Effective use of Interactive Learning Modules in Classroom Study for Computer Science Education

The National Science Foundation (NSF) is spending substantial resources to improve science, technology, engineering, and mathematics (STEM) education in the United States. The ultimate goal of these programs is to produce students with a better knowledge of math and science and who are more likely to pursue careers in STEM fields. Interactive learning modules can be used in the classroom environment for effective learning. This study examines the learning preferences of Logan High School (located in Logan, Utah) students and evaluates the impacts of using interactive learning modules with classroom lectures compared to other traditional methods of teaching

Intelligent robotic rehabilitation system for treatment of disabilities subsequent to injuries or neurological disorders

Injuries or neurological trauma, such as stroke, complete and incomplete spinal cord injuries result in paraplegia and hemiplegia, which is the leading cause of disabilities world over. Survivors have muscle coordination discrepancies resulting in impaired joint motions and inability to perform activities of daily living (ADL). Neurological trauma falls in top 15 risk factors for Kazakhstan people and their health conditions. Urgent steps are required to be initiated as the current rate of such disorders is predicted to increase by three times over the next 30 years. Robot assisted physical therapy has shown some preliminary signs of improvement in subjects and therefore active orthosis have been developed to impart repetitive, prolonged and systematic therapy. Existing robots are normally inspired by the industrial robots and thus provide constrained motion to the articulating joints in an uncomfortable and unsafe manner. There is a need to develop human friendly, safe and intelligent robots in order to carry out physical therapy. We aim at developing an intelligent rehabilitation system (IRS) using wearable robots equipped with state of the art sensors and actuators, optimization routines (to identify musculoskeletal functions at the affected limb) and development of advanced controllers. Physical therapy is expected to be evidence based, objective and human friendly

Software development for analysis of stochastic petri nets using transfer functions

This thesis research is an implementation of a closed-form analytical technique for study, evaluation and analysis of Stochastic Petri Nets (SPN). The technique is based on a theorem that an isomorphism exists between an SPN and a Markov Chain. The procedure comprises five main steps: reachability graph generation of the underlying Petri net, transformation of the reachability graph to a state machine Petri net, calculation of transfer functions, computation of equivalent transfer functions via Mason\u27s rule, and computation of performance parameters of the SPN model from the equivalent transfer functions and their derivatives. The software is developed in UNIX using C and applied to various SPN models. Future research includes implementation of Mason\u27s rule for complex cases and symbolic derivation of equivalent transfer functions

Intelligent robotic rehabilitation system for treatment of disabilities subsequent to injuries or neurological disorders

Injuries or neurological trauma, such as stroke, complete and incomplete spinal cord injuries result in paraplegia and hemiplegia, which is the leading cause of disabilities world over. Survivors have muscle coordination discrepancies resulting in impaired joint motions and inability to perform activities of daily living (ADL). Neurological trauma falls in top 15 risk factors for Kazakhstan people and their health conditions. Urgent steps are required to be initiated as the current rate of such disorders is predicted to increase by three times over the next 30 years. Robot assisted physical therapy has shown some preliminary signs of improvement in subjects and therefore active orthosis have been developed to impart repetitive, prolonged and systematic therapy. Existing robots are normally inspired by the industrial robots and thus provide constrained motion to the articulating joints in an uncomfortable and unsafe manner. There is a need to develop human friendly, safe and intelligent robots in order to carry out physical therapy. We aim at developing an intelligent rehabilitation system (IRS) using wearable robots equipped with state of the art sensors and actuators, optimization routines (to identify musculoskeletal functions at the affected limb) and development of advanced controllers. Physical therapy is expected to be evidence based, objective and human friendly

Interactive effects of selenium on arsenic and cadmium induced toxicity in rainbow trout (Oncorhynchus mykiss)

The existing scientific literature suggests that selenium can modify arsenite or cadmium toxicity in fish; however, our current understanding of the biochemical pathways involved in such interactions is obtained predominantly from mammalian experimental systems, and the literature on aquatic organisms is sparse. To address this knowledge gap, the modulatory effects of selenium on cadmium or arsenite toxicity was investigated using a model freshwater fish, rainbow trout (Oncorhynchus mykiss). Interactions at the cellular level were investigated using trout hepatocytes in primary culture. Selenite and selenomethionine were used as the inorganic and organic chemical forms of selenium to understand the chemical species-dependent effects. Interactions at the organismal level were studied by feeding the fish with Artemia based diets supplemented with selenomethionine in combination with cadmium or arsenite for 30 days. At the cellular level, cadmium and arsenite disrupted redox homeostasis which was alleviated by low-moderate doses of selenite and selenomethionine (< 25 µM). Further analysis revealed that selenite antagonized arsenite-induced oxidative stress by augmenting enzymatic antioxidants, whereas selenomethionine upregulated the GSH-dependent non-enzymatic antioxidative pathway. At the organismal level, supplementing the diet with only cadmium (40 µg/g diet) or arsenite (80 µg/g diet) increased the tissue level deposition of the respective elements and caused oxidative stress in the liver. However, medium dose (10 µg/g diet) of selenomethionine reduced cadmium accumulation in the liver and alleviated oxidative stress. In contrast, supplementation of diet with selenomethionine (both at low and high levels) in combination with arsenite resulted in higher degree of oxidative stress relative to the fish treated with arsenite alone. Furthermore, fish co-treated with arsenite and selenomethionine accumulated significantly higher levels of arsenic in liver, kidney and muscle relative to fish treated with arsenite alone. Similarly, the synchrotron-based X-ray fluorescence imaging also revealed a dose-dependent increase in the co-localization of arsenic and selenium in the brain of fish co-treated with dietary arsenite and selenomethionine, whereas no arsenic deposition in the brain was recorded in fish treated with dietary arsenite alone. Overall, the results indicated that selenium at moderate doses could antagonize cadmium-induced oxidative stress; however, selenomethionine can interact metabolically with arsenite at systemic level and increase its toxicity in fish

