Monitoring of multivariable dynamic processes and sensor auditing

Industrial continuous processes are usually operated under closed-loop control, yielding process measurements that are autocorrelated, cross correlated, and collinear. A statistical process monitoring (SPM) method based on state variables is introduced to monitor such processes. The statistical model that describes the in-control variability is based on a canonical variate (CV) state space model. The CV state variables are linear combinations of the past process measurements which explain the variability of the future measurements the most, and they are regarded as the principal dynamic dimensions. A T² statistic based on the CV state variables is utilized for developing the SPM procedure. The CV state variables are also used for monitoring sensor reliability. An experimental application to a high temperature short time (HTST) pasteurization process illustrates the proposed methodology.     

Reactions with 2,3,4,5-Tetrahydro-benzo[b]thiepin-5-one and its Derivatives

2,3,4,5-Tetrahydro-benzo[b]thiepin-5-one, its 7-methyl derivative, and their S, S-dioxides condense with aromatic aldehydes to give the corresponding 4-arylidene derivatives 3 and 4 . Compounds 4 react with hydrazine and phenylhydrazine to yield 3, 3a, 4, 5-tetrahydro-2 H-benzo-[b]thiepino[4, 5-c]pyrazole S, S-dioxide derivatives 5 and 6 . Some of the arylidene derivatives 4 add GRIGNARD reagents to give 7 . The IR spectra of representative examples are discussed.     

Exposure of Mice to Thirdhand Smoke Modulates In Vitro and In Vivo Platelet Responses

Smoking is a risk factor for a variety of deleterious conditions, such as cancer, respiratory disease and cardiovascular disease. Thrombosis is an important and common aspect of several cardiovascular disease states, whose risk is known to be increased by both first- and secondhand smoke. More recently, the residual cigarette smoke that persists after someone has smoked (referred to as thirdhand smoke or THS) has been gaining more attention, since it has been shown that it also negatively affects health. Indeed, we have previously shown that 6-month exposure to THS increases the risk of thrombogenesis. However, neither the time-dependence of THS-induced thrombus formation, nor its sex dependence have been investigated. Thus, in the present study, we investigated these issues in the context of a shorter exposure to THS, specifically 3 months, in male and female mice. We show that the platelets from 3-month THS-exposed mice exhibited enhanced activation by agonists. Moreover, we also show that mice of both sexes exposed to THS have decreased tail bleeding as well as decreased thrombus occlusion time. In terms of the role of sex, intersex disparities in thrombus development and hemostasis as well as in platelet aggregation were, interestingly, observed. Together, our findings show that exposing mice to THS for 3 months is sufficient to predispose them to thrombosis; which seems to be driven, at least in part, by an increased activity in platelets, and that it does not manifest equally in both sexes.     

Association Mechanism and Conformational Changes in Trypsin on Its Interaction with Atrazine: A Multi- Spectroscopic and Biochemical Study with Computational Approach

Atrazine (ATR) is a herbicide globally used to eliminate undesired weeds. Herbicide usage leads to various adverse effects on human health and the environment. The primary source of herbicides in humans is the food laced with the herbicides. The ATR binding to trypsin (TYP) was investigated in this study to explore its binding potential and toxicity. In vitro interaction of ATR with TYP was studied using multi-spectroscopic methods, molecular docking, and enzyme kinetics to explore the mechanism of binding for the TYP-ATR system. The TYP-ATR complex revealed binding constants (10³ M⁻¹), suggesting a moderate binding. The free energy for the TYP-ATR complexes was negative, suggesting a spontaneous interaction. Thermodynamic parameters enthalpy (ΔH) and entropy (ΔS) obtained positive values for the TYP-ATR system suggesting hydrophobic interactions in the binding process. Micro-environmental and conformational changes in TYP molecules were induced on interaction with ATR. Reduced catalytic activity of TYP was observed after interaction with ATR owing to the changes in the secondary structure of the TYP.     

