Displacement Changes Research Articles

Neuromuscular Performance and the Intensity of External Training Load During the Preseason in National Collegiate Athletic Association Division I Men's Collegiate Basketball Players.

Curtis, M, Kupperman, N, Westbrook, J, Weltman, AL, Hart, J, and Hertel, J. Neuromuscular performance and the intensity of external training load during the preseason in National Collegiate Athletic Association Division I men's collegiate basketball players. J Strength Cond Res XX(X): 000-000, 2024-The aim of the study was to determine whether acute changes in neuromuscular performance can be detected through countermovement jumps (CMJs) conducted pre- and postpractice sessions in conditions of high or low intensity measured by microsensors technology. Using an observational repeated measures design, data were collected from 10 male collegiate basketball players. Countermovement jump data were collected before and after practice exposures over 4 weeks of preseason. Select CMJ kinetics were compared in conditions of high and low training load intensity to detect neuromuscular performance changes in displacement of the center of mass and kinetics. Kinetic measures were categorized as output, underpinning, and strategy-related variables. We investigated "output" defined as displacement (jump height [JH]), "underpinning" defined as force-related (mean eccentric force, mean concentric force, force at zero velocity), and "strategy" defined as time-related (countermovement depth [CMD], eccentric duration (EccDur), concentric duration [ConcDur]) variables. There were significant condition × time interactions in CMJ variables namely eccentric mean force (EccForce), force at zero velocity (Force@0), CMDepth, EccDur, and ConcDur. In conditions of high intensity, players had significant, but small decreases in EccForce and Force@0, with small increases in CMD, EccDur, and ConDur, respectively. However, there were no significant decreases in JH. High-intensity practice exposures did not impact neuromuscular performance specific to "output," suggesting that collegiate basketball athletes can maintain JH despite alterations in "underpinning" and "strategy-related" variables. This could have relevance in understanding how fatigue associated with higher-intensity training exposures may potentially alter jump strategy and force production capacities due to external load intensity in collegiate basketball athletes.

Global and Local Shear Behavior of the Frozen Soil–Concrete Interface: Effects of Temperature, Water Content, Normal Stress, and Shear Rate

The interface between soil and concrete in cold climates has a significant effect on the structural integrity of embedded structures, including piles, liners, and others. In this study, a novel temperature control system was employed to conduct direct shear tests on this interface. The test conditions included normal stress (25 to 100 kPa), temperature (ranging from 20 to −6 °C), water content (from 10 to 19%), and shear rates (0.1 to 1.2 mm/min). Simultaneously, the deformation process of the interface was continuously photographed using a modified visual shear box, and the non-uniform deformation mechanism of the interface was analyzed by combining digital image correlation (DIC) technology with the photographic data. The findings revealed that the shear stress–shear displacement curves did not exhibit a discernible peak strength at elevated temperatures, indicating deformation behavior characterized by strain hardening. In the frozen state, however, the deformation softened, and the interfacial ice bonding strength exhibited a positive correlation with decreasing temperature. When the initial water content was 16% and the normal stress was 100 kPa, the peak shear strength increased significantly from 99.9 kPa to 182.9 kPa as the test temperature dropped from 20 °C to −6 °C. Both shear rate and temperature were found to have a marked effect on the peak shear strength, with interface cohesion being the principal factor contributing to this phenomenon. At a shear rate of 0.1 mm/min, the curve showed hardening characteristics, but at other shear rates, the curves exhibited strain-softening behavior, with the softening becoming more pronounced as shear rates increased and temperatures decreased. Due to the refreezing of interfacial ice, the residual shear strength increased in proportion to the reduction in shear rate. On a mesoscopic level, it was evident that the displacement of soil particles near the interface exhibited more pronounced changes. At lower shear rates, the phenomenon of interfacial refreezing became apparent, as evidenced by the periodic changes in interfacial granular displacement at the interface.

