Curve Evolution Research Articles

Study on compaction characteristics and mechanical model of dry crushing filling material under lateral confinement condition

The compaction characteristics and bearing capacity of dry filling materials in goaf have a significant influence on stope control and surface stability. Through acoustic emission monitoring and mechanical model analysis, a series of confined compression tests were conducted on crushed waste with varying particle sizes and Talbot coefficients. The deformation, fragmentation, and acoustic emission characteristics under corresponding working conditions were determined. The results indicate that the stress–strain curves of crushed stone with different particle sizes and Talbot coefficients exhibit similar nonlinear behavior during confined compression. However, the strain response varies with changing stress levels. By analyzing the slope change rate of the stress–strain curve, the lateral uniaxial compression process of waste rock can be divided into three deformation stages: rapid compression, stable crushing, and slow compaction. The compressive deformation characteristics of gravel differ based on particle size and Talbot coefficient. Specimens with a higher Talbot coefficient demonstrate stronger compressive resistance and weaker deformation resistance during initial compaction loading. Notably, the internal pressure structure strength is influenced by factors such as maximum particle size D, grading coefficient n, and particle size distribution continuity, rather than solely by the proportion of large particles. The evolution of acoustic emission signals and energy-time curve during waste rock confined axial compression synchronizes with the compaction process. Overall, compaction plays a critical role in maintaining the stability of goaf in dry crushed waste filling.

Data-driven mathematical modeling of sleep consolidation in early childhood

Across early childhood development, sleep behavior transitions from a biphasic pattern (a daytime nap and nighttime sleep) to a monophasic pattern (only nighttime sleep). The transition to consolidated nighttime sleep, which occurs in most children between 2- and 5-years-old, is a major developmental milestone and reflects interactions between the developing homeostatic sleep drive and circadian system. Using a physiologically-based mathematical model of the sleep-wake regulatory network constrained by observational and experimental data from preschool-aged participants, we analyze how developmentally-mediated changes in the homeostatic sleep drive may contribute to the transition from napping to non-napping sleep patterns. We establish baseline behavior by identifying parameter sets that model typical 2-year-old napping behavior and 5-year-old non-napping behavior. Then we vary six model parameters associated with the dynamics of and sensitivity to the homeostatic sleep drive between the 2-year-old and 5-year-old parameter values to induce the transition from biphasic to monophasic sleep. We analyze the individual contributions of these parameters to sleep patterning by independently varying their age-dependent developmental trajectories. Parameters vary according to distinct evolution curves and produce bifurcation sequences representing various ages of transition onset, transition durations, and transitional sleep patterns. Finally, we consider the ability of napping and non-napping light schedules to reinforce napping or promote a transition to consolidated sleep, respectively. These modeling results provide insight into the role of the homeostatic sleep drive in promoting interindividual variability in developmentally-mediated transitions in sleep behavior and lay foundations for the identification of light- or behavior-based interventions that promote healthy sleep consolidation in early childhood.

A second-order in time, BGN-based parametric finite element method for geometric flows of curves

Over the last two decades, the field of geometric curve evolutions has attracted significant attention from scientific computing. One of the most popular numerical methods for solving geometric flows is the so-called BGN scheme, which was proposed by Barrett et al. (2007) [8], due to its favorable properties (e.g., its computational efficiency and the good mesh property). However, the BGN scheme is limited to first-order accuracy in time, and how to develop a higher-order numerical scheme is challenging. In this paper, we propose a fully discrete, temporal second-order parametric finite element method, which integrates with two different mesh regularization techniques, for solving geometric flows of curves. The scheme is constructed based on the BGN formulation and a semi-implicit Crank-Nicolson leap-frog time stepping discretization as well as a linear finite element approximation in space. More importantly, we point out that the shape metrics, such as manifold distance and Hausdorff distance, instead of function norms, should be employed to measure numerical errors. Extensive numerical experiments demonstrate that the proposed BGN-based scheme is second-order accurate in time in terms of shape metrics. Moreover, by employing the classical BGN scheme as mesh regularization techniques, our proposed second-order schemes exhibit good properties with respect to the mesh distribution. In addition, an unconditional interlaced energy stability property is obtained for one of the mesh regularization techniques.

