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The temporal compounding of two contrasting extremes of the hydrological spectrum (droughts and floods) reflects a volatile hydrological cycle and makes water resources management more challenging. To this end, the present study examines extreme wet-dry events and their temporal compounding over the Upper Jhelum Basin (UJB) in the future climate context based on simulations of climate models from three modeling initiatives (CMIP6, CORDEX - WAS-44 domain and CORDEX-CORE - WAS-22 domain) under low, medium and high emission scenarios for two-time segments i.e., near future (2040-2059) and far future (2080-2099). Wet and dry events are characterized by using a multivariate drought index (namely the Standardized Precipitation Evapotranspiration Index, SPEI), which is derived from daily precipitation and maximum and minimum temperatures. The temporally compound event (hereafter referred as compound event-CE), which is defined as a successive transition from one powerful state to another, includes dry to wet (D-to-W) events and wet to dry (W-to-D) events in the adjacent month. Therefore, the minimum duration of a compound event is 2 months. A D-to-W compound event is defined as a dry spell (SPEIi ≤−1) abruptly changing into a wet spell (SPEIi+1 ≥1) in the next month. Conversely, a W-to-D compound event is defined as a wet spell (SPEIi ≥1) abruptly changing into a dry spell (SPEIi+1 ≤−1) in the next month. The statistical interdependency of temporally compound wet and dry events (CEs) and their statistical significance are investigated using event coincidence analysis (ECA). The significance test is performed based on the assumption of a Poisson process with the null hypothesis that the successive occurrence of wet and dry event is randomly distributed. Results show that the probability of D-to-W CEs is much higher than the W-to-D CEs under both retrospective (i.e., past) or prospective (i.e., future) climate contexts. Specifically, the probability of D-to-W events is high in the southwest of the basin (up to 80 %, statistically significant at 5% level) both in the historical and projections. In contrast, the W-to-D CEs are found to be statistically non-significant for a 95% confidence level (up to 40 %) with no clear pattern of occurrence. There are some differences depending on the climate model ensembles used. CORDEX models (WAS44 and WAS22) show decreasing probability of D-to-W CEs in the southwest part of the basin by the end of the century whereas the CMIP6 ensemble shows a negligible increase from near to far future especially under the highest emission scenario. Overall, the CMIP6 ensemble presents higher probability of CEs under all scenarios and time segments. Climate projections of this kind of extreme events, spanning different scenarios and all sources of uncertainty are essential to fully characterize their impacts on water-related sectors and to plan possible adaptation strategies, such as developing more efficient reservoir operation rules or agricultural planning.

Background of the Study: Cardiovascular Disease (CVD) is affecting millions of people in both developed and developing countries. Although the rate of death attributable to the disease has declined in developed countries in the past several decades, it is still the leading cause of death and extorts a heavy social and economic toll globally. In low-middle income countries, the prevalence of CVD has increased dramatically. By 2020, the disease is forecasted to be the major cause of morbidity and mortality in most developing nations. The Global Burden of Disease study estimate of age-standardized CVD death rate of 272 per 100000 populations in India is higher than the global average of 235 per 100000 populations. CAD was estimated to account for around 15%–20% and 6%–9% of all deaths in India and the US. In addition to mortality, CAD is also responsible for morbidity and loss of quality of life Materials and Methods: Qualitative cross-sectional study design with a descriptive research approach was adopted for the present study. The study was conducted in D. Y. Patil Hospital and Terna Multi-Speciality Hospital and Research Centre, Nerul, Navi Mumbai with a sample size of 75. A Non-probability purposive sampling technique was used. In this study samples were patients who underwent Percutaneous revascularization for coronary artery disease. Data was collected using an Interview technique. The data was tabulated and analysed in terms of objectives of the study, using descriptive and inferential statistics. Results: The study results show that the majority of the respondents belonged to the age group 46 - 65 years with a frequency of 27 (36%) and were married 57 (76%). Representation of male respondents was 44 (59%) and the rest of the respondents belonged to female gender. They were educated up to high school and employed (service staff); their monthly income was

