Multiple factor design for reactive mixture selection for use in reactive walls in mine drainage treatment.

Sulfate-reducing reactive walls installed in situ in the path of acid mine drainage contaminated groundwater, present a promising passive treatment technology. However, a rigorous and methodical selection of the most appropriate reactive mixture composition still needs to be investigated. The aim of this study was the selection of the most reactive medium using a multiple factor design and the modeling of the sulfate-reduction rate. Reactivity of 17 mixtures was assessed in batch reactors (in duplicates) using a synthetic AMD. Results indicate that within 41 days, sulfate concentrations decreased from initial concentrations of 2,000-3,200 mg/l to final concentrations of <90 mg/l. Metal removal efficiencies ranged between 51-84% for Ni and 73-93% for Zn. Generated sulfate-reduction rate predictive models which had very satisfactory parameters (R2 = 0.86, F = 62.38 (p-level < 10(-13)) and R2 = 0.90. F = 62.30 (p-level < 10(-13))) identified poultry manure and two other carbon sources as the critical variables for sulfate-reduction rate.     

Novel (Phenothiazinyl)Vinyl-Pyridinium Dyes and Their Potential Applications as Cellular Staining Agents

We report here the synthesis and structural characterization of novel cationic (phenothiazinyl)vinyl-pyridinium (PVP) dyes, together with optical (absorption/emission) properties and their potential applicability as fluorescent labels. Convective heating, ultrasound irradiation and mechanochemical synthesis were considered as alternative synthetic methodologies proficient for overcoming drawbacks such as long reaction time, nonsatisfactory yields or solvent requirements in the synthesis of novel dye (E)-1-(3-chloropropyl)-4-(2-(10-methyl-10H-phenothiazin-3-yl)vinyl)pyridin-1-ium bromide 3d and its N-alkyl-2-methylpyridinium precursor 1c. The trans geometry of the newly synthesized (E)-4-(2-(7-bromo-10-ethyl-10H-phenothiazin-3-yl)vinyl)-1-methylpyridin-1-ium iodide 3b and (E)-1-methyl-4-(2-(10-methyl-10H-phenothiazin-3-yl)vinyl)pyridin-1-ium tetrafluoroborate 3a′ was confirmed by single crystal X-ray diffraction. A negative solvatochromism of the dyes in polar solvents was highlighted by UV-Vis spectroscopy and explanatory insights were supported by molecular modeling which suggested a better stabilization of the lowest unoccupied molecular orbitals (LUMO). The photostability of the dye 3b was investigated by irradiation at 365 nm in different solvents, while the steady-state and time-resolved fluorescence properties of dye 3b and 3a′ in solid state were evaluated under one-photon excitation at 485 nm. The in vitro cytotoxicity of the new PVP dyes on B16-F10 melanoma cells was evaluated by WST-1 assay, while their intracellular localization was assessed by epi-fluorescence conventional microscopy imaging as well as one- and two-photon excited confocal fluorescence lifetime imaging microscopy (FLIM). PVP dyes displayed low cytotoxicity, good internalization inside melanoma cells and intense fluorescence emission inside the B16-F10 murine melanoma cells, making them suitable staining agents for imaging applications.     

Well-Known and Novel Serum Biomarkers for Risk Stratification of Patients with Non-ischemic Dilated Cardiomyopathy

Non-ischemic dilated cardiomyopathy encompasses a wide spectrum of myocardial disorders, characterized by left ventricular dilatation with systolic impairment and increased risk of sudden cardiac death. In spite of all the therapeutic progress that has been made in recent years, dilated cardiomyopathy continues to be an important cause of cardiac transplant, being associated with an enormous cost burden for health care systems worldwide. Predicting the prognosis of patients with dilated cardiomyopathy is essential to individualize treatment. Late gadolinium enhancement-cardiac magnetic resonance imaging, microvolt T-wave alternans, and genetic testing have emerged as powerful tools in predicting sudden cardiac death occurrence and maximizing patient’s selection. Despite all these new diagnostic modalities, additional tests to complement or replace current tools are required for better risk stratification. Therefore, biomarkers are an easy and important tool that can help to detect patients at risk of adverse cardiovascular events. Additionally, identifying potential biomarkers involved in dilated cardiomyopathy can provide us important information regarding the diagnostic, prognostic, risk stratification, and response to treatment for these patients. Many potential biomarkers have been studied in patients with dilated cardiomyopathy, but only a few have been adopted in current practice. Therefore, the aim of our review is to provide the clinicians with an update on the well-known and novel biomarkers that can be useful for risk stratification of patients with non-ischemic dilated cardiomyopathy.     

Łukasiewicz logic and Riesz spaces

We initiate a deep study of Riesz MV-algebras which are MV-algebras endowed with a scalar multiplication with scalars from \([0,1]\) . Extending Mundici’s equivalence between MV-algebras and \(\ell \) -groups, we prove that Riesz MV-algebras are categorically equivalent to unit intervals in Riesz spaces with strong unit. Moreover, the subclass of norm-complete Riesz MV-algebras is equivalent to the class of commutative unital C \(^*\) -algebras. The propositional calculus \({\mathbb R}{\mathcal L}\) that has Riesz MV-algebras as models is a conservative extension of ?ukasiewicz \(\infty \) -valued propositional calculus and is complete with respect to evaluations in the standard model \([0,1]\) . We prove a normal form theorem for this logic, extending McNaughton theorem for ? ukasiewicz logic. We define the notions of quasi-linear combination and quasi-linear span for formulas in \({\mathbb R}{\mathcal L},\) and relate them with the analogue of de Finetti’s coherence criterion for \({\mathbb R}{\mathcal L}\) .     