Separation and conversion of CO2 reduction products into high-concentration formic acid using bipolar membrane electrodialysis

Electrochemical CO2 reduction to value-added chemicals such as formate represents a crucial pathway in advancing carbon-neutral fuel production. However, the separation of formate from KHCO3 electrolyte solutions and its conversion to formic acid remain cost intensive steps in this process. This study demonstrated the use of bipolar membrane electrodialysis (BMED) to efficiently convert and concentrate formic acid directly from a cathodic solution for CO2 electroreduction. The migration of formate ions during BMED was optimized under different cell configurations and current densities. Mathematical modelling was developed to predict the concentration evolution curves of formic acid production. The results showed that formic acid diffusion through an anion-exchange membrane was more pronounced than that a bipolar membrane; the former diffusion was a key factor that limited the formic acid concentration and reduced the current efficiency. A formic acid concentration of 3.49 mol/L was obtained at an optimum current density of 40 mA/cm2 and a salt-to-acid compartment volume ratio of 25:1. Thus, BMED has emerged as a viable and effective technique for isolating high-purity formic acid from a cathodic solution for CO2 electroreduction.

Effects of multiple relaxation times in the annular flow of pulsatile electro-osmotic flow of a complex biological fluid: blood with low and high cholesterol

This study investigates the electro-osmotic flow of a biological fluid (blood with varying cholesterol levels) in annular flow to simulate a first approximation to arterial occlusion. The fluid´s rheology is characterized by a multi-modal convected Maxwell model equation. The charge density follows the Boltzmann distribution, governing the electrical field. Mathematically, this scenario can be modeled by the Poisson–Boltzmann partial differential equation. Assuming a small zeta potential (less than 25 mV) using the Debye–Huckel approximation and considering a pulsatile electrical field, analytical solutions are derived using the Fourier transform formalism. These solutions, expressed in terms of the modified Bessel function, provide transfer functions for axial velocity and volumetric flow as functions of material parameters represented by characteristic dimensionless numbers. This study further analyzes thermal, electric, inertial, viscoelastic, and various interactions within the plasma, hematocrit, hematocrit–cholesterol, and cholesterol–cholesterol as well as weight concentration through numerical simulations. Finally, the flow and rheology predictions are validated using experimental data on human blood with varying cholesterol levels. The obtained transfer functions reveal that the electric–thermal–viscoelastic effects and the multiple geometric relationships contribute to the dynamic response of the interactions between the input electrical field and output volumetric flow and shear stress functions, leading to and evolution of resonance curves. It is noteworthy that electro-osmotic flow in blood with pathologies associated with low and high cholesterol has been scarcely reported in the literature on rheology. Thus, this work represents a significant contribution to the field.

A frost heave pressure model for fractured rocks subjected to repeated freeze-thaw deterioration

Rock engineering in the Tibetan Plateau is usually suffered severe freeze-thaw (F-T) deterioration, triggering numerous geotechnical engineering disasters. As the essential triggering factor of F-T damage, the frost heave pressure (FHP) in rocks should be quantitatively described and predicted. In this study, a novel theoretical model is established and validated to estimate the critical entire evolution process of FHP in fractured rocks subjected to repeated F-T deterioration, in which the influence of fracture geometric configuration, rock mechanical properties and F-T conditions are comprehensively considered. Besides, given the obvious five-stage manner of FHP evolution, the combination effect of different dominant mechanisms in different stages is theoretically addressed. During freezing, after a silence stage induced by temperature above freezing point of water, volumetric expansion and frost-heave cracking separately controls the generation and reduction stages of FHP, and the solutions are obtained based on elastic mechanics and Griffith energy balance theory, respectively. During thawing, ice segregation dominates the second-arising stage of FHP that is quantitatively described via segregation potential and water migration velocity, and then the FHP enters the dissipation stage owing to complete melting of fracture ice. In addition, a decay coefficient is introduced to estimate the influence of F-T cycle number on FHP, and a piecewise FHP model is finally constructed for fractured rocks subjected to repeated F-T deterioration. To validate our new model, a total of 12 F-T cycle tests with real-time FHP monitoring are conducted on granite and sandstone specimens considering three typical influencing factors, i.e., fracture width, rock types and freezing temperatures. A rational consistency is identified between the theoretical and testing results in terms of the FHP evolution curves and the peak FHPs in rock fracture, demonstrating the generalizability and robustness of our proposed model.

