The Results of the Reading Improvement Classes in the Emerson Elementary School, Seattle, Washington, 1957-1958

The purposes of this study were (1) to determine the degree of individual growth in reading ability made by the pupils enrolled in the Reading Improvement classes at the Emerson Elementary School, Seattle, Washington, during the 1957-1958 school year; (2) to keep an accurate record and description of techniques and materials used in securing this individual growth; and (3) to present the findings in a form that might be of assistance to other teachers in developing similar programs

Aging Characterization of Li-ion Batteries

The depleting nature of fossil energy resources accompanied by increasing demand for energy and their influence on increasing the climate change rates and greenhouse gas emissions motivated the governments and decision-makers to adopt energy sources that are less harmful to the environment and community. Hence, exploiting the potential power of sunlight, water, wind, and underground energy was the cornerstone player in achieving cleaner and more sustainable energy systems. Unfortunately, it is almost impossible to rely on these resources to match the energy demand because of their erratic behavior. Thus, efficient storage systems are needed to enhance reliability and increase the dependency on these energy production systems by storing excess energy and releasing it when needed. In the essence of this development, lithium-ion rechargeable batteries stand out to be a practical solution for different energy uses, starting from small appliances, transportation, and even grid applications. Although at different levels of utilization, all types of Lithium batteries experience the problem of aging and capacity degradation. LiBs aging is a unique and complicated phenomenon influenced by the interdependency between different internal and external factors. Also, the degradation rates, modes, and mechanisms are affected by the battery's design, production process, and application field. Hence, it has become indispensable to simulate the battery functionality accurately to indicate and fix the possible failures in advance. Different approaches were employed for tracing and estimating the capacity fade. Some models rely on an offline investigation of the battery cell(s), while others succeed in scoring high estimation results while the battery is in operation. Data-driven model (DDM) is an example of an online model that doesn't need a comprehensive understanding of the battery components and the chemical reactions inside. Hence, a specific machine learning type of DDM approach called the long-short term memory algorithm (LSTM) was utilized in this thesis. LSTM excels in solving a time-dependent problem; hence, it is adopted here as battery aging is an accumulated problem affected by its previous state. Herein, a Lithium titanate oxide (LTO) pouch battery cell was employed and subjected to experimental characterization under two different C-rates at a temperature of 25 oC. The test results were then treated to extract specific health indicators that are studied in the literature. The estimation model was built in a python programming language with the help of data manipulation, machine learning, and visualization libraries. The model's outputs were then evaluated using metrics like mean absolute error (MSE), and root mean squared error (RMSE)

Drop Tower Impact of 3D Printed Structures

Drop Tower Impact of 3D Printed Structure

Seasonal dynamics of heavy metal uptake in some aquatic plants of the Tigris River

This work aimed to study the accumulation of heavy metals Cadmium, Lead, Chromium, and Nickel in different aquatic plants along the Tigris River. The research focused on the seasonal variations in heavy metal uptake by Phragmites australis, Typha domingensis, Persicaria salicifolia, Azolla filiculoides, and Ceratophyllum demersum. Samples were collected from three distinct locations along the river, each characterized by varied environmental conditions. Using Atomic Absorption Spectrophotometry, the quantified metal concentrations were measured, revealing significant differences across seasons and locations. The study provides crucial insights into the dynamics of heavy metal accumulation in riverine ecosystems, underscoring the role of environmental factors and plant species in metal uptake

Adherence to the management of type i diabetes among Palestinian patients in Nablus city: a cross-sectional study

The purpose of this study is to investigate the adherence to the management of Type I Diabetes and to investigate factors associated with non-adherence among Palestinian Type 1 Diabetes patients. One hundred and twenty-six patients diagnosed with Type 1 Diabetes were enrolled in an observational cross-sectional study. Diabetes self-care adherence was measured using the Self Care Inventory (SCI). The patients were recruited from a diabetes clinic in Nablus city in Palestine. One-way ANOVA test and simple linear regressions were used in the statistical analysis. Participants age ranged from 3-43 years; 56% of them were females. The mean age at diagnosis for them was 10 years (+/-6.25). The mean glycosylated hemoglobin (A1C) was 9 +/-2.32. 66% of patients reported significant non-adherence to glucose testing, 89% reported non-adherence to diet recommendations, 79% reported non-adherence to exercise, and 21% reported non-adherence to administering insulin on time. Age (r = 0.29, P < 0.05), A1C (r = 0.21, P < 0.05), sex (P < 0.05), and patient educational level (P< 0.05) were significantly related to adherence score. Adherence to treatment among patients with Type 1 Diabetes is poor and is associated with age, sex, A1C, and patient educational level. Designed education programs should be implemented among patients with Type 1 Diabetes, which address the importance of adherence to the management of the diseases. More strategies should focus on monitoring the diet and insulin administration. © 2022, An-Najah National University. All rights reserved

Fingerprinting Hysteresis

We test the predictive power of first-oder reversal curve (FORC) diagrams using simulations of random magnets. In particular, we compute a histogram of the switching fields of the underlying microscopic switching units along the major hysteresis loop, and compare to the corresponding FORC diagram. We find qualitative agreement between the switching-field histogram and the FORC diagram, yet differences are noticeable. We discuss possible sources for these differences and present results for frustrated systems where the discrepancies are more pronounced.Comment: 4 pages, 5 figure