Search Results (710)

At temperatures higher than 5 °C in the cooling chambers of refrigeration systems, bacteria multiply rapidly on fresh fishes, thereby leading to an increased risk of foodborne diseases. Maintaining the storage temperature within the recommended bounds of 0 °C and 5 °C is needed to maintain food safety and quality. This study presents model predictive control of a data-driven medium-temperature cold storage system using subspace system identification techniques. The identified linear model presents a holistic view of the whole system, with each subsystem cohesively linked together. The data-driven model was developed from synthetic data derived from a high-fidelity simulation benchmark model of a supermarket refrigeration system from Aalborg University, Denmark. The benchmark model consists of a medium-temperature closed display case, the suction manifold, and the compressor rack. The data of the expansion valve, suction pressure, compressor capacity, heat transfer rate, and ambient temperature were taken as inputs, while the data of the air and goods temperatures were taken as outputs based on expert knowledge. A linear model predictive controller was designed to control the temperature outputs of the identified linear model, and the outputs were compared with the proportional–integral dead band control used in the benchmark. Simulation results for 24 h showed that the model predictive controller was able to achieve an air temperature and a goods temperature within the recommended temperature range of 0 °C and 5 °C that guarantees safe storage of fresh fishes. These results imply that a reduced-order model of a commercial refrigeration system that is robust, reliable, and stable can be developed and controlled to achieve the goal of food safety, thereby guaranteeing food security and reducing costs. Full article

This paper reports initial experimental results related to the preparation of colored anodic titania thin layers using various deep eutectic solvent (DES)-based formulations. Electrolytes based on choline dihydrogen citrate–oxalic acid–ethylene glycol (1:1:1 molar ratio), choline chloride–oxalic acid (1:1 molar ratio) and choline chloride–lactic acid (1:2 molar ratio) eutectic mixtures were investigated. The anodization has been performed at constant voltage in a range of 10–100 V for various periods of time between 1 and 5 min at room temperature under mild stirring. A brief description of anodization procedures, as well as of some characteristics, from appearance and morphological viewpoints, is presented. A quantitative analysis of color characteristics in relation to the DES-based electrolyte and applied voltage using the CIELAB system is also discussed. The achieved chromatic scale follows this order of colors: golden—blue—light blue—light blue/green—pink—violet. This depends on the applied potential and the DES-based electrolyte. The films present a relatively high brightness and color saturation. The hue vs. anodization voltage diagrams suggest an almost linear dependence of the oxide growth measured against the applied voltage. The corrosion performance has been assessed through continuous immersion tests in (i) 0.5 M NaCl for 240 h and (ii) Hank’s biological solution for 96 h with intermediate visual examinations and recording corrosion potential, as well as potentiodynamic polarization curves and impedance spectra at open circuit potential. Different corrosion performances are discussed considering the aggressive medium involved and the used DES-based systems. Full article

Brake pedals and wheel braking units are mechanically decoupled in brake-by-wire systems. This causes the driver to lose the familiar pedal feel. To address this issue, this paper designed an active braking pedal simulator based on the long-travel Halbach-array linear motor. Firstly, this paper conducted both qualitative and quantitative analyses on the pedal characteristics of a traditional hydraulic braking system and used them as a reference. A dual-coil independent control strategy was designed in order to overcome the thrust instability at the junction of the Halbach-array magnetic field. This enables the linear motor to achieve smooth and continuous thrust output throughout the entire travel range. Secondly, this paper also designed a “linear motor + spring” solution to reduce energy consumption and peak motor thrust. By conducting a quantitative analysis of the relationship between the spring stiffness, motor work and peak thrust, the spring stiffness was optimized. The results show that when the spring stiffness is 3.73 N/mm, the motor work can be reduced to 5.92 Joules while significantly reducing the peak thrust. Finally, this paper also established a testing platform. It was used to verify the performance of the proposed pedal simulator under low-intensity, medium-intensity, and high-intensity braking conditions as well as an anti-lock braking system intervention. The testing results show that the pedal simulator can actively adjust the pedal characteristics according to the braking intensity, and it can provide clear vibration feedback during the anti-lock braking system intervention. Therefore, the proposed pedal simulator effectively simulates the pedal feel of hydraulic braking systems while improving energy efficiency and operational stability. It provides a feasible solution for enhancing the driver–vehicle interaction and the driving comfort of brake-by-wire systems. Full article

