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The study aimed to evaluate the efficacy of octyl-2-cyanoacrylate as well as sutures as a wound closure material. Whether octyl-2-cyanoacrylate can be used as an alternative to suture in the closure of facial wounds. Out of total of 19 wounds, 11 wounds were closed with sutures and tissue adhesive both, out of rest 8 wounds, 4 wounds were closed using sutures alone and in 4 wounds, closure was done with tissue adhesive alone. Therefore, a total of 15 facial wounds were divided into two groups: Group-I Cases in whom 3-0 Black silk suture was used for closure of the wound and Group-II Cases in whom Dermabond (Octyl-2-Cyanoacrylate) was used for closure of the wound. Results showed that Octyl-2-cyanoacrylate offered the benefit of decreased procedure time with less pain, no need for its removal, and better cosmetic outcome compared to sutures.

Rapid urbanization and exponential increase in the number of vehicles on city roads have triggered issues like air pollution and accidents, endangering the health of millions of people in Indian cities. Vehicular emission is a major contributor to air pollution in Indian cities. This study primarily analyzes the relative effects of riding quality and pavement surface type on vehicular fuel consumption (FC) in an urban environment. This study utilizes the Road Asset Management System (RAMS) applications to predict FC in different scenarios of pavement maintenance. Highway Development and Management (HDM-4) software was integrated into RAMS for network & economic analysis and FC prediction of the road network. The study was conducted on the Pune city road network in India, and the results revealed a 2.32 % reduction in fuel use if timely maintenance is provided. Over 0.128 million liters of fuel per 1000 vehicle-km can be saved over the study network of only 36.5 km over the next 15 years, equivalent to US$ 155,206.18 in 2021. The analysis of covariance test results showed the significant effect of pavement surface type on fuel consumption, with 4.86 % less fuel consumed on cement concrete surfaces than bituminous surfaces. About 99.431 liters per 1000 vehicle-km of fuel were utilized by the vehicle fleet on concrete pavements, while 104.513 liters per 1000 vehicle-km of fuel were consumed on bituminous pavements after adjusting for roughness characteristics of both the surface types.

Highway Development and Management (HDM-4) is an internationally recognised tool to analyse pavement management and investment alternatives. The HDM-4 pavement deterioration models help to predict the initiation and progression of various pavement distresses under the different combinations of traffic, climate, pavement structure, and composition. Since the rate of initiation and propagation of each pavement distress is strongly dependent on local conditions, it is essential to calibrate and validate the HDM-4 models for local conditions before their use. Validation of the calibrated HDM-4 pavement deterioration models is needed to check the adequacy of the calibration factors before the model is put to use for future applications. Time series data collected consecutively for three years of 23 high-speed corridors sections constructed with modified binders in India was used to calibrate the HDM-4 distress models. The main aim of this paper is to discuss the validation aspects of the calibrated HDM-4 models, to compare the distresses predicted to those observed on test sections. In this study, a novel technique termed the “proximity to the line of equality” approach is used to validate the HDM-4 models. In addition, Student’s t-test is also used as a conventional validation technique. The advantage of the “proximity to the line of equality” approach is that it removes subjectivity associated with judging the nearness of best-fit straight line of predicted-observed data to the line of equality. Validation results show that distresses predicted by HDM-4 are statistically similar to those observed on the sections. Therefore, the calibrated HDM-4 models can be adopted for planning future maintenance strategies for flexible pavement sections with modified asphalt binder road surfacing.

In recent years, the use of foamed bitumen technology along with Reclaimed Asphalt Pavement is gaining popularity across the world. The mechanical response of foamed bitumen mixtures containing reclaimed asphalt pavement is significantly influenced by constituent material properties and aggregate gradation. This article presents results from a study where foamed bitumen mixtures conforming to Indian specifications were evaluated. For this purpose, foamed bitumen mixtures using a different percentage of reclaimed asphalt pavement and bitumens were prepared. Initially, the foaming characteristics of virgin bitumens were evaluated to optimize for optimum water content and foaming temperature. In the second stage, mixture design was conducted to optimize for foamed bitumen content in foamed bitumen mixtures containing a different percentage of reclaimed asphalt pavement. Finally, these foamed bitumen mixtures were evaluated for their mechanical properties. The results from this laboratory study indicated properties of foamed bitumen and foamed mixtures are significantly influenced by properties of bitumen, the quantity of bitumen, and reclaimed asphalt pavement. Among the different mixtures, a mixture containing 50% reclaimed asphalt pavement exhibited best results in resilient modulus and resistance to moisture damage tests. A mixture containing 80% reclaimed asphalt pavement also shows acceptable strength and resistance to water susceptibility. Thus, it is possible to design high-quality bituminous mixes using higher reclaimed asphalt pavement percentages, which meet the required volumetric and desired performance criteria.

A large variety of sound sources in the ocean, including biological, geophysical, and man-made, can be simultaneously monitored over instantaneous continental-shelf scale regions via the passive ocean acoustic waveguide remote sensing (POAWRS) technique by employing a large-aperture densely-populated coherent hydrophone array system. Millions of acoustic signals received on the POAWRS system per day can make it challenging to identify individual sound sources. An automated classification system is necessary to enable sound sources to be recognized. Here, the objectives are to (i) gather a large training and test data set of fin whale vocalization and other acoustic signal detections; (ii) build multiple fin whale vocalization classifiers, including a logistic regression, support vector machine (SVM), decision tree, convolutional neural network (CNN), and long short-term memory (LSTM) network; (iii) evaluate and compare performance of these classifiers using multiple metrics including accuracy, precision, recall and F1-score; and (iv) integrate one of the classifiers into the existing POAWRS array and signal processing software. The findings presented here will (1) provide an automatic classifier for near real-time fin whale vocalization detection and recognition, useful in marine mammal monitoring applications; and (2) lay the foundation for building an automatic classifier applied for near real-time detection and recognition of a wide variety of biological, geophysical, and man-made sound sources typically detected by the POAWRS system in the ocean.