Comparison of some components of pigs kept in natural (free-range) and large-scale conditions

A new pig genotype of Hungarian Large White (75%) × Mangalica (pig with curly bristles, 25%) was used in the experiments. The experimental group was kept in a farming system under strictly natural circumstances until a body weight of 120 kg was attained. Neither antibiotics nor yield-increasing hormones were given to this group. The control group was kept in the usual large-scale farming conditions until body weight of 120 kg was attained. In most cases, protein, zinc, and copper levels and, in some cases, iron levels were significantly higher in some major cuts (neck-end (Boston-butt), loin, ham) of the 'free-range' pigs (n = 12) in comparison with the control animals kept in large-scale farming conditions. There was, on average, 15% less cholesterol in the muscles and 30% less cholesterol in the liver and less linoleic acid in all tissues of 'free-range' pigs than in the control group. There was less fat, but the amount of thiamin and riboflavin in the liver of the naturally kept pigs was twice that in the controls. In respect of TBA-reactive compounds, there were no significant differences between the two groups, but superoxide dismutase (SOD) showed significantly higher activities in all cuts from pigs kept in a large-scale farming system. This may be the effect of a higher level of linoleic acid in the fat.     

Microbial growth and biochemical changes on naturally contaminated chilled-beef subcutaneous adipose tissue stored aerobically

Naturally contaminated beef-brisket fat showed a psychrotroph count of 4 × 10(9) CFU/cm(2) after 14 days of aerobic refrigerated storage (5°C ± 1°C). Pseudomonas was the predominating genus. Other micro-organisms, such as Enterobacteriaceae and Brochothrix thermosphacta, grew up to 2·5 × 10(8) cfu/cm(2) and 1·6 × 10(8) cfu/cm(2), respectively. Concentrations of different substrates that could support microbial growth were measured. Glucose concentration dropped to approximately one-third of the initial level during the first week of storage. Lactic acid also declined. Free fatty acids increased significantly (P < 0·05) during refrigeration. However, other lipid-deterioration indices, such as the thiobarbituric acid number and the peroxide value, remained unchanged. Beef subcutaneous fat had a high initial microbial load and a capacity to support extensive bacterial growth. It may therefore constitute an important source of contamination for meat and manufactured meat products.     

State of the Art of Molecular Visualization in Immersive Virtual Environments

Visualization plays a crucial role in molecular and structural biology. It has been successfully applied to a variety of tasks, including structural analysis and interactive drug design. While some of the challenges in this area can be overcome with more advanced visualization and interaction techniques, others are challenging primarily due to the limitations of the hardware devices used to interact with the visualized content. Consequently, visualization researchers are increasingly trying to take advantage of new technologies to facilitate the work of domain scientists. Some typical problems associated with classic 2D interfaces, such as regular desktop computers, are a lack of natural spatial understanding and interaction, and a limited field of view. These problems could be solved by immersive virtual environments and corresponding hardware, such as virtual reality head-mounted displays. Thus, researchers are investigating the potential of immersive virtual environments in the field of molecular visualization. There is already a body of work ranging from educational approaches to protein visualization to applications for collaborative drug design. This review focuses on molecular visualization in immersive virtual environments as a whole, aiming to cover this area comprehensively. We divide the existing papers into different groups based on their application areas, and types of tasks performed. Furthermore, we also include a list of available software tools. We conclude the report with a discussion of potential future research on molecular visualization in immersive environments.     

Improving robustness of industrial object detection by automatic generation of synthetic images from CAD models

Object detection (OD) is used for visual quality control in factories. Images that compose training datasets are often collected directly from the production line and labeled with bounding boxes manually. Such data represent well the inference context but might lack diversity, implying a risk of overfitting. To address this issue, we propose a dataset construction method based on an automated pipeline, which receives a CAD model of an object and returns a set of realistic synthetic labeled images (code publicly available). Our approach can be easily used by non-expert users and is relevant for industrial applications, where CAD models are widely available. We performed experiments to compare the use of datasets obtained by the two different ways—collecting and labeling real images or applying the proposed automated pipeline—in the classification of five different industrial parts. To ensure that both approaches can be used without deep learning expertise, all training parameters were kept fixed during these experiments. In our results, both methods were successful for some objects but failed for others. However, we have shown that the combined use of real and synthetic images led to better results. This finding has the potential to make industrial OD models more robust to poor data collection and labeling errors, without increasing the difficulty of the training process.     

Deterministic Polymorphic Engineering of MoTe2 for Photonic and Optoelectronic Applications

Developing selective and coherent polymorphic crystals at the nanoscale offers a novel strategy for designing integrated architectures for photonic and optoelectronic applications such as metasurfaces, optical gratings, photodetectors, and image sensors. Here, a direct optical writing approach is demonstrated to deterministically create polymorphic 2D materials by locally inducing metallic 1T′-MoTe₂ on the semiconducting 2H-MoTe₂ host layer. In the polymorphic-engineered MoTe₂, 2H- and 1T′- crystalline phases exhibit strong optical contrast from near-infrared to telecom-band ranges (1–1.5 µm), due to the change in the band structure and increase in surface roughness. Sevenfold enhancement of third harmonic generation intensity is realized with conversion efficiency (susceptibility) of ≈1.7 × 10⁻⁷ (1.1 × 10⁻¹⁹ m² V⁻²) and ≈1.7 × 10⁻⁸ (0.3 × 10⁻¹⁹ m² V⁻²) for 1T′ and 2H-MoTe₂, respectively at telecom-band ultrafast pump laser. Lastly, based on polymorphic engineering on MoTe₂, a Schottky photodiode with a high photoresponsivity of 90 AW⁻¹ is demonstrated. This study proposes facile polymorphic engineered structures that will greatly benefit realizing integrated photonics and optoelectronic circuits.     

New approach for optimizing the interpretation and representation of the degree of historical-archaeological evidence in the virtual reconstructions

Virtual Reality - Virtual reconstruction is defined as the visual recovery of a building or object through the creation of a three-dimensional model of the asset to be reconstructed, in a...     

Fuzzy Adaptive Control Law for Trajectory Tracking Based on a Fuzzy Adaptive Neural PID Controller of a Multi-rotor Unmanned Aerial Vehicle

International Journal of Control, Automation and Systems - This article presents a fuzzy adaptive control law (FACL) designed for tracking the trajectory of a low-scale unmanned aerial vehicle...     

Optimal Control of Nonlinear Systems Using Experience Inference Human-Behavior Learning

Safety critical control is often trained in a simulated environment to mitigate risk. Subsequent migration of the biased controller requires further adjustments. In this paper, an experience inference human-behavior learning is proposed to solve the migration problem of optimal controllers applied to real-world nonlinear systems. The approach is inspired in the complementary properties that exhibits the hippocampus, the neocortex, and the striatum learning systems located in the brain. The hippocampus defines a physics informed reference model of the real-world nonlinear system for experience inference and the neocortex is the adaptive dynamic programming (ADP) or reinforcement learning (RL) algorithm that ensures optimal performance of the reference model. This optimal performance is inferred to the real-world nonlinear system by means of an adaptive neocortex/striatum control policy that forces the nonlinear system to behave as the reference model. Stability and convergence of the proposed approach is analyzed using Lyapunov stability theory. Simulation studies are carried out to verify the approach.      

Impact of white-matter mask selection on DTI histogram-based metrics as potential biomarkers in cerebral small vessel disease

Magnetic Resonance Materials in Physics, Biology and Medicine - Histogram-based metrics extracted from diffusion-tensor imaging (DTI) have been suggested as potential biomarkers for cerebral small...