Measurement System Research Articles

A Real-Time Signal Measurement System Using FPGA-Based Deep Learning Accelerators and Microwave Photonic

A Real-Time Signal Measurement System Using FPGA-Based Deep Learning Accelerators and Microwave Photonic

Investigation of the Measurement Systems’ Suitability for the Non-Destructive Measurement of Complex Polymer-Based Micro and Nanostructures

Investigation of the Measurement Systems’ Suitability for the Non-Destructive Measurement of Complex Polymer-Based Micro and Nanostructures

An automatic rebar spacing measuring method based on the YOLOv8-GB model

In engineering construction projects, rebar spacing measurement requires significant manual labor with low efficiency. This paper proposes a new intelligent rebar spacing measurement method based on the YOLOv8-GB model to save the workforce and improve efficiency. This method collects images of rebars to be measured using a binocular camera, utilizes the proposed YOLOv8-GB model to extract rebars from the scene, and achieves spacing measurement. The system is deployed on the NVIDIA Jetson TX2 NX for on-site portable measurement and can run in real-time at 24 frames per second. Experimental results show that the improved YOLOv8-GB network, compared with the YOLOv8n network, increased Recall, Precision, mAP@0.5, and mAP50-95 by 0.6 %, 5.5 %, 2.3 %, and 7.6 %, respectively. The measurement system built with YOLOv8-GB achieved an average absolute error of ± 1.7 mm, ±2.1 mm, and ± 2.7 mm for rebar spacing measurements on three different ground textures, with average relative errors of 0.85 %, 0.93 %, and 1.32 %, meeting engineering requirements. Compared to the measurement system built with YOLOv8n, the average absolute error decreased by 37.0 %, 8.0 %, and 25.0 % under the three different ground textures, while the average relative error decreased by 36.1 %, 8.8 %, and 23.7 %, respectively.

UHPC girder multi-modal deformation measurements: Photogrammetry, physical sensing, and FEA

Ultra-high performance concrete (UHPC) has become increasingly popular in flexural design of structural members that require high performance. Although numerous experimental studies on passively reinforced UHPC flexural members exist, studies on monolithic members with larger cross sections are limited, and no information exists on full-field deformation measurements of such specimens. An experimental program consisting of 8 large-scale UHPC doubly-reinforced specimens with continuous longitudinal rebars was conducted under 4-point monotonic loading. The experimental objectives were to investigate rebar slip from one side of the specimens (longitudinal rebar with hooks only on one side), track crack propagation, and capture the full-field displacement and strain measurements during the loading. The noncontact measurements from the multi-camera computer vision system using 3D digital image correlation (3D-DIC) and AprilTag-based photogrammetry were compared with the physical (contact) displacement measurement system. Strain fields were obtained using dual-camera 3D-DIC and finite element (FE) analysis. Results showed a close agreement of the point-wise displacements obtained from the physical and computer vision monitoring systems. The asymmetric structural design caused slip that delayed rebar fracture and reduced the peak load below that predicted by sectional analysis. The measured global force-deflection curve was predicted by the FE model when using a calibrated bond-slip model between rebar and UHPC. Comparison between the full-field measurements using 3D-DIC and FE numerical models showed that the evolution of principal strains and cracking were consistent. 3D-DIC proved to be a promising measurement method for monitoring strain/displacement and calibrating/confirming FE model that conventional methods without full-field measurements cannot provide.

Design and data analysis of a wearable basketball training posture measurement system based on multifunctional conjugated polymer composite materials

Conjugated materials in basketball training are specific polymers included in sportswear to record and analyze player motions, helping to improve skills and prevent injuries by offering an in-depth analysis of the biomechanics and movements of athletes during training sessions. These materials provide basketball players with lightweight, long-lasting, and versatile qualities, offering comfortable gear that precisely monitors movements, complementing their training requirements for enhanced performance and technique improvement. This article describes creating and examining a novel wearable basketball conditioning posture assessment system called DMAS4B (Dynamic Motion Analysis System for Basketball). The technology includes sophisticated computer vision algorithms (CVA-Kalman Fusion Algorithm), Inertial Measurement Units (IMUs), and versatile, conjugated polymer composite materials. These materials, strategically positioned within specially developed sportswear, enable real-time tracking and evaluation of basketball player locations during training sessions. DMAS4B includes gathering detailed body movement data and focusing on essential basketball skills like shooting technique, dribbling stance, and defensive alignments. The collected data is delivered wirelessly to the MotionPro+ Basketball Analytics Software, a specialized platform for thorough analysis and visualization. The ability of IMUs, multifunctional conjugated polymer composites, and computer vision algorithms to work together to record and analyze basketball player movements precisely is demonstrated in this study. The system’s implementation seeks to connect traditional training methods with advanced technology, providing athletes and coaches instant and thorough feedback on posture accuracy, balance, and mastery of techniques. The comprehensive examination of data collected from DMAS4B offers a novel method to improve basketball training programs, enhance player performance, and reduce the likelihood of injuries. In addition, the flexible character of this technology provides a foundation for possible use in various sports, transforming customised training methods worldwide.

