The work proposes a new approach for evolutionary global optimization which, in simple terms, may be described as a fusion of quantum and simulated annealing. This becomes possible by using basic concepts from Homotopy Theory, conjugated to the already existing Fuzzy Adaptive Simulated Annealing paradigm and other components. In this fashion, it occurs a temporal and nonlinear superposition of the two types of annealing, provoking interesting effects in runtime, including the so-called quantum tunneling, when there is a sudden transition between attraction basins of different minima without "climbing" potential barriers. In addition, the proposal includes a generalization of the "deformation" of Hamiltonians used in quantum annealing by suggesting the use of general homotopies between the surface corresponding to the cost function under processing and another specific landscape, being this possible because of the ability of Fuzzy ASA of handling time-varying objective functions. The proposed paradigm shows that it is possible and beneficial to superpose the two types of annealing, displaying amazing numerical results and suggesting a kind of interlacing or synergic behavior - perhaps we could call it an "annealing entanglement". Finally, given the fast advances in commercial quantum annealing processors, it seems sensible to expect that an implementation of the proposed approach using such devices may occur very soon. In order to demonstrate the efficacy of the proposed algorithm, some significant and detailed examples are included in the text, so as to illustrate and clarify the presented ideas.

An addition sequence is an important operation in many applications of computer science, such as multi-modular exponentiation and outsourcing protocols. Finding an addition sequence for a set of positive integers with the shortest length is challenging due to the high computational time required to find the solution. In this paper, a new metaheuristic algorithm is designed based on the simulated annealing strategy to generate a short addition sequence. The efficiency of the proposed algorithm was proved experimentally by comparing it with the previous exact and heuristic algorithms in terms of running time and the length of the addition sequence.

Metaheuristic algorithms have been frequently using to tackle optimization problems, however such algorithms in the analysis of health-related data is not commonly used as developing metaheuristic algorithms that work well on health-related data is a difficult task due to complexity of the health data in particular genomics and epigenetics data. One of the important tasks in genomics is to predict genomic elements that are incorporating together to regulate a disease-related genes. Predicting such elements are important as they can be used to develop a personalized cure. In this study, we present for the first time, a multi-object simulated annealing algorithm to identify enhancer-promoter like interactions from Hi-C (chromosome conformation capture) data. These regulatory elements can potentially play vital roles as promoters and/or enhancers in appearance and exacerbation of the regulation of gene.s To evaluate the efficiency of the proposed method, we applied our proposed method and traditional methods on the Hi-C data from mice and compared together. Our results show that the interacting elements identified by our new method are more likely to be functional. The source code of the method is publicly available.

The present work sets out the evaluation of composite laminates through optimization objective functions. Genetic Algorithms (GA), as well as Simulated Annealing (SA), were performed in order to determine the optimal ply orientations of a fiber-reinforced polymer laminate for three given load cases: 1) in-plane loads, 2) combined moments, and 3) in-plane loads and combined moments. It searches the optimal orientation layup, which fulfills at the same time both the maximum strain criterion and the Tsai-Wu failure criterion. Construction of an objective function based on the strains and the stresses involves a minimization process to deformations and a maximization of the safety factor. For the first load case, the initial solution is [±45/0/90/±45]s, and the best solution is [(45/135)2/452]s. For the second load case, [-45/45/45/-45/0/90]s is the initial layup sequence, then the best solution obtained is [(45/-45)2/452]s, where plies at 0° and 90º are not necessary even when axial loads are applied. For the third study case, the original layup sequence is [0/45/-45/45/0/90]s; meanwhile, the best solution calculated is [21/24/145/140/45/49]s. An interesting observation is that each pair of layers has a 5º gap. The simulations show that the qualitative results from the GA are better than the SA, but with a significantly higher computational cost. These kinds of computational tools are expected to be used as a reference guide for an optimal fiber configuration with respect to the common orientations used when composite laminates are designed for a structural application.

With the engineering system becoming more and more complex, the uncertainty factors have a more and more profound influence on the reliability and security of the engineering system. In recent years, Reliability-Based Design Optimization (RBDO) has been studied extensively in complex engineering system design. The research on reliability optimization design considering stochastic uncertainty has been comprehensive and widely used. However, the reliability optimization design considering mixed uncertainty has the disadvantages of large computation and imprecise convergence. This study proposes an RBDO method based on Particle Swarm Optimization (PSO) and Simulated Annealing (SA) to overcome this challenge. In the method, PSO is used to solve the most probable point, while SA has excellent global optimization capability to acquire the global optimal solution. Finally, three examples are given to illustrate the advantages of the proposed method.

For the soil in different regions, the nutrient fertility contained in it is different, and the detection and zoning management of soil nutrients before tillage every year can improve grain yield. In this paper, an integrated learning strategy model based on black soil hyperspectral data is designed for rapid classification of organic matter content classification of black soil. Soil hyperspectral image dataset of Xiangyang Experimental Base was collected; by changing the internal structure of the stacking model, an LSVM-stacking model with (MLP, SVC, DTree, XGBl, kNN) five classifiers as the L1 layer was built, and the simulated annealing algorithm was used for hyperparameter optimization. Compared to other stacking models, the LSVM-stacking metrics are significantly improved. The accuracy rate of hyperparameter optimization is improved by 38.6515%, the accuracy rate of the independent test data set is 0.9488, and the comparison of individual learners can improve the recognition classification accuracy of label"1" to 1.0.

Bearings are widely used in various types of electrical machinery and equipment. As their core components, failures will often cause serious consequences . At present, most methods of parameter adjustment are still manual adjustment of parameters. This adjustment method is susceptible to prior knowledge and easy to fall into the local optimal solution, failing to obtain the global optimal solution and requires a lot of resources.Therefore, this paper proposes a new method of bearing fault diagnosis based on wavelet packet transform and convolutional neural network optimized by simulated annealing algorithm.The experimental results show that the method proposed in this paper has a more accurate effect in feature extraction and fault classification compared with traditional bearing fault diagnosis methods. At the same time, compared with the traditional artificial neural network parameter adjustment, this paper introduces the simulated annealing algorithm to automatically adjust the parameters of the neural network, thereby obtaining an adaptive bearing fault diagnosis method. To verify the effectiveness of the method, the Case Western Reserve University bearing database was used for testing, and the traditional intelligent bearing fault diagnosis method was compared. The results show that the method proposed in this paper has good results in bearing fault diagnosis. Provides a new way of thinking in the field of bearing fault diagnosis in parameter adjustment and fault classification algorithms

Vibration monitoring is a critical aspect of assessing the health and performance of machinery and industrial processes. This study explores the application of machine learning techniques, specifically the Random Forest (RF) classification model, to predict and classify chatter—a detrimental self-excited vibration phenomenon—during machining operations. While sophisticated methods have been employed to address chatter, this research investigates the efficacy of a simplified RF model. The study leverages simulated vibration data, bypassing resource-intensive real-world data collection, to develop a versatile chatter detection model applicable across diverse machining configurations. The feature extraction process combines time-series features and Fast Fourier Transform (FFT) data features, streamlining the model while addressing challenges posed by feature selection. By focusing on the RF model’s simplicity and efficiency, this research advances chatter detection techniques, offering a practical tool with improved generalizability, computational efficiency, and ease of interpretation. The study demonstrates that innovation can reside in simplicity, opening avenues for wider applicability and accelerated progress in the machining industry.

This study deals with vibrational and crystallographic aspects of the thermally induced transformation of serpentine-like garnierite into quartz, forsterite, and enstatite occurring at about 620 °C. Powder specimens of garnierite have been annealed in static air between room temperature and 1000 °C. The resulting products from the transformations detected based on thermogravimetric and differential thermal analysis, have been extensively characterized via microRaman spectroscopy, and X-ray diffraction. Our study shows that serpentine-like garnierite consists of a mixture of different mineral species. Furthermore, these garnierites and their composition can provide details based on the mineralogy and the crystalline phases resulting from the thermal treatment.

In this study, we address the formidable challenge of solving large-scale Max-Cut problems (MCP). We introduce a rapid computational procedure utilizing a hybrid 1-flip/r-flip local search heuristic. This innovative strategy significantly reduces the computational time required for MCP problems while consistently generating solutions of exceptional quality. The paper presents substantial computational insights, showcasing the effectiveness of our approach on very-large-scale Max-Cut instances with varying densities. Our proposed heuristic is rigorously evaluated by comparing its performance against a quantum annealing solver, leveraging a multi-start Tabu Search framework. The results underscore the potency of this unique combination as an efficient and effective solution for large-scale QUBO problems. Notably, our hybrid heuristic consistently delivers high-quality solutions within the stringent CPU time limits of 600 seconds, demonstrating its efficacy across Max-Cut instances ranging from 10,000 to 40,000 variables. This research contributes to advancing the state-of-the-art in large-scale QUBO problem-solving, offering a powerful and time-efficient approach with broad applicability.

The microstructure evolution during the cold rolling and subsequent annealing of Alloy 800H was investigated. Two distinct rolling methods, unidirectional rolling and cross-rolling, were intro-duced. Results show that better ductility was observed in the unidirectional rolling than in cross-rolling, whilst a higher volume fraction of large deformed grains was observed in the cross-rolled plates than in the unidirectionally rolled plates. Recrystallization occurred faster in plates from unidirectional rolling than from cross-rolling.

A statistical simulation is presented which reproduces the correlation obtained from EPR coincidence experiments without non-local connectivity. Defining spin under the quaternion group reveals hyper-helicity, a hitherto missed attribute of spin. Including this in the treatment, reveals two complementary properties: spin polarization and spin coherence. The former has a CHSH value of 2, and spin coherence has a CHSH = 1 giving CHSH = 3 for an EPR pair. The simulation here gives 2.995. We suggest that Nature has CHSH=3 being considerable more than predicted from quantum mechanics of $2\sqrt{2}$. There are no Local Hidden Variables. We suggest that quaternion spin is more fundamental than Dirac spin. A computer program which performs the simulation without non-local connectivity is described.

Quantum computers are invaluable tools to explore the properties of complex quantum systems. We show that dynamical localization of the quantum sawtooth map, a highly sensitive quantum coherent phenomenon, can be simulated on actual, small-scale quantum processors. Our results demonstrate that quantum computing of dynamical localization may become a convenient tool for evaluating advances in quantum hardware performances.

Ultra-short laser pulses (1030 nm/230 fs) were used to laser ablate surface of crystalline sapphire. Laser ablated patterns were annealed at high temperature 1500∘C. Surface reconstruction took place removing ablation debris field at the edges of ablated pits in oxygen flow. Partial reconstruction of ripples was also observed.

In fisheries monitoring, catch is assumed to be a product of fishing intensity, catchability, and availability, where availability is defined as the number or biomass of fish present and catchability refers to the relationship between catch rate and the true population. Ecological monitoring programs use catch per unit of effort (CPUE) to standardize catch and monitor changes in fish populations; however, CPUE is proportional to the portion of the population that is vulnerable to the type of gear that is used in sampling, which is not necessarily the entire population. Programs often deal with this problem by assuming that catchability is constant, but if catchability is not constant, it is not possible to separate the effects of catchability and population size using monitoring data alone. This study uses individual-based simulation to separate the effects of changing environmental conditions on catchability and availability in environmental monitoring data. The simulation combines a module for sampling conditions with a module for individual fish behavior to estimate the proportion of available fish that would escape from the sample. The method is applied to the case study of the well-monitored fish species Delta Smelt (Hypomesus transpacificus) in the San Francisco Estuary, where it has been hypothesized that changing water clarity may affect catchability for long-term monitoring studies. Results of this study indicate that given constraints on Delta Smelt swimming ability, it is unlikely that the apparent declines in Delta Smelt abundance are due to an effect of changing water clarity on catchability.

With an explosion of data in the nearly every domain, from physical and environmental sciences to econometrics and even social science, we have entered a golden era of time-domain data science. In addition to ever increasing data volumes and varieties of time-series, there's a plethora of techniques available to analyses them. Unsurprisingly, machine learning approaches are very popular. In environmental sciences (ranging from climate studies to space weather/solar physics), machine learning (ML )and deep learning (DL) approaches complement the traditional data assimilation approaches. In solar and astrophysics, multiwavelength time-series or lightcurves along with observations of other messengers like gravitational waves provide a treasure trove of time-domain data for ML/DL approaches for modeling and forecasting. In this regard, deep learning algorithms such as recurrent neural networks (RNNs) should prove extremely powerful for forecasting as it has in several other domains. Such methods agnostic of the physics can only predict transient flares that are represented in the original distribution trained on (eg. coloured noise fluctuations) and not special, isolated episodes (eg. a one-off outburst like a major coronal mass ejection) potentially distinguishing them. Therefore it is vital to test robustness of these techniques ; here we attempt to make a small contribution to this by exploring sensitivity of RNNs with some rudimentary experiments. We test the performance of a very successful class of RNNs, the Long Short Term Memory (LSTM) algorithms with simulated lightcurves. As an example, we focus on univariate forecasting of time-series (or lightcurves) characteristic certain variable astrophysical objects (eg. active galactic nuclei or AGN). Specifically, we explore the sensitivity of training and test losses to key parameters of the LSTM network and data characteristics namely gaps and complexity measured in terms of number of Fourier components. We find that typically, the performances of LSTMs are better for pink or flicker noise type sources. The key parameters on which performance is dependent are batch size for LSTM and the gap percentage of the lightcurves. While a batch size of $10-30$ seems optimal, the most optimal test and train losses are under $10 \%$ of missing data for both periodic and random gaps in pink noise. The performance is far worse for red noise. This compromises detectability of transients. Thus, we show that generative models (time-series simulations) are excellent guides for use of RNN-LSTMs in building forecasting systems

Estimating ground surface PM2.5 with fine spatiotemporal resolution is a critical technique for exposure assessments in epidemiological studies of its health risks. Previous studies have utilized monitoring, satellite remote sensing or air quality modeling data to evaluate the spatiotemporal variations of PM2.5 concentrations, but such studies rarely combined these data simultaneously. We develop a three-stage model to fuse PM2.5 monitoring data, satellite-derived aerosol optical depth (AOD) and community multi-scale air quality (CMAQ) simulations together and apply it to estimate daily PM2.5 at a spatial resolution of 0.1˚ over China. Performance of the three-stage model is evaluated using a cross-validation (CV) method step by step. CV results show that the finally fused estimator of PM2.5 is in good agreement with the observational data (RMSE = 23.00 μg/m^3 and R2 = 0.72) and outperforms either AOD-retrieved PM2.5 (R2 = 0.62) or CMAQ simulations (R2 = 0.51). According to step-specific CVs, in data fusion, AOD-retrieved PM2.5 plays a key role to reduce mean bias, whereas CMAQ provides all-spacetime-covered predictions, which avoids sampling bias caused by non-random incompleteness in satellite-derived AOD. Our fused products are more capable than either CMAQ simulations or AOD-based estimates in characterizing the polluting procedure during haze episodes and thus can support both chronic and acute exposure assessments of ambient PM2.5. Based on the products, averaged concentration of annual exposure to PM2.5 was 55.75 μg/m3, while averaged count of polluted days (PM2.5 > 75 μg/m3) was 81, across China during 2014. Fused estimates will be publicly available for future health-related studies.

