Bioindicative values of microfungi in starch and possible deficiencies of the new Serbian regulation on food hygiene

The results of tests on the presence of yeasts and molds in cornstarch [AD ‘IPOK’ Zrenjanin, 2007-2008, made at the time when previous Regulations were valid] were analyzed in terms of bioindicative values of microfungi as indicators of quality and safety of raw material or final food products. Microbiological analysis was used to detect the presence of a number of microorganisms MMI-0001, and a questionnaire was designed at the Department of Public Health in Zrenjanin town (Republic of Serbia), where the anal­yses were done, regarding the microbiological tests on starch. In order to rationalize the analyses and make them more economical, several areas of product quality control (water, food, raw materials, space) were recommended either to be excluded or regarded as optional. Thus, analysis of presence of microfungi as indicators of product quality was categorized as optional. The results obtained from this research suggest a different conclusion because the bacteria in the samples indicated ˮmicrobiologically“, namely bacteriologically, safe samples of food, while, on the contrary, the presence of some microfungi as distinct xerophilous or xerotolerant microorganisms, indicated that the food was mycologically non-safe. The obtained data are crucial for questioning the decision to exclude the earlier required (mycological) analysis of the samples (in the production of starch, or end products, etc.) and categorize such analyses in new Regulations as optional, depending on the manufacturer’s preference. Bioindicative values of microfungi as indicators of the quality of starch, clearly point to the shortsightedness of the new Regulations on food hygiene and safety, where tests on certain microorganisms (in this case, yeasts and molds) are not legally defined as mandatory, but the Law leaves manufacturers a possibility to choose (or not to choose) the testing and frequency of testing on the presence (absence) of microorganisms, which can be risky, both in the production and marketing of the finial products. [Projekat Ministarstva nauke Republike Srbije, br. OI-179079

Sampling-based Algorithms for Optimal Motion Planning

During the last decade, sampling-based path planning algorithms, such as Probabilistic RoadMaps (PRM) and Rapidly-exploring Random Trees (RRT), have been shown to work well in practice and possess theoretical guarantees such as probabilistic completeness. However, little effort has been devoted to the formal analysis of the quality of the solution returned by such algorithms, e.g., as a function of the number of samples. The purpose of this paper is to fill this gap, by rigorously analyzing the asymptotic behavior of the cost of the solution returned by stochastic sampling-based algorithms as the number of samples increases. A number of negative results are provided, characterizing existing algorithms, e.g., showing that, under mild technical conditions, the cost of the solution returned by broadly used sampling-based algorithms converges almost surely to a non-optimal value. The main contribution of the paper is the introduction of new algorithms, namely, PRM* and RRT*, which are provably asymptotically optimal, i.e., such that the cost of the returned solution converges almost surely to the optimum. Moreover, it is shown that the computational complexity of the new algorithms is within a constant factor of that of their probabilistically complete (but not asymptotically optimal) counterparts. The analysis in this paper hinges on novel connections between stochastic sampling-based path planning algorithms and the theory of random geometric graphs.Comment: 76 pages, 26 figures, to appear in International Journal of Robotics Researc

Reversible Martensitic Transformation under Low Magnetic Fields in Magnetic Shape Memory Alloys

Magnetic field-induced, reversible martensitic transformations in NiCoMnIn meta-magnetic shape memory alloys were studied under constant and varying mechanical loads to understand the role of coupled magneto-mechanical loading on the transformation characteristics and the magnetic field levels required for reversible phase transformations. The samples with two distinct microstructures were tested along the [001] austenite crystallographic direction using a custom designed magneto-thermo-mechanical characterization device while carefully controlling their thermodynamic states through isothermal constant stress and stress-varying magnetic field ramping. Measurements revealed that these meta-magnetic shape memory alloys were capable of generating entropy changes of 14 J kg(−1) K(−1) or 22 J kg (−1) K(−1), and corresponding magnetocaloric cooling with reversible shape changes as high as 5.6% under only 1.3 T, or 3 T applied magnetic fields, respectively. Thus, we demonstrate that this alloy is suitable as an active component in near room temperature devices, such as magnetocaloric regenerators, and that the field levels generated by permanent magnets can be sufficient to completely transform the alloy between its martensitic and austenitic states if the loading sequence developed, herein, is employed

