Impact of Adoption of Improved Groundnut Varieties on Factor Demand and Productivity in Uganda

The study analyzed the impact of adoption of improved groundnut varieties on farm inputs demand and productivity using instrumental variables approach. The data was collected from a simple random sample of 161 groundnut farmers in Eastern Uganda. Econometric results show significant increase in expenditure on improved seed and labor among adopters relative to the non-adopters. Adoption of improved varieties significantly increased groundnuts yield, by about 1688kg per hectare. Thus, more effort is needed to increase farmers’ access to improved varieties. The Government and partners should facilitate the development of local seed multiplication systems to reduce the cost of improved seed..Production Economics, Productivity Analysis, Research and Development/Tech Change/Emerging Technologies,

Using the local gyrokinetic code, GS2, to investigate global ITG modes in tokamaks. (I) s-α{\alpha} model with profile and flow shear effects

This paper combines results from a local gyrokinetic code with analytical theory to reconstruct the global eigenmode structure of the linearly unstable ion-temperature-gradient (ITG) mode with adiabatic electrons. The simulations presented here employ the s-${\alpha}$ tokamak equilibrium model. Local gyrokinetic calculations, using GS2 have been performed over a range of radial surfaces, x, and for ballooning phase angle, p, in the range -${\pi} {\leq} p {\leq\pi}$, to map out the complex local mode frequency, ${\Omega_0(x, p) = \omega_0(x, p) + i\gamma_0(x, p)}$. Assuming a quadratic radial profile for the drive, namely ${\eta_i = L_n/L_T}$, (holding constant all other equilibrium profiles such as safety factor, magnetic shear etc.), ${\Omega_0(x, p)}$ has a stationary point. The reconstructed global mode then sits on the outboard mid plane of the tokamak plasma, and is known as a conventional or isolated mode, with global growth rate, ${\gamma}$ ~ Max[${\gamma_0(x, p)}$], where ${\gamma_0(x, p)}$ is the local growth rate. Taking the radial variation in other equilibrium profiles (e.g safety factor q(x)) into account, removes the stationary point in ${\Omega_0(x, p)}$ and results in a mode that peaks slightly away from the outboard mid-plane with a reduced global growth rate. Finally, the influence of flow shear has also been investigated through a Doppler shift, ${\omega_0 \rightarrow \omega_0 + n\Omega^{\prime}x}$, where n is the toroidal mode number and ${\Omega^{\prime}}$ incorporates the effect of flow shear. The equilibrium profile variation introduces an asymmetry to the growth rate spectrum with respect to the sign of ${\Omega^{\prime}}$, consistent with recent global gyrokinetic calculations.Comment: 10 pages, 8 figures and 1 tabl

Renormalization of the singular attractive 1/r41/r^4 potential

We study the radial Schr\"odinger equation for a particle of mass $m$ in the field of a singular attractive $g^2/{r^4}$ potential with particular emphasis on the bound states problem. Using the regularization method of Beane \textit{et al.}, we solve analytically the corresponding ``renormalization group flow" equation. We find in agreement with previous studies that its solution exhibits a limit cycle behavior and has infinitely many branches. We show that a continuous choice for the solution corresponds to a given fixed number of bound states and to low energy phase shifts that vary continuously with energy. We study in detail the connection between this regularization method and a conventional method modifying the short range part of the potential with an infinitely repulsive hard core. We show that both methods yield bound states results in close agreement even though the regularization method of Beane \textit{et al.} does not include explicitly any new scale in the problem. We further illustrate the use of the regularization method in the computation of electron bound states in the field of neutral polarizable molecules without dipole moment. We find the binding energy of s-wave polarization bound electrons in the field of C$_{60}$ molecules to be 17 meV for a scattering length corresponding to a hard core radius of the size of the molecule radius ($\sim 3.37$ \AA). This result can be further compared with recent two-parameter fits using the Lennard-Jones potential yielding binding energies ranging from 3 to 25 meV.Comment: 8 page

Secure Cloud-based IoT Water Quality Gathering for Analysis and Visualization

Water quality refers to measurable water characteristics, including chemical, biological, physical, and radiological characteristics usually relative to human needs. Dumping waste and untreated sewage are the reasons for water pollution and several diseases to the living hood. The quality of water can also have a significant impact on animals and plant ecosystems. Therefore, keeping track of water quality is a substantial national interest. Much research has been done for measuring water quality using sensors to prevent water pollution. In summary, those systems are built based on online and reagent-free water monitoring SCADA systems in wired networks. However, centralized servers, transmission protocols, and data access can present challenges and disadvantages for those systems. This paper proposes a secure Cloud-based IoT water quality gathering architecture for water quality analysis and visualization to address the limitations of the current systems. The proposed architecture will send, analyze and visualize water quality data in the Cloud by utilizing specialized sensors and IoT-based gateways to capture water measurements (Dioxygen concentration, and temperature, among others). Then, they communicate securely to the Cloud-based server through a high-speed wireless network. We evaluated the performance of the proposed framework on a process-oriented approach to success metrics for cyberinfrastructures. The experiments were conducted in a laboratory and focused on network security and resiliency, the IoT prototype performance in dropping real-time data transmission, and remote access. The results demonstrate higher data collection and transmission effectiveness with minimal data loss and low energy usage over time. The accompanying cloud-based platform provided the flexibility needed for water quality monitoring and laboratory studies

GR-40 Design and Implementation of a Microservices Web-based Architecture for Code Deployment and Testing

