Mathematical Modeling of Drying Processes of Selected Fruits and Vegetables

This study investigates the behavior of fruit and vegetable samples during drying. The experimental data are fitted to several different thin-layer drying models. Regression analysis is used to determine model parameters, while statistical indicators serve to evaluate the goodness of fit. The power function model gives the best fit for all examined samples. Based on this model, different drying and heat storage technologies can be combined to ensure that the required residual moisture content of an agricultural product is reached. It is demonstrated on the case of a specific Togolese processing plant that under favorable conditions, fossil fuel consumption can be decreased by 33 %.     

Analysis of stepwise charging limits and its implementation for efficiency improvement in switched capacitor DC–DC converters

In this work we analysed the stepwise charging technique to find the limits from which it is beneficial in terms of load capacitance and charge–discharge frequency. We included in the analysis practical limitations such as the consumption of auxiliary logic needed to implement the technique and the minimum size of auxiliary switches imposed by the technology. We proposed an ultra-low-power logic block to push these limits and to obtain benefits from this technique in small capacitances. Finally, we proposed to use a stepwise driver in the driving of the gate capacitance of power switches in switched-capacitor (SC) DC–DC converters. We designed and manufactured, in a 130 nm process, a SC DC–DC converter and measured a 29% energy reduction in the gate-drive losses of the converter. This accounts for an improvement of 4% (from 69 to 73%) in the overall converter efficiency.

     

Optimization methods in inverse problems and applications to science and engineering

Optimization and Engineering -     

A Conversion Method for the Preparation of Calcium Formate

Theoretical Foundations of Chemical Engineering - Calcium formate is widely used in construction, tanning, and textile manufacture and as an E238 biological additive in cosmetology and the food...     

Dysprosium doped copper oxide (Cu1-xDyxO) nanoparticles enabled bifunctional electrode for overall water splitting

The production of hydrogen, a favourable alternative to an unsustainable fossil fuel remains as a significant hurdle with the pertaining challenge in the design of proficient, highly productive and sustainable electrocatalyst for both oxygen evolution reaction (OER) and hydrogen evolution reaction (HER). Herein, the dysprosium (Dy) doped copper oxide (Cu_1-xDy_xO) nanoparticles were synthesized via solution combustion technique and utilized as a non-noble metal based bi-functional electrocatalyst for overall water splitting. Due to the improved surface to volume ratio and conductivity, the optimized Cu_1-xDy_xO (x = 0.01, 0.02) electrocatalysts exhibited impressive HER and OER performance respectively in 1 M KOH delivering a current density of 10 mAcm^?2 at a potential of ?0.18 V vs RHE for HER and 1.53 V vs RHE for OER. Moreover, the Dy doped CuO electrocatalyst used as a bi-functional catalyst for overall water splitting achieved a potential of 1.56 V at a current density 10 mAcm^?2 and relatively high current density of 66 mAcm^?2 at a peak potential of 2 V. A long term stability of 24 h was achieved for a cell voltage of 2.2 V at a constant current density of 30 mAcm^?2 with only 10% of the initial current loss. This showcases the accumulative opportunity of dysprosium as a dopant in CuO nanoparticles for fabricating a highly effective and low-cost bi-functional electrocatalyst for overall water splitting.     

Digital Tools for Statistical Quality Management in Automobile Production

Russian Engineering Research - Digital tools for managing improvements in automobile production are developed. An operative tool provides warnings regarding the operational quality of the vehicles...     

A review of phosphorescent and fluorescent phosphors for fingerprint detection

Currently, the efficient detection of fingerprints is essential for the crime investigations. Revealing fingerprints is commonly achieved with fluorescent organic compounds but they are not efficient for fingerprint detection on porous or reflective surfaces. In order to solve the problem of collecting fingerprints on porous/reflective surfaces, inorganic phosphors have been employed, since they have characteristics of variable color emission, afterglow, high chemical stability and nano-size, which allow the fingerprint detection on any porous or non-porous surfaces. Due to these last properties, this review presents a summary about the use of phosphorescent and fluorescent phosphors for the detection of latent fingerprints. First, we discussed the main physical and chemical characteristics of the fingerprints which permit their detection and collection from any surface. After this, we presented the main morphological, structural and luminescent properties of the phosphorescent and fluorescent phosphors that allow their use for fingerprint detection. Later, we demonstrated with pictures of fingerprints (with and without light emission from the phosphors deposited on them) that both, phosphorescent and fluorescent phosphors can be used to visualize fingerprints with high resolution and high contrast without interference of the background surface, which is ideal for its collection and registration in the Automated Fingerprint Identification System (AFIS). We believe that this review could be useful to understand how to select an appropriate phosphorescent or fluorescent material for fingerprint detection depending on the type of surface (porous or non-porous, reflective or not reflective) where the fingerprint is deposited.     

Multicriteria Minimax Problems: Localization of the Pareto Set and Suboptimal Control Design

Automation and Remote Control - We consider multicriteria minimax optimization problems with criteria in the form of the maxima of functionals given by the induced norms of linear operators taking...     

Prediction of Chameleonic Efficiency

Chameleonic properties, i. e., the capacity of a molecule to hide polarity in non-polar environments and expose it in water, help achieving sufficient permeability and solubility for drug molecules with high MW. We present models of experimental measures of polarity for a set of 24 FDA approved drugs (MW 405-1113) and one PROTAC (MW 1034). Conformational ensembles in aqueous and non-polar environments were generated using molecular dynamics. A linear regression model that predicts chromatographic apparent polarity (EPSA) with a mean unsigned error of 10 Ų was derived based on separate terms for donor, acceptor, and total molecular SASA. A good correlation (R²=0.92) with an experimental measure of hydrogen bond donor potential, Δlog P_oct-tol, was found for the mean hydrogen bond donor SASA of the conformational ensemble scaled with Abraham's A hydrogen bond acidity. Two quantitative measures of chameleonic behaviour, the chameleonic efficiency indices, are introduced. We envision that the methods presented herein will be useful to triage designed molecules and prioritize those with the best chance of achieving acceptable permeability and solubility.     

Role of Endocrine-Disrupting Chemicals in the Pathogenesis of Non-Alcoholic Fatty Liver Disease: A Comprehensive Review

Non-alcoholic fatty liver disease (NAFLD) is considered the most common liver disorder, affecting around 25% of the population worldwide. It is a complex disease spectrum, closely linked with other conditions such as obesity, insulin resistance, type 2 diabetes mellitus, and metabolic syndrome, which may increase liver-related mortality. In light of this, numerous efforts have been carried out in recent years in order to clarify its pathogenesis and create new prevention strategies. Currently, the essential role of environmental pollutants in NAFLD development is recognized. Particularly, endocrine-disrupting chemicals (EDCs) have a notable influence. EDCs can be classified as natural (phytoestrogens, genistein, and coumestrol) or synthetic, and the latter ones can be further subdivided into industrial (dioxins, polychlorinated biphenyls, and alkylphenols), agricultural (pesticides, insecticides, herbicides, and fungicides), residential (phthalates, polybrominated biphenyls, and bisphenol A), and pharmaceutical (parabens). Several experimental models have proposed a mechanism involving this group of substances with the disruption of hepatic metabolism, which promotes NAFLD. These include an imbalance between lipid influx/efflux in the liver, mitochondrial dysfunction, liver inflammation, and epigenetic reprogramming. It can be concluded that exposure to EDCs might play a crucial role in NAFLD initiation and evolution. However, further investigations supporting these effects in humans are required.