The prevalence of radio frequency signals in indoor environments has in recent years given rise to new technologies across many domains such as robotics, healthcare, and surveillance. Radio frequency signals propagate in the wireless medium through multiple paths and carry useful environment-dependent information. Capturing and analyzing these signal patterns can offer new solutions for a number of applications relevant to ranging, tracking, perception and recognition. In this work we propose a novel architecture, separating physical, back-bone networks, and inference layers, towards fully ubiquitous passive recognition systems that scale with the number of environments and applications. We propose a back-bone architecture that utilizes a novel Cross Dual-Path Attention (CDPA) block to capture spatial and temporal correlations from Channel State Information (CSI) for device-free, multi-task applications. Subsequently, a distill and transfer algorithm is proposed to generalize the inference capabilities of CDPA over multiple target environments for scalable training and reduced computational costs. By sharing knowledge between models across a shared network, experimentation shows that edge devices can be deployed with improved performance while simultaneously meeting strict computation and memory requirements. Our distributed learning paradigm demonstrates that CDPA-based models are capable of using passive signals in a non-intrusive and privacy-protecting manner, in order to achieve ubiquitous recognition at scale in smart environments. Full article

Microplastics spread through the environment in various ways. Inland waters are an ideal medium for their dispersal, as they collect pollutants from various sources and transport them over long distances. From there, microplastics can enter the marine environment, break down into smaller particles or end up in drinking water treatment plants. However, the fate, transport and potential health effects of microplastics after ingestion of drinking water and water in food are not yet fully understood. It is therefore necessary to evaluate the quantification and identification of microplastics in drinking water by analysing real samples in order to assess the potential impact on human health. To this end, microplastic contamination in 32 treated drinking water samples from a surface water treatment plant in north-eastern Italy were analysed using micro-Fourier transform infrared spectroscopy (µ-FT-IR). The results indicated low levels of contamination, with all the samples containing less than 170 microplastics per litre, which is in line with European drinking water levels. Polyolefins with size 50–500 µm, such as polypropylene and polyethylene, were the predominant polymers detected (50.2%), while surprisingly polyethylene terephthalate was scarcely present (0.1%, size range 10–50 µm). Statistical analysis revealed a significant negative correlation between microplastic concentration and sampling volume, with larger volumes yielding fewer particles. This inconsistency likely results from the lack of bottle rinsing when only a fraction of the sampling volume is filtered. It was also found that rinsing the sampling bottles with ethanol alone prior to analysis was sufficient to ensure accurate quantification. These results highlight the challenges in standardising the detection of microplastics in drinking water and underline the need for optimised sampling protocols. Full article

The microstructure and properties of a cobalt-free, cost-effective Al_0.4CrFe₂Ni₂ medium-entropy alloy (MEA) after multi-stage thermomechanical processing, including annealing, rolling over a wide temperature range from hot to cryogenic conditions, and subsequent precipitation strengthening, were investigated in the present study. The initially cast microstructure was effectively homogenized through hot rolling with an 80% thickness reduction followed by homogenization annealing, resulting in the formation of a single-phase supersaturated solid solution and enhanced stability of plastic deformation. Strengthening of the MEA was achieved by rolling under both ambient and cryogenic conditions, with the deformation process predominantly governed by shear band formation. However, rolling under cryogenic conditions led to a more pronounced localization of plastic deformation, promoting the formation of deformation nanotwins and resulting in significantly higher strengthening compared to ambient rolling, with the alloy reaching a yield strength of 1040 MPa and an ultimate tensile strength of 1235 MPa. Precipitation hardening was governed by the formation of B2-type (ordered body-centered cubic, BCC) precipitates, which preferentially nucleated along deformation bands, thereby effectively strengthening the alloy to a yield strength of 1420 MPa and an ultimate tensile strength of 1465 MPa. Our results demonstrate that the investigated MEA offers a wide range of tunable mechanical properties, which can be effectively tailored through appropriate combinations of thermomechanical processing routes. Full article