The Evolution of Curve Patterns in Adolescent Idiopathic Scoliosis during Chêneau Brace Treatment.

This retrospective study analyzed bracing outcomes in AIS patients, focusing on curve pattern changes and brace efficacy. To analyze the effectiveness of the Chêneau brace across different curve patterns and to evaluate the tendencies in curve evolution during treatment. Adolescent idiopathic scoliosis (AIS) presents diverse curve patterns, each responding differently to bracing. Understanding these variations is crucial for optimizing treatment strategies. The study included 177 AIS patients treated with Chêneau orthoses, categorized based on curve patterns as per the main curve and modified Lenke (mLenke) classifications. We compared patients according to curve patterns and assessed changes in curve magnitude and pattern before and after treatment. Over an average follow-up of 28.1±10.7 months, the primary curve magnitude decreased from 28.8±6.6° to 25.9±10.5°. Significant reductions were observed in mLenke V and VI patients (P<0.05). Patients with main lumbar curves showed better initial in-brace correction and curve control compared with those with main thoracic curves (P<0.05). In single-curve patterns, binary logistic regression indicated that mLenke V patients demonstrated higher rates of curve control compared with mLenke I patients (P<0.05). No significant differences were found in double-curve patterns between mLenke III and VI (P>0.05). At the final follow-up, thoracolumbar/lumbar curves improved significantly in mLenke III and VI patients (P<0.05), while thoracic curves did not (P>0.05). Furthermore, at the last follow-up, the proportions of mLenke I, II, and IV increased, while mLenke III, V, and VI decreased. Bracing outcomes were more favorable in patients with main lumbar curves than those with main thoracic curves. However, no significant differences were found in patients with double-curve patterns. Thoracic curves exhibited a higher progression risk compared with thoracolumbar/lumbar curves within the same curve pattern. During bracing, a tendency for primary curves to shift proximally was noted.

Curvature-Based Active Region Segmentation for Improved Image Processing of Aspergillus Species

Aspergillus is one of the most ubiquitous of the airborne saprophytic fungi that can withstand various climatic conditions and could cause multiple type of illness. It can be beneficial to humankind and also can be infectious to humans and animals. Direct microscopic is used by trained microscopist as one of the alternatives in identification process to any specimen that suspected of having fungal infection. Confirmation towards identification is often necessary as the structure of Aspergillus is complex and dissimilar in each cycle. In addition, the structure of some species of Aspergillus are the almost same, which can be incorrectly recognized. In prevention of misidentification, computer-based Aspergillus species identification is proposed. The detection process is the earliest and important process hence, this paper proposed an active region-based segmentation method in order to detect the presence of fungi. This method is literally not depending on the gradient or sharp edges of the object and implementing level set function for curve evolution which able to reduce the computational cost. Originally, this function was developed for tracking fluid interfaces but in this study, this function has been applied to fungi database. Two different methods were tested and compared to observe their ability to segment different 80 of Aspergillus images which included four species. Experiments conducted have been compared with the baseline technique and the proposed method is outperformed in terms of accuracy, specificity with average of 90% and PSNR value of greater than 40dB. Meanwhile the active contour (snake) was slightly underperformed but well performed particularly in terms of sensitivity with greater than 80% for all the species. Moreover, upon scrutinizing the dice coefficients provided in both tables, it becomes apparent that there is a lack of significant variance in the values, except in the instance of Aspergillus fumigatus (active region-based) that which produces a result below 36%.

How to promote cooperative innovation in environmentally friendly technology: a case of agricultural biotechnology in China

This study explored the factors influencing cooperative innovation in environmentally friendly agricultural biotechnology in China. First, we constructed an evolutionary game model comprising the factors of net income of cooperative innovation, net income of independent innovation, market constraints, and government subsidies. Using MATLAB simulation, we assigned different values to the aforementioned variables to explore the evolutionary trend of innovators’ willingness to cooperate. Results showed that when the values of net income of cooperative innovation, net income of independent innovation, market constraints, and government subsidies exceeded the threshold, innovators’ willingness to cooperate was significantly enhanced. Furthermore, the proportion of innovators who cooperated with others gradually increased to 100%; otherwise, it gradually decreased to 0%. Comparing the simulation curve with the real evolution curve of cooperative innovation in agricultural biotechnology in China, we found that the gradual decline in the willingness to cooperate could be due to insufficient subsidies for cooperative innovation, low income from cooperative innovation, weak profitability of innovators, and weak market constraints.