Atomic force microscopy wide-field scanning imaging using homography matrix optimization

During the offline combination of multiple atomic force microscopy (AFM) images, changes in probe displacement can be affected by dynamic noise, leading to dislocation and tearing in the stitching. To overcome this, we designed a homography matrix optimization method to describe the relative positional relationship between images by constructing the original image matrix and applying singular value decomposition to denoise the homography matrix. Additionally, we implemented a scale-invariant feature transform (SIFT) to extract feature points. To verify the effectiveness of this method, the SIFT + RANSAC (R), SIFT + affine transformation (AT), and oriented FAST and rotated BRIEF (ORB) algorithms were compared with the proposed algorithm. The experimental results demonstrate that the proposed method precisely computes the transformation matrix, thereby guaranteeing the geometric consistency of mosaic imaging. The proposed method preserves the intricate details of the original image and enhances the stitching quality of wide-field images.

Landslide displacement prediction using time series InSAR with combined LSTM and TCN: application to the Xiao Andong landslide, Yunnan Province, China

AbstractResearch on landslide displacement prediction based on interferometric synthetic aperture radar (InSAR) deformation data involves two main issues. First, InSAR can provide only one-dimensional deformation data along the satellite’s line of sight (LOS), which cannot truly reflect the deformation of the landslide body in the downward direction along the slope. Second, the use of a single prediction model does not adequately account for both long-term and local changes in landslide displacement, affecting the accuracy of the predictions. To address this, in this study, Long Short-Term Memory networks (LSTM) and temporal convolutional network (TCN) models are combined to construct a method (LSTM-TCN) of landslide displacement prediction. This method can consider the long-term and localized changes in landslide displacement. The method is first based on InSAR technology to obtain surface deformation. The deformation of the landslide is subsequently computed in the downward direction along the slope to obtain the landslide displacement time series data. Next, the LSTM-TCN is used for landslide displacement prediction. Finally, the mean absolute error (MAE), root mean square error (RMSE) and coefficient of determination (R2) are used to evaluate the performance of the model. The experiment is conducted on the Xiao Andong landslide in Anshi village, Fengqing County, Lincang City, Yunnan Province, China. The LSTM-TCN model achieves an R2 of 0.75, an RMSE of 0.43 cm, and an MAE of 0.36 cm. Compared with the individual LSTM and TCN models, the LSTM-TCN model exhibits the highest prediction accuracy and the smallest prediction error, which is closer to the true result that in the other models. These results demonstrate that the combined LSTM-TCN model effectively captures the complex features and long-term trends in landslide displacement data, significantly enhancing the accuracy of predictions.

A new Multivariate Drought Severity Index to identify short-term hydrological signals: case study of the Amazon River basin

The Earth's climate is changing rapidly and unexpectedly, causing more frequent, longer and more severe droughts, with lasting impacts on plants, ecosystems, communities and people. Consequently, this is leading to an increased importance of monitoring the climate and water storage trends in different regions. This information on a global scale is already commonly derived using satellite-based geodetic techniques such as the Global Positioning System (GPS) and the Gravity Recovery and Climate Experiment (GRACE). The use of both techniques has significant advantages, especially in regions where changes in the hydrosphere are notable, such as the Amazon basin, where 25 GPS stations were lately classified as benchmarks for hydrogeodesy. We show that the vertical displacements obtained from GPS and GRACE have good spatio-temporal agreement with the Standardized Precipitation and Standardized Precipitation Evapotranspiration indices, abbreviated respectively as SPI and SPEI, for all these stations. Drought severity index (DSI) estimated separately from GPS-observed and GRACE-derived vertical displacements on a station-by-station basis is capable to identify dry and wet events previously reported for the Amazon basin. However, due to the weaknesses of both techniques, such as technique-related systematic errors or coarse spatial resolution, a few extreme hydrological events may not be properly captured by GPS-DSI and/or GRACE-DSI. To take full advantage of both techniques and overcome their weaknesses, we introduce a completely new methodology to combine individual GPS-DSI and GRACE-DSI indices. As a novelty, both indices are estimated using short-term changes (<9 months) of monthly vertical displacements observed by GPS permanent stations and those derived by GRACE for GPS locations. Then, to capture and detect drought events that either both geodetic techniques metrics missed or incorrectly depicted, the Multivariate Drought Severity Index (MDSI) is estimated through the concept of Frank copulas. We demonstrate that the MDSI captures more hydroclimatic events reported in previous studies, which are not identified by individual series of GPS-DSI or GRACE-DSI indices, and is temporally consistent with Standardized Streamflow Index (SSI) based on the in-situ river discharge changes.