During coal mining, detecting subsurface structures (such as faults, voids, collapse columns, etc.) using radio waves in existing mines is hindered by the absence of effective three-dimensional coal seam medium models and simulation methods, adversely affecting the forward modeling of data analysis. This study establishes a Three-Dimensional Finite-Difference Time-Domain (3D-FDTD) radio wave penetration medium model based on coal seam tunnel penetration working conditions to simulate the electric field intensity characteristics of longitudinal and transverse waves in various coal rock mediums. Firstly, a higher-order finite difference method based on Maxwell’s equations is employed to analyze the electric field characteristics of gas-enriched areas under various geological conditions, enabling the exploration of the relationship between the position and size of the electromagnetic wave field strength in different areas. The electromagnetic wave field strength response data are then analyzed during the actual detection process to determine the specific location, shape, and size of the abnormal area. Finally, by comparing the simulation results with an actual engineering project, electromagnetic wave field strength attenuation data were collected from 158 measuring points at a working face of a coal mine in Anhui. The detection results clearly illustrate the changes in electric field intensity (with attenuation coefficients ranging from 0.41 to 0.77 dB/m) in anomalous areas, enabling the forward simulation to accurately determine the position and size of faults. The novelty of this study lies in the establishment of a conductivity-weighted 3D-FDTD model specifically calibrated for complex coal seam environments, which significantly improves the accuracy of fault boundary detection compared to traditional linear inversion methods. Full article

Bee-derived products such as apitoxin, royal jelly, propolis, bee pollen, and honey are increasingly being used as part of cosmetic products because all of them contain a large number of bioactive compounds with antioxidant, anti-inflammatory, antimicrobial, and regenerative properties, which enable them to be used for therapeutic purposes. The aim of this investigation was to assess the performance of an automated growth-based system in order to make a quantitative examination of the total aerobic viable counts in bee-derived personal care products using NF-TVC vials that contained a nutrient-based medium with dextrose as the carbon source. According to USP general chapter <1223>, pivotal validation criteria such as linearity, equivalence of results, operative range, precision, accuracy, ruggedness, limit of quantification, and limit of detection have demonstrated that the automated system can be used for a reliable total aerobic viable count. Moreover, the actual research demonstrated that polysorbates efficiently block the antimicrobiological potential of bioactive compounds, such as phenols, flavonoids, enzymes, peptides, and fatty acids, which naturally occur in apitoxin, royal jelly, propolis, bee pollen, and honey, allowing for efficient microorganism recovery from the bee-made products tested. Therefore, this AGBS could be applied efficiently within the cosmetic industry to assess the total aerobic viable count in bee-derived products such as capillary treatments, toothpaste, and anti-aging cream, affording several benefits associated with faster product release into the market. Full article