Advancing the C[formula omitted] low-temperature oxidation chemistry through species measurements in a rapid compression machine, Part A: 1-Butene

Alkene chemistry plays a crucial role in the autoignition and oxidation of larger hydrocarbons. Unlike its other isomers, 1-butene is characterized by a two-stage ignition process. Various previous studies of 1-butene oxidation have used experimental techniques, including the measurement of ignition delay times in rapid compression machines (RCM) and in shock tubes, the determination of flame velocities, and the measurement of species concentrations in flames and in jet-stirred reactors (JSR). JSR studies provide an important insight into intermediate species formation at low temperatures but are constrained to low pressures and/or highly diluted conditions. To bridge the gap between JSR and engine-relevant conditions, this study presents species concentration measurements during the oxidation of 1-butene at 733 K and 30 bar under stoichiometric ’air-like’ conditions in an RCM, complemented by IDT measurements in the temperature range of 680–910 K. We designed an innovative 2-valve sampling setup to reduce quantitative uncertainties and the time required for species measurements. Our results indicate that existing 1-butene models fail to accurately predict the IDTs and the formation of the key oxidation intermediates. In response, potential optimizations for an improved kinetic model based on NUIGMech1.3 are discussed. Rate parameters for predominantly fuel consumption pathways, along with other reactions and thermochemical properties in the Waddington mechanism, have been altered within expected uncertainty limits to reflect the experimentally observed IDTs and species concentrations of this study and other validation data from the literature. However, the refined model does not predict the formation of 2-ethenyloxirane and ethene, indicating a gap in our understanding of the chemistry of these components. Overall, this study demonstrates the importance of measuring intermediates under the same conditions as IDTs to accurately address deficiencies in current kinetic mechanisms, and represents the first phase of a comprehensive investigation advancing the understanding of C4 oxidation chemistry.Novelty and significance statementThe novelty of this research lies in the design of an innovative sampling system for RCM species measurements, lowering the time for experimental execution and the uncertainties of the measurements. This enabled first-time species measurements during the oxidation of butene isomers in an RCM at high pressure and low level of dilution, contributing to the refinement of the 1-butene sub-mechanism within the NUIGMech1.3 framework. This research contributes to the understanding of the oxidation of alkenes, an important class of intermediates in gasoline and biofuel combustion. It emphasizes the need to measure intermediate species at the same conditions as ignition delay times, which are essential for understanding oxidation pathways under engine-relevant conditions. This research is part of a broader investigation of C4 oxidation chemistry, along with our companion work on n-butane. The resulting kinetic model is capable of reproducing most of the available n-butane and 1-butene validation targets.

