The Data Mining applied for the prediction of highway roughness due to overloaded trucks

Currently, the quality of the Indonesian national road network is inadequate due to several constraints, including overcapacity and overloaded trucks. The high deterioration rate of the road infrastructure in developing countries along with major budgetary restrictions and high growth in traffic have led to an emerging need for improving the performance of the highway maintenance system. However, the high number of intervening factors and their complex effects require advanced tools to successfully solve this problem. The high learning capabilities of Data Mining (DM) are a powerful solution to this problem. In the past, these tools have been successfully applied to solve complex and multi-dimensional problems in various scientific fields. Therefore, it is expected that DM can be used to analyze the large amount of data regarding the pavement and traffic, identify the relationship between variables, and provide information regarding the prediction of the data. In this paper, we present a new approach to predict the International Roughness Index (IRI) of pavement based on DM techniques. DM was used to analyze the initial IRI data, including age, Equivalent Single Axle Load (ESAL), crack, potholes, rutting, and long cracks. This model was developed and verified using data from an Integrated Indonesia Road Management System (IIRMS) that was measured with the National Association of Australian State Road Authorities (NAASRA) roughness meter. The results of the proposed approach are compared with the IIRMS analytical model adapted to the IRI, and the advantages of the new approach are highlighted. We show that the novel data-driven model is able to learn (with high accuracy) the complex relationships between the IRI and the contributing factors of overloaded trucks

Goblet cell density association with tear function and ocular surface physiology

Purpose: To determine the relationship of goblet cell density (GCD) with tear function and ocular surface physiology. Methods: This was a cross-sectional study conducted in 35 asymptomatic subjects with mean age 23.8±3.6 years. Tear film assessment, conjunctiva and cornea examination were done in each subject. Conjunctival impression cytology was performed by applying Nitrocellulose Millipore MFTM-Membrane filter over the superior bulbar conjunctiva. The filter paper was than fixed with 96% ethanol and stained with Periodic Acid Schiff, Hematoxylin and Eosin. GCD was determined by optical microscopy. Relation between GCD and Schirmer score, tear break-up time (TBUT), bulbar redness, limbal redness and corneal staining was determined. Results: The mean GCD was 151±122 cells/mm2. GCD was found higher in eyes with higher Schirmer score but it was not significant (p = 0.75). There was a significant relationship ofGCDwith TBUT (p = 0.042). GCD was not correlated with bulbar redness (p = 0.126), and limbal redness (p = 0.054) as well as corneal staining (p = 0.079). No relationship of GCD with age and gender of the subjects (p > 0.05) was observed. Conclusion: GCD was found correlated with TBUT but no significant correlation was found with the aqueous portion of the tear, limbal as well as bulbar redness and corneal staining.

Sex differences in the fetal heart rate variability indices of twins

Aims: To evaluate the differences in linear and complex heart rate dynamics in twin pairs according to fetal sex combination [male-female (MF), male-male (MM), and female-female (FF)]. Methods: Fourteen twin pairs (6 MF, 3 MM, and 5 FF) were monitored between 31 and 36.4 weeks of gestation. Twenty-six fetal heart rate (FHR) recordings of both twins were simultaneously acquired and analyzed with a system for computerized analysis of cardiotocograms. Linear and nonlinear FHR indices were calculated. Results: Overall, MM twins presented higher intrapair average in linear indices than the other pairs, whereas FF twins showed higher sympathetic-vagal balance. MF twins exhibited higher intrapair average in entropy indices and MM twins presented lower entropy values than FF twins considering the (automatically selected) threshold rLu. MM twin pairs showed higher intrapair differences in linear heart rate indices than MF and FF twins, whereas FF twins exhibited lower intrapair differences in entropy indices. Conclusions: The results of this exploratory study suggest that twins have sex-specific differences in linear and nonlinear indices of FHR. MM twins expressed signs of a more active autonomic nervous system and MF twins showed the most active complexity control system. These results suggest that fetal sex combination should be taken into consideration when performing detailed evaluation of the FHR in twins.