Real-time monitoring unsafe behaviors of portable multi-position ladder worker using deep learning based on vision data.

INTRODUCTION: Fatal fall from height accidents, especially on construction sites, persist, underscoring the importance of monitoring and managing worker behaviors to enhance safety. Deep learning showed the possibility of substituting the manual work of safety managers. However, applying detection results to determine compliance with safety regulations has limitations. METHOD: This study estimated the actual working height depending on the height of the object detection bounding box by specifying the consistent hinge part as a target marker based on ladder manufacturing regulations. Furthermore, an attempt was made to improve the separation between workers, coworkers, and persons unconnected to ladder activities by applying an optimized loss function alongside an attention mechanism. RESULTS: The experimental results showed that an average precision increased from 87.60% to 90.44%. The performance of the monitoring unsafe behavior of ladder worker following the Korea Occupational Safety and Health Agency (KOSHA) guide was evaluated by 91.40 F1-Score, which accumulated sorted according to the working height. CONCLUSIONS: Experimental results show the feasibility of the real-time automate safety monitoring in ladder work. PRACTICAL APPLICATIONS: By linking the estimated working height and deep learning multi-detection results to established safety regulations, the proposed method shows the potential to automatically monitoring unsafe behaviors in construction site.

Acidity in rainwater and airborne suspended particles in the southwestern coast of the East Sea (Sea of Japan): Their potential impact on seawater total alkalinity.

Our understanding of the impact of atmospheric acid deposition on marine carbonate system remains limited, largely due to a lack of data regarding acidity present in atmospheric particles and precipitation. Previous research has relied on the electroneutrality-based ion balance method for indirect estimation of atmospheric acidity. In this study, atmospheric samples collected at a coastal site of South Korea were mixed with seawater to measure the change in seawater total alkalinity (ΔTAAPL) associated with atmospheric proton loading. For the precipitation samples, the measured ΔTAAPL and electroneutrality-based estimates showed a significant correlation. However, we did not observe similar results for the atmospheric particle samples. Furthermore, the decrease in oceanic TA due to ΔTAAPL was substantially smaller than that in dissolved inorganic carbon from concurrent nitrogen fertilization. Consequently, the adverse impact of acid deposition on ocean acidification or air-sea exchange of CO2 appears to be insignificant on a short-term scale.

A quantitative analysis of multi-decadal shoreline changes along the East Coast of South Korea.

South Korea's east coast is facing several issues related to coastal erosion because of sea-level rise, typhoon-induced storm surges, and various coastal development projects. In recent decades, high storm waves have frequently appeared on the east coast, causing casualty, beach erosion, and coastal infrastructure damage, drawing significant public attention. Thus, we analyzed the multi-decadal shoreline changes to understand the coastal dynamics and the forces responsible for the spatio-temporal changes along the 173 km coastline. The shorelines covering 38 years between 1984 and 2022 were derived from Landsat images and the change statistics, i.e., linear regression rate (LRR), endpoint rate (EPR), weighted linear regression (WLR), and net shoreline movement (NSM), were calculated at a 100 m alongshore intervals using Digital Shoreline Analysis System (DSAS), revealed several distinct behaviors of shoreline position. The long-period (1984-2022) assessment showed an average shoreline change rate (LRR) of 0.17 m/year with an estimated mean erosion and deposition rate of -0.57 and 2.07 m/year, respectively. The long-term surface gain and loss of the backshore region exhibited that the net surface gain of the east coast is 421.13 ha, and the net loss is 181.82 ha. The assessment of decadal shoreline changes showed a cyclic pattern of erosion (from 1984-1990 and 1999-2010) and accretion (from 1990-1999 and 2010-2022). Furthermore, a secondary level of investigation was conducted to address a wider variety of coastal behaviors by segmenting shoreline change rates based on coast types and average slopes along coastlines. It was observed that the frequent coastal deformation is associated with a flatter beach compared to a steep one. This study found that the artificial structures constructed along the east coast have not completely solved or stopped the erosion issues but shifted it from one location to another. The analysis of local and regional shoreline changes had shown that typhoon-induced storm surges, high storm waves, and anthropogenic activities like encroachment and the development of artificial coastal structures were the primary drivers of coastline changes along the east coast. Finally, we proposed a decision-making classification scheme that can be used to determine the mechanism of decision for protective and preventive measures against further coastal deterioration.

