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ObjectiveTo investigate the quality standards and anti-proliferative effects of Gardenia jasminoides J.Ellis (GJE) at different harvesting periods, and to determine the optimal harvesting time for anti-cancer applications.MethodsA fast, simple, and accurate analytical method was established using UFLC/Q-TOF-MS technology in positive and negative ion modes to identify differential components in GJE samples collected at seven harvesting periods. The anti-proliferative effects of GJE extracts were evaluated against MCF7 breast cancer and HepG2 hepatocellular carcinoma cell lines using MTT assay.ResultsA total of 52 components were successfully identified from GJE samples, including iridoid glycosides, flavonoids, and phenolic acids. GJE demonstrated stronger anti-proliferative effects against HepG2 cells compared to MCF7 cells. The anti-proliferative activity increased progressively with fruit maturation, reaching peak efficacy at stages 5–6 (orange-red to red fruits) and declining at stage 7 (overripe dark red fruits). Most iridoid glycosides, flavonoids and phenolic acids showed increasing trends during the growth process, correlating with enhanced anti-proliferative effects.ConclusionGJE may serve as a potential source for developing anti-cancer therapeutic agents due to its demonstrated anti-proliferative activity. The mature fruits at stages 5–6 are most suitable for anti-cancer applications, providing scientific guidance for optimal harvesting time and quality standardization of GJE as a medicinal material.

The oil yield, fatty acid (FA) composition, physicochemical, quality characteristics and thermal properties were studied in flax, perilla, and basil seed oils cultivated in Iran. Also the similarities and differences among these seed oils were investigated using principal component analysis (PCA). The results indicated that perilla seed oil contained the highest lipid content followed by flax and basil seed oils. The n-6/n-3 FA ratios of these oils had a range of 0.190–0.320, which was notably lower than those of most vegetable oils. Trilinolenin as the predominant triacylglycerol in the studied flax, perilla, and basil seed oils was found at 21.3, 32.0, and 27.5%, respectively. The bioactive compounds, namely tocols, phytosterols, and total phenolics, present in basil and perilla oils were higher than those of flax seed oil. The results of differential scanning calorimeter indicated that the thermal properties of these seed oils were varied, with lower melting and crystallization peak temperature for perilla and basil seed oils. The results of PCA showed that these seed oils could be distinguished using some components however, C14:0, C16:0, C18:3, UFA and ECN 42 could not be used to discriminate among these seed oils. The results were suggestive of the proper nutritional qualities of the studied oils and their possibly being the potential sources of FAs for enriching the diets with α-linolenic acid and other functional compounds.

Recent work has demonstrated the use of sparse sensors in combination with the proper orthogonal decomposition (POD) to produce data-driven reconstructions of the full velocity fields in a variety of flows. The present work investigates the fidelity of such techniques applied to a stalled NACA 0012 aerofoil at$ {Re}_c=75,000 $at an angle of attack$ \\alpha ={12}^{\\circ } $as measured experimentally using planar time-resolved particle image velocimetry. In contrast to many previous studies, the flow is absent of any dominant shedding frequency and exhibits a broad range of singular values due to the turbulence in the separated region. Several reconstruction methodologies for linear state estimation based on classical compressed sensing and extended POD methodologies are presented as well as nonlinear refinement through the use of a shallow neural network (SNN). It is found that the linear reconstructions inspired by the extended POD are inferior to the compressed sensing approach provided that the sparse sensors avoid regions of the flow with small variance across the global POD basis. Regardless of the linear method used, the nonlinear SNN gives strikingly similar performance in its refinement of the reconstructions. The capability of sparse sensors to reconstruct separated turbulent flow measurements is further discussed and directions for future work suggested. Sparse reconstruction of full-field information using a limited subset of data is widely relevant to data-centric engineering applications; from reconstructing human faces with limited pixels to predicting laminar and turbulent flow fields from limited sensors. The focus of the present study is of the latter example with high relevance to active flow control in aerospace and related industry. There are multiple data-driven methodologies for obtaining flow field reconstructions from sparse measurements ranging from the linear unsupervised proper orthogonal decomposition to the use of nonlinear supervised NNs. The feasibility of such methods to flow fields that are highly turbulent as well as obtained via experiment remains an open area of research. The present study reveals the capability of these techniques to create a time-invariant library that can predict instantaneous states of the flow from sparse measurements alone (provided that these states are within the bounds of the applied training data). The proposed linear methods, as well as the NN architecture, provide well-characterized frameworks for future efforts in sparse sensing and state estimation applications: particularly for highly nonlinear underlying systems such as turbulent flow.