In the present study, a nanostructured FeAl coating was prepared by cold spraying of ball milled powder. Annealing treatment was applied to the coating to investigate its effect on the microstructure, phase structure and microhardness of the cold-sprayed nanostructured FeAl coating. The results showed that the FeAl phase was kept unchangeable when the coating annealed at the temperature above 500oC. Annealing temperature significantly influenced the microstructure and microhardness of cold-sprayed FeAl coating. With raising annealing temperature, the lamellar structure in the as-sprayed coating disappeared and a dense coating microstructure with fully bonding of deposited particles at their interfaces was achieved after annealing at 950oC. Nanograin growth of the FeAl phase occurred at an annealing temperature higher than 800oC. The microhardness of cold-sprayed FeAl coating remained about 400 Hv0.1 at the annealing temperature below 800oC and decreased to 300 Hv0.1 at 1100oC.

The radiation-induced optical absorption at 1.5-5.5 eV (up to the beginning of fundamental absorption) has been analyzed in CVD diamond disks exposed to 231-MeV 132Xe ions with four fluences from 1012 to 3.81013 cm-2. The 5-mm diameter samples (thickness 0.4 mm) were prepared by Diamond Materials, Freiburg (Germany), average grain size at growth site was around 80 m, the range of xenon ions was R= 11.5 m. The intensity of several bands grows with ion fluence thus confirming radiation-induced origin of the defects responsible for these bands. The recovery of radiation damage has been investigated via isochronal (stepwise) thermal annealing procedure up to 650°C, while all spectra were measured at room temperature. Based on these spectra, the annealing kinetics of several defects, in particular carbon vacancies (GR1 centers with a broad band 2 eV) and complementary C-interstitial-related defects ( 4 eV), as well as vacancies located nearby nitrogen substitutional atoms (narrow bands around 2.5 eV) have been constructed. The experimental kinetics have also been analyzed in terms of the diffusion-controlled bimolecular reactions. The migration energies of tentatively interstitial atoms (mobile components in recombination process) are obtained, their dependence on the irradiation fluences is discussed.

In this paper, in order to provide proper parameters for the preparation of semi-solid billets, the semi-solid annealing of hot-rolled 2A14 Al alloy was investigated. The microstructure was characterized by X-ray diffraction (XRD), scanning electron microscope (SEM) with X-ray energy dispersive spectrometer (EDS) and electron backscattered diffraction (EBSD), scanning transmission electron microscope (STEM). XRD results show that with the increase of temperature, equilibrium θ-Al2Cu gradually dissolved in the matrix. The EDS results of SEM and STEM show that there were coarse θ-Al2Cu phase, ultra-fine precipitate Al(MnFeSi) or (Mn, Fe)Al6 phase and atomic clusters in the microstructure. EBSD results show that the recrystallization mechanism was dominated by continuous static recrystallization (CSRX), the homogeneous nucleation occurred when the sample was heated to near solidus temperature, and CSRX happened in the semi-solid temperature. In the process of recrystallization, the micro-texture changed from preferred orientation to random orientation. A variety of experimental results show that static recrystallization (SRX) occurred at semi-solid temperature due to the blocking effect of atomic clusters on dislocation slip and the Zener drag effect of fine precipitates on low angle grain boundaries (LAGBs) disappeared with melting at semi-solid temperature.

By using hydrogen quench continuous annealing technology, Stelco Inc. has developed a suite of Advanced High Strength Steel (AHSS) grades with tensile strength greater than 1000MPa to meet standard automotive specifications and for unique customer requirements. These grades were optimized by correlating chemical composition and processing parameters with microstructures and mechanical properties. Dual-Phase 980 (Stelco trademarked STELMAXTM 980DP), Multi-Phase 1180 (STELMAXTM 1180MP), Martensitic Steel 1300 (STELMAXTM 1300M) and 1500 (STELMAXTM 1500M) products met strength and formability requirements with excellent flatness and surface quality. Hydrogen quench continuous annealing technology not only ensures all developed AHSS grades have consistent mechanical properties across the entire strip length (from strip head to tail) and width (from edge to edge), but also produces high product yield compared with other continuous annealing processes.

The research focuses on the electrochemical behavior of TiVN trilayers in a liquid that simulates a physiological environment (blood plasma). TiVN films are obtained through Physical Direct Current Vapor (PVD) Deposition on titanium bases, depositing TiN and VN layers as an intermediate layer during the procedure. Impedance measurements are carried out before and during the wear test to determine the impact on the sample. The results show that the TiVN trilayer enhances corrosion resistance according to the time of exposure to the electrolyte. Initially, the load resistance (Rct) was 10.50 Ohms, but after 16 days, the Rct rose markedly to 13.87 Ohms, signaling an advance in corrosion resistance, a valuable property for wide applications.

We recently reported that refocusing attention between temporal and spatial tasks becomes more difficult with increasing age, which could impair daily activities such as driving (Callaghan et al., 2017). Here we investigated the extent to which difficulties in refocusing attention extend to naturalistic settings such as simulated driving. 118 participants in five age groups (18-30; 40-49; 50-59; 60-69; 70-91 years) were compared during simulated driving, where they switched from a spatially focal yet temporally complex task (braking due to traffic ahead) to a spatially more distributed task (reading a motorway road sign). Sequential-Task (switching) performance was compared to Single-Task performance (road sign only) to calculate age-related switch-costs. Electroencephalography was recorded in 34 participants (17 in the 18-30 and 17 in the 60+ years groups) to explore age-related changes in the neural oscillatory signatures of refocusing attention while driving. We indeed observed age-related impairments in attentional refocusing, evidenced by increased switch-costs in response times and by deficient modulation of theta and alpha frequencies. Our findings highlight virtual reality (VR) and Neuro-VR as important methodologies for future psychological and gerontological research.

This study examines the effects of the δ phase and annealing twins on the hardness, Charpy impact toughness, and tensile properties of Inconel 718 fabricated using L-PBF. Two heat treatment methods, involving solid solution and precipitation hardening, were utilized. The δ phase was formed through solid solution heat treatment at 980C for 1 hour while annealing twins were generated at 1100C for 3 hours. After precipitation hardening, specimens with a higher concentration of  precipitates exhibited increased ultimate tensile strength (13%), yield strength (27%), and hardness (12%) compared to those with annealing twins. This can be attributed to the smaller grain size, subgrains, and δ precipitates, which contribute to the differences in mechanical strength. On the contrary, specimens with annealing twins showed significantly higher impact toughness (4 times) and ductility (twice) than those with δ precipitates. This is caused by the formation of  precipitates, which serve as sites for void formation and crack propagation, leading to a decrease in plasticity due to lattice mismatches with the matrix. Microstructural, compositional, phase, crystallographic, and fractographic analyzes were performed using OM, SEM, TEM and XRD techniques to identify the factors responsible for the variations in the measurements. The results demonstrate that the heat treatment method involving annealing twins significantly improves the ductility of Inconel 718 while maintaining the required mechanical strength.

This study utilized electron back scattered diffraction (EBSD) and X-ray diffraction (XRD) to investigate the impact of inter-annealing temperature and heating rate of final annealing on the microstructure of high-voltage anode aluminum foils. The findings indicate that the formation of cube texture in the final products is significantly influenced by the inter-annealing temperature, as low inter-annealing temperatures retain a considerable amount of deformation stored energy, providing a strong driving force for nucleation. The cube texture is observed to deviate from the ideal position at lower inter-annealing temperatures. Additionally, an increase in heating rate during final annealing leads to a gradual decrease in the fraction and grain size of recrystallization. This is attributed to the fact that a higher heating rate (below the critical heating rate) reduces the time available for grain boundary migration, thereby slowing the recrystallization process.

A reinforcement learning algorithm is proposed to improve the accuracy of short-term load forecasting (STLF) in this article. The proposed model integrates radial basis function neural network (RBFNN), support vector regression (SVR), and adaptive annealing learning algorithm (AALA). In the proposed methodology, firstly, the initial structure of RBFNN is determined by using SVR. Then, an AALA with time-varying learning rates is used to optimize the initial parameters of SVR-RBFNN (AALA-SVR-RBFNN). In order to overcome the stagnation for searching optimal RBFNN, a particle swarm optimization (PSO) is applied to simultaneously find promising learning rates in AALA. Finally, the short-term load demands are predicted by using the optimal RBFNN. The performance of the proposed methodology is verified on the actual load dataset from Taiwan Power Company (TPC). Simulation results reveal that the proposed AALA-SVR-RBFNN can achieve a better load forecasting precision as compared to various RBFNNs.

This study was carried out to evaluate the effect of exogenous proline on growth, biochemical responses, and plant recovery of drought-stressed oilseed rape plants after renewed irrigation. The experiment was conducted under controlled laboratory conditions. After 21 days of cultivation, 3-4 leaf stage seedlings were sprayed with proline (1 mM), then subjected to prolonged drought stress for 8 days to achieve a severe water deficit, then irrigation was resumed and recovery was assessed after 4 days. The results show that exogenous application of proline reduced drought-induced growth inhibition of seedlings while maintaining relative water content (RWC) and growth parameters closer to those of irrigated plants. Proline had a positive effect on chlorophyll accumulation and membrane permeability while decreasing ethylene, H2O2, and MDA levels. Moreover, after 4 days of recovery, the H2O2 content of the proline-treated plants was significantly lower (2-fold) and the MDA content was close to that of continuously irrigated plants. Thus, all these biochemical reactions influenced plant survival: after drought + proline treatment, the number of surviving plants was 2 times higher than that of drought-treated plants. The findings show that exogenous proline has antioxidant, osmotic, and growth-promoting properties that improve the drought tolerance of winter oilseed rape plants and is, therefore, beneficial for drought adaptation in oilseed rape.

The study presents the effect of annealing process parameters on the microstructure, hardness and strain hardening coefficients i.e., the strength coefficient c and the strain hardening exponent n, of 42CrMo4 steel. Seven selected annealing time-temperature schemes are examined for superior steel formability in cold metal forming conditions. The c and n coefficients are first determined in experimental upsetting of annealed samples and then used in FEM simulations of the upsetting process. The results demonstrate that the strain hardening coefficients (c and n) depend on the employed annealing scheme. Compared to the as-received sample, the annealing process reduces the true stress and effectively decrease the hardness of 42CrMo4 steel, improves microstructural spheroidization and, consequently, facilitates deformability of this material. The annealing schemes relying on heating the material to 750 °C and its subsequent slow cooling lead to the highest decrease in hardness ranging from 162 to 168HV. Results obtained with the SEM-EDS, LOM and XRD methods lead to the conclusion that the employed heat treatment schemes cause the initial ferritic-pearlitic microstructure to develop granular and semi-lamellar precipitation of cementite enriched with Mo and Cr in the ferrite matrix. In addition, the annealing process affects the growth of α-Fe grains. The highest cold hardening rate, and thus formability, is obtained for the annealing scheme producing the lowest hardness. The results of FEM simulations are positively validated by experimental results. Obtained results are crucial for further numerical simulations and experimental research connected with developing new cold metal forming methods for producing parts made of 42CrMo4 steel.

Fabrics treated to repel water, superhydrophobic, and water and oil, superamphiphobic, have numerous industrial and consumer-level benefits. These coatings are typically non-permanent. This is largely due to chemical or physical changes of the coating to prolonged exposure to relatively harsh environments. To develop more durable fabric treatments for specific applications, it is necessary to measure the extent to which the treated fabrics retain their low-wettability after being subjected to controlled aggressive environmental conditions. In this study, plain weave fabrics made from polyester filaments and coated with silicone nanofilaments in-solution were exposed to aerodynamic icing conditions. The coated fabrics showed superhydrophobic behavior, or superamphiphobic for those that were fluorinated. The wettability of the fabrics was progressively evaluated by contact angle and roll-off-angle measurements. The fabrics were able to maintain their low-wettability characteristics after exposure to water droplet clouds at airspeeds up to 120 m/s, despite damage to the silicone nanofilaments, visible through scanning electron microscopy.

