Slope Parameter Research Articles

Analyzing Three Types of Design Methods for 5G N41 Band Acoustic Wave Filters

This paper presents three design methods for acoustic wave (AW) filters: the direct conversion design method, the slope parameter method, and the band edge fitting method (BEFM). Since the conventional BVD model consists only of lumped elements and has accuracy only near the resonance frequency, an NM-BVD model capable of broadband modeling is proposed in this paper and used to design the filter. In the proposed BEFM, a systematically optimal filter method is used to design the AW filter, and each AW resonator is tuned to the filter prototype value to meet the desired specifications. Thus, the filter design time and the number of resonators can be efficiently improved, and the filter design time can be reduced compared with the direct conversion and slope parameter methods commonly used in filter design. To demonstrate the effectiveness of these design methods, the proposed methods were used to design and fabricate an N41 filter using scandium-doped aluminum nitride (ScAlN) resonators. The broadband capabilities of the filter were verified using BEFM. The design, fabrication, and measurement of a broadband filter that meets the requirements of the 5G N41 frequency band centered at 2.593 GHz with a bandwidth of 196 MHz have verified the filter fabricated using the proposed design method. The insertion loss is less than -3 dB in the target band and more than 30 dB out of band. In summary, the proposed BEFM provides an efficient and accurate method for designing AW filters.

Terrain slope parameter recognition for exoskeleton robot in urban multi-terrain environments

Lower limb augmentation exoskeletons (LLAE) have been applied in several domains to enforce human walking capability. As humans can adjust their joint moments and generate different amounts of mechanical energy while walking on different terrains, the LLAEs should provide adaptive augmented torques to the wearer in multi-terrain environments, which requires LLAEs to implement accurate terrain parameter recognition. However, the outputs of previous terrain parameter recognition algorithms are more redundant, and the algorithms have higher computational complexity and are susceptible to external interference. Therefore, to resolve the above issues, this paper proposed a neural network regression (NNR)-based algorithm for terrain slope parameter recognition. In particular, this paper defined for the first time a unified representation of terrain parameters: terrain slope (TS), a single parameter that can provide enough information for exoskeleton control. In addition, our proposed NNR model uses only basic human parameters and LLAE joint motion posture measured by an Inertial Measurement Unit (IMU) as inputs to predict the TS, which is computationally simpler and less susceptible to interference. The model was evaluated using K-fold cross-validation and the results showed that the model had an average error of only 2.09∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^\\circ $$\\end{document}. To further validate the effectiveness of the proposed algorithm, it was verified on a homemade LLAE and the experimental results showed that the proposed TS parameter recognition algorithm only produces an average error of 3.73∘\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$^\\circ $$\\end{document} in multi-terrain environments. The defined terrain parameters can meet the control requirements of LLAE in urban multi-terrain environments. The proposed TS parameter recognition algorithm could facilitate the optimization of the adaptive gait control of the exoskeleton system and improve user experience, energy efficiency, and overall comfort.

A cluster differences unfolding method for large datasets of preference ratings on an interval scale: Minimizing the mean squared centred residuals.

Clustering and spatial representation methods are often used in combination, to analyse preference ratings when a large number of individuals and/or object is involved. When analysed under an unfolding model, row-conditional linear transformations are usually most appropriate when the goal is to determine clusters of individuals with similar preferences. However, a significant problem with transformations that include both slope and intercept is the occurrence of degenerate solutions. In this paper, we propose a least squares unfolding method that performs clustering of individuals while simultaneously estimating the location of cluster centres and object locations in low-dimensional space. The method is based on minimising the mean squared centred residuals of the preference ratings with respect to the distances between cluster centres and object locations. At the same time, the distances are row-conditionally transformed with optimally estimated slope parameters. It is computationally efficient for large datasets, and does not suffer from the appearance of degenerate solutions. The performance of the method is analysed in an extensive Monte Carlo experiment. It is illustrated for a real data set and the results are compared with those obtained using a two-step clustering and unfolding procedure.

