Group-Based Diabetes Self-Management Education for Somali population with Type II Diabetes Mellitus

Background and Purpose: Type II Diabetes Mellitus (T2DM) is a serious chronic disease that requires knowledge, daily self-management, and lifestyle modifications. T2DM is a widespread disease in Western world, however, it affects racial minority immigrant populations, including Somalis at disproportionally higher rates than the general population. This quality improvement project was developed and piloted to discern whether culturally appropriate small group-based education program for Somali patients with T2DM may improve self-management skills to alleviate long-term complications. Methods: This project used descriptive statistics to compare participants’ knowledge and T2DM self-management behavior pre and post intervention. Subsequent to Seattle University IRB approval, participants were recruited from HealthPoint Midway clinics in King County, WA. Informed consent was obtained verbally on enrollment and participants were asked to complete demographic surveys and pre-intervention questionnaires at that time. The T2DM intervention topics in the study included general knowledge of T2DM, healthy eating, physical activity, stress management, as well as glucose monitoring and medication regiment. A total of 5 educational sessions, each lasting approximately 1.5 hours were delivered via zoom. Education was provided in the Somali language which the investigator and participants spoke at home. Results: Tow men and four women (N=6), between ages of 42-55 years old, diagnosed with T2DM participated in the project. All of the participants were of Somali origin. Participants’ average pre-intervention A1c level was M=10.7 and the average post-intervention A1c level was M=9.1 (Appendix A, Table 3). There was also a significant improvement in the participants’ knowledge of T2DM and improvement in confidence related to self-care (Appendix B, Table 4). Conclusions: This project, carried out with a small sample of Somali immigrants with T2DM demonstrated that culturally appropriate health interventions delivered in the patients’ first language and carried out in a small group setting may be an effective health promotion and disease management strategy for this population, contributing to alleviating health disparities long term

Optimal Power Flow in the Smart Grid Using Direct Load Control Program

This paper proposes an Optimal Power Flow (OPF) algorithm by Direct Load Control (DLC) programs to optimize the operational cost of smart grids considering various scenarios based on different constraints. The cost function includes active power production cost of available power sources and a novel flexible load curtailment cost associated with DLC programs. The load curtailment cost is based on a virtual generator for each load (which participates in DLC program). To implement the load curtailment in the objective function, we consider incentive payments for participants and a load shedding priority list in some events. The proposed OPF methodology is applied to IEEE 14, 30-bus, and 13-node industrial power systems as three examples of the smart grids, respectively. The numerical results of the proposed algorithm are compared with the results obtained by applying MATPOWER to the nominal case by using the DLC programs. It is shown that the suggested approach converges to a better quality solution in an acceptable computation time

Adoption of Online Learning during the Covid19 Pandemic Lockdown by Universities in Garowe

In response to the Covid-19 outbreak the world closed and therefore countries like Somalia have not been exceptional. The government of Somalia and all higher education institutions adopted crisis intervention measures on implementation of blended learning approaches like online teaching and learning. In this chapter we explore the process and challenges of adopting online learning in response to the world wide lockdown due to the pandemic. Given that this was an abrupt requirement, the survey was interested in finding out whether universities adopted and adapted easily. Researchers compared findings from previous studies and theoretical inclinations on online learning. Results indicate that the adoption of online learning among universities in Garowe was as a matter of crisis management whereby administration, lecturers and students were all not ready and had no prior grounding in this pedagogical learning platform. Just like previous studies online learning implementers have continued to encounter several challenges like intermittent internet network, cost of gadgets and facilities, inadequate skills of both the instructors and students, aspects of communication and satisfaction from stakeholders. With the research survey in Garowe, results show that this is still pervading and therefore need for more rigorous contextualised research on this subject

Optimal emergency demand response program integrated with multi-objective dynamic economic emission dispatch problem

Nowadays, demand response programs (DRPs) play an important role in price reduction and reliability improvement. In this paper, an optimal integrated model for the emergency demand response program (EDRP) and dynamic economic emission dispatch (DEED) problem has been developed. Customer’s behavior is modeled based on the price elasticity matrix (PEM) by which the level of DRP is determined for a given type of customer. Valve-point loading effect, prohibited operating zones (POZs), and the other non-linear constraints make the DEED problem into a non-convex and non-smooth multi-objective optimization problem. In the proposed model, the fuel cost and emission are minimized and the optimal incentive is determined simultaneously. The imperialist competitive algorithm (ICA) has solved the combined problem. The proposed model is applied on a ten units test system and results indicate the practical benefits of the proposed model. Finally, depending on different policies, DRPs are prioritized by using strategy success indices

New complexes of manganese (II) and copper (II) derived from the two new furopyran-3, 4-dione ligands: synthesis, spectral characterization, ESR, DFT studies and evaluation of antimicrobial activity