Rapid, sensitive, and environmentally sustainable spectrophotometric methods for the determination of nitrite (${{\mathrm{N}\mathrm{O}}_2}^{-}$) in environmental specimens are proposed. The presented procedures are grounded in the diazotization of sulphathiazole (STZ), followed by coupling with rhodanine (RDN) or 7-hydroxycoumarin (7-HC) in an alkaline medium, and the results were studied. This reaction gave an intense soluble red color at 504 nm and a pale red color at 525 nm for RDN and 7-HC, respectively. The conditions producing the maximum performance and other important analytical criteria in relation to the proposed procedures were investigated to enhance their sensitivity. Beer’s law was abided by for ${{\mathrm{N}\mathrm{O}}_2}^{-}$ over the concentration ranges of 0.08–2.0 µg mL⁻¹ and 0.04–2.4 µg mL⁻¹ using RDN and 7-HC, respectively. The lower limit of detection (LLOD), lower limit of quantification (LLOQ), molar absorptivity (ε), and Sandell’s sensitivity were calculated as follows: 0.0303 µg mL⁻¹, 0.0918 µg mL⁻¹, 4.20 × 10⁴ L mol⁻¹ cm⁻¹, and 1.63 × 10⁻⁶ µg cm⁻² (in the case of RDN); and 0.0387 µg mL⁻¹, 0.1172 µg mL⁻¹, 6.90 × 10⁴ L mol⁻¹ cm⁻¹, and 1.00 × 10⁻⁶ µg cm⁻² (in case of 7-HC). Furthermore, the ecological implications were assessed using three green assessment methodologies: Analytical Eco-Scale (ESA), Analytical GREEnness metric (AGREE), and Green Analytical Procedure Index (GAPI). Thus, our proposed procedures are fully validated and implemented in order to carry out ${{\mathrm{N}\mathrm{O}}_2}^{-}$ quantification in the selected ecological samples (water and soil samples). Full article

Hericium erinaceus is a fungus that, in addition to its health-promoting properties (including regenerative properties for gastrointestinal membranes and support for neuronal regeneration in neurodegenerative diseases such as Parkinson’s disease), has the ability to synthesize valuable metabolites, such as flavonoids (polyphenols) and terpenoids. These compounds possess strong biocidal properties. These substances provide the growing H. erinaceus mycelium with protection against colonization by other species of rot fungi, such as Trametes versicolor. For these reasons, the biological compounds produced by H. erinaceus can be used to produce ecological fungicides, which will find innovative applications in protecting forest tree seedlings. It should also be emphasized that valuable fungal substances are synthesized primarily by the mycelium of H. erinaceus during the initial stages of its development. Therefore, we undertook to develop an updated and modernized methodology for cultivating H. erinaceus mycelium in the laboratory, with the goal of commercializing the production of this mycelium, which will be used to isolate fungicidal substances metabolized by the fungus cultures. The biocidal substances obtained will be used to produce innovative fungicides in order to protect forest tree seedlings. The studies were conducted using various types of nutrient media, including Potato Dextrose Agar (PDA), Malt Extract Agar (MEA), and wort medium, at various temperatures ranging from 15 °C to 25 °C. Simultaneously, experiments were conducted using solidified media with a pH ranging from 4.0 to 7.0. The research was also expanded to include the growth and execution of experiments using a processed wood substrate, namely, sawdust made from individual structural wood elements. The sawdust was prepared from the bark, sapwood, and heartwood of sessile oak. The PDA medium was more favourable to the mycelium growth of H. erinaceus at 25 °C. It was also found that an acidic pH in the range of 4.0–5.0 significantly influenced the changes in the growth rate of the mycelium species and their phenotype. It was observed that mycelial growth on a substrate of oak sawdust made from sapwood resulted in intensive mycelial growth and a significant reduction in the wood substrate compared to sawdust made from bark, heartwood, and a mixture of all types of sawdust. The reason for the low mycelial growth, low mass reduction and slight reduction in the mass of sawdust made from bark, heartwood, and a mixture of all types of sawdust was the presence of high levels of tannins, which inhibited the fungal growth. Full article

