Effect of Nitrogenous Fertilizer on the Vegetative Growth and Yield Attribute of Pea (Pisum sativum L.)

An experiment was conducted to study the effect of chemical fertilizer on the pea growth and yield attributes. Therefore, the main objective of this study was to investigate the effect of chemical fertilizer alone and in combination. This study consists of three different nitrogen levels (90, 100 and 110 kg ha-1as urea), three different levels of phosphorus (60, 70 and 80 P2O5 kg ha-1 as DAP) and their combination. Treatments were arranged in a complete randomized block design with three replications. The results showed that both the single and combined application of nitrogen and phosphorus fertilizer increased the growth and yield attribute of the pea plant. Maximum number of primary (6.91) and secondary branches per plant (7.97), number of leaves per plant (12.50) and plant height (51.24 cm) was attained by the combine application of P80+N110. Similarly, the maximum increase in yield parameters such as pod length (7.5 cm), number of pods per plant(7.23), pod weight (12.50 g) and number of grains per pod was obtained in P80+N110. In general, combined application of fertilizers significantly increased all the growth and yield attribute of the pea plant when compared to fertilizers applied alone with respect to control

The Influence of Plastic Mulching Materials and Sowing Dates on the Yield and Yield Components of Pea (Pisum sativum L.)

The use of plastic mulches affects the microclimate in the vicinity of the plant by modifying the radiation on the soil surface and reduce the loss of water. Pea is more nutritious and 2nd food source after cereals at Pakistan, but due to lake of proper management, yield is still not up to mark as compare to developed world. To reduce this problem, a field experiment was conducted to investigate the effect of mulching material and sowing dates on the yield of Pea. The study consisted of three different mulching materials (Polythene Black, Polythene Blue and Polythene Brown) with three different sowing dates (1st, 15th and 30th October) arranged in a Randomized Complete Block Design with three replications. The results showed that different sowing dates and mulching materials had significant effect on the yield parameters of Pea. Regarding sowing dates, maximum days to pod formation (8.08 days), pods plant?1 (21.25), Pod weight (18.84 g) and pod yield (4.39 tons ha?1) were noted in pea sown on October 1st. Whereas, minimum data of days to pod formation (3.08 days), pod plant?1 (15.34), pod weight (13.17 g) and pod yields (2.69tons ha?1) were recorded in pea sown on October 30th. In case of mulching types maximum number of pods plant?1 (19.00), pod length (6.89 cm), seeds pod?1 (7.78), pod weight (17.34 g) and pod yield (3.69 tons ha?1) were observed in pea mulched with Polythene Black, while minimum pods plant-1, pod length, seeds pod-1, pod weight and pod yield were found in control. The study suggested that pea should be sown on October 1st while mulched with Polythene Black to produce maximum yield and production in agro environment of district Peshawar

Effect of Integrated Marketing Communications on Consumer Buying Decision of Internet Service (An Empirical Study of Mobilink in Multan City)

The study finds how IMC influence the consumer decision to buy internet services; which include (internet marketing, public relations, advertising, sales promotion, direct marketing). Questionnaire were used for data collection and 435 questionnaires were distributed among Mobilink service users. The results showed that internet marketing, public relations, advertising, sales promotion and direct marketing positively influence consumer buying decision. The paper recommended that Mobilink should focus more on public relations with related parties to create a positive image about Mobilink which will enhance their buying decision of internet service

Bayesian, Maximum Parsimony and UPGMA Models for Inferring the Phylogenies of Antelopes Using Mitochondrial Markers