A theoretical study of solvent effects on Kolbe-Schmitt reaction kinetics

A theoretical DFT study was employed to confirm the Kolbe-Schmitt reaction mechanism and investigate solvent effects on this reaction. The use of a solvent in the Kolbe-Schmitt reaction is desirable to facilitate a homogeneous reaction mixture and potentially improve the reaction rate. The candidate solvents were designed using computer aided molecular design (CAMD) and tested using DFT solvation calculations. The results from the quantum mechanical calculations were then used to determine the rate constants for each elementary step, the overall reaction yields and the corresponding residence time. The methodology was tested on the reaction without solvent, with solvents reported in the literature, and with the designed solvents. The study revealed that in the presence of solvents with high dielectric constant the reaction becomes reversible, leading to low product yields.     

Dynamic load balancing with adaptive factoring methods in scientific applications

To improve the performance of scientific applications with parallel loops, dynamic loop scheduling methods have been proposed. Such methods address performance degradations due to load imbalance caused by predictable phenomena like nonuniform data distribution or algorithmic variance, and unpredictable phenomena such as data access latency or operating system interference. In particular, methods such as factoring, weighted factoring, adaptive weighted factoring, and adaptive factoring have been developed based on a probabilistic analysis of parallel loop iterates with variable running times. These methods have been successfully implemented in a number of applications such as: N-Body and Monte Carlo simulations, computational fluid dynamics, and radar signal processing. The focus of this paper is on adaptive weighted factoring (AWF), a method that was designed for scheduling parallel loops in time-stepping scientific applications. The main contribution of the paper is to relax the time-stepping requirement, a modification that allows the AWF to be used in any application with a parallel loop. The modification further allows the AWF to adapt to load imbalance that may occur during loop execution. Results of experiments to compare the performance of the modified AWF with the performance of the other loop scheduling methods in the context of three nontrivial applications reveal that the performance of the modified method is comparable to, and in some cases, superior to the performance of the most recently introduced adaptive factoring method.

Analytical‐Based Methodologies for Examining the In Vitro Absorption,Distribution, Metabolism,and Elimination (ADME) of Silver Nanoparticles

The clinical applications of silver nanoparticles (AgNPs) remain limited due to the lack of well‐established methodologies for studying their nanokinetics. Hereby, the primary goal is to adapt a suite of analytical‐based methodologies for examining the in vitro absorption, distribution, metabolism, and elimination of AgNPs. Vero 76 and HEK 293 cells are exposed to ≈10‐nm spherical AgNPs⁺ and AgNPs^? at relevant concentrations (0–300 µg mL^?1) and times (4–48 h). Absorption: Inductively coupled plasma optical emission spectroscopy (ICP‐OES) demonstrates that the two AgNP formulations are not bioequivalent. For example, different bioavailabilities (C _maximum < 20.7 ± 4% and 6.82 ± 0.4%), absorption times (T _maximum > 48 and ≈24 h), and absorption rate laws (first‐ and zeroth‐order at 300 µg mL^?1) are determined in Vero 76 for AgNPs⁺ and AgNPs^?, respectively. Distribution: Raman and CytoViva hyperspectral imaging show different cellular localizations for AgNPs⁺ and AgNPs^?. Metabolism: Cloud point extraction (CPE)‐tangential flow filtration (TFF) reveal that ≤ 11% ± 4% of the administered, sublethal AgNPs release Ag⁺ and contribute to the observed cytotoxicity. Elimination: ICP‐OES‐CPE suggests that AgNPs are cleared via exocytosis.     

Joint forecasts of Dow Jones stocks under general multivariate loss function

When forecasts are assessed by a general loss (cost-of-error) function, the optimal point forecast is, in general, not the conditional mean, and depends on the conditional volatility—which, for stock returns, is time-varying. In order to provide forecasts of daily returns of 30 DJIA stocks under a general multivariate loss function, the following issues are addressed. We discuss what conditions define a multivariate loss function, and a simple class of such functions is proposed. Based on suitable combinations of univariate losses, the suggested multivariate functions are convenient for practical applications with many variables. To keep the computational aspect tractable, a flexible multivariate GARCH model is employed in estimating the conditional forecast distributions. The model easily copes with large number of series while allowing for skewness, fat tails, non-ellipticity, and tail dependence. Based on Engle’s DCC GARCH, it uses multivariate affine generalized hyperbolic distributions as conditional probability law, and the number of parameters to be estimated simultaneously does not depend on the number of series. The model is fitted using daily data from 2002 to 2007 (keeping data from 2008 for out-of-sample forecasts), and a bootstrap procedure is used to derive point forecasts under several multivariate loss functions of the proposed type.