The role of pyrrhotite (Fe7S8) and the sample texture in the hydrothermal transformation of pentlandite ((Fe,Ni)9S8) to violarite ((Ni,Fe)3S4)

The catalytic role of pyrrhotite (Fe₇S₈) in the reaction kinetics of the hydrothermal transformation of pentlandite ((Fe,Ni)₉S₈) to violarite ((FeNi₂S₄) was found to depend on the physical form of pyrrhotite. Pyrrhotite in fine scale intergrown with pentlandite boosts the reaction, whereas in a mechanical mixture of pyrrhotite and pentlandite, it plays the opposite role. This phenomenon was interpreted as result of dissolution of pyrrhotite under reaction conditions.     

Physical mechanisms of phonation onset: a linear stability analysis of an aeroelastic continuum model of phonation

In an investigation of phonation onset, a linear stability analysis was performed on a two-dimensional, aeroelastic, continuum model of phonation. The model consisted of a vocal fold-shaped constriction situated in a rigid pipe coupled to a potential flow which separated at the superior edge of the vocal fold. The vocal fold constriction was modeled as a plane-strain linear elastic layer. The dominant eigenvalues and eigenmodes of the fluid-structure-interaction system were investigated as a function of glottal airflow. To investigate specific aerodynamic mechanisms of phonation onset, individual components of the glottal airflow (e.g., flow-induced stiffness, inertia, and damping) were systematically added to the driving force. The investigations suggested that flow-induced stiffness was the primary mechanism of phonation onset, involving the synchronization of two structural eigenmodes. Only under conditions of negligible structural damping and a restricted set of vocal fold geometries did flow-induced damping become the primary mechanism of phonation onset. However, for moderate to high structural damping and a more generalized set of vocal fold geometries, flow-induced stiffness remained the primary mechanism of phonation onset.     

A new lot sizing and scheduling heuristic for multi-site biopharmaceutical production

Biopharmaceutical manufacturing requires high investments and long-term production planning. For large biopharmaceutical companies, planning typically involves multiple products and several production facilities. Production is usually done in batches with a substantial set-up cost and time for switching between products. The goal is to satisfy demand while minimising manufacturing, set-up and inventory costs. The resulting production planning problem is thus a variant of the capacitated lot-sizing and scheduling problem, and a complex combinatorial optimisation problem. Inspired by genetic algorithm approaches to job shop scheduling, this paper proposes a tailored construction heuristic that schedules demands of multiple products sequentially across several facilities to build a multi-year production plan (solution). The sequence in which the construction heuristic schedules the different demands is optimised by a genetic algorithm. We demonstrate the effectiveness of the approach on a biopharmaceutical lot sizing problem and compare it with a mathematical programming model from the literature. We show that the genetic algorithm can outperform the mathematical programming model for certain scenarios because the discretisation of time in mathematical programming artificially restricts the solution space.     

Noninvasive assessment of hepatic fibrosis in patients with chronic hepatitis C using serum Fourier transform infrared spectroscopy

Assessment of liver fibrosis is of paramount importance to guide the therapeutic strategy in patients with chronic hepatitis C (CHC). In this pilot study, we investigated the potential of serum Fourier transform infrared (FTIR) spectroscopy for differentiating CHC patients with extensive hepatic fibrosis from those without fibrosis. Twenty-three serum samples from CHC patients were selected according to the degree of hepatic fibrosis as evaluated by the FibroTest: 12 from patients with no hepatic fibrosis (F0) and 11 from patients with extensive fibrosis (F3–F4). The FTIR spectra (ten per sample) were acquired in the transmission mode and data homogeneity was tested by cluster analysis to exclude outliers. After selection of the most discriminant wavelengths using an ANOVA-based algorithm, the support vector machine (SVM) method was used as a supervised classification model to classify the spectra into two classes of hepatic fibrosis, F0 and F3–F4. Given the small number of samples, a leave-one-out cross-validation algorithm was used. When SVM was applied to all spectra (n = 230), the sensitivity and specificity of the classifier were 90.1% and 100%, respectively. When SVM was applied to the subset of 219 spectra, i.e., excluding the outliers, the sensitivity and specificity of the classifier were 95.2% and 100%, respectively. This pilot study strongly suggests that the serum from CHC patients exhibits infrared spectral characteristics, allowing patients with extensive fibrosis to be differentiated from those with no hepatic fibrosis.     

