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This paper presents a 13-level switched capacitor inverter with a novel modulation method designed to minimize the number of switches and significantly reduce switching losses. The inverter stands out for its simplicity, requiring only ten semiconductor switches to generate 13 levels. A key feature is the inherent self-voltage balancing of the capacitors, which eliminates the need for additional control mechanisms. The inverter's unique architecture, comprising high-voltage and low-voltage modules, enables modulation using a hybrid PWM approach that combines step waveform modulation with level-shifted PWM (LS-PWM). This innovative technique dramatically lowers the switching frequency of the high-voltage module's switches, independent of the carrier frequency, thereby limiting the number of switches in high-frequency operation and achieving substantial reductions in switching losses. This paper provides a detailed analysis of the inverter's operating modes, voltage-balancing mechanisms, and parameter calculations. The advantages of the topology presented in this paper are demonstrated by comparison. Finally, the simulation and experimental results confirm the practicality and effectiveness of the proposed inverter and its modulation strategy. [ABSTRACT FROM AUTHOR]

This study investigates the influence of varying austenitizing temperatures on the microstructure and mechanical properties of 35Si2MnCr2Ni3MoV steel, utilizing Charpy impact testing and microscopic analysis techniques such as scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD). The findings reveal that optimal combination of strength and toughness is achieved at an austenitizing temperature of 980 °C, resulting in an impact toughness of 67.2 J and a tensile strength of 2032 MPa. The prior austenite grain size initially decreases slightly with increasing temperature, then enlarges significantly beyond 1100 °C. The martensite blocks' and packets' structures exhibit a similar trend. The proportion of high–angle grain boundaries, determined by the density of the packets, peaks at 980 °C, providing maximal resistance to crack propagation. The amount of retained austenite increases noticeably after 980 °C; beyond 1200 °C, the coarsening of packets and a decrease in density reduce the likelihood of trapping retained austenite. Across different austenitizing temperatures, the steel demonstrates superior crack initiation resistance compared to crack propagation resistance, with the fracture mode transitioning from ductile dimple fracture to quasi–cleavage fracture as the austenitizing temperature increases. [ABSTRACT FROM AUTHOR]

This study aims to investigate in situ the three-dimensional (3D) morphology and distribution of primary carbides (PCs) in electro-slag remelting (ESR) forged 30Cr3Ni3Mo2V steel. A facile non-aqueous electrolytic etching method was applied to prepare 3D PCs on the matrix. The morphology, composition, and element concentrations of PCs were characterized using a combination of optical microscopy (OM), scanning electron microscopy (SEM) with energy dispersive spectroscopy (EDS), and electron back-scattered diffusion (EBSD). The precipitation, type, and composition of PCs in the same steel were also simulated using Thermo-Calc software Version 2015a. The results indicate that PC is rich in Nb, which is a potential heterogeneous nucleating agent. Both the size and number of PCs increase from the edge to the center of the ingot. The large-sized PCs present three dominant types of morphology, which vary in different regions, i.e., a bulky type dominates in the edge region, a lamellar type dominates in the middle region, and a stripy type dominates in the core region. The results of EBSD analysis show that the orientation of PCs with different morphologies is different and that more nanosized V-rich type carbides are precipitated on the matrix. The thermodynamic calculations show that MC precipitates from the liquid phase when the solid phase fraction is greater than 0.985 and that the MC-type carbides are rich in Nb, which agrees well with the experimental results. [ABSTRACT FROM AUTHOR]

