In this chapter we give a survey for the use of sinc methods in computing eigenvaluesEigenvaluesof various types of boundary value problems. The techniques cover the classical sinc-method, regularized sinc-method, Hermite interpolations and the associated regularized technique, sinc-Gaussian, Hermite-Gauss and generalized sinc-Gaussian methods. The application of these methods covers a very wide class of problems, involving, but not limited to, second order differential operators, λ-type problems in L2(a,b)⊕ℂr$$L^{2}(a,b)\oplus \mathbb {C}^{r}$$spaces, discontinuous problems, multiparameter problems, in self-adjoint and non self-adjoint settings, regular and singular problems. Both horizontal and vertical extensions of the application of the technique are still open and under consideration.

Excessive salt accumulation in soils is a major ecological and agronomical problem, in particular in arid and semiarid areas. While important physiological insights about the mechanisms of salt tolerance in plants have been gained, the transfer of such knowledge into crop improvement has been limited. The identification and exploitation of soil microorganisms (especially rhizosphere bacteria and mycorrhizal fungi) that interact with plants by alleviating stress opens new alternatives for a pyramiding strategy against salinity as well as
new approaches to discover new mechanisms involved in stress tolerance. Considering the kingdom of fungi, arbuscular mycorrhizal fungi (AMF) stand out as the most significant and widespread group of plant growth–promoting microorganisms. Ectomycorrhizal fungi (EMF) are also important symbionts of particular relevance for many woody plants. Considering the kingdom of bacteria, a wide range of microorganisms including different species and strains of Bacillus, Burkholderia, Pseudomonas, and the well-known nitrogen-fixing organisms
Rhizobium, Bradyrhizobium, Azotobacter, Azospirillum,
and Herbaspirillum are classically regarded as
important plant growth–promoting rhizobacteria
(PGPR). Today, it is widely accepted that
AMF, EMF, and PGPR promote plant growth and
increase tolerance against stress conditions, at
least in part, because they facilitate water and
nutrient uptake and distribution as well as alter
plant hormonal status, and this ability has been
attributed to various mechanisms. This chapter
addresses the significance of soil biota in alleviation
of salinity stress and their beneficial effects
on plant growth and productivity. Moreover,
it emphasizes new perspectives and challenges
in physiological and molecular studies on salt
stress alleviation by soil biota.

Optimization algorithms are necessary to solve many problems such as parameter tuning. Particle Swarm Optimization (PSO) is one of these optimization algorithms. The aim of PSO is to search for the optimal solution in the search space. This paper highlights the basic background needed to understand and implement the PSO algorithm. This paper starts with basic definitions of the PSO algorithm and how the particles are moved in the search space to find the optimal or near optimal solution. Moreover, a numerical example is illustrated to show how the particles are moved in a convex optimization problem. Another numerical example is illustrated to show how the PSO trapped in a local minima problem. Two experiments are conducted to show how the PSO searches for the optimal parameters in one-dimensional and two-dimensional spaces to solve machine learning problems.

This paper presents proposed performance criteria evaluation based on a comparison between sentiment techniques. The target is measuring the sentiments performance through several significant perspectives in sentiment analysis. This measurement is very tight of accuracy evaluating for sentiments. However, evaluating sentiments is a hard challenge for language technologies, and achieving good results is much more difficult than some human think. Also, we introduce a comprehensive study for different sentiment techniques based on proposed performance criteria. The performance evaluation plays a vital role in accuracy measurement through a sentiment analysis word level. The performance criteria include two types of performance measurement namely F-measure and Runtime. These criteria include the balance of performance perspectives priorities. These types include a relationship between perspectives of performance to improve it. There are different performance perspectives: F-measure and speed of run time, memorability, and sentiment analysis challenges. It helps in understanding the contextual meaning and getting a score in less time and higher accuracy. The comparisons are based on the sentiment analysis word-level. They can understand some phrases as do not directly through caring with the classification of reviews. Finally, we show the efficiency and effectiveness of the proposed criteria.