Hyperventilation Syndromes As Seen Is Kathmandu

Sharma, Bharati

doi:10.31729/jnma.1246

Cited by 3 publications

(5 citation statements)

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“…For stem volume, the average basal area of tree was calculated from, the species specific, stem diameter over the bark at a height of 1.3 m. First, the average diameter per hectare per plot is calculated, which is used to find basal area (in m 2 ) of trees per plot, by using formula ( 1 ). Finally, this area is used to calculate the volume of the stem by following allometric equation developed by [ 21 ]

Here, v is the tree volume per hectare (m 3 /ha), h is the height of the trees (m), and a is the average basal area (m 2 ) of the trees per hectare per subplot. a , b , and c are the coefficients depending on the species [ 21 ].…”

Section: Methodsmentioning

confidence: 99%

“…Finally, this area is used to calculate the volume of the stem by following allometric equation developed by [ 21 ]

Section: Methodsmentioning

confidence: 99%

“…The tree stem biomass is calculated by species specific stem density values of the stem. The stem density is the air dried density in kg/m 3 [ 21 ]. Hence the stem biomass is calculated by the following equation:

…”

Section: Methodsmentioning

confidence: 99%

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Linear Regression Model to Identify the Factors Associated with Carbon Stock in Chure Forest of Nepal

Sharma

Kakchapati

2018

Scientifica

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Use of woody plants for greenhouse gas mitigation has led to the demand for rapid cost-effective estimation of forest carbon stock and related factors. This study aims to assess the factors associated with carbon stock in Chure forest of Nepal. The data were obtained from Department of Forest Research and Survey (DFRS) of Nepal. A multiple linear regression model and then sum contrasts were used to observe the association between variables such as stem volume, diameter at breast height, altitude, districts, number of trees per plot, and ownership of the forest. 95% confidence interval (CI) plots were drawn for comparing the adjusted carbon stocks with each of the factors and with the overall carbon stock. The linear regression showed a good fit of the model (adjusted R2 = 83.75%) with the results that the stem volume (sv), diameter at breast height (dbh), and the number of trees per plot showed statistically significant (p value ≤ 0.05) positive association with carbon stock. The highest carbon stock was associated with sv more than 199 m3/ha, average dbh more than 43.3 cm/plot, and number of trees more than 20/plot, whereas the altitude, geographical location, and ownership had no statistical associations at all. The results can be of use to the government for enhancing carbon stock in Chure that supports both natural resource conservation and United Nations-Reducing Emission from Deforestation and Forest Degradation program to mitigate carbon emission issues.

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Section: Methodsmentioning

confidence: 99%

“…Finally, this area is used to calculate the volume of the stem by following allometric equation developed by [ 21 ]

Section: Methodsmentioning

confidence: 99%

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Linear Regression Model to Identify the Factors Associated with Carbon Stock in Chure Forest of Nepal

Sharma

Kakchapati

2018

Scientifica

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“…The construction industry in Nepal, which contributes about 10 percent of the GDP of the country (Central Bureau of Statistics, 2000), is the second‐largest employer in the country. About 60 percent of the nation's development budget is spent through the use of contractors (Sharma, 1998). Thus, productivity improvement efforts in the construction industry would have a significant impact on the overall improvement of the national economy.…”

Section: Practical Applicationmentioning

confidence: 99%

Downtime model development for construction equipment management

Nepal

Park

2004

Engineering, Construction and Architectural Management

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Downtime (DT) caused by non‐availability of equipment and equipment breakdown has non‐trivial impact on the performance of construction projects. Earlier research has often addressed this fact, but it has rarely explained the causes and consequences of DT – especially in the context of developing countries. This paper presents a DT model to address this issue. Using this model, the generic factors and processes related to DT are identified, and the impact of DT is quantified. By applying the model framework to nine road projects in Nepal, the impact of DT is explored in terms of its duration and cost. The research findings highlight how various factors and processes interact with each other to create DT, and mitigate or exacerbate its impact on project performance. It is suggested that construction companies need to adopt proactive equipment management and maintenance programs to minimize the impact of DT.

