Miracle-dz/UniFAR-FTUs huggingface dataset:
Simplicial 2-Complex Convolutional Neural Networks

Recently, neural network architectures have been developed to accommodate when the data has the structure of a graph or, more generally, a hypergraph. While useful, graph structures can be potentially limiting. Hypergraph structures in general do not account for higher order relations between their hyperedges. Simplicial complexes offer a middle ground, with a rich theory to draw on. We develop a convolutional neural network layer on simplicial 2-complexes.
Discovering Multi-Table Functional Dependencies Without Full Join Computation

In this paper, we study the problem of discovering join FDs, i.e., functional dependencies (FDs) that hold on multiple joined tables. We leverage logical inference, selective mining, and sampling and show that we can discover most of the exact join FDs from the single tables participating to the join and avoid the full computation of the join result. We propose algorithms to speed-up the join FD discovery process and mine FDs on the fly only from necessary data partitions. We introduce JEDI (Join dEpendency DIscovery), our solution to discover join FDs without computation of the full join beforehand. Our experiments on a range of real-world and synthetic data demonstrate the benefits of our method over existing FD discovery methods that need to precompute the join results before discovering the FDs. We show that the performance depends on the cardinalities and coverage of the join attribute values: for join operations with low coverage, JEDI with selective mining outperforms the competing methods using the straightforward approach of full join computation by one order of magnitude in terms of runtime and can discover three-quarters of the exact join FDs using mainly logical inference in half of its total execution time on average. For higher join coverage, JEDI with sampling reaches precision of 1 with only 63% of the table input size on average.
Axial vector transition form factors in holographic QCD and their contribution to the muon g-2

Whereas the theoretical results for the dominant contributions to hadronic light-by-light scattering coming from pseudoscalar meson exchange have converged over the past years, the various published estimates of the contribution due to axial vector meson exchange differ wildly. Since holographic AdS/QCD models have proved to provide rather good models of singly and doubly virtual pion transition form factors, which reproduce remarkably well the known low-energy data and also the asymptotic leading-order pQCD behavior, it is of interest to consider their predictions for axial vector transition form factors. Indeed, we find that these reproduce also very well existing data from the L3 experiment for $f_1\to\gamma\gamma^*$. Including the full infinite tower of axial vector mesons of the AdS/QCD models we moreover show that the Melnikov-Vainshtein short-distance constraint can be satisfied, while almost all existing models for hadronic light-by-light scattering fail to incorporate it. The contribution to $g-2$, which is dominated by the first few resonances, turns out to be significantly larger than estimated previously.
A case for robust translation tolerance in humans and CNNs. A commentary on Han et al.

Han et al. (2020) reported a behavioral experiment that assessed the extent to which the human visual system can identify novel images at unseen retinal locations (what the authors call "intrinsic translation invariance") and developed a novel convolutional neural network model (an Eccentricity Dependent Network or ENN) to capture key aspects of the behavioral results. Here we show that their analysis of behavioral data used inappropriate baseline conditions, leading them to underestimate intrinsic translation invariance. When the data are correctly interpreted they show near complete translation tolerance extending to 14° in some conditions, consistent with earlier work (Bowers et al., 2016) and more recent work Blything et al. (in press). We describe a simpler model that provides a better account of translation invariance.
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization

Flow-based models are powerful tools for designing probabilistic models with tractable density. This paper introduces Convex Potential Flows (CP-Flow), a natural and efficient parameterization of invertible models inspired by the optimal transport (OT) theory. CP-Flows are the gradient map of a strongly convex neural potential function. The convexity implies invertibility and allows us to resort to convex optimization to solve the convex conjugate for efficient inversion. To enable maximum likelihood training, we derive a new gradient estimator of the log-determinant of the Jacobian, which involves solving an inverse-Hessian vector product using the conjugate gradient method. The gradient estimator has constant-memory cost, and can be made effectively unbiased by reducing the error tolerance level of the convex optimization routine. Theoretically, we prove that CP-Flows are universal density approximators and are optimal in the OT sense. Our empirical results show that CP-Flow performs competitively on standard benchmarks of density estimation and variational inference.
Spectroscopic studies of microwave plasmas at atmospheric pressure.

