Machine Learning Algorithm to Predict Acidemia Using Electronic Fetal Monitoring Recording Parameters

Background: Electronic fetal monitoring (EFM) is the universal method for the surveillance of fetal well-being in intrapartum. Our objective was to predict acidemia from fetal heart signal features using machine learning algorithms. Methods: A case–control 1:2 study was carried out compromising 378 infants, born in the Miguel Servet University Hospital, Spain. Neonatal acidemia was defined as pH < 7.10. Using EFM recording logistic regression, random forest and neural networks models were built to predict acidemia. Validation of models was performed by means of discrimination, calibration, and clinical utility. Results: Best performance was attained using a random forest model built with 100 trees. The discrimination ability was good, with an area under the Receiver Operating Characteristic curve (AUC) of 0.865. The calibration showed a slight overestimation of acidemia occurrence for probabilities above 0.4. The clinical utility showed that for 33% cutoff point, missing 5% of acidotic cases, 46% of unnecessary cesarean sections could be prevented. Logistic regression and neural networks showed similar discrimination ability but with worse calibration and clinical utility. Conclusions: The combination of the variables extracted from EFM recording provided a predictive model of acidemia that showed good accuracy and provides a practical tool to prevent unnecessary cesarean sections.     

Self-similar vortex reconnection

As shown by Crow in 1970, the evolution of two almost parallel vortex filaments with opposite circulation exhibits a long-wave instability. Ultimately, the symmetric mode increases its amplitude reconnecting both filaments and ending into the formation of an almost periodic structure of vortex rings. This is a universal process, which appears in a wide range of scales: from the vortex trails behind an airplane to a microscopic scale of superfluids and Bose–Einstein condensates. In this paper, I will focus on the vortex reconnection for the latter case by employing Gross–Pitaevskii theory. Essentially, I focus on the well-known laws of interaction and motion of vortex filaments. By means of numerical simulations, as well as theoretically, I show that a self-similar finite-time dynamics manifests near the reconnection time. A self-similar profile is selected showing excellent agreement with numerical simulations.     

Simulation of Organic Liquid Product Deoxygenation through Multistage Countercurrent Absorber/Stripping Using CO2 as Solvent with Aspen-HYSYS: Process Modeling and Simulation

In this work, the deoxygenation of organic liquid products (OLP) obtained through the thermal catalytic cracking of palm oil at 450 °C, 1.0 atmosphere, with 10% (wt.) Na₂CO₃ as a catalyst, in multistage countercurrent absorber columns using supercritical carbon dioxide (SC-CO₂) as a solvent, with an Aspen-HYSYS process simulator, was systematically investigated. In a previous study, the thermodynamic data basis and EOS modeling necessary to simulate the deoxygenation of OLP was presented. This work addresses a new flowsheet, consisting of 03 absorber columns, 10 expansions valves, 10 flash drums, 08 heat exchanges, 01 pressure pump, and 02 make-ups of CO₂, aiming to improve the deacidification of OLP. The simulation was performed at 333 K, 140 bar, and (S/F) = 17; 350 K, 140 bar, and (S/F) = 38; 333 K, 140 bar, and (S/F) = 25. The simulation shows that 81.49% of OLP could be recovered and that the concentrations of hydrocarbons in the extracts of absorber-01 and absorber-02 were 96.95 and 92.78% (wt.) on a solvent-free basis, while the bottom stream of absorber-03 was enriched in oxygenated compounds with concentrations of up to 32.66% (wt.) on a solvent-free basis, showing that the organic liquid products (OLP) were deacidified and SC-CO₂ was able to deacidify the OLP and obtain fractions with lower olefin contents. The best deacidifying condition was obtained at 333 K, 140 bar, and (S/F) = 17.     

Rhodium-catalyzed intermolecular hydroacylation of 1-alkynes: Effect of phosphines and MK-10 on the reaction selectivity

The use of bulky ligands in the rhodium-catalyzed reaction of aldehydes 7 (R¹ = Ph) and 18 with 1-octyne increased the selectivity for ketones 13 and 20, to the detriment of ketones 12 and 19. Bulky phosphines reduced the hydroacylation reaction rate, leading to competition from the addition of the benzoic acid co-catalyst to the alkynes. This competing reaction can be suppressed by using the clay Montmorillonite K 10 (MK-10) as the co-catalyst instead of benzoic acid.     

Multi‐responses Methodology Applied in the Electroanalytical Determination of Hair Dye by Using Printed Carbon Electrode Modified with Graphene

This paper describes a rapid and sensitive method for determination of the hair dye Basic Blue 41 in wastewater samples using screen‐printed carbon electrodes modified with graphene (SPCE/Gr). The method is based on the reversible reduction of azo groups of the dye at potential of ?0.23 V/?0.26 V, where both the anodic and cathodic currents increased 1,300 % when compared to screen‐printed carbon (SPCE) and glassy carbon electrodes (GCE). The optimization of a square wave voltammetric method was performed by means of 2³ factorial design, Doehlert matrix and multi‐response assays, and the best parameters were: frequency (54.8 Hz), step potential (6 mV), pulse amplitude (43.7 mV) and pH 4.5. The analytical curve was constructed from 3.00×10^?8 to 2.01×10^?6 mol L^?1, with detection and quantification limits of 5.00×10^?9 and 1.70×10^?8 mol L^?1, respectively. The repeatability of the method evaluated for 10 consecutive measurements at concentrations of 1.70×10^?7 mol L^?1 and 1.70×10^?6 mol L^?1, showed relative standard deviation of 3.56 and 0.57 %, respectively. The sensor based in SPCE/Gr was successfully applied in wastewater samples collected from a drinking water treatment plant and validated by comparison with HPLC‐DAD method with good accuracy.     