Sarcocystis cruzi in cattle (Bos taurus) and Sarcocystis poephagicanis in yaks (Bos grunniens) are morphologically indistinguishable. However, the relationship between the two parasites is still unclear. Here, muscular tissues of the two species of domestic animal collected from abattoirs in China were examined for sarcocysts of S. cruzi and S. poephagicanis. The sarcocysts isolated from the samples were analyzed using light microscopy (LM), transmission electron microscopy (TEM), and DNA analysis. Sarcocysts of S. cruzi and S. poephagicanis were found in 405 of 950 (42.6%) cattle and 304 of 320 (95.0%) yaks. LM and TEM showed that the sarcocysts of the two parasites had similar morphological characteristics. The thin-walled sarcocysts had hair-like protrusions on the surface. The ultrastructures were demonstrated to include a primary cyst wall containing irregularly folded, hirsute, or bone-like protrusions. Four genetic markers of the two parasites were sequenced and analyzed, namely, 18S rDNA, 28S rDNA, mitochondrial cox1, and apicoplast rpl6. The sequences of the four loci had an interspecific similarity of 97.9–98.6%, 97.2–98.1%, 89.5–90.4%, and 96.9–97.2% identity, respectively. Phylogenetic analysis using 28S rDNA and cox1 sequences indicated that both S. cruzi and S. poephagicanis were placed into a group encompassing Sarcocystis spp. in ruminants with canid as known or putative definitive hosts. Sarcocystis cruzi and S. poephagicanis represent separate species, and cox1 and rpl6 were suitable for distinguishing between them. [ABSTRACT FROM AUTHOR]

In this paper, a high-sensitivity microelectromechanical system (MEMS) piezoelectric accelerometer based on a Scandium-doped Aluminum Nitride (ScAlN) thin film is proposed. The primary structure of this accelerometer is a silicon proof mass fixed by four piezoelectric cantilever beams. In order to enhance the sensitivity of the accelerometer, the Sc0.2Al0.8N piezoelectric film is used in the device. The transverse piezoelectric coefficient d31 of the Sc0.2Al0.8N piezoelectric film is measured by the cantilever beam method and found to be −4.7661 pC/N, which is approximately two to three times greater than that of a pure AlN film. To further enhance the sensitivity of the accelerometer, the top electrodes are divided into inner and outer electrodes; then, the four piezoelectric cantilever beams can achieve a series connection by these inner and outer electrodes. Subsequently, theoretical and finite element models are established to analyze the effectiveness of the above structure. After fabricating the device, the measurement results demonstrate that the resonant frequency of the device is 7.24 kHz and the operating frequency is 56 Hz to 2360 Hz. At a frequency of 480 Hz, the sensitivity, minimum detectable acceleration, and resolution of the device are 2.448 mV/g, 1 mg, and 1 mg, respectively. The linearity of the accelerometer is good for accelerations less than 2 g. The proposed piezoelectric MEMS accelerometer has demonstrated high sensitivity and linearity, making it suitable for accurately detecting low-frequency vibrations. [ABSTRACT FROM AUTHOR]

SAR interferometry (InSAR) has emerged in the big-data era, particularly benefitting from the acquisition capability and open-data policy of ESA's Sentinel-1 SAR mission. A large number of Sentinel-1 SAR images have been acquired and archived, allowing for the generation of thousands of interferograms, covering millions of square kilometers. In such a large-scale interferometry scenario, many applications actually aim at monitoring localized deformation sparsely distributed in the interferogram. Thus, it is not effective to apply the time-series InSAR analysis to the whole image and identify the deformed targets from the derived velocity map. Here, we present a strategy facilitated by the deep learning networks to firstly detect the localized deformation and then carry out the time-series analysis on small interferogram patches with deformation signals. Specifically, we report following-up studies of our proposed deep learning networks for masking decorrelation areas, detecting local deformation, and unwrapping high-gradient phases. In the applications of mining-induced subsidence monitoring and slow-moving landslide detection, the presented strategy not only reduces the computation time, but also avoids the influence of large-scale tropospheric delays and unwrapping errors. The presented detection-first strategy introduces deep learning to the time-series InSAR processing chain and makes the mission of operationally monitoring localized deformation feasible and efficient for the large-scale InSAR. [ABSTRACT FROM AUTHOR]