Wind turbine plants are complex dynamic and uncertain processes driven by stochastic inputs and disturbances, as well as different loads represented by gyroscopic, centrifugal, and gravitational forces. Moreover, as their aerodynamic models are nonlinear, both modelling and control become challenging problems. On one hand, high-fidelity simulators should contain different parameters and variables in order to accurately describe the main dynamic system behaviour. Therefore, the development of modelling and control for wind turbine systems should consider these complexity aspects. On the other hand, these control solutions have to include the main wind turbine dynamic characteristics without becoming too complicated. The main point of this paper is thus to provide two practical examples of development of robust control strategies when applied to a simulated wind turbine plant. Experiments with the wind turbine simulator and the Monte–Carlo tools represent the instruments for assessing the robustness and reliability aspects of the developed control methodologies when the model-reality mismatch and measurement errors are also considered. Advantages and drawbacks of these regulation methods are also highlighted with respect to different control strategies via proper performance metrics.

Bismuth sodium titanate thin films (BNT) were deposited on Pt/SiN substrates by Sol-Gel spin coating technique under O2 atmosphere. Microstructural, structural, and electrical properties of the obtained film were investigated. Scanning electron microscopy and atomic force microscopy micrographs were used to analyze the microstructure of the films. Furthermore, EDX analysis revealed a Na-deficient composition for the obtained film. X-ray diffraction and Raman spectroscopy allowed the identification of a pure perovskite BNT phase. Dielectric, ferroelectric, and leakage current measurements revealed good frequency stability of the dielectric constant and dielectric losses for BNT thin film. The results are discussed in terms of Na-deficiency effects on the defect structure of BNT. Further, the film showed attractive electrostatic energy storage properties with energy density that exceeds 1.04 J/cm3 under E = 630 kV/cm.

Thin-wall heat pipe is an efficient heat transfer component, which has been widely used in the field of heat dissipation of high-power electronic equipment in recent years. In this study, the orange peel morphology defect of thin-wall heat pipes after bending deformation was analyzed both for the macro 3D profile and for the micro-formation mechanism. The results show that after high temperature sintering treatment, the matrix grains of heat pipe are coarsened seriously and formed a strong Goss texture, while a certain annealing twins with the unique Copper orientation are retained. The distribution of Schmid factor value subjected to the uniaxial stress indicate the inhomogeneity of intergranular deformation exist among the annealing twins and matrix grains. The annealing twin exhibit a “hard-oriented” component during the deformation; thus, it plays a role as barrier and hinder the slipping of dislocation. As the strain accumulates, part of the annealing twins may protrude from the surface of heat pipe, forming a large-scale fluctuation of the surface as the so called the “orange peel” morphology. The 3D profile shows the bulged twins mostly perpendicular to the drawing direction, with about 200-300μm in width and 10-20μm in height.

Cyclists are one of the main categories of road users particularly exposed to accident risk. The increasing use of this ecological means of transport requires a specific assessment of cyclist safety in terms of traffic flow and human factors. In this study particular visual tracking tool has been used in order to highlight not only the main critical points of the infrastructure, where a high level of distraction is recorded but also the various interactions with different road users (pedestrians, vehicles, buses, wheelchairs, cyclists). In order to confirm the critical points of the infrastructure and the trend of workload, a similar circuit was reproduced in a bicycle simulator, which also allowed a meaningful comparison of cycling behaviour. The cycling performance was also evaluated both from an objective point of view, with the count of frames related to each category of visualization, and a subjective one, through the questionnaires. The results show the crossing as a critical point because of only 4/3% fixation for both simulated and real tests in order to confirm the significance of the comparison between the two experiments. The high attention rate resulting from frame-by-frame analysis also points to a clear difference in the perception of users, who feel with a low workload.

Social networks have become the scenario with the greatest potential for the circulation of disinformation, hence there is a growing interest in understanding how this type of information is spread, especially in relation to the mechanisms used by disinformation agents such as bots, trolls, among others. In this scenario, the potential of bots to facilitate the spread of disinformation is recognised, however, the analysis of how they do this is still in its initial stages. Taking into consideration what was previously stated, this paper aimed to model and simulate scenarios of disinformation propagation in social networks caused by bots based on the dynamics of this mechanism documented in the literature. For achieving the purpose, System dynamics was used as the main modelling technique. The results present a mathematical model, as far as disinformation by this mechanism is concerned, and the simulations carried out against the increase in the rate of activation and deactivation of bots. Thus, the preponderant role of social networks in controlling disinformation through this mechanism, and the potential of bots to affect citizens, is recognised.

The vertebrate basal ganglia are thought to play an important role in action selection—the resolution of conflicts between alternative motor programs. The effective operation of basal ganglia circuitry is also known to rely on appropriate levels of tonic dopamine transmission. We show that when the tonic level of simulated dopamine in a robotic model of the basal ganglia is significantly reduced or increased, relative to an effective operating baseline, a variety of behavioral outcomes are observed that provide interesting comparisons with the results of human and animal studies. The main findings were that progressive reductions in the levels of simulated dopamine caused a slowing of the robot’s movements and eventually an inability to initiate movement. These states were partially relieved at increased salience levels (stronger sensory/motivational input). Conversely, increased levels of simulated dopamine could cause distortion of the robot’s motor acts through partially-expressed motor activity relating to losing actions; this could also lead to increased frequency of switching between behaviors. Levels of simulated dopamine that were either significantly lower or higher than baseline could cause changes to the timing of behavior switching that could cause a loss of behavioral integration, sometimes leaving the robot in a ‘behavioral trap’. That some analogous traits are observed in animals and humans affected by dopamine dysregulation suggests that embodied (robotic) models could prove useful in understanding the role of dopamine neurotransmission in basal ganglia function and dysfunction. That the effects of simulated dopamine on robot action selection were partially, but not fully, predictable from the selection properties of the non-embodied basal ganglia model, also points to the added value of using robotic models to explore the relationship between brain activity and behavior.

The corrosion resistance of two cast CoCr based alloys, with different amounts of chromium and with different alloying elements in the bulk composition of the alloy, was assessed. Herewith, we investigated the corrosion behavior of Co21Cr8Mo7W and Co29Cr7W by open circuit potential (OCP), potentiodynamic polarization (PP) and electrochemical impedance spectroscopy (EIS) in 0.1 M phosphate buffer solution (PBS) at 37°C for long time immersion. After 1000 hours of immersion, the corrosion current density (icor), estimated from anodic polarization tests, is lower for Co21Cr8Mo7W (i.e. 49 nA cm-2) alloy compared to Co29Cr7W alloy (180 nA cm-2). As regards the corrosion potential (Ecor), a nobler value was observed for Co21Cr8Mo7W (i.e. -59 mV vs. Ag/AgCl) compared to Co29Cr7W (i.e. -114 mV vs. Ag/AgCl). These findings suggest a better corrosion resistance of the film formed on the alloy containing lower amount of Cr and two alloying elements, namely Mo and W. These results are promising ones in terms of medical applications because they open new strategies in obtaining alloys with lower content of chromium and with higher protective properties against corrosion attack.

Novel model of biodegradable PHA copolymer films preparation was applied to evaluate biodegradability of various PHA copolymers and discuss its biomedical applicability. In this study, we illustrate the potential biomaterial degradation rate affectability by manipulation of monomer composition via controlling biosynthetic strategies. Within the experimental investigation, we have prepared two different copolymers of 3-hydroxybutyrate and 4-hydroxybutyrate – P(3HB-co-36 mol.% 4HB) and P(3HB-co-66 mol.% 4HB), by cultivating thermophilic bacterial strain Aneurinibacillus sp. H1 and further investigated its degradability in simulated body fluids (SBFs). Both copolymers revealed faster weight reduction in synthetic gastric juice (SGJ) and artificial colonic fluid (ACF) than simple homopolymer P3HB. In addition, degradation mechanisms differed across tested polymers, according to SEM micrographs. While incubated in SGJ, samples were fragmented due to fast hydrolysis sourcing from substantially low pH, which suggest abiotic degradation as the major degradation mechanism. On the contrary, ACF incubation indicated obvious enzymatic hydrolysis. Further, no cytotoxicity of the waste fluids was observed on CaCO-2 cell line. Based on these results in combination with high production flexibility, we suggest P(3HB-co-4HB) copolymers produced by Aneurinibacillus sp. H1 as very auspicious polymers for intestinal in vivo treatments.

Almond is worldwide consumed and renowned as a valuable healthy food. In spite of this, it is also a potent source of allergenic proteins able to trigger several mild to life-threatening immunoreactions. Food processing proved to alter biochemical characteristics of proteins, thus affecting the respective allergenicity. In this paper we investigated the effect of autoclaving, preceded or not by a hydration step, on the biochemical and immunological properties of almond proteins. Any variation in the stability and immunoreactivity of almond proteins extracted from the treated materials, were evaluated by total protein quantification, ELISA assay and protein profiling by electrophoresis-based separation (SDS-PAGE). The autoclaving alone was found to weakly affect almond proteins stability, despite what observed for the combination of hydration and autoclaving, which resulted in a loss of approximately 70% of total protein content compared to untreated sample, and in a final negligible immunoreactivity, as well. The final SDS-PAGE protein pattern recorded for almonds hydrated and autoclaved disclosed significant changes. In addition, the same samples were further submitted to in vitro simulated gastro-duodenal (GI) digestion to evaluate potential changes induced by these processing on allergens digestibility. Digestion products were identified by HPLC-HRMS/MS analysis followed by software-based data mining, and complementary information were provided by analyzing the proteolytic fragments lower that 6 kDa in size. The autoclave based treatment was found not to alter the allergens digestibility, whereas an increased susceptibility to proteolytic action of digestive enzymes was observed in almonds subjected to the combination of prehydration and autoclaving. Finally, the residual immunoreactivity of the GI resistant peptides was investigated in-silico by bioinformatic tools, confirming that by following both approaches, no epitopes survived the almond digestion, thus demonstrating the potential effectiveness of these treatments to reduce almond allergenicity.

Comparison of the influence of conditioning temperature of microspheres made of medical grade poly(L-lactide) (PLLA) and polylactide with 4wt.% of D-lactide content (PLA), on its thermal and structural properties is presented. The microspheres were fabricated by solid-in-oil-in-water method for application in additive manufacturing. The microspheres were annealed below glass transition temperature (Tg), above Tg but below onset of cold crystallization, and at two temperatures selected from the range of cold crystallization corresponding to crystallization of α’ and α form of poly(L-lactide) respectively, i.e., at 40°C, 70°C, 90°C and 120°C, in order to verify the influence of conditioning temperatures on sinterability of microspheres set as sintering window (SW). Based on differential scanning calorimetry measurements SW of microspheres were evaluated with consideration of existence of cold crystallization and reorganization of crystal polymorph. The results indicate that the conditioning temperature influence on availability and range of SW that depending on the D-lactide presence. We postulate the need for an individual approach for polylactide powders in determining the SW as a temperature range free of any thermal events. Moreover, other core powder characteristic, such as residual solvent content, morphology, particle size distribution, powder flowability and thermal conductivity, as a key property for successful laser sintering, are characterized. The microspheres are close to sphere and the size of microspheres are below 100 µm. Residual solvents content decreases with the increase of annealing temperature. The thermal conductivity is 0.073 W/mK and 0.064 W/mK for PLA and PLLA microspheres, respectively, and it depends on the spherical shape of the microspheres. Furthermore, the WAXD studies prove that an increase in the conditioning temperature causes a slight increase in crystallinity degree for PLLA microspheres and clear increase in crystallization for PLA microspheres.

In this paper were analyzed the effects of double reduction and annealing during rolling process on texture evolution in an ultrathin sheet of low carbon steel. Experimental samples were obtained from each process stage. EBSD technique and correlated tools as orientation density functions and pole figures were used to analyze the microstructural changes and the texture. Results show that {111} recrystallized grains were formed during process, reducing dramatically gamma-fibre texture intensity and generating an adequate finished product for deep die stamping.

Marked changes in temperature, pH, dissolved oxygen (DO) content, and nutrient content typically occur in marine thermoclines, which are key factors that affect the corrosion of metals. Offshore platforms have required marine metals to be exposed to deep-sea environments and have thus increased their penetration into the marine thermocline. This study investigates the galvanic corrosion of E690 steel in a marine thermocline using a simulated marine thermocline (SMT). Specifically, the corrosion of E690 steel was analyzed using the wire beam electrode (WBE) technique, linear polarization (LP), corrosion morphology, and weight loss measurement. Results indicated that the SMT had a stable multilayer structure, and the variations of temperature, DO, pH and nutrient concentration in the SMT were similar to those in the natural marine thermocline. Galvanic corrosion occurred after the intrusion of E690 steel into the marine thermocline. The driver of galvanic corrosion was the of E690 steel at various depths of the marine thermocline. The Ecorr of E690 steel was influenced by the temperature, pH and DO of seawater, and the order was DO >> T > pH. The continuous reduction of Ecorr with depth contributed to the large-scale galvanic corrosion, and the oscillation variation of Ecorr with depth was the reason for small-scale galvanic corrosion. The primary anodic regions of galvanic corrosion were located in the area with the fastest temperature variation in the thermocline. The proportion of galvanic corrosion in the average corrosion rate could increase up to approximately 80% in the stable anodic region. There were many deep corrosion pits in the long-term and stable anodic region of galvanic corrosion.