Bias correction (BC) is often a necessity to improve the applicability of global and regional climate model (GCM and RCM, respectively) outputs to impact assessment studies, which usually depend on multiple potentially dependent variables. To date, various BC methods have been developed which adjust climate variables separately (univariate BC) or jointly (multivariate BC) prior to their application in impact studies (i.e., the component-wise approach). Another possible approach is to first calculate the multivariate hazard index from the original, biased simulations, and bias-correct the impact model output or index itself using univariate methods (direct approach). This has the advantage of circumventing the difficulties associated with correcting the inter-variable dependence of climate variables which is not considered by univariate BC methods. Using a multivariate drought index (i.e., SPEI) as an example, the present study compares different state-ofthe- art BC methods (univariate and multivariate) and BC approaches (direct and component-wise) applied to climate model simulations stemming from different experiments at different spatial resolutions (namely CORDEX, CORDEX-CORE and CMIP6). The BC methods are calibrated and evaluated over the same historical period (1986–2005). The proposed framework is demonstrated as a case study over a transboundary watershed, i.e. the Upper Jhelum Basin (UJB) in the Western Himalaya. Results show that (1) there is some added value of multivariate BC methods over the univariate methods in adjusting the inter-variable relationship, however, comparable performance is found for SPEI indices. (2) The best performing BC methods exhibits a comparable performance under both approaches with a slightly better performance for the direct approach. (3) The added value of the high-resolution experiments (CORDEX-CORE) compared to their coarser resolution counterparts (CORDEX) are not apparent in this study.

Introduction: Despite extensive research in various preventive technologies over the years, white spot lesion (WSL) development in association with orthodontic treatment with fixed appliances remains an unwanted clinical problem. Materials and Methods: This study was conducted to compare the efficacy of various cariostatic products available commercially that would help in prevention of white spot lesions. Total 120 healthy extracted premolars were taken and divided into a sample of four groups. GC Tooth Mousse, Clin pro and Anticay were compared for their protective efficiency. Three test groups had three different topical agents applied and the fourth group acted as a control. After the test materials were applied they were subjected to pH cycling using artificial saliva with a pH of 4.5 that acted as a demineralization agent and fluorescence was assessed using spectroscopy. Results: One way Anova and Student‘t’ test revealed the efficacy of all the three materials as cariostatic agents, GC Tooth Mousse and Anticay were revealed to have the best protective efficiency. Conclusion: GC Tooth Mousse and Anticay can be used by the orthodontic patients as an in home application product for the prevention of development of white spot lesions. Keywords: White spot lesions, Spectroscopy, Artificial Saliva, CPP-ACP, CaSP.

The present study was carried out at Water Management Research Centre, University of Agriculture, Faisalabad, Pakistan, to investigate the effect of row spacing, deficit irrigation and dual plantation on tomato yield grown in high tunnel under polyethylene black mulch and drip irrigation system. The field experiment layout comprised of three rows spacing (S1, S2 and S3) as (0.45, 0.60, and 0.75 m respectively) and two irrigation levels (I1 and I2) as (100% and 75% of required irrigation respectively). In addition, a dual plantation treatment spaced at 0.45 m was also investigated under both irrigation levels. Results showed that the total fruit yield was significantly influenced by row spacing and irrigation level, however, their interaction was non-significant. The 100% irrigation gave 6.53, 4.49, and 5.94% more yield than 75% irrigation treatment under 0.45, 0.60, and 0.75 m row spacing, respectively. However, the irrigation water use efficiency was found to be higher in deficit treatment (75% irrigation) by 25.16, 27.60, and 25.86% than full irrigation treatments under 0.45, 0.60, and 0.75 m row spacing, respectively. The results of single and dual plantation showed that dual plantation increased the fruit yield by 7.62 and 11.28% than the single plantation under full and deficit irrigation respectively and covering approximately the same area.

The compound occurrence of two extremes of the hydrological spectrum (droughts and floods) either in space and/or time, could aggravate the associated socio-economic impacts with respect to those caused by the individual extreme event. Both extreme events share the potentially linked driving mechanisms and interconnected characteristics, therefore the better understanding of the dependence structures of the contributing variables is essential to avoid the underestimation of the possible risks of compound hazards. To this end, the present study focusses on spatio-temporally compound extreme events under a changing climate and identify/locate the most vulnerable hotspots in the Upper Jhelum Basin (South Asia), paving the way for adaptation and mitigation measures. Climate models are the main tools to assess climate projections and, particularly, to provide relevant information for sectoral applications. They often present systematic biases, thus some sort of bias adjustment is performed in impact assessments. The framework of the present study is two-fold: (i) evaluation of bias correction (BC) of climate model historical simulations and (ii) projection of extreme compound events in the near future (2040-2059) and far future (2080-2099) for three different Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5). Droughts and floods are characterized by using a multivariate drought index (namely the Standardized Precipitation Evapotranspiration Index, SPEI), which is derived from daily precipitation (P) and maximum (Tmax) and minimum temperatures (Tmin). In the first step, the intercomparison of different state-of-the-art BC methods (uni- and multi-variate) and BC approaches (direct and component-wise) for climate model simulations stemming from different experiments (CMIP6, CORDEX -WAS-44- and CORDEX CORE -WAS-22) is performed following a multivariate framework. The added value/performance of BC and climate model simulations is examined in terms of inter-variable physical coherence of involved key essential variables (P, Tmax and Tmin) and characteristics of extreme events (duration, severity, intensity, and frequency of floods and droughts) during the historical period. In the second step, projected changes in the extreme events characteristics and their compounding in space and time are analyzed for the near and far future under all available scenarios. Climate projections of this kind of extreme events, spanning different scenarios and other sources of uncertainty is essential to better implement adaptation and mitigation solutions that can help reduce the negative impacts of climate change.