Isovector properties of finite nuclei: Constraints from neutron stars observations

The nuclear symmetry energy plays a crucial role in the structure of finite nuclei and the bulk properties of neutron stars. However, its values at high densities are highly uncertain, and the corresponding experimental data have large errors. One way to determine or at least estimate these high-density values is through neutron star observations. Recently, observations of gravitational waves from binary neutron star mergers have provided useful information on their radius and tidal deformability, which are directly related to the symmetry energy. This work attempts to use recent observations to constrain the structure of finite nuclei. Specifically, we parameterize the equation of state (EoS) describing asymmetric and symmetric nuclear matter using the parameter η = (K0L2)1/3, where K0 is the incompressibility and L is the slope parameter, The parameter η regulates the stiffness of the EoS, and we expect its values to affect both finite nuclei and neutron star properties, especially given the important role of isovector interactions. It is natural to expect that constraints on η for finite nuclei will also imply constraints on neutron star properties and vice versa. In light of the above, we propose a simple yet self-consistent method to simultaneously examine the effects of η on the properties of finite nuclei and neutron stars. We found constraints on these systems by combining recent experimental data (PREX-2) and observational data from the LIGO and Virgo detectors.

River Morphological Stability of Juana River based on Sediment Transport

Juana River is a river located in the north of Central Java. The downstream part of the Juana River flows into the North Java Sea. Problems with the Juana River include drought during the dry season and flooding during the rainy season. In addition, saline water intrusion makes it difficult for communities to access raw water. Flooding in the Juana River is caused by land use changes in the upper reaches of the river, the presence of a large number fishing boats anchored downstream, flooding in the lower reaches, and the relatively gentle slope of the Juana River. Currently, the Ministry of Public Works and Housing (Kementerian PUPR) is undertaking the construction of normalization, dam raising, and rubber dams in the Juana River. This study aims to analyze the stability of the Juana River. The analysis in this study uses the regime method to obtain the dimension of stability in the Juana River. The analysis in this study uses the regime method to obtain the dimension of stability in the Juana River. The results of the stability analysis in the Juana River found that the depth and slope parameters in the Juana River were unstable while the width parameters in the Juana River were stable. This research is useful to provide input to the Central and Regional Governments in planning and implementing river management in the Juana River.

Rheological behavior of granular materials under different relative densities

Granular materials typically exhibit complex behaviour especially during shearing under different states. The material behaviour transitions from fluid-like to unfluid-like primarily due to various fundamental mechanisms involved during the shearing process such as momentum transport, compaction, and jamming. Describing this transition is particularly relevant in a variety of natural phenomena like landslides, debris flow, mudflow, and liquefaction. The mechanism involved in the transitional response is predominantly governed by the initial packing of granular medium, shear rate and boundary stresses. In this study, the influence of relative densities (20% to 74%) on the rheological behaviour of sand is studied using a vane-shear apparatus. The variation of critical shear strength (during jamming), yield strength, apparent viscosity, and the maximum shear rate with relative density is determined from this experimental program. Further, the characterization of the flow behaviour of sand revealed the existence of pre-jamming and post-jamming regimes. The post-jamming response is evaluated by using slope parameters (m and ξ) which predicted an increasing trend with increase in relative density and overburden pressure.

Stability analysis of pit slopes in Zapadno-Ozerny quarry to ensure mine safety

The article discusses the design parameters of open pit slopes and the approach to calculating the stability of open pit slopes. The main deformations of slopes of open pits are considered. An assessment of the influence of the stress-strain state of quarry slopes on their stability is made. On the example of an open pit at the Zapadno-Ozernoye field, the assessment of stability under the actual stress-strain state of the site was performed. Recommendations to determine the new boundaries of the open pit, in which the section of the South Eastern slope of the open pit will be stable are given.

Influence of shear cut holes on the fatigue performance of hot-rolled 800 MPa automotive steel grades

Experimental fatigue tests were carried out for two t = 3 mm 800 MPa hot-rolled (HR) high-strength steel grades. These steels have good formability, and it is possible to use shear cutting to enable high productivity. The test campaign included unnotched base metal specimens to evaluate the fatigue performance of HR surface and notched specimens with shear-punched and electrical discharge-machined circular holes to evaluate the effect of cutting process and geometrical shape on the fatigue strength capacity. In this context, the properties of the shear-cut affected zone (SAZ) and resulting high tensile residual stresses, and their effects on the fatigue performance, were evaluated. The fatigue test results were first evaluated based on the nominal stress approach, followed by the applications of local approaches. The mean fatigue strength of the specimens with shear cut holes in the nominal stress system was 125 MPa (with a slope parameter of m = 3, stress range at the net cross section), which is at the comparable level to laser cut holes. Fractography analysis, conducted with scanning electron microscopy (SEM), showed local crack-like defects at the SAZ, and the characterization of local defect feature was utilized in the fatigue strength assessment using a multiparametric notch stress method applying effective stresses obtained by the critical distance approach.