Interval prediction method for dynamic zoning of displacements in super-high arch dam under significant water level fluctuations

Displacement is one of the most intuitive indicators reflecting the influence of internal and external environments on dam structures. However, existing displacement monitoring models mostly rely on static fitting of single point and deterministic point value estimation, failing to deeply consider the similarity and uncertainty of displacement in dynamic changes under significant water level fluctuations. To address this issue, the displacements are first divided into three periods: ascending, descending, and stable periods. Second, based on the Ward criterion, the displacements of measuring points in different periods are clustered and partitioned, and the CRITIC method is applied to amalgamate the displacement of multiple points within each partition into comprehensive displacements, which reflect the displacement changes of the corresponding partition. Then, the comprehensive displacements are predicted utilizing deep learning model convolutional neural network-gated recurrent unit (CNN-GRU). Finally, to consider the uncertainty and randomness of displacement changes, prediction intervals based on Bootstrap method are employed to quantify the impact of uncertain factors. Engineering examples show that the proposed method can provide scientific basis and technical support for the safety monitoring and health diagnosis of super-high arch dams.

Thermal properties of mullite‐type SnAlBO4 and SnGaBO4

AbstractWe report on temperature‐dependent structural and spectroscopic properties of two new members of the mullite‐type ceramics SnAlBO4 and SnGaBO4. In‐situ X‐ray powder diffraction (XRPD) demonstrates positive thermal expansion behavior for all orthorhombic lattice parameters between 13 and 840 K. The lattice thermal expansion is modeled by Grüneisen first‐order approximation, where the vibrational energy is calculated by the Debye–Einstein–anharmonicity (DEA) approach. Although the thermal changes of the metric parameters do not show any discontinuity, the double‐Debye model and low‐temperature thermal analysis leave hints for subtle displacive changes. Splitting of the tin‐doublets of the 119Sn Mössbauer spectra at low temperature is assumed to be associated with structural modulation although the temperature‐dependent Raman spectra could not support these findings. The modulation could either be dynamic which requires much longer thermal equilibration than the speed of the data collection for XRPD and Raman spectroscopy. Selective Raman mode frequencies are analyzed using a modified Klemens model, which helps to understand the thermal anharmonic behaviors of the SnO4, MO6, and BO3 polyhedra as a function of temperature.

Risk Prediction Model for Tailings Ponds Based on EEMD-DA-LSTM Model

With the passage of time, the constant changes in relevant factors, and the daily maintenance of tailings ponds, the difficulty of tailings pond safety management is increasing day by day. In order to systematically improve the early warning ability for tailings pond dam break risk, the relationship between and influence of various related dam break risk factors of tailings ponds are utilised and the combination with dual attention is innovatively proposed. The risk prediction model for tailings ponds, EEMD-DA-LSTM, is improved. First, Pearson correlation coefficients are used to analyse the correlation between risk factors of tailings ponds. Then, the EEMD method is used to decompose the nonlinear displacement sequence, and the weights of input features are dynamically adjusted by double attention (DA). Finally, the LSTM network model is constructed to predict the displacement change. Taking valley-type tailings pond WKB-1 and mountainside tailings pond WKB-2 as examples, the dam break risk prediction models for tailings ponds are constructed based on three different models, the prediction results of different models are compared and analysed, and the prediction accuracy of the models is evaluated by three different evaluation criteria. The research results show that the integration of the EEMD-LSTM model with the DA model, that is, the EEMD-DA-LSTM model, has a better prediction effect for the dam break risk of tailings ponds WKB-1 and WKB-2 than other models through experimental verification. Therefore, the EEMD-DA-LSTM model is of great significance for preventing and resolving the safety risks of tailings ponds. It is valuable for practitioners in the mining industry and environmentally sustainable development.