On evolutes of curves in the isotropic plane

On evolutes of curves in the isotropic plane

Discrete anisotropic curve shortening flow in higher codimension

Abstract We introduce a novel formulation for the evolution of parametric curves by anisotropic curve shortening flow in ${{\mathbb{R}}}^{d}$, $d\geq 2$. The reformulation hinges on a suitable manipulation of the parameterization’s tangential velocity, leading to a strictly parabolic differential equation. Moreover, the derived equation is in divergence form, giving rise to a natural variational numerical method. For a fully discrete finite element approximation based on piecewise linear elements we prove optimal error estimates. Numerical simulations confirm the theoretical results and demonstrate the practicality of the method.

Sodium alanate in-situ doped with Ti2C MXene with enhanced hydrogen storage properties

NaAlH4 is a reversible hydrogen storage material and has attracted great attention recently. However, the application of NaAlH4 in hydrogen storage still has great difficulties. In this study, 2D MXene Ti2C-doped NaAlH4 samples were prepared in-situ by reaction ball milling of NaH under moderate condition. TPD measurement results show that all the as-prepared samples exhibit good thermodynamic performance except for the sample doped with 1 wt% Ti2C. And DSC analysis results show that at the heating rate of 5 K/min, the first and second dehydrogenation peak temperatures of the sample doped with 7 wt% Ti2C were 127.1 °C and 150.6 °C respectively, which are 57.4 °C and 123.6 °C lower than those of pure NaAlH4 (after ball milling), respectively. Meanwhile, NaH/Al-7 wt.% Ti2C sample displays a superior kinetics behavior. Isothermal hydrogen evolution curves show that NaH/Al-7 wt.%Ti2C released 5.21 wt% H2 within 30 min at 150 °C and then absorbs 5.2 wt% H2 in 90 s at 120 °C. Even at a lower temperature of 80 °C, the sample still absorbed 4.71 wt% H2 within 60 min. In addition, almost no release capacity attenuation was observed for NaH/Al-7 wt.%Ti2C after 10 hydrogen absorption/desorption cycles. The improvement of the hydrogen storage properties can be ascribed to the high reactivity of NaAlH4 produced in situ and catalysis of lamellar Ti3+/0 species formed by the reduction of high valent Ti in Ti2C during ball milling.

RFLSE: Joint radiomics feature‐enhanced level‐set segmentation for low‐contrast SPECT/CT tumour images

AbstractDoctors typically use non‐contrast‐enhanced computed tomography (NCECT) in the treatment of kidney cancer to map kidney and tumour structural information to functional imaging single‐photon emission computed tomography, which is then used to assess patient kidney function and predict postoperative recovery. However, the assessment of kidney function and formulation of surgical plans is constrained by the low contrast of tumours in NCECT, which hinders the acquisition of accurate tumour boundaries. Therefore, this study designed a radiomics feature‐enhanced level‐set evolution (RFLSE) to precisely segment small‐sample low‐contrast kidney tumours. Integration of high‐dimensional radiomics features into the level‐set energy function enhances the edge detection capability of low‐contrast kidney tumours. The use of sensitive radiomics features to control the regional term parameters achieves adaptive adjustment of the curve evolution amplitude, improving the level‐set segmentation process. The experimental data used low‐contrast, limited‐sample tumours provided by hospitals, as well as the public datasets BUSI18 and KiTS19. Comparative results with advanced energy functionals and deep learning models demonstrate the precision and robustness of RFLSE segmentation. Additionally, the application value of RFLSE in assisting doctors with accurately marking tumours and generating high‐quality pseudo‐labels for deep learning datasets is demonstrated.

Research on anisotropic characteristics and energy damage evolution mechanism of bedding coal under uniaxial compression

Bedding structures are commonly present in the underground coal mine pillar rock mass, posing a certain threat to its stability. In order to gain a deeper understanding of the damage, destruction, and energy conversion of bedding coal, uniaxial compression experiments were conducted on bedding coal samples. The research results reveal that the compressive strength of coal is highest when the bedding dip angle is 0° (28.74 MPa), followed by 30° and 90° (15.03 and 14.02 MPa), and lowest at 60° (10.03 MPa). The damage evolution curve of coal at a bedding dip angle of 60° exhibits an early sharp increase, indicating that macroscopic damage is easily induced along the bedding planes under this condition. As the bedding dip angle increases from 0° to 90°, the degree of damage to coal under energy drive exhibits a pattern of difficulty-ease-difficulty. When the bedding dip angle is 0°, the coal sample fractures steadily as cracks expand. At 30°, the failure process involves a gradual and steady expansion of cracks followed by an unstable extension. At 60° and 90°, the fractures result in sudden and unstable damage. Furthermore, this study explores the inherent mechanisms of anisotropy and the evolution models of damage in bedding coal.