Gender bias in university student mobility: a cohort analysis in Italy

PurposeThis paper aims to assess gender bias in Italian university student mobility controlling for the field of study. It uses data from the Italian National Student Archive (Anagrafe Nazionale degli Studenti – ANS) for the cohort of freshmen enrolled in the 2017 academic year. The macro-regional comparison unfolds across the following areas: North and Centre, Southern Italy and main Islands (Sicily and Sardinia).Design/methodology/approachThe analysis is firstly carried out at the national level, and secondly, it focusses on macro-geographical areas. University mobility choices are thus investigated from a gender perspective, conditioning upon other theoretically relevant characteristics collected for the prospective first-year university student population enrolled in 2017. The authors analyse data in a regression setting (logit models) within the multilevel framework, which considers students at level 1 and the field of study at level 2. Gender differences in the propensity to be a mover – conditional upon the choice of the field of study – were captured by introducing random intercepts to account for clustering of students in fields of study and random slopes to allow the gender effect to differ among them.FindingsFindings show that university student mobility in Italy leads evidence of gender bias. This has been detected using a multilevel random slope approach that allowed the authors to jointly estimate a slope parameter for gender within each field of study. Moreover, using a regression setting allowed the authors to control for heterogeneity in geographical, educational and socio-demographic characteristics across students. In line with previous empirical findings, the authors' data highlight the presence of a relevant mobility flow of university students from the South toward the North-Centre of Italy and lower mobility of female students compared to male students from the South and Islands.Originality/valueTo the best of the authors' knowledge, there are no studies in Italy, which investigate if families' investment in higher education in terms of selection of no-local universities are affected by gender bias and if geographical differences in this behaviour between macro-areas are in place. Thus, investigating students' choices in tertiary education allows the authors to shed light on the presence of gender bias in families' education strategies addressed to increase the endowment of students' assets for future job opportunities.

Actuarial aging rates in human cohorts

Aging rate is an important characteristic of human aging. Attempts to measure aging rates through the Gompertz slope parameter lead to a conclusion that actuarial aging rates were stable during the most of the 20th century, but recently demonstrate an increase over time in the majority of studied populations. These findings were made using cross-sectional mortality data rather than by the analysis of mortality of real birth cohorts. In this study we analyzed historical changes of actuarial aging rates in human cohorts. The Gompertz parameters were estimated in the age interval 50-80 years using data on one-year cohort age-specific death rates from the Human Mortality Database (HMD). Totally, data for 2,294 cohorts of men and women from 76 populations were analyzed. Changes of the Gompertz slope parameter in the studied cohorts revealed two distinct patterns for actuarial aging rate. In higher mortality Eastern European countries actuarial aging rates showed continuous decline from the 1910 to 1940 birth cohort. In lower mortality Western European countries, Australia, Canada, Japan, New Zealand, and USA actuarial aging rates declined from the 1910th to approximately 1930th cohort and then increased. Overall, in 50 out of 76 populations (68%) actuarial aging rate demonstrated decreasing pattern of change over time. Compensation effect of mortality (CEM) was tested for the first time in human cohorts and the cohort species-specific lifespan was estimated. CEM was confirmed using cohort data and human cohort species-specific lifespan estimates were similar to the estimates obtained for the cross-sectional data published earlier.

