17 for evaluation of soil resources for optimizing their use and enhancing the productivity of the watershed. The results indicated that Kavalur-1 micro-watershed has both red and black soils, though the former is dominant. The climate is semi-arid with a mean annual average rainfall of 572 mm. A detailed soil survey was conducted in Kavalur-1 micro-watershed using toposheets with 1:50,000 scale. Eighteen soil pedons were characterized in Kavalur-1 micro-watershed and studied for physical properties. Soil texture varied from sandy clay loam (scl) to clay (c). The average bulk density did not vary much between red and black soil pedons. In general, the bulk density was less in the surface horizon and increased with depth. The average maximum water holding capacity of red soil pedons was considerably lower (38.0%) than that of black soil pedons (45.7%). The maximum water holding capacity increased downward upto certain depth and further decreased in lower horizons, especially BC horizon. Special features like strong effervescence with dil. HCl was observed in pedon 3, 5 and 12. Slickensides and pressure faces were observed in pedon 9.
Co‐incorporation of biodegradable wastes with crop residues to reduce nitrate pollution of groundwater and decrease waste disposal to landfill

Return of high nitrogen (N) content crop residues to soil, particularly in autumn, can result in environmental pollution resulting from gaseous and leaching losses of N. The EU Landfill Directive will require significant reductions in the amounts of biodegradable materials going to landfill. A field experiment was set up to examine the potential of using biodegradable waste materials to manipulate losses of N from high N crop residues in the soil. Leafy residues of sugar beet were co‐incorporated into soil with materials of varying C:N ratios, including molasses, compactor waste, paper waste, green waste compost and cereal straw. The amendment materials were each incorporated to provide approximately 3.7 t C per hectare. The most effective material for reducing nitrous oxide (N2O) production and leaching loss of NO3− was compactor waste, which is the final product from the recycling of cardboard. Adding molasses increased N2O and NO3− leaching losses. Six months following incorporation of residues, the double rate application of compactor waste decreased soil mineral N by 36 kg N per hectare, and the molasses increased soil mineral N by 47 kg N per hectare. Compactor waste reduced spring barley grain yield by 73% in the first of years following incorporation, with smaller losses at the second harvest. At the first harvest, molasses and paper waste increased yields of spring barley by 20 and 10% compared with sugar beet residues alone, and the enhanced yield persisted to the second harvest. The amounts of soil mineral N in the spring and subsequent yields of a first cereal crop were significantly correlated to the lignin and cellulose contents of the amendment materials. Yield was reduced by 0.3–0.4 t/ha for every 100 mg/g increase in cellulose or lignin content. In a second year, cereal yield was still reduced and related to the cellulose content of the amendment materials but with one quarter of the effect. Additional fertilizer applied to this second crop did not relieve this effect. Although amendment materials were promising as tools to reduce N losses, further work is needed to reduce the negative effects on subsequent crops which was not removed by applying 60 kg/ha of fertilizer N.
Crescimento e trocas gasosas de plantas de feijão-caupi sob irrigação salina e doses de potássio

A intensidade do estresse causado pela salinidade nas culturas ira depender, principalmente, do nivel de tolerância da especie ou cultivar e das estrategias de manejo utilizadas. Dessa forma, objetivou-se com este trabalho avaliar o crescimento e as respostas fisiologicas de duas cultivares de feijao-caupi, irrigadas com agua salina e submetidas a diferentes niveis de potassio, em condicoes de ambiente protegido. Foram utilizadas sementes das cultivares CE 790 e CE 104, as quais foram submetidas a niveis crescentes de salinidade, utilizando-se agua de irrigacao com condutividade eletrica (CEa) de 0,8; 2,2; 3,6 e 5,0 dS m-1 e doses crescentes de potassio (K) na forma de KCl (0,5; 1,0; 2,0 e 4,0 g por vaso KCl). Aos 47 e aos 55 dias apos o plantio (DAP) foram realizadas leituras das trocas gasosas foliares e de crescimento das plantas (comprimento da haste principal, diâmetro do caule e materia seca total), respectivamente. O aumento da salinidade da agua de irrigacao reduziu o comprimento da haste principal, diâmetro do caule e materia seca total, em ambas as cultivares. As maiores doses de potassio em conjunto com a salinidade proporcionaram efeito depressivo no crescimento da haste principal e na condutância estomatica, em comparacao ao efeito isolado da salinidade, sendo um indicativo da intensificacao dos efeitos osmoticos. A existencia de interacoes entre salinidade e potassio e um indicativo de que a dose otima desse nutriente depende da salinidade na zona radicular das plantas, sendo uma informacao importante para o manejo de cultivos em ambientes salinos.
Conformational landscapes of aromatic amino acids in the gas phase : infrared and ultraviolet ion dip spectroscopy of tryptophan

