Curvature Index Research Articles

A New Retest-Stable Tortuosity Metric for Retinal Vessel Analyses.

Existing retinal vessel tortuosity metrics lack standardization and retest reliability, hindering their clinical utility. Our study addresses this gap by introducing a novel metric, coined as the "vascular curvature index" (VCI), to enhance accuracy and consistency in biomarkers associated with medical conditions. We assess VCI's performance in terms of retest reliability in healthy subjects to transform early detection and monitoring approaches for various diseases. We recruited 44 patients for a single-session study, capturing fundus images before and after a five-minute break. Using AutoMorph, we generated vessel segmentation maps and evaluated retest reliability using multiple tortuosity metrics. The VCI was introduced and statistically compared to existing metrics. We performed a paired one-sided t-test to test for significantly improved retest reliability of our newly proposed metric. We analyzed distribution histograms, Fisher-Pearson coefficient of skewness, and correlation matrices for further insights. VCI is the most retest-reliable metric, statistically surpassing other curvature metrics, except inverse spherical radius tortuosity. With a somewhat negatively distributed pattern (coefficient of skewness of -0.52), VCI exhibits the strongest correlation with the second most retest-reliable metric; inverse-radius-tortuosity (Pearson and Spearman correlation of 0.7 and 0.72, respectively). Its correlation with angle-tortuosity is lower (Pearson and Spearman correlation of 0.05 and 0.07, respectively). The VCI emerges as a highly retest-reliable metric with a relatively normal distribution in healthy patients. Further investigation is warranted to evaluate its clinical performance in real-world applications, potentially influencing proactive healthcare interventions and personalized treatment decision-making.

Geospatial Modelling of Flood Susceptibility of the Calabar City, Cross River State, Nigeria

Flooding remains a major environmental problem in many parts of the world including Nigeria, causing untold losses. This study modelled the flood susceptibility of Calabar Metropolis using frequency ratio and geographical information system (GIS). Direct field observation and key informant approaches were used to obtain 127 previous and current flood locations in the study area from which a database of historical flood occurrence was developed. Using the geostatistical analyst tool within a geographical information environment the flood locations were split into two parts in the ratio of 70:30 percent for the training and testing processes, respectively. Eight flood conditioning factors (elevation, slope, aspect, curvature topographic position index, topographic wetness index, land cover and normalized difference vegetation index) were extracted from SRTM-30m DEM and Landsat 8 data accordingly and used in the geospatial analysis of flood occurrence within the GIS. The frequency ratio model was then developed using the training dataset. The final product was the flood susceptibility map of the study area. The results revealed that 9.3 percent of the study area was considered to have very high flood susceptibility, 19.97 percent was classified as high flood susceptibility while 31.79 percent was under moderate risk area. About 39 percent of the study area was classified at least under low flood susceptibility. The order of contribution of the conditioning factors to the model were topographic position index (TPI), elevation, normalized difference vegetation index (NDVI), land cover, curvature, aspect, slope, and topographic wetness index (TWI). The validation of the model using the receiver operating characteristics (ROC) curve returned an AUC value of 74.81 percent. Hence, the result was acceptable for the prediction of flood locations in the study area. The findings would assist urban planners, environmental managers, risk reduction and management agencies, land developers, policy makers, and indeed the general public.

Effect of Age and Sex on Medullation Types and Fiber Characteristics in Huacaya Alpacas