Many tech stars like Netflix, Amazon, PayPal, eBay, and Twitter are evolving from monolithic to a microservice architecture due to the benefits for Agile and DevOps teams. Microservices architecture can be applied to multiple industries, like IoT, using containerization. Virtual containers give an ideal environment for developing and testing IoT technologies. Since the IoT industry has exponential growth, it is the responsibility of universities to teach IoT with hands-on labs to minimize the gap between what the students learn and what is on-demand in the job market. That can be done by using containerization. There are many approaches in the containerization field, but they can be difficult to use without depth knowledge in virtualization and code encapsulation. After a deep analysis of the containerization challenges, we came with an idea of a microservice infrastructure based on Docker, which is an open- platform for developing, testing, and running applications using containers, to solve the virtualization and code-encapsulation problem. Our infrastructure will provide a code development and testing web-based platform that allows users to securely go in the process of containerization without spending research time in learning virtualization. So, students and researchers can focus more on the development and testing of algorithms and codes. For example, it will be easy to develop containers that allow sensors to connect to an external server in few cliques, or to run a python code in a total isolate process in minutes without downloading any containerization software.Advisors(s): Dr. Maria Valero [email protected] Dr Hossain Shahriar [email protected](s): IoT/Cloud/Networkin

GR-182 - IoT Clusters Platform for Data Collection, Analysis, and Visualization Use Case

Climate change is happening, and many countries are already facing devastating consequences. Populations worldwide are adapting to the season\u27s unpredictability they relay to lands for agriculture. Our first research was to develop an IoT Clusters Platform for Data Collection, analysis, and visualization. The platform comprises hardware parts with Raspberry Pi and Arduino clusters connected to multiple sensors. The clusters transmit data collected in real-time to microservices-based servers where the data can be accessed and processed. Our objectives in developing this platform were to create an efficient data collection system, relatively cheap to implement and easy to deploy in any part of the world. Since we have completed the first part, we are implementing a study case for a field used by the platform. Thus, we are implementing an environment monitoring technology base on weather data. For this study, the platform will collect real-time environmental data using sensors (Temperature, humidity, light and ultraviolet sensors, and other sensors). We are setting those sensors in relatively limited superficies due to resources problem. Next, we will use this data to find patterns in weather changes using Machine and Deep learning techniques since these environmental data come from a designated area. The main objective of this part is to find a weather pattern using collected data specific to this area. Data collected during this research and the IoT platform are available on campus for students to use for their class projects or future research. Currently, we are in the data collection process. We also evaluate the degradation and environmental effects on devices and sensors used. This study case is a needed step in the IoT Clusters Platform for Data Collection, Analysis, and Visualization research project. At the end of the project, the data collection framework will be efficient and cost less

IoT Clusters Platform for Data Collection, Analysis, and Visualization Use Case

Climate change is happening, and many countries are already facing devastating consequences. Populations worldwide are adapting to the season\u27s unpredictability they relay to lands for agriculture. Our first research was to develop an IoT Clusters Platform for Data Collection, analysis, and visualization. The platform comprises hardware parts with Raspberry Pi and Arduino\u27s clusters connected to multiple sensors. The clusters transmit data collected in real-time to microservices-based servers where the data can be accessed and processed. Our objectives in developing this platform were to create an efficient data collection system, relatively cheap to implement and easy to deploy in any part of the world. Since we have completed the first part, we are implementing a study case for a field used of the platform. Thus, we are implementing an environment monitoring technology base on weather data. For this study, the platform will collect real-time environmental data using sensors (Temperature, humidity, light and ultraviolet sensors, and other sensors). We are setting those sensors in relatively limited superficies due to resources problem. Next, we will use this data to find patterns in weather changes using Machine and Deep learning techniques since these environmental data come from a designated area. The main objective of this part is to find a weather pattern using collected data specific to this area. Data collected during this research and the IoT platform are available on campus for students to use for their class projects or future research. Currently, we are in the data collection process. We also evaluate the degradation and environmental effects on devices and sensors used. This study case is a needed step in the IoT Clusters Platform for Data Collection, Analysis, and Visualization research project. At the end of the project, the data collection framework from it will be efficient and cost less

Correlated detection of neutral and charged fragments in collision induced fragmentation of molecular clusters

accepté dans International Journal of Mass SpectrometryWe report on collision induced fragmentation of isolated molecular nanosystems studied with an event by event detection technique including the correlated detection of both neutral and charged fragments. This work focuses on the dissociation induced by collisional excitation without ionisation and electron-capture. Two molecular cluster cations are investigated: the collision of protonated hydrogen clusters at 60keV/amu with helium targets and that of protonated water clusters at 8keV with an argon gas. In addition to the molecular evaporation process the dissociation channel leading to the production of the H3+ or H3O+ molecular cations (loss of all the molecules) is observed with an unexpected abundance. The cross section for the production of these cations is observed to increase with the number of molecules in the cluster. Such an increase cannot be associated with the direct collisional excitation of the cation core of the cluster

Solving Ratio-Dependent Predator-Prey System with Constant Effort Harvesting using Variational Iteration Method

Due to wide range of interest in use of bio-economic models to gain insight into the scientific management of renewable resources like fisheries and forestry,variational iteration method (VIM) is employed to approximate the solution of the ratio-dependent predator-prey system with constant effort prey harvesting.The results are compared with the results obtained by Adomian decomposition method and reveal that VIM is very effective and convenient for solving nonlinear differential equations