A method of multi-bit optical coding by constructing Brewster angles to enhance photonic spin Hall effect

The photonic spin Hall effect, characterized by its polarization-driven spin-related displacement, has played an essential role in coding information processing. In this Letter, using a two-period double-layer dielectric plate, the displacement changes within the angle region are first observed, and a two-bit effective coding is achieved through non-uniform quantization of displacement values and coding. Afterward, by constructing Brewster angles (BAs), effective three-bit coding is achieved at the selected BA by dividing the angle domain. By changing the relative refractive index of the constituent materials (nB), effective coding is achieved at corresponding angles (45°–85°). By connecting two-bit and three-bit coding, a five-bit coding is fulfilled. By setting the last six invalid values, effective correspondence of 26 English letters is obtained. At the same time, the largest displacement peak itself is huge and varies accordingly with different values of nB. This work can provide some reference for designing optical coders.

Numerical study of vehicle motion during water exit under combined lifting force and wave action

During the retrieval process of the deep-sea mining vehicle (DSMV), the stability of the retrieval system is strongly influenced by the interaction between the vehicle body and the surrounding seawater due to the vehicle's complex shape and wave motion. Naturally, the negative side effects of significant changes in the vehicle's attitude and the water exit position can only increase retrieval's challenge. To investigate the characteristic of the flow field of the DSMV, this study employs the computational fluid dynamics method based on the Reynolds-averaged Navier–Stokes equations integrating the volume-of-fluid multiphase flow model with a fifth-order Stokes-wave model to explore the attitude and displacement changes of the vehicle during the water exit process in the ocean wave environment. The results indicate that the wave phase and lifting force are the major effect factors in the DSMV's water exit process. An appropriate lifting force under a specific wave phase can effectively reduce attitude changes and positional drift of the DSMV during water exit, thereby enhancing recovery efficiency and stability.

Automobile Intelligent Vehicle-machine and Human-computer Interaction System based on Big Data

This paper measures the accelerator, brake pedal, clutch, transmission device and steering wheel under different driving conditions in real-time and accurately on the simulation experiment platform. The goal is to conduct human-machine-road system interaction in a virtual simulation of human-vehicle-road systems. Fitting test data establishes the mathematical model of traffic control parameters. In terms of hardware, the distributed architecture of upper and lower computers is utilized. The system communicates point-to-point with the host computer through the RS-232 serial port. The system adopts multi-thread technology and serial communication technology. The simulation system of driving operation is designed with the visual central controller. The system takes 89S52 as the core. The slave program is written in C language. Then, the system establishes a multi-target coordinated obstacle avoidance method based on a multi-sensor information vehicle cooperation collision avoidance method. The multi-vehicle cooperation obstacle avoidance problem is transformed into an optimal control problem under multiple constraints. Simulation analysis shows that the velocity and displacement obtained by the multi-robot collaborative collision avoidance method are in good agreement with the measured values. Compared with the time series algorithm, the output accuracy of the proposed collaborative collision avoidance algorithm is significantly reduced, and the changes in velocity and displacement in the time domain are more stable.

Dynamics and internal structure of a rock glacier: Inferring relationships from the combined use of differential synthetic aperture radar interferometry, electrical resistivity tomography and ground‐penetrating radar

AbstractRock glaciers are characteristic landforms in alpine environments originating from the movement of permanently frozen ground. Hereby, rock glacier velocity (RGV) is an important parameter for understanding the effects of climate change on mountain permafrost. Although understanding of rock glacier dynamics has increased during the last decades, linking small‐scale surface kinematics to sub‐surface properties and heterogeneities remains a challenge. To address this gap, we conducted geophysical surveys (electrical resistivity tomography [ERT] and ground‐penetrating radar [GPR]) along two profile lines of 450 and 950 m in length on a rock glacier in the Central Swiss Alps. Additionally, RGV was derived from Sentinel‐1 differential synthetic aperture radar interferometry (DInSAR) to quantify annual east–west displacement and elevation change as well as seasonal acceleration during the snow‐free summer months with a ground sampling distance of 5 m. Our results show that movement angle and seasonality are highly associated with different patterns in sub‐surface structure. These different movement patterns are linked to subunits of different morphological origins. Thereby, we can upscale the geophysical results based on the DInSAR surface movement parameters and outline an area within the study site probably affected by ice of glacial origin. Hence, DInSAR movement angle and seasonality can help to bring local sub‐surface information derived from time‐consuming geophysical investigations into the spatial domain. In this way, a better understanding of the current morphodynamics as well as the past and future evolution of the landform can be reached. Applying the approach to other sites with available geophysical investigations could enhance our knowledge about systematic links between surface kinematics and the internal structure of rock glaciers and other ice‐rich glacial and peri‐glacial landforms, as well as their response to a warming climate.

