Search Results (404)

This study presents an experimental optimization of an industrial-scale compressed air system aimed at improving energy efficiency and operational performance. The evaluation was conducted in accordance with ISO 11011 standards, covering supply, distribution, demand, and air quality aspects. Reference and optimized scenarios were directly compared under equivalent operating conditions. The most significant improvement was the elimination of a 0.54-bar pressure drop, which enabled the compressor’s set pressure to be reduced from 7.0 bar to 6.5 bar and prevented unnecessary load cycles. In addition, the detection and repair of leakage points significantly reduced constant loads during non-production hours. As a result, average power consumption decreased by 32.6%, while idle consumption was reduced by 70%. Improvements in filtration and condensate management lowered moisture and oil carryover, thereby enhancing process reliability. Considering annual operating hours, the optimization was estimated to offer a potential reduction of approximately 63.5 tons of CO₂ emissions. The results demonstrate that substantial efficiency and sustainability gains can be achieved through physical adjustments and operational measures without modifying control algorithms. Full article

In automated sorting and grasping of livestock meat cuts, the ideal assumption of symmetric mass distribution is often violated due to irregular morphology and soft tissue deformation. Under the combined effects of gripping forces and gravity, the originally balanced configuration evolves into an asymmetric state, resulting in dynamic shifts of the center of gravity (CoG) that undermine the stability and accuracy of robotic grasping. To address this challenge, this study proposes a CoG trajectory prediction method tailored for meat-cut grasping tasks. First, a dynamic model is established to characterize CoG displacement during grasping, quantitatively linking gripping force to CoG shift. Then, the prediction task is reformulated as a nonlinear state estimation problem, and a Small-Target Bayesian–Probability Hypothesis Density (STB-PHD) algorithm is developed. By incorporating historical error feedback and adaptive covariance adjustment, the proposed method compensates for asymmetric perturbations in real time. Extensive experiments validated the effectiveness of the proposed method: the Optimal Sub-Pattern Allocation (OSPA) metric reached 4.82%, reducing the error by 4.35 percentage points compared to the best baseline MGSTM (9.17%). The task completion time (TC Time) was 6.15 s, demonstrating superior performance in grasping duration. Furthermore, the Average Track Center Distance (ATCD) reached 8.33%, outperforming the TPMBM algorithm (8.86%). These results demonstrate that the proposed method can accurately capture CoG trajectories under deformation, providing reliable control references for robotic grasping systems. The findings confirm that this approach enhances both stability and precision in automated grasping of deformable objects, offering valuable technological support for advancing intelligence in meat processing industries. Full article

Formaldehyde (FA) is commonly used for hatchery disinfection, where it reduces microbial growth, ensures successful egg hatch and enhances healthy production, but its specific effects on embryonic development remain unclear. MicroRNAs (miRNAs) regulate gene expression post-transcriptionally and may mediate FA-induced transcriptional responses. Here, we investigated the impact of FA treatment on miRNA profiles in chicken embryo liver. Small RNA-seq libraries were constructed and sequenced using the Illumina NextSeq platform. Reads were trimmed and quantified using miRDeep2 version 2.0.0.3. Differential expression analysis was performed with DESeq2 (p-adjusted < 0.05 and |log₂FC| > 1). Target genes of differentially expressed miRNAs (DEMs) were predicted with miRDB, and GO/KEGG/Reactome enrichment was conducted. Out of 662 total mature miRNAs detected, differential expression analysis identified 30 DEMs (11 up-regulated, 19 down-regulated). The highest fold increase was determined for gga-miR-3533 (log₂FC = 4.45), and the most significant decrease was determined for gga-miR-133b (log₂FC = −3.38). Pathway analysis revealed miRNAs affecting signaling pathways along with modules related to post-translational protein modification, immune system, and oxidative stress pathways. Our study demonstrates that FA treatment can affect critical biological processes by altering miRNA-mediated regulation in the developing embryonic liver and point to the need for functional validation of miRNA-target interactions to help determine mechanisms for FA benefits. Long term, these data may help serve as reference to identify new treatments with optimized response profiles. Full article

