Quality and nutritional characteristics of traditional curd cheese enriched with thermo-coagulated acid whey protein and indigenous Lactococcus lactis strain

Consumer interest in a healthy lifestyle and health-promoting natural products is a major driving force for the increasing global demand for bio-functional and sustainable dairy foods. Supplementation of curd cheese with thermo-coagulated acid whey protein (TAWP) led to 8–10% higher contents of moisture, 23–31% of lactose, 12–13% of unsaturated, 5–6% of monounsaturated, 63% of polyunsaturated, and 3–4% of long-chain fatty acids. Lipid quality indices – TI, AI, h/H, and Omega 6/3 among others, were also significantly better than those of control cheese. The addition of indigenous Lactococcus lactis strain enhanced the flavour of cheese samples, decreased the counts of yeast and mould up to 1 log cfu g⁻¹ after 10 days of storage. The replacement of curd with TAWP resulted in novel cheese with overall sensory perception above 77 points and added nutritional and functional value, however, body and texture parameters of modified cheese samples require an improvement.     

High-Movement Human Segmentation in Video Using Adaptive N-Frames Ensemble

A wide range of camera apps and online video conferencing services support the feature of changing the background in real-time for aesthetic, privacy, and security reasons. Numerous studies show that the Deep-Learning (DL) is a suitable option for human segmentation, and the ensemble of multiple DL-based segmentation models can improve the segmentation result. However, these approaches are not as effective when directly applied to the image segmentation in a video. This paper proposes an Adaptive N-Frames Ensemble (AFE) approach for high-movement human segmentation in a video using an ensemble of multiple DL models. In contrast to an ensemble, which executes multiple DL models simultaneously for every single video frame, the proposed AFE approach executes only a single DL model upon a current video frame. It combines the segmentation outputs of previous frames for the final segmentation output when the frame difference is less than a particular threshold. Our method employs the idea of the N-Frames Ensemble (NFE) method, which uses the ensemble of the image segmentation of a current video frame and previous video frames. However, NFE is not suitable for the segmentation of fast-moving objects in a video nor a video with low frame rates. The proposed AFE approach addresses the limitations of the NFE method. Our experiment uses three human segmentation models, namely Fully Convolutional Network (FCN), DeepLabv3, and Mediapipe. We evaluated our approach using 1711 videos of the TikTok50f dataset with a single-person view. The TikTok50f dataset is a reconstructed version of the publicly available TikTok dataset by cropping, resizing and dividing it into videos having 50 frames each. This paper compares the proposed AFE with single models and the Two-Models Ensemble, as well as the NFE models. The experiment results show that the proposed AFE is suitable for low-movement as well as high-movement human segmentation in a video.     

Comparison of EEG signal decomposition methods in classification of motor-imagery BCI

A brain–computer interface (BCI) provides a link between the human brain and a computer. The task of discriminating four classes (left and right hands and feet) of motor imagery movements of a simple limb-based BCI is still challenging because most imaginary movements in the motor cortex have close spatial representations. We aimed to classify binary limb movements, rather than the direction of movement within one limb. We also investigated joint time-frequency methods to improve classification accuracies. Neither of these, to our knowledge, has been investigated previously in BCI. We recorded EEG data from eleven participants, and demonstrated the classification of four classes of simple-limb motor imagery with an accuracy of 91.46% using intrinsic time-scale decomposition and 88.99% using empirical mode decomposition. In binary classifications, we achieved average accuracies of 89.90% when classifying imaginary movements of left hand versus right hand, 93.1% for left hand versus right foot, 94.00% for left hand versus left foot, 83.82% for left foot versus right foot, 97.62% for right hand versus left foot, and 95.11% for right hand versus right foot. The results show that the binary classification performance is slightly better than that of four-class classification. Our results also show that there is no significant difference in terms of spatial distribution between left and right foot motor imagery movements. There is also no difference in classification performances involving left or right foot movement. This work demonstrates that binary and four-class movements of the left and right feet and hands can be classified using recorded EEG signals of the motor cortex, and an intrinsic time-scale decomposition (ITD) feature extraction method can be used for real time brain computer interface.

     

The crossover of strain from school principals to teachers and vice versa.

The study investigated crossover of stress and strain in the workplace on a sample of 47 school principals and 183 teachers in Israeli elementary schools. The main goal of this study was to examine whether the crossover effect found among couples in the family also exists in the workplace. A 2nd aim of the study as to unravel the mechanisms that account for the crossover process. Using structural equation modeling, the authors found a significant crossover of job-induced tension but not of burnout from principals to teachers and vice versa. Being undermined by their principals elevated teachers' burnout and job-induced tension. This is the 1st study to demonstrate crossover of strain in the workplace and to discuss the implications of contagious job-induced tension in work environments. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

PV/batteries sizing and energy dispatching using Continuous Petri Net

Electrification of isolated area is commonly ensured by autonomous power installation including renewable energy sources. Many software tools are available to size such installations. These tools refer to the daily energy need and the site global renewable potential which leads to inaccurate and wasteful sizing. This paper presents an alternative tool based on the energy consumption and the daily loads profile to compute the size of a standalone PV/batteries system installed in an isolated chalet in Sfax, Tunisia. Obtained results are compared to those provided by PVsyst sizing tool to confirm the proposed algorithm effectiveness. Referring to obtained results, an assessment is proposed to dispatch energy between connected autonomous installations to cover the need of some houses by energy surplus offered by neighbors. A Continuous Petri Net (CPN) is used to model the energy flow between houses.     