Study on the deformation and failure laws of surrounding rock under reduced roof thickness in Salt Cavern Gas Storage

Under the premise of guaranteeing the stability of the gas storage reservoir, reducing the thickness of the salt layer on the top plate of the gas storage reservoir can improve the utilization rate of the salt layer in the construction section and increase the vertical height of the gas storage reservoir cavity, creating a larger gas storage space. The mechanical planar model of the casing-cement sheath-surrounding rock in the top plate of the salt cavern gas storage reservoir yields the elastic–plastic theoretical solution for the stress and deformation of the well wall surrounding rock. Based on this, a three-dimensional mechanical numerical model of the top plate is constructed to compare the effects of various top plate thicknesses on the surrounding rocks of the gas storage reservoir and to analyze the stress and deformation behavior of the wall surrounding the rock of the top plate of the reservoir in the cementing section and bare wells under the long-term injection and extraction cycle. The results indicate that reducing the thickness of the roof salt layer primarily affects vertical displacement, radial displacement, equivalent strain, and principal stress changes in the cement sheath and surrounding rock. All other roof parameters, except for equivalent strain, show an increasing trend. Reducing the salt layer thickness in the cementing section has the least impact on the gas storage roof’s stability. In contrast, reducing the salt layer thickness in the cementing section and bare wells has a moderate impact, while reducing the thickness solely in the bare wells is the most detrimental. These findings provide valuable insights for optimizing the roof thickness of gas storage facilities and enhancing the utilization of the limited salt layer in the reservoir section.

Aggregation‐Enhanced Photodynamic Activity of Organometallic Ru(II)–Arene Complexes

ABSTRACTOrganometallic Ru(II)–arene complexes have emerged as potential chemotherapeutic agents for improved cancer treatment. However, the application of Ru(II)–arene complexes as photosensitizers has been rarely explored. In consideration of their excellent biological performance, herein, three Ru(II)–arene complexes 1–3 bearing 2,3,8,9,14,15‐hexamethyl‐5,6,11,12,17,18‐hexaazatrinapthalene (HATN‐Me6) as acceptor ligand have been designed and investigated as potential photosensitizers. Distinctively, complexes 1–3 produced negligible singlet oxygen (1O2) generation in DMF. The mechanism investigations indicated that the large change in equilibrium displacement between the excited and ground states rather than narrow energy gap results in the increased vibrational wave function overlap and non‐radiative decay rate. Remarkably, complexes 1–3 induced greatly enhanced 1O2 generation efficiency in an aggregated state due to the suppression of the non‐radiative decay process, implying that the electronic structures of excited states play an essential role in the photochemical properties and functions of the organometallic Ru(II)–arene complexes. The biological evaluation showed that complexes 1–3 exhibited potent photocytotoxicity against cancer cells, highlighting that organometallic Ru(II)–arene scaffolds are potential platforms for the fabrication of efficient photosensitizers.

Rossby waves impact on persistent oxic and suboxic chlorophyll maxima in the Eastern Tropical North Pacific

This study aims to describe the response of two persistent chlorophyll-a maxima to physical processes that affect the po- sition of the thermocline/nitracline in the Eastern Tropical North Pacific (ETNP). We focused on Long Rossby Waves (LRWs) due to their relevance to the ETNP circulation and their potential role in introducing nutrients into the euphotic zone. We found that the shallower chlorophyll-a maximum in oxygenated waters became more intense when denser waters (containing more nu- trients) moved toward the surface. This suggests that changes in isopycnals and nitracline displacements modify nutrient supply in the euphotic zone, leading to changes in phytoplankton growth. The suboxic and deeper chlorophyll-a maximum showed a strong association with the 26 kg m-3 isopycnal, which was only mechanically displaced, and its chlorophyll-a content did not seem to covary with irradiance or nutrients. The decor- related responses of the chlorophyll-a maxima could be ex- plained if different phytoplankton groups are associated with them. LRWs can affect the position of the thermocline/nitracline and isopycnals in an annual cycle, but it seems to be a “back- ground” signal modulated by higher frequency processes such as mesoscale eddies and other Rossby waves. The co-occurrence of processes can control the nitracline depth, and thus the input of nutrients into the euphotic zone, leading to sporadic enhance- ments in chlorophyll-a concentration in one maximum.