Nanoindentation load-depth (P-h) plots is the basis for determination of mechanical properties of the samples and is especially vital for thin coatings deposited on substrates of various mechanical makeup from amorphous-brittle (borosilicate glass) to Silicon (having different crystallographic texture) to ductile substrates like stainless steel as well other aspects like indenter tip shape. The elastic-plastic response by simulated P-h plots as per modified empirical relations have been presented. The outcomes of this computational studies enlighten the database on the P-h plots for various coating/substrate systems and shall aid in the analysis of experimental P-h plots obtained,

Different kinds of freshwater fish soups show a diverse range of health functions, due to their different nutritional substances and corresponding bioactivities. Crucian carp soup and snakehead soup have different dietotherapy functions, crucian carp soup is suitable for lactating women and snakehead soup is suitable for postoperative patients. In the current study, the changes of nutrient profiles in the different fish soups, such as chemical composition, free amino acids, mineral and fatty acid contents, were investigated. The antioxidant activities of the fish soups were evaluated by using the DPPH radical scavenging activity, the ferrous ion chelating activity, the hydroxyl radical-scavenging activity and the reducing power effect. In order to learn the theoretical basis of the potential role fish soup plays in diet therapy functions after being digested by the human body, the nutrient profiling and bioactivities of the fish soup samples after simulated gastrointestinal digestion were also explored. The intensive profiles of nutritional composition and antioxidant activities of these two kinds of fish soups were expected to partly provide the theoretical basis of therapeutic effects.

An ultraviolet (UV) nanosecond pulsed laser with a wavelength of 355 nm was applied to anneal amorphous indium-gallium-zinc oxide (a-IGZO) thin-film transistors (TFT) at various laser beam powers ranging from 0 to 280 mW. Laser irradiation was selectively carried out on the a-IGZO channel area using the beam scanning method after the a-IGZO TFT was formed through indium-tin oxide (ITO) electrode patterning and a subsequent lift-off process. After laser annealing, negative shifts in the threshold voltages and enhanced on-currents were observed at laser-beam powers ranging from 54 to 120 mW. No meaningful parameters were investigated for laser beams higher than 200 mW. By extracting the energy band gap and work function of a-IGZO from the transmittance and ultraviolet photoelectron spectroscopy (UPS) results, the ITO electrode/a-IGZO channel energy band structures were established under different laser annealing conditions, and the electron injection mechanism from the ITO to the a-IGZO channel was analyzed and optimized at a laser beam power of 120 mW. The results show that the electrical characteristics of the a-IGZO TFTs can be improved without any heat damage to the substrate because of the selective annealing process.

Abstract: This study aimed to compare the effcacy of robot-assisted and manual cannula insertion in simulated big-bubble deep anterior lamellar keratoplasty (DALK). Novice surgeons with no prior experience in performing DALK were trained to perform the procedure using manual or robot-assisted techniques. The results showed that both methods could generate an airtight tunnel in the porcine cornea, and result in successful generation of a deep stromal demarcation plane representing suffcient depth reached for big-bubble generation in most cases. However, the combination of intraoperative OCT and robotic assistance received a signifcant increase in the depth of achieved detachment in non-perforated cases, comprising a mean of 89% as opposed to 85% of the cornea in manual trials. This research suggests that robot-assisted DALK may offer certain advantages over manual techniques, particularly when used in conjunction with intraoperative OCT.

The widely adopted temperature for solid solution heat treatment (ST) for the conventionally fabricated Inconel 718 is 1100 °C for a hold time of 1 h or less. This ST scheme is however not enough to dissolve Laves and annihilate dislocations completely in samples fabricated with Laser metal powder bed fusion (L-PBF) additive manufacturing (AM)-Inconel 718. In spite this, the highest hardness obtained after aging for ST temperatures (970 - 1250 °C) is at 1100 °C/1h [1]. The unreleased residual stresses in the retained lattice defects are potentially affecting other properties of the material. Hence, this work aims to investigate if a longer hold time of ST at 1100 °C will lead to complete recrystallization while maintaining the strength after aging or not. For this study, L-PBF-Inconel 718 samples were ST at 1100 °C at various hold times (1, 3, 6, 9, 16 or 24 h) and aged to study the effects on microstructure and hardness. In addition, a sample was directly aged to study the effects of bypassing ST. The samples (ST and aged) gain hardness by 43 – 49 %, depending on hold time. A high density of annealing twins evolved during 3 h of ST and the quantity only slightly varies for longer ST.

Here we report the effect of substrate, sonication process, and post-annealing on the structural, morphological, and optical properties of ZnO thin films grown in the presence of isopropyl alcohol (IPA) at temperature 30 – 65 ℃ by successive ionic layer adsorption and reaction (SILAR) method on both soda lime glass (SLG) and Cu foil. The X-ray diffraction (XRD) patterns confirmed the preferential growth thin films along (002) and (101) plane of wurtzite ZnO structure while grown on SLG and Cu foil substrate respectively. Both XRD and Raman spectra confirmed the ZnO and Cu-oxide phases of the deposited films. Scanning electron microscope (SEM) image of the deposited films shows compact and uniformly distributed grains for samples grown without sonication while using IPA at temperature 50 and 65 ℃. The post-annealing treatment improves the crystallinity of the films, further evident by XRD and transmission and reflection results. The estimated optical bandgaps are in the range of 3.37-3.48 eV for as-grown samples. Results revealed that high-quality ZnO thin films could be grown without sonication using IPA dispersant at 50 ℃, which is much lower than the reported results using the SILAR method. This study suggests that in the presence of IPA, the SLG substrate results in better c-axis oriented ZnO thin films than that of DI water, ethylene glycol, propylene glycol at the optimum temperature of 50 ℃. Air-annealing of the samples grown on Cu foils induced the formation of Cu_xO/ZnO junctions which is evident from the characteristic I-V curve including the structural and optical data.

This article presents a novel computational approach to visualizing memristor dynamics within a simulated neural network. Memristors, known for their ability to emulate synaptic plasticity due to their variable resistance characteristics, are key components in neuromorphic computing and hold potential for advancing our understanding of neural processes. Our study introduces a sophisticated memristor model that incorporates non-linear resistance changes, simulating the complex behavior of synaptic connections in a neural network.The neural network, consisting of multiple interconnected neurons with memristor-based synapses, is subjected to a series of electrical stimuli. Each memristor's resistance is modulated in response to the applied voltage, mimicking the synaptic weight adjustments that occur during learning and memory formation in biological neural networks. To effectively illustrate these changes, we employ a high-contrast color mapping scheme, where the varying resistance of each memristor is represented by distinct colors, providing a clear and intuitive visualization of synaptic modifications over time.Our simulation runs through multiple iterations, demonstrating how synaptic weights evolve in response to different input patterns. The use of an extended voltage range and increased scaling factors ensures pronounced changes in memristance, enhancing the visibility of synaptic adaptations. The resulting visualizations offer a compelling representation of how memristors can mimic the dynamic nature of biological synapses, contributing to the field of neuromorphic engineering and deepening our comprehension of neural mechanisms underlying learning and memory.This work not only showcases the potential of memristors in simulating neural behavior but also provides a valuable educational tool for illustrating complex concepts in neuroscience and neuromorphic computing. The insights gained from this study pave the way for further exploration into the development of advanced neural network models and the design of memristor-based computing systems.

Speckle noise reduction is an important area of research in the field of ultrasound image processing. Several algorithms for speckle noise characterization and analysis have been recently proposed in the area. Synthetic ultrasound images can play a key role in noise evaluation methods as they can be used to generate a variety of speckle noise models under different interpolation and sampling schemes, and can also provide valuable ground truth data for estimating the accuracy of the chosen methods. However, not much work has been done in the area of modelling synthetic ultrasound images, and in simulating speckle noise generation to get images that are as close as possible to real ultrasound images. An important aspect of simulated synthetic ultrasound images is the requirement for extensive quality assessment for ensuring that they have the texture characteristics and gray-tone features of real images. This paper presents texture feature analysis of synthetic ultrasound images using local binary patterns (LBP) and demonstrates the usefulness of a set of LBP features for image quality assessment. Experimental results presented in the paper clearly show how these features could provide an accurate quality metric that correlates very well with subjective evaluations performed by clinical experts.

ABSTRACT The work is focused on determining the energy transfer from EV’s to grid for different operating conditions. The study has been simulated on a scaled model and later validated through experimental tests on batteries of 20 kWh, 40 kWh, 60 kWh and 80 kWh for EV’s energy rates from 130 Wh/km to 180 Wh/km. Tests have been developed to evaluate the energy transfer from driving distance between 0 and 50 km. Results have proved there is a linear dependence between energy transfer and energy rate. Experimental and simulated values have been correlated showing a 99.6% accuracy. The ratio of energy transfer to battery energy capacity depends not only on this latter parameter, but also on the energy rate of the electric vehicle. Experimental tests have shown a variation from a minimum transfer ratio of 54.1% for the highest electric vehicle energy rate and lowest battery energy capacity and power transfer to grid rate to a maximum of 88.6% for the highest power transfer to grid rate and battery energy capacity and lowest electric vehicle energy rate.

Digital twins are gaining in popularity for simulating complex natural and urban environments. In this context, accurate segmentation of objects within 3D urban environments is of crucial importance. The aim of this project is to develop a methodology for extracting buildings from textured 3D meshes. To this end, PicassoNet-II, a semantic segmentation architecture is employed. The methodology also incorporates Markov field-based contextual analysis to assess post-segmentation features. In addition, building instantiation is performed using cluster analysis algorithms. Training this model to fit various datasets requires a large amount of annotated data, both from Quebec City, Canada, and from simulated data. Experimental results show that the use of simulated data improves segmentation accuracy, and the DBScan algorithm proves effective in extracting isolated buildings. This project paves the way for improved applications in 3D urban modeling, offering opportunities in fields ranging from urban planning to resource management. The positive results with simulated data reinforce the impact of this research on improving digital models of our ever-changing urban environments.

Size effect on plain concrete specimens is well known and can be correctly captured when performing numerical simulations by using a well characterised softening function, but in the case of fibre reinforced concrete this is not directly applicable, since an only diagram cannot capture the material behaviour on elements with different size due to dependence of the orientation factor of the fibres with the size of the specimen. In previous works, the use of a trilinear softening diagram proved to be very convenient for reproducing fracture of polyolefin fibre reinforced concrete elements, but only if it is previously adapted for each specimen size. In this work, a predictive methodology is used to reproduce fracture of polyolefin fibre reinforced concrete specimens of different sizes under three-point bending. Fracture is reproduced by means of a well known embedded cohesive model, with a trilinear softening function that is defined specifically for each specimen size. The fundamental points of these softening functions are defined a priori by using empirical expressions proposed in past works, based on an extensive experimental background. Therefore, the numerical results are obtained in a predictive manner, and then compared with a previous experimental campaign, showing that this approach properly captures the size effect, although some values of the fundamental points in the trilinear diagram could be defined more accurately.

Multiple unique environmental factors such as space radiation and microgravity (µG) pose a serious threat to human gene stability during space travel. Recently, we reported that simultaneous exposure of human fibroblasts to simulated µG and radiation results in more chromosomal aberrations than in cells exposed to radiation alone. However, the mechanisms behind this remain unknown. The purpose of this study was thus to obtain comprehensive data on gene expression using a 3D clinostat synchronized to a carbon (C)-ion or X-ray irradiation system. Human fibroblasts (1BR-hTERT) were maintained under standing or rotating conditions for 3 or 24 h after synchronized C-ion or X-ray irradiation at 1 Gy as part of a total culture time of 2 days. Among 57,773 genes analyzed with RNA sequencing, we focused particularly on the expression of 82 cell cycle-related genes after exposure to the radiation and simulated µG. The expression of cell cycle-suppressing genes (ABL1 and CDKN1A) decreased and that of cell cycle-promoting genes (MKI67, KPNA2, CCNB1, STMN1, and MCM4) increased after C-ion irradiation under µG. The cell cycle may pass through the G1/S and G2 checkpoints with DNA damage due to the combined effects of C-ions and µG, suggesting that increased genomic instability might occur in space.

We studied the effect of annealing and the applied magnetic field from 50 Oe to 20 kOe on the magneto-structural behavior of Ni2FeSi-based Heusler microwires fabricated by using Taylor-Ulitovsky technique. Using the XRD analysis, a strong effect of annealing, manifested as the development of the crystallization process, was observed. The average grain size and crystalline phase content of annealed sample increase from 21.3 nm and 34 % to 32.8 nm and 79%, respectively, as-compared to the as-prepared one. In addition, upon annealing phase transforms into a monoclinic martensitic structure with modulation 10M were observed, which cannot be found in the as-prepared sample. Concerning the magnetic properties, both samples show ferromagnetic behavior below and above the room temperature, where the Curie temperature of Ni2FeSi is higher than room temperature. The induced secondary phases have a noticeable effect on the magnetic behavior of the annealed sample, where a high normalized saturation magnetization (NMs) and low normalized reduced remenance (Mr = M/M5K), compared to the as- prepared have been detected. Additionally, the coercivity of annealed sample shows one flipping point at 155 K where it behavior with temperature is changed. Meanwhile, the as-prepared sample show two flipped point at 205 K and 55 K. A mismatch between field cooling (FC) and field heating (FH) magnetization curves with temperature has been detected for annealed sample at low applied magnetic field. In addition the FC and FH curves shows different slopes with variation the temperature and the magnetic field. By increasing the external magnetic field higher than 200 Oe and up to 20 kOe a gradual changing in the magnetic behavior has been detected, where the mismatch and different slopes disappeared at applying magnetic field about 20 kOe. The difference in magnetic and structure behavior of Ni2FeSi microwires sample is discussed considering the effect of induced internal stresses by the presence of a glass coating and the recrystallization and stresses relaxation upon annealing.