To address path deviation and efficiency reduction issues in traditional interpolation optimization algorithms for complex path machining, this paper proposes a chord error-priority bilevel interpolation optimization method (CPBI). First, arc length parametric modeling of the machining path is performed within the Frenet–Serret framework, yielding curvature and torsion information. After introducing geometric-based multi-machining constraints in the outer layer, the velocity upper limit is established by controlling chord error to dynamically adjust regions with curvature mutation. In the inner layer, combining the velocity limit with bidirectional scanning achieves adaptive optimization of interpolation step size and optimal velocity planning that balances precision and smoothness. Simulation results demonstrate that CPBI effectively reduces the number of interpolation points by 30–50% while ensuring the chord error. Compared with the reference method, the CPBI improved efficiency by 14.31% and 34.72% in machining experiments on S-shaped and wave-shaped paths, respectively. The results validated the CPBI’s high precision and efficiency advantages in complex path machining, providing an effective solution for CNC path optimization in high-end manufacturing. Full article

Currently, the PPP-B2b service faces challenges such as long convergence times and re-convergence issues after signal interruptions due to the lack of high-precision atmospheric enhancement. To address this, this study develops a multi-frequency uncombined Precise Point Positioning (PPP) model that accounts for Clock Constant Bias (CCB) based on PPP-B2b products, extracting atmospheric delays from reference stations and performing regional modeling. Considering the spatiotemporal characteristics of the ionosphere, a stochastic model for enhancement information that varies with time and satellite elevation is established. The performance of atmospheric-enhanced PPP-B2b is validated on the user end. Results demonstrate that zenith wet delay (ZWD) and ionospheric modeling generally achieve centimeter-level accuracy. However, during certain periods, ionospheric modeling errors are significant. By adjusting the stochastic model, approximately 98% of modeling errors can be enveloped. With atmospheric constraints, both convergence speed and positioning accuracy of PPP-B2b are significantly improved. Using thresholds of 30 cm horizontally and 40 cm vertically, the convergence times for horizontal and vertical components are approximately (16.7, 21.3) min for single BDS-3 and (3.8, 5.0) min for the dual-system combination, respectively. In contrast, with atmospheric constraints applied, convergence thresholds are met almost at the first epoch. Within one minute, single BDS-3 and the dual-system combination achieve accuracies better than (0.15, 0.3) m and (0.1, 0.2) m horizontally and vertically, respectively. Furthermore, even under high-elevation cutoff conditions, stable and rapid high-precision positioning remains achievable through atmospheric enhancement. Full article

Background/Objectives: Clozapine remains the gold standard for treatment-resistant schizophrenia. However, its narrow therapeutic window and risk of severe side effects require close monitoring of both clozapine and its primary metabolite, norclozapine. Existing therapeutic drug monitoring (TDM) methods are limited by delays, high costs, and operational complexity. This study introduces three rapid point-of-care (POC) assays utilizing a miniature mass spectrometer (Mini-MS) to quantify clozapine and norclozapine in plasma, whole blood, and dried blood spots (DBSs), facilitating applications across diverse clinical settings. Methods: The analytical performance of the assay was evaluated for sensitivity, specificity, reproducibility, and correlation with reference methods. Clinical samples from two hospitals were analysed and validated against conventional liquid chromatography tandem mass spectrometry (LC-MS/MS) reference standards at New South Wales Health Pathology (NSWHP) and Tsinghua University laboratories. Results: The Mini-MS assay accurately quantified both analytes within therapeutic ranges across all matrices. Inter-assay coefficients of variation ranged from 7.9 to 14.1% for clozapine and from 1.6 to 14.6% for norclozapine. Accuracy fell between 85 and 117% in plasma and blood extracts. Strong linearity was demonstrated (R² = 0.98–0.99) over the concentration range of 10–1000 ng/mL. Results from the Mini-MS analysis showed excellent correlations with LC-MS/MS results (r = 0.998). Conclusions: In this proof-of-concept study, the Mini-MS-based POC assays enable rapid, reliable quantification of clozapine and norclozapine, with performance comparable to conventional laboratory methods. This platform supports real-time TDM, facilitating timely dose adjustments, adherence monitoring, and ultimately improving patient outcomes. Full article

