The Impact of Small Group Instruction on Preschool Literacy Skills

This study focused on 17 preschool students in a northern Jordan city. Preschoolerswere taught specific literacy skills in a small group instructional setting. The students’ skill level was assessed at the beginning and middle of the school year. The researcher’s goal was to determine if teaching literacy skills in a small group setting would improve the skill level of the preschool students. Results showed that using small groups was an effective way to increase preschool students’ literacy skill levels

An Assessment of Bullying/Victimization Behaviors among Third-Graders in Jordanian Public Schools

This study investigates the prevalence of bullying/victimization behaviors among third graders in Jordanian public schools from the perspectives of both students and their teachers. The study involved 500 third-grade students and 52 teachers who randomly selected from 20 Jordanian public schools in the first Irbid directorate schools. Results of the students’ perceptions of bullying and victims of bullying behaviors indicated a generally low amount of bullying and victims of bullying among third graders. However, teachers reported more bullying by other students than the students reported. Also, teachers in this study reported physical bullying/victims of bullying as the most frequent and verbal bullying as the least frequent. Implications for ministry of education and schools were discussed. Key words: bullying, victimization, physical, verbal, relational

Material length scales in gradient-dependent plasticity/damage and size effects: theory and computation

Structural materials display a strong size-dependence when deformed non-uniformly into the inelastic range: smaller is stronger. This effect has important implications for an increasing number of applications in structural failure, electronics, functional coatings, composites, micro-electro-mechanical systems (MEMS), nanostructured materials, micro/nanometer fabrication technologies, etc. The mechanical behavior of these applications cannot be characterized by classical (local) continuum theories because they incorporate no ‘material length scales’ and consequently predict no size effects. On the other hand, it is still not possible to perform quantum and atomistic simulations on realistic time and structures. It is therefore necessary to develop a scale-dependent continuum theory bridging the gap between the classical continuum theories and the atomistic simulations in order to be able to design the size-dependent structures of modern technology. Nonlocal rate-dependent and gradient-dependent theories of plasticity and damage are developed in this work for this purpose. We adopt a multi-scale, hierarchical thermodynamic consistent framework to construct the material constitutive relations for the scale-dependent plasticity/damage behavior. Material length scales are implicitly and explicitly introduced into the governing equations through material rate-dependency (viscosity) and coefficients of spatial higher-order gradients of one or more material state variables, respectively. The proposed framework is implemented into the commercially well-known finite element software ABAQUS. The finite element simulations of material instability problems converge to meaningful results upon further refinement of the finite element mesh, since the width of the fracture process zone (shear band) is determined by the intrinsic material length scale; while the classical continuum theories fail to address this problem. It is also shown that the proposed theory is successful for the interpretation of indentation size effects in micro/nano-hardness when using pyramidal and spherical indenters and gives sound interpretations of the size effects in micro-torsion of thin wires and micro-bending of thin beams. Future studies should be directed toward incorporation of the size effects into design procedures and code recommendations of modern engineering structures (e.g. for MEMS, NEMS, coatings, thin films), fiber composites (e.g. for aircrafts and ships), etc

A finite deformation coupled plastic-damage model for simulating fracture of metal foams

Metal foams are a novel class of lightweight materials with unique mechanical, thermal, and acoustical properties. The low ductility of metal foams hinders the possibilities of applying secondary forming techniques to shape metal foam sandwich panels into desired industrial components. An important factor is the limited studies on their macroscopic damage and fracture behavior under complex loading conditions. There exist numerous mechanistic micromechanics models describing the fracture behavior of metal foams at the strut level, but very few work have been done on modeling their macroscopically coupled plasticity-damage constitutive behavior. The objective of this study is to develop a continuum finite deformation elasto-plastic-damage mechanics-based constitutive model for metal foams. The constitutive model is implemented in a user-defined material subroutine (UMAT) in the finite element software ABAQUS/Standard. The elasto-plastic part is implemented using backward-Euler return algorithm within Deshpande–Fleck constitutive framework. Continuum damage mechanics framework is formulated for the development of damage evolution equations. These damage evolution equations take into consideration the various key degradation mechanisms that lead to the macroscopic fracture of metal foams under various loading conditions. The model is calibrated and validated based on experimental data on aluminum foams under different loading paths, strain rates, and temperatures