This paper presents a second and third-order wave active low pass filter (WALPF) using modern active block Voltage Differencing Differential Input Buffered Amplifier (VDDIBA) with a lower supply voltage of 1V. The wave-active approach is chosen for the filter designing to get a higher order, lower sensitivity, modular and stable filter structure. The design procedure of WALPF involves the implementation of wave-active equivalent for series inductor and shunt capacitor. And it needs to realize the subtractor block physically, and the lossy subtractor integrator block using VDDIBA gives a flavor of differencing voltage property. So, the physical implementation of the subtractor block and the lossy subtractor integrator block goes very smoothly using this block. It is considered a possible reason for reducing active blocks and passive components. Theoretical justification of the proposed WALPF is achieved by using the wave-equivalent concept of the wave-active approach. This method of WAF design consists of only one resistor and capacitor, making the filter structure less complex easy to use with a cut-off frequency of 10MHz. Finally, the workability test is examined with the PSPICE simulation that results in the WALPF frequency response using 180 nm TSMC CMOS technology parameter for VDDIBA.

As critical components of aircraft skins and rocket fuel storage tank shells, large thin-walled workpieces are susceptible to vibration and deformation during machining due to their weak local stiffness. To address these challenges, we propose a novel tunable electromagnetic semi-active dynamic vibration absorber (ESADVA), which integrates with a magnetic suction follower to form a followed ESADVA (follow-ESADVA) for mirror milling. This system combines a tunable magnet oscillator with a follower, enabling real-time vibration absorption and condition feedback throughout the milling process. Additionally, the device supports self-sensing and frequency adjustment by providing feedback to a linear actuator, which alters the distance between magnets. This resolves the traditional issue of being unable to directly monitor vibration at the machining point due to space constraints and tool interference. The frequency shift characteristics and vibration absorption performance are comprehensively investigated. Theoretical and experimental results demonstrate that the prototyped follow-ESADVA achieves frequency synchronization with the milling tool, resulting in a vibration suppression rate of approximately 47.57%. Moreover, the roughness of the machined surface decreases by 18.95%, significantly enhancing the surface quality. The results of this work pave the way for higher-quality machined surfaces and a more stable mirror milling process.

The high penetration rate of distributed generations (DGs) makes the distribution network’s fault characteristics complex and variable, which limits the application of traditional current differential protection (CDP) in active distribution networks. According to the amplitude and phase characteristics analysis of positive-sequence current fault components (PSCFCs) in the active distribution network, a novel CDP method based on the adaptive phase angle compensation coefficient is proposed. The method improves the traditional CDP by introducing an adaptive phase angle compensation coefficient, which adaptively compensates the phase of PSCFCs on the DG side according to the phase difference and amplitude ratio of PSCFCs on both sides of the protected feeder. To effectively cope with the negative impact of unmeasurable load branches on protection reliability, the polarity information of the action impedance is used to construct an auxiliary criterion. The effectiveness of the proposed protection scheme is verified in the PSCAD/EMTDC. Compared with the traditional CDP, this scheme can meet the protection needs of active distribution networks under various fault scenarios with high sensitivity and reliability. The proposed method can withstand high fault resistance and large time synchronization errors, and it can still trip correctly under 150 Ω fault resistance or 4.6 ms time synchronization errors.