Effect of the C/N ratio modification on the corrosion behavior and performance of carbonitride coatings prepared by cathodic arc deposition

This study focuses on investigating carbonitride coatings, specifically CNTi-(Zr, ZrNb, and ZrSi), as promising candidates for enhancing the durability and efficiency of Ti6Al4V materials used in nuclear fusion technology. X-ray diffraction analysis identified distinct phases, including TiN, ZrN, ZrC, and TiC. The corrosion studies showed complete degradation of the TiN, ZrC, and ZrN phases in the TiZrCN coating after tests, while the TiC phase exhibited relative stability. The surface morphologies and elemental mapping analysis demonstrated the loss of homogeneity in element distribution after corrosion process. The addition of Si and Nb elements into TiZrCN significantly influenced the coatings' corrosion behavior, with breakaway corrosion observed in CNTi- (Zr and ZrSi) coatings and localized corrosion in CNTi-(ZrNb) coatings. Notably, the CNTi-(ZrSi) coating formed an oxide phase in the presence of NaCl, whereas the CNTi-(ZrNb) coating exhibited continuous resistance and a low corrosion rate. Irradiation was carried out for the generation of active isotopes, showing that no radioactive isotopes were formed in any of the investigated samples

Person Re-identification with Deep Similarity-Guided Graph Neural Network

The person re-identification task requires to robustly estimate visual similarities between person images. However, existing person re-identification models mostly estimate the similarities of different image pairs of probe and gallery images independently while ignores the relationship information between different probe-gallery pairs. As a result, the similarity estimation of some hard samples might not be accurate. In this paper, we propose a novel deep learning framework, named Similarity-Guided Graph Neural Network (SGGNN) to overcome such limitations. Given a probe image and several gallery images, SGGNN creates a graph to represent the pairwise relationships between probe-gallery pairs (nodes) and utilizes such relationships to update the probe-gallery relation features in an end-to-end manner. Accurate similarity estimation can be achieved by using such updated probe-gallery relation features for prediction. The input features for nodes on the graph are the relation features of different probe-gallery image pairs. The probe-gallery relation feature updating is then performed by the messages passing in SGGNN, which takes other nodes' information into account for similarity estimation. Different from conventional GNN approaches, SGGNN learns the edge weights with rich labels of gallery instance pairs directly, which provides relation fusion more precise information. The effectiveness of our proposed method is validated on three public person re-identification datasets.Comment: accepted to ECCV 201

Application of Correct-by-Construction Principles for a Resilient Risk-Aware Architecture

In this paper we discuss the application of correct-by-construction techniques to a resilient, risk-aware software architecture for onboard, real-time autonomous operations. We mean to combat complexity and the accidental introduction of bugs through the use of verifiable auto-coding software and correct-by-construction techniques, and discuss the use of a toolbox for correct-by-construction Temporal Logic Planning (TuLiP) for such a purpose. We describe some of TuLiP’s current functionality, specifically its ability to model symbolic discrete systems and synthesize software controllers and control policies that are correct-by-construction. We then move on to discuss the use of these techniques to define a deliberative goal-directed executive capability that performs risk-informed action-planning – to satisfy the mission goals (specified by mission control) within the specified priorities and constraints. Finally, we discuss an application of the TuLiP process to a simple rover resilience scenario

Lattice vibrations boost demagnetization entropy in a shape-memory alloy

Magnetocaloric (MC) materials present an avenue for chemical-free, solid state refrigeration through cooling via adiabatic demagnetization. We have used inelastic neutron scattering to measure the lattice dynamics in the MC material Ni45Co5Mn36.6In13.4. Upon heating across the Curie Temperature (TC), the material exhibits an anomalous increase in phonon entropy of 0.22 +/- 0.04 kB/atom, which is ten times larger than expected from conventional thermal expansion. This transition is accompanied by an abrupt softening of the transverse optic phonon. We present first-principle calculations showing a strong coupling between lattice distortions and magnetic excitations