Background: Fiber is a distinctive attribute of the alpaca due to its softness qualities; it contains less grease and has a finer cuticle compared to sheep's wool. Therefore, the types of medullation were estimated: non-medullated fibers (NoMed), fragmented medulla (FragMed), discontinuous medulla (DiscMed), continuous medulla (ContMed) and strongly medullated fibers (StrMed), considering the age and sex of Huacaya breed alpacas (Vicugna pacos) under extensive management conditions in high Andean pastures. Methods: Six grams of fiber samples were collected from the mid-side region (located above the third last rib, halfway between the midline of the belly and the midline of the back) of 240 Huacaya alpacas from the district of Macusani, province of Carabaya, Puno, during the year 2022. They were then processed in the Fiber Laboratory of the Faculty of Textile Engineering and Garments at the National University of Juliaca using the FIBER EC V4.0 and FIBER MED V1.0 equipment. Result: The results obtained show that the percentage of non-medullated fibers decreases as the animal’s age increases (1 year= 75.60%, 2 years=69.43%, 3 years=69.05% and greater than 4 years=66.25%) (P≤0.05). The percentage of medullated fibers in animals of 1 year was 24.40%; 2 years, 30.57%; 3 years, 30.95% and greater than 4 years, 33.59% (P≤0.05). The mean fiber diameter in 1-year-old alpacas is 17.32 mm, 2 years=19.49 mm, 3 years = 19.91 mm and 4 years=20.10 mm (P≤0.05). The comfort factor in 1-year-old animals is 99.47%, 2 years with 98.02%, 3-year-olds with 97.01% and those older than 4 years with 96.45% (P≤0.05). Regarding the curvature index, values of 55.86 °/mm were obtained for 1-year-old animals, 53.43 °/mm for 2-year-olds, 53.99 °/mm for 3-year-olds and 52.23°/mm for those older than 4 years (P≤0.05). In conclusion, Huacaya alpacas exhibit low values for the percentage of strongly medullated fibers due to the age and sex of the animal, demonstrating very good fleece uniformity.

Underlying Microstructure of the Lamina Cribrosa at the Site of Microvasculature Dropout.

To determine the microstructure of the lamina cribrosa (LC) associated with microvasculature dropout (MvD) of the deep optic nerve head (ONH) in primary open-angle glaucoma (POAG) and to identify factors related to the presence of MvD. POAG eyes that exhibited MvD in the LC (MvD-LC) or MvD in the peripapillary choroid (MvD-PC) underwent optical coherence tomography and optical coherence tomography angiography (OCTA) to evaluate the structure and microvasculature of the deep ONH, respectively. The presence of MvD-LC or MvD-PC was determined using en face OCTA images of the deep ONH. The sectoral LC thickness (LCT) and LC curvature index (LCCI) (at MvD-LC site, when applicable), the mean LCT and LCCI of the global ONH, and other clinical characteristics were measured and compared between eyes with and without MvD-LC. The study included 93 eyes with and 51 without MvD-LC. The presence of MvD-LC was associated with lower sectoral LCT (odds ratio [OR] = 0.96, P < 0.001) and mean LCT (OR = 0.97, P = 0.032), larger visual field pattern standard deviation (PSD; OR = 1.20, P = 0.038), and higher pretreatment intraocular pressure (IOP; OR = 1.22, P = 0.012). Fifteen percent of the eyes with MvD-LC (14/93) did not present MvD-PC. Those eyes had younger age (P = 0.043), thicker juxtapapillary choroid (P = 0.018), larger sectoral LCCI (P = 0.040), thicker retinal nerve fiber layer (P = 0.024), smaller PSD (P = 0.008), and higher pretreatment IOP (P = 0.006) than those with both MvD-LC and MvD-PC. MvD-LC was associated with a localized morphologic alteration of the LC, and eyes with MvD-LC tended to have a higher pretreatment IOP. The clinical implications of MvD-LC should differ from those of MvD-PC in eyes with POAG.

Smart decision support system for keratoconus severity staging using corneal curvature and thinnest pachymetry indices

BackgroundThis study proposes a decision support system created in collaboration with machine learning experts and ophthalmologists for detecting keratoconus (KC) severity. The system employs an ensemble machine model and minimal corneal measurements.MethodsA clinical dataset is initially obtained from Pentacam corneal tomography imaging devices, which undergoes pre-processing and addresses imbalanced sampling through the application of an oversampling technique for minority classes. Subsequently, a combination of statistical methods, visual analysis, and expert input is employed to identify Pentacam indices most correlated with severity class labels. These selected features are then utilized to develop and validate three distinct machine learning models. The model exhibiting the most effective classification performance is integrated into a real-world web-based application and deployed on a web application server. This deployment facilitates evaluation of the proposed system, incorporating new data and considering relevant human factors related to the user experience.ResultsThe performance of the developed system is experimentally evaluated, and the results revealed an overall accuracy of 98.62%, precision of 98.70%, recall of 98.62%, F1-score of 98.66%, and F2-score of 98.64%. The application's deployment also demonstrated precise and smooth end-to-end functionality.ConclusionThe developed decision support system establishes a robust basis for subsequent assessment by ophthalmologists before potential deployment as a screening tool for keratoconus severity detection in a clinical setting.