Aiming at the challenges of design complexity and parameter adjustment difficulties in existing distributed controllers, a novel power flow sensitivity-based distributed cooperative control approach is proposed for voltage regulation and power sharing in droop-controlled DC distribution networks (DCDNs). Firstly, based on the power flow model of droop-controlled DCDNs, a comprehensive sensitivity model is established that correlates bus voltages, voltage source converter (VSC) loading rates, and VSC reference power adjustments. Leveraging the sensitivity model, a discrete-time linear state-space model is developed for DCDNs, using all VSC reference power as control variables, along with the weighted sum of the voltage deviation at the VSC connection point and the loading rate deviation of adjacent VSCs as state variables. A distributed consensus controller is then designed to alleviate the communication burden. The feedback gain design problem is formulated as an unconstrained multi-objective optimization model, which simultaneously enhances dynamic response speed, suppresses overshoot and oscillation, and ensures stability. The model can be efficiently solved by global optimization algorithms such as the genetic algorithm, and the feedback gains can be designed in a systematic and principled manner. The simulation results on a typical four-terminal DCDN under large power disturbances demonstrate that the proposed distributed control method achieves rapid voltage recovery and converter load sharing under a sparse communication network. The design complexity and parameter adjustment difficulties are greatly reduced without losing the control performance. Full article

This paper presents a high-sensitivity multi-point seawater temperature detection system based on the virtual Vernier effect, achieved through multiplexed Fabry–Perot (FP) cavities combined with optical frequency-modulated continuous wave (FMCW) interferometry. To address the nonlinear frequency scanning issue inherent in FMCW systems, this paper implemented a software compensation method. This approach enables accurate positioning of multiple FP sub-sensors and effective demodulation of the sensing interference spectrum (SIS) for each FP interferometer (FPI). Through digital signal processing (DSP) algorithms and spectral demodulation, each sub-FP sensor generates an artificial reference spectrum (ARS). The virtual Vernier effect is then achieved by means of a computational process that combines the SIS intensity with the corresponding ARS intensity. This eliminates the need for physical reference arrays with carefully detuned spatial frequencies, as is required in traditional Vernier effect implementations. The sensitivity amplification can be dynamically adjusted with the modulation function parameters. Experimental results demonstrate that an optical fiber link of 82.3 m was achieved with a high spatial resolution of 23.9 $\mathsf{\mu }\mathrm{m}$. Within the temperature range of ${30 }^{\circ }\mathrm{C}$ to ${70 }^{\circ }\mathrm{C}$, the temperature sensitivities of the three enhanced EIS reached −275.56 $\mathrm{pm}{/}^{\circ }\mathrm{C}$, −269.78 $\mathrm{pm}{/}^{\circ }\mathrm{C}$, and −280.67 $\mathrm{pm}{/}^{\circ }\mathrm{C}$, respectively, representing amplification factors of 3.32, 4.93, and 6.13 compared to a single SIS. The presented approach not only enables effective multiplexing and spatial localization of multiple fiber sensors but also successfully amplifies weak signal detection. This breakthrough provides crucial technical support for implementing quasi-distributed optical sensitization sensing in marine environments, opening new possibilities for high-precision oceanographic monitoring. Full article

We report a novel tablet-based reverse titration system for rapid, point-of-use measurement of water hardness, overcoming key limitations of conventional EDTA titration. Reagents are encapsulated in pullulan matrix giving two separate tablets. The first tablet contains the Eriochrome black T (EBT) and N-cyclohexyl-3-aminopropanesulfonic acid (CAPS) buffer, while the second encapsulates ethylenediaminetetraacetic acid (EDTA) disodium salt dihydrate. The system employs a trimodal detection strategy: qualitative screening via immediate color change with the EBT tablet, semi-quantitative estimation through combined tablet dissolution and adjusting the sample volume to a reference level, and quantitative determination using reverse titration, where water is gradually added until the red wine endpoint appears. This approach enhances interference tolerance from competing metal ions and improves accuracy over traditional methods. Testing with real water samples showed excellent agreement with standard titration. The tablets remain stable for over seven months, and the system eliminates the need for skilled personnel, laboratory equipment, or bulky instrumentation. This low-cost, user-friendly, and interference-tolerant platform enables rapid and accurate water hardness assessment at the point of use. Full article