The increasing rate of occurrence of extreme events (droughts and floods) and their rapid transition magnify the associated socio-economic impacts with respect to those caused by the individual event. Understanding of spatio-temporal evolution of wet–dry events collectively, their characteristics, and the transition (wet to dry and dry to wet) is therefore significant to identify and locate most vulnerable hotspots, providing the basis for the adaptation and mitigation measures. The Upper Jhelum Basin (UJB) in South Asia was selected as a case study, where the relevance of wet–dry events and their transition has not been assessed yet, despite clear evidence of climate change in the region. The standardized precipitation evapotranspiration index (SPEI) at the monthly timescale was applied to detect and characterize wet and dry events for the period 1981–2014. The results of temporal variations in SPEI showed a strong change in basin climatic features associated with El Niño–Southern Oscillation (ENSO) at the end of 1997, with the prevalence of wet and dry events before and after 1997 respectively. The results of spatial analysis show a higher susceptibility of the monsoon-dominated region towards wet events, with more intense events occurring in the eastern part, whereas a higher severity and duration are featured in the southwestern part of the basin. In contrast, the westerlies-dominated region was found to be the hotspot of dry events with higher duration, severity, and intensity. Moreover, the surrounding region of the Himalaya divide line and the monsoon-dominated part of the basin were found to be the hotspots of rapid wet–dry transition events.

The increasing rate of extreme events (Droughts and floods) and their rapid transition magnifies the associated socio-economic impacts than the individual event. Understanding of spatio-temporal evolution of wet-dry events collectively, their characteristics and transition (wet to dry and dry to wet) is therefore significant to identify and locate most vulnerable hotspots, providing the basis for the adaptation and mitigation measures. The Upper Jhelum Basin (UJB)-South Asia was selected as a case study, where the relevance of wet-dry events and their transition have not been assessed yet, despite of clear evidence of climate change in the region. The Standardized Precipitation Evapotranspiration Index (SPEI) at the monthly time scale was applied to detect and characterize wet and dry events for the period 1981–2014. The results of temporal variations of SPEI showed a strong change in basin climatic features associated with El Niño Southern Oscillation (ENSO) at the end of 1997, with the prevalence of wet and dry events before and after 1997 respectively. The results of spatial analysis show a higher susceptibility of the monsoon-dominated region towards wet events, with more intense events occurring in the eastern part, whereas a higher severity and duration is featuring in the southwestern part of the basin. In contrast, westerlies-dominated region was found to be the hotspot of dry events with higher duration, severity, and intensity. Moreover, the surrounding region of the Himalaya divide line and the monsoon-dominated part of the basin were found to be the hotspots of rapid wet-dry transition events.

Global warming and anthropogenic activities have significantly altered the hydrological cycle and amplified the extreme events (floods and droughts) in many regions of the world, with associated environmental, economic, and social losses. For effective hydro extremes hazards management, it is significant to understand how climate change influences the occurrence, duration, and severity of the regional dryness/wetness conditions (droughts/floods). The present study was carried out over Upper Jhelum Basin (UJB) in Pakistan which lies in the western Himalaya, a most effected mountainous range by Climate Change. Firstly, a suitable gridded precipitation dataset was selected/chosen among various datasets (APHRODITE, CHIRPS, ERA5, PGMFD, MSWEP) through spatio-temporal comparison against in situ data at monthly, seasonal, and annual scale. Secondly, selected gridded data was adjusted for biases using linear (Linear scaling-LS, Local intensity scaling-LOCI) and nonlinear (Power transformation-PT and Distribution mapping-DM) statistical methods. Finally, standardized precipitation index (SPI) at multiple time scale was used to analyses dryness/wetness conditions in the Upper Jhelum Basin over a 35-year period (1981–2015). Results show the higher capability of ERA5 data to represent the UJB precipitation patterns with correlation coefficient (r=0.79) and normalized standard deviation (nSD=1.1), despite of overestimation especially during peak months. Regarding precipitation bias adjustment, all methods were able to correct the mean values while LOCI and DM take advantage over other two methods to correct wet-day probability and precipitation intensity. The SPI analysis at different time scales showed that wet periods occurred more in the first half of the study period, but at later years, drying periods ranging from moderate to severe continue to be seen with increasing frequency. A strong change in dry/wet conditions was observed around years 1997/1998. This change may be the result of the strongest El Nino event (1997-98) occurred in the history. However, further studies are still needed to check whether there is only a large multi-decadal variation or dry conditions will prevail in future. Overall, these findings would assist to better understand the changing pattern of extreme events with climate variability and help water resources managers to develop basin wide appropriate mitigation and adaptation measures to combat climate change and its consequences.