The Role of the Immune System in IBD-Associated Colorectal Cancer: From Pro to Anti-Tumorigenic Mechanisms

Patients with inflammatory bowel disease (IBD) have increased incidence of colorectal cancer (CRC). IBD-associated cancer follows a well-characterized sequence of intestinal epithelial changes, in which genetic mutations and molecular aberrations play a key role. IBD-associated cancer develops against a background of chronic inflammation and pro-inflammatory immune cells, and their products contribute to cancer development and progression. In recent years, the effect of the immunosuppressive microenvironment in cancer development and progression has gained more attention, mainly because of the unprecedented anti-tumor effects of immune checkpoint inhibitors in selected groups of patients. Even though IBD-associated cancer develops in the background of chronic inflammation which is associated with activation of endogenous anti-inflammatory or suppressive mechanisms, the potential role of an immunosuppressive microenvironment in these cancers is largely unknown. In this review, we outline the role of the immune system in promoting cancer development in chronic inflammatory diseases such as IBD, with a specific focus on the anti-inflammatory mechanisms and suppressive immune cells that may play a role in IBD-associated tumorigenesis.     

Proteome Based Approach Defines Candidates for Designing a Multitope Vaccine against the Nipah Virus

Nipah virus is one of the most harmful emerging viruses with deadly effects on both humans and animals. Because of the severe outbreaks, in 2018, the World Health Organization focused on the urgent need for the development of effective solutions against the virus. However, up to date, there is no effective vaccine against the Nipah virus in the market. In the current study, the complete proteome of the Nipah virus (nine proteins) was analyzed for the antigenicity score and the virulence role of each protein, where we came up with fusion glycoprotein (F), glycoprotein (G), protein (V), and protein (W) as the candidates for epitope prediction. Following that, the multitope vaccine was designed based on top-ranking CTL, HTL, and BCL epitopes from the selected proteins. We used suitable linkers, adjuvant, and PADRE peptides to finalize the constructed vaccine, which was analyzed for its physicochemical features, antigenicity, toxicity, allergenicity, and solubility. The designed vaccine passed these assessments through computational analysis and, as a final step, we ran a docking analysis between the designed vaccine and TLR-³ and validated the docked complex through molecular dynamics simulation, which estimated a strong binding and supported the nomination of the designed vaccine as a putative solution for Nipah virus. Here, we describe the computational approach for design and analysis of this vaccine.     

The impact of international GHG trading regimes on penetration of new energy technologies and feasibility to implement EU Energy and Climate Package targets

The EU's new energy and environment policy - agreed by government leaders in their Council meeting in March 2007 - established a political agenda to tackle three core energy objectives: sustainability, economic competitiveness and security of supply. A triad of specific policies addresses these challenges: first, the 20/20/20 targets of the EU; then, the Second Strategic Energy Review of the European Commission; and finally, plans to liberalise energy markets. The European Union's ‘20/20/20′ targets for 2020: reduce greenhouse gas emissions by 20% comparing with 1990 level (to become a 30% reduction if other major global economies join), increase the share of renewables in the final energy consumption to 20% and to achieve 20% improvement in energy efficiency compared to the level in 2020 if existing trends were to continue.The aim of the paper is to analyse the feasibility of EU to implement 20/20/20 targets under the various international GHG trading regimes. GHG trading regimes were addressed by developing 10 energy scenarios until 2020 for EU by applying several energy modelling tools ranging from top down partial equilibrium to detailed technology based bottom up models.     

Effect of moist curing and use of lightweight sand on characteristics of high-performance concrete

Factorial design approach was undertaken to determine the effect of initial moist-curing duration (0 and 6 days) on properties of high-performance concrete (HPC) made with different water-to-cementitious materials ratios (w/cm) of 0.30 and 0.40 and sand substitution rates with lightweight sand (LWS) of 0 and 30 %, by volume. Mechanical properties of HPC are shown to be mainly affected by w/cm and total shrinkage of concrete by the LWS replacement rate and initial moist-curing period. It should be noted that concrete made with 30 % LWS replacement that did not receive any moist-curing exhibited lower shrinkage than moist-cured concrete prepared without any LWS, regardless of the w/cm. Combined use of 30 % LWS and 7 days of moist curing can lead to greater increase in compressive strength and larger decrease in total shrinkage compared to the use of 30 % LWS without moist curing or 7 days of moist curing without LWS. The use of LWS, however, is more practical and efficient to reduce shrinkage of HPC for deep concrete elements.