Soybean and grapevine rusts accelerate the defoliation rates of host plants

AbstractGrapevine leaf rust (GLR) and soybean rust (SBR), caused by Neophysopella tropicalis and Phakopsora pachyrhizi, respectively, may lead to early defoliation of the host, depending on disease severity level. The rate of defoliation is an important parameter in mechanistic models aimed at simulating yield loss, but such knowledge is not available for these rust diseases. This work aimed to (i) relate the temporal dynamics of GLR and SBR to defoliation; and (ii) estimate the relative rates of defoliation and model their relationship with rust severities. Grapevine and soybean plants were inoculated in the field at increasing concentrations of urediniospore suspensions of the respective causal agent. Control plots of the vineyard and the soybean field were protected with sequential fungicide sprays to evaluate natural defoliation. Rust severity (proportion of area affected) of each leaf or leaflet was evaluated every three or four days on 1323 grapevine leaves and 655 soybean leaflets, respectively. The relative rates of defoliation were estimated as the slope parameters of linear regression of the Napierian logarithm of the number of alive leaves or leaflets over time. Defoliation rates in grapevine and soybean incremented logarithmically with the increase of rust severity. Defoliation rates on symptomless grapevine and soybean leaves were 0.018 and 0.05 day−1, respectively, while they averaged 0.033 day−1 on diseased grapevine leaves (rust severity between 5% and 12%), and 0.12 day−1 on diseased soybean leaflets (rust severity between 25% and 60%). Thus, a quantitative relationship was established between rust severity and defoliation on grapevine and soybean.

Comparison of the agar contact method and the wet-dry double swabbing method for determining the total viable bacterial count on pig carcass surfaces

A practical and representative sampling method for microbiological examination of the slaughter process is useful for identifying abattoir-specific risk factors within the pig slaughter line. The aim of this study was to examine the suitability of an agar contact method (ACM), where the agar was homogenized before the microbiological processing, in comparison with the wet-dry double swabbing method (WDSM) for quantitative determination of total viable counts (TVC) on pig skin surfaces. In our experimental trial, pig skin pieces were artificially contaminated at 2 levels (3 log and 7 log cfu/ml) with a suspension of bacteria species commonly found on pig skin and cultivated in vitro. Within our field trial, pig carcasses were investigated at pre-chilling in an abattoir under standard processing conditions. For both sampling methods, TVC was determined, and statistical equivalence tests were calculated. Linear regression models showed the similarity of the sampling methods, with coefficient of determination (R2) > 90% and slope parameters of nearly 1 for both trials separately. Statistically significant equivalence between the 2 sampling methods was proven in both trials (with p < 0.0001 within an equivalence range of ± 0.5 log cfu/ml, respectively). The field trial revealed TVC on carcass surfaces sometimes at or below the lower detection limit for the ACM, while TVC from all carcasses were able to be determined by WDSM. Overall, low contamination levels were less reliably detectable by ACM than by WDSM. The ACM can be seen as an additional and suitable sampling procedure for pig skin and can contribute to the identification of abattoir specific risk factors for investigations of the hygienic status at process stages along the pig slaughter line.

Decline in small mammal species richness in coastal-central California, 1997-2013.

The richness and composition of a small mammal community inhabiting semiarid California oak woodland may be changing in response to climate change, but we know little about the causes or consequence of these changes. We applied a capture-mark-recapture model to 17 years (1997-2013) of live trapping data to estimate species-specificabundances. The big-eared woodrat was the most frequently captured species in the area, contributing 58% of total captures. All small mammal populations exhibited seasonal fluctuations, whereas those of the California mouse, brush mouse, and pinyon mouse declined during the study period. We also applied a multispecies dynamic occupancy model to our small mammal detection history data to estimate species richness, occupancy (), detection (p), local extinction (), and colonization () probabilities, and to discern factors affecting these parameters. We found that decreased from 0.369 ± 0.088 in 1997 to 0.248 ± 0.054 in 2013; was lower during the dry season (May-September) than the wet season (October-April) and was positively influenced by total seasonal rainfall (slope parameter, = 0.859 ± 0.371; 95% CI = 0.132-1.587). Mean mammalian species richness decreased from 11.943 ± 0.461 in 1997 to 7.185 ± 0.425 in 2013. With highly variable climatic patterns expected in the future, especially increased frequency and intensity of droughts,itis important to monitor small mammal communities inhabiting threatened California oak woodlands.