Implantable intrabody communication (IBC) is a method that enables low-power, high-security communication between implanted in-body devices that could track biomedical signals and an on-body receiver by using the human body as a communication medium. As the human body consists of various tissues that each have different conductivity, this paper explores the effects of the conductivity of the communication medium on the channel gain over a wide frequency range from 10 MHz up to 300 MHz through the measurements and two models: an electrical circuit model and a FEM simulation model. Measurements are conducted using a liquid phantom with varying conductivity values from 0 S/m up to 1 S/m, covering most human tissues in the frequency range of interest. The circuit and FEM models are designed to mimic the measurement setup in order to verify the measurement results. Results show that the circuit model predicts the communication channel characteristics well at lower frequencies but cannot account for the influence of the measurement setup at higher frequencies. The influence of wire inductances, which can cause a resonant behavior when measuring at frequencies above 100 MHz, was observed using the FEM model. The results also show that the higher the conductivity of the tissue in which the device is implanted, the lower the gain of the signal, with the difference in gain being more prominent when capacitive termination with a high-impedance load is used instead of low-impedance termination. These findings provide valuable insight for selecting the appropriate interface (low-impedance vs. high-impedance termination) across specific frequency ranges for in-body to on-body (IB2OB) communication devices, while illustrating the effect of tissue conductivity on an IBC channel, thereby supporting the optimized design and implementation of reliable IB2OB communication systems. Full article

Direct detection (DD) is a straightforward, cost-effective receiving scheme for medium- and short-range fiber-optic communication systems, yet directly accessing phase information presents inherent challenges. The temporal transport-of-intensity equation (T-TIE) enables phase recovery from intensity data, but the accuracy of this phase-retrieval method is constrained by finite difference approximation errors of intensity derivatives and electrical noise interference. In this paper, we propose a 4th-order central difference method for calculating intensity derivatives to enhance approximation accuracy and implement multiple intensity measurements to further mitigate electrical noise interference. The proposed method is validated in a 28 GBaud single-carrier 16-quadrature amplitude modulation (16QAM) direct detection system. The research results indicate that, under conditions of 10 nA dark current and 20 pA/Hz^^1/2 thermal noise, our method achieves a receiver sensitivity gain of 14.85 dB compared with the 1st-order forward difference method and 8.47 dB compared with the 2nd-order central difference method at the 7% hard decision forward error correction (7% HD-FEC) threshold. Full article

Copper and nickel ions play pivotal, albeit distinct, roles as essential trace elements in living systems, and primarily serve as co-factors for a range of enzymes. However, as with all trace metal ions, excessive concentrations can exert adverse toxicological properties. Interestingly, the incorporation of these in cell culture media can establish novel chemical interactions, with their speciation status markedly influencing characteristics, including cell maturation, and cellular uptake mechanisms. Thus, the primary objective of this study was to investigate and determine the speciation status (i.e., complexation) of nickel(II) and copper(II) ions by biomolecules present in RPMI 1640 mammalian cell culture medium using virtually non-invasive high-resolution proton NMR analysis, an investigation of much relevance to now routine studies of their toxicological actions towards cultured cells. Samples of the above aqueous culture medium were ¹H NMR-titrated with increasing added concentrations of 71–670 µmol/L Ni(II)(aq.), and 0.71–6.7, 7.1–67 and 71–670 µmol/L Cu(II)(aq.), in duplicate or triplicate. ¹H NMR spectra were acquired on a JEOL ECZ-600 spectrometer at 298 K. Results demonstrated that addition of increasing concentrations of Ni(II) and Cu(II) ions to the culture medium led to the selective broadening of a series of biomolecule resonances, results demonstrating their complexation by these agents. The most important complexants for Ni(II) were histidine > glutamine > acetate ≈ methionine ≈ lysine ≈ threonine ≈ branched-chain amino acids (BCAAs) > asparagine ≈ aspartate > tyrosine ≈ tryptophan, whereas for Cu(II) they were found to be histidine > glutamine > phenylalanine ≈ tyrosine ≈ nearly all remaining aliphatic metabolites (particularly the wealth of amino acids detectable) > 4-hydroxyphenylacetate (trace culture medium contaminant), in these orders. However, Cu(II) had the ability to influence the linewidths of these signals at much lower added levels (≤7 µmol/L) than that of Ni(II), the broadening effects of the latter occurring at concentrations which were approximately 10-fold greater. Virtually all of these added metal ion-induced resonance modifications were, as expected, reversible on addition of equivalent or excess levels of the chelator EDTA. From this study, changes in the co-ordination sphere of metal ions in physiological environments can give rise to marked modifications in their physicochemical properties (e.g., redox potentials, electronic charges, the potential catalytic generation of reactive oxygen species (ROS), and cell membrane passages). Moreover, given that the above metabolites may also function as potent hydroxyl radical (^●OH) scavengers, these findings suggest that generation of this aggressively reactive oxidant directly from Cu(II) and Ni(II) ions in physiologically-relevant complexes may be scavenged in a ‘site-dependent’ manner. This study is of further relevance to trace metal ion research in general since it enhances our understanding of the nature of their interactions with culture medium biomolecules, and therefore provides valuable information regarding their overall chemical and biological activities, and toxicities. Full article