Three-phase balance relay using numerical techniques experimentally verified on synchronous machines

In this paper, a multifunction three-phase balance relay based on normalized correlation coefficients is proposed to detect and estimate imbalances and perturbations in synchronous machine output signals. Furthermore, fresh definitions of imbalance and disturbance indicators derived using the correlation estimators are introduced, taking into account the changes in the waveform phase displacement, frequency, amplitude, and shape of the machine three-phase waves. Experimental tests are performed on a motor–generator set connected to a three-phase load, which is used to identify and evaluate the imbalance and disturbance conditions of the voltage and current measurements. Extensive tests for different fault types have been presented. The practical results show that the proposed protection can respond quickly to faults, and assess online the level of the imbalance/disturbance with high accuracy. Its running time is within one cycle. In addition, the proposed algorithm’s reliability and accuracy are its most significant attributes, whose percentages exceed 96.6%. The present algorithm considers the impact of both negative and zero sequence components when measuring di-symmetry factors, while some conventional approaches merely rely on the negative sequence component computed for the machine voltages and currents.

Phase behavior of the carbon dioxide/toluene/poly(ethylene glycol) ternary system

The phase behavior of a carbon dioxide (CO2)/toluene (Tol)/poly(ethylene glycol) (PEG) ternary system was investigated in this study to consider the effect of the polymer species on the phase diagram. Measurements were performed using a synthetic method combined with laser displacement and turbidity measurements. Bubble points (vapor–liquid phase separation) were determined from changes in the piston displacement and cloud points (liquid–liquid (LL) phase separation) were determined from changes in the turbidity. The phase boundaries of the CO2 mass fractions ranging from 0.113 to 0.496 were measured by varying the Tol/PEG mass ratio. The homogeneous phase area decreased when the mass ratio of PEG to Tol increased and/or the temperature decreased. These changes in the LL phase-separation behavior were explained by referring to the free volume fraction and solubility parameter estimated using the Sanchez–Lacombe equation of state. The free volume integral fraction could explain the phase diagram, but not the solubility parameter; the effect of polymer species on the Px phase diagram of the ternary system was explained by considering specific interactions between dissimilar components. These results could promote a comprehensive understanding of the phase diagram of CO2/organic solvent/polymer systems and aid the prediction of phase behavior.

A Cost-Effective and Easy-to-Fabricate Conductive Velcro Dry Electrode for Durable and High-Performance Biopotential Acquisition.

Compared with the traditional gel electrode, the dry electrode is being taken more seriously in bioelectrical recording because of its easy preparation, long-lasting ability, and reusability. However, the commonly used dry AgCl electrodes and silver cloth electrodes are generally hard to record through hair due to their flat contact surface. Claw electrodes can contact skin through hair on the head and body, but the internal claw structure is relatively hard and causes discomfort after being worn for a few hours. Here, we report a conductive Velcro electrode (CVE) with an elastic hook hair structure, which can collect biopotential through body hair. The elastic hooks greatly reduce discomfort after long-time wearing and can even be worn all day. The CVE electrode is fabricated by one-step immersion in conductive silver paste based on the cost-effective commercial Velcro, forming a uniform and durable conductive coating on a cluster of hook microstructures. The electrode shows excellent properties, including low impedance (15.88 kΩ @ 10 Hz), high signal-to-noise ratio (16.0 dB), strong water resistance, and mechanical resistance. After washing in laundry detergent, the impedance of CVE is still 16% lower than the commercial AgCl electrodes. To verify the mechanical strength and recovery capability, we conducted cyclic compression experiments. The results show that the displacement change of the electrode hook hair after 50 compression cycles was still less than 1%. This electrode provides a universal acquisition scheme, including effective acquisition of different parts of the body with or without hair. Finally, the gesture recognition from electromyography (EMG) by the CVE electrode was applied with accuracy above 90%. The CVE proposed in this study has great potential and promise in various human-machine interface (HMI) applications that employ surface biopotential signals on the body or head with hair.