Genetic Elements Orchestrating Lactobacillus crispatus Glycogen Metabolism in the Vagina

Glycogen in the female lower reproductive tract is a major carbon source for colonization and acidification by common vaginal Lactobacillus species, such as Lactobacillus crispatus. Previously, we identified the amylopullulanase encoding gene pulA of Lactobacillus crispatus to correlate with the ability to autonomously utilize glycogen for growth. Here, we further characterize genetic variation and differential regulation of pulA affecting the presence of its gene product on the outer surface layer. We show that alpha-glucan degrading activity dissipates when Lactobacillus crispatus is grown on glucose, maltose and maltotriose, in agreement with carbon catabolite repression elements flanking the pulA gene. Proteome analysis of the S-layer confirmed that the amylopullulanase protein is highly abundant in an S-layer enriched fraction, but not in a strain with a defective amylopullulanase variant or in an amylopullulanase-sufficient strain grown on glucose. In addition, we provide evidence that Lactobacillus crispatus pulA mutants are relevant in vivo, as they are commonly observed in metagenome datasets of human vaginal microbial communities. Analysis of the largest publicly available dataset of 1507 human vaginal metagenomes indicates that among the 270 samples that contain a Lactobacillus crispatus pulA gene, 62 samples (23%) had a defective variant of this gene. Taken together, these results demonstrate that both environmental, as well as genetic factors explain the variation of Lactobacillus crispatus alpha-glucosidases in the vaginal environment.     

SURFACE ROUGHNESS OF SPUTTERED SILICON. II. MODEL VERIFICATION

Experimental verification of the mathematical surface roughness model for sputtered silicon was performed. The beam shape and its significant level of intensity were determined first by measuring the topography of craters sputtered by focused ion beam (FIB). Then the beam function was generated for various combinations of beam parameters. The material function was developed both by theoretical and experimental analysis. These two functions were then used in the model to calculate the theoretical surface roughness. Microsurface analysis was formed by FIB sputtering of a (100) silicon wafer. The surface roughness at the bottom of the sputtered features was then measured using an atomic force microscope. The theoretical surface roughness was found to be within ±1 and ±5 nm of the measured surface roughness with the measurement uncertainty (standard deviation) of about ±0.36 and ±0.85 nm for R_a and R_t, respectively.     

Ensemble learning of diffractive optical networks

A plethora of research advances have emerged in the fields of optics and photonics that benefit from harnessing the power of machine learning.Specifically,there has been a revival of interest in optical computing hardware due to its potential advantages for machine learning tasks in terms of parallelization,power efficiency and computation speed.Diffractive deep neural networks(D²NNs)form such an optical computing framework that benefits from deep learning-based design of successive diffractive layers to all-optically process information as the input light diffracts through these passive layers.D²NNs have demonstrated success in various tasks,including object classification,the spectral encoding of information,optical pulse shaping and imaging.Here,we substantially improve the inference performance of diffractive optical networks using feature engineering and ensemble learning.After independently training 1252 D²NNs that were diversely engineered with a variety of passive input filters,we applied a pruning algorithm to select an optimized ensemble of D²NNs that collectively improved the image classification accuracy.Through this pruning,we numerically demonstrated that ensembles of N=14 and N=30 D²NNs achieve blind testing accuracies of 61.14±0.23%and 62.13±0.05%,respectively,on the classification of GFAR-10 test images,providing an inference improvennent of>16%compared to the average performance of the individual D²NNs within each ensemble.These results constitute the highest inference accuracies achieved to date by any diffractive optical neural network design on the same dataset and might provide a significant leap to extend the application space of diffractive optical image classification and machine vision systems.     

Mitochondrial Dysfunction Plays Central Role in Nonalcoholic Fatty Liver Disease

Nonalcoholic fatty liver disease (NAFLD) is a global pandemic that affects one-quarter of the world’s population. NAFLD includes a spectrum of progressive liver disease from steatosis to nonalcoholic steatohepatitis (NASH), fibrosis, and cirrhosis and can be complicated by hepatocellular carcinoma. It is strongly associated with metabolic syndromes, obesity, and type 2 diabetes, and it has been shown that metabolic dysregulation is central to its pathogenesis. Recently, it has been suggested that metabolic- (dysfunction) associated fatty liver disease (MAFLD) is a more appropriate term to describe the disease than NAFLD, which puts increased emphasis on the important role of metabolic dysfunction in its pathogenesis. There is strong evidence that mitochondrial dysfunction plays a significant role in the development and progression of NAFLD. Impaired mitochondrial fatty acid oxidation and, more recently, a reduction in mitochondrial quality, have been suggested to play a major role in NAFLD development and progression. In this review, we provide an overview of our current understanding of NAFLD and highlight how mitochondrial dysfunction contributes to its pathogenesis in both animal models and human subjects. Further we discuss evidence that the modification of mitochondrial function modulates NAFLD and that targeting mitochondria is a promising new avenue for drug development to treat NAFLD/NASH.