Land surface temperature trends derived from Landsat imagery in the Swiss Alps

Abstract. The warming of high mountain regions caused by climate change is leading to glacier retreat, decreasing snow cover, and thawing permafrost, all of which have far-reaching effects on ecosystems and societies. Landsat Collection 2 provides multi-decadal land surface temperature (LST) data, principally suited for large-scale monitoring at high spatial resolution. In this study, we assess the potential to extract LST trends using Landsat 5, 7, and 8 time series. We conduct a comprehensive comparison of both LST and LST trends with data from 119 ground stations of the Intercantonal Measurement and Information System (IMIS) network, located at high elevations in the Swiss Alps. The direct comparison of Landsat and IMIS LST yields robust satellite data with a mean accuracy and precision of 0.26 and 4.68 K, respectively. For LST trends derived from a 22.6-year record length, as imposed by the IMIS data, we obtain a mean accuracy and precision of −0.02 and 0.13 K yr−1, respectively. However, we find that Landsat LST trends are biased due to unstable diurnal acquisition times, especially for Landsat 5 and 7. Consequently, LST trend maps derived from 38.5-year Landsat data exhibit systematic variations with topographic slope and aspect that we attribute to changes in direct shortwave radiation between different acquisition times. We discuss the origin of the magnitude and spatial variation of the LST trend bias in comparison with modeled changes in direct shortwave radiation and propose a simple approach to estimate the LST trend bias. After correcting for the LST trend bias, the remaining LST trend values average between 0.07 and 0.10 K yr−1. Furthermore, the comparison of Landsat- and IMIS-derived LST trends suggests the existence of a clear-sky bias, with an average value of 0.027 K yr−1. Despite these challenges, we conclude that Landsat LST data offer valuable high-resolution records of spatial and temporal LST variations in mountainous terrain. In particular, changes in the mountain cryosphere, such as glacier retreat, glacier debris cover evolution, and changes in snow cover, are preserved in the LST trends and potentially contribute to improved prediction of permafrost temperatures with large spatial coverage. Our study highlights the significance of understanding and addressing biases in LST trends for reliable monitoring in such challenging terrains.

Radiological Approach to Assessment of Lower-Limb Alignment-Coronal and Transverse Plane Analysis.

Lower-limb alignment deformities constitute a significant clinical concern, as they can lead to serious complications, including progressive degenerative diseases and disabilities. Rotational deformities may give rise to conditions such as joint arthrosis, patellar instability, and the degeneration of the patellofemoral cartilage. Therefore, a comprehensive evaluation of lower-limb alignment is essential for the effective patient management, preoperative planning, and successful correction of these deformities. The primary assessment method employs full-length standing radiographs in the anteroposterior (AP) projection, which facilitates accurate measurements of the anatomical and mechanical axes of the lower limb, including angles and deviations. The outcomes of this analysis are vital for the meticulous planning of osteotomy and total knee arthroplasty (TKA). In addition, computed tomography (CT) provides a specialized approach for the precise evaluation of femoral and tibial rotation. In this area, there are potential opportunities for the implementation of AI-based automated measurement systems.

Effect of temperature on permeability of mudstone subjected to triaxial stresses and its application

In order to prevent leakage of pyrolysed oil and gas and the release of contaminants from the top and bottom strata, it is essential to carry out a comprehensive study of the seepage behaviour of these strata under high temperature triaxial stress conditions. The findings of this study will contribute to the development of effective strategies for the containment and integrity monitoring of subsurface reservoirs and storage environments. Mudstone, serving as both the upper and lower strata, offers an effective barrier due to its inherently low permeability. In order to explore the change rule of mudstone sealing performance under high temperature triaxial stress, an air-heated low permeability rock mass air permeability measurement system is used to measure the ground stress buried 500 m deep and the temperature variation characteristics of mudstone permeability on the roof and floor of Jimsar oil shale in Xinjiang under 100 °C. It was found that the permeability of stressed mudstone decreased with the temperature rising up to 100 °C. The primary factor influencing the outcome was the thermal expansion of the mudstone. The magnitude of the drop value was contingent upon the triaxial stresses that could potentially be induced by the application of significant tensile forces, resulting in a relatively minor drop value. The average hydraulic radius of pore in the mudstone was also calculated, which also exhibited continuous reduction as heating up to 100 °C and the degree of reduction could reach 68%. The capacity, that prevent oil & gas and contaminant from moving cross strata as a barrier, would be strengthened when the mudstone strata from roof and floor experienced the temperature low than 100 °C. The barrier performance of mudstone as a pollutant migration barrier layer to gas pollutant migration during in-situ heat injection mining of oil shale was further evaluated.

Buddhist Currency in Ancient Period: A Comparative Study.