Abstract Safflower (Carthamus tinctorius L.) is a multipurpose minor crop consumed by developed and developing nations around the world with a limited research fund and genetic resources. Genomic selection (GS) is an effective modern breeding tool which could help to fast track the genetic diversity preserved in genebank collections to facilitate rapid and efficient germplasm improvement and variety development. In the present study, we simulated four GS strategies to compare genetic gains and inbreeding rates during breeding cycles in a safflower recurrent selection breeding program targeting grain yield (GY) and seed oil content (OL). We observed positive genetic gains over cycles in all four GS strategies, where the first cycle delivered the largest genetic gain. Single traits GS strategies had the greatest gain for the target trait but with very limited genetic improvement for the other trait. Simultaneous selection for GY and OL via index indicated higher gains for both traits than crossing between the two single trait independent culling strategies. The the multi-trati GS strategy with inbreeding control (GS_GY+OL+Rel) showed lower inbreeding rate but similar gain compared to GS_GY+OL (without inbreeding control) after few cycles. Our finding lay the foundation for the future safflower GS breeding.

Chest X-ray (CXR) is the first tool globally employed to detect cardiopulmonary pathologies. These acquisitions are highly affected by scattered photons due to the large field-of-view required. Scatter in CXRs introduces background in the images, which reduces their contrast. We developed three deep learning-based models to estimate and correct the scatter contribution to CXRs. We used a Monte Carlo (MC) ray-tracing model to simulate CXRs from human models obtained from CT scans using different configurations (depending on the availability of dual-energy acquisitions). The simulated CXRs contained the separated contribution of direct and scattered X-rays in the detector. These simulated datasets were then used as the reference for the supervised training of several NN. Three NN models (single and dual energy) were trained with the MultiResUNet architecture. The performance of the NN models was evaluated on CXRs obtained with the MC code from chest CTs of patients affected by COVID-19. The results showed that the NN models were able to estimate and correct the scatter contribution to CXRs with an error <5%, being robust to variations in the simulation setup and improving the contrast in soft tissue. The single-energy model was tested with real CXRs, providing robust estimations of the scatter-corrected CXRs.

This research evaluated the role and feasibility of the granular nanocellulose particles (GNC) from sugarcane bagasse obtained from enzymatic hydrolysis in reducing lipid digestibility and permeability in the in vitro simulated gastrointestinal (GI) system. GNC concentration (0.02%, w/v) had significantly affected the released free fatty acid (FFA) reduction of approximately 20%. The Pick-ring emulsion of the GNC and olive oil simulation mixture revealed higher oil droplet size distribution and stability in the initial stage than the vortexed mixture formation. The difference in particle size distribution and zeta potential of the ingested GNC suspension and GNC-olive oil emulsion were displayed during the in vitro gastrointestinal simulation. GNC particles interacted and distributed surrounding the oil droplet leading to the interfacial emulsion. The GNC concentration (0.01-0.10%, w/v) showed low toxicity on the HIEC-6 cell, ranging from 80.0 to 99% of cell viability. The release of FFA containing the ingested GNC suspension and GNC-olive oil emulsion was about 30% reduction compared to without GNC digest solution. The FFA and triglyceride permeability through the HIEC-6 intestinal epithelium monolayer were deceased in the digesta containing the ingested GNC and emulsion. This work indicated that GNC represented a significantly critical role and properties in the GI tract and reduced lipid digestion and absorption. This GNC could be utilized as an alternative food additive or supplement in fatty food for weight control due to their inhibiting lipid digestibility and assimilation.

In this communication, we present a new simulated in situ lab/on-deck incubator, light spectrum replicator (LSR), and method to simulate the measured in situ HOCR light spectrum curves in incubation chambers. Carbon flux studies require detailed knowledge of primary and secondary production, including an understanding of temporal and spatial scales of variation. Interpretation of the processes involved during measurements continues to be difficult [1] since the incubation of the samples does not permit the study of rapid variations in carbon assimilation. Further, the significance of Dissolved Organic Matter of DOM in primary production is gaining attention as many autotrophic species are known for using organic substrates for growth, even in the dark [2–4] and since a significant portion of DOM can be accounted for from active release of intracellular metabolites by microbial consortia [5]. On the other hand, the major uncertainties in bacterial production measurements lie with the conversion factors used to calculate bacterial production (BP). For a given thymidine incorporation rate, estimates of BP can range by a factor of more than 20 [6,7]. Even though various new analytical tools have emerged [8], understanding of complex patterns of interactions within the microbial loop remains an open question.

Trash mulches are very effective in preventing soil erosion; reduce sediment transport rate, runoff rate and increasing infiltration. The study was carried out with the objectives to observe the sediment outflow from sugar cane leaf (trash) mulch treatments at selected land slopes under simulated rainfall conditions by using rainfall simulator of size 10 m × 1.2 m × 0.5 m with the locally available soil material collected from Pantnagar. In the present study, trash mulches with different quantities were selected to observe the effect of mulching in soil loss reduction. The quantity of mulch was taken as, 6 t/ha, 8 t/ha and 10 t/ha, three rainfall intensities viz. 11cm/h, 13cm/h and 14.65cm/h at 0%, 2% and 4% land slopes were selected. The duration of rainfall was fixed (10 minutes) for every mulch treatment. The total runoff volume was found to be varying with different mulch rates for particular rainfall input and land slope. The runoff distribution pattern was observed to be increasing with the increase in land slope. The average sediment concentration (SC) and outflow was found to be increasing with the increasing land slope, but SC and outflow decreased with increasing mulch rate for particular land slope and rainfall intensity. The SOR (SOR) for no mulch treated land was higher as compared to trash mulch treated lands. Mathematical relationships were developed for relating SOR, SC, land slope and rainfall intensity for a particular mulch treatment. It was observed that values of SOR and average SC had a good correlation with rainfall intensity and land slope for each mulch treatment. The correlation coefficients of developed models were found to be more than 90%.

Seed bank survival underpins plant population persistence but studies on seed bank trait-environment interactions are few. Changes in environmental conditions relevant to seed banks occur in desert ecosystems owing to solar energy development. We developed a conceptual model of seed bank survival to complement methodologies using in-situ seed bank packets. Using this framework, we quantified the seed bank survival of two closely related annual desert plant species, one rare (Eriophyllum mohavense) and one common (Eriophyllum wallacei) and the seed bank-environment interactions of these two species in the Mojave Desert within a system that emulates microhabitat variation associated with solar energy development. We tracked 4,860 seeds buried across 540 seed packets and found, averaged across both species, that seed bank survival was 21% and 6% for the first and second growing seasons, respectively. After two growing seasons, the rare annual had a significantly greater seed bank survival (10%) than the common annual (2%). Seed bank survival, across both species, was significantly greater in Shade (10%) microhabitats compared to Runoff (5%) microhabitats and Control microhabitats (3%). Our study confers insight into this early life-stage across rare and common congeners and their environmental interactions using a novel conceptual framework for seed bank survival.

This study reports on the assessment of the growth potential of five edible vegetables which were grown in Cr (VI) spiked soils. The vegetable plants that were used in this study were Vigna angularis, Cicer arietinum, Spinacia oleracea, Amaranthus dubius Thell and Phaseolus vulgaris. Dried ground samples from roots, stems and leaves were analysed for various oxidation states of Cr. The daily intake of chromium (DIC), hazard quotient (HQ) and hazard index (HI) methods were employed to assess the potential human health risks posed by these Cr oxidation states through vegetable consumption. The results showed that Vigna angularis was the only vegetable that germinated in highly concentrated Cr (VI) in the simulated soil (456 mg/kg). The highest bioaccumulation factor of CrT in the roots was found in Cicer arietinum at 3.5 ± 0.51 mg/kg DW. The highest translocation factor in stem was that of Cicer arietinum and Vigna angularis at 1.0 ± 0.00, while Cicer arietinum and Spinacia oleracea translocated highest Cr to the leaf at 2.1 ± 0.21. A child or an adult consuming such contaminated Cicer arietinum were likely to take in between 508 -785 mg/kg/day of total Cr which were above the World Health Organisation guidelines of 220 and 340 mg/kg/day, respectively. The highest HQ was found in Cicer arietinum at 8.7 and 13.4 for adults and children, respectively. The same species of plants had also high HI at 17.4 and 27.2 for adults and children respectively. This indicated that consumers of the edible vegetables grown in Cr (VI) rich soil may be exposed to health risks and the children were more likely to be vulnerable to these adverse effects than the adult.

This paper outlines a tool developed with the purpose of creating a simple configurable emulated network environment that can be used in cyber defence exercises. Research has been conducted into the various related subject areas: cyber defence exercises, network threats, network emulation, network traffic replay, network topologies, and common network services. From this research a requirements specification was produced to encapsulate the features required to create this tool. A network, containing many of the aspects researched, was designed and implemented using Netkit-NG to act as a blueprint for the tool and to further knowledge in the construction of an emulated network. Following this the tool was developed and tested to ensure requirements were met.

The article discusses the results of investigations performed during a thermo-mechanical treatment of forgings made of chromium-molybdenum 42CrMo4 grade steel. The treatment was realized during a regular series production. The forging process was combined with a heat treatment carried out directly after forging on a specially adapted station. Such a production technology will make it possible to eliminate the step of repeated heating of the forgings. On the example of an element of a steering gear, it was demonstrated how it is possible to perform an isothermal annealing process starting from the temperature at which the trimming of the forgings ends. During the cooling of the forgings, it is enough to maintain the temperature at the proper level in order for the exothermal phase transformation of austenite into pearlite to take place. With an appropriate design of the processing line, the heat released during the transformation could be used to maintain the applied temperature, thus limiting the consumption of energy needed to power the devices. The test results show that, with the properly selected temperature of isothermal annealing, it is possible to obtain an equilibrial ferritic-pearlitic structure in the required hardness scope. Introducing such a solution into the industrial practice would allow significant savings of the energy used for the heat treatment.

This study investigated the accuracy and precision of a commercially available PNT solution that uses DGNSS-SBAS technology. Time and position data were sampled at a frequency of 20Hz during both short and long trajectory of a simulated controlled dry-land slalom, as well as during a real-world on-water slalom exercise. The primary objective was to assess the positional accuracy, availability, integrity, and service continuity of the PNT solution while evaluating its ability to differentiate between trajectories. Additionally, the simulated results were compared with an on-water real-world slalom test to validate the findings. The results of the controlled dry-land slalom test indicate that the PNT solution provided accurate measurements with an overall mean±SD Hrms of 0.20±0.02m. The integrity measures, HDOD and PDOP were found to be ideal to excellent, with values of 0.68±0.03, and 1.36±0.07, respectively. The PNT solution utilised an average of 20±1 satellites from the constellation, resulting in an accuracy of

Many studies have focused on the impacts of rainfall duration and intensity while overlooking the role of rainfall patterns on intensive tillage erosion in hilly agricultural landscapes. The objective of this study was to determine the combined effects of rainfall patterns and intensive tillage erosion on surface runoff and soil loss on sloping farmland in the purple-soil area of China. Five simulated rainfall patterns (constant, rising, falling, rising-falling, and falling-rising) with the same total precipitation were designed, and the intensive tillage erosion treatment (IT) and no-tillage treatment (NT) were subjected to simulated rainfall using rectangular steel tanks (2 m × 5 m) with a slope of 15°. To analyse the differences in the hydrodynamic characteristics induced by tillage erosion, we calculated the flow velocity (V), Reynolds number (Re), Froude number (Fr), and Darcy-Weisbach resistance coefficient (f). The results indicate that significant differences in surface runoff and soil loss were found among different rainfall patterns and stages (P < 0.05). The falling pattern and falling-rising pattern had faster runoff-initiating times and larger sediment yields than those of the other rainfall patterns. f varied from 0.30 to 9.05 for the IT and 0.48 to 11.57 for the NT and exhibited an approximately inverse trend to V and Fr over the course of the rainfall events. Compared with the NT, the mean sediment yield rates from the IT increased the dynamic range of 8.34%–16.21% among different rainfall patterns. The net contributions of the IT ranged from 2.77% to 46.39% on surface runoff and 10.14%–78.95% on soil loss on sloping farmland. Surface runoff and soil loss were positively correlated with rainfall intensity, V, and Fr but negatively correlated with f irrespective of tillage intensive (P < 0.05). For varying-intensity rainfall patterns, soil and water loss fluctuated during rainfall events, suggesting that the changes in rainfall intensity and tillage intensity would result in drastic variations in soil hydrological characteristics and sediment transport mechanisms. The time sequences of rainfall intensity in each rainfall pattern significantly affected surface runoff, soil erosion, and their contribution rates to total soil and water loss. Moreover, tillage erosion effects on soil and water loss were closely related to rainfall patterns in hilly agricultural landscapes. Our study not only sheds light on the mechanism of tillage erosion and rainfall erosion but also provides useful insights for developing tillage-water erosion prediction models to evaluate soil and water loss on cultivated hillslopes.

While machine learning (ML) has been quite successful in the field of structural health monitoring (SHM), its practical implementation has been limited. This is because ML model training requires data containing a variety of distinct damaged instances captured from a real structure and the experimental generation of such data is challenging. One way to tackle this issue is by generating training data through numerical simulations. However, simulated data cannot capture the bias and variance of experimental uncertainty. To overcome this problem, this work proposes a deep learning-based domain transformation method for transforming simulated data to the experimental domain. Use of this technique has been demonstrated for debonding location and size prediction of stiffened panels using a vibration-based method. The results are satisfactory for both, debonding location and size prediction. This domain transformation method can be used in any field where experimental data for training machine learning models is scarce.

