System Parameters Research Articles

Protostellar Outflows at the EarliesT Stages (POETS) VI. Evidence of disk-wind in G11.92-0.61 MM1

Magnetohydrodynamic disk-winds are thought to play a key role in the formation of massive stars by providing the fine-tuning between accretion and ejection, where excess angular momentum is redirected away from the disk, allowing further mass growth of a young protostar. However, only a limited number of disk-wind sources have been detected to date. To better constrain the exact mechanism of this phenomenon, expanding the sample is critical. We performed a detailed analysis of the disk-wind candidate G11.92-0.61 MM1 by estimating the physical parameters of the massive protostellar system and constraining the wind-launching mechanism. Atacama Large Millimeter/submillimeter Array (ALMA) Band 6 observations of G11.92-0.61 MM1 were conducted in September 2021 with ALMA's longest baselines, which provided a synthesised beam of ∼30 mas. We obtained high-resolution images of the CH_3CN (varv_8=1 and varv=0), CH_3OH, SO_2, and SO molecular lines, as well as the 1.3 mm continuum. Our high-resolution molecular data allowed us to refine the parameters of the disk-outflow system in MM1. The rotating disk is resolved into two regions with distinct kinematics: the inner region ($<$300 au) is traced by high-velocity emission of high-excitation CH_3CN lines and shows a Keplerian rotation; the outer region ($>$300 au), traced by mid-velocity CH_3CN emission, rotates in a sub-Keplerian regime. The central source is estimated to be ∼20 M_⊙, which is about half the mass estimated in previous lower-resolution studies. A strong collimated outflow is traced by SO and SO_2 emission up to ∼3400 au around MM1a. The SO and SO_2 emissions show a rotation-dominated velocity pattern, a constant specific angular momentum, and a Keplerian profile that suggests a magneto-centrifugal disk-wind origin with launching radii of ∼50-100 au. G11.92-0.61 MM1 appears to be one of the clearest cases of molecular line-traced disk-winds detected around massive protostars.

Significance of Tool Coating Properties and Compacted Graphite Iron Microstructure for Tool Selection in Extreme Machining

This study aims to determine the extent to which coating composition and workpiece properties impact machinability and tool selection when turning Compacted Graphite Iron (CGI) under extreme roughing conditions. Two CGI workpieces, differing in pearlite content and graphite nodularity, were machined at a cutting speed of 180 m/min, feed rate of 0.18 mm/rev, and depth of cut of 3 mm. To assess the impact of tool properties across a wide range of commercially available tools, four diverse multilayered cemented carbide tools were evaluated: Tool A and Tool B with a thin AlTiSiN PVD coating, Tool C with a thick Al2O3-TiCN CVD coating, and Tool D with a thin Al2O3-TiC PVD coating. The machinability of CGI and wear mechanisms were analyzed using pre-cutting characterization, in-process optical microscopy, and post-test SEM analysis. The results revealed that CGI microstructural variations only affected tool life for Tool A, with a 110% increase in tool life between machining CGI Grade B and Grade A, but that the effects were negligible for all other tools. Tool C had a 250% and 70% longer tool life compared to the next best performance (Tool A) for CGI Grade A and CGI Grade B, respectively. With its thick CVD-coating, Tool C consistently outperformed the others due to its superior protection of the flank face and cutting edge under high-stress conditions. The cutting-induced stresses played a more significant role in the tool wear process than minor differences in workpiece microstructure or tool properties, and a thick CVD coating was most effective in addressing the tool wear effects for the extreme roughing conditions. However, differences in tool life for Tool A showed that tool behavior cannot be predicted based on a single system parameter, even for extreme conditions. Instead, tool properties, workpiece properties, cutting conditions, and their interactions should be considered collectively to evaluate the extent that an individual parameter impacts machinability. This research demonstrates that a comprehensive approach such as this can allow for more effective tool selection and thus lead to significant cost savings and more efficient manufacturing operations.

