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Alternaría alternata were isolated and identified from root, foliage and soil of both wheat and rice crops and their aggressiveness was studied using aggressiveness analysis. Isolates of Alternaría alternata were genetically characterized using RAPD's. The investigations were based on surveys of wheat and rice crops in the rice-wheat cropping areas of Pakistan. The study showed that Alternaría alternata is root rot causing fungi and during root rot aggressiveness analysis the isolates showed higher aggressiveness on rice varieties than on wheat but in foliar aggressiveness the overall number of aggressive isolates was higher on wheat varieties than on rice. In genetic characterization Random Amplified Polymorphism DNA (RAPD) was used to study the polymorphism and genetic variation within the population of Alternaría alternata that established correlation between aggressiveness and genetical characters of fungi. Alternaría alternata tree is constructed based on the pattern of bands. This study highlighted the correlation between morphological, aggressiveness and genetic variations of Alternaría alternata.
In this paper, we combine the recent development on mathematical statistics with modern chemistry in order to provide a new approach for soil quality analysis. Precisely, from modern chemistry we use near-infrared reflectance (NIR) spectroscopy procedure as a fast, accurate and inexpensive tool to evaluate chemical properties. Based on the collected data, the relationship between soil quality variables is modeled by using the functional statistics, which allows for analyzing a data as a curve or an image. The used predictor models are functional classical regression (FCR), functional local linear regression (FLLR), functional relative error regression (FRER) and functional robust regression (FRR). We prove that the performance of these models is closely linked to the homogeneity of the data. Considering the Abisko soil data, we show that FNR and FLLR are suitable for soil organic matter data, while for the Ergosterol concentration data the use of FRER and FRR are adequate. Furthermore, the proposed functional approach, permits us to avoid many drawbacks of the classical approach as principal component regression (P.C.R.).
In this study, at-site frequency analysis (AFA) of an annual daily maximum rainfall (ADMR) series was carried out using the method of linear moments (L-moments) and their variants such as trimmed linear moments (TL-moments) and higher order linear moments (LH-moments). The ADMR series we investigated was observed at 28 meteorological observatories across Pakistan as retrieved from the Pakistan Meteorological Department (PMD). The basic aim of the study was to fi nd best-fit (i.e., the most suitable) probability distribution among the class of various probability distributions. Initially different goodness-offit (GOF) measures such as the Kolmogorov-Smirnov test (KST), Anderson-Darling test (ADT), root mean square error (RMSE) and L-moments ratio diagram (LRD) were applied to determine not only the best-fit distributions but also the best linear estimation method for AFA. We observed that no single probability distribution could be declared as the best-fi t distribution for all the stations. Five distributions were found to be the most appropriate: generalized extreme value (GEV), three parameter lognormal (LN3), Pearson type III (P3), generalized logistic (GLO), and generalized pareto (GPA). The TL-moments method was also applied for parameter estimation to mitigate the effect of outliers on fi nal estimates. LH-moments were used for estimating the upper part of probability distributions and larger events in the data samples. LH moments alleviate the unwanted affects due to small sample values that may be obvious during estimation of events related to larger return periods. Using different GOF tests, we observed that the L-moments method was best for eight stations, TL-moments with trimming (1, 0), and LH-moments with level η =2, 3, 4 were best for six and 14 stations, respectively. A theoretical relationship between TL-moments and LH-moments was also revisited, which revealed that LH-moments are special cases of TL-moments when we are motivated to make trimming only from the lower side.
We evaluated morphometric parameters of the Haro River drainage network to determine flooding potential in the river basin. The drainage network is derived from topographic maps while using shuttle radar topography mission digital elevation model (SRTM-DEM) and geographic information systems (GIS). A total of 2917 streams (dendritic to semi-dendritic) are recognized, among which 1,536 are identified as first-order streams, followed by 731 as second order, 360 as third order, 173 as fourth order, 78 as fifth order, and 39 as sixth order. Linear and areal morphometric parameters revealed lower values for form factor (0.25), stream frequency (0.99), and drainage density (0.84 km/ sq.km), which suggest that the basin is being elongated with permeable strata; whereas lower values of mean bifurcation ratio (2.0) and relief ratio (20.68) indicate less potential for flooding in the main river channel. Understanding drainage morphometry could bring better hydrological solutions for similar studies.
In order to evaluate the phenotypic effects of implanted neural stem cells (NSCs) in the mouse model of Niemann-Pick C (NPC) disease, we injected a well-characterized clone of murine NSCs into the cerebella of neonatal Npc1-/- and control mice. The implanted cells survived and were abundant in some regions of the cerebellum. Life span was lengthened in NPC mice with the implanted NSCs. However, the rate of weight gain and subsequent weight loss, resulting from neurodegeneration, was not significantly different from un-injected controls. Ataxia was measured by Rota-Rod performance. The overall rate of decline in time on the Rota-Rod was not significantly slowed down. Thus, in this small group of NPC mice, a single administration in the neonatal period of the NSCs (which were not engineered to over-express the missing gene and not directed into the parenchyma) was only partially therapeutic.