Passive sampling devices to improve the monitoring of anthropogenic pollutants in river catchments in India: report of researcher exchange May 2017

The India-UK Water Centre (IUKWC) promotes cooperation and collaboration between the complementary priorities of NERC-MoES water security research. This report documents and discusses activities undertaken during a Researcher Exchange funded by the India-UK Water Centre (IUKWC) on the topic of “The use of passive sampling devices to improve the monitoring of anthropogenic pollutants in river catchments in India”. This exchange enabled Professor Gary Fones, from the University of Portsmouth, UK to conduct a 12-day exchange visit hosted by Dr Pryinka Jamwal at the Ashoka Trust for Research in Ecology and the Environment (ATREE) in Bangalore, India from 8-19 May 2017. This report provides background on the rationale for conducting the research exchange on the topic of ‘Improving freshwater monitoring frameworks and data for research and management’, as well as a review of the objectives. This is followed by a description of the activities undertaken during the exchange and a summary of the themes and outcomes arising from a one day workshop conducted on the topic of ‘Surface water quality monitoring: Key issues, challenges and the way forward

Prasugrel versus ticagrelor in patients with Acute Coronary syndrome treated with percutaneous coronary intervention

Background: No association studies for the efficacy and safety of ticagrelor vs. prasugrel have been published in India. Aim of the study was to compare the safety and efficacy of Prasugrel versus Ticagrelor in Patients with Acute Coronary Syndrome Treated with Percutaneous Coronary Intervention.Methods: This retrospective study was designed to compare the efficacy and safety of prasugrel and ticagrelor in acute coronary syndromes (ACS) with percutaneous coronary intervention (PCI). A total of 480 patients were studied who had been prescribed either prasugrel or ticagrelor during PCI. Primary end-point was defined as death, re-infarction, urgent target vessel revascularization, serious bleeding requiring transfusion.Results: Primary endpoint was different between the groups receiving prasugrel and ticagrelor (1.2% and 4.0%, respectively; OR (95% CI) 0.38 (0.098; 1.43); P=0.065). Difference was found in the need for urgenttarget vessel revascularization which was significantly lower in the prasugrel group.Rest of the parameters were almost similar with no significant difference.Conclusions: This study comparing prasugrel and ticagrelor shows that Prasugrel is more effective than Ticagrelor in lowering ischemic events in the acute coronary syndromes treated with PCI strategy, especially incidence of stent thrombosis. These observations need further analysis and follow-up

A Study of Software Development Models for Small Organisations

Software Development is a complex and often difficult process requiring the synthesis of many disciplines, like modelling and design to code generation, project management, testing, deployment, change management and beyond. Software development organizations follow some process while developing a software product. A key component of any software development process is the lifecycle model on which the process is based

Estimating fast and slow reacting components in surface water and groundwater using a two-reactant model

Maintaining residual chlorine levels in a water distribution network is a challenging task, especially in the context of developing countries where water is usually supplied intermittently. To model chlorine decay in water distribution networks, it is very important to understand chlorine kinetics in bulk water. Recent studies have suggested that chlorine decay rate depends on initial chlorine levels and the type of organic and inorganic matter present in water, indicating that a first-order decay model is unable to accurately predict chlorine decay in bulk water. In this study, we employed the two-reactant (2R) model to estimate the fast and slow reacting components in surface water and groundwater. We carried out a bench-scale test for surface water and groundwater at initial chlorine levels of 1, 2, and 5 mg L−1. We used decay data sets to estimate optimal parameter values for both surface water and groundwater. After calibration, the 2R model was validated with two decay data sets with varying initial chlorine concentrations (ICCs). This study arrived at three important findings. (a) We found that the ratio of slow to fast reacting components in groundwater was 30 times greater than that of the surface water. This observation supports the existing literature which indicates the presence of high levels of slow reacting fractions (manganese and aromatic hydrocarbons) in groundwater. (b) Both for surface water and groundwater, we obtained good model prediction, explaining 97 % of the variance in data for all cases. The mean square error obtained for the decay data sets was close to the instrument error, indicating the feasibility of the 2R model for chlorine prediction in both types of water. (c) In the case of deep groundwater, for high ICC levels (> 2 mg L−1), the first-order model can accurately predict chlorine decay in bulk water