Maximum-Power Stirling-like Heat Engine with a Harmonically Confined Brownian Particle

Heat engines transform thermal energy into useful work, operating in a cyclic manner. For centuries, they have played a key role in industrial and technological development. Historically, only gases and liquids have been used as working substances, but the technical advances achieved in recent decades allow for expanding the experimental possibilities and designing engines operating with a single particle. In this case, the system of interest cannot be addressed at a macroscopic level and their study is framed in the field of stochastic thermodynamics. In the present work, we study mesoscopic heat engines built with a Brownian particle submitted to harmonic confinement and immersed in a fluid acting as a thermal bath. We design a Stirling-like heat engine, composed of two isothermal and two isochoric branches, by controlling both the stiffness of the harmonic trap and the temperature of the bath. Specifically, we focus on the irreversible, non-quasi-static case—whose finite duration enables the engine to deliver a non-zero output power. This is a crucial aspect, which enables the optimisation of the thermodynamic cycle by maximising the delivered power—thereby addressing a key goal at the practical level. The optimal driving protocols are obtained by using both variational calculus and optimal control theory tools. Furthermore, we numerically explore the dependence of the maximum output power and the corresponding efficiency on the system parameters.

MOA-2022-BLG-033Lb, KMT-2023-BLG-0119Lb, and KMT-2023-BLG-1896Lb: Three low mass-ratio microlensing planets detected through dip signals

We examined the anomalies in the light curves of the lensing events MOA-2022-BLG-033, KMT-2023-BLG-0119, and KMT-2023-BLG-1896. These anomalies share similar traits: they occur near the peak of moderately to highly magnified events and display a distinct short-term dip feature. We conducted detailed modeling of the light curves to uncover the nature of the anomalies. This modeling revealed that all signals originated from planetary companions to the primary lens. The planet-to-host mass ratios are very low: q∼ 7.5 for MOA-2022-BLG-033, $q∼ 3.6 $ for KMT-2023-BLG-0119, and q∼ 6.9 for KMT-2023-BLG-1896. The anomalies occurred as the source passed through the negative deviation region behind the central caustic along the planet-host axis. The solutions are subject to a common inner-outer degeneracy, which results in varying estimations of the projected planet-host separation. For KMT-2023-BLG-1896, although the planetary scenario provides the best explanation for the anomaly, the binary companion scenario is possible. We estimated the physical parameters of the planetary systems through Bayesian analyses based on the lensing observables. While the event timescale was measured for all events, the angular Einstein radius was not measured for any. Additionally, the microlens parallax was measured for MOA-2022-BLG-033. The analysis identifies MOA-2022-BLG-033L as a planetary system with an ice giant with a mass of approximately 12 times that of Earth orbiting an early M dwarf star. The companion of KMT-2023-BLG-1896L is also an ice giant, with a mass of around 16 Earth masses, orbiting a mid-K-type main-sequence star. The companion of KMT-2023-BLG-0119L, which has a mass around that of Saturn, orbits a mid-K-type dwarf star. The lens for MOA-2022-BLG-033 is highly likely to be located in the disk, whereas for the other events the probabilities of the lens being in the disk or the bulge are roughly equal.

Universality in diffusion-controlled nucleation and growth.

Nucleation and growth are studied in a system that undergoes diffusion-controlled condensation under gradual changes in parameters, such as cooling. It is demonstrated that when the Gibbs-Thompson effect becomes negligible, the system falls into a universal regime. i.e., the final droplet size distribution remains invariant under certain rescaling of system parameters. An approximate yet very accurate analytic form is obtained for the final droplet size distribution in this regime.

Electronic CPA‐Laser Having Enhanced Sensitivity and Tunability

AbstractExceptional point degeneracies, which are spectral singularities of non‐Hermitian systems, have been widely utilized for building optical, mechanical, or electrical sensing systems with much larger responses than those utilizing Hermitian degeneracies. However, such systems suffer from enhanced noise, which negates the enhanced response and thus does not provide any improvement in signal‐to‐noise ratio. Recently, the coherent perfect absorber (CPA)‐laser, which also utilizes non‐Hermitian singularity, has been used in sensing systems resulting in better noise robustness and enhanced responsivity. Nonetheless, CPA‐laser (CPAL) implementation requires all system parameters to be immutable, which hinders progress toward their practical use for sensing purposes. Here, a tunable electronic CPA‐laser is reported that overcomes these obstacles providing ultrahigh sensitivity as validated in the experiments for monitoring arterial pressure and respiration. This CPAL sensing scheme utilizes inductive coupling between gain and loss sub‐components and thereby the whole system can be decomposed into an active reader and a passive sensor, which enables better tunability and performance compared to previously reported CPAL systems. Moreover, the proposed CPAL system exhibits better performance compared to exceptional point‐based systems having a similar circuit structure. This research paves the way for exploring electronic CPAL for sensing applications and may have a profound impact on the next‐generation, ultrasensitive electromagnetic sensing system.