Effective Use of Catastrophe Multicriteria Decision Analysis in Delineating Groundwater Recharge Potential Zones

Multicriteria decision analysis based on Thom’s [1] Catastrophe Theory (CT) has been applied extensively in solving various social, physical and natural sciences problems. It has become a key tool for identifying the groundwater potentiality of an area with a Geographic Information System (GIS). This paper aimed to apply catastrophe theory effectively by utilizing the standardization formulae suggested by Li et al. [2] and the modified formulae provided by Hongwei Zhu [3]. Depending on the nature of a hydrogeological parameter, CT formulae were chosen to ensure that the least important features also get attention during standardization using Hongwei Zhu's formulae where applicable, which were not possible using Li’s formulae. The standardized values of the features of all the themes obtained using four formulae were sorted in ascending order to estimate the normalized values to ensure that no normalized value of a feature exceeds the others having very close but lower standardized values. The effective use of CT technique was employed in a GIS environment to delineate groundwater recharge potential zones of the middle-west part of Kushtia district, Bangladesh, by integrating influential recharge factors, such as land type, slope, drainage density, distance from surface water bodies, soil permeability, surface clay thickness, rainfall, topographic ruggedness index, topographic curvature index, topographic wetness index and topographic position index. The groundwater recharge potential zones were classified as very good (28.76%), good (32.17%), and moderately good (39.05%) for effective CT technique. But in case of the improper use of CT covering area were 17.24%, 54.05% and 28.71% respectively, and the respective most sensitive factors are rainfall and drainage density. Finally, recharge potential zones were validated using groundwater recharge data with a determinant coefficient of 0.92 and 0.84 for effective and improper use of CT technique respectively.

Alternate levels versus all levels mini-plate fixation in C3-6 cervical laminoplasty: a retrospective comparative study

ObjectiveThe purpose of this study is to compare radiological and clinical outcomes between alternate levels (C4 and C6) and all levels mini-plate fixation in C3-6 unilateral open-door laminoplasty.MethodsNinety-six patients who underwent C3-6 unilateral open-door laminoplasty with alternate levels mini-plate fixation (54 patients in group A) or all levels mini-plate fixation (42 patients in group B) between September 2014 and September 2019 were reviewed in this study. Radiologic and clinical outcomes were assessed. Clinical results included Visual Analogue Scale (VAS) of axial neck pain and Japanese Orthopedic Association (JOA) score. Radiographic results included cervical range of motion (ROM), cervical curvature index (CCI), and the spinal canal expansive parameters including open angle, anteroposterior diameter (APD), and Pavlov`s ratio.ResultsThere was no significant difference in VAS, JOA score, ROM, and CCI between two groups. There was no significant difference in canal expansion postoperatively between two groups. However, open angle, APD, and Pavlov`s ratio in group A decreased significantly during the follow-up. In group B, APD, Pavlov`s ratio, and open angle were maintained until the final follow-up. There was no hardware failure or lamina reclosure occurred in both groups during the follow-up. The mean cost of group B was higher than that of group A.ConclusionsDespite the differences in the maintenance of canal expansion, alternate levels mini-plate fixation can achieve similar clinical outcomes as all levels mini-plate fixation in C3-6 unilateral open-door laminoplasty. As evidenced in this study, we believe C3-6 laminoplasty with alternate levels (C4 and C6) mini-plate fixation is an economical, effective, and safe treatment method.

Assessment of OCT-Based Macular Curvature and Its Relationship with Macular Microvasculature in Children with Anisomyopia.