Although the elevated orbit and highly squinted observation geometry bring advantages for medium-earth-orbit (MEO) synthetic aperture radar (SAR) in applications, they also complicate signal processing. The severe spatial variability of Doppler parameters and large extended range distribution of echo make it challenging for the traditional imaging algorithms to get the expected results. To quantify the variation, a spatially variable two-dimensional (SV2D) spectrum is established in this paper. The sufficient order and spatially variable terms allow it to preserve the features of targets both in the scene center and at the edge. In addition, the huge data volume and incomplete azimuth signals of edge targets, caused by the large range walk when MEO SAR operates in squinted mode, are alleviated by the variable pulse repetition interval (VPRI) technique. Based on this, a novel data-focusing method for highly squinted MEO SAR is proposed. The azimuth resampling, achieved through the non-uniform fast Fourier transform (NUFFT), eliminates the impact of most Doppler parameter space variation. Then, a novel imaging kernel is applied to accomplish target focusing. The spatially variable range cell migration (RCM) is corrected by a similar idea, with Doppler parameter equalization, and an accurate high-order phase filter derived from the SV2D spectrum guarantees that the targets located in the center range gate and the center Doppler time are well focused. For other targets, inspired by the non-linear chirp scaling algorithm (NCSA), the residual spatially variable mismatch is eliminated by a cubic phase filter during the scaling process to achieve sufficient focusing depth. The simulation results are given at the end of this paper and these validate the effectiveness of the method. Full article

Air pollution is an important environmental issue that affects social development and human life. Atmospheric fine particulate matter (PM_2.5) is the primary pollutant affecting the air quality of most cities in the authors’ country. It can cause severe haze, reduce air visibility and cleanliness, and affect people’s daily lives and health. Therefore, it has become a primary research object. Ground monitoring and satellite remote sensing are currently the main ways to obtain PM_2.5 data. Satellite remote sensing technology has the advantages of macro-scale, dynamic, and real-time functioning, which can make up for the limitations of the uneven distribution and high cost of ground monitoring stations. Therefore, it provides an effective means to establish a mathematical model—based on atmospheric aerosol optical thickness data obtained through satellite remote sensing and PM_2.5 concentration data measured by ground monitoring stations—in order to estimate the PM_2.5 concentration and temporal and spatial distribution. This study takes the Yangtze River Delta region as the research area. Based on the measured PM_2.5 concentration data obtained from 184 ground monitoring stations in 2023, the newly released sixth version of the MODIS aerosol optical depth product obtained via the US Terra and Aqua satellites is used as the main prediction factor. Dark-pixel AOD data with a 3 km resolution and dark-blue AOD data with a 10 km resolution are combined with the European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis meteorological, land use, road network, and population density data and other auxiliary prediction factors, and XGBoost and LSTM models are used to achieve high-precision estimation of the spatiotemporal changes in PM_2.5 concentration in the Yangtze River Delta region. Full article