Emission spectroscopy has been used to study plasmas generated in a microwave cavity at atmospheric pressure. Plasmas were generated in air, nitrogen and different mixtures of helium with air, nitrogen and argon. The spectral components of the emitted radiation have been identified and their relative distribution have, in some cases, been measured. Electron temperatures and vibrational temperatures of molecules have been calculated assuming local thermal equilibrium, L TE, to hold. The not very accurate results yield an electron temperature of about 3400 K, and a gas temperature of about 5000 K, in the studied plasmas. These temperatures indicate that L TE is not valid. Taking the limited line emission obtained in consideration, a corona-like state of equilibrium for the studied plasmas is suggested.
Better call Surrogates: A hybrid Evolutionary Algorithm for Hyperparameter optimization

In this paper, we propose a surrogate-assisted evolutionary algorithm (EA) for hyperparameter optimization of machine learning (ML) models. The proposed STEADE model initially estimates the objective function landscape using RadialBasis Function interpolation, and then transfers the knowledge to an EA technique called Differential Evolution that is used to evolve new solutions guided by a Bayesian optimization framework. We empirically evaluate our model on the hyperparameter optimization problems as a part of the black box optimization challenge at NeurIPS 2020 and demonstrate the improvement brought about by STEADE over the vanilla EA.
RENATA: REpreseNtation And Training Alteration for Bias Mitigation

We propose a novel method for enforcing AI fairness with respect to protected or sensitive factors. This method uses a dual strategy performing Training And Representation Alteration (RENATA) for mitigation of two of the most prominent causes of AI bias, including: a) the use of representation learning alteration via adversarial independence, to suppress the bias-inducing dependence of the data representation from protected factors; and b) training set alteration via intelligent augmentation, to address bias-causing data imbalance, by using generative models that allow fine control of sensitive factors related to underrepresented populations. When testing our methods on image analytics, experiments demonstrate that RENATA significantly or fully debiases baseline models while outperforming competing debiasing methods, e.g., with (% overall accuracy, % accuracy gap) of (78.75, 0.5) vs. baseline method's (71.75, 10.5) for EyePACS, and (73.71, 11.82) vs. the (69.08, 21.65) baseline for CelebA. As an additional contribution, recognizing certain limitations in current metrics used for assessing debiasing performance, this study proposes novel conjunctive debiasing metrics. Our experiments also demonstrate the ability of these novel metrics in assessing the Pareto efficiency of the proposed methods.
Sublinear classical and quantum algorithms for general matrix games

We investigate sublinear classical and quantum algorithms for matrix games, a fundamental problem in optimization and machine learning, with provable guarantees. Given a matrix, sublinear algorithms for the matrix game were previously known only for two special cases: (1) the maximizing vectors live in the L1-norm unit ball, and (2) the minimizing vectors live in either the L1- or the L2-norm unit ball. We give a sublinear classical algorithm that can interpolate smoothly between these two cases: for any fixed q between 1 and 2, we solve, within some additive error, matrix games where the minimizing vectors are in an Lq-norm unit ball. We also provide a corresponding sublinear quantum algorithm that solves the same task with a quadratic improvement in dimensions of the maximizing and minimizing vectors. Both our classical and quantum algorithms are optimal in the dimension parameters up to poly-logarithmic factors. Finally, we propose sublinear classical and quantum algorithms for the approximate Carathéodory problem and the Lq-margin support vector machines as applications.
Copolymer MCJS as a retarder of the acid–rock reaction speed for the stimulation of deep carbonate reservoirs

The fast reaction rate between hydrochloric acid and carbonates causes the most acid consumption near the wells, and the acid cannot penetrate the deeper places of the carbonate reservoir; this limits the application of acidizing modifications for the reservoir. In this study, we chose acrylamide, 2-acrylamido-2-methyl-1-propane sulfonic acid (AMPS), allyl alcohol polyoxyethylene ether (APEG), and N-dimethyl-N-vinyl nonadecan-1-aminium chloride (DMAAC-18) to synthesize a quadripolymer (MCJS) that could reduce the reaction rate mentioned previously. The molecular structure of MCJS was characterized by Fourier transform infrared and 1H-NMR spectroscopy. The molecular weight and molecular weight distribution of MCJS was determined by gel permeation chromatography. Carbonate rock was analyzed by X-ray diffraction and energy-dispersive X-ray spectroscopy. The retarding properties of the acid mixed with MCJS (MCJS acid) were investigated, and the resulting reaction rate between the acid and carbonate decreased obviously, even at a low viscosity. Scanning electron microscopy and core flood experiments showed that the MCJS could be adsorbed on the carbonate rock surface and form a hydrated film that delayed the reaction. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015, 132, 41471.
Expression, Reinigung und molekulare Charakterisierung des Proteins ETHYLENE INSENSITIVE 2 (EIN2)