All-in-One Process for Mass Production of Membrane-Type Carbon Aerogel Electrodes for Solid-State Rechargeable Zinc-Air Batteries.

This study presents a mass-production process for conductive carbon membrane-type sponge electrodes derived from recyclable cellulose biowaste. It includes an all-in-one hydrogel fabrication process for mass production, which significantly shortens the complex and expensive process for the conventional process of catalytic electrodes based on conductive supporting substrates such as the gas diffusion layer (GDL). The presence of pre-adsorbed melamine powder in the all-in-one hydrogel induces internal diffusion of the gaseous reactant for the uniform growth of carbon nanotubes (CNTs) onto the sponge-like porous carbon aerogel with a relatively thick and tortuous pore structure, thereby providing the electrochemical properties and mechanical strength simultaneously required for the air electrodes of rechargeable and quasi solid-state zinc-air batteries.

Three-Dimensional Engine-Based Geometric Model Optimization Algorithm for BIM Visualization with Augmented Reality.

Building information modeling (BIM), a common technology contributing to information processing, is extensively applied in construction fields. BIM integration with augmented reality (AR) is flourishing in the construction industry, as it provides an effective solution for the lifecycle of a project. However, when applying BIM to AR data transfer, large and complicated models require large storage spaces, increase the model transfer time and data processing workload during rendering, and reduce visualization efficiency when using AR devices. The geometric optimization of the model using mesh reconstruction is a potential solution that can reduce the required storage while maintaining the shape of the components. In this study, a 3D engine-based mesh reconstruction algorithm that can pre-process BIM shape data and implement an AR-based full-size model is proposed, which is likely to increase the efficiency of decision making and project processing for construction management. As shown in the experimental validation, the proposed algorithm significantly reduces the number of vertices, triangles, and storage for geometric models while maintaining the overall shape. Moreover, the model elements and components of the optimized model have the same visual quality as the original model; thus, a high performance can be expected for BIM visualization in AR devices.

Supercritical CO2-Induced Evolution of Alkali-Activated Slag Cements.

The phase changes in alkali-activated slag samples when exposed to supercritical carbonation were evaluated. Ground granulated blast furnace slag was activated with five different activators. The NaOH, Na2SiO3, CaO, Na2SO4, and MgO were used as activators. C-S-H is identified as the main reaction product in all samples along with other minor reaction products. The X-ray diffractograms showed the complete decalcification of C-S-H and the formation of CaCO3 polymorphs such as calcite, aragonite, and vaterite. The thermal decomposition of carbonated samples indicates a broader range of CO2 decomposition. Formation of highly cross-linked aluminosilicate gel and a reduction in unreacted slag content upon carbonation is observed through 29Si and 27Al NMR spectroscopy. The observations indicate complete decalcification of C-S-H with formation of highly cross-linked aluminosilicates upon sCO2 carbonation. A 20-30% CO2 consumption per reacted slag under supercritical conditions is observed.

Verification of Tensile Force Estimation Method for Temporary Steel Rods of FCM Bridges Based on Area of Magnetic Hysteresis Curve Using Embedded Elasto-Magnetic Sensor.

The free cantilever method (FCM) is a bridge construction method in which the left and right segments are joined in sequence from a pier without using a bottom strut. To support the imbalance of the left and right moments during construction, temporary steel rods, upon which tensile force is applied that cannot be managed after construction, are embedded in the pier. If there is an excessive loss of tensile force applied to the steel rods, the segments can collapse owing to the unbalanced moment, which may cause personal and property damage. Therefore, it is essential to monitor the tensile force in the temporary steel rods to prevent such accidents. In this study, a tensile force estimation method for the temporary steel rods of an FCM bridge using embedded Elasto-Magnetic (EM) sensors was proposed. After the tensile force was applied to the steel rods, the change in tensile force was monitored according to the changing area of a magnetic hysteresis curve, as measured by the embedded EM sensors. To verify the field applicability of the proposed method, the EM sensors were installed in an FCM bridge pier under construction. The three sensors were installed in conjunction with a sheath tube, and the magnetic hysteresis curve was measured over nine months. Temperature data from the measurement period were used to compensate for the error due to daily temperature fluctuations. The estimated tensile force was consistent with an error range of ±4% when compared with the reference value measured by the load cell. Based on the results of this experiment, the applicability of the proposed method was demonstrated.