Chemoselective Preparation of New Families of Phenolic-Organoselenium Hybrids—A Biological Assessment

Being aware of the enormous biological potential of organoselenium and polyphenolic compounds, we have accomplished the preparation of novel hybrids, combining both pharmacophores in order to obtain new antioxidant and antiproliferative agents. Three different families have been accessed in a straightforward and chemoselective fashion: carbohydrate-containing N-acylisoselenoureas, N-arylisoselenocarbamates and N-arylselenocarbamates. The nature of the organoselenium framework, number and position of phenolic hydroxyl groups and substituents on the aromatic scaffolds afforded valuable structure–activity relationships for the biological assays accomplished: antioxidant properties (antiradical activity, DNA-protective effects, Glutathione peroxidase (GPx) mimicry) and antiproliferative activity. Regarding the antioxidant activity, selenocarbamates 24–27 behaved as excellent mimetics of GPx in the substoichiometric elimination of H₂O₂ as a Reactive Oxygen Species (ROS) model. Isoselenocarbamates and particularly their selenocarbamate isomers exhibited potent antiproliferative activity against non-small lung cell lines (A549, SW1573) in the low micromolar range, with similar potency to that shown by the chemotherapeutic agent cisplatin (cis-diaminodichloroplatin, CDDP) and occasionally with more potency than etoposide (VP-16).     

Generalized limits for single-parameter quantum estimation

We develop generalized bounds for quantum single-parameter estimation problems for which the coupling to the parameter is described by intrinsic multisystem interactions. For a Hamiltonian with k-system parameter-sensitive terms, the quantum limit scales as 1/Nk, where N is the number of systems. These quantum limits remain valid when the Hamiltonian is augmented by any parameter-independent interaction among the systems and when adaptive measurements via parameter-independent coupling to ancillas are allowed.     

Numerical simulation of two-dimensional Bingham fluid flow by semismooth Newton methods

This paper is devoted to the numerical simulation of two-dimensional stationary Bingham fluid flow by semismooth Newton methods. We analyze the modeling variational inequality of the second kind, considering both Dirichlet and stress-free boundary conditions. A family of Tikhonov regularized problems is proposed and the convergence of the regularized solutions to the original one is verified. By using Fenchel’s duality, optimality systems which characterize the original and regularized solutions are obtained. The regularized optimality systems are discretized using a finite element method with (cross-grid P₁)-Q₀ elements for the velocity and pressure, respectively. A semismooth Newton algorithm is proposed in order to solve the discretized optimality systems. Using an additional relaxation, a descent direction is constructed from each semismooth Newton iteration. Local superlinear convergence of the method is also proved. Finally, we perform numerical experiments in order to investigate the behavior and efficiency of the method.     

Cyclic Codes over the Integers Modulop

The purpose of this paper is twofold. First, we generalize the results of Pless and Qian and those of Pless, Solé, and Qian for cyclic ₄-codes to cyclic _p^m-codes. Second, we establish connections between this new development and the results on cyclic _p^m-codes obtained by Calderbank and Sloane. We produce generators for the cyclic _p^m-codes which are analogs to those for cyclic ₄-codes. We show that these may be used to produce a single generator for such codes. In particular, this proves that the ringR_n= _p^m[x]/(xⁿ− 1) is principal, a result that had been previously announced with an incorrect proof. Generators for dual codes of cyclic _p^m-codes are produced from the generators of the corresponding cyclic _p^m-codes. In addition, we also obtain generators for the cyclicp^m-ary codes induced from the idempotent generators for cyclicp-ary codes.     

Quantum mechanical modeling of Zn-based spinel oxides: Assessing the structural,vibrational, and electronic properties

The structural, electronic, and vibrational properties of two leading representatives of the Zn-based spinel oxides class, normal ZnX₂O₄ (X = Al, Ga, In) and inverse Zn₂MO₄ (M = Si, Ge, Sn) crystals, were investigated. In particular, density functional theory (DFT) was combined with different exchange-correlation functionals: B3LYP, HSE06, PBE0, and PBESol. Our calculations showed good agreement with the available experimental data, showing a mean percentage error close to 3% for structural parameters. For the electronic structure, the obtained HSE06 band-gap values overcome previous theoretical results, exhibiting a mean percentage error smaller than 10.0%. In particular, the vibrational properties identify the significant differences between normal and inverse spinel configurations, offering compelling evidence of a structure-property relationship for the investigated materials. Therefore, the combined results confirm that the range-separated HSE06 hybrid functional performs the best in spinel oxides. Despite some points that cannot be directly compared to experimental results, we expect that future experimental work can confirm our predictions, thus opening a new avenue for understanding the structural, electronic, and vibrational properties in spinel oxides.