Indian medicinal plants are used since ancient times to treat different diseases and ailments as these natural products exert broad-spectrum actions. The present study was justifiably planned to raise the callus of valuable medicinal plant Holarrhena antidysenterica L. in in vitro condition with various combinations/concentrations of plant growth regulators, and to compare the antioxidant and phytochemical content difference in the in vivo plant and in vitro grown callus of Holarrhena antidysenterica. The callus and crude extracts were used for total phenolic contents, primary metabolite detection and antioxidant activity by (DPPH and OH radical scavenging methods). Maximum callus (88.19%) was obtained on MS medium supplemented with (2, 4-D+Kinetin) at (2.0+1.5)mg/L. Significantly higher DPPH scavenging activity (85.11%) at 280μg/ml and (58.34%) at 240μg/ml in both the extracts i.e. leaf and callus in comparison to OH scavenging activity (74.11%) at 280μg/ml and (50.30%) at 240μg/ml with phenol contents (2.11mg/g) and (1.53mg/g) were observed in leaf and in vitro raised callus extract respectively. The findings indicates greater amount of phenolic compounds leads to more potent radical scavenging effect as shown by leaf extracts of Holarrhena antidysenterica and the ability to utilize tissue culture techniques towards development of desired bioactive metabolites from in vitro culture as an alternative way to avoid using endangered plants in pharmaceutical purposes.
This paper proposes a novel approach for overcoming the bottleneck in financial data mining. In this study, a composite kernel machine (CKM) on a kernel local fisher discriminant space (KLFDS) was constructed for solving three problems in high-dimensional financial data mining: the curse of dimensionality, data complexity and nonlinearity. The CKM exploits multiple data sources with strong capability to identify the relevant ones and their apposite kernel representation. KLFDS is an optimal projection of original data to a low dimensional space which maximizes the margin between data points from different classes at each local area of a data manifold. This new system robustly overcomes the weaknesses of CKMs, and outperforms many traditional classification systems.
The question is whether biomass energy development can meet rising global electricity demand amid international concerns over fossil fuel dependence, global warming, and land use conflicts. A causal loop diagram illustrates the interrelationships between factors that positively and negatively influence the development of biomass as a renewable energy fuel. This research presents a life cycle assessment (LCA) of biomass energy systems to analyze some of the limiting factors. Limiting factors such as increased land use, fossil fuel use, and corresponding CO2 emissions influence further international biomass development efforts. The life cycle assessment evaluated alternative processes that might increase efficiency. The LCA revealed that integrating Salix short-rotation forests, biological fertilizers, and integrated gasification technologies into the biomass energy system would reduce fossil fuel use and CO2 emissions by 74 percent and land use by roughly 97 percent. Biomass energy systems can become much more efficient and competitive sources of renewable electricity by implementing Salix, biological fertilizer, and gasification technologies.
A single phase regenerative shunt active filter is proposed in this paper. This proposed converter consists of single phase Voltage Source Converter (VSC). It works as a shunt active filter during addition of harmonics by nonlinear loads and a rectifier after the reduction of harmonics. This conversion is done by controlling the gate pulses to the converter. The converter has advantages like reduced circuit complexity, low cost, best harmonic reducer of both low & higher order, compared to conventional shunt active filter. In this work, the switching of the converter is controlled by using the Fuzzy and neural controllers. The hysteresis current controller is used for giving the PWM pulses to the proposed converter. The single phase full bridge and half converter are used as nonlinear loads. The simulations are done with the help of MATLAB/Simulink software and the results illustrate the effectiveness of the proposed Active Regenerative Filter (ARF).
The main purpose of this paper is investigating causal relationships and ranking effective mediator factors in market-orientation on business performance. This research is practical in terms of goal and it is qualitative depending on data type. Statistical population includes employees of Iran Khodro Industrial Group. Sample size was calculated 118 according to the Cochran formula. Sampling method was Simple random. In this study, questionnaires were used as essential tools for data collection and data were analyzed using Lisrel software. The results of this study show a positive relationship between market-orientation and business performance in Iran Khodro Company.
Recent developments in the renewable energy sector suggest that the wind turbine and photo voltaic as Distributed Generation systems in the distribution network is gaining popularity as a new source of energy. One of the important factors associated with the traditional network is that their protection and setting scheme are inadequate when a distributed generation system is connected to the network as the protection and control requirement of the distributed generators is different than the transmission network. Thus, this interconnected system consistently imposes new challenges in the power system stability. This study investigates the affect of distributed generators on distribution network during fault condition and includes voltage dips, transients and line short circuit fault current. The robust and effective fast switching of the circuit breakers acts as a protection system with respect to these fault conditions. This study is also valid for sources like photo voltaic, although only wind turbines are selected as an example.
This research is about software project scheduling and use of earned value method on software projects. As a result of the study, a solution for software project scheduling problems is proposed. A mathematical formulation, developed using integer programming method, is at the heart of the solution. Objective of the formulation is to minimize the development costs consisting of direct labor cost, indirect costs and probable penalty costs. The formulation takes the capability and compatibility variances among resources into account whereas contemporary approaches mostly focus on resource availability. Formulation is of type discrete time and takes the time span to be searched as input. Therefore a heuristic approach has been developed for providing time span input to the models developed using the formulation. The heuristic approach has been proven to be calculating a time span that does not hinder achieving the absolute optimum schedule and shortens the solution time of the integer programs. The heuristic approach and problem formulation have been incorporated into a computer program that generates integer programs and heuristic solutions. This research also describes a method for preparing an earned value plan, based on the scheduling solution defined. The method aims to help project managers in determining the status of their projects and deciding whether any corrective action is required or not. Besides the method, approaches for incorporating indirect costs and penalty costs, which are not explicitly discussed in literature, into final cost estimation have been described.