Management of Tooth Size Arch Size Discrepancy (TSASD) in Patients with Sleep Disorder Breathing.

This case report describes the interdisciplinary management of an adult patient with sleep disorder breathing i.e. snoring. Treatment involved combined ortho-surgical management. Marked improvement in general health, good esthetic results, and dental relationships were achieved by the treatment.

Pharyngeal airway analysis in obese and non-obese patients with obstructive sleep apnea syndrome.

BACKGROUND: Sleep disorders are a group of disorders characterized by abnormalities of respiration during sleep. OSA (Obstructive Sleep Apnea) is characterized by the repetitive episodes of complete or partial collapse of the upper airway during sleep, causing a cessation or a significant reduction of airflow. METHOD: The study population consisted of 30 control patients (AHI ≤ 5) events per hour, 74 patients with OSAS, including 34 Obese (BMI ≥ 27) and 40 non-obese (BMI ≤ 27). Polysomnography and measurements of 21 cephalometric variables were carried out for all patients with OSAS. RESULTS: Obese patient with OSAS showed significant difference in following cephalometric parameters: (1) PAS (2) MPT (3) MPH (4) PNS-P (5) SAS. In addition, obese patient had longer tongue (TGL), more anteriorly displaced hyoid bones (H-VL) and more anterior displacement of mandible (G-VL) when compared with control groups. The findings of non-obese patients when compared to controls showed all the findings of obese patients and in addition to that narrow bony oropharynx were significant. Step wise regression analysis showed the significant predictors for all patients were MPH, PNS-P, bony nasopharynx (PNSBa), MPT, and palatal length (ANS-PNS) for AHI. The significant predictors for obese OSA (obstructive sleep apnea) group were MAS while for non-obese OSA group ANS-PNS was significant predictor for AHI (apnea-hypopnea index). CONCLUSION: Craniofacial landmarks such as increase in hyoid distance, longer tongue and soft palate with increased thickness and narrowing of superior pharyngeal, oropharyngeal and hypopharyngeal airway space may be important risk factors for development of OSAS.

Response of glacier modelling parameters to time, space, and model complexity: Examples from eastern slopes of Canadian Rocky Mountains.

Mountain glaciers are at risk of rapid retreat and require an accurate prediction of their melt and evolution. However, there is a great deal of hassle with mountain glacier melt modelling at a regional scale. Most advanced physical process-based models require an ample amount of high-resolution measurements, while widely-used empirical models suffer from parameter transferability. We developed a glacier melt, mass balance, and evolution modelling framework using three temperature index melt modelling approaches. We performed 24 model scenarios to examine the response of 19 empirical parameters to the effects of: (1) two time periods, for understanding how parameter response can vary with time period considered for the simulation; (2) two glaciers located at the eastern slopes of the Canadian Rocky Mountains, for understanding the effects of glaciers hydro-climate and geographic setting; and (3) two levels of complexity in the model structure including melt and mass balance models coupled with (complex) and without (simple) glacier evolution modules. The results showed that the best optimal melt parameter sets vary temporally and spatially for both simple and complex models, indicating that they are not transferable from one period to another and across glaciers. The variations of ice melt parameters are greater than the snowmelt parameters. The spatiotemporal variations of parameters are resulted from the geographical and local climatic settings and energy balance components, including albedo parameterization on the glacier surface, the altitudinal variations of the glaciers, and the slope and aspects to which glaciers are exposed. For all models, the most sensitive parameter is temperature Lapse rate (LR), but with increasing model complexity, the parameter responses vary depending on the melt model structure and input data. Our study provides important information for modelling glacier melt and evolution at a regional scale.

Assessing the snow cover dynamics and its relationship with different hydro-climatic characteristics in Upper Ganges river basin and its sub-basins.

Snowmelt is an important source of water in upstream part of the Ganges river basin (GRB), which provides water for different purposes to its 655 million inhabitants. However, studies assessing relationship between snow cover dynamics and changes in hydro-climatic variables are limited within this region, motivating the current research. In this study, MODIS snow cover product (MOD10A1) was used to assess the snow cover area (SCA) dynamics within the Upper Ganges river basin (UGRB) and its sub-basins for the time period of 2002-2014; available climate and hydrological data were used to assess the hydrological characteristics within three selected sub-basins in Nepal; and relationships between snow cover and different hydro-climatic variables are established for three sub-basins owing to availability of hydro-climatic data. Results show that the average annual maximum SCA is around 24.6-47.5% for UGRB and its sub-basins. Upper Yamuna river basin (UYRB) with lowest mean elevation among the sub-basins shows a single SCA peak in spring within an annual cycle, whereas UGRB and the higher sub-basins show an additional lower peak in fall mainly resulted from snow sublimation. During 2002-2014, SCA shows slight decreasing trends for UGRB (Kendall's Tau τ = -0.039) and the higher elevation zones B (3001-4500 m a.s.l.) and C (>4500 m a.s.l.) of most sub-basins, with significance in Zone C of SaRB (τ = -0.070) and KoRB (τ = -0.062). Annual discharge for Gandaki river basin (GaRB) and Koshi river basin (KoRB) shows non-significant decreasing trends (τ = -0.182, -0.303) which are resulted from decreasing discharge in different seasons in different sub-basins. Seasonal correlation analysis indicates an important water supply from rainfall in GaRB and combined water supply from rainfall and snowmelt in KoRB, along with dominant contribution of precipitation in monsoon months and snowmelt in non-monsoon months for all the three sub-basins.

Flood inundation mapping- Kerala 2018; Harnessing the power of SAR, automatic threshold detection method and Google Earth Engine.

Flood inundation maps provide valuable information towards flood risk preparedness, management, communication, response, and mitigation at the time of disaster, and can be developed by harnessing the power of satellite imagery. In the present study, Sentinel-1 Synthetic Aperture RADAR (SAR) data and Otsu method were utilized to map flood inundation areas. Google Earth Engine (GEE) was used for implementing Otsu algorithm and processing Sentinel-1 SAR data. The results were assessed by (i) calculating a confusion matrix; (ii) comparing the submerge water areas of flooded (Aug 2018), non-flooded (Jan 2018) and previous year's flooded season (Aug 2016, Aug 2017), and (iii) analyzing historical rainfall patterns to understand the flood event. The overall accuracy for the Sentinel-1 SAR flood inundation maps of 9th and 21st August 2018 was observed as 94.3% and 94.1% respectively. The submerged area (region under water) classified significant flooding as compared to the non-flooded (January 2018) and previous year's same season (August 2015-2017) classified outputs. Summing up, observations from Sentinel-1 SAR data using Otsu algorithm in GEE can act as a powerful tool for mapping flood inundation areas at the time of disaster, and enhance existing efforts towards saving lives and livelihoods of communities, and safeguarding infrastructure and businesses.