In this paper, a grounded inductance simulator circuit employing single voltage differencing differential difference amplifier (VDDDA) and a grounded capacitor is proposed. The purpose of this paper is to present an inductance simulator using minimum number of active and passive components. Due to the use of grounded capacitor in the proposed inductance simulator, the circuit is suitable for analog integrated circuit implementations. The circuit does not require any conditions of component matching. Furthermore, the presented circuit has electronically tunability property through changing the biasing current of the VDDDA. Inductance value of the circuit is analyzed for different biasing current values and at various temperatures. Additionally, in order to analyze the performance of the inductance simulator circuit, it is used in a second-order multifunction filter and third-order high pass filter structures. Noise voltage, frequency response, time domain response and total harmonic distortion analyzes are simulated for the filters. The simulation results of the proposed inductance simulator and filter circuits are verified and demonstrated with LTSPICE by using 0.18 µm TSMC CMOS process parameters.

Estimating losses accurately for magnetic materials in power conversion circuits is a challenging task. Solving the partial differential equations in a complex geometry of inductive components such as filter-integrated transformers is an additional prominent challenge. While there are some commercially available finite element simulation tools that provide loss calculations in time-domain for multi-dimensional geometries of magnetic materials, the principle of analysis is not fully disclosed and less flexible for engineers to use. In this paper, we introduce a comprehensive method for systematically and flexibly applying time-domain dynamic loss equations to geometric finite element methods in multi-dimensions. The developed post-process framework for magnetic core loss calculations is coded in an open-source programming language, Python, and verified by comparison with analytical solutions for a filter integrated isolation transformer under a variety of operating conditions. Parallel processing is used to deal with the large datasets associated with element-by-element numerical calculations in the time domain. A high level of accuracy is achieved and verified.

To investigate whether exhaled breath analysis using an electronic nose can identify differences between inflammatory joint diseases and healthy controls. In a cross-sectional study, the exhaled breath of 21 rheumatoid arthritis (RA) and 18 psoriatic arthritis (PsA) patients with active disease was compared to 21 healthy controls using an electronic nose (Cyranose 320; Smiths Detection, Pasadena, CA, USA). Breathprints were analyzed with principal component analysis, discriminant analysis, and area under curve (AUC) of receiver operating characteristics (ROC) curves. Volatile organic compounds (VOCs) were identified by gas chromatography and mass spectrometry (GC-MS), and relationships between breathprints and markers of disease activity were explored. Breathprints of RA patients could be distinguished from controls with an accuracy of 71% (AUC 0.75, 95% CI 0.60-0.90, sensitivity 76%, specificity 67%). Breathprints from PsA patients were separated from controls with 69% accuracy (AUC 0.77, 95% CI 0.61-0.92, sensitivity 72%, specificity 71%). Distinction between exhaled breath of RA and PsA patients exhibited an accuracy of 69% (AUC 0.72, 95% CI 0.55-0.89, sensitivity 71%, specificity 72%). There was a positive correlation in RA patients of exhaled breathprints with disease activity score (DAS28) and number of painful joints. GC-MS identified seven key VOCs that significantly differed between the groups. Exhaled breath analysis by an electronic nose may play a role in differential diagnosis of inflammatory joint diseases. Data from this study warrant external validation.

The aim of this research is to acquire a mathematical model for the quarter vehicle model's passive and active suspension system and to build an active and passive suspension control for a quarter-vehicle model. The passive design of the suspension scheme is a compromise between vehicle handling capacity and passenger ride comfort. Passive suspension provides one of these two circumstances that conflict. Current car suspension systems use passive components only by using a coefficient of spring and damping with a fixed coefficient and two degrees of freedom. In the design and manufacture of cars, passenger comfort is a very significant parameter. The objective of the active suspension system is to enhance both the comfort of the ride and the handling of the highway by directly regulating the actuators of suspension power. In the active suspension system, the Proportional Integral Differential Controller (PID) method is applied. Various kinds of highway profiles and controllers such as P, PD, PI, and PID controllers evaluate the efficiency of the active suspension system comparing it with passive suspension scheme. This efficiency will be determined by using the MATLAB and SIMULINK to perform computer simulations.