To evaluate the characteristics of traffic noise under different network structures, an evaluation method is established to clarify the mechanism of traffic noise impacted by variational network structures. First, a stochastic user equilibrium (SUE) model considering intersection delays is developed to allocate traffic flows of different network structures, and a flow-based univariate noise prediction model is used to simulate network noise distribution. Secondly, differentiation indexes including the coefficient of inhomogeneity (COI) and the concept of Lane Area Ratio (LAR) are set to quantify the network structure differences. Finally, a structural equation model (SEM) is developed to investigate the influence mechanism of network structure differentiation on traffic noise. The following conclusions are obtained: (1) The impact of network density differentiation on traffic noise is mainly reflected in the changes of road traffic flow and speed. Traffic noise decreases as the network density increases. In this case, when network density increases by 1 km/km2, traffic noise decreases by 1.6 dB. As network density increases, which means a dispensation of traffic flow, traffic noise is diminished by a reduction in traffic flow and speed. (2) The impact of road spatial location differentiation on traffic noise mainly depends on the number of noise sources. Traffic noise increases with the dense distribution of roads. In this case, when the COI increases by 1, the traffic noise increases by 3.0 dB. A higher COI indicates that the region will be exposed to more noise sources, which leads to traffic noise raises. The study can provide an effective basis for traffic noise control at the initial stage of network planning. [ABSTRACT FROM AUTHOR]

In this paper, an ultrasonic target detection system based on Piezoelectric Micromachined Ultrasonic Transducers (PMUTs) is proposed, which consists of the PMUTs based ultrasonic sensor and the sensor system. Two pieces of 3 × 3 PMUTs arrays with the resonant frequency of 115 kHz are used as transmitter and receiver of the PMUTs-based ultrasonic sensor. Then, the sensor system can calculate the target's position through the signal received by the above receiver. The static and dynamic performance of the proposed prototype system are characterized on black, white, and transparent targets. The experiment results demonstrated that the proposed system can detect targets of different colors, transparencies, and motion states. In the static experiments, the static location errors of the proposed system in the range of 200 mm to 320 mm are 0.51 mm, 0.50 mm and 0.53 mm, whereas the errors of a commercial laser sensor are 2.89 mm, 0.62 mm, and N\A. In the dynamic experiments, the experimental materials are the targets with thicknesses of 1 mm, 1.5 mm, 2 mm and 2.5 mm, respectively. The proposed system can detect the above targets with a maximum detection error of 4.00%. Meanwhile, the minimum resolution of the proposed system is about 0.5 mm. Finally, in the comprehensive experiments, the proposed system successfully guides a robotic manipulator to realize the detecting, grasping, and moving of a transparent target with 1 mm. This ultrasonic target detection system has demonstrated a cost-effective method to detect targets, especially transparent targets, which can be widely used in the detection and transfer of glass substrates in automated production lines. [ABSTRACT FROM AUTHOR]

In this work, a miniaturized, low-cost, low-power and high-sensitivity AlN-based micro-electro-mechanical system (MEMS) hydrophone is proposed for monitoring water pipeline leaks. The proposed MEMS Hydrophone consists of a piezoelectric micromachined ultrasonic transducer (PMUT) array, an acoustic matching layer and a pre-amplifier amplifier circuit. The array has 4 (2 × 2) PMUT elements with a first-order resonant frequency of 41.58 kHz. Due to impedance matching of the acoustic matching layer and the 40 dB gain of the pre-amplifier amplifier circuit, the packaged MEMS Hydrophone has a high sound pressure sensitivity of −170 ± 2 dB (re: 1 V/μPa). The performance with respect to detecting pipeline leaks and locating leak points is demonstrated on a 31 m stainless leaking pipeline platform. The standard deviation (STD) of the hydroacoustic signal and Monitoring Index Efficiency (MIE) are extracted as features of the pipeline leak. A random forest model is trained for accurately classifying the leak and no-leak cases using the above features, and the accuracy of the model is about 97.69%. The cross-correlation method is used to locate the leak point, and the localization relative error is about 10.84% for a small leak of 12 L/min. [ABSTRACT FROM AUTHOR]