To evaluate the intraocular differences in optical coherence tomography (OCT)-based macular curvature index (MCI) among children with anisomyopia and to investigate the relationship between MCI and the macular microvasculature. Fifty-two schoolchildren with anisometropia > 2.00 D were enrolled and underwent comprehensive examinations including cycloplegic refraction, axial length (AL), and swept source OCT/OCT angiography. OCT-based MCIs were determined from horizontal and vertical B-scans by a customized curve fitting model in MATLAB R2022 at 1-mm-, 3-mm-, and 6-mm-diameter circles at fovea. Characteristics and topographic variation of MCI was analyzed, and the relationships with microvascularity and its associated factors were investigated. MCI achieved high reliability and repeatability. There were overall larger MCIs in the more myopic eyes than the less myopic eyes in 1-mm-, 3-mm-, and 6-mm-diameter circles at fovea (all p < 0.001). For the topographic variation, horizontal MCI was significantly greater than vertical MCI (all p < 0.001), and was the largest in 6-mm circle, followed by 3-mm and 1-mm circles. Stronger correlation of horizontal MCI with myopic severity than vertical MCI was found. Partial Pearson's correlation found MCI was negatively associated with deep capillary plexus (DCP) vessel density (p = 0.016). Eyes with a higher MCI in a 6-mm circle were more likely to have longer AL (p < 0.001), lower DCP vessel density (p = 0.037), and thinner choroidal thickness (ChT) (p = 0.045). Larger MCI was found in the more myopic eyes of children with anisomyopia and was significantly associated with smaller DCP density, suggesting that MCI was an important indicator of myopia-related retinal microvascularity change, and it could be a valuable metric for myopia assessment in children.

Comparing the morphology of optic nerve head and lamina cribrosa in full-term and preterm school-aged children.

To evaluate the morphology of lamina cribrosa (LC) in preterm school-aged children. A study of 120 eyes from 120 patients, including 42 full-term children (control group), 41 preterm children without retinopathy of prematurity (ROP), 16 children with ROP treated with intravitreal bevacizumab (IVB), and 21 children with ROP treated with laser. Five parameters of LC were measured by optical coherence tomography, including Bruch's membrane opening (BMO) diameter, minimum rim width (MRW), LC depth, prelaminar tissue (PLT) thickness, and LC curvature index (LCCI). The PLT thickness increased with age in full-term and preterm children (β = 30.1, P = 0.003 and β = 19.6, P < 0.001, respectively). LC depth and LCCI showed no differences between full-term and preterm children. Worse refractive errors in preterm children were associated with greater MRW and PLT thickness (β = -17.1, P = 0.001 and β = -5.7, P = 0.03, respectively). However, this relationship was not found in full-term children. Laser-treated children had greater MRW, PLT, temporal peripapillary retinal nerve fibre layer, and foveal thickness than full-term or other preterm children (all P < 0.05). Prematurity and ROP treatment may have an impact on the structural development of the LC. Refractive status plays a vital role in the LC structure of preterm children. This highlights the refractive errors of preterm children at school age that merit greater attention.

Unraveling the optimal strategies for asphalt pavement longevity through preventive maintenance: A case study in South Korea

This study provides a comprehensive evaluation of three pavement surface treatments—Re-Ascon, Micro-surfacing, and Fog-seal—aimed at enhancing the longevity of asphalt concrete pavement. Utilizing visual inspection, bearing capacity measurements, and linear regression modeling, this study rigorously assesses the effectiveness of these strategies in real-world road environments. Notably, Re-Ascon emerges as the least damaged method in visual inspection, offering crucial insights into initial pavement conditions. Visual inspections consistently underscore Re-Ascon's outstanding performance in mitigating pavement distress, particularly in addressing cracking. Quantitative analysis using the Surface Curvature Index (SCI) from Falling Weight Deflectometer (FWD) measurements highlights Re-Ascon's superior elastic modulus (E1) and resistance to deflection compared to alternatives. Re-Ascon's 20 % SCI reduction compared to Fog-seal highlights its superior deflection resistance, supported by logarithmic elastic modulus values. Correlation analysis confirms Re-Ascon's resilience, maintaining low SCI even under higher loads and adverse weather conditions. Geographical variations and method-specific influences are revealed through PCI analysis, emphasizing the vital impact of preventive maintenance. The identified PCI threshold of 60 % guides timely interventions for major maintenance, while service life analysis forecasts approximately 3.0, 2.5, and 1.5 years for Micro-surfacing, Re-Ascon, and Fog-seal methods, respectively. In conclusion, this research furnishes critical insights into preventive maintenance methods, advocating a holistic assessment through visual, structural, and predictive perspectives, and emphasizing the need for ongoing research to advance sustainable strategies.