Development of quantitative precipitation estimation (QPE) relations for dual-polarization radars based on raindrop size distribution measurements in Metro Manila, Philippines

Quantitative precipitation estimates (QPE) can be further improved using estimation algorithms derived from localized raindrop size distribution (DSD) observations. In this study, DSD measurements from two disdrometer stations within Metro Manila during the Southwest monsoon (SWM) period were used to investigate the microphysical properties of rainfall and develop localized dual-polarimetric relations for different radar bands and rainfall types. Observations show that the DSD in Metro Manila is more distributed to larger diameters compared to Southern Luzon and neighboring countries and regions in the Western Pacific. This is reflected by the relatively higher mass-weighted mean diameter (Dm) and smaller shape (μ) and slope (Λ) parameters measured in the region. The average values of Dm and normalized intercept parameter (Nw) in convective rain samples also suggest that convective rains in Metro Manila are highly influenced by both continental and oceanic convective processes. Dual-polarimetric variables simulated using the T-matrix scattering method showed good agreement with disdrometer-derived reflectivity (ZH) values. The 0.5 dB and 0.3° km−1 thresholds for the differential reflectivity (ZDR) and specific differential phase (KDP) based on the blended algorithm of Cifelli (J Atmos Ocean Technol 28:352-364, 2011) and Thompson et al. (2017) are proven to be useful since the utility of the dual-polarimetric variables as rainfall estimators are shown to have dependencies on the radar band and rainfall type. Evaluation of the QPE products with respect to the C-band shows that R (KDP, ZDR) has the best performance among the dual-pol relations and statistically outperformed the conventional Marshall & Palmer relation [R(ZMP)]. The results show that dual-polarimetric variables such as ZDR and KDP can better represent the DSD properties compared to one-dimensional Z, hence providing more accurate QPE products than the conventional R(Z) relations.

Deciphering dark matter: A computational analysis of stellar velocity distributions

This study examines the dark matter density in the Galaxy by fitting recent data on stellar rotational velocities. We employ a model including the disk, the bulge, and the dark matter halo. The disks density is parameterized using a modified Bessel function, and the bulge is modeled using both the De Vaucouleurs and Exponential Sphere functions to better fit large and small radii respectively. The dark halo is modeled using the generalized Navarro-Frenk-White profile, with slope parameters for standard NFW and Moore profiles, and an Isothermal profile for comparison. The fit of the model parameters is established using local Dark Matter density and total Dark Matter mass as boundary conditions, with circular velocities derived via a Newtonian approach. The least chi-square ( 2 ) method is used for rotation curve fitting. Results demonstrate successful fitting of rotational velocity data and significant influence of the DH at large radial distances from the Galactic center.

Analysis of Flood-Prone Areas on Bekasi River Watershed

Das Kali Bekasi is an area that has physical conditions that support the occurrence of local and natural flood disasters during the rainy season. This research aims to: (1) Determine the distribution of floodprone areas in the Bekasi River Watershed, (2) Find out the most dominant factors of flood vulnerability that occur in the Bekasi River Watershed. The method used in the research is quantitative descriptive analysis. Analyze the data to determine the distribution area prone to flooding by weighting scoring and overlaying rainfall, land use, slope, soil type, and river density. To find out the dominant factors that cause flood vulnerability, a correlation test is used. The results of the research are (1) Flood vulnerability in the Bekasi river basin, based on the results of this research, is divided into 3 classes, namely the not vulnerable class with an area of 82.61 Km² (5.93%), the moderately vulnerable class with an area of 323.85 Km² (23, 26%), very vulnerable class with an area of 985.96 Km² (70.81%). (2) Correlation test to determine the dominant factor causing flooding in the Bekasi River basin and it is known that the dominant factor is the slope parameter, followed by the river density parameter, soil type parameter, land use parameter, and rainfall parameter with the lowest correlation value.

Deep residual shrinkage networks with adaptively convex global parametric rectifier linear units for fault diagnosis

In response to the challenge posed by traditional deep learning methods, which apply uniform nonlinear transformations to all vibration signals and thus struggle to address fault diagnosis under variable working conditions, a novel activation function called the convex global parametric rectifier linear unit (CGPReLU) is developed based on our prior research. Initially, an analysis of the numerical patterns governing the adaptive derivation process of GPReLU’s two slope parameters revealed the surprising observation that these convex parameter combinations invariably appear in pairs. This discovery serves as the primary motivation for the development of CGPReLU. Leveraging this convex regularity, we subsequently redesigned a lightweight convex sub-network for the adaptive derivation of the CGPReLU’s slope. Simultaneously, a deep residual shrinkage network with CGPReLU is constructed for fault diagnosis. Furthermore, we introduce an innovative evaluation metric designed to measure the collective influence of diagnostic accuracy and computational complexity after the process of model lightweight. Finally, it is experimentally demonstrated that the developed method can maintain a better diagnostic performance while greatly improving the diagnostic efficiency under variable operating conditions compared to our previous work.

