Polyethylene/Polycaprolactone Nanocomposite Films for Food Packaging Modified with Magnetite and Casein: Oxygen Barrier,Mechanical, and Thermal Properties

Polyethylene (PE) was modified and prepared as double-layer polyethylene/polycaprolactone (PE/PCL) film. Magnetite and casein were added to the PCL-coating film to improve barrier properties and prevent destruction of basic structure of primary polymer PE. Significant improvements were observed with regards to mechanical (tensile strength, elongation at break) and thermal properties, while barrier (O₂ permeability) properties were slightly improved. Overall migration values into acetic acid were lower (from 1 to 4.6 mg/dm²) than the upper limit set by the legislation. Specific migration of iron in PE/PCL-Fe samples is also below (µg/L) specific migration limit value set by the legislation (mg/kg).     

Galectins in Early Pregnancy and Pregnancy-Associated Pathologies

Galectins are a family of conserved soluble proteins defined by an affinity for β-galactoside structures present on various glycoconjugates. Over the past few decades, galectins have been recognized as important factors for successful implantation and maintenance of pregnancy. An increasing number of studies have demonstrated their involvement in trophoblast cell function and placental development. In addition, several lines of evidence suggest their important roles in feto-maternal immune tolerance regulation and angiogenesis. Changed or dysregulated galectin expression is also described in pregnancy-related disorders. Although the data regarding galectins’ clinical relevance are still at an early stage, evidence suggests that some galectin family members are promising candidates for better understanding pregnancy-related pathologies, as well as predicting biomarkers. In this review, we aim to summarize current knowledge of galectins in early pregnancy as well as in pregnancy-related pathologies.     

Application of GC–MSD and LC–MS/MS for the determination of priority pesticides in baby foods in Serbian market

Babies and small children are especially sensitive population to the exposure to environmental contaminants. Their small mass and developing systems, including brain development may show adverse health effects from even low levels of contamination on a chronic or single dose case. In this paper one extraction method and two chromatographic techniques for the determination of pesticide residues in baby food were evaluated. A liquid chromatography–tandem mass spectrometry technique combined with electrospray ionization (ESI), (LC–MS/MS) and gas chromatography–mass spectrometry detection (GC–MSD) technique were applied in the detection of 50 pesticides in baby food. So-called QuEChERS (quick, easy, cheap, effective, rugged and safe) method was used as a sample preparation procedure. The recoveries were investigated at three levels (5, 10 and 50 μg/kg) and the results obtained showed compliance with the contemporary EU requirements with a few exceptions. LOQs for most of the tested pesticides were below the EU MRLs (10 μg/kg), except deltamethrin, cypermethrin, fenvalerate, phosalone and beta-cyfluthrin (LOQs were 10 μg/kg). Both techniques were applied in the analysis of 50 samples of baby food manufactured in Serbia.     

Modeling of dibenzothiophene oxidative desulfurization using response surface methodology

The effect of reaction temperature, mixing speed and oxidant to catalyst volume ratio, including their interactions on the oxidative desulfurization of dibenzothiophene by using response surface methodology was studied. Hydrogen peroxide was used as oxidant and acetic acid as catalyst. The obtained model accurately predicts conversion of dibenzothiophene and the best conversion of 98.7% was observed at temperature 70°C, mixing speed of 1250 rpm and oxidant to catalyst volume ratio of 1:1. At high temperatures, a major limitation of the desulfurization process is the mass transfer and the high mixing speed is needed to achieve an efficient process.     

Optimal attacks on qubit-based Quantum Key Recycling

Quantum Key Recycling (QKR) is a quantum cryptographic primitive that allows one to reuse keys in an unconditionally secure way. By removing the need to repeatedly generate new keys, it improves communication efficiency. ?kori? and de Vries recently proposed a QKR scheme based on 8-state encoding (four bases). It does not require quantum computers for encryption/decryption but only single-qubit operations. We provide a missing ingredient in the security analysis of this scheme in the case of noisy channels: accurate upper bounds on the required amount of privacy amplification. We determine optimal attacks against the message and against the key, for 8-state encoding as well as 4-state and 6-state conjugate coding. We provide results in terms of min-entropy loss as well as accessible (Shannon) information. We show that the Shannon entropy analysis for 8-state encoding reduces to the analysis of quantum key distribution, whereas 4-state and 6-state suffer from additional leaks that make them less effective. From the optimal attacks we compute the required amount of privacy amplification and hence the achievable communication rate (useful information per qubit) of qubit-based QKR. Overall, 8-state encoding yields the highest communication rates.     

New multi-criteria LNN WASPAS model for evaluating the work of advisors in the transport of hazardous goods

Neural Computing and Applications - Successfully organizing the transport of hazardous materials and handling them correctly is a very important logistical task that affects both the overall flow...     

Data clustering based on quantum synchronization

Natural Computing - There exists a specific class of methods for data clustering problem inspired by synchronization of coupled oscillators. This approach requires an extension of the classical...     

Analysis of medications change in Parkinson’s disease progression data

Parkinson’s disease is a neurodegenerative disorder that affects people worldwide. Careful management of patient’s condition is crucial to ensure the patient’s independence and quality of life. This is achieved by personalized treatment based on individual patient’s symptoms and medical history. The aim of this study is to determine patient groups with similar disease progression patterns coupled with patterns of medications change that lead to the improvement or decline of patients’ quality of life symptoms. To this end, this paper proposes a new methodology for clustering of short time series of patients’ symptoms and prescribed medications data, and time sequence data analysis using skip-grams to monitor disease progression. The results demonstrate that motor and autonomic symptoms are the most informative for evaluating the quality of life of Parkinson’s disease patients. We show that Parkinson’s disease patients can be divided into clusters ordered in accordance with the severity of their symptoms. By following the evolution of symptoms for each patient separately, we were able to determine patterns of medications change which can lead to the improvement or worsening of the patients’ quality of life.