Intraoperative squash cytology and histopathological correlation of primary temporal lobe lesions: a 6 year study at tertiary care centre of Kashmir, India

Background: Central nervous system (CNS) tumors constitute about 1-2% of all the tumors. They are the 6th most common tumors in adults and 2nd most common among childhood tumors. Gliomas are the most common CNS neoplasms. In addition to gliomas temporal lobe has predilection for some peculiar tumor subtypes having good prognosis, including pleomorphic xanthoastrocytoma (PXA), low grade astrocytic tumors and dysembryoplastic neuroepithelial tumor (DNET) in children.Methods: Study was conducted in the department of pathology Sher-e-Kashmir institute of medical sciences (SKIMS) Soura, Srinagar Kashmir India. This was six-year study.Results: Temporal lobe tumors were commonly seen in 3rd to 4th decade of life accounting for 37.9% of the cases followed by 4th to 5th decade (27.5%). The mean age of presentation being 40±10 yrs. Males outnumbered females with a male: female ratio of 1.7:1. Intraoperative squash smears were mostly reported as High grade gliomas (WHO Grade III-IV) accounting to a total of 42 cases (36.2%). On histopathology frequent temporal lobe tumor seen was Glioblastoma multiforme (GBM) 17.4%, followed by pleomorphic xanthoastrocytoma and oligodendroglioma accounting for 14.6% of cases each. On comparing the diagnostic accuracy of intraoperative squash smears to that of Histopathological diagnosis an overall accuracy of 86.2% was observed.Conclusions: Intra operative squash technique in CNS tumors is universally accepted method. In temporal lobe lesions, on adequate sampling and careful examination, squash cytology has fairly good diagnostic accuracy rate of 86.2% when compared to histopathology

Eco-friendly dyeing of wool and pashmina fabric using Quercus robur L. (fruit cups) dye and Salix alba L. (wood extract) mordant

Study was conducted to investigate the dyeing potential of Quercus robur L. (fruit cups) dye and Salix alba L. (wood extract) mordant on wool and pashmina fabrics. The experiment was conducted keeping in view the environmental safety by using unutilized plant materials and excluding the usage of chemical agents. The dyeing was carried out individually including and excluding mordant adopting different mordanting methods. The parameters like percent absorption, colour coordinates, colour strength (K/S), relative colour strength and colour fastness with regard to washing, light and rubbing were investigated. The results revealed higher percent absorption of mordanted samples than unmordanted samples. Colour coordinates (L*a*b*, Chroma, hue and ?E) of dyed wool and pashmina fabric exhibited satisfactory results. The colour strength (K/S) and relative colour strength of pashmina fabric recorded higher than wool fabric. The fastness properties to washing, light and rubbing showed satisfactory grades including and excluding natural mordant. However, the grades of mordanted samples were found better than unmordanted samples. The dye and mordant in isolation and in combination showed beautiful colours and shades on selected fabrics with satisfactory retention properties, hence can be utilized commercially for coloration of wool and pashmina fabrics

Rank Set Sampling in Improving the Estimates of Simple Regression Model

<p>In this paper Rank set sampling (RSS) is introduced with a view of increasing the efficiency of estimates of Simple regression model. Regression model is considered with respect to samples taken from sampling techniques like Simple random sampling (SRS), Systematic sampling (SYS) and Rank set sampling (RSS). It is found that R² and Adj R²obtained from regression model based on Rank set sample is higher than rest of two sampling schemes. Similarly Root mean square error, p-values, coefficient of variation are much lower in Rank set based regression model, also under validation technique (Jackknifing) there is consistency in the measure of R², Adj R² and RMSE in case of RSS as compared to SRS and SYS. Results are supported with an empirical study involving a real data set generated of <em>Pinus Wallichiana</em> taken from block Langate of district Kupwara. </p

EFFICIENCY OF RANKED SET SAMPLING IN HORTICULTURAL SURVEYS

<p>DOI: 10.12957/cadest.2015.19114</p> <p>Abstract</p> <p>In this paper, we explore the feasibility of using RSS (Ranked Set Sampling) in improving the estimates of the population mean in comparison  to SRS (Simple Random Sampling) in Horticultural research. We use an experience developed with a survey of apples in India. The numerical results suggest that RSS procedure results in a substantial reduction of standard errors, and  thus provides more efficient estimates than SRS, in the  specific Horticultural Survey studied, using the same sample size. Then it is recommended as an easy-to-use accurate method to management of this Horticulture problem.</p> <p>Key-words: Ranked Set Sampling, Simple Random Sampling, Standard Error, Accuracy.</p><p><em> </em></p><p><em> </em></p><p><em> </em></p><p><em> </em></p><p> </p

Obtaining Strata Boundaries under Proportional Allocation with Varying Cost of Every Unit

One of the main reasons for stratifying the population is to produce a gain in precision of the estimates, in the sample surveys. For achieving this, one of the problem is determination of optimum strata boundaries. The strata boundaries should be obtained in such a way, so that it can reasonably expect to reduce the cost of the survey as much as possible without sacrificing the accuracy or alternatively, reducing the margin of error to the greatest possible extent for the same expected cost. In this paper, we have discussed the way of obtaining optimum strata boundaries when the cost of every unit varies in the whole strata. The problem is formulated as non-linear programming problem which is solved by using Bellman’s principle of optimality. For numerical illustration an example is presented for uniformly distributed study variable