Impurities in polypropylene random copolymer (PPR) raw materials can seriously affect the performance of the final product, and efficient and accurate impurity detection is crucial to ensure high production quality. In order to solve the problems of high small-target miss rates, weak anti-interference ability, and difficulty in balancing accuracy and speed in existing detection methods used in complex industrial scenarios, this paper proposes an enhanced machine vision detection algorithm based on YOLOv11. Firstly, the FasterLDConv module dynamically adjusts the position of sampling points through linear deformable convolution (LDConv), which improves the feature extraction ability of small-scale targets on complex backgrounds while maintaining lightweight features. The IR-EMA attention mechanism is a novel approach that combines an efficient reverse residual architecture with multi-scale attention. This combination enables the model to jointly capture feature channel dependencies and spatial relationships, thereby enhancing its sensitivity to weak impurity features. Again, a DC-DyHead deformable dynamic detection head is constructed, and deformable convolutions are embedded into the spatial perceptual attention of DyHead to enhance its feature modelling ability for anomalies and occluded impurities. We introduce an enhanced InnerMPDIoU loss function to optimise the bounding box regression strategy. This new method addresses issues related to traditional CIoU losses, including excessive penalties imposed on small targets and a lack of sufficient gradient guidance in situations where there is almost no overlap. The results indicate that the average precision (mAP@0.5) of the improved algorithm on the self-made PPR impurity dataset reached 88.6%, which is 2.3% higher than that of the original YOLOv11n, while precision (P) and recall (R) increased by 2.4% and 2.8%, respectively. This study provides a reliable technical solution for the quality inspection of PPR raw materials and serves as a reference for algorithm optimisation in the field of industrial small-target detection. Full article

Multi-material structures have great potential in high-end fields such as aerospace and energy. Which integrate the advantages of various metals and meet the demands of complex working conditions. Among additive manufacturing technologies for multi-material structures, wire-based processes have become a research hotspot due to their high material utilization, low cost, and high efficiency. This article systematically reviews the progress of research on this technology. The working principles and characteristics of common heat sources (WAAM, LWAM, EBAM) are introduced. Furthermore, the advantages and limitations of these heat sources for manufacturing multi-material structures are critically analyzed. Moreover, various metal wire combination systems (such as steel/Ni, Al/steel, Ti/Al, and Cu/Ti, etc.) were reviewed, and the differences and influences of different wire feeding methods and directions were discussed. The review highlights research findings on microstructure regulation, interfacial bonding mechanisms, and the mechanical property optimization of polymetallic structures. The influence laws of critical process parameters on structural properties are also elucidated. The existing problems in the current research were pointed out, and the future development trends were prospected. Unlike previous articles, this review establishes a more comprehensive process–structure–performance framework through the discussion of integrated heat source characteristics, wire feeding systems, and interface adjustment strategies. It aims to provide references for promoting the development and engineering application of additive manufacturing technology for wire-based multi-metal structures. Full article

This research explores a phase-shift-based discontinuous PWM method used for 24 V battery-powered onboard micro inverters, which are critical for thermally limited applications like micromachines, where efficient heat dissipation and compact size are paramount. Discontinuous pulse width modulation (DPWM) reduces switching losses by clamping the phase voltage to the DC bus in order to improve inverter efficiency. Due to the change in power factor at different operating points from motors or the inductor load, the use of only one DPWM method cannot achieve the optimal efficiency of a three-phase voltage source inverter (3ph-VSI). This paper proposes a generalized DPWM method with a continuously adjustable phase shift angle, which extends the six traditional DPWM methods to any type. According to different power factors, the proposed DPWM method is divided into five power factor angle intervals, namely [−90°, −60°], [−60°, −30°], [−30°, 30°], [30°, 60°], and [60°, 90°], and automatically adjusts the phase shift angle to the optimal-efficiency DPWM mode. The power factor is calculated by means of the Synchronous Reference Frame Phase-Locked Loop (SRF-PLL) method. The switching losses and harmonic characteristics of the proposed DPWM are analyzed, and finally, a 24 V onboard 3ph-VSI experimental platform is built. The experimental results show that the efficiency of DPWM methods can be improved by 3–6% and the switching loss can be reduced by 40–50% under different power factors. At the same time, the dynamic performance of the proposed algorithm with a transition state is verified. This method is particularly suitable for miniaturized inverters where efficiency and thermal management are critical. Full article