Sacroiliac (SI) joint dysfunction can lead to debilitating pain but can be treated with minimally invasive sacroiliac joint fusion (SIJF). This treatment is commonly performed using 2D fluoroscopic guidance. This makes placing the implants without damaging surrounding neural structures challenging. Virtual surgical planning (VSP) using simulated fluoroscopic images may improve perioperative guidance. This article describes a workflow with VSP in SIJF using simulated fluoroscopic images and evaluates achieved implant placement accuracy. Routinely collected survey data on the added value of VSP were also evaluated. Ten interventions were performed on 10 patients by the same surgeon, comprising 30 implants; the median age was 39 years, and all patients were female. The overall mean implant placement accuracy was 4.9 ± 1.26 mm and 4.0 ± 1.44°. There were no malpositioning complications. The VSP helped the surgeon understand the anatomy and determine the optimal position and length of the implants. The average Likert scale score of the survey was 4.7, suggesting a positive role of VSP for SIJF. Planned positions of the implants could be reproduced in surgery with clinically acceptable accuracy and VSP was a valuable asset for the surgeon.

The accumulation of process waste in the production line causes fluctuations, bottlenecks, and increased inventory in workstations disrupting process flow. In this paper, the aim is the use a simulated value stream mapping (SVSM) as a lean assessment tool for decision-making in the continuous improvement process to influence and provide consideration and consistency on productivity improvement in the production system. The proposed methodology applied discrete event simulation for production process operations improvement to eliminate non-value adding times and provides good quality products at the lowest cost and highest efficiency. The results are the analysis of the current state of the production system in a South African truck manufacturing industry small and medium enterprise (SMEs) as a potential solution for the production system future state. The identified non-value adding times in the 6 most critical workstations was eliminated by SVSM which resulted in a productivity improvement of 4%, most importantly bringing the productivity to 95% and total cycle time improvement to 451 for small units and 466 for large units. The results proposed combined VSM and Simulation techniques which enhance the LEAN application by DES to increase productivity and performance improvement to remain competitive in the global economy.

Frost heave, which is the volumetric expansion of frozen soil, has great ecological significance, since it creates water storage spaces in soils at the beginning of the growing season in cold temperate forests. To understand the characteristics of frost heave in seasonally frozen soil and the factors that impact its extent, we investigated the frost heave rates of forest soil from different depths and with different soil moisture contents, using both lab-based simulation and in situ measurement in a broadleaved Korean pine forest in the Changbai Mountains (northeastern China). We found that frost heave was mainly affected by soil moisture content, soil type, and gravitational pressure. Frost heave rate increased linearly with soil moisture content, and for each 100% increase in soil moisture content, the frost heave rate increased by 41.6% (loam, upper layer), 17.2% (albic soil, middle layer), and 4.6% (loess, lower layer). Under the same soil moisture content, the frost heave rate of loam was highest, whereas that of loess was lowest, and the frost heave of the uppermost 15 cm, which is the biologically enriched layer, accounted for ~55% of the frost heave. As a result, we determined the empirical relationship between frost heave and freezing depth, which is important for interpreting the effects of frost heave on increases in the storage space of forest soils and for calculating changes in soil porosity.

To assess the usefulness of an attachable video laryngoscope (AVL) by attaching a camera and monitor to a conventional Macintosh laryngoscope (CML). Normal and tongue edema airway scenarios were simulated using a manikin. Twenty physicians performed tracheal intubations using CML, AVL, Pentax AWS® (AWS), and McGrath MAC® (MAC) in each scenario. Ten physicians with more than 10 cases of clinical experience with tracheal intubation using CML were included in the skilled group. Ten physicians with less than 10 cases of clinical experience with tracheal intubation using CML were included in the unskilled groups. The time required to intubate and the success rate were recorded. The degree of difficulty of use and glottic view assessment scored by participants. All 20 participants successfully completed the study. There was no difference in the success rate and time required for tracheal intubation in the normal airway scenarios. For the skilled group, in the tongue edema airway scenario, the AWS had the highest success rate (100%) followed by AVL (60%), MAC (60%), and CML (20%) (p = 0.001). The time required to intubate with the AWS was significantly shorter than with AVL (10.2 vs 22.3 s; p=0.002) or MAC (10.2 vs 23.7 s; p=0.001). There was no significant (p &gt; 0.05) difference between AVL and MAC. The degree of Difficulty of Use for AVL was significantly lower than that for CML (7.8 vs 2.8; p &lt; 0.001). There was no significant (p &gt; 0.05) difference between AVL and other video laryngoscopes. AVL had a higher rate of successful tracheal intubation than CML in the tongue edema scenario. AVL showed a similar success rate and time of tracheal intubation to the MAC. Therefore, AVL may be a possible alternative video laryngoscope device.

It is well established that the interacting effects of temperature and precipitation will alter agroecological systems on a global scale. These shifts will influence the fitness of specialty crops, specifically strawberries (Fragaria x ananassa), an important crop in the Northeastern United States. In this study, four precipitation scenarios were developed that are representative of current and probable-future growing season precipitation patterns. Using a precipitation simulator, we tested these scenarios on potted day neutral strawberries. This study generated four primary results: (1) though treatments received different amounts of precipitation, little difference was observed in soil volumetric water content or temperature. However, treatments designed to simulate future conditions were more likely those designed to simulate current conditions to have higher nitrate-in-leachate (N-leachate) concentrations; (2) neither total precipitation nor seasonable distribution were associated with foliar or root disease pressure; (3) while there was a slightly higher chance that photosynthetic potential and capacity would be higher in drier conditions, little difference was observed in the effects on chlorophyll concentration, and no water stress was detected in any treatment; and (4) leaf biomass was likely more affected by total rather than seasonal distribution of precipitation, but interaction between changing rainfall distribution and seasonal totals is likely to be an important driver of root biomass development in the future.

Body temperature responses were recorded during phases of work (waiting to work in close proximity to search site, active work in a search site, and post-work recovery crated in vehicle) in human remains detection dogs during search training. State or federally certified human remains detection dogs (n = 8) completed eight iterations of searching, rotating through six different types of search environments to detect numerous scent sources including partial and complete, buried, hidden, or fully visible human remains. Internal temperature (Tgi) of the body was measured continuously using an ingestible thermistor in the gastrointestinal tract. Mean total phase times were: waiting to work: 9.17 minutes (± 2.27); active work: 8:58 minutes (± 2:49); and post work recovery: 24:04 minutes (± 10.59). Tgi was impacted by phase of work (P < 0.001) with a small increase during active work, with mean peak temperature 39.4 °C (± 0.34 ºC) during that period. Tgi continued to increase for a mean of 7:37 (± 6:04) minutes into the post-work recovery phase in the handler’s vehicle with a mean peak Tgi of 39.66 °C (± 0.41 ºC). No significant increase in temperature was measured during the waiting to work phase, suggesting anticipation of work did not appear to contribute to overall body temperature increase during the waiting to work recovery cycle. Continued increase of gastrointestinal body temperature several minutes after cessation of exercise indicates that risk of heat injury does not immediately stop when the dog stops exercising, although none of the dogs in this study reached clinically concerning body temperatures or displayed any behavioral signs suggestive of pending heat injury. More work is needed to better understand the impact of vehicle crating on post-work recovery temperatures in dogs.

This paper presents an investigation of the oxidation of Alloy X-750 containing 5% Fe in a simulated boiling water reactor (BWR) environment. To mimic the conditions in which the bare metal is exposed to the reactor water the samples were not pre-oxidized. The specimens were exposed for durations ranging from 2 to 840 hours, and the development of the oxide microstructure was mainly studied using electron microscopy. The results showed that the oxide scale consisted of blocky crystals of trevorite on top of a porous inner layer rich in Ni and Cr. After the longest exposure time, the trevorite crystals completely covered the specimen surface. The study further revealed that the speed at which the oxide grew and the metal dissolved both decreased with time. Additionally, the metal thinning process was found to be sub-parabolic. Given the significant variation in iron content in the X-750 specification, the influence of this element on the material's corrosion performance in BWR was examined by comparing the results from this investigation with those from previous work on material containing 8 wt% Fe. The study demonstrated that the oxide growth, metal dissolution and metal thinning were slower in the material with higher Fe content, indicating the importance of this element in limiting the degradation of Alloy X-750 in BWR environments.

The use of tuning forks to measure fluid density and viscosity is widely employed in fields such as food, medicine, textiles, automobiles, petrochemicals, and deep drilling. The explicit analytical model based on Euler-Bernoulli cantilever beam theory for the relationship between tuning fork resonance characteristics and the density and viscosity of fluid is only applicable to the situation where the fluid viscous effect is very small. In this paper, the finite element method is used to simulate the influence of large variations in fluid density and viscosity on the resonance characteristic parameters (resonant frequency and quality factor) of the tuning fork. The numerical simulation results are compared with the analytical analysis results and experimental measurement results. Then, the sensitivity of tuning fork resonance characteristic parameters to fluid density and viscosity is studied. The results show that compared with the analytical results, the numerical simulation results have a higher degree of agreement with the experimental measurement results. The relative difference in resonant frequency is less than 2%, and the relative difference in quality factor is less than 4%. This indicates that the finite element method includes the influence of fluid viscosity on tuning fork resonance parameters, which is more in line with the actual conditions than the analytical model. Simulating and analyzing the sensitivity of the tuning fork to fluid density and viscosity by the finite element method, it is possible to consider the situation where fluid density and viscosity vary over a large range. Compared with experimental measurements, this method has higher efficiency and can significantly save time and economic costs. This study can overcome the limitation of existing explicit analytical models, which are only applicable when the viscous effects of the fluid are very small. It enables a more accurate simulation of the coupling vibration between tuning forks and fluids, thereby providing theoretical references for further optimizing tuning fork structural parameters to enhance the accuracy of measuring fluid characteristic parameters.

Grape pomace is a byproduct of wineries and sustainable source of bioactive phenolic compounds. Encapsulation of phenolics with a well-chosen coating may be a promising means of delivering them to the intestine, where they can then be absorbed and exert their health-promoting properties. Ionic gelation of grape pomace extract with natural coatings (sodium alginate and its combination with maltodextrins, gelatin, chitosan, tragacanth gum, and gum arabic) was performed, and the resulting hydrogel microbeads were then air-, vacuum-, or freeze-dried to prevent their spoilage. The physicochemical characterization (size, shape, texture, and morphology) of the microbeads and the in vitro release of phenols from microbeads were studied and a good relationship between them was established. Freeze-dried microbeads showed the highest cumulative release of phenols as in the intestinal phase (23.31 – 43.27 mgGAE/gMB), followed by vacuum-dried (23.31 - 35.41 mgGAE/gMB) and air-dried (22.74 – 31.38 mgGAE/gMB), while the most suitable release dynamics in the intestinal phase were observed for alginate-based microbeads combined with gelatin (58.4 %), gum arabic (34 %) and 1.5 % w/v chitosan (15.3 %). The results highlight the importance of developing encapsulated formulations containing a natural source of bioactive compounds that can be used in various functional foods and pharmaceutical products.

Given of the outstanding versatile properties, the multilayered anti-corrosion coatings have drawn great interests in academic and engineering fields. However, the application of multilayered coatings is restricted by some limitations such as low interlayer compatibilities, harsh preparation process, etc. This work introduced a composite film fabricated on 2A12 aluminum alloy surface, including an anodic oxide film, a sol-gel film as well as a layer-by-layer (LBL) self-assembling film from bottom to top. The microstructure and elemental characterization indicated that the finish of the coating with the LBL film resulted in a closely connected multilayered coating with a smoother surface. The anticorrosion performance was systematically evaluated in the simulated corrosive medium and neutral salt-spray environment. The intergrated coating with the LBL film presented an excellent anticorrosion ability with the system impedance over 108 Ω•cm² and the self-corrosion current density two orders of magnitude lower than that of the other coatings. After the acceleration test in salt-spray environment, the multilayered coatings could still show a good protective performance with almost no cracks and no penetration of chloride ions. It is believed that the as-constructed multilayered coating with high corrosive properties and fine surface state will have promising applications in the field of anticorrosion engineering.

The presence of dyes in wastewater effluents made from the textile industry is a major environmental problem due to their complex structure and poor biodegradability. In this study, a cationic lignin polymer was synthesized via the free radical polymerization of lignin with [2- (methacryloyloxy) ethyl] trimethylammonium chloride (METAC) and used to remove anionic azo-dyes (reactive black 5, RB5, and reactive orange 16, RO16) from simulated wastewater. The effects of pH, salt and concentration of dyes, well as the charge density and molecular weight of lignin-METAC polymer on dye removal were examined. Results demonstrated that lignin-METAC was an effective flocculant for the removal of dye via charge neutralization and bridging mechanisms. The dye removal efficiency of lignin-METAC polymer was independent of pH. The dosage of the lignin polymer required for reaching the maximum removal had a linear relationship with the dye concentration. The presence of inorganic salts including NaCl, NaNO3 and Na2SO4 had marginal effect on the dye removal. Under the optimized conditions, greater than 98 % of RB5 and 94 % of RO16 were removed at lignin-METAC concentrations of 120 mg/L and 105 mg/L in the dye solutions, respectively.

Super duplex stainless steel (SDSS) is used for manufacturing large valves and pipes in offshore plants because of its excellent strength and corrosion resistance. Large valves and pipes are manufactured by forging after casting, and the outside and inside microstructures are different owing to the difference in the cooling rate caused by the thermal conductivity. This microstructural variation causes cracks during solution annealing, which breaks the materials. To study toe corrosion resistance of the SDSS forged material, the microstructure was conducted based on the difference in the cooling rate between the inside and outside of the cast SDSS. To analyze the effects of the secondary phase fraction before solution annealing on the solution and corrosion resistance, the corrosion resistance with and without solution annealing was measured using the potentiodynamic polarization test and critical temperature test after the precipitation of the secondary phase. In the potentiodynamic polarization test, the secondary phase decreased the activation polarization and increased the corrosion rate. The critical pitting temperature exhibited the effect of the secondary phase.