Landslide Analysis of Western Lombok Island Using Weight of Evidence (WoE) Method

Landslides are widely distributed in all parts of Indonesia. West Nusa Tenggara Province is one of Indonesia's provinces with a quite high landslide distribution. This research was conducted in the western part of Lombok Island, including West Lombok Regency, Mataram City and North Lombok Regency, which has a moderate to high landslide risk class based on the 2021 Indonesian Disaster Risk Index (IRBI) data, so it is necessary to mitigate landslides by making a landslide vulnerability map. This research aims to determine the main factors of landslides in western Lombok Island, create a landslide vulnerability level map and analyse the distribution of landslide-prone areas in western Lombok Island using the weight of evidence (WoE) method. The research methods used are the literature study method (collecting information about land movement events in the research location and other information about the theories needed and used during the research) and the ArcGIS-based WoE method. This research shows that the slope parameter is the main factor of ground movement based on the analysis result of the WoE method. The landslide vulnerability level of the WoE method and the distribution of landslide occurrence points are high vulnerability level with an area of 473.45 km2, medium with an area of 198.88 km2, low with an area of 210.58 km2 and very low with an area of 911.73 km2.

Variation of graphene/titanium dioxide concentration as electrocatalyst for an oxygen reduction reaction in constructed wetland-microbial fuel cells

Constructed wetlands-microbial fuel cells (CW-MFC) are an innovative technology used for simultaneous bioelectricity generation and wastewater treatment. This is possible due to the installation of macrophytes in an electrode configuration, in which electroactive microorganisms use organic substrates as biofuel. One way to improve the electrochemical performance of CW-MFCs is through the impregnation of cathodic electrocatalysts. Therefore, in this study the bioelectricity production capacity of CW-MFCs was evaluated from the oxygen reduction reaction (ORR). For this study, the concentrations 0 (CW-MFC1), 0.5 (CW-MFC2), and 1 mg/cm2 (CW-MFC3) of graphene/titanium dioxide (G/TiO2) as electrocatalyst on the cathodes were evaluated. Using the Koutecky-Levich analysis, it was determined that the ORR transfer mechanism arises via a 4-electron pathway. The electrokinetic parameters of Tafel slope, charge transfer coefficient, and exchange current density determined the efficiency of the ORR, registering 92 mV/dec, 0.93 (α), and 2.30 x10-3 mA/cm2, respectively for CW-MFC3. The highest electrochemical performance was obtained at a concentration of 1 mg/cm2 (CW-MFC3) of G/TiO2, generating 144 mW/m2 of power density, 157 Ω of internal resistance, −150 mV of anodic potential, and 383 mV of cathodic potential. The surface modification carried out on the cathodes resulted in a catalytic increase in the ORR.

Insight into the crack characteristics and mechanisms of retrogressive slope failures: A large-scale model test

Cracks in the crown area are one of the important indicators in the instability of the landslide headscarp, potentially offering early warnings for landslide hazards. Due to the complex causes of crack formation and numerous influencing factors, the understanding of crack development characteristics is still insufficient. In this paper, a large-scale soil slope model test is carried out through a large tilting platform to simulate the whole process of retrogressive slope failures including the first-time failure and the enlargement of the failure. The characteristics of crack development, the relations between internal slope parameters (e.g., internal strain and earth pressure) and cracks, and the evolutionary mechanisms of retrogressive failures are focused. The model test is monitored by high-tech equipment, including optical fibres, pressure gauges, and cameras. The results show that crack developments are divided into four stages based on crack location, quantity, and size. Optical fibre monitoring shows that the areas of tension crack development fall within the negative strain area in the slope model. In addition, the failure mode of the retrogressive landslides can be summarized in three stages: a deformation stage with sparse local cracks, a destabilizing stage with main cracks, and a retrogressive failure stage with dense secondary cracks. This study offers preliminary insights into the relations between crack development and the mechanisms in soil multiple retrogressive failures, which can be beneficial for better identifying and interpreting landslides at sites through crack monitoring.