Partial discharge (PD) localization is important for monitoring and maintaining high-voltage equipment, which can help to prevent accidents. In this work, an acoustic localization sensor based on microelectromechanical system (MEMS) microphone array is proposed, which can detect and locate the partial discharge through a beam-forming algorithm. The MEMS microphone array consists of eight commercial MEMS microphones (SPV08A0LR5H-1, Knowles Electronics, IL, USA) with an aperture size of about 0.1 m × 0.1 m, allowing for a small hardware size and low cost. In order to optimize the acoustic performance of the array, a random array topology is designed. The simulation analysis indicates that the designed random topology is superior to several commonly used topologies. In terms of the localization algorithm, a deconvolution method called Fourier-based fast iterative shrinkage thresholding algorithm (FFT-FISTA) is applied. Simulation and experiment results demonstrate that FFT-FISTA used in the proposed acoustic localization sensor has significant advantages over the conventional beam-forming algorithm on spatial resolution and sidelobe suppression. Experimental results also show that the average localization error of the proposed scheme is about 0.04 m, which can meet the demands of practical application. [ABSTRACT FROM AUTHOR]

Bowel sounds contain some important human physiological parameters which can reflect information about intestinal function. In this work, in order to realize real-time monitoring of bowel sounds, a portable and wearable bowel sound electronic monitor based on piezoelectric micromachined ultrasonic transducers (PMUTs) is proposed. This prototype consists of a sensing module to collect bowel sounds and a GUI (graphical user interface) based on LabVIEW to display real-time bowel sound signals. The sensing module is composed of four PMUTs connected in parallel and a signal conditioning circuit. The sensitivity, noise resolution, and non-linearity of the bowel sound monitor are measured in this work. The result indicates that the designed prototype has high sensitivity (−142.69 dB), high noise resolution (50 dB at 100 Hz), and small non-linearity. To demonstrate the characteristic of the designed electronic monitor, continuous bowel sound monitoring is performed using the electronic monitor and a stethoscope on a healthy human before and after a meal. Through comparing the experimental results and analyzing the signals in the time domain and frequency domain, this bowel sound monitor is demonstrated to record bowel sounds from the human intestine. This work displays the potential of the sensor for the daily monitoring of bowel sounds. [ABSTRACT FROM AUTHOR]

Previous studies have demonstrated that the suicidality in patients with major depressive disorder (MDD) is related to abnormal brain functional connectivity (FC) patterns. However, little is known about its relationship with dynamic functional connectivity (dFC) based on the assumption that brain FCs fluctuate over time. Temporal stabilities of dFCs within the whole brain and nine key networks were compared between 52 MDD patients and 21 age, sex-matched healthy controls (HCs) using resting-state functional magnetic resonance imaging and temporal correlation coefficients. The alterations in MDD were further correlated with the scores of suicidality item in the Hamilton Rating Scale for Depression (HAMD). Compared with HCs, the MDD patients showed a decreased temporal stability of dFC as indicated by a significantly decreased temporal correlation coefficient at the global level, as well as within the default mode network (DMN) and subcortical network. In addition, temporal correlation coefficients of the DMN were found to be significantly negatively correlated with the HAMD suicidality item scores in MDD patients. These results suggest that MDD may be characterized by excessive temporal fluctuations of dFCs within the DMN and subcortical network, and that decreased stability of DMN connectivity may be particularly associated with the suicidality in MDD. [ABSTRACT FROM AUTHOR]