The commercial use and unrestricted disposal of synthetic dyes in soil and water-bodies, following the industrial revolution, has led to a major threat towards environmental safety. The azo-dye, Remazol Black B (RBB) is one of the most commonly used synthetic reactive dyes in textile industries. In the present study, the decolourization and biodegradation of RBB were investigated using a bacterium isolated from the marine environment, which was later identified as Pseudomonas aeruginosa AR-7 by 16S rRNA analysis. P. aeruginosa AR-7 showed 99% decolourization at 100mg/L dye concentration when cultured at optimum conditions of incubation i.e., 96h at 37⁰C under static conditions using minimal salts medium (pH 7-9) supplemented with 0.1% glucose and yeast extracts. However, the dye degradation ability of the isolate was reduced to 29% on increasing the dye concentration to 500mg/L. In addition, P. aeruginosa AR-7 showed decolourization and degradation of RBB in wastewater obtained after dyeing a cotton fabric. In further experiments, the Fe3O4 nanoparticles were synthesized using co-precipitation method and were used to immobilize the cells of P. aeruginosa AR-7 by adsorption, in order to compare the RBB degrading abilities of the free and coated cells. The prepared nanoparticles (50-150nm) were characterized by FTIR and SEM analysis to study its structural properties. Also, upon magnetization studies using SQUID magnetometer, Fe3O4 nanoparticles were shown to have a magnetization of about 63emu/g. Interestingly, the coated cells not only showed better degradation ability of RBB but also produced simpler products such as alkane, carboxylic acids, ketone, etc. on complete degradation. On the other hand, the free cells mainly produced esters as indicated by the comparison of GC-MS results.

Urbanisation causes land degradation problems, including an increased pressure on natural resources and management of water resources. This study aims to investigate the impact of the spatio-temporal dynamics of land use land cover (LULC) changes on groundwater table in the region of Al Ain, United Arab Emirates (UAE), from 2006 to 2016. The Landsat images, Landsat ETM for 2006 and Landsat 8 for 2016, were acquired from the earth explorer site. A semi-supervised hybrid classification method was used for image classification and post-classification techniques for LULC change detection. The study area was categorised into six major LULC classes. These are agriculture/farms/oasis, gardens/playgrounds, urban areas, sandy areas, lake and mixed urban/sandy areas. Accuracy assessment of LULC were evaluated using confusion matrix and ground truthing. The obtained land use and land cover maps were also correlated with spatial groundwater table maps prepared with groundwater data. It was found that agriculture/farms/oasis and urban areas expanded from 42,560 ha to 45,950 ha (7.38%) and from 8150 ha to 9105 ha (10.49%) from 2006 to 2016, respectively. The corresponding water demand was increased by 9.56% and 22.22%, respectively. Natural sandy area was found to decrease by 8.10%. As groundwater is major source of water for agriculture in this region, the spatial maps also revealead average declining rate of groundwater depth 40.44% with expansion of urban and agricultural areas over the last 10 years. The outcomes of the study would help concerning authorities for a sustainable management of its land and groundwater resources.

Objective: The purpose of the study was to evaluate Beta (β) angle variation in different facial types among Garhwali population and also to evaluate the differences in Beta angle in male and female subgroups. Materials & Method: The sample included pre-treatment lateral cephalograms of 90 native Garhwali subjects (age 16-24 years) who were divided into three groups: normodivergent, hypodivergent and hyperdivergent; of 30 subjects of each group 15 were male and 15 were female. Result: In Garhwali population subjects with a β angle between 28° to 32° have a normodivergent facial type (ANOVA p < 0.01). Conclusion: There is a significant difference in the mean values of β angle in Garhwali population among various facial types. DOI: http://dx.doi.org/10.3126/ojn.v3i1.9280 Orthodontic Journal of Nepal, Vol.3, No.1, 2013: 37-40