In this research article, a fast and efficient hybrid Maximum Power Point Tracking (MPPT) control technique is proposed for photovoltaic (PV) systems. The method combines two phases—offline and online—to estimate the appropriate duty cycle for operating the converter at the maximum power point (MPP). In the offline phase, temperature and irradiance inputs are used to compute the real-time reference peak power voltage through an Adaptive Neuro-Fuzzy Inference System (ANFIS). This estimated reference is then utilized in the online phase, where the Robust Backstepping Super-Twisting (RBST) controller treats it as a set-point to generate the control signal and continuously adjust the converter’s duty cycle, driving the PV system to operate near the MPP. The proposed RBST control scheme offers a fast transient response, reduced rise and settling times, low tracking error, enhanced voltage stability, and quick adaptation to changing environmental conditions. The technique is tested in MATLAB/Simulink under three different scenarios: continuous variation in meteorological parameters, sudden step changes, and partial shading. To demonstrate the superiority of the RBST method, its performance is compared with classical backstepping and integral backstepping controllers. The results show that the RBST-based MPPT controller achieves the minimum rise time of $0.018$$\mathrm{s}$, the lowest squared error of $0.3015$$\mathrm{V}$, the minimum steady-state error of $0.29$%, and the highest efficiency of $99.16$%. Full article

Acoustic spiral wavefronts demonstrate linear phase directionality, facilitating precise azimuth estimation in underwater navigation through phase comparison with reference wavefronts characterized by constant phase directionality. The reliability of azimuth estimation depends on the phase directionality accuracy of both the spiral and reference wavefront sources. This study introduces a seven-element transmitting array, constructed using bender disk transducers, which is capable of generating both spiral and reference acoustic wavefronts with minimal phase directionality error. The array design was developed and evaluated using a point source array model and numerical simulations, followed by physical fabrication. To address the sensitivity of the phase–azimuth linearity to manufacturing imperfections in sound sources, a phase error compensation technique was implemented by adjusting the input signal parameters to the acoustic emitters. Experimental validation was conducted in an anechoic water tank, where both spiral and reference wavefronts were transmitted across multiple frequencies. The results reveal that the array prototype achieved sub-degree-level compensated phase directionality accuracy for both wavefront types at all the tested frequencies. Notably, at the resonance frequency of 7.3 kHz, the root-mean-square phase directionality error of the spiral wavefront was reduced to as low as 0.19°. Full article

This study evaluates ground mandarin peel (MP) as a low-cost modifier for sodium-bentonite water-based drilling fluids. Formulations with 2% (w/w) MP and 1–4% bentonite were prepared to locate the composition break point using segmented regression with the Davies test; the threshold was 2.5% bentonite (B/MP ≈ 1.25). Below this level, yield stress drops sharply, and American Petroleum Institute (API) fluid loss increases nonlinearly. Two 3% bentonite muds were then compared: a polymer-stabilized reference (0.3% xanthan gum (XCD), 1% low-viscosity carboxymethyl cellulose (CMC LV), 1% modified starch) and the same package plus 2% MP. Twelve-speed rheometry and API tests showed that adding MP left plastic viscosity essentially unchanged, increased yield stress to ~3.4 Pa, reduced API fluid loss from 9 to 5.5 mL per 30 min, and thinned the filter cake from 0.30 to 0.10 mm. Because MP is a zero-price waste stream, material cost remained essentially unchanged while performance improved. These results support a practical dosing window for MP and a polymer adjustment pathway; high temperature and high-salinity stability require further verification. Full article