Improving the Ability of a Laser Ultrasonic Wave-Based Detection of Damage on the Curved Surface of a Pipe Using a Deep Learning Technique.

With the advent of the Fourth Industrial Revolution, the economic, social, and technological demands for pipe maintenance are increasing due to the aging of the infrastructure caused by the increase in industrial development and the expansion of cities. Owing to this, an automatic pipe damage detection system was built using a laser-scanned pipe's ultrasonic wave propagation imaging (UWPI) data and conventional neural network (CNN)-based object detection algorithms. The algorithm used in this study was EfficientDet-d0, a CNN-based object detection algorithm which uses the transfer learning method. As a result, the mean average precision (mAP) was measured to be 0.39. The result found was higher than COCO EfficientDet-d0 mAP, which is expected to enable the efficient maintenance of piping used in construction and many industries.

Atmospheric deposition of inorganic nutrients to the Western North Pacific Ocean.

We evaluated the potential impacts of atmospheric deposition on marine productivity and inorganic carbon chemistry in the northwestern Pacific Ocean (8-39°N, 125-157°E). The nutrient concentration in atmospheric total suspended particles decreased exponentially with increasing distance from the closest land-mass (Asia), clearly revealing anthropogenic and terrestrial contributions. The predicted mean depositional fluxes of inorganic nitrogen were approximately 34 and 15 µmol m-2 d-1 to the west and east of 140°E, respectively, which were at least two orders of magnitude greater than the inorganic phosphorus flux. On average, atmospheric particulate deposition would support 3-4% of the net primary production along the surveyed tracks, which is equivalent to ~2% of the dissolved carbon increment caused by the penetration of anthropogenic CO2. Our observations generally fell within the ranges observed over the past 18 years, despite an increasing trend of atmospheric pollution in the source regions during the same period, which implies high temporal and spatial variabilities of atmospheric nutrient concentration in the study area. Continued atmospheric anthropogenic nitrogen deposition may alter the relative abundances of nitrogen and phosphorus.

Fuzzy Logic-Based and Nondestructive Concrete Strength Evaluation Using Modified Carbon Nanotubes as a Hybrid PZT-CNT Sensor.

Concrete strength and factors affecting its development during early concrete curing are important research topics. Avoiding uncertain incidents during construction and in service life of structures requires an appropriate monitoring system. Therefore, numerous techniques are used to monitor the health of a structure. This paper presents a nondestructive testing technique for monitoring the strength development of concrete at early curing ages. Dispersed carbon nanotubes (CNTs) were used with cementitious materials and piezoelectric (PZT) material, a PZT ceramic, owing to their properties of intra electromechanical effects and sensitivity to measure the electromechanical impedance (EMI) signatures and relevant properties related to concrete strength, such as the elastic modulus, displacement, acceleration, strength, and loading effects. Concrete compressive strength, hydration temperature, mixture ratio, and variation in data obtained from the impedance signatures using fuzzy logic were utilized in the comparative result prediction method for concrete strength. These results were calculated using a fuzzy logic-based model considering the maturity method, universal testing machine (UTM) data, and analyzed EMI data. In the study, for data acquisition, a hybrid PZT-CNT sensor and a temperature sensor (Smart Rock) were embedded in the concrete to obtain the hydration temperature history to utilize the concrete maturity method and provide data on the EMI signatures. The dynamic changes in the medium caused during the phase in the concrete strengthening process were analyzed to predict the strength development process of concrete at early curing ages. Because different parameters are considered while calculating the concrete strength, which is related to its mechanical properties, the proposed novel method considers that changes in the boundary condition occurring in the concrete paste modify the resonant frequency response of the structure. Thus, relating and analyzing this feature can help predict the concrete strength. A comprehensive comparison of the results calculated using the proposed module, maturity method, and cylindrical specimens tested using the UTM proved that it is a cost-effective and fast technique to estimate concrete strength to ensure a safe construction of reinforced cement concrete infrastructures.

LiDAR-Based Bridge Displacement Estimation Using 3D Spatial Optimization.