Currency is a very important element in the economic system of a society as a medium of exchange. A coin is a piece of metal that needs to have a specific purity and weight. It is also important simultaneously to consider it as a medium of exchange. In ancient India, ‘cowry shells’ were used as an easy means of exchange of goods. The weight of ‘guñjā’ seeds were used as a unit of measurement in the Indus Valley civilization. In the ancient Indian monetary system weight was measured with great precision. In Vedic literature, the word ‘niṣka’, ‘śatamāna’ etc. are used to denote metal fragments. The eighth chapter of the ‘Manusaṃhitā’ mentions the ‘trasareṇu’ as the first unit of measurement, which actually refers to the very small mote which is seen when the sun shines through a lattice. Apart from this, the words likṣā, sarṣapa, kr̥ṣṇala, māṣaka, suvarṇa, paṇa/kārṣāpaṇa, pala, dharaṇa, sāhasa etc. associated with various currencies and their measurement system can be noticed in ‘Manusaṃhitā’ and ‘Arthaśāstra’. However, after the discovery of coins that found in Taxila and Kabul, there is undoubted evidence of the circulation of metal coins in India in the 5th century BC. The ‘kārṣāpaṇa’ coin mentioned in the Buddhist scriptures of the Pre-Maurya era is quite similar to these. In various Buddhist texts such as Vinaya Piṭaka, Dhammapada, Jātaka, visuddhimaggo, etc., there are references to various coins and currency measurement terms such as Kahāpaṇa, Kākaṇikā, Dharaṇa, Pala, Pāda, Māsaka, Aḍḍha etc. Through the said discussion, based on the information and data found in various Buddhist texts including ‘Manusaṃhitā’ and ‘Arthaśāstra’ etc. to provide a detailed discussion about the currency of the Ancient Buddhist era and its measurement system.

Development of a Shoelace Tensile Testing System and Investigation into the Effects of Different Running Speeds on Shoelace Tensile Variation

AbstractThis study investigated the validity and sensitivity of a custom-made shoelace tensile testing system. The aim was to analyze the distribution pattern of shoelace tension in different positions and under different tightness levels during running. Mechanical tests were conducted using 16 weights, and various statistical analyses, including linear regression, Bland-Altman plots, coefficient of variation, and intraclass correlation coefficient, were performed to assess the system’s validity. Fifteen male amateur runners participated in the study, and three conditions (loose, comfortable, and tight) were measured during an upright stance. The system utilized VICON motion systems, a Kistler force plate, and a Photoelectric gate speed measurement system. Results showed a linear relationship between voltage and load at the three sensors (R2 ≥ 0.9997). Bland-Altman plots demonstrated 95% prediction intervals within ± 1.96SD from zero for all sensors. The average coefficient of variation for each sensor was less than 0.38%. Intraclass correlation coefficient values were larger than 0.999 (p<0.0001) for each sensor. The peak tension of the front shoelace was greater than that of the front and middle when the shoelace was loose and tight. The rear shoelace had the highest tension force. The study also found that shoelace tension varied throughout the gait cycle during running. Overall, this research provides a novel and validated method for measuring shoelace tensile stress, which has implications for developing automatic shoelace fastening systems.

Optimization of the method for determining the velocity of surface acoustic waves

The methodological aspects of measuring the velocity of Rayleigh surface waves are considered. The main attention is paid to the method for determining the change in surface wave velocity under the influence of certain factors on the object of study. The main sources of error in determining the change in surface acoustic wave velocity are discussed. The use of a transducer with rigidly connected elements for exciting and recording surface acoustic waves to determine the change in velocity is examined. A distinctive feature of such a transducer is the stable measurement base length, which eliminates the need for its determination during the measurement process. It is shown that the main sources of decreased surface acoustic wave measurement accuracy are the temperature instability of the measuring equipment and the transducer, as well as the instability of the acoustic contact layer between the transducer ele-ments and the object of study. The instability of the acoustic contact is caused by the uncertainty in the distribution of the coupling fluid between the transducer and the specimen during the bonding process, leading to changes in the acoustic signal propagation time. The source of temperature instability is random changes in the ambient temperature. Another source of such instability is the heating of equipment elements due to the release of heat when electrical and acoustic energy pass through them. This is particularly important for the transducer, where electrical energy is converted into acoustic energy, as a significant portion of it is transformed into heat. The magnitude of temperature instability arising from prolonged system operation, as well as the instability caused by the installation of the transducer on the object of study, is experimentally evaluated. The use of a reference sample to compensate for the temperature instability of the measurement system is considered. The possibility of using a measurement scheme with a reference sample to reduce temperature instability and the error caused by the instability of the acoustic contact between the transducer and the object of study is analyzed.