For this paper we conducted a regional analysis (RA) of annual peak flows using linear combination of order statistics, i.e., linear-moments (LM) and trimmed linear moments (TLM). Design flood estimates are calculated and compared at different return periods, which are useful for water resources management, including hydrological structures and basin management. The main objective of our study was to compare regional design flood estimates for untrimmed and trimmed samples. LM is the special case of TLM, when we have no trimming from either side. First, regional flood frequency analysis is performed for LM and then for TLM. After initial screening of the annual peak flow series, a discordancy measure was used to diagnose the discordant sites. No site was found to be discordant. For homogeneity of the region, the homogeneity measure “H” was employed using simulation study based on Kappa distribution, and found that the nine sites on the Indus Basin included in the study constitute a single homogeneous region. In this study we used TLM with trimming values (γ, 0), where γ = 1, 2, 3, 4. In order to determine the most appropriate probability distribution for regional quantile estimates, different probability distributions are used, namely: generalized extreme value (GEV), generalized pareto (GPA), generalized logistic (GLO), Pearson type three (PE3), and generalized normal (GNO). L-moments ratio diagram and Z-test as goodness of fit are engaged to identify the most suitable probability distribution. A comparison revealed that GNO is the best distribution for first three cases as (0, 0), (1, 0), and (2, 0), while for the last two cases of (3, 0) and (4, 0) the most appropriate choice is GEV. A simulation study was also carried out to evaluate the performance and robustness of the best fit probability distribution using relative bias (RB) and relative root mean square error (RRMSE).
Endoxifen, an active metabolite of tamoxifen, has been shown to be an effective anti-estrogenic agent in estrogen receptor-positive breast cancer patients. In melanoma, estrogen receptor expression is shown to be associated with disease progression. However, the therapeutic benefit of endoxifen in melanoma has not yet been evaluated. Here, we present the first demonstration of the anti-melanogenic activity of endoxifen in vitro and in vivo. The in vitro cytotoxic effect of endoxifen was tested using a cell viability assay. The in vivo anti-melanogenic activity was evaluated in B16F10 cell-bearing C57BL/6 mice, a mouse melanoma model. The general toxicity was tested in Swiss albino mice. Endoxifen exhibited greater activity against melanoma cell lines. Treatment of B16F10 mouse and SK-MEL-5 human melanoma cell lines with 10 μM of endoxifen for 48 h respectively resulted in 93.6 and 92.5% cell death. Orally administered endoxifen, at dose levels of 4 and 8 mg/kg body weight/day for 20 consecutive days, respectively reduced metastatic melanoma nodules in the lungs by 26.7 and 82.7%. Endoxifen was found to be a safe and effective anti-melanogenic agent in animal studies.
The contamination of soil and water with heavy metals is one of the major environmental problems in the world. Oil and gas exploration and production activities contaminate the environment with heavy metals. In this study, heavy metal concentration was assessed in drilling waste discharges of different oil and gas wells at Khyber Pakhtunkhwa (KP), Pakistan. Moreover, the concentration of heavy metals in the soil surrounding the drilling waste discharges was determined. The representative samples were collected from seven oil and gas drilling waste discharges and the surrounding soil. The collected samples were analyzed for selected heavy metals (Ba, Pb Cr, Cd, Zn, Mn, and Ni) by atomic absorption spectrometric standard methods. Analysis showed that oil and gas well drilling operation waste is enriched with determined heavy metals. The high concentration of heavy metals, particularly Ba and Pb, was also found in the surrounding soil samples. In particular, Ba concentration varied from 1050 to 4168 mg/kg soil. Statistical correlational analysis depicted a common origin of the heavy metals in the soil of the study area, potentially the drilling waste discharges from oil and gas wells. The concentration of heavy metals in oil and gas well drilling waste discharge high, and also affects surrounding soils.
This research investigates the spatial and temporal trend analysis of precipitation time series. Precise predictions of precipitation trends can play an imperative role in economic growth of a country. This study examined precipitation inconsistency for 23 stations at Dongting Lake, China, over a 52-year study period (1961-2012). Statistical, nonparametric Mann- Kendall (MK) and Spearman’s rho tests were applied to identify trends within monthly, seasonal, and annual precipitation. The trend-free pre-whitening method was used to exclude sequential correlation in the precipitation time series. The performance of the Mann-Kendall (MK) and Spearman’s rho tests was steady at the tested significance levels. The results showed a fusion of increasing and decreasing trends at different stations within monthly and seasonal time scales. The results obtained with the Mann-Kendall and Spearman’s rho tests showed agreement in their assessments of monthly, seasonal, and annual precipitation trends. The variability of negative and positive trends at various stations points to the need for more detailed studies on the climate change of this region. In the case of whole Dongting basin on the monthly time scale, a significant positive trend is found, while at Yuanjiang River and Xianjiag River both positive and negative significant trends are identified. Only Yuanjiang River has shown a significant trend on the seasonal time scale. No significant trends have been exhibited on the annual time scale in any case. In the case of monthly, Nanxian station exhibited the maximum positive increase in monthly precipitation during the months of July and September. In the case of seasonal, only Tongren station showed a positive trend on the monthly level, and no significant negative trends were detected in both spring and autumn seasons.