As civil engineering structures become larger, non-contact inspection technology is required to measure the overall shape and size of structures and evaluate safety. Structures are easily exposed to the external environment and may not be able to perform their original functions depending on the continuous load for a long time. Therefore, in this study, we propose a method for estimating the vertical displacement of structures using light detection and ranging, which enables non-contact measurement. The point cloud acquired through laser scanning was rearranged into a three-dimensional space, and internal nodes were created by continuously dividing the space. The generated node has its own location information, and the vertical displacement value was calculated by searching for the node where the deformation occurred. The performance of the proposed displacement estimation technique was verified through static loading experiments, and the octree space partitioning method is expected to be applied and utilized in structural health monitoring.

Artificial Intelligence-Based Bolt Loosening Diagnosis Using Deep Learning Algorithms for Laser Ultrasonic Wave Propagation Data.

The application of deep learning (DL) algorithms to non-destructive evaluation (NDE) is now becoming one of the most attractive topics in this field. As a contribution to such research, this study aims to investigate the application of DL algorithms for detecting and estimating the looseness in bolted joints using a laser ultrasonic technique. This research was conducted based on a hypothesis regarding the relationship between the true contact area of the bolt head-plate and the guided wave energy lost while the ultrasonic waves pass through it. First, a Q-switched Nd:YAG pulsed laser and an acoustic emission sensor were used as exciting and sensing ultrasonic signals, respectively. Then, a 3D full-field ultrasonic data set was created using an ultrasonic wave propagation imaging (UWPI) process, after which several signal processing techniques were applied to generate the processed data. By using a deep convolutional neural network (DCNN) with a VGG-like architecture based regression model, the estimated error was calculated to compare the performance of a DCNN on different processed data set. The proposed approach was also compared with a K-nearest neighbor, support vector regression, and deep artificial neural network for regression to demonstrate its robustness. Consequently, it was found that the proposed approach shows potential for the incorporation of laser-generated ultrasound and DL algorithms. In addition, the signal processing technique has been shown to have an important impact on the DL performance for automatic looseness estimation.

Beam Deflection Monitoring Based on a Genetic Algorithm Using Lidar Data.

The Light Detection And Ranging (LiDAR) system has become a prominent tool in structural health monitoring. Among such systems, Terrestrial Laser Scanning (TLS) is a potential technology for the acquisition of three-dimensional (3D) information to assess structural health conditions. This paper enhances the application of TLS to damage detection and shape change analysis for structural element specimens. Specifically, estimating the deflection of a structural element with the aid of a Lidar system is introduced in this study. The proposed approach was validated by an indoor experiment by inducing artificial deflection on a simply supported beam. A robust genetic algorithm method is utilized to enhance the accuracy level of measuring deflection using lidar data. The proposed research primarily covers robust optimization of a genetic algorithm control parameter using the Taguchi experiment design. Once the acquired data is defined in terms of plane, which has minimum error, using a genetic algorithm and the deflection of the specimen can be extracted from the shape change analysis.

Determination of Plate Corrosion Dimension Using Nd:YAG Pulsed Laser-generated Wavefield and Experimental Dispersion Curves.

Corrosion detection using a pulsed laser scanning system can be performed via ultrasonic wave propagation imaging. This method outputs illustrations of the wave field within the host structure; thus, it can depict wave-corrosion area interactions. Additionally, post-processing can be performed to enhance the visualization of corroded areas. The wavefield energy computed using RMS (Root Mean Square) is a validated post-processing tool capable of displaying the location and area of corrosion-damaged regions. Nonetheless, to characterize corrosion, it is necessary to determine its depth. The measurement of depth in conjunction with that of the corroded area via the RMS distribution enables the determination of all dimensions of corrosion damage. Thereafter, the flaw severity can be evaluated. This study employed a wavefield within a plate on which corrosion was developed artificially to generate frequency-wavenumber dispersion curves. The curves were compared with their counterparts from a corrosion-free plate. Alternatively, they could be compared with dispersion curves drawn using the depth and material properties of a pristine plate via a computer program. Frequency-wavenumber pairs were extracted from the dispersion curves produced using the portion of the wavefield within the corroded area. These were inserted into the Rayleigh-Lamb equation, from which depths were calculated and averaged.

Comparison of Depth Camera and Terrestrial Laser Scanner in Monitoring Structural Deflections.