Evaluation of lamina cribrosa curvature index in different types of glaucoma.

The aim of this study was to evaluate the lamina cribrosa curvature index in different types of glaucoma in comparison with clinical findings and conventional measurement methods. Patients older than 18years who were followed up in Glaucoma Unit of Department of Ophthalmology at Fırat University Faculty of Medicine, whose disease had been under control at least for 1year, who had at least three reliable visual fields, whose refractive error was between - 6 and + 5 diopter and who did not have any disease other than glaucoma that would affect the visual field, were included in the study. Clinical and demographic characteristics, visual field, optical coherence tomography and lamina cribrosa curvature index (LCCI) results were evaluated. The study patients were divided into six groups: early-stage primary open-angle glaucoma (POAG) as group 1 and intermediate-advanced stage POAG as group 2, pseudo-exfoliation glaucoma (PEXG) as group 3, normal tension glaucoma (NTG) as group 4, ocular hypertension patients whom subsequently developed POAG as group 5 and healthy control as group 6. A total of 189 eyes of 101 patients were included in our study. Forty-seven patients were male (46.5%) and 54 were female (53.5%). The mean age was 62.43 ± 1.49years. LCCI, mean deviation (MD), visual field index (VFI), pattern standard deviation (PSD) and retinal nerve fiber layer thickness (RNFL) values were analyzed in all groups and Pearson correlation analysis showed statistically significant correlation between PSD and RNFL measurements with LCCI values in all groups. MD value was correlated with LCCI in groups 2, 3 and 4, while VFI value was correlated with LCCI in all groups except group 5. When the groups were compared with each other according to the Post-Hoc Tamhane test, LCCI measurement showed statistically significant results in accordance with MD, VFI, PSD and RNFL values. The LCCI assessment is mostly consistent with conventional tests. In this study, in which different types of glaucoma and healthy subjects were examined simultaneously, LCCI shows promise as a detailed and reliable assessment method.

GIS-based multi-criteria decision making for delineation of potential groundwater recharge zones for sustainable resource management in the Eastern Mediterranean: a case study

In light of population growth and climate change, groundwater is one of the most important water resources globally. Groundwater is crucial for sustaining many vital sectors in Syria, including industrial and agricultural sectors. However, groundwater exploitation has significantly escalated to meet different water needs especially in the post-war period and the earthquake disaster. Therefore, the goal was this study delineation of the groundwater potential zones (GPZs) by integrating the analytic hierarchy process (AHP) method in a geographic information systems (GIS) within the AlAlqerdaha river basin in western Syria. In this study, ten criteria were used to map the spatial distribution of GPZs, including slope, geomorphology, drainage density, land use/land cover (LU/LC), lineament density, lithology, rainfall, soil, curvature and topographic wetness index (TWI). GPZs map was validated by using the location of 74 wells and the Receiver Operating Characteristic Curve (ROC). The findings suggest that the study area is divided into five GPZs: very low, 21.39 km2 (10.87%); low, 52.45 km2 (26.65%); moderate, 65.64 km2 (33.35%); high, 40.45 km2 (20.55%) and very high, 16.90 km2 (8.58%). High and very high zones mainly corresponded to the western regions of the study area. The conducted spatial modeling indicated that the AHP-based GPZs map showed a remarkably acceptable correlation with wells locations (AUC = 87.7%, n = 74), demonstrating the precision of the AHP–GIS as a rating method. The results of this study provide objective and constructive outputs that can help decision-makers to optimally manage groundwater resources in the post-war phase in Syria.