Semiconductor photocatalytic performances can be modulated through morphology modification. Herein porous hierarchical BiOBr microspheres (BiOBr-MS) of ~3 m was firstly self-assembled without the assistance of a template via a facile solvothermal synthesis in triethylene glycol (TEG) at 150 oC for 3 h. KBrO3 was exploited as a bromine source, which slowly provided bromide ions upon reduction in TEG and controlled the growth and self-assembly of primary BiOBr nanoplates. The addition of PVP during solvothermal synthesis of BiOBr-MS reduced the particle size by about three-fold to generate BiOBr sub-microspheres (BiOBr-sMS) of <1 m. BiOBr-sMS exhibited significantly higher photocatalytic activity than BiOBr-MS for aerobic photooxidation of benzyl alcohol (BzOH) to benzaldehyde (BzH) under simulated sunlight irradiation (conversions of BzOH (50 mM) over BiOBr-sMS and BiOBr-MS were respectively 51.3% and 29.6% with 100% selectivity to BzH after Xenon illumination for 2 h at 25 oC). The photogenerated holes and •O2- were found to be main reactive species for the BzOH oxidation over BiOBr spheres by scavenging tests and spin-trapping EPR spectra. The higher photocatalytic activity of BiOBr-sMS was attributed to its more open hierarchical structure, efficient charge separation, more negative conduction band position and generation of larger amounts of •O2-.

The effects of simulated acid rain (SAR) on the photosynthetic performance of subtropical coniferous species have not been thoroughly investigated. In this study, we treated two coniferous species, Pinus massoniana (PM) and Cunninghamia lanceolata (CL), with SAR and then analyzed photosynthetic activities via the simultaneous measurement of prompt fluorescence(PF), delayed fluorescence(DF), and modulated reflection at 820 nm(MR820). Following the low-pH SAR treatment, the I–P phase of the OJIP curves of PM and CL decreased significantly and then the K-band and L-band were detectable. The delayed fluorescence for both PM and CL decreased as the pH of the SAR solution decreased, with a more significant decrease in the I1 peak than in the I2 peak. According to the MR820 curve, the exposure to SAR stress inhibited the rapid decrease and slow increase in the MR820 transients of PM and CL. The gradients of the decreasing and increasing phases were lower for CL than for PM at pH 2.5. In addition, SAR decreased the light energy captured per unit area (ABS/CSm) and the quantum yield of electron transfer per unit area (ETO/CSm), but it increased the accumulation of QA−, thereby decreasing primary photochemical efficiency (TRO/CSm, φPO). These changes in photosystem II (PSII) resulted in a decrease in the maximum quantum yield of PSII (Fv/Fm) and the performance index (PIABS). Moreover, PSII was protected from thylakoid membrane photodamages through the increase in heat dissipation per unit area (DIO/CSm) in response to SAR. The increase in δRO as the pH of the SAR solution decreased was observed for PM, but not for CL. Considered together, the study findings suggest that SAR treatments can decrease chlorophyll contents and damage the OEC in PM and CL, which obstructs the transfer of electrons on the donor and acceptor sides of PSII. However, PM is better able to withstand SAR stress than CL, likely because of the activation of a protective mechanism (reflected by the change in δRO). Therefore, in coniferous forest areas severely affected by acid rain, CL may need to be protected more than PM.

Suicide dynamics form a complex system deeply influenced by interrelated factors, necessitating advanced methodologies for comprehensive analysis. This study pioneers the application of Particle Markov Chain Monte Carlo (PMCMC) methods in suicide research, recognized for their enhanced sampling efficiency over traditional techniques in complex, high-dimensional models. PMCMC is particularly adept at handling non-Gaussian distributions and navigating parameter spaces efficiently, preventing the entrapment in local optima. Utilizing PMCMC, our research simulated a broad spectrum of potential outcomes, clarifying the probable scenarios and their likelihoods, thus enriching the predictive accuracy and understanding of suicide dynamics. These methods facilitated the exploration of dynamic interactions among key risk factors such as mental health issues, trauma, substance use, social isolation, and access to harmful means, whose complex interplays challenge predictive modeling. The study extends previous applications of PMCMC in complex systems like H1N1, opioid crises, and COVID-19 to the domain of suicide, suggesting its potential in enhancing decision-making and intervention strategies. However, limitations due to the model's simplified assumptions and the specificity of the data to certain populations underscore the necessity for broader application to validate findings across varied demographics. In summary, while PMCMC offers robust capabilities for the dynamic modeling of suicide, it requires careful parameter selection and consideration of computational demands. Future research should continue to leverage this approach in more complex settings, enhancing our ability to predict and mitigate suicide risks effectively.

We present the results of calculations of magnetic properties of 3 compounds from Laves phase C15 family: DyAl2, HoAl2 and ErAl2 performed with a new computation system called ATOMIC MATTERS MFA. We compare these findings with the recently published results for TbAl2, GdAl2 and SmAl2. The calculation methodology was based on the localized electron approach applied to describe the thermal evolution electronic structure of rare-earth R3+ ions over a wide temperature range and to compute magnetocaloric effect (MCE). Thermomagnetic properties were calculated based on the fine electronic structure of 4f9, 4f10 and 4f11 configurations of the Dy3+, Ho3+, Er3+ ions, respectively. Our calculations yield the magnetic moment value and direction; single-crystalline magnetization curves in zero field and external magnetic field applied in various directions of m(T, Bext); the 4f-electronic components of specific heat c4f(T, Bext); and temperature dependence of the magnetic entropy and isothermal entropy change with external magnetic field -S(T, Bext). The cubic CEF parameter values used for DyAl2 calculations are taken from earlier research of A.L. Lima, A.O. Tsokol and recalculated for universal cubic parameters (Amn) for the RAl2 series. Our studies reveal the importance of multipolar charge interactions when describing thermomagnetic properties of real 4f electronic systems and the effectiveness of an applied self-consistent molecular field in calculations for magnetic phase transition simulation.

Large language models (LLMs) excel in providing natural language responses that sound authoritative, reflect knowledge of the context area, and can present from a range of varied perspectives. Agent Based Models and Simulation consist of simulated agents that interact within a simulated environment to explore societal, social, and ethical, among other, problems. Agents generate large volumes of data over time and discerning useful and relevant content is an onerous task. LLMs can help in communicating agents’ perspectives on key events by providing natural language narratives. However, these narratives need to be factual, transparent, and reproducible. To this end, we present a structured narrative prompt for sending queries to LLMs. Chi-square tests and Fisher’s Exact tests are applied to assess statistically significant difference in sentiment scores of the narrative messages between simulation generated narratives, ChatGPT-generated narratives, and real tweets. The narrative prompt structure effectively yields narratives with the desired components from ChatGPT. This structure is expected to be extensible across LLMs. In 14 out of 44 categories, ChatGPT generated narratives which has sentiment scores that were not discernibly different, in terms of statistical significance (alpha level of 0.05), from the sentiment expressed in real tweets. Three outcomes are provided: (1) a list of benefits and challenges for LLMs in narrative generation; (2) a structured prompt for requesting narratives of a LLM based on simulated agents’ information; and (3) an assessment of statistical significance in the sentiment prevalence of the generated narratives compared to real tweets. This indicates significant promise in the utilization of LLMs for helping to connect simulated agent’s experiences with real people.

In the previous work, the pure fatigue behavior of AM60 magnesium alloy (PF-AM60) was compared with the corrosion fatigue behavior of these specimens (CF-AM60). In this research, in continuation of the previous job, the pure fatigue behaviors of AM60 with polylactic acid (PLA) coating (PF-AM60-PLA) and also, corrosion fatigue behaviors of magnesium alloy with PLA coating (CF-AM60-PLA) were evaluated. Polymer coating was made by fused deposition modeling (FDM) with a 3D printer and attached to standard fatigue test specimens with a glue. Then, they were immersed in the simulated body fluid (SBF) for 27 days. In the end, a high-cycle bending fatigue test was performed on samples. The fracture surface of the samples was also observed using the field emission scanning electron microscopy (FESEM). Due to corrosion, the weight of the specimens redcued by an average of 35%. The corrosion rate decreased in the first 7 days and then increased. PF samples with coating had an average of 49% increase in fatigue lifetime. Regarding the CF samples, despite the use of a 10 times stronger solution, the fatigue lifetime of these samples decreased by only 35%. FESEM results also showed cleavage plates and striations. In addition, the separation of the glue from the coating and Mg was observed. Corrosion products including microcracks and holes were seen on the fracture surface of CF specimens, which caused stress concentration and crack growth. Holes caused by the release of gases were also observed in polymer coatings.

The paper focuses on the application of a multilevel, integrative and territorial approach to the protection of cultural heritage through planning instruments in Serbia. It points out the problems of the sectoral approach and discusses international recommendations that can be integrated into the planning methodology. The case study is the area of Djerdap National Park, which has an already established international and national importance. The research suggests that the cultural heritage in the area, with the exception of the Roman limes, is still recognized at the level of individual localities. The study emphasizes the importance of aligning all levels of governance to safeguard the whole spatial entity rather than focusing solely on its particular areas. The interna-tional and national importance of the planning area contributes to the strengthening of awareness of heritage and its institutional protection. However, the vitality of the area, which is key to its sustainable development, comes from the local level. Planning documents contribute to the inte-gration of local values and local communities into development programs and projects.

Glycosidic linkage analysis was conducted on the unfractionated polysaccharides in the alcohol-insoluble residues (AIRs) prepared from six red seaweeds (Gracilariopsis sp., Prionitis sp., Mastocarpus papillatus, Callophyllis sp., Mazzaella splendens, and Palmaria palmata) using GC-MS/FID analysis of partially methylated alditol acetates (PMAAs). The cell walls of P. palmata primarily contained mixed-linkage xylans and small amounts of sulfated galactans and cellulose. In contrast, the unfractionated polysaccharides of the other five species were rich in galactans displaying diverse 3,6-anhydro-galactose and galactose linkages with varied sulfation patterns. Different levels of cellulose were also observed. This glycosidic linkage method offers advantages for cellulose analysis over traditional monosaccharide analysis that is known for underrepresenting glucose in crystalline cellulose. Relative linkage compositions calculated from GC-MS and GC-FID measurements showed that anhydro sugar linkages generated more response in the latter detection method. This improved linkage workflow presents a useful tool for studying polysaccharide structural variations across red seaweed species. Furthermore, for the first time, relative linkage compositions from GC-MS and GC-FID measurements, along with normalized FID and total ion current (TIC) chromatograms without peak assignments, were analyzed using principal component analysis (PCA) as a proof-of-concept demonstration of the technique's potential to differentiate various red seaweed species.

Background: Educating college students about the importance of good sleep habits could lead to the adoption of healthier sleep routines, including sufficient sleep duration and sleep quality. The current pre-post study examines the impact of completing a sleep education program called “Sleep 101” on (1) sleep hygiene practices, (2) sleep quality, and (3) weekday and weekend sleep behaviors among college students. “Sleep 101” is an interactive online course developed to educate college students about the importance of sleep by addressing basic sleep physiology, the impact of sleep on mood, academic and physical performance, the interactions between sleep and various substances, and common sleep disorders. Methods: 338 college students were recruited from a midsized public university in the US and invited to participate in “Sleep 101”, of which 25 participants completed the baseline and post-intervention questionnaire. The Sleep Hygiene Index (SHI) was utilized to evaluate sleep hygiene practices, while standard questions were employed to assess weekday and weekend sleep behaviors and overall sleep quality. Results: Those who completed the study demonstrated a significant increase in weekday sleep duration and were less likely to engage in negative prior bedtime activities. In addition, 40% of those who completed baseline and post-intervention assessments noticed improvements in their sleep quality. Conclusion: These findings suggest that a brief online program is beneficial in improving sleep behaviors among college and could be a scalable approach to addressing current sleep issues and preventing future sleep problems in college students.

The profile of secondary metabolites occurring in apple cuticular layer is not only characteristic for particular apple cultivar, but also dynamically reflects various external factors in growing environment. In this study, the possibility to authenticate apple samples based on analysis of their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. In total, 274 authentic apple samples, four cultivars harvested within the seasons 2020 to 2022 in the Czech Republic and Poland were analysed. The generated complex data processed by univariate and multivariate statistical methods enabled to build classification models for discrimination of apple cultivars as well as their geographical origin. The models showed very good performance in differentiation of Czech and Polish samples for three of four cultivars: ‘Gala’, ‘Golden Delicious’ and ‘Idared’, moreover, the validity of the models was verified over harvest seasons. The diagnostic markers, besides metabolites of triterpene biosynthetic pathway, mainly represented wax esters. ‘Jonagold’, which is known to be susceptible to mutations, was the only cultivar for which the unambiguous classification of geographical origin was not possible.

