SRK equation of state: Predicting binary interaction parameters of hydrocarbons and related compounds

The parameter mixing rules of the Soave–Redlich–Kwong (SRK) equation of state are rewritten as Huron–Vidal mixing rules, where infinite-pressure activity coefficients are predicted by group contributions. Alkanes are treated as composed by one group type and aromatics by two types, aliphatic and aromatic. Hydrocarbon mixtures can be treated using one universal interaction parameter. Light compounds like methane, N₂, CO₂, H₂S, etc. are treated as separate groups; each one requires a pair of parameters for its interactions with aliphatic and aromatic groups. Group interaction parameters were determined from experimental VLE data. From them, binary interaction constants of the classical quadratic mixing rules can directly be derived.     

FTIR microspectroscopy of melanocytic skin lesions: a preliminary study

Fourier transform infrared (FTIR) microspectroscopy has been employed to investigate benign (ordinary dermal and Reed nevi), dysplastic and malignant (invasive melanoma) skin lesions through the analysis of spectral changes of melanocytes as well as in the evaluation of the presence of melanin. Hierarchical cluster analysis and principal component analysis led to a satisfactory separation of malignant from dysplastic and normal melanocytes. Also, on enlarging the clustering with spectra from Reed and dermal nevi, the multivariate analysis segregated well the spectral data into discrete clusters, allowing the obtaining of reliable average spectra for analysis at the molecular level of the main groups or components responsible for the biological and biochemical changes. The most significant spectral characteristics appear to be related to differences in secondary protein structures, in nucleic acid conformation, in intra- and intermolecular bonding. In all cases, supervised and unsupervised spectral analyses resulted in satisfactory agreement with histopathological findings.     

Effects of Lactobacillus rhamnosus on zebrafish oocyte maturation: an FTIR imaging and biochemical analysis

The aim of this study was to verify the effects of probiotic Lactobacillus rhamnosus on zebrafish oocyte maturation using FPA (focal plane array) FTIR imaging together with specific biochemical assays (SDS-PAGE, real-time PCR and enzymatic assay). Oocyte growth is prevalently due to a vitellogenic process which consists of the hepatic synthesis of vitellogenin and its selective uptake during maturation. The administration of L. rhamnosus IMC 501 for 10 days induced chemical changes to oocyte composition, promoting the maturation process. Some interesting biochemical features, linked to protein secondary structure (amide I band) and to phospholipidic and glucidic patterns, were detailed by vibrational analysis. The spectroscopic results were supported by the early increase of the lysosomal enzyme involved in the final oocyte maturation, the cathepsin L. This enzyme increases during follicle maturation, with the highest levels in class IV oocytes. In treated females, class III oocytes showed higher cathepsin L gene expression and enzymatic activity, with levels comparable to class IV oocytes isolated from controls; this can be related to the proteolytic cleavage of the higher molecular mass yolk protein components, as evidenced by SDS-PAGE.     

Analysis of trace degradation products (decarboxylated diastereoisomers) of S-adenosylmethionine by electrophoresis in capillaries with cationic coatings (N-methylpolyvinylpyridinium or divalent barium)

Commercial preparations of S‐adenosylmethionine (SAM) when analyzed in uncoated capillaries show a minute impurity believed to be decarboxylated (dc) SAM. By using two types of cationic coatings, thus reducing the electro‐endo‐osmotic flow (EOF), it was possible to separate this impurity into two diastereoisomers of dcSAM. The coatings evaluated for this purpose were: (i) N‐methylpolyvinylpyridinium, used under reversed EOF at acidic conditions (pH 4.0) and (ii) deposition of divalent barium at alkaline pH values (pH 9.4), providing reduced EOF. Under these conditions, it was possible to separate this impurity into two diastereoisomers, which by chemical synthesis were indeed proven to be dcSAM. It was further demonstrated that, in the alkylation of 5′‐methylthioadenosine by 3‐bromopropylamine in bromidric acid to dcSAM, another minute impurity was present, proven, via mass spectrometry, to consist of S‐(5′‐adenosyl)‐3‐thiopropylamine (decarboxylated and demethylated (dc‐SAH)). The LOD for the two dcSAM diastereoisomers was assessed as 17.5 μg/mL and their LOQ as 25.5 μg/mL. By the barium‐based protocol it was possible to quantify the dcSAM, present in a commercial sample of SAM, as a 0.1% impurity.     