The present invention was undertaken to study and determine the effect of potassium metabisulphite (6%) and potassium sorbate (350 ppm) treatments on the nutritional quality of osmotically-dehydrated, infrared- and microwave-blanched dried mango slices (local cultivars “Chaunsa” and “Fajri”) stored for the period of 6 months under ambient conditions. The studied parameters included physical characteristics such as water activity, non-enzymatic browning, and color values, chemical parameters such as moisture, ash, fi ber, acidity and content of proteins, sugars, vitamin C, total carotenoids, and sensory attributes such as appearance, fl avor and texture. Vitamin C content in osmotically-dried mango slices was higher than that of IR and MW blanched dried mango slices but the content of vitamin C of both cultivars was lower than of the fresh mango samples (Chaunsa: 135 mg/100 g, Fajri: 94 mg/100 g). Signifi cant loss was noticed in total carotenoids content of both the cultivars with passage of time because of their susceptibility to oxidative loss caused by dry heat. No growth of yeast and mold was detected in potassium sorbate-treated dried mango slices due to their preservative effect. From the point of view of the composition and sensory quality, dried mango slices of both the cultivars have excellent nutritional qualities.
Seed pre-sowing magnetic field treatment was reported to induce biochemical and physiological changes. In the present study, response surface methodology was used for deduction of optimal magnetic field doses. Improved growth and yield responses in the pea cultivar were achieved using a rotatable central composite design and multivariate data analysis. The growth parameters such as root and shoot fresh masses and lengths as well as yield were enhanced at a certain magnetic field level. The chlorophyll contents were also enhanced significantly vs. the control. The low magnetic field strength for longer duration of exposure/ high strength for shorter exposure were found to be optimal points for maximum responses in root fresh mass, chlorophyll ‘a’ contents, and green pod yield/plant, respectively and a similar trend was observed for other measured parameters. The results indicate that the magnetic field pre-sowing seed treatment can be used practically to enhance the growth and yield in pea cultivar and response surface methodology was found an efficient experimental tool for optimization of the treatment level to obtain maximum response of interest.
The present study was conducted in a potted experiment to examine the effects of chromium pollution on absorption of mineral nutrients and some morphophysiological attributes of two sunflower (Helianthus annuus L.) hybrids (FH-331 and FH-259) in the presence and absence of ethylene diamine tetra acetic acid (EDTA) used as a chelating agent. Four concentrations of chromium (Cr³⁺) i.e., 0, 20, 30 and 40 mg kg⁻¹ with and without 0.3 g kg⁻¹ , EDTA as chelating agent were applied to 25-day-old sunflower plants. A gradually decreasing trend in absorption of all minerals and other parameters studied were observed. Different treatments of Cr³⁺ as well as Cr³⁺ and EDTA significantly reduced root and shoot fresh weight; however, root, shoot and achene Cr³⁺ contents of two sunflowers hybrids under higher chromium and EDTA stress varied significantly whereas movement of Cr³⁺ contents to leaves was non-significant. Absorption of Na⁺, K⁺, N₂ and P through roots and shoots significantly reduced with increasing concentration of Cr³⁺ treatments. In fact addition of EDTA to the medium further enhanced the toxicity of chromium.
In this study we investigated the projections of climate change and its impacts on the water resources of the Xin’anjiang watershed and optimal hydropower production using future run-offs (the decades of the 2020s, 2050s, and 2080s). The arc SWAT hydrological model and change factor downscaling technique were integrated to detect the run-offs and to downscale CMIP5 future climate variables, respectively. Optimal hydropower generation using future runoff was predicted by developing a mathematical model and by applying the particle swarm optimization technique within its paradigm. The results depict an increase of up to 5.9ºC in monthly mean maximum temperature, and 5.58ºC in minimum temperature until the 2080s. There will be a 63% increase in flow magnitudes more than the base year flow during the 2020s, whereas up to 70% and 31.40% increments have been observed for the 2050s and 2080s, respectively. The results revealed potential hydropower generation of 19.23*10⁸ kWh using 2020s runoff of rainy years. Similarly, 19.35*10⁸ kWh and 14.23*10⁸ kWh were estimated from the flows during the 2050s and 2080s, respectively.
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