Statistical FT-IR Spectroscopy for the Characterization of 17 Vegetable Oils

Vegetable oils have been utilized for centuries in the food, cosmetic, and pharmaceutical industries, and they contribute beneficially to overall human health, to active skincare, and to effective treatments. Monitoring of the vegetable oils is carried out by the methods described in the European Pharmacopeia, which is time-consuming, has poor repeatability, and involves the use of toxic organic chemicals and expensive laboratory equipment. Many successful studies using IR spectroscopy have been carried out for the detection of geographical origin and adulteration as well as quantification of oxidation parameters. The aim of our research was to explore FT-IR spectroscopy for assessing the quality parameters and fatty acid composition of cranberry, elderberry, borage, blackcurrant, raspberry, black mustard, walnut, sea buckthorn, evening primrose, rosehip, chia, perilla, black cumin, sacha inchi, kiwi, hemp, and linseed oil. Very good models were obtained for the α-linolenic acid and linoleic acid contents, with R² = 1.00; R_v² values of 0.98, 0.92, 0.89, and 0.84 were obtained for iodine value prediction, stearic acid content, palmitic acid content, and unsaponifiable matter content, respectively. However, we were not able to obtain good models for all parameters, and the use of the same process for variable selection was found to be not suitable for all cases.     

Preclassification of Broadband and Sparse Infrared Data by Multiplicative Signal Correction Approach

Preclassification of raw infrared spectra has often been neglected in scientific literature. Separating spectra of low spectral quality, due to low signal-to-noise ratio, presence of artifacts, and low analyte presence, is crucial for accurate model development. Furthermore, it is very important for sparse data, where it becomes challenging to visually inspect spectra of different natures. Hence, a preclassification approach to separate infrared spectra for sparse data is needed. In this study, we propose a preclassification approach based on Multiplicative Signal Correction (MSC). The MSC approach was applied on human and the bovine knee cartilage broadband Fourier Transform Infrared (FTIR) spectra and on a sparse data subset comprising of only seven wavelengths. The goal of the preclassification was to separate spectra with analyte-rich signals (i.e., cartilage) from spectra with analyte-poor (and high-matrix) signals (i.e., water). The human datasets 1 and 2 contained 814 and 815 spectra, while the bovine dataset contained 396 spectra. A pure water spectrum was used as a reference spectrum in the MSC approach. A threshold for the root mean square error (RMSE) was used to separate cartilage from water spectra for broadband and the sparse spectral data. Additionally, standard noise-to-ratio and principle component analysis were applied on broadband spectra. The fully automated MSC preclassification approach, using water as reference spectrum, performed as well as the manual visual inspection. Moreover, it enabled not only separation of cartilage from water spectra in broadband spectral datasets, but also in sparse datasets where manual visual inspection cannot be applied.     

Molecular Interactions Associated with Coagulation of Organic Pollutants by 2S Albumin of Plant Proteins: A Computational Approach

The removal of organic pollutants is a major challenge in wastewater treatment technologies. Coagulation by plant proteins is a promising technique for this purpose. The use of these proteins has been experimentally investigated and reported in the literature. However, the determination of the molecular interactions of these species is experimentally challenging and the computational approach offers a suitable alternative in gathering useful information for this system. The present study used a molecular dynamic simulation approach to predict the potentials of using Moringa oleifera (MO), Arachis hypogaea, Bertholletia excelsa, Brassica napus, and Helianthus annuus plant proteins for the coagulation of organic pollutants and the possible mechanisms of coagulation of these proteins. The results showed that the physicochemical and structural properties of the proteins are linked to their performance. Maximum coagulation of organic molecules to the proteins is between 50–100%. Among five proteins studied for coagulation, Brassica napus and Helianthus annuus performed better than the well-known MO protein. The amino acid residues interacting with the organic molecules play a significant role in the coagulation and this is peculiar with each plant protein. Hydrogen bond and π—interactions dominate throughout the protein–pollutants molecular interactions. The reusability of the proteins after coagulation derived from their structural quality analysis along with the complexes looks promising and most of them are better than that of the MO. The results showed that the seed proteins studied have good prediction potentials to be used for the coagulation of organic pollutants from the environment, as well as the insights into their molecular activities for bioremediation.     