Google Earth Engine and Machine Learning for Flash Flood Exposure Mapping—Case Study: Tetouan, Morocco

Recently, the earth’s climate has changed considerably, leading to several hazards, including flash floods (FFs). This study aims to introduce an innovative approach to mapping and identifying FF exposure in the city of Tetouan, Morocco. To address this problem, the study uses different machine learning methods applied to remote sensing imagery within the Google Earth Engine (GEE) platform. To achieve this, the first phase of this study was to map land use and land cover (LULC) using Random Forest (RF), a Support Vector Machine (SVM), and Classification and Regression Trees (CART). By comparing the results of five composite methods (mode, maximum, minimum, mean, and median) based on Sentinel images, LULC was generated for each method. In the second phase, the precise LULC was used as a related factor to others (Stream Power Index (SPI), Topographic Position Index (TPI), Slope, Profile Curvature, Plan Curvature, Aspect, Elevation, and Topographic Wetness Index (TWI)). In addition to 2024 non-flood and flood points to predict and detect FF susceptibility, 70% of the dataset was used to train the model by comparing different algorithms (RF, SVM, Logistic Regression (LR), Multilayer Perceptron (MLP), and Naive Bayes (NB)); the rest of the dataset (30%) was used for evaluation. Model performance was evaluated by five-fold cross-validation to assess the model’s ability on new data using metrics such as precision, score, kappa index, recall, and the receiver operating characteristic (ROC) curve. In the third phase, the high FF susceptibility areas were analyzed for two-way validation with inundated areas generated from Sentinel-1 SAR imagery with coherent change detection (CDD). Finally, the validated inundation map was intersected with the LULC areas and population density for FF exposure and assessment. The initial results of this study in terms of LULC mapping showed that the most appropriate method in this research region is the use of an SVM trained on a mean composite. Similarly, the results of the FF susceptibility assessment showed that the RF algorithm performed best with an accuracy of 96%. In the final analysis, the FF exposure map showed that 2465 hectares were affected and 198,913 inhabitants were at risk. In conclusion, the proposed approach not only allows us to assess the impact of FF in this study area but also provides a versatile approach that can be applied in different regions around the world and can help decision-makers plan FF mitigation strategies.

Comparative study of dynamic parameters for damage identification of carbon fiber reinforced polymer tube

AbstractThe primary objective of the paper is the numerical and experimental investigation related to the damage recognition effects for CFRP tubes of four dynamic parameters. Four damage identification indexes consisting of natural frequency‐based index, Mode Shape‐based index (MS), Mode Shape Curvature‐based index (MSC), and Modal Flexibility Curvature‐based index (MFC) are established by analyzing the dynamic parameter data obtained before and after damage occurs. The performances of dynamic parameters are thoroughly discussed in the context of numerical simulations and experiment. The results indicate that the effect of natural frequency is not as significant as that of mode shape. MFC has the most notable effectiveness out of the four indexes. The simulation peak index pair is predicted to rise from 0.3 to 0.6 as the damage in the simulation model increases by 25% from 12.5%, indicating that MFC can feedback the damage degree. Moreover, the circumferential curvature index exhibits superior performance compared to the axial curvature index. To enhance the accuracy of the axial curvature index, it is proposed to increase the number of measuring sites along the tube's long direction.Highlights Damage identification indexes of four dynamic parameters are established. Discuss the identification ability of dynamic parameters by simulation and test. Two numerical models of CFRP tube with delamination damage are established. Impact and modal tests are executed to study the ability of four indexes.