Das Phytohormon Ethylen ist in der Pflanze an der Regulation einer Vielzahl physiologischer Prozesse der Pflanzenentwicklung wie an der Kontrolle von Fruchtreife, Blattfall und anderen Senezenzprozessen beteiligt und spielt daher agrarokonomisch eine wichtige Rolle Molekulargenetische Studien in Arabidopsis thaliana haben zu der Entwicklung eines Modells fur die Signaltransduktion von Ethylen gefuhrt, in dem zwar die an der Signalwahrnehmung und Weiterleitung beteiligten Proteine identifiziert werden konnten, doch die molekularen Mechanismen der einzelnen Schritte der Signaltransduktion sind noch weitestgehend ungeklart blieben. Fur die Untersuchungen des zugrunde liegende Mechanismus kann jedoch nicht auf indirekte, genetische Methoden zuruckgegriffen werden, sondern sie erfordern Analysen zu Struktur und Funktion an isolierten Proteinen. Im Rahmen dieser Arbeit wurde ein Reinigungsprotokoll entwickelt, mit dem der putativ membran-extrinsische Bereich des EIN2-Proteins, der ca 63 % des Gesamtproteins ausmacht, in ausreichender Menge fur funktionelle Untersuchungen isoliert werden konnte. Eine erste strukturelle Charakterisierung des EIN2-Fragments wurde durch die Untersuchung der Sekundarstruktur mittels Zirkular Dichroismus (CD) Spektroskopie durchgefuhrt. In der vorliegenden Arbeit ist es erstmals gelungen, wichtige Hinweise auf die Funktion des EIN2 Proteins zu erhalten. In funktionellen Untersuchungen konnte sowohl mikrokalorimetrisch als auch fluoreszenzspektroskopisch die Bindung zweiwertiger Kationen an mindestens zwei verschiedenen Typen von Bindungsstellen nachgewiesen werden und somit ein Zusammenhang mit der postulierten Sensorfunktion des Proteins fur Metallionen hergestellt werden. Durch sequenzbasierte Suche fur Kalziumsbindungsstellen konnten sieben putative EF-hand-Motive in EIN2 479-1294 identifiziert werden. Die experimentell bestimmten Dissoziations-konstanten fur Kalzium und Magnesium unterstutzten einen postulierten Bindungs-mechanismus in EIN2 uber EF Hand-Motive. Ein weiteres Argument fur die Ionenbindung uber dieses Motiv sind die durch Kalziumionen induzierten Konformationsanderungen in a-helikalen Bereichen von EIN2 479-1294.
Metallization of solid iodine in phase I: X-ray diffraction measurements, electrical resistance measurements, and ab initio calculations

Metallization of solid iodine has carefully been investigated using X-ray diffraction (XRD) measurements, electrical resistance measurements, and ab initio calculations based on the density functional theory. The XRD and electrical resistance measurements have clarified that iodine takes the insulator-to-metal transition at 14–16 GPa in the diatomic molecular solid phase. The ab initio calculations have predicted that the electronic band gap decreases monotonically with increasing pressure, and it completely closes at around 11–12 GPa in the molecular phase, which is consistent with the experimental observations. At the metallization, we also experimentally and theoretically found the anomaly in the decrease of lattice constants along with pressurization.
Self-assembled silane monolayers: A step-by-step high speed recipe for high-quality, low energy surfaces