The Microscopic World: Deign and Construction a Low-cost, Portable Reflective Digital Holographic Microscope

In daily life, scratches are often left on reflective surfaces, including rearview mirrors, makeup mirrors, and optical lenses, posting significant problems on image quality. Traditional 3D measurement methods usually use expensive and massive instruments, such as confocal microscopes or electron microscopes, which are not practical for high school research projects. Digital microscopy has the advantages of being non-contact, full-field, real-time, and high-precision, offering a solution. Therefore, this paper explores the use of digital holographic microscopy to measure the 3D surface of reflective surfaces. The study is based on a Michelson interferometer, reducing the systems size by using folded optical path and eliminating unnecessary converging lenses. Through simulation experiments, this research explores how various optical system parameters affect imaging quality and optimizes the clarity of the 3D reconstruction. Based on the conclusions from the simulations, hardware set-up of the system was selected, including a 635nm laser, collimation lenses, a beam splitter, mirrors, and a CMOS camera, keeping the total cost under 3000 yuan. In the experimental section, the system was built, and through adjustments in the reference beam angle and the distance between the object and the camera, clear interference fringes were successfully obtained. To further enhance the research, MATLAB was used to write an angular spectrum diffraction reconstruction algorithm. The experiments conducted on lenses and wafers produced their 3D profiles. This research demonstrates the potential of digital microscopy in both solving real-world problems and helping high school students explore the field of physics, promoting a deeper understanding of concepts like optical interference and diffraction

Discrete adaptive sliding mode control for uncertain fractional-order Hammerstein system

This study explores controlling discrete fractional-order Hammerstein systems through two different approaches. The first method involves a detailed exploration of discrete sliding mode control (SMC), while the second method employs adaptive sliding mode techniques to address challenges posed by unknown time-varying system parameters. The aim is to enhance control strategies for these systems by ensuring stability and robustness amid evolving parameters. Stability analysis using Lyapunov Theory is carried out to establish the stability of the proposed control schemes. Comprehensive reachability analysis is then performed to show that the system reaches a quasi-sliding mode in finite time. The effectiveness of the proposed methods is thoroughly evaluated using simulation cases, covering three distinct scenarios. Finally, a discussion section analyzes the simulation outcomes and assesses the efficiency methodologies in handling complex system dynamics. Through comparative analysis and discussion, this study contributes to advancing control strategies tailored for systems characterized by fractional-order dynamics and varying parameters.

Controllable antibunching of two-magnon bundle in a hybrid ferromagnet-superconductor system

We propose an alternative scheme for implementing the antibunching effects of two-magnon bundle in a hybrid ferromagnet-superconductor system, where a magnon mode from the yttrium iron garnet (YIG) sphere interacts with a three-level superconducting qubit via photon virtual excitation in the microwave cavity. With the help of the qubit driving from the ground state to the excited state, the cascaded emission of magnon occurs and then the two-magnon bundle is formed. By analyzing the ordinary and generalized second-order correlation functions, it is found that the antibunched two-magnon bundle could be achieved via properly choosing the system parameters, which is originated from the anharmonicity of dressed energy levels induced by magnon–qubit couplings. The distinct feature is that high-proportion n-magnon emission could be obtained via relaxing the restriction on the strong qubit driving and magnon–qubit coupling, which may provide a feasible method to realize the high-quality multimagnon source for quantum metrology and quantum information processing.