Simple Summary: Sarcocystis spp. are cyst-forming intracellular protozoan parasites characterized by a two-host prey–predator life cycle. The alpaca (Vicugna pacos) is one of the South American camelids (SACs), and in recent years, this animal was introduced to China to be raised for its meat, skin, and wool and to be kept as tourist attractions and as pets. There is considerable confusion regarding the classification and nomenclature of the species of Sarcocystis in SACs. Two Sarcocystis species, named S. auchenia and S. masoni, are currently regarded as valid in SACs based on sarcocyst morphology and 18S rDNA sequences. However, the definitive host of S. masoni remains unknown. Here, S. masoni sarcocysts in an alpaca were morphologically described and molecularly characterized. Furthermore, the life cycle of S. masoni was completed via experimental animal infection. The present analysis showed that S. masoni has a close relationship with S. cameli in the dromedary camel (Camelus dromedaries), and the relationship between the two parasites needs to be clarified in the future. Only 18S rDNA sequences of Sarcocystis spp. in South American camelids (SACs) are deposited in GenBank as references, and the definitive host of S. masoni in SACs is still unclear. Here, S. masoni sarcocysts detected in an alpaca (Vicugna pacos) in China were investigated with the aid of light (LM) and transmission electron (TEM) microscopy, and characterized using four genetic markers, i.e., 18S rDNA, 28S rDNA and ITS, and the mitochondrial cox1. Additionally, the life cycle of the parasite was completed via experimental animal infection. Under LM, S. masoni sarcocysts exhibited numerous 1.3–2.1 μm conical protrusions. Under TEM, the sarcocyst wall contained conical, cylindrical, or irregular-shaped villar protrusions, similar to type 9j. Two dogs (Canis familiaris) fed S. masoni sarcocysts shed sporocysts with a prepatent period of 8–9 days. The newly obtained 18S rDNA sequences showed 98.4–100% identity with those of S. masoni in SACs previously deposited in GenBank. Interestingly, the newly obtained sequences of 18S rDNA and mitochondrial cox1 shared 99.6–100% and 98.2–98.5% identity, respectively, with those of S. cameli in dromedary camels (Camelus dromedaries). Phylogenetic analysis based on sequences of 18S rDNA, 28S rDNA, or mitochondrial cox1 revealed that S. masoni has a close relationship with Sarcocystis spp. in ruminants. The relationship between S. masoni and S. cameli deserves to be further clarified in the future. [ABSTRACT FROM AUTHOR]

Crocetin is one of the major active constituents of saffron (Crocus sativus L.) which has a reputation for facilitating blood circulation and dispersing blood stasis in traditional Chinese medicine. However, there is little evidence showing the relationship between crocetin intake and the risk of gastrointestinal diseases such as colitis. In order to investigate the effect of crocetin on the regulation of intestinal barrier function and intestinal microbiota composition, mice were treated with crocetin after 3% dextran sulfate sodium (DSS) administration for one week. We found that crocetin intake at 10 mg/kg aggravated colitis in mice, showing increased weight loss and more serious histological abnormalities compared with the DSS group. The 16s rDNA sequencing analysis of the feces samples showed that mice treated with 10 mg/kg crocetin had lower species diversity and richness than those treated with DSS. At the genus level, a higher abundance of Akkermansia and Mediterraneibacter, and a lower abundance of Muribaculaceae, Dubosiella, Paramuribaculum, Parasutterella, Allobaculum, Duncaniella, Candidatus Stoquefichus, and Coriobacteriaceae UCG-002 were observed in the crocetin group. Untargeted metabolomic analyses revealed that crocetin reduced the levels of primary and secondary bile acids such as 12-ketodeoxycholic acid, 7-ketodeoxycholic acid, 3-sulfodeoxycholic acid, 6-ethylchenodeoxycholic acid, chenodeoxycholate, glycochenodeoxycholate-7-sulfate, glycocholate, and sulfolithocholic acid in the colon. In conclusion, crocetin intake disturbed intestinal homeostasis and prolonged recovery of colitis by promoting inflammation and altering gut microbiota composition and its metabolic products in mice. Our findings suggest that patients with gastrointestinal diseases such as inflammatory bowel disease should use crocetin with caution. [ABSTRACT FROM AUTHOR]