Enhancing pavement performance prediction with traffic speed deflection data

ABSTRACT Pavement performance modelling is an essential part of pavement management. Past research has shown that a structural indicator can be included in pavement performance models to capture differences in performance between weak and strong pavements. Weak pavements are expected to deteriorate more rapidly than strong pavements, as consistently shown in past research. The work presented in this paper uses the Traffic Speed Deflectometer (TSD) to calculate multiple structural indexes and compares their ability to differentiate between poor and well performing pavements. Historical condition data from the US National Parks pavement network is used in this assessment. Two approaches for calculating the subgrade resilient modulus and two approaches for calculating the effective structural number from the TSD results are compared. The temperature corrected centre deflection, surface curvature index and ratio of effective to required structural number are all calculated from the TSD data. Performance models are developed for two condition indexes and the International Roughness Index (IRI). In all cases, the addition of the structural indexes improved the quality of predictions, and the IRI prediction showed the most improvement from including the indexes. Ultimately, it was shown that the TSD testing results can be used to inform the pavement management process.

Evaluation of Effect of Structural Condition on Surface Deterioration for Flexible Pavements Using Traffic Speed Deflection Device

With the introduction of traffic speed deflection devices (TSDD), collecting network-level surface deflection data becomes more efficient and convenient. State highway agencies (SHAs) are paying more attention to the incorporation of structural information into pavement management systems to support maintenance and rehabilitation (M&amp;R) analysis. For those SHAs who conduct M&amp;R analysis based solely on surface condition data, it is crucial to understand how the inclusion of structural condition data may affect the performance model, which structural indices may be well-suited for their needs, and where these indices may be placed in their current flowchart of M&amp;R analysis. To address these issues, in this study, the effects of eight structural indices obtained from TSDD on surface condition deterioration were investigated using TSDD data and surface condition data collected in Tennessee. The effects of structural indices on surface deterioration were evaluated using multiple regression, classification and regression tree analysis, and 1-year deterioration curve analysis. Surface curvature index, SCI_12, was found to be a significant factor influencing surface deteriorations. Structural indices representing condition of base layers and subgrade were less sensitive to the surface deterioration. To facilitate implementation, a flowchart of how to incorporate structural indices into M&amp;R analysis procedure was proposed.

Distribution and Characteristics of Springs in Two Neighboring Areas of Different Morphogenic Relief Type—Example of SW Medvednica Mountain (Central Croatia)

Hydrogeological characteristics of certain areas are the most important factor in the distribution and hydrological characteristics of springs. Nevertheless, geomorphological, i.e., morphometrical characteristics can also play an important role in their distribution and/or can serve as spatial indicators of spring positions. This study compares the distribution of springs, their hydrological and morphometric characteristics in two neighboring areas of different morphogenic relief types in the Medvednica mountain (central Croatia), as well as their relationship with known faults. Results show that most of the springs in both areas researched have discharges between 0.01 L/s and 0.1 L/s. Nevertheless, in the fluviokarst area, there is a higher share of springs with discharges higher than 0.1 L/s. Morphometric characteristics of springs studied (altitude, slope, relative relief, curvature and Topographic Wetness Index (TWI)) have shown certain differences that are connected to the hydrogeological characteristics of the area. Results indicate that spring locations in the fluviodenudation relief area are more connected to the geomorphological processes caused by surface and shallow underground water runoff, while in the fluviokarst relief, that connection is less pronounced. Research has also shown that spring distribution in both areas is connected to faults, with somewhat higher concurrence in the fluviodenudation relief.

Dynamic Digital Radiography Pulmonary Function Testing: A Machine Learning Lung Study Alternative

BackgroundCommon diagnostic tests for pulmonary disorders include chest radiography and pulmonary function tests (PFTs). Although essential, these tests only offer a static assessment. Chest dynamic digital radiography (DDR) integrates lung and diaphragm motion in one study with limited radiation exposure. DDR is relatively easy to obtain, but barriers to its clinical adoption include time consuming manual analysis and unclear correlation with PFTs. Research questionsCan a machine learning pipeline automate DDR analysis? What is the strength of the relationship between PFT-measures and automated DDR-based lung area measurements? Study design and MethodsPFT and DDR studies were obtained in fifty-five participants. We developed an analysis pipeline utilizing convolutional neural networks (CNN) capable of quantifying lung areas in DDR images to generate DDR-based PFTs (dPFTs). PFT and dPFT measures were correlated in patients with normal, obstructive and restrictive lung physiology. ResultsWe observed statistically significant (p values < 1x10-6), strong correlations between dPFT areas and PFT volumes including TLC (r=0.764), FEV1 (r=0.591), VC (r=0.763) and FRC (r=0.756). Automated DDR and lung shape tracking revealed differences between normal, restrictive and obstructive physiology using diaphragm curvature indices and strain-analysis measurements. Linear regressions allowed for derivation of PFT values from dPFT measurements. InterpretationStatistically significant correlations found between dPFTs and PFTs suggest that dPFTs can act as a surrogate to PFTs when these are not available or unable to be performed. This study contributes to the potential integration of DDR as a reliable alternative to PFTs.

