We investigated MAXIMAL Prym varieties on  nite  elds by attaining their upper bounds on the number of rational points. This concept gave us a motivation for de ning a generalized de ni-tion of MAXIMAL curves i. e., MAXIMAL morphisms. By MAGMA, we give some non-trivial examples of MAXIMAL morphisms that results in non-trivial examples of MAXIMAL Prym varieties.

A vast number of organizational projects as well as complexity of decision making process can cause particular challenges for project management and its leadership. In order to use organization assets and opportunities efficiently, it is necessary that manager implement a comprehensive multidimensional project PORTFOLIO management system that considers economic, social and technical details of the projects. Resource constraint compels managers to select operational proposal projects. Thus managers can maximize organizational utility due to project PORTFOLIO’s resource constraint. This study considers the interactive effects of project PORTFOLIO evaluation and sharing organizational project resources with respect to its evaluation and choice of the projects. In this two-step model, first a branch and bound algorithm with resource interaction was utilized to screen MAXIMAL PORTFOLIO and, in the next step, each PORTFOLIO was evaluated based on artificial neural networks to rank the end project PORTFOLIOs. Also, the ANN scores are strongly correlated with the DEA and COLS efficiency scores.

An optimal labeling of a graph with $n$ vertices and $m$ edges is an injective assignment of the first $n$ nonnegative integers to the vertices‎, ‎that induces‎, ‎for each edge‎, ‎a weight given by the sum of the labels of its end-vertices with the property that the set of all induced weights consists of the first $m$ positive integers‎. ‎We explore the connection of this labeling with other well-known functions such as super edge-magic and $\alpha$-labelings‎. ‎A graph with $n$ vertices is MAXIMAL when the number of edges is $2n-3$; all the results included in this work are about MAXIMAL graphs‎. ‎We determine the number of optimally labeled graphs using the adjacency matrix‎. ‎Several techniques to construct MAXIMAL graphs that admit an optimal labeling are introduced as well as a family of outerplanar graphs that can be labeled in this form.

‎‎The PORTFOLIO optimization problem, including PORTFOLIO selection, typically aims to maximize return and minimize risk. In this paper, we discuss about increasing use of stochastic PORTFOLIOs in investments and aim to create optimal PORTFOLIOs. It follows the relative wealth process of these PORTFOLIOs, outperforms the market PORTFOLIO over sufficiently long time-horizons. In this regard, initially, a model of the market is presented by the stochastic PORTFOLIO theory (SPT) and features like Growth rate, Excess growth rate are mentioned. Then, functionally-generated PORTFOLIOs are defined by using diversity weighted PORTFOLIOs with parameters p ∈ (0, 1), p < 0 and combination of them. Finally, by obtaining the daily closing price of 10 stocks in Tehran Stock Exchange (TSE) ,the performance of diversity weighted PORTFOLIOs is investigated.

In this note we describe some recent advances in the area of MAXIMAL function inequalities. We also study the behaviour of the centered Hardy- Littlewood MAXIMAL operator associated to certain families of doubling, radial decreasing measures, and acting on radial functions. In fact, we precisely determine when the weak type (1, 1) bounds are uniform in the dimension.