Silanization bases on the adsorption, selfassembly and covalent binding of silane molecules onto surfaces, resulting in a densely packed self-assembled monolayer (SAM). Following standard recipes, however, the quality of the monolayer is often variable and therefore unsatisfactory. The process of self-assembly is highly affected by the chemicals involved in the wet-chemical process, by the ambient parameters during preparation such as humidity or temperature and by possibly present contaminants (or impurities). Here, we present a reliable, efficient, and wet-chemical recipe for the preparation of ultra-smooth, highly ordered alkylterminated silane SAMs on Si wafers.
A Comparative Study of Sequential Hydrogen-methane and Independent Methane Production from Kitchen Wastes

Abstract Analysis of sequential hydrogen-methane and independent methane production were carried out in this study to investigate the optimal bio-energy production from kitchen wastes. The study indicated that production of hydrogen and the sequential methane achieved 75.0 and 287.4 mL/gVS, respectively, during the sequential hydrogen-methane process. Specifically, the sequential methane increased by 34.0% compared to independent methane production. Additionally, the measured concentration of total organic acids increased to 13,599.8 mg/L at the end of hydrogen fermentation, then decreased to 4,284.9 mg/L at the end of the sequential methane process. The major acid component was butyric acid in the sequential methane process as opposed to acetic acid in an independent process. Remarkably, it was found that the major component of extracellular polymeric substances in hydrogen producing sludge was exopolysaccharide, while in both methane producing processes it was exoprotein. The maximum measured concentration of exoprotein and exopolysaccharide reached to 84.3, 36.3 mg/gVS and 63.4, 30.4 mg/gVS, while DNA increased throughout the stages of the two methane processes. These findings may represent a feasible method for high energy achievement from kitchen wastes.
Mathematical Model of Coupled Heat and Mass Transfer in Unsaturated Soils

A systematic study of coupled heat and mass transfer in unsaturated soils under complex boundary conditions wa carried out and a mathematical model of heat and mass transfer in unsaturated soils was established by non-equilibrium thermodynamic theory.The gradient of volumetric moisture ontent,the gradient of emperature, the salt mass concentration and vapor pressure were the primary driving fores influencing the process of heat and mass transfer in unsaturated soils . Based on the thermodynamic analysis and the mass and energy conservation principles,a set of mass and energy equations were develped,The intial and boundary conditions of soil coulumn for on dimension were aslo given out.
The temperature dependence of mass accommodation of sulfur dioxide and hydrogen peroxide on aqueous surfaces

The authors report the laboratory determination of the temperature-dependent mass accommodation coefficients of SO{sub 2} and H{sub 2}O{sub 2} on aqueous surfaces over the range 260-292 K. Mass accommodation kinetics involve fundamental chemical interactions of liquid surfaces about which little is known. Uptake of SO{sub 2} and H{sub 2}O{sub 2} by cloud droplets is believed to be critical to S(IV) oxidation in the troposphere. Our experimental method combines a monodisperse train of droplets (200 {mu}m in diameter) and a low-pressure flow reactor. Uptake rates of trace gases are determined by measuring changes in trace gas number density as a function of exposed liquid surface area. Experiments with systematic variation of water vapor and rare gas partial pressures permit deconvolution of gas diffusion and temperature-dependent mass accommodation. In the case of SO{sub 2}, variation of droplet-gas interactions on millisecond time scales resolved pH-dependent saturation effects at the aqueous surface. Results for SO{sub 2} show {gamma}{sub 273} = 0.11 {plus minus} 0.02 with no significant temperature variation. H{sub 2}O{sub 2} shows a strong temperature dependence consistent with an attractive well depth of at least 26 kJ mol{sup {minus}1} with {gamma}{sub 273} = 0.18 {plus minus} 0.02. These results are discussed in termsmore » of the different aqueous solubilities of SO{sub 2} and H{sub 2}O{sub 2}. « less
Effect of gamma irradiation, packaging and storage on the nutrients and shelf life of palm dates.