Effect of Sclerosis Bands in Femoral Head Necrosis on Non-Vascularized Fibular Grafting-A Finite Element Study.

Femoral head necrosis is a challenging condition in orthopaedics, and the occurrence of collapse is an important factor affecting the prognosis of femoral head necrosis. Sclerosis bands are known to influence the collapse of the femoral head, yet there is a lack of research on the biomechanical role of sclerosis bands in non-vascularized fibular grafting surgery. This study aims to evaluate the biomechanical impact of sclerosis bands in femoral head necrosis and their role in non-vascularized fibular grafting surgery (NVFG) using finite element analysis. We constructed 11 finite element models based on CT scan data of a normal hip joint, simulating different sclerosis band thicknesses and defect scenarios. The models were analyzed for changes in femoral head displacement and von Mises stress. We constructed a hip joint model based on CT data from a normal hip joint, and after reconstruction, assembly, and optimization using 3-matic. We created five groups consisting of 11 finite element analysis models of the hip joint. Mesh partitioning and mechanical parameter settings were performed in ANSYS. The changes and differences in femoral head displacement and von Mises stress of these models were analyzed. Increasing sclerosis band thickness led to reduced peak displacement of the femoral head by 28.6%, 42.9%, and 47.6%, and increased surface von Mises stress by 28.3%, 13.8%, and 13.0%, respectively. Post-surgery, peak displacement decreased in all groups compared to pre-surgery levels. Increasing sclerosis band thickness post-surgery resulted in decreased maximum von Mises stress of the femoral head by 13.9%, 3.0%, and 8.1%. Defect volume in the defect groups correlated with increased peak displacement of the femoral head by 10.0%, 30.0%, and 100.0%, and increased surface maximum von Mises stress of the femoral head by 9.3%, 14.0%, and 15.1%. Sclerosis band formation exacerbates von Mises stress concentration on the femoral head surface. However, thicker sclerosis bands improve post-NVFG stability and mechanical performance. Larger anterior lateral sclerosis band defects significantly compromise postoperative stability, increasing the risk of collapse. Protecting the anterior lateral sclerosis band during NVFG surgery is crucial.

Effect of lighting conditions on implantable collamer lens vault: Influence of anterior chamber and lens parameters

PurposeTo investigate the change in the vault of the implantable collamer lens (ICL) under dark-to-light conditions and its association with anterior chamber and lens parameters in patients undergoing ICL surgery. MethodsIn 76 eyes from 40 patients, preoperative anterior chamber volume (ACV), pupil diameter (PD), anterior chamber angle, central corneal thickness (CCT), white-to-white (WTW), lens thickness (LT), axial length (AL), spherical equivalent (SE) and patient's age were collected. Postoperative vault, PD and LT were measured under dark and light conditions using anterior segment optical coherence tomography (CASIA2; TOMEY, Japan), and changes and lens displacement under dark-to-light conditions were calculated. Mixed-effects models were used to analyze the correlation between the vault change and the anterior chamber and lens parameters of all subjects and the high-vault subgroup. ResultsThe vault under light condition (648.36 ± 304.47 μm) was significantly smaller compared to the vault under dark condition (708.89 ± 316.15 μm). In all patients, vault change increased with the increase of age, lens displacement and PD change; and increased with the decrease of ACV, LT change and baseline vault (under dark condition). In the high-vault subgroup, vault change increased with the increase of CCT, lens displacement and PD change; and increased with the decrease of ACV. ConclusionsICL vault changes significantly from dark to light, influenced by age, ACV, PD change, LT change, lens displacement, and baseline vault. A higher baseline vault is correlated with a larger LT change, affecting the levels of accommodation under dark-to-light transition.