Bifurcation and Chaos Control of Mixed Rayleigh‐LiéNard Oscillator With Two Periodic Excitations and Mixed Delays

ABSTRACTThis paper investigates the bifurcation, chaos, and active control of a mixed Rayleigh‐Liénard oscillator with mixed time delays. First, the effects of system parameters on the supercritical pitchfork bifurcations are discussed in detail by applying the fast‐slow separation method. Second, it is rigorously proved by the Melnikov method that chaotic vibration exists when the parameters of the uncontrolled system are selected above the threshold of chaos occurrence. By fine‐tuning the system parameters, a criterion for designing the control parameters to make the Melnikov function non‐zero is derived. In addition, the routes to chaos in controlled system are explored by bifurcation diagrams, largest Lyapunov exponents, phase portraits, Poincaré maps, basins of attraction, frequency spectra, and displacement time series. The results indicate that by properly adjusting the displacement feedback coefficient and the amplitude of parameter excitation, the chaotic motion caused by increasing of the amplitude of external excitation and strength of distributed time delay can be effectively suppressed. This research result can provide theoretical support for exploring the potential chaotic motion of other types of oscillators.

Identification of Parameters for Solar Photovoltaic Systems Using a Human Optimization Algorithm

By increasing the global demand for electricity, there is a heightened need for power generation. The rising costs of natural gas and regulatory pressures to limit greenhouse gas emissions have escalated the expenses associated with electricity production from fossil fuels. Consequently, there is a growing inclination to utilize alternative energy sources for electricity generation, particularly solar power through photovoltaic systems. Evolutionary algorithms are among the most favored methods for identifying and optimally estimating the parameters of photovoltaic systems, and this article examines their functionality. A critical issue in these systems is the appropriate selection of photovoltaic system parameters. This paper presents a new method for optimal parameters identification of the photovoltaic (PV) systems using a newly modified version of a metaheuristic algorithm. The propose algorithm is based on adapting the performance of the Human Evolutionary Optimizer and is called AHEO algorithm. Simulation results indicate that the estimation of the photovoltaic cell's circuit model parameters has been effectively accomplished, with the mean square error (MSE) associated with the AHEO demonstrating a high level of accuracy and robustness in parameters identification of the PV system.

Aquatic Temperature and Its Ecological Systems: A Review of Knowledge and Approaches for Studying Aqua-biota Responses

Available studies directing to aquatic temperature in Niger Delta aquatic ecological systems was carefully studied and developed as a review that takes on the tempo-spatial variation in that systems, the essence of being knowledgeable in facts relating to aquatic temperature of ecological systems, the vital points in the development of aquatic temperature modelling through its measurement, anthropogenic agenda that modify the aquatic temperature, the impact of temperature changes on the physico-chemical parameters of aquatic system; and on aqua-biota. Various ways of assessing the impacts of temperature variations in aqua-biota are spelled out and aquatic temperature criteria for the protection of aqua-biota are detailed. This review paper beams on the complexity of aquatic temperature in the ecological system; the need of being knowledgeable in tempo-spatial variability, the various responses of aqua-biota to temperature thermal stress; the anthropogenic agenda that modified the aquatic temperature and the current threat to aquatic ecology systems the climate change.

FS-DDPG: Optimal Control of a Fan Coil Unit System Based on Safe Reinforcement Learning

To optimize the control of fan coil unit (FCU) systems under model-free conditions, researchers have integrated reinforcement learning (RL) into the control processes of system pumps and fans. However, traditional RL methods can lead to significant fluctuations in the flow of pumps and fans, posing a safety risk. To address this issue, we propose a novel FCU control method, Fluctuation Suppression–Deep Deterministic Policy Gradient (FS-DDPG). The key innovation lies in applying a constrained Markov decision process to model the FCU control problem, where a penalty term for process constraints is incorporated into the reward function, and constraint tightening is introduced to limit the action space. In addition, to validate the performance of the proposed method, we established a variable operating conditions FCU simulation platform based on the parameters of the actual FCU system and ten years of historical weather data. The platform’s correctness and effectiveness were verified from three aspects: heat transfer, the air side and the water side, under different dry and wet operating conditions. The experimental results show that compared with DDPG, FS-DDPG avoids 98.20% of the pump flow and 95.82% of the fan flow fluctuations, ensuring the safety of the equipment. Compared with DDPG and RBC, FS-DDPG achieves 11.9% and 51.76% energy saving rates, respectively, and also shows better performance in terms of operational performance and satisfaction. In the future, we will further improve the scalability and apply the method to more complex FCU systems in variable environments.