Strawberry root rot caused by Neopestalotiopsis clavispora is one of the main diseases of strawberry and significantly impacts the yield and quality of strawberry fruit. There are now no effective control techniques available except for fungicide sprays, which may directly impact consumers. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional synthetic chemical fungicides. Trichoderma is widely used as a biological agent for controlling strawberry root rot. In order to provide resources for screening the highly effective biocontrol fungus for controlling strawberry root rot caused by Neopestalotiopsis clavispora, the biocontrol mechanism,the control effects of Trichoderma asperellum CMT10 against strawberry root rot and growth-promoting effects on strawberry seedlings were investigated by plate culture, microscopy observation and root drenching methods.The results showed that CMT10 had obvious competitive, antibiotic and hyperparasitism effects on Neopestalotiopsis clavispora CMGF3. The CMT10 could quickly occupy nutritional space, and the inhibition rates of CMT10 against CMGF3 in confrontation culture on 7 d was 65.49%. The inhibition rates of volatile metabolite and fermentation metabolite produced by CMT10 against CMGF3 were 79.67% and 69.84%, respectively. The mycelium of strain CMT10 can act as hyperparasites by making contacting, winding and penetrating hyphae of CMGF3. Pot experiment showed that the biocontrol efficacy of CMT10 on strawberry root rot caused by Neopestalotiopsis clavispora was 63.00%. CMT10 had obvious promotion effect on strawberry growth, the plant height, root length, total fresh weight, root fresh weight, stem fresh weight and root dry weight, with the promotion rates were 20.09%, 22.39%, 87.11%, 101.58%, 79.82% and 72.33%, respectively. Overall, this study showed the ability of Trichoderma asperellum CMT10 to control strawberry root rot and their potential to develop as novel biocontrol agents to replace chemical fungicides for eco-friendly, sustainable agriculture.

Apis mellifera, especially weak ones, are highly vulnerable to Carpoglyphus lactis mites, which can rapidly infest and consume stored pollen, leading to weakened colonies and potentially colony collapse. This study aimed to ascertain and investigate the prevalence of this mite in honeybee colonies across 9 provinces in the Republic of Korea (ROK). A total of 615 honeybee colonies were collected, from 66 apiaries during the spring and 58 apiaries during the summer of 2023. A 1,242 bp segment of the the Cytochrome c oxidase subunit 1 (COI) gene was amplified using the polymerase chain reaction method. The detection levels of C. lactis in the honeybees were compared between winter and summer. Based on the COI sequence analysis, the nucleotide sequence similarity of C. lactis mites isolated in the ROK with those from China (NC048990.1) was found to be 99.5%, and with those from the United Kingdom (KY922482.1) was 99.3%. This study is the first report of C. lactis in Korean apiaries. The findings in this study demonstrate a significantly higher detection rate in winter, which is 4.1 times greater than that in summer (p &lt; 0.001). Furthermore, the results underscore the usefulness of molecular diagnostic techniques for detecting C. lactis mites.

COX II containing a dual core CuA active site is one of the three core subunits of mitochondrial Cco, which plays a significant role in the physiological process. In this report, the full-length cDNA of COXⅡ gene was cloned from Sitophilus zeamais, which had an ORF of 684 bp encoding 227 amino acids residues. The predicted COXⅡ protein had a molecular mass of 26.2 kDa with pI value of 6.37, and multiple sequence alignment and phylogenetic analysis indicated that Sitophilus zeamais COXⅡ had high sequence identity 78.51% with the COXⅡ of other insect species, especially similarity to sitophilus oryzae. This gene was subcloned into the prokaryotic expression vector pET-32a, and induced by IPTG in E.coli Transetta (DE3) expression system. Finally the COXⅡ with 6-His tag was purified using affinity chromatography with Ni²⁺-NTA agarose. WB showed the recombinant COXⅡ was about 44 kD, and the concentration of fusion protein was 50μg/mL. UV-spectrophotometer and infrared spectrometer analysis showed that recombinant COXⅡ could catalyze the oxidation of substrate Cytc, and influenced by AITC. It was found that AITC could form a hydrophobic region with COXⅡ protein via molecular docking, besides, a sulfur atom of AITC structure could form a length of 2.9 Å hydrogen bond with Leu-31. These results will provide valuable information for elucidating the role of COXⅡ in Sitophilus zeamais responses to AITC, meanwhile, it will helpful to carry out a point mutation in AITC binding sites for the future research.

The properties of the annual, semiannual and triennial oscillations (AO, SAO and TO) in the middle atmosphere have been investigated using the TIMED/SABER temperature data. The Lomb-Scargle and wavelet spectra were used to determine the dominant oscillations in the background temperature field. The AO is prominent at the mid-latitudes. The AO amplitudes present an asymmetry between the two Hemispheres, being larger in the mesosphere than in the stratosphere. The SAO dominates the tropical regions, with three amplitude maxima at altitudes of 45, 75, and 85 km. The SAOs in the upper mesosphere (75 km) are out of phase with those in the mesopause (85 km) in the tropical regions, which can generate an enhancement of 11 K at each equinox, contributing to the lower mesospheric inversion layer. The TO is significant in the tropical region, with amplitude being maximum at 35, 45 and 85 km. Result shows that there may be potential interaction by the TO with SAO at 85km at the equator. The relation between ENSO and TO has also been discussed. The ENSO signal may modulate the amplitude of the TO, mainly in the lower stratosphere. The real origin of the TO may lie in the wave-mean-flow interaction.

This paper is focused on typical rural settlements in the Stara Planina Mountain area in Serbia. They are distinguished by their authenticity, identity and character, and they have still not been destroyed by inappropriate development as is the case in some other mountain areas in Serbia, where the effects of urbanization, globalization and homogenization are obvious. Consequently, there is a need to prevent these effects in mountain areas where there is a threat of disbalance between development and the inherited natural and cultural values. The paper starts from several important concepts that relate contemporary approaches to cultural heritage preservation, place morphology and planning future development. The concept definitions from recent documents from related fields are used. These concepts are then applied to the area of Stara Planina Mountain and its rural settlements. The necessity for an integrative approach to planning this area with significant natural and anthropogenic potential is pointed out, including its integration into international programs of sustainable development.

The research reported on this paper was aimed at improving the overall efficiency of a PDO certified artisanal cheese production process. Being a PDO certified foodstuff by the EU, it is considered to have properties and qualities determined by the geographical environment in which is made, with its production taking place in a specific and determined geographical location, in this case the Serra da Estrela region. In that sense, the authors conducted a mapping according to a systemic perspective of the processes involved in the context of manufacturing and distribution of certified Serra da Estrela cheese. Numerous methods were used throughout the process, such as a systemic design analysis, and techniques derived from ethnographic methods, which led to the collection of data in the field and consequently provided the immersion of the researcher in genuine work situations. Critical points were identified and emphasized in the systemic map with the purpose of encouraging initiatives to address and overcome the gaps and inefficiencies detected. The systemic design analysis triggered the development of design work. Observations following an ethnographic approach identified ergonomic risks in cheese making during the process of cutting excess chips, fostering the emergence of musculoskeletal disorders at the wrist. A tool that fits best to the task at hand was developed. A prototype of the new tool enabled collecting feedback from use in the work context, in order to inform product development. The domains of agricultural production and microbiology, considering the specific microorganisms developed trough the ripening process of the cheese, turned out to be aspects of high importance for the issue under focus, contributing to a broader understanding of the ripening process and its risks, simultaneously improving the efficiency and success of cheese production. If it were not for the systemic analysis, which served as a link between the boundaries of distinct domains such as the risk of microorganism contamination, ergonomics, energy efficiency, legislation and regulation policies, transportation challenges and economic viability, approached throughout the research. Simultaneously creating bridges between them, the various problems might not have been detected in the first place, as they are usually addressed in specialized disciplines, predetermined by the restrictions of each specific area of knowledge. As a consequence of the development of this research, which was based on an analysis that sought to establish possible connections between various disciplines and tried to constantly maintain a holistic perspective, making new connections and observing the issues from a new angle, apart from the already established methodologies. All this allowed to lay out the seeds for the development of a plan to tackle the critical points identified by the systemic analysis reported in this paper.

Promoting green development has become an important way to optimize the ecological and economic structure and promote sustainable development. The Yangtze River Economic Belt is an important economic corridor in China, and it remains to be examined whether the implementation of environmental regulations has enhanced the green total factor productivity (GTFP) of cities. This paper calculates the green total factor productivity of 107 cities within the Yangtze River Economic Belt by using the super-efficient SBM model and the GML index with Chinese city panel data from 2007-2019 and measures the intensity of environmental regulations through textual analysis. The bidirectional fixed-effects model constructed in this paper suggests an inverted U-shaped relationship between environmental regulation and GTFP, which is confirmed by a series of robustness tests. Green technology innovation and advanced industrial structure play a mechanism role in this. In regions with lower levels of green technology and industrial structure, the inverted U-shaped relationship between environmental regulation and green total factor productivity is more significant. In addition, the phenomenon of GTFP rising and then falling because of environmental regulation is more obvious in cities in the middle and upper reaches of the Yangtze River and outside the urban agglomerations. Therefore, when formulating environmental regulation policies, it is necessary to balance the relationship between economic development and environmental protection and harmonize the environment and economic development of the entire Yangtze River Basin.

The wetlands in northeastern Bangladesh are home to some of the most prolific and valuable ecosystems on the planet, offering a wide range of benefits to both the local and wider communities. A limited number of research on this topic have been carried out in various wetlands in coastal hilsa, but none have been located in the northeastern region of Bangladesh. Thus, the goal of this study was to better understand the most commercially relevant species (anadromous hilsa) in northeastern Bangladesh as well as to assess the wetland ecosystem services more thoroughly with the contribution of their fish genetic resources. In addition to laboratory studies, fieldwork was done in the fishing settlements along the Surma River, Hakaluki Haor, and Tanguar Haor. The study classified 77 fish species into 21 subcategories of ecosystem services, of which 56% were not threatened, 17% were vulnerable, and 10% were highly endangered. The species Hilsa was found to be the most economically significant, accounting for 1% of the GDP overall. The study determined if the hilsa stock of the examined wetlands maintains a single or several subpopulations in comparison to other parts of the country when they migrate from saline water to northeastern Bangladesh (freshwater). But when compared to other groups, the FST score was between 0.000 to 0.017, indicating that the populations are identical and that there is genetic material sharing between them. Additionally, these statistics imply that the Sylhet haor and adjacent river systems contain a single stock of Hilsa fish. Nevertheless, a number of stresses and risks, including overexploitation, illicit and destructive fishing, siltation, and natural disasters like flash floods, have been linked to changes in the supply of hilsa and other ecosystem services. This study also emphasizes the necessity of policy attention and research to address the concerns.

In this paper, we introduce a specialized, fully automated experimental arrangement designed for assessing the effectiveness of augmented and virtual reality technologies in healthcare setting and explore its design principles focusing on depth sensor characterization. The main goal of this project is to establish a robust benchtop platform for the quantitative evaluation of extended reality technologies in a controlled environment, emphasizing the practical assessment of augmented reality head-mounted devices. We outline a design concept and considerations for an experimental configuration aimed at creating a realistic testing environment. This apparatus comprises an observation platform mounted on a three-degree-of-freedom motorized system and a test phantom stage. Focusing on real-case scenarios, we utilized a range of sensors, including readily available range-sensing cameras and commercial augmented reality headsets, such as the Intel RealSense L515 LiDAR camera, mounted on the motion control system. The setup enabled automated data collection and facilitates controlled assessments and validation of various facets of augmented reality technologies, including object, hand, and head tracking, as well as static and dynamic image registration. This paper describes the system architecture, the process of automated data collection, and presents several evaluation studies conducted with this setup, providing insights into the quality and temporal noise associated with static or moving objects or observers in augmented reality applications.

To conduct high-precision and high-resolution numerical simulation of complex flow structures in turbomachinery, a high-order finite volume weighted essentially non-oscillatory (WENO) scheme for the large eddy simulation (LES) is improved and embedded into the three-dimensional viscous unsteady CFD solver NUAA-Turbo. Firstly, the spectral characteristics and unsteady convergence of the improved WENO scheme are studied. Compared with the classical WENO scheme, the improved WENO scheme has better dissipation and dispersion characteristics and faster convergence speed. Then, the coefficient CW of the Wall-Adapting Local Eddy-viscosity (WALE) model is calibrated by decaying homogeneous isotropic turbulence (DHIT) test case. Finally, the scheme is applied to conduct high-precision LES calculations of turbulent boundary layer flow, supersonic compression corner flow, and low-pressure turbine cascade separation flow. The numerical simulation results show that this WENO scheme has excellent shock wave capture ability and turbulence resolution and can capture more flow field details with less mesh size, greatly reducing the computational cost and laying a foundation for large-scale engineering application of LES.

To secure logic circuits against the illegal copying the insertion of the so-called key bit inputs using XOR/XNOR gates has been proposed in . The inserted gates modify (lock) the behavior of the original circuit and only the correct choice of the secret key bits guarantees the equivalent behaviour of the locked circuit to the original circuit. To break this kind of security, i.e. to find the secret key bits, there was a SAT solver based attack proposed in . The aim of this work is to experimentally verify this attack on several locked circuits with various number of primary inputs and outputs and with various number of gates. Except for the random placement of the key gates we evaluate also the positioning with chaining elimination. The obtained and presented results show that we were able to unlock 10 of 11 circuits within few minutes on a common PC.

Intermetallic compounds are increasingly being expected to utilize in tribological environments, but to date the works are hindered by insufficient ductility at low and medium temperature. This paper presents a novel multiphase intermetallic alloy with the chemical composition of Mo-40Ni-13Si (at.%). Microstructure characterization reveals that a certain amount of ductile Mo phases formed during the solidification process of ternary Mo-Ni-Si alloy melt, which is undoubtedly beneficial to the ductility improvement of intermetallic alloy. Tribological properties of the designed alloy, including wear resistance, friction coefficient and metallic tribological compatibility, were evaluated under dry sliding wear test conditions at room temperature. Results suggested that the multiphase alloy possesses an excellent property for room-temperature wear applications, which is attributed to the unique microstructural features and thereby good combination in hardness and ductility. The corresponding wear mechanism is also reported by observing the worn surface, subsurface and wear debris of alloy, which to be found is soft abrasive wear.