Dynamics, Mechanistic and Equilibrium Studies for the Biosorption of Nickel on Palm Tree Leaves

Adsorption of heavy metals on biological sorbents, activated carbon and synthetic resin particles is a common separation technique. In this study, the biosorption of nickel ions from aqueous solution by palm tree leaves was investigated as a function of shaking time, nickel ions concentration and equilibrium pH. Competitive adsorption of nickel on palm tree leaves with EDTA and citric acid was also investigated. Batch adsorption experiments revealed that the biosorption of nickel on palm tree leaves was strongly pH dependent, and maximum nickel sorption was found to occur at equilibrium pH of 6.0. Dynamics studies showed that: the initial uptake of nickel on palm tree leaves was rapid, equilibrium was established within 30 minutes, and the data followed the pseudo-second order reaction. The equilibrium sorption data of nickel on palm tree leaves at solution pH 6.0 were described by two-parameter isotherm models such as the Langmuir, Freundlich, and D-R models and three-parameter models such as Redlich-Peterson and Sips isotherm models. Ion-exchange, adsorption-complexation and intraparticle diffusion mechanisms were found to be involved in the biosorption process. The Effect of ions interference on the biosorption of nickel on palm tree leaves showed that the sorption of nickel on palm tree leaves was adversely affected by the presence of chelating agents such as EDTA and citric acid

Prosopis cineraria as an Unconventional Legumes, Nutrition and Health Benefits

Prosopis cineraria (L.) Druce is considered as one of the highly valued plants in the native system of medicine for many arid and dry areas in the world. Ancient literature for Arabian Gulf and Indian desert illustrated the important of the plant in treated various ailments like asthma, dysentery, leucoderma, leprosy, dyspepsia, earache, etc. The present chapter review the using of P. cineraria as unconventional legumes that not well known as a rich and sustainable source of protein for many people in the world. It emphasis on its broad food and nonfood applications, nutritional values and health benefits. As well as looking at the phytochemical constituent’s content that has been identified in the various parts of the plant as alkaloid, steroids, alcohol and alkane. The present paper describes the morphological trait of P. cineraria and identifies the environmental conditions required for its natural distribution. Historically, this plant has drag attention for its various uses therefore, it has been considered as the National Tree of the United Arab Emirates in the Arabian Gulf

The Impact of Small Group Instruction on Preschool Literacy Skills

This study focused on 17 preschool students in a northern Jordan city. Preschoolers were taught specific literacy skills in a small group instructional setting. The students’ skill level was assessed at the beginning and middle of the school year. The researcher’s goal was to determine if teaching literacy skills in a small group setting would improve the skill level of the preschool students. Results showed that using small groups was an effective way to increase preschool students’ literacy skill levels

A deep learning energy-based method for classical elastoplasticity

The deep energy method (DEM) has been used to solve the elastic deformation of structures with linear elasticity, hyperelasticity, and strain-gradient elasticity material models based on the principle of minimum potential energy. In this work, we extend DEM to elastoplasticity problems involving path dependence and irreversibility. A loss function inspired by the discrete variational formulation of plasticity is proposed. The radial return algorithm is coupled with DEM to update the plastic internal state variables without violating the Kuhn-Tucker consistency conditions. Finite element shape functions and their gradients are used to approximate the spatial gradients of the DEM-predicted displacements, and Gauss quadrature is used to integrate the loss function. Four numerical examples are presented to demonstrate the use of the framework, such as generating stress-strain curves in cyclic loading, material heterogeneity, performance comparison with other physics-informed methods, and simulation/inference on unstructured meshes. In all cases, the DEM solution shows decent accuracy compared to the reference solution obtained from the finite element method. The current DEM model marks the first time that energy-based physics-informed neural networks are extended to plasticity, and offers promising potential to effectively solve elastoplasticity problems from scratch using deep neural networks