A new 2D hyperchaotic model-based encryption strategy for multiple images via pixel fusion

Abstract In view of the intrinsic characteristics of chaotic system, it can be widely applied in image encryption. Considering the common issues of insufficient chaotic performance and discontinuous range of control parameters in current chaotic systems, a hybrid chaotic model with the characteristics of simple and easy to design is devised to address these challenges. Through phase portraits, bifurcation diagrams, and the analysis of Lyapunov exponent spectrum, it is demonstrated that the proposed system can exhibit robust traversal performance. To meet the demands of digital image encryption, an effective encryption strategy for multi-image based on this model is proposed, which can accommodate the varying image sizes and types simultaneously. In the given strategy, the pixels are merged from multiple images at first, and then the keys can be derived with SHA-512. By the application of discrete wavelet transform, the information can be embedded from the plaintext images, which can ensure the robust resistance to data loss while facilitating the shared transmission of plaintext information. Finally, by leveraging the developed chaotic system, a three-dimensional cross-plane scrambling and diffusion algorithm is introduced to enhance the effectiveness of encryption scheme.

A Seismic Landslide Hazard Assessment in Small Areas Based on Multilevel Physical and Mechanical Parameters: A Case Study of the Upper Yangzi River

Many landslides triggered by earthquakes have caused a countless loss of life and property, therefore, it is very important to predict landslide hazards accurately. In this work, regional seismic landslide data were obtained via a field survey, remote sensing interpretation, and data collection, and a multilevel physical and mechanical parameter system for seismic landslide hazard assessment was established; this system included a landslide inventory, loose accumulation layers, and geological units, enabling higher accuracy in the data. The Newmark displacement model with a modified correlation coefficient was used to assess the regional seismic landslide hazard in four scenarios (a = 0.1, 0.2, 0.3, 0.4) to study the influence of the landslide hazard at different peak ground accelerations. Moreover, the information value model was used to modify the calculated results to improve their accuracy in the assessment. By assessing the potential seismic landslide hazard in Shimian County in the upper reaches of the Yangtze River, the regional landslide distribution and pattern at different peak ground accelerations were obtained. The results show that with decreasing parameter accuracy in the system, the importance of the landslide inventory increases. When the peak ground acceleration is a = 0.3, which can be defined as a high hazard grade, in which the landslide area demonstrates a large-scale sharp increase, a devastating hazard threshold is reached. As the peak ground acceleration increases, the factor controlling landslides transforms from the landslide inventory to the slope, which reflects the reasonableness of the parameters in the system. The input parameters were regarded as important factors for efficiently increasing the accuracy of the results of the Newmark displacement model in the discussion.

Type-2 Backstepping T-S Fuzzy Bionic Control Based on Niche Symmetry Function

Niche can reflect the changes in the quality of the ecological environment and the balance of ecological state. The more advanced the ecosystem, the more complex and higher-order nonlinearities and uncertainties that are presented. For such an uncertain parameter system with complex nonlinearity, backstepping fuzzy control is a good control method. When the backstepping control method is introduced into the Type-2 fuzzy T-S control principle, the equality index symmetry function composed of ecological factors is used as the backstepping control consequence, and the Lyapunov function is constructed to analyze the stability and find out the adaptive law of the ecological factors in the equality index symmetry function of the control consequence. This reflects that the individual organisms always develop in their own favorable direction, highlighting the bionic intelligent control of the method. Through simulation analysis, the Type-2 Backstepping control method is effective in stability and parameter tracking, which reflects the self-development ability and self-coordination ability of individual organisms, highlighting the physical background and symmetry of the bionic intelligent control of this method.