The conformational structures of tryptophan, isolated in the gas phase, have been assigned by combining the results of ultraviolet hole-burning and infrared ion dip spectroscopy with the predictions of ab initio calculations conducted at the MP2/6-311 + G(d,p)//B3LYP/6-31 + G(d) levels of theory. As in phenylalanine, the most strongly populated, and lowest energy conformer presents a folded alanyl side chain that is stabilised by a ‘daisy chain’ of hydrogen-bonded interactions. These link the acidic proton, the amino group and the indole ring. There is a further interaction between the carbonyl oxygen and the neighbouring CH group on the pyrrole ring. A quantitative evaluation of the dipole–dipole interactions between the alanyl side chain and the indole ring in the 1La and 1Lb electronic states does not support the suggestion of electronic state mixing. In particular it casts doubt on the assignment of the fluorescence of the most stable, ‘special’ conformer to emission from the 1La state.
Resistance degradation in early stage of electromigration of Al(Cu) metal lines

Resistance degradation in the early stage of electro migration of Al(Cu) metal lines has been investigated by using high resolution resistance measurement. The resistance variation due to Cu diffusion along the line was separated form that due to the thermal stress in the electro migration test. It was found that Cu diffusion along the line strongly depends on the metal line structure. In a wide line with polycrystalline structure, the resistance drop due to Cu diffusion is linearly increased with the test time. However, as the linewidth is reduced and the line becomes bamboo structure, most of resistance drop is ascribed to the thermal stress and Cu diffusion along the line is almost negligible. This finding indicates that the role of Cu in the electro migration reliability strongly depends on the line structure, and previous theory on the role of Cu in improvement of electro migration reliability can not simply apply to the metal line with bamboo structure.
Cation Distribution and g Factors of Certain Spinels Containing Ni++, Mn++, Co++, Al+++, Ga+++, and Fe+++

X‐ray measurements on NiOAl2O3, MnOAl2O3, and CoOAl2O3 show that the Ni spinel is almost completely inverted, the Mn partially so, and the Co compound almost completely normal. This information combined with the magnetic susceptibility vs temperature data yields a g‐value of approximately 4.0 for both tetrahedrally coordinated Ni++ and for octahedrally coordinated Co++. X‐ray measurements indicate that the Ni++ ion also prefers the octahedral site in NiOGa2O3, NiOFe1.00Al1. 00O3, and NiOFe0.25Al1. 75O3.
Effect of cultvars and potassium levels on content and uptake of nutrients, yield and quality of Bt. cotton

A field experiment was conducted at the Instrucional Farm, College of Agriculture, Junagadh Agricultural University, Junagadh on "Effect of cultvars and potassium levels on content and uptake of nutrients, yield and and quality of Bt. Cotton". The experiment consisting of 15 treatment combinations with five Bt cotton cultivars viz., Ankur-165, Vikram-5, Shakti-7, Rashi-2 and Mico-162 and three levels of K2O(0, 80 and 120 kg ha). The results revealed that the cultivar V4(Rashi-2) recorded significantly the highest dry matter yield, lint yield, seed cotton yield, total cotton yield, higher balls per plant, ball weight, as well as the higher value of micronair, stepple length and 2.5% span length. The application of potash @ 120 kg ha gave significantly higher dry matter, lint yield, seed cotton yield, stalk yield and total cotton yield. The quality parameters viz., micronair, stepple length, span length, oil content and ginning percentage were also recorded higher with cultivar Vikram-5. The concentration and uptake of K were recorded higher with dry matter, stalk and seed cotton were recorded higher under application of K2O @ 120 kg ha Similarly, the application of K2O @ 120 kg ha registered significantly higher uptake of N, P and K by seed cotton.