Performance Modulation of S-CO2 Brayton Cycle for Marine Low-Speed Diesel Engine Flue Gas Waste Heat Recovery Based on MOGA

(1) Background: the shipping industry forced ships to adopt new energy-saving technologies to improve energy efficiency. With the timing modulation for the marine low-speed diesel engine S-CO₂ Brayton cycle, the waste heat recovery system is optimized to improve fuel economy. (2) Methods: with the 6EX340EF marine low-speed diesel engine established in AVL Cruise M and verified by the bench test data, the model of the S-CO₂ Recompression Brayton Cycle (SCRBC) system for the low-speed engine flue gas waste heat recovery was developed in EBSILON, and verified by SANDIA experimental data. On this basis, the effects of injection timing and valve timing parameters on the comprehensive performance of the main engine and the waste heat recovery system were investigated. By optimizing the timing modulation parameters through multi-objective genetic algorithm (MOGA) and evaluating the flue gas waste heat recovery from the perspective of thermodynamic performance and emission reduction, the research on the performance modulation method of the S-CO₂ Brayton Cycle for flue gas waste heat in marine low-speed engines has been completed. (3) Results: the SCRBC with waste heat modulation will further increase the total power and efficiency, which in turn brings about a reduction in the fuel consumption rate. The efficiency of the SCRBC system with the addition of waste heat modulation increases by 2.28%, 1.04% and 2.07% at 50%, 75% and 100%, respectively. After adding the residual heat modulation, the maximum annual CO₂ emission reduction of 748.51 × 10³ kg·a⁻¹ occurred at 50% load; with the exergy analysis, the cooler has the largest system exergy loss of 165 kW, with the exergy loss efficiency of 2.06% under 100% load. (4) Conclusions: the research on the performance modulation method of S-CO₂ Brayton cycle for flue gas waste heat in the marine low-speed engine has been completed, which further improves the efficiency of the system and can be extended to other engines.     

Group Testing with Blocks of Positives and Inhibitors

The main goal of group testing is to identify a small number of specific items among a large population of items. In this paper, we consider specific items as positives and inhibitors and non-specific items as negatives. In particular, we consider a novel model called group testing with blocks of positives and inhibitors. A test on a subset of items is positive if the subset contains at least one positive and does not contain any inhibitors, and it is negative otherwise. In this model, the input items are linearly ordered, and the positives and inhibitors are subsets of small blocks (at unknown locations) of consecutive items over that order. We also consider two specific instantiations of this model. The first instantiation is that model that contains a single block of consecutive items consisting of exactly known numbers of positives and inhibitors. The second instantiation is the model that contains a single block of consecutive items containing known numbers of positives and inhibitors. Our contribution is to propose efficient encoding and decoding schemes such that the numbers of tests used to identify only positives or both positives and inhibitors are less than the ones in the state-of-the-art schemes. Moreover, the decoding times mostly scale to the numbers of tests that are significantly smaller than the state-of-the-art ones, which scale to both the number of tests and the number of items.     

Comparison of the Characteristics of Recycled Carbon Fibers/Polymer Composites by Different Recycling Techniques

In this study, three recycling methods, namely, mechanical grinding, steam pyrolysis, and the supercritical solvent process, which are used to acquire recycled carbon fibers (RCFs), were compared for their application in synthesizing polymer-matrix composites. RCF-reinforced polyethylene (PE) composites were prepared to compare the mechanical properties of the composites generated using the three recycling methods. The PE/RCF composites exhibited 1.5 times higher mechanical strength than the RCF-reinforced PE composites, probably because of the surface oxidation effects during the recycling processes that consequently enhanced interfacial forces between the RCF and the matrix. Further, the steam pyrolysis process showed the highest energy efficiency and can thus be applied on a large production scale in domestic recycled CF markets.     