Simple Summary: The Pyraloidea is a large superfamily of Lepidoptera in species composition. To date, the higher-level phylogenetic relationships in this group remain unresolved, and many taxa, with taxonomic positions historically established by morphological characters, need to be confirmed through sequencing of DNA, including mitochondrial genome sequences (mitogenomes). Here, we newly generated nine complete mitogenomes for Pyraloidea that shared identical gene content, and arrangements that are typical of Lepidoptera. The current phylogenetic results confirmed previous multilocus studies, indicating the effectiveness of mitogenomes for inference of Pyraloidea higher-level relationships. Unexpectedly, Orybina Snellen was robustly placed as basal to the remaining Pyralidae taxa, rather than nested in the Pyralinae of Pyralidae as morphologically defined and placed. Our results bring a greater understanding to Pyraloidea phylogeny, and highlight the necessity of sequencing more pyraloid taxa to reevaluate their phylogenetic positions. The Pyraloidea is one of the species-rich superfamilies of Lepidoptera and contains numerous economically important pest species that cause great loss in crop production. Here, we sequenced and annotated nine complete mitogenomes for Pyraloidea, and further performed various phylogenetic analyses, to improve our understanding of mitogenomic evolution and phylogeny of this superfamily. The nine mitogenomes were circular, double-stranded molecules, with the lengths ranging from 15,214 bp to 15,422 bp, which are comparable to other reported pyraloid mitogenomes in size. Gene content and arrangement were highly conserved and are typical of Lepidoptera. Based on the hitherto most extensive mitogenomic sampling, our various resulting trees showed generally congruent topologies among pyraloid subfamilies, which are almost in accordance with previous multilocus studies, indicating the suitability of mitogenomes in inferring high-level relationships of Pyraloidea. However, nodes linking subfamilies in the "non-PS clade" were not completely resolved in terms of unstable topologies or low supports, and future investigations are needed with increased taxon sampling and molecular data. Unexpectedly, Orybina Snellen, represented in a molecular phylogenetic investigation for the first time, was robustly placed as basal to the remaining Pyralidae taxa across our analyses, rather than nested in Pyralinae of Pyralidae as morphologically defined. This novel finding highlights the need to reevaluate Orybina monophyly and its phylogenetic position by incorporating additional molecular and morphological evidence. [ABSTRACT FROM AUTHOR]

In this paper, a novel ring-down suppression system based on transfer function is proposed for the first time to suppress the ring-down time and decrease the blind area of PMUTs (Piezoelectric Micromachined Ultrasonic Transducers). This suppression system includes a transfer function and a simple P (proportion) controller, which can reduce the ring-down time without degrading any performances of PMUTs. The transfer function serves as a virtual PMUT device, feeding its output into the P controller; then, the P controller generates a suppression signal to the actual PMUT device. The ring-down time of a 115-kHz PMUT array is demonstrated to be reduced by up to 93% through the suppression system. In addition, the P controller has been experimentally optimized, reducing the blind area of the PMUT array by about 40%. Moreover, a low ring-down PMUTs system design guideline is established, which is practical and straightforward for industrial scenarios. Finally, the system can be easily integrated into ASIC (Application Specific Integrated Circuit). [ABSTRACT FROM AUTHOR]

The design and implementation of the filters for the fifth-generation (5G) mobile communication systems are challengeable due to the demands of high integration, low-cost, and high-speed data transmission. In this paper, a dual-wideband bandpass filter (BPF) and a tri-wideband BPF for 5G mobile communications are proposed. The dual-wideband BPF consists of two folded open-loop stepped-impedance resonators (FOLSIRs), and the tri-wideband BPF is designed by placing a pair of folded uniform impedance resonator inside the dual-wideband BPF with little increase in the physical size of the filter. By employing a novel structural deformation of a stepped-impedance resonator, the FOLSIR is achieved with a more compact structure, a controllable transmission zero, and an adjustable resonant frequency. The measurement results show that the working bands of the two filters are 1.98–2.28/3.27–3.66 GHz and 2.035–2.305/3.31–3.71/4.54–5.18 GHz, respectively, which are consistent with the full-wave EM simulation results. The implemented filters have a compact size and the results show low loss, good out-of-band rejection, and wide passbands covering sub-6 GHz bands of 5G mobile communications and a commonly used spectrum. [ABSTRACT FROM AUTHOR]