Soret‐Induced Convection in a Layered Porous Medium Simulating an Anticlinal Geological Fold Under the Action of a Geothermal Temperature Gradient

ABSTRACTThe paper is devoted to the investigation of three‐dimensional Soret‐induced convection in a three‐layer porous system imitating an anticlinal geological fold, under the influence of a geothermal temperature gradient. The layer porosities are the same and the permeabilities are different. The mixture of tetralin and dodecane is considered as a fluid saturating the porous medium. First, we study the linear stability of the motionless state of a binary mixture in an inclined porous layer under the vertical temperature gradient. It is found that at any layer inclination angle, the most dangerous disturbances are longitudinal rolls with finite wave numbers in perpendicular direction. With the system parameters under consideration, the presence of an impurity can change the convection threshold in both directions depending on the layer inclination angle. The threshold change can reach 26%. Nonlinear calculations are performed for fixed permeabilities of the external layers, lower than the threshold value according to the linear theory. Calculations have shown that after a long period of time from the beginning of the process (about 500 years or more for lower permeabilities), a flow arises. The development of a steady flow occurs over a long period of up to 6000 years. It is found that at small permeabilities of all layers, arising flow has a longwave character. With the increase of permeability of the middle layer (higher than ), the flow in the plane of a geological fold limbs takes the form of longitudinal rolls and in the perpendicular direction the flow structure becomes multicellular, this flow structure well corresponds to the linear stability results. The flow is localized in the middle layer and significantly influences the concentration field.

Fluorescent aptasensor based on target-induced hairpin conformation switch coupled with nicking enzyme-assisted signal amplification for detection of beta-amyloid oligomers in cerebrospinal fluid.

Afluorescent aptasensor was developedbased on target-induced hairpin conformation switch coupled with nicking enzyme-assisted signal amplification (NESA) to detect the oligomeric form of ß-amyolidpeptide (AβO) in cerebrospinal fluid. The hairpin DNA probe (HP) was specifically designed to recognize AβO. When AβO is present in the sensing system, it induces an HP conformational switch and triggers the NESA reaction. After evaluating the parameters of the aptasensor system, we selected Hairpin10, which has a 10-nucleotide extended sequence, as the hairpin sequence that interacts with AβO. The quantitative linear range of the proposed aptasensor is from11.3 to 113 ng mL-1 in artificial cerebrospinal fluid (aCSF), and the detection limit was 7.29 ng mL-1. The present work realized the assay of AβO in aCSF with satisfactory quantitative results.

Estimation of Solar Irradiance using the measured parameters of the photovoltaic system by Artificial Neural Network

This article aims to estimate irradiance using measured parameters from a real photovoltaic system. For this study, output current and voltage values were used from a set of solar panels with a capacity of 10 kW and a 10 kVA power inverter, which provide the necessary data for irradiance estimation. The data was collected at a sampling frequency of 15 seconds. To achieve this goal, an Artificial Neural Network (ANN) was applied to the reference data, which includes time series of solar irradiance, current, and voltage produced by the photovoltaic panels on different days of the year under varying weather conditions. Once the ANN is trained, its performance will be validated by comparing the estimation generated by the network with data from a reference cell on the days selected for the study. Additionally, the model will be evaluated using data from other days, not used in the training, to verify its ability to generalize under different meteorological conditions.

Advancing haptic realism: modelling grasp contact vibrations for enhanced virtual environment interaction

Abstract In haptic technology, achieving realistic tactile feedback is crucial for enhancing the user experience in virtual environments. Previous studies lack effective methods for transmitting high-frequency vibrations crucial for realistic tactile feedback in haptic interfaces, highlighting the need for our research to address this gap. This paper explores the application of a tactile gripping interface to transmit the high-frequency vibrations produced when contacting a hard object's surface. These short vibrations improve the tactile sensation of hard virtual surfaces when overlaid on traditional position-based force feedback within a haptic environment. The enhanced realism of virtual objects is achieved by effectively estimating the vibration composition from user-induced parameters. This work presents a prototype grasping interface and empirically demonstrates this device's utility. We examine empirical grasp contact data, recorded and interpreted, to recognise the relationship between dynamic user-controlled parameters and the resulting vibration transients. This relationship effectively incorporates these changing dynamics to model the grasp impact and estimate the essential system parameters to understand the influence of the user's grasp force. Through our multi-point grasping interface design, this work demonstrates a mathematical relationship between the user's grasp force and the high-frequency vibrations from contact with hard surfaces. The study found that the proposed haptic interface had an RMSE of 0.05, demonstrating the system's high level of accuracy. This low RMSE value indicates that the predicted vibrations closely matched the actual measured vibrations, proving the effectiveness of our methods through objective validation.