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“…The Siwalik Group, known as the molassic sediments exposed in association with Himalayan uplift, was deposited during the middle Miocene to the early Pleistocene as a 4 -6 km thick fl uvial sediments at the southern front of the entire Himalayan belt (Gansser 1964, Prakash et al 1980, Tokuoka et al 1986, Quade et al 1995, Dhital et al 1995, Burbank et al 1996, DeCelles et al 1998, Corvinus and Rimal 2001. The Siwalik Group has been traditionally classifi ed as three units (Lower, Middle and Upper Siwaliks) (Auden 1935, Hagen 1969, Yoshida and Arita 1982, Quade et al 1995, DeCelles et al 1998, Gautam and Fujiwara 2000, Ojha et al 2000, Robinson et al 2006, Sharma et al 2007) and with locally two-, four-or fi ve-fold units is acceptable (Glennie and Ziegler 1964, Sharma 1973, Tokuoka et al 1986, 1988Sah et al 1994, Corvinus and Nanda 1994, Dhital et al 1995, Ulak and Nakayama 1998, Sigdel et al 2011. The common three-fold classifi cation starts in general with the mudstone-dominated Lower Siwalik, grading upward into the sandstone-dominated Middle Siwalik and the Upper Siwalik of the conglomerate-dominated sediments (Medlicott 1875, Pilgrim 1913, Wadia 1957, Auden 1935, Hagen 1969, Yoshida and Arita 1982, Quade et al 1995, DeCelles et al 1998…”

Section: Introductionmentioning

confidence: 99%

Lithostratigraphy of the Siwalik Group, Khutia Khola section, Far Western Nepal Himalaya

Adhikari

Sakai

2015

Journal of Nepal Geological Society

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The Neogene fl uival sediments (Siwalik Group) forming the southernmost hills in the Himalaya is well exposed along the Khutia Khola in the Far Western Nepal. The newly established lithostratigraphy is subdivided into the Jagati Formation (2110 m, equivalent to the Lower Siwalik) and the Kala Formation (2050 m, equivalent to the Middle Siwalik) in ascending order. Each formation is further divided into three members; the lower, middle and upper, based on the ratio of mudstone vs. sandstone beds as well as color and grain size of sandstone. The Jagati Formation is characterized by reddish-brown mudstones interbedded with very fi ne-to coarse-grained sandstones. Paleosols characterized with burrows, rhizoliths, desiccation cracks, concretions and nodules are present in higher proportion than thinly laminated or massive mudstone beds. The Kala Formation comprises thin-to thick-bedded, very fi ne-to very coarse-grained sandstones and pebbly sandstones interbedded with reddishbrown, greenish-grey to dark-grey mudstones. Sandstone beds exhibit "salt and pepper" appearance. In the lower part of the upper member sub-rounded to rounded pebbles are scattered along with trough and planar cross-laminations in sandstone beds, whereas the gravel size tends to be larger and few cobble size gravels also appear in the upper part. Thinly laminated or massive mudstones are common and paleosols are less frequent. The age of the boundary between the Jagati and Kala Formations (Lower-Middle Siwaliks) is around 11.05 Ma. The boundaries age between the middle and upper members of the Jagati Formation is around 12.7 Ma and between the lower and middle members of the Kala Formation is around 9.0 Ma. The dominance of fi ner sediments and thinner sandstone units than that of neighboring Siwalik successions indicate the fl uvial facies of the Khutia Khola section is deposited by a small river system and may represent the interfl uve setting of major river systems.

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Hyperventilation Syndromes As Seen Is Kathmandu

Abstract: NA

Cited by 3 publications

References 0 publications

Linear Regression Model to Identify the Factors Associated with Carbon Stock in Chure Forest of Nepal

Linear Regression Model to Identify the Factors Associated with Carbon Stock in Chure Forest of Nepal

Downtime model development for construction equipment management

Lithostratigraphy of the Siwalik Group, Khutia Khola section, Far Western Nepal Himalaya

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