Influence of gamma irradiation and colored polyethylene packaging on the selected parameters, namely moisture, proteins, fiber, fats and shelf life of palm date (Phoenix dactylifera L.) was studied. The date samples were irradiated with 20, 50, 100, 200 and 300 krads, respectively. The treated and whole samples were packed in blue, green, yellow, black and white polyethylene bags. The moisture contents of date were very close in all packed and treated date samples with irregular changes. In proteins, the decrease is higher in the first 3 months, whereas in the last 3 months no prominent difference was noticed. Maximum protein decrease was recorded for control samples in the blue packaging, i.e., the decrease is from 2.32 to 0.1%. Minimum decrease (2.32–1.4%) was recorded for samples in white and yellow packaging, at doses of 300 and 200 krads, respectively. The fiber contents of date samples irradiated with 20, 50, 100, 200 and 300 krads and packed in white packaging decrease as 2.33, 2.37, 2.36, 2.34 and 2.31%, respectively. The fiber levels decrease gradually in all samples in irregular pattern. The results of fat contents clearly indicate that packaging and radiation doses up to 300 krads do not affect the contents. PRACTICAL APPLICATIONS Conservation and preservation of food is a prerequisite for food security. It provides economic stability and self-reliance to a nation. Date palms (Pheonix dactylera L.) are usually stored for longer periods and thus postharvest contamination of dates is common. The spoilage of fresh/dried dates by insects, bacteria, color deterioration and chemical changes during storage is a serious problem in hot, humid tropical conditions like in that Pakistan. Because of the ban on chemical fumigants, many countries have had to either limit or stop the export of some agricultural commodities. This resulted in economic loss, further balance-of-trade deficits and curtailment of consumer food choices. In this situation, food irradiation offers a significant alternative method for reducing storage losses and meeting plant quarantine requirements. The study conducted was of prime importance and great economic value, especially to the forthcoming regulations and standards of the World Trade Organization, involving pest-free quality-export commodities.
A Simple High Performance Liquid Chromatography/Ionspray Tandem Mass Spectrometry Method for the Direct Determination of Paraquat and Diquat in Water

A method has been developed for the direct determination of paraquat and diquat in water samples. No sample preparation was required and analysis was done using high performance liquid chromatography coupled with ionspray tandem mass spectrometry. Heptafluorobutyric acid was used as the ion-pair agent. Further improvements in this method included the incorporation of an internal standard (caffeine). Using this method, detection limits of 5 and 1 μg/L were obtained for paraquat and diquat respectively. Recoveries were consistently 10% over the concentration range 5–100 μg/L. To our knowledge, this method is the first application of ionspray tandem mass spectrometry, and the first to use heptafluorobutyric acid as an ion-pair reagent, for the analysis of paraquat and diquat. © 1997 John Wiley & Sons, Ltd.
Mechanistic studies in the chemistry of urea. Part 8. Reactions of urea, 1-methylurea, and 1,3-dimethylurea with some acyloins and butane-2,3-dione (diacetyl) in acid solution

Urea and 1-methylurea react with both aromatic and aliphatic acyloins to form 4-imidazolin-2-ones but, under the same reaction conditions, 1,3-dimethylurea does not react. However, 1,3-dimethylurea does react with diacetyl to form 4,4′-methylenebis-(1,3,5-trimethyl-4-imidazolin-2-one)(4a). The carbon atom lost in the formation of (4a) is eliminated as formaldehyde. We propose a reaction mechanism which involves formation of an oxetan ring. With 1-methylurea and urea the main products of reaction with diacetyl are the bicyclic compounds (6a–c). However, it is possible that reactions analogous to that leading to the formation of (4a) also occur and that the carbonium ion (5c) is the coloured species formed in the well known colorimetric procedure for the determination of urea concentrations in biological liquids.
Blood Rheology, Haemostatic Function and Peripheral Blood Flow in Diabetes Mellitus: A Study of the Effects of Improved Blood Glucose Control and Treatment With Biosynthetic Human Insulin

The aims of the studies were to examine blood rheology, haemostatic factors and peripheral blood flow in diabetes mellitus in relation to treatment and the presence of vascular damage. First, studies of the specificity of positive pressure filtration of dilute erythrocyte suspensions as a measure of erythrocyte deformability were made. Second, the effects of improved blood glucose control (achieved by outpatient management) on whole blood viscosity, haemostatic factors, peripheral blood flow and peripheral nerve function was examined. Third, a double-blind crossover study of the effects of treatment with biosynthetic human insulin (BHI) and purified porcine insulin (PPI) on blood rheology, haemostatic factors and peripheral blood flow was carried out.