One of the major issues in developing convective-scale ensemble forecasts is what is widely known as under-dispersion. This can be addressed through the consideration of spatial uncertainties via post-processing, motivating the development of various techniques to represent the spatial uncertainties of ensembles. In this study, a recently developed fraction-based approach (the ensemble agreement scale, EAS) is applied to characterize the spatial predictability and spread–skill performances of precipitation forecasts using a WRF-EnKF convective-scale ensemble forecast system over the Yangtze and Huai river valleys, China. Fourteen heavy rainfall events during the Meiyu season of 2013 and 2014 were classified into two categories—strong forcing (SF) and weak forcing (WF)—using the convective adjustment timescale. The results show that the spatial predictability and spread–skill relationship are highly regime-dependent and that both exhibit lower values under WF. Furthermore, a new object-based probabilistic approach (OBJ_NEP) is proposed as a supplement to traditional neighborhood ensemble probability (NEP) and a recently proposed fraction-based approach (EAS_NEP). The results of the application of OBJ_NEP are evaluated, and a comparison is made between NEP and EAS_NEP for the analysis of experiments involving both idealized and 'real' events by using objective verification methods. The results imply that OBJ_NEP can be effectively employed under different large-scale forcings. Consequently, these results can aid the understanding of spatial-based approaches to probabilistic forecasting, which has been widely applied to post-processing processes of convective-scale ensemble forecast systems (CSEFs) in recent years. [ABSTRACT FROM AUTHOR]

Radio frequency identification (RFID) is well known as an identification, track, and trace approach and is considered to be the key physical layer technology for the industrial internet of things (IIoT). However, IIoT systems have to introduce additional complex sensor networks for pervasive monitoring, and there are still challenges related to item-level sensing and data recording. To overcome the shortage, this work proposes an artificial intelligence (AI)-assisted RFID-based multi-sensing technology. Both passive and semi-passive RFID tag-integrated multi-sensors are developed. The main contributions and the novelty of this investigation are as follows. A UHF RFID tag-integrated multi-sensor with a boosted charge pump is proposed; it enables high RF signal sensitivity and a long operational range. The whole hardware design, including the antenna and energy harvester, are studied. Moreover, a demonstration with real-world ham product sensing data is conducted. This work also proposes and successfully demonstrates the integration of machine learning algorithms, specifically the NARX neural network, with RFID sensing data for food product quality assessment and sensing (QAS). This application of machine learning to RFID-generated data for quality assessment is also a novel aspect of the research. The deployment of an autoregressive model with an exogenous input (NARX) neural network model, tailored for nonlinear processes, emerges as the most effective, achieving a root mean square error (RMSE) of 0.007 and an R-squared value of 0.99 for ham product QAS. By deploying the technology, low-cost, timely, and flexible product QAS can be achieved in manufacturing industries, which helps product quality improvement and the optimization of the manufacturing line and supply chain.

Machine-to-machine (M2M) communication is a key enabling technology for industrial internet of things (IIoT)-empowered industrial networks, where machines communicate with one another for collaborative automation and intelligent optimisation. This new industrial computing paradigm features high-quality connectivity, ubiquitous messaging, and interoperable interactions between machines. However, manufacturing IIoT applications have specificities that distinguish them from many other internet of things (IoT) scenarios in machine communications. By highlighting the key requirements and the major technical gaps of M2M in industrial applications, this article describes a collaboration-oriented M2M (CoM2M) messaging mechanism focusing on flexible connectivity and discovery, ubiquitous messaging, and semantic interoperability that are well suited for the production line-scale interoperability of manufacturing applications. The designs toward machine collaboration and data interoperability at both the communication and semantic level are presented. Then, the application scenarios of the presented methods are illustrated with a proof-of-concept implementation in the PicknPack food packaging line. Eventually, the advantages and some potential issues are discussed based on the PicknPack practice., Competing Interests: The authors declare no conflict of interest.

A metal-insulator-metal structure resistive switching device based on H 0.5 Z 0.5 O₂ (HZO) thin film deposited by pulse laser deposition (PLD) has been investigated for resistive random access memory (RRAM) applications. The devices demonstrated bistable and reproducible unipolar resistive switching (RS) behaviors with an extremely high OFF/ON ratio over 5400. The retention property had no degradation at 6 × 10⁴ s. The current-voltage characteristics of the HZO samples showed a Schottky emission conduction in the high voltage region (V reset < V < V set ), while at the low voltage region (V < V reset ), the ohmic contact and space charge limited conduction (SCLC) are suggested to be responsible for the low and high resistance states, respectively. Combined with the conductance mechanism, the RS behaviors are attributed to joule heating and redox reactions in the HZO thin film induced by the external electron injection.