This investigation was aimed to compare the inference of antelope phylogenies resulting from the 16S rRNA, cytochrome-b (cyt-b) and d-loop segments of mitochondrial DNA using three different computational models including Bayesian (BA), maximum parsimony (MP) and unweighted pair group method with arithmetic mean (UPGMA). The respective nucleotide sequences of three Oryx species (Oryx leucoryx, Oryx dammah and Oryx gazella) and an out-group (Addax nasomaculatus) were aligned and subjected to BA, MP and UPGMA models for comparing the topologies of respective phylogenetic trees. The 16S rRNA region possessed the highest frequency of conserved sequences (97.65%) followed by cyt-b (94.22%) and d-loop (87.29%). There were few transitions (2.35%) and none transversions in 16S rRNA as compared to cyt-b (5.61% transitions and 0.17% transversions) and d-loop (11.57% transitions and 1.14% transversions) while comparing the four taxa. All the three mitochondrial segments clearly differentiated the genus Addax from Oryx using the BA or UPGMA models. The topologies of all the gamma-corrected Bayesian trees were identical irrespective of the marker type. The UPGMA trees resulting from 16S rRNA and d-loop sequences were also identical (Oryx dammah grouped with Oryx leucoryx) to Bayesian trees except that the UPGMA tree based on cyt-b showed a slightly different phylogeny (Oryx dammah grouped with Oryx gazella) with a low bootstrap support. However, the MP model failed to differentiate the genus Addax from Oryx. These findings demonstrate the efficiency and robustness of BA and UPGMA methods for phylogenetic analysis of antelopes using mitochondrial markers

Optimal energy management of a campus microgrid considering financial and economic analysis with demand response strategies

An energy management system (EMS) was proposed for a campus microgrid (µG) with the incorporation of renewable energy resources to reduce the operational expenses and costs. Many uncertainties have created problems for microgrids that limit the generation of photovoltaics, causing an upsurge in the energy market prices, where regulating the voltage or frequency is a challenging task among several microgrid systems, and in the present era, it is an extremely important research area. This type of difficulty may be mitigated in the distribution system by utilizing the optimal demand response (DR) planning strategy and a distributed generator (DG). The goal of this article was to present a strategy proposal for the EMS structure for a campus microgrid to reduce the operational costs while increasing the self-consumption from green DGs. For this reason, a real-time-based institutional campus was investigated here, which aimed to get all of its power from the utility grid. In the proposed scenario, solar panels and wind turbines were considered as non-dispatchable DGs, whereas a diesel generator was considered as a dispatchable DG, with the inclusion of an energy storage system (ESS) to deal with solar radiation disruptions and high utility grid running expenses. The resulting linear mathematical problem was validated and plotted in MATLAB with mixed-integer linear programming (MILP). The simulation findings demonstrated that the proposed model of the EMS reduced the grid electricity costs by 38% for the campus microgrid. The environmental effects, economic effects, and the financial comparison of installed capacity of the PV system were also investigated here, and it was discovered that installing 1000 kW and 2000 kW rooftop solar reduced the GHG generation by up to 365.34 kg CO2/day and 700.68 kg CO2/day, respectively. The significant economic and environmental advantages based on the current scenario encourage campus owners to invest in DGs and to implement the installation of energy storage systems with advanced concepts

Potencial de protección de las semillas Trachyspermum ammi en la nefrotoxicidad inducida por la gentamicina en modelo de conejo

La nefrotoxicidad es uno de los efectos secundarios más importantes limitaciones terapéuticas de los antibióticos aminoglucósidos, especialmente gentamicina. La nefrotoxicidad inducida por gentamicina implica generación de radicales libres, la reducción en el mecanismo de defensa antioxidante y la disfunción renal. Una serie de extractos de hierbas crudas tienen potencial para mejorar la nefrotoxicidad inducida por gentamicina debido a la presencia de varios compuestos antioxidantes. Por lo tanto, el objetivo del presente estudio fue evaluar la actividad protectora del extracto acuoso semillas de T. ammi contra la nefrotoxicidad inducida por gentamicina en conejos albinos. Los resultados mostraron que la gentamicina causó graves alteraciones en los parámetros bioquímicos séricos y los marcadores de riñón, junto con alteraciones severas en los tejidos renales. Sin embargo, el extracto de T. ammi, cuando se administra junto con la gentamicina, invierte la gravedad de la nefrotoxicidad inducida por gentamicina por la normalización de los indicadores de la función renal, por ejemplo, urea sérica, creatinina, nitrógeno ureico en sangre, albúmina y los parámetros de electrolitos séricos que indican el potencial nefroprotector de T. ammi. Del mismo modo, el extracto tiene la capacidad para aumentar la maquinaria enzimática antioxidante endógena mediante un aumento de la actividad de la enzima antioxidante catalasa y reduciendo el estado total de oxidante. El potencial nefroprotector fue confirmado por el examen histopatológico. El potencial nefroprotector podría ser debido a la presencia de compuestos polifenólicos antioxidantes en el extracto acuoso de semillas de T. Ammi