Structural Analysis of a Helical Peptide Unfolding Pathway

The analysis of the folding mechanism in peptides adopting well‐defined secondary structure is fundamental to understand protein folding. Herein, we describe the thermal unfolding of a 15‐mer vascular endothelial growth factor mimicking α‐helical peptide (QK_L10A) through the combination of spectroscopic and computational analyses. In particular, on the basis of the temperature dependencies of QK_L10A H_α chemical shifts we show that the first phase of the thermal helix unfolding, ending at around 320 K, involves mainly the terminal regions. A second phase of the transition, ending at around 333 K, comprises the central helical region of the peptide. The determination of high‐resolution QK_L10A conformational preferences in water at 313 K allowed us to identify, at atomic resolution, one intermediate of the folding–unfolding pathway. Molecular dynamics simulations corroborate experimental observations detecting a stable central helical turn, which represents the most probable site for the helix nucleation in the folding direction. The data presented herein allows us to draw a folding–unfolding picture for the small peptide QK_L10A compatible with the nucleation–propagation model. This study, besides contributing to the basic field of peptide helix folding, is useful to gain an insight into the design of stable helical peptides, which could find applications as molecular scaffolds to target protein–protein interactions.     

Characterization of the volatile organic compounds of Italian 'Fossa' cheese by solid-phase microextraction gas chromatography/mass spectrometry

Fossa cheese is an Italian hard cheese, ripened for up to 3 months in underground pits dug into tuffaceous rock. During this period, the cheese develops a unique flavour and intense and somewhat piquant aroma. Solid-phase microextraction gas chromatography/mass spectrometry (SPME-GC/MS) was utilized to characterize the volatile organic compounds (VOCs) of Fossa cheese. A total of 75 VOCs were separated and identified; in particular, the major class of compounds found in the cheeses ripened in the pits were the esters of fatty acids. Discriminant analysis of volatile profiles allowed us to distinguish between cheeses in different stages of seasoning (60-day-old cheese and cheese ripened an additional 90 days in and out of the pits).     

Percolation transition in Yang-Mills matter at a finite number of colors

We examine baryonic matter at a quark chemical potential of the order of the confinement scale μ(q)～Λ(QCD). In this regime, quarks are supposed to be confined but baryons are close to the "tightly packed limit" where they nearly overlap in configuration space. We show that this system will exhibit a percolation phase transition when varied in the number of colors N(c): at high N(c), large distance correlations at the quark level are possible even if the quarks are essentially confined. At low N(c), this does not happen. We discuss the relevance of this for dense nuclear matter, and argue that our results suggest a new "phase transition," varying N(c) at constant μ(q).     

Refined methods for the identifiability of tensors

We prove that the general tensor of size \(2^n\) and rank \(k\) has a unique decomposition as the sum of decomposable tensors if \(k\le 0.9997\frac{2^n}{n+1}\) (the constant 1 being the optimal value). Similarly, the general tensor of size \(3^n\) and rank \(k\) has a unique decomposition as the sum of decomposable tensors if \(k\le 0.998\frac{3^n}{2n+1}\) (the constant 1 being the optimal value). Some results of this flavor are obtained for tensors of any size, but the explicit bounds obtained are weaker.     

On unitals in PG(2,q^2) stabilized by a homology group

The linear collineation group of a classical unital of $\mathrm{PG}(2,q^2)$ contains a group of homologies of order $q+1$ . In this paper we prove that if $\mathcal{U }$ is a unital of PG $(2,q^2)$ stabilized by a homology group of order $q+1$ and $q$ is a prime number, then $\mathcal{U }$ is classical.     

Approximate dynamic programming for stochastic N-stage optimization with application to optimal consumption under uncertainty

Stochastic optimization problems with an objective function that is additive over a finite number of stages are addressed. Although Dynamic Programming allows one to formally solve such problems, closed-form solutions can be derived only in particular cases. The search for suboptimal solutions via two approaches is addressed: approximation of the value functions and approximation of the optimal decision policies. The approximations take on the form of linear combinations of basis functions containing adjustable parameters to be optimized together with the coefficients of the combinations. Two kinds of basis functions are considered: Gaussians with varying centers and widths and sigmoids with varying weights and biases. The accuracies of such suboptimal solutions are investigated via estimates of the error propagation through the stages. Upper bounds are derived on the differences between the optimal value of the objective functional and its suboptimal values corresponding to the use at each stage of approximate value functions and approximate policies. Conditions under which the number of basis functions required for a desired approximation accuracy does not grow “too fast” with respect to the dimensions of the state and random vectors are provided. As an example of application, a multidimensional problem of optimal consumption under uncertainty is investigated, where consumers aim at maximizing a social utility function. Numerical simulations are provided, emphasizing computational pros and cons of the two approaches (i.e., value-function approximation and optimal-policy approximation) using the above-mentioned two kinds of basis functions. To investigate the dependencies of the performances on dimensionality, the numerical analysis is performed for various numbers of consumers. In the simulations, discretization techniques exploiting low-discrepancy sequences are used. Both theoretical and numerical results give insights into the possibility of coping with the curse of dimensionality in stochastic optimization problems whose decision strategies depend on large numbers of variables.