The effect of bias-temperature stress on Na<Superscript>+</Superscript> incorporation into thin insulating films

The action of Na⁺ incorporation into thin insulating films and transport therein under influence of a bias voltage and temperature (BT stress) is the subject of this work. Deposited onto highly n-doped Si wafers, the insulators get BT stressed and subsequently investigated by means of time-of-flight–secondary ion mass spectrometry (ToF-SIMS). A thin PMMA film, spin-coated onto the insulator, serves as host matrix for a defined amount of Na⁺, provided via sodium triflate. Combining BT stress and ToF-SIMS depth profiling enables the unambiguous detection of Na⁺, incorporated into the insulating material. The insulators of interest vary in their nitride content: SiO₂, SiO_xN_y, and Si₃N₄. For SiO₂, it is shown that once a threshold BT stress is exceeded, Na⁺ gets quantitatively incorporated from PMMA into the underlying insulator, finally accumulating at the SiO₂/Si interface. A quantitative assessment by combination of Butler–Volmer kinetics with hopping dynamics reveals activation energies of E _a = 1.55 − 2.04 eV for Na⁺ transport in SiO₂ with varying thickness. On the other hand, SiO_xN_y and Si₃N₄ films show a different Na⁺ incorporation characteristic in this type of experiment, which can be explained by the higher coordination of nitrogen and hence the reduced Na⁺ permeability within these insulators.     

Evolutionary search for difficult problem instances to support the design of job shop dispatching rules

Dispatching rules are simple scheduling heuristics that are widely applied in industrial practice. Their popularity can be attributed to their ability to flexibly react to shop floor disruptions that are prevalent in many real-world manufacturing environments. However, it is a challenging and time-consuming task to design local, decentralised dispatching rules that result in a good global performance of a complex shop.An evolutionary algorithm is developed to generate job shop problem instances for which an examined dispatching rule fails to achieve a good solution due to a single suboptimal decision. These instances can be easily analysed to reveal limitations of that rule which helps with the design of better rules. The method is applied to a job shop problem from the literature, resulting in new best dispatching rules for the mean flow time measure.     

Inverse perturbation analysis: Improving the accuracy of potential energy curves

The equation for the first-order energy correction is used inversely to find the perturbation responsible for the energy correction. In the specific application to the calculation of a potential energy curve from the spectroscopic term values, the sought perturbation is a correction to an approximate potential curve. Consequently, an approximate potential curve (e.g. an RKR (Rydberg-Klein-Rees) curve) can be improved until the eigenvalues calculated for this curve agree with the spectroscopic term values within the experimental uncertainty. Results are given for the X²Σ⁺ state of HgH.     

Prediction of vapour-liquid equilibria for systems containing longer-chain alcohols and alkanes by various group-contribution methods

Comparisons are made of predicted excess free enthalpies provided by the parameters available for the ASOG model of Derr and Deal, the UNIFAC model of Fredenslund et al., and the CRG (chemical-reticular group-contribution) method of Neau and Péneloux. These methods are applied to predict vapour-liquid equilibria for alcohol-alkane systems having carbon numbers up to 16. Overall, the accuracy of prediction increases in the order UNIFAC, ASOG, CRG.     

Statistical evaluation of electrospray tandem mass spectra for optimized peptide fragmentation

Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has become the method of choice for the analysis of complex peptide mixtures. It combines the separation power of nanoflow LC with highly specific sequence analysis, allowing automated peptide sequencing with high resolution and throughput. For peptide fragmentation, the current experimental setup uses predefined parameters based on the mass-to-charge ratio of the individual precursor. Suitable parameters are typically established by empirical evaluation of fragment spectra of individual peptides used as standards. As a result, nonoptimal fragment spectra are obtained if peptides show fragmentation behavior different from these standards, which often result in the loss of sequence-specific fragment ion information. Here we describe a statistical approach for the systematic evaluation of the quality of individual peptide fragment spectra based on the calculation of their arithmetic mean and standard deviation. The method utilizes the dependence of these parameters on the difference in electric potential across the collision cell to determine the value that results in maximum information content. We show that the method is applicable to fragment spectra generated from a variety of multiply-charged tryptic peptides, over a wide concentration range, and on different types of mass analyzers. We also show how this novel approach can be used to define optimized collision energy settings over a wide mass-to-charge range.