New Exponential Ratio Estimator in Ranked Set Sampling

In this study, we adapted the families of estimators from Ünal and Kadilar (2021) using the exponential function for the population mean in case of non-response for simple random sampling for the estimation of the mean of the population with the RSS (ranked set sampling) method. The equations for the MSE (mean square error) and the bias of the adapted estimators are obtained for&nbsp; RSS&nbsp; and it, in theory, shows that the proposed estimator is additional efficient than the present RSS mean estimators in the literature.&nbsp; In addition, we support these theoretical results with real COVID-19 real data and conjointly the simulation studies with different distributions and parameters. As a result of the study, it was observed that the efficiency of the proposed estimator was better than the other estimators

ISSN: 2454-132X Impact factor: 4.295 A Statistical study on Network Service Providers in Kashmir

Abstract-Survey methodology studies the sampling of individual from a population and data collection with a view towards making statistical inferences about the population represented by the sample and the constructs represented by the measures. In this paper, data has been collected from different colleges related to network service providers and statistical analysis has been made in MINITAB with many conclusions like the students belonging to rural are more using cell phones rather than urban students. Not only this but also, majority of the students are of the opinion that mobile has a large bad effect on children. The graphical representation has been given with respective contents included in the paper

A New-Fangled Ratio-Type Exponential Estimator for Population Variance using Auxiliary Information

This manuscript provides new exponential ratio type estimator in simple random sampling for estimating the population variance using auxiliary information. The key purpose of this paper is to propose a new estimator and to increase the efficiency of the estimator for the population variance. The proposed exponential product-type estimator’s bias and mean square error expressions have been derived. The optimum value of the characterizing scalar has been found, which minimizes the MSE of the proposed estimator. The proposed estimator was theoretically compared to competing estimators. It is shown that the proposed estimator outperforms its competitors. To demonstrate the practical use of different estimation formulae and empirically demonstrate the efficiency of the constructed estimators, a numerical analysis is conducted using real data sets

Modified Regression Estimators for Improving Mean Estimation -Poisson Regression Approach

In this article, a class of Poisson-regression based estimators has been proposed for estimating the finite population mean in simple random sampling without replacement (SRSWOR). The Poisson-regression model is the most common method used to model count responses in many studies. The expression for bias and mean square error (MSE) of proposed class of estimators are obtained up to first order of approximation. The proposed estimators have been compared theoretically with the existing estimators, and the condition under which the proposed class of estimators perform better than existing estimators have been obtained. Two real data sets are considered to assess the performance of the proposed estimators. Numerical findings confirms that the proposed estimators dominate over the existing estimators such as Koc (2021) and Usman et al. (2021) in terms of mean squared error

Soil Quality Index as Affected by Integrated Nutrient Management in the Himalayan Foothills

Soil quality assessment serves as an index for appraising soil sustainability under varied soil management approaches. Our current investigation was oriented to establish a minimum data set (MDS) of soil quality indicators through the selection of apt scoring functions for each indicator, thus evaluating soil quality in the Himalayan foothills. The experiment was conducted during two consecutive years, viz. 2016 and 2017, and comprised of 13 treatments encompassing different combinations of chemical fertilizers, organic manure, and biofertilizers, viz. (i) the control, (ii) 20 kg P + PSB (Phosphorus solubilizing bacteria), (iii) 20 kg P + PSB + Rhizobium, (iv) 20 kg P + PSB + Rhizobium+ FYM, (v) 20 kg P + 0.5 kg Mo + PSB, (vi) 20 kg P + 0.5 kg Mo + PSB + Rhizobium, (vii) 20 kg P + 0.5 kg Mo + PSB + Rhizobium + FYM, (viii) 40 kg@ P + PSB, (ix) 40 kg P + PSB + Rhizobium, (x) 40 kg P + PSB + Rhizobium+ FYM, (xi) 40 kg P + 0.5 kg Mo + PSB, (xii) 40 kg P + 0.5 kg Mo + PSB + Rhizobium, and (xiii) 40 kg P + 0.5 kg Mo + PSB + Rhizobium + FYM. Evaluating the physical, chemical, and biological indicators, the integrated module of organic and inorganic fertilization reflected a significant improvement in soil characteristics such as the water holding capacity, available nitrogen, phosphorus, potassium, and molybdenum, different carbon fractions and soil biological characteristics encircling microbial biomass carbon (MBC), and total bacterial and fungal count. A principal component analysis (PCA) was executed for the reduction of multidimensional data ensued by scoring through the transformation of selected indicators. The soil quality index (SQI) established for different treatments exhibited a variation of 0.105 to 0.398, while the magnitude of share pertaining to key soil quality indicators for influencing soil quality index encircled the water holding capacity (WHC), the dehydrogenase activity (DHA), the total bacteria count, and the available P. The treatments that received an integrated nutrient package exhibited a higher SQI (T10—0.398; T13—0.372; T7—0.307) in comparison to the control treatment (T1—0.105). An enhanced soil quality index put forth for all organic treatments reflected an edge of any conjunctive package of reduced synthetic fertilizers with prime involvement of organic fertilizers over the sole application of inorganic fertilizers