Mesoscopic precursor anomaly characteristics of red sandstone under uniaxial compression after cyclic high-temperatures

The deformation and failure characteristics of rock caused by periodic changes of temperature are not only significantly different from that under normal temperature, but also significantly different from that produced by a single high-temperature event. Here, using a three-dimensional digital image correlation (3D-DIC) integrated test system, mechanical and micro-damage tests of red sandstone are performed under cycles of high-temperature and natural-cooling with a temperature range of 25°C to 300°C and the number of cycles varying between 0 and 25. Macroscopic, mesoscopic and microscopic characteristics such as rock strength, deformation, strain field and fracture morphology are examined and their evolution with the number of heating-cooling cycles is discussed. Using the time-history evolution of the differentiation rate of the precursor anomaly (En), the characteristic coefficient (K) and the damage variable (DF), three kinds of characteristic time points are put forward to quantify the incubation and development time of precursor abnormal characteristics and are used to divide the whole process of deformation and failure. These time points are the precursor abnormal differentiation time (PADT) tE, the precursor abnormal startup time (PAST) tK, and the precursor abnormal failure time (PAFT) tD. Test results show that: (1) The action of cyclic high-temperature natural-cooling not only shows the strengthening effect of temperature, but also shows the strengthening effect of a certain number of cycles. (2) The evolution sequence of the three precursor abnormal characteristic moments is PADT, PAST and PAFT in turn, and this sequence can intuitively describe the whole complex process of rock deformation and failure, and there are wave peaks in the evolution curve with the number of high-temperature cycle. (3) The effect of high temperature (i.e., 300°C) cyclic heating on rock properties is similar to the threshold effect of a single high-temperature heating event.

Classification and evolution of bifurcation curves of semipositone problem with Minkowski-curvature operator and its applications

In this paper, we study the classification and evolution of bifurcation curves of semipositone problem with Minkowski-curvature operator{−(u′/1−u′2)′=λf(u), in (−L,L),u(−L)=u(L)=0,where λ,L>0, f∈C2(0,∞), and the following conditions (H1)–(H2) hold:(H1)there exists β>0 such that (β−u)f(u)<0 for u>0 and u≠β.(H2)Let F(u)≡∫0uf(t)dt. Then F:[0,∞)⟶R is continuous and differentiable for u>0. And there exists η>0 such that (η−u)F(u)<0 for u>0 and u≠η. Notice that we allow f(0+)=−∞. In particular, we further obtain the exact shapes of the bifurcation curve as f is convex or concave. Finally, we apply these results in several problems.

Kilonova Parameter Estimation with LSST at Vera C. Rubin Observatory

The upcoming Vera Rubin Observatory’s Legacy Survey of Space and Time (LSST) opens a new opportunity to rapidly survey the southern sky at optical wavelengths (i.e., ugrizy bands). In this study, we aim to test the possibility of using LSST observations to constrain the mass and velocity of different kilonova (KN) ejecta components from the observation of a combined set of light curves from afterglows of γ-ray bursts and KNe. We used a sample of simulated light curves from the aforementioned events as they would have been seen during the LSST survey to study how the choice of observing strategies impacts the parameter estimation. We found that the design of observing strategy that is the best compromise between light-curve coverage, observed filters, and reliability of the fit involves a high number of visits with long-gap pairs of about 4 hr every two nights in the same or different filters. The features of the observing strategy will allow us to recognize the different stages of the evolution of the light curve and gather observations in at least three filters.

