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Introduction: Patient satisfaction is an important component of quality nursing care and is often determined by the nursing care in any health institution. The aim of the study is to find the presence of satisfaction among in-ward patients of five major wards at a tertiary care hospital regarding the quality of care provided by nursing staff. Methods: A descriptive cross-sectional study was conducted among 105 patients of Patan Hospital from 3rd July to 3rd August, 2015 after obtaining ethical clearance from Institutional Review Committee. Sample size was calculated and stratified random sampling was done. Data was collected in Microsoft Excel and analyzed in Sta 13.0. Point estimate at 95% Confidence Interval was calculated and frequency and percentage was calculated for binary data. Subgroup analysis was done on the basis of demographic variables. Results: Among 105 patients, 99 (94.3%) [94.93-95.07 at 95%CI] were satisfied with the nursing care provided at a tertiary care center in Nepal. Among them, 60 (60.6%) were females and 39 (39.4%) were males. Age of the patients ranged from 1 year to 85 years. The length of the stay in the hospital ranged from 2 to 17 days (mean = 5.6 days). Conclusions: Most of the patients were satisfied with the nursing care provided in a tertiary care centre. Routine nursing care surveys and immediate feedbacks would keep the authorities updated and deliver good health care.

Feasibility of near-infrared (NIR) spectroscopy for developing multi-species model for plantation timber was explored for estimation of holocellulose in un-extracted milled wood samples. Six commonly planted species of Eucalyptus tereticornis, E. camaldulensis, E. grandis, Leucaena leucocephala, Dalbergia sissoo and Populus deltoides from a wide range of locations and varying age groups were taken for the present study. Few samples of E. hybrid between E. tereticornis and E. camaldulensis were also included in the study to make the model useful for practical application. NIR models were evaluated using partial least squares regression (PLSR-1—full cross-validation, PLSR-2—cross-validation which leaves more than one out) and by dividing the samples into calibration and prediction (test) sets and interchanging them from calibration to prediction sets. The predictive ability of the model was assessed by calculating four ratios of multivariate statistics for individual species model and combined species models. A final combined model for all the species having component range of 76.14–63.03 % and standard deviation of 2.586 % was developed in the spectral range of 7502–4246 cm−1 wave number using 1st derivative plus multiplicative scatter correction using factor of nine by removing samples with outliers found in all the PLSR-2 evaluation steps and in most of the models. The model remained stable even when 30 % of the samples were left out with no outlier detected.

Guaranteeing reliable and ubiquitous signal reception is one of the current challenges faced by wireless communications systems. Ideally, wireless transmissions suffer only from propagation losses. In reality, the landscape through which wireless information travels often contains structures that contribute to significant losses in signal reception. While increasing broadcast power will boost signal integrity, it will invariably contribute to increased co-channel interference. The high demand for ubiquitous signal reception, coupled with the aforementioned challenges, has motivated research into the development of propagation prediction models based upon extensive spatio-temporal wireless channel measurements.