Automated analysis of retinal microcirculation in type 1 diabetes mellitus

BACKGROUND: The paper is dedicated to the assessment of the retinal microvasculature in patients with type 1 diabetes mellitus (DM) with various features of the clinical course and different stages of diabetic retinopathy (DR). Automatic analysis of optical coherence tomogram angiograms (OCT-A) was carried out with specially developed software that provides the ability to estimate quantitative vascular parameters.AIM: The purpose of the study was to assess diagnostic accuracy of clinical parameters and imaging biomarkers in type 1 diabetes using a new algorithm for OCT-A analysis.MATERIALS AND METHODS: The study involved 186 people (365 eyes) with type 1 diabetes. The analysis of the OCT-A parameters was performed with a specially developed software. The range of studied parameters included: foveal avascular zone (FAZ), vessel area density (VAD), skeletonized vessel density (VSD), vessel diameter index (VDI), vascular curvature index (VCI) at the level of superficial (SCP) and deep (DCP) retinal capillary plexuses in the macular region. A correlation between the involvement of OCT-A biomarkers and age, degree of DM, increased glycated hemoglobin (HbA1c) level, stage of DR, and maximally corrected visual acuity (BCVA) was analysed.RESULTS: A significant dependence of all quantitative OCT-A parameters on the age of and duration of diabetes (p&lt;0.05) was revealed. An increase in FAZ SCP (K=0.788, p=0) and DCP (K=0.764, p=0.03); decrease in VAD SCP (K=-0.476, p=0) and DCP (K=-0.485, p=0); VSD SCP (K=0.692, p=0) and DCP (K=0.713, p=0); an increase in VDI SCP (K=0.698, p=0) and DCP (K=787, p&lt;0.01), as well as an increase in the VCI SCP (K=0.735, p=0) and DCP (K=0.694, p p=0). An inverse relationship was found between HbA1c level and VAD SCP (K=-0.636, p=0) and DCP (K=-0.619, p=0.05) were identified as well as a direct relationship with VDI DCP (K=0.717, p&lt;0.05). The influence of the HbA1c level on other parameters was not confirmed (p&gt;0.05). The presence of correlation between BCVA and FAZ DCP (K=-0.728, p=0), as well as VSD DCP (K=-0.754, p=0) was proved.CONCLUSION: As a result of a comprehensive analysis of clinical data and imaging biomarkers, a number of patterns that have diagnostic value in diabetic retinopathy were identified.

Structural damage localisation based on generalised flexibility change rate curvature and data fusion technology

ABSTRACT Damage localisation is the key to structural damage identification. Based on the study of damage index using the flexibility method, this paper presents a damage localisation index using the generalised flexibility matrix before and after structural damage. To enhance the accuracy of structural damage localisation, it is necessary to improve the sensitivity of damage index. Therefore, this paper puts forward a generalised flexibility change rate curvature index with the objective of improving the accuracy in localising structural damage. The curvature index is defined as the second-order difference of the generalised flexibility change before and after damage. Consequently, the curvature-based index usually is more sensitive to structural damages. To enhance the accuracy and efficiency of multiple damage localisation, the generalised flexibility change rate curvature index is combined with data fusion technology based on Dempster-Shafer’s theory. Numerical simulations and experimental studies have validated the capability and efficiency of the proposed method for damage localisation also in the case of multiple damages, noise impact, and limited modal orders.