Flexural fatigue performance of recycled sand concrete for high-speed railway track bed

To investigate the applicability of recycled sand concrete in high-speed railway ballastless track bed, in this study, the fatigue life, strain evolution curve and calculated stiffness of C40 concrete incorporating 0, 50 % and 100 % recycled sand were explored. Digital image correlation (DIC) and the nanoindentation test were used to explore the influence of recycled sand on the performance of concrete. The results show that the flexural fatigue life of recycled sand concrete conforms to a two-parameter Weibull distribution. The fatigue strain progression and calculated stiffness demonstrate a distinct three-stage trend. Compared to natural aggregate concrete, the first-stage strain contribution of recycled sand concrete decreases by approximately 10 %. With the increase of fatigue cycles, the calculated stiffness decreased significantly, the dissipated energy increases gradually. Compared with recycled sand-free concrete and full recycled sand concrete, the concrete containing 50 % recycled sand possesses the highest elastic modulus and lowest thickness of the interfacial transition zone (ITZ), thus the average fatigue life of recycled sand concrete increased by 4.9 and 10.2 times.

Impact damage testing based on high-speed continuous water jet aircraft coatings

When an aircraft passes through a rainy area at high speed, the coating on the front edge of the fuselage will be continuously eroded by raindrops, causing the coating to wear, crack or even peel off. This paper uses carbon fiber T300 material as the base material, and at the different impact speeds and impact numbers, water cutting equipment was used to simulate the erosion of the coating caused by the continuous impact of water droplets. The damage morphology of samples at different damage stages was observed by digital microscope and Scanning Electron Microscope (SEM), and the damage evolution curve was established to analyze and reveal the damage behavior and damage mechanism of rain erosion. The results show that the degree of damage experienced an increasing trend with the increase of impact numbers and speed, until circular peel damage was formed; no damage occurred during the incubation period, and the curvature of the damage evolution curve increased significantly after the expansion period and eventually showed a stable expansion trend. The mechanical properties of the coating material were the main influencing factors of its rain corrosion resistance. Moreover, the axially symmetric unsteady contact problem of droplets impacting the surface of a solid deformable body was studied. And the contact area was determined based on the iterative algorithm boundary positioning method. A mathematical model and closed mathematical formula describing the unsteady interaction between a droplet and a solid deformable obstacle were proposed.

Diagnosis of Forme Fruste Keratoconus Using Corvis ST Sequences with Digital Image Correlation and Machine Learning.

This study aimed to employ the incremental digital image correlation (DIC) method to obtain displacement and strain field data of the cornea from Corvis ST (CVS) sequences and access the performance of embedding these biomechanical data with machine learning models to distinguish forme fruste keratoconus (FFKC) from normal corneas. 100 subjects were categorized into normal (N = 50) and FFKC (N = 50) groups. Image sequences depicting the horizontal cross-section of the human cornea under air puff were captured using the Corvis ST tonometer. The high-speed evolution of full-field corneal displacement, strain, velocity, and strain rate was reconstructed utilizing the incremental DIC approach. Maximum (max-) and average (ave-) values of full-field displacement V, shear strain γxy, velocity VR, and shear strain rate γxyR were determined over time, generating eight evolution curves denoting max-V, max-γxy, max-VR, max-γxyR, ave-V, ave-γxy, ave-VR, and ave-γxyR, respectively. These evolution data were inputted into two machine learning (ML) models, specifically Naïve Bayes (NB) and Random Forest (RF) models, which were subsequently employed to construct a voting classifier. The performance of the models in diagnosing FFKC from normal corneas was compared to existing CVS parameters. The Normal group and the FFKC group each included 50 eyes. The FFKC group did not differ from healthy controls for age (p = 0.26) and gender (p = 0.36) at baseline, but they had significantly lower bIOP (p < 0.001) and thinner central cornea thickness (CCT) (p < 0.001). The results demonstrated that the proposed voting ensemble model yielded the highest performance with an AUC of 1.00, followed by the RF model with an AUC of 0.99. Radius and A2 Time emerged as the best-performing CVS parameters with AUC values of 0.948 and 0.938, respectively. Nonetheless, no existing Corvis ST parameters outperformed the ML models. A progressive enhancement in performance of the ML models was observed with incremental time points during the corneal deformation. This study represents the first instance where displacement and strain data following incremental DIC analysis of Corvis ST images were integrated with machine learning models to effectively differentiate FFKC corneas from normal ones, achieving superior accuracy compared to existing CVS parameters. Considering biomechanical responses of the inner cornea and their temporal pattern changes may significantly improve the early detection of keratoconus.