A total of four new metal complex derivatives of two new ligands 2-(hydroxy(phenyl)-6-methyl-2H-furo [3,2-c]pyran-3,4-dione (L1) and 2-(hydroxyl (2-hydroxyphenyl) -6-methyl-2H-furo [3,2-c]pyran-3,4-dione (L2) with the metal ions Mn(II) and Cu(II) have been successfully prepared in alcoholic medium. The complexes obtained are investigated by spectral studies with the use of FT-IR and UV–vis techniques, ESR and magnetic measurements. The IR spectra suggest that the oxygen atoms of the two ligands are engaged in the bond with the central metal. The electronic spectra of the complexes and their magnetic moments provide information about geometries. The molar conductance measurements showed that the complexes are non-electrolytes. Theoretical calculations invoking geometry optimization and molecular orbital description HOMO and LUMO are done using DFT density functional theory. The experimental results and the calculated structural parameters, bond distances and angles, revealed a distorted octahedral geometries around the manganese and copper center through the oxygen of the furan ring for the synthesized complexes ([M(L)2(H2O)2]nH2O; M: metal; L: ligand). The antimicrobial activity of the ligands and their complexes was evaluated in vitro against different bacteria and fungi using agar diffusion method. The ligands and their complexes of manganese (II) and copper (II) exhibited a strong antifungal activity. Copper and manganese complexes have different antibacterial properties against bacteria. The ligand L1 and there complexes were found to be more active against Gram-positive than Gram-negative bacteria.publishe

A One-Pot Diastereoselective Synthesis of 2-[Aryl(hydroxy)methyl]-6-methyl-2H-furo[3,2-c]pyran-3,4-diones: Crystallographic Evidence for the Furanone Ring Closure

Novel furopyran-3,4-dione-fused heterocycles have been obtained by a one-pot reaction of -brominated dehydroacetic acid and benzaldehydes under organobase conditions. The prepared 2-[aryl(hydroxy)methyl]-6-methyl-2H-furo[3,2-c]pyran-3,4-diones were fully characterized by 2D NMR spectroscopy and supported by single-crystal X-ray analysis to unequivocally prove the furan-3-one five-membered ring-closure mechanism instead of the dihydroflavanon-3-ol six-membered cyclization which has recently been proposed in the literature

Genetic and biochemical diversity of Paenibacillus larvae isolated from Tunisian infected honey bee broods

Paenibacillus larvae is the causative agent of American foulbrood (AFB), a virulent disease of honeybee (Apis mellifera) larvae. In Tunisia, AFB has been detected in many beekeeping areas, where it causes important economical losses, but nothing is known about the diversity of the causing agent. Seventy five isolates of P. larvae, identified by biochemical tests and 16S rRNA gene sequencing, were obtained from fifteen contaminated broods showing typical AFB symptoms, collected in different locations in the northern part of the country. Using BOX-PCR, a distinct profile of P. larvae respect to related Paenibacillus species was detected which may be useful for its identification. Some P. larvae-specific bands represented novel potential molecular markers for the species. BOX-PCR fingerprints indicated a relatively high intraspecific diversity among the isolates not described previously with several molecular polymorphisms identifying six genotypes on polyacrylamide gel. Polymorphisms were also detected in several biochemical characters (indol production, nitrate reduction, methyl red and oxidase test). Contrary to the relatively high intraspecies molecular and phenotypic diversity, the in-vivo virulence of three selected P. larvae genotypes did not differ significantly, suggesting that the genotypic/phenotypic differences are neutral or related to ecological aspects other than virulence

A Study on Machine Learning Models in Predicting Volatile Spot Prices : A Case Study on Norway’s Electricity Market

The uncertainty caused by the increased use of renewable energy sources makes it more essential to find good forecasting tools that can offset the increased risk in predicting elspot prices. Different supervised machine learning models are applied in this thesis to predict electricity prices for the different price areas in Norway using hourly data for elspot prices, energy prices and temperature collected for the period 2014-2020. The results show that some models are better suited for predicting elspot prices compared to others, with the Linear regression model, Gradient Boosting and Extra Randomised Trees regressor (ET) giving the best results out of the 11 tested models. The findings also suggest that choosing seasonal forecasting horizon together with adding more explanatory variables such as system load and wind power will improve the predictive performance of the models by capturing price spikes and anticipating changes in the elspot prices that longer forecasting horizon fail to capture.M-ECO

A Brief Review of Microgrid Surveys, by Focusing on Energy Management System

Microgrids are new concepts in power systems that can upgrade current power systems due to their technical, economic, and environmental advantages. In addition, the increasing penetration of renewable energies and their use in microgrids have increased the complexity of these new grids in terms of planning and operation. Along with numerous research and practical projects built in different countries with multiple applications, countless types of research have also been performed relying on different aspects of MGs. In this paper, based on a review of studies and review articles related to MGs, an attempt has been made to evaluate and report the optimal energy management of MGs, based on what is addressed in the literature. In addition, the most critical surveys on various topics of MGs are introduced as a guide for researchers to draw a road map for future works