Experimental study of twin-fluid flow differences and Sauter mean diameter prediction according to Y-jet nozzle mixing-tube design

In this study, we experimentally investigate the effect of internal flow variation on the design characteristics of a Y-jet twin-fluid nozzle and its utilization for spray droplet size prediction. For this study, a laboratory-scale twin-fluid nozzle spray test system was constructed. Sauter mean diameter (SMD) measurements were made by a droplet measurement system using the laser diffraction principle, and spray images were obtained using a high-speed camera. The mass flow rate of the twin fluids under different spray conditions was expressed in terms of the gas-to-liquid mass flow rate ratio (GLR) and turn-down ratio. The GLR tended to decrease when the nozzle orifice diameter increased because the pressure of the supplied twin-fluid was the same. By contrast, increasing the nozzle mixing-tube length resulted in a negligible increase in GLR. This is because the nozzle design characteristics affect the internal pressure of the nozzle, which changes its spray characteristics. In general, the spray characteristics of Y-jet nozzles are most affected by GLR. However, in this study, a generalised GLR was devised to consider not only GLR but also the difference in the flow rate of the twin-fluid due to nozzle design factors. The generalised GLR has the advantage that it is constant under changes in twin-fluid pressure, unlike the GLR expressed by considering only the mass flow rate of the twin-fluid. Therefore, to estimate the SMD more accurately under different spray pressures for a constant GLR, we investigated the SMD estimation using the internal pressure ratio and generalised GLR.

Collision causal discovery and real-time prediction of freeway tunnels: A novel dual-task approach

Although tunnels are critical traffic nodes in freeway networks, academic research addressing their real-time traffic safety is noticeably lacking. This study proposes a novel dual-task approach to analyze causal precursors and predict real-time collision risks in freeway tunnels. Unlike traditional models, which often trade off between predictive accuracy and causal depth, the proposed approach achieves both high causal interpretability and predictive performance. The approach utilizes a structural agnostic model (SAM) to discover causal precursors of freeway tunnel collisions using observational data. The collision causal graph data is then constructed based on the causal relationships identified by SAM. Additionally, the Causal Directed Graph Convolutional Networks (CDGCN) model is developed to capture causal relationships in the graph for real-time collision prediction. Utilizing freeway tunnel collision analysis data collected from the Caltrans Performance Measurement System, the approach performs dual tasks: identifying causal precursors of collisions and predicting future collisions in real time. The SAM results reveal five critical causal precursors influencing the likelihood of collisions. Comparative analyses with existing interpretable machine learning models show similarities between the causal precursors of tunnel collision risk revealed by SAM and the important correlation precursors identified by the comparative models. However, correlation is not the same as causation. When tested against current state-of-the-art real-time collision predictive models, the proposed CDGCN model demonstrates superior accuracy, especially on datasets containing causally relevant precursors, highlighting the potential of this approach for feature selection and risk prediction. This advancement not only provides a practical framework for mitigating collision risks in freeway tunnels but also makes a significant contribution to traffic safety research.

Which Strategic Control Suits Wine Family Companies to Improve Control? A Proposal Through the Balanced Scorecard in a Tuscany Wine Company of Michele Satta

ABSTRACTIn the last few years, growth and increased market and organizational complexity, including the effects of the pandemic era, require family firm members to develop managerial strategies to improve their businesses. This study pays attention to the study of strategic performance measurement systems, as important tools that, if well applied, positively influence business management, being directly linked to critical success factors. First, particular attention is on The Tuscany Region, in the area of Bolgheri. Second, to carry out the empirical study of this research, the first implementation of the Balanced Scorecard (BSC) will be realized with the collaboration of one company in the same Region. This article sheds useful insights for practitioners on the effective implementation of accounting and strategic innovations and it encourages wine companies to seriously weigh investing in developing strategic performance management systems.

Інтегральний показник для оцінювання ефективності спеціалізованих моніторингових систем

The purpose of the article is to develop a methodology for calculating the integral index based on existing methods for calculating soil pollution, with the proposal of an algorithm for calculating the system of integral indices. Based on the integral indicator, the effectiveness of the developed complex was evaluated in comparison with other known solutions in the field of soil pollution monitoring, which showed the advantage of the developed complex in comparison with analogues at the level of 42%. In addition, performance measurements serve as the basis for setting performance targets and service level agreements. By establishing quantifiable performance indicators and benchmarks, organizations can set clear expectations for system performance and reliability. These performance targets not only provide a means of evaluating the success of software projects, but also serve as the basis for contractual agreements between service providers and customers. To measure these indicators, it is proposed to use information and measurement systems that are easy to implement from a technical and technological point of view. Therefore, the article proposes mathematical and software for monitoring soil and groundwater contamination by harmful emissions and subsequent modeling of processes using an integral indicator.

