Improving students’ use of argumentation is front and center in the increasing emphasis on scientific practice in K-12 Science and STEM programs. We explore the construct validity of scenario-based assessments of claim-evidence-reasoning (CER) and the structure of the CER construct with respect to a learning progression framework. We also seek to understand how middle school students progress. Establishing the purpose of an argument is a competency that a majority of middle school students meet, whereas quantitative reasoning is the most difficult, and the Rasch model indicates that the competencies form a unidimensional hierarchy of skills. We also find no evidence of differential item functioning between different scenarios, suggesting

This paper presents the Extended State Observer (ESO) based repetitive control (RC) for piezoelectric actuator (PEA) based nano-positioning systems. The system stability is proved using Linear Matrix Inequalities (LMIs), which guarantees the asymptotic stability of the system. The ESObased RC used in this paper has the ability to eliminate periodic disturbances, aperiodic disturbances and model uncertainties. Moreover, ESO can be tuned using only two parameters and the model free approach of ESO-based RC, makes it an ideal solution to overcome the challenges of nano-positioning system control. Different types of periodic and aperiodic disturbances are used in simulation to demonstrate the effectiveness of the algorithm. The comparison studi

In general, path-planning problem is one of most important task in the field of robotics. This paper describes the path-planning problem of mobile robot based on various metaheuristic algorithms. The suitable collision free path of a robot must satisfies certain optimization criteria such as feasibility, minimum path length, safety and smoothness and so on. In this research, various three approaches namely, PSO, Firefly and proposed hybrid FFCPSO are applied in static, known environment to solve the global path-planning problem in three cases. The first case used single mobile robot, the second case used three independent mobile robots and the third case applied three follow up mobile robot.  Simulation results, whi

Cancer is in general not a result of an abnormality of a single gene but a consequence of changes in many genes, it is therefore of great importance to understand the roles of different oncogenic and tumor suppressor pathways in tumorigenesis. In recent years, there have been many computational models developed to study the genetic alterations of different pathways in the evolutionary process of cancer. However, most of the methods are knowledge-based enrichment analyses and inflexible to analyze user-defined pathways or gene sets. In this paper, we develop a nonparametric and data-driven approach to testing for the dynamic changes of pathways over the cancer progression. Our method is based on an expansion and refinement of the pathway bei

D-mannose sugar was used to prepare [benzoic acid 6-formyl-2, 2-dimethyl-tetrahydrofuro [3, 4-d][1, 3] dioxol-4-yl ester](compound A). The condensation reaction of folic acid with (compound A) resulted in the formation of new ligand [L]. These compounds were characterized by elemental analysis CHN, atomic absorption AA,(FT-IR),(UV-Vis), TLC, ES mass (for electrospray), molar conductance, and melting point. The new tetradentate ligand [L], reacted with two moles of some selected metal ions and two moles of (2-aminophenol),(metal: ligand: 2-aminophenol) at reflux in water medium to give a series of new complexes of the general formula K2 [M2 (L)(HA) 2] where M= Co (II), Ni (II), Cu (II) and Cd (II). These complexes were characterized by eleme

     Binary relations or interactions among bio-entities, such as proteins, set up the essential part of any living biological system. Protein-protein interactions are usually structured in a graph data structure called "protein-protein interaction networks" (PPINs). Analysis of PPINs into complexes tries to lay out the significant knowledge needed to answer many unresolved questions, including how cells are organized and how proteins work. However, complex detection problems fall under the category of non-deterministic polynomial-time hard (NP-Hard) problems due to their computational complexity. To accommodate such combinatorial explosions, evolutionary algorithms (EAs) are proven effective alternatives to heuristics in solvin

Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security