Movie Tags Prediction and Segmentation Using Deep Learning

The sheer volume of movies generated these days requires an automated analytics for ef cient classi cation, query-based search, and extraction of desired information. These tasks can only be ef ciently performed by a machine learning based algorithm. We address the same issue in this paper by proposing a deep learning based technique for predicting the relevant tags for a movie and segmenting the movie with respect to the predicted tags. We construct a tag vocabulary and create the corresponding dataset in order to train a deep learning model. Subsequently, we propose an ef cient shot detection algorithm to nd the key frames in the movie. The extracted key frames are analyzed by the deep learning model to predict the top three tags for each frame. The tags are then assigned weighted scores and are ltered to generate a compact set of most relevant tags. This process also generates a corpus which is further used to segment a movie based on a selected tag. We present a rigorous analysis of the segmentation quality with respect to the number of tags selected for the segmentation. Our detailed experiments demonstrate that the proposed technique is not only ef cacious in predicting the most relevant tags for a movie, but also in segmenting the movie with respect to the selected tags with a high accuracy

Immense Industrialization And Their Air Prominent Pollutants Effect On Urban Air Quality Index

On the basis of the reported air quality index (API) and air pollutant monitoring data obtained at the Peshawar over the last seven years, the characteristics of air quality prominent pollutants and variation of the average annual concentrations of SO2, NO2total suspended particulate (TSP) fine particulates (PM10) CO and dust fall in Peshawar City were analyzed. Results showed that SO2and NO2were the prominent pollutants in the ambient air environment of Peshawar City. Of the prominent pollutants TSP accounted for nearly 63 % SO2, 32.8 ppb NO2, 147 ppb of CH4 , 13.8 ppb of CO, 94.5µg/m3of MC and 0.60 ppb of O3respectively in 2013. NO2to SO2 comparison ratio initially declined to 39.3 in 2009 and then starts to increase to 42.5 in 2010 while in 2013 reached upto 44.8 and O3 to SO2 ratio in the last year of observation, the ratio drop to 0.01830 µg/m3. Concentrations of air pollutants have shown a upward trend in recent years but they are generally worse than ambient air quality standards for EPA-USA, Pak and EU. SO2and NOx pollution were still serious impling that waste gas pollution from all kinds of vehicles had become a significant problem for environmental protection in Peshawar. The possible causes of worsening air quality were also discussed in this paper

Exergoeconomic optimization of a forward feed multi-effect desalination system with and without energy recovery

The escalating freshwater demand is stimulating the researchers to optimize the performance of desalination technologies. The current study presents the exergoeconomic optimization of a forward feed multi-effect desalination (FF-MED) system under two configurations i.e., conventional MED and MED with energy recovery (MED-ER). A detailed numerical model concerning energy, exergy, and a component-based exergoeconomic analysis is employed to estimate the energy consumption, exergy destruction, and water production cost. Thereafter, the FF-MED-ER system is optimized using a Genetic Algorithm for four different objective functions i.e., maximum gain output ratio (GOR), and minimum specific energy consumption (SEC), exergy destruction, and water production cost. The constraint variables included steam temperature, brine salinity, and the last effect brine temperature. The analysis showed that the incorporation of an energy recovery section increased GOR by 17.9% and decreased SEC and water production cost by 14%, and 10.5%, respectively. Moreover, the optimization improved GOR by 9.26%, decreased SEC by 12.86%, exergy destruction by 12.59%, and the water production cost by 8.25% compared to the standard nonoptimal system