Tailoring structural, morphological, and magnetic properties of Sr0.54Ca0.46Fe6.5-xNixAl5.5O19 hexaferrites via Ni substitution

Sr0.54Ca0,46Fe6.5-xNixAl5.5O19 (0 ≤ x ≤ 0.3) hexaferrite powders were prepared by the sol-gel auto combustion method and characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDX). Magnetic measurements were performed with physical properties measurement system (PPMS). The lattice parameters, volume, and lattice strain were calculated. XRD analyses revealed a reduction in crystallite size with increasing Ni content. Interestingly, the magnetic analysis indicated that nickel, with its low magnetic moment, significantly enhanced the magnetization of Sr0.54Ca0.46Fe6.5-xNixAl5.5O19 (0.0 ≤ x ≤ 0.3) and reduced the coercive field. Furthermore, the Law of Approach to Saturation (LAS) theory was employed to extract the first anisotropy constant, the anisotropy field, and several essential magnetic parameters, providing valuable insights into the magnetic behavior of samples.

Traffic Flow Prediction Using Novel Spatial-Temporal Multi-Head Attention Graph Convolution Networks

For urban development, accurate traffic flow prediction is crucial. Traffic flow prediction data can be used for optimizing public transportation systems, reducing congestion, planning road networks, and improving overall city infrastructure management. Despite numerous spatiotemporal methods used to forecast traffic flow, information aggregation at each site neither produce optimal results, because of the use non-Euclidean distance data. For more accurate results of traffic flow prediction, we propose a spatial-temporal multi-head attention graph convolution network (STMAGCN). It extracts temporal features using temporal convolutional layers and enriches nodes with spatial attention and multi-head attention mechanisms. By combining them, we can extract space characteristics more effectively. We also introduce a novel graph structure construction method that employs graph-based transformations to convert non-connected data points into a comprehensive graph structure, facilitating the effective application of our STMAGCN. This approach improves the predictive efficiency and accuracy of our model by ensuring seamless integration of disparate data sources. Experimental results indicate that the preferential extraction of spatiotemporal data significantly enhances traffic flow prediction accuracy. Compared with the latest models, our performance on the California Department of Transportation Performance Measurement System (PeMS) PeMS04 and PeMS08 datasets shows a slight improvement, with an average increase of 16.8%. Additionally, the average improvement in time is approximately 445.95%.

An efficient automated measurement method for aero-engine fan blade geometric parameters

The length of aero-engine fan blades usually exceeds 1 m, making contact-based coordinate measuring machines (CMM) costly and time-consuming. To enhance measurement efficiency and accuracy, we developed a large-field flexible measurement system. We propose the system calibration method using a standard sphere as the reference and taking the turntable axis into account. A model-driven path planning and multi-view data fusion (MVDF) strategy was introduced to enhance efficiency and reduce misalignment due to the robotic arm’s lower positioning accuracy. To improve cross-sectional data sorting and thinning, we proposed an adaptive threshold synchronous sorting and noise suppression method. Additionally, we developed algorithms for chord length and maximum thickness extraction to streamline the process. Experiments show improved accuracy for blade thickness (0.092 mm) and chord length (0.096 mm).

Exploring the metabolic daylength measurement system: implications for photoperiodic growth.

Photoperiod is an environmental signal that varies predictably across the year. Therefore, the duration of sunlight available for photosynthesis and in turn the ability of plants to accumulate carbon resources also fluctuates across the year. To adapt to these variations in photoperiod, the metabolic daylength measurement (MDLM) system measures the photosynthetic period rather than the absolute photoperiod, translating it into seasonal gene expression changes linked to photoperiodic growth. In this Tansley Insight, we briefly summarize the current understanding of the MDLM system and highlight gaps in our knowledge. Given the system's critical role in seasonal growth, understanding the MDLM system is essential for enhancing plant adaptation to different photoperiods and optimizing agricultural production.