Effects of Ultra-High Pressure on Endogenous Enzyme Activities,Protein Properties,and Quality Characteristics of Shrimp (Litopenaeus vannamei) during Iced Storage

The present study aimed to explore the effects of ultra-high pressure (UHP) on the cathepsin (B, D, H, and L) activities, protein oxidation, and degradation properties as well as quality characteristics of iced shrimp (Litopenaeus vannamei). Fresh shrimps were vacuum-packed, treated with UHP (100–500 MPa for 5 min), and stored at 0 °C for 15 days. The results showed that the L* (luminance), b* (yellowness), W (whiteness), ΔE (color difference), hardness, shear force, gumminess, chewiness, and resilience of shrimp were significantly improved by UHP treatment. Moreover, the contents of surface hydrophobicity, myofibril fragmentation index (MFI), trichloroacetic acid (TCA)-soluble peptides, carbonyl, dityrosine, and free sulfhydryl of myofibrillar protein (MP) were significantly promoted by UHP treatment. In addition, UHP (above 300 MPa) treatment enhanced the mitochondrial membrane permeability but inhibited the lysosomal membrane stability, and the cathepsin (B, D, H, and L) activities. UHP treatment notably inhibited the activities of cathepsins, delayed protein oxidation and degradation, as well as texture softening of shrimp during storage. Generally, UHP treatment at 300 MPa for 5 min effectively delayed the protein and quality deterioration caused by endogenous enzymes and prolonged the shelf life of shrimp by 8 days.     

Modulation in Techno-Functional,Textural Properties,In Vitro Starch Digestibility and Macromolecular–Structural Interactions of Pasta with Potato (Solanum tuberosum L.)

The replacement of semolina with potato flour (PF) and potato mash (PM) at different levels was assessed for its effects on pasta quality. The results showed that the addition of PF and PM increased the pasting viscosity of the blends; in addition, PF enhanced the functional properties, while PM reduced them. The minimum cooking time decreased with PF and PM, while the PF pasta exhibited a higher cooking loss (5.02 to 10.44%) than the PM pasta, which exhibited a lower cooking loss. The pasta with PF and PM showed an increase in the total phenolic and flavonoid content, with reduced in vitro digestibility as confirmed by Fourier transform infrared spectroscopy. The PF pasta exhibited lower lightness and higher yellowness than the PM pasta, and its firmness and toughness also modulated owing to the complex interaction between potato starches and the gluten protein matrix, as evident from scanning electron microscopy. Sensory data revealed that pasta containing 30% PF and 16% PM was highly acceptable.     

并联谐振电路实验方法的研究

本文试图利用并联谐振电路的选择性对这一方法的适用范围进行讨论,并且通过实验给予验证。     

Critical Quality Control Methods for a Novel Anticoagulant Candidate LFG-Na by HPSEC-MALLS-RID and Bioactivity Assays

A low molecular weight fucosylated glycosaminoglycan sodium (LFG-Na) is a novel anticoagulant candidate from the sea cucumber Holothuria fuscopunctata that selectively inhibits intrinsic tenase (iXase). The molecular weight, molecular weight distribution and bioactivities are the critical quality attributes of LFG-Na. The determination of these quality attributes of such an oligosaccharides mixture drug is challenging but critical for the quality control process to ensure its safety and efficacy in clinical use. Herein, the molecular weight and molecular weight distribution of LFG-Na were successfully determined using high performance size exclusion chromatography coupled with multi angle laser light scattering and refractive index detector (HPSEC-MALLS-RID). Comparing to the conventional method, HPSEC-MALLS-RID based on the refractive index increment (dn/dc) did not require the reference substances to establish the calibration curve. The acceptance criteria of LFG-Na were established, the weight-average molecular weight (Mw) should be 4000 to 6000 Da, the polydispersity (Mw/Mn) < 1.40, and the fraction with molecular weights of 1500 to 8000 Da should be no less than 80% of the total. HPSEC-MALLS-RID was also utilized for the determination of the starting material native fucosylated glycosaminoglycan (NFG) to choose a better manufacturing process. Furthermore, APTT assay was selected and the potency of anti-iXase, referring to the parallel line assay (PLA) method, was established to clarify the consistency of its biological activities. The results suggest that HPSEC-MALLS-RID and bioactivity assays are critical quality control methods for multi-component glycosaminoglycan LFG-Na. The methods also provide a feasible strategy to control the quality of other polysaccharide medicines.