Modeling a structure in the virtual world using three-dimensional (3D) information enhances our understanding, while also aiding in the visualization, of how a structure reacts to any disturbance. Generally, 3D point clouds are used for determining structural behavioral changes. Light detection and ranging (LiDAR) is one of the crucial ways by which a 3D point cloud dataset can be generated. Additionally, 3D cameras are commonly used to develop a point cloud containing many points on the external surface of an object around it. The main objective of this study was to compare the performance of optical sensors, namely a depth camera (DC) and terrestrial laser scanner (TLS) in estimating structural deflection. We also utilized bilateral filtering techniques, which are commonly used in image processing, on the point cloud data for enhancing their accuracy and increasing the application prospects of these sensors in structure health monitoring. The results from these sensors were validated by comparing them with the outputs from a linear variable differential transformer sensor, which was mounted on the beam during an indoor experiment. The results showed that the datasets obtained from both the sensors were acceptable for nominal deflections of 3 mm and above because the error range was less than ±10%. However, the result obtained from the TLS were better than those obtained from the DC.

MFL-Based Local Damage Diagnosis and SVM-Based Damage Type Classification for Wire Rope NDE.

Wire ropes used in various applications such as elevators and cranes to safely carry heavy weights are vulnerable to breakage or cross-sectional loss caused by the external environment. Such damage can pose a serious risk to the safety of the entire structure because damage under tensile force rapidly expands due to concentration of stress. In this study, the magnetic flux leakage (MFL) method was applied to diagnose cuts, corrosion, and compression damage in wire ropes. Magnetic flux signals were measured by scanning damaged wire rope specimens using a multi-channel sensor head and a compact data acquisition system. A series of signal-processing procedures, including the Hilbert transform-based enveloping process, was applied to reduce noise and improve the resolution of signals. The possibility of diagnosing several types of damage was verified using enveloped magnetic flux signals. The characteristics of the MFL signals according to each damage type were then analyzed by comparing the extracted damage indices for each damage type. For automated damage type classification, a support vector machine (SVM)-based classifier was trained using the extracted damage indices. Finally, damage types were automatically classified as cutting and other damages using the trained SVM classifier.

Comparative Analysis and Strength Estimation of Fresh Concrete Based on Ultrasonic Wave Propagation and Maturity Using Smart Temperature and PZT Sensors.

Recently, the early-age strength prediction for RC (reinforced concrete) structures has been an important topic in the construction industry, relating to project-time reduction and structural safety. To address this, numerous destructive and NDTs (non-destructive tests) are applied to monitor the early-age strength development of concrete. This study elaborates on the NDT techniques of ultrasonic wave propagation and concrete maturity for the estimation of compressive strength development. The results of these comparative estimation approaches comprise the concrete maturity method, penetration resistance test, and an ultrasonic wave analysis. There is variation of the phase transition in the concrete paste with the changing of boundary limitations of the material in accordance with curing time, so with the formation of phase-transition changes, changes in the velocities of ultrasonic waves occur. As the process of hydration takes place, the maturity method produces a maturity index using the time-feature reflection on the strength-development process of the concrete. Embedded smart temperature sensors (SmartRock) and PZT (piezoelectric) sensors were used for the data acquisition of hydration temperature history and wave propagation. This study suggests a novel relationship between wave propagation, penetration tests, and hydration temperature, and creates a method that relies on the responses of resonant frequency changes with the change of boundary conditions caused by the strength-gain of the concrete specimen. Calculating the changes of these features provides a pattern for estimating concrete strength. The results for the specimens were validated by comparing the strength results with the penetration resistance test by a universal testing machine (UTM). An algorithm used to relate the concrete maturity and ultrasonic wave propagation to the concrete compressive strength. This study leads to a method of acquiring data for forecasting in-situ early-age strength of concrete, used for secure construction of concrete structures, that is fast, cost effective, and comprehensive for SHM (structural health monitoring).

Atmospheric deposition of anthropogenic inorganic nitrogen in airborne particles and precipitation in the East Sea in the northwestern Pacific Ocean.

The atmospheric deposition of anthropogenic nitrogen is an increasingly important new source of nitrogen to the ocean. Coastal areas east of the Korean Peninsula are suitable for the investigation of the effects of atmospheric anthropogenic nitrogen on the ocean nutrient system because of the low riverine discharge rates and the prevailing influence of the East Asian outflow. Thus, we measured the concentrations of nitrate (NO3-) and ammonium (NH4+) in airborne particles and in precipitation from March 2014 to February 2016 at a coastal site (37.08°N, 129.41°E) on the east coast of Korea. The dry deposition of NO3- (27-30 mmol N m-2 yr-1) was far greater than that of NH4+ (6-8 mmol N m-2 yr-1). The greater rate of dry NO3- deposition was associated with air masses traveling over northeastern China and central Korea. In contrast, the rates of wet deposition of NO3- (17-24 mmol N m-2 yr-1) and NH4+ (14-27 mmol N m-2 yr-1) were comparable and were probably associated with in-cloud scavenging of these ions. The results indicate that the total deposition of NO3- and NH4+ combined could contribute to ~2.4% and ~1.9% of the primary production in the coastal areas east of the Korean Peninsula and in the East Asian marginal seas, respectively, which would be a lower bound because the dry deposition of reactive nitrogen gas was not included. Our study shows that the atmospheric input of anthropogenic NO3- and NH4+ may substantially increase phytoplankton biomass in the coastal waters of the East Sea near the Korean Peninsula.

Inter-observer Reproducibility in the Pathologic Diagnosis of Gastric Intraepithelial Neoplasia and Early Carcinoma in Endoscopic Submucosal Dissection Specimens: A Multi-center Study.

PURPOSE: The diagnostic criteria of gastric intraepithelial neoplasia (IEN) are controversial across the world. We investigated how many discrepancies occur in the pathologic diagnosis of IEN and early gastric carcinoma in endoscopic submucosal dissection (ESD) specimens, and evaluated the reasons of the discordance. MATERIALS AND METHODS: We retrospectively reviewed 1,202 ESD specimens that were originally diagnosed as gastric IEN and early carcinoma at 12 institutions. RESULTS: The final consensus diagnosis of carcinoma were 756 cases, which were originally 692 carcinomas (91.5%), 43 high-grade dysplasias (5.7%), 20 low-grade dysplasias (2.6%), and 1 others (0.1%), respectively. High- and low-grade dysplasia were finally made in 63 and 342 cases, respectively. The diagnostic concordance with the consensus diagnosis was the highest for carcinoma (91.5%), followed by low-grade dysplasia (86.3%), others (63.4%) and high-grade dysplasia (50.8%). The general kappa value was 0.83, indicating excellent concordance. The kappa values of individual institutions ranged from 0.74 to 1 and correlated with the proportion of carcinoma cases. The cases revised to a final diagnosis of carcinoma exhibited both architectural abnormalities and cytologic atypia. The main differential points between low- and high-grade dysplasias were the glandular distribution and glandular shape. Additional features such as the glandular axis, surface maturation, nuclear stratification and nuclear polarity were also important. CONCLUSION: The overall concordance of the diagnosis of gastric IEN and early carcinoma in ESD specimens was excellent. It correlated with the proportion of carcinoma cases, demonstrating that the diagnostic criteria for carcinoma are more reproducible than those for dysplasia.

Long-Term Clinical Outcomes of Endoscopic Submucosal Dissection in Patients with Early Gastric Cancer: A Prospective Multicenter Cohort Study.

Background/Aims: Endoscopic submucosal dissection (ESD) has been regarded as a curative treatment for early gastric cancer (EGC) in indicated cases. The aim of this study was to evaluate the nationwide long-term clinical outcomes of ESD for EGC in Korea. Methods: A prospective multicenter cohort study was performed to evaluate the long-term efficacy of ESD for EGC within pre-defined indications at 12 institutes in Korea. The cases that met the expanded criteria upon pathological review after ESD were followed for 5 years. The primary outcome was 5-year disease specific free survival. Results: Six hundred ninety-seven patients with 722 EGCs treated with ESD were prospectively enrolled and followed for 5 years. Complete resection was achieved in 81.3% of the cases, and curative resection was achieved in 86.1%. During the 5-year follow-up, the overall survival rate was 96.6%, and the disease specific free survival rate was 90.6%. Local recurrence developed in 0.9%, and metachronous tumor development occurred in 7.8%; both conditions were treated by endoscopic or surgical treatment. Distant metastasis developed in 0.5% during follow-up. Conclusions: ESD showed excellent long-term clinical outcomes and can be accepted as a curative treatment for patients with EGC who meet the expanded criteria in final pathology studies.