Robust Appointment Scheduling for Random Service Time Using Min-Max Optimization

Appointment Scheduling is an increasingly challenging problem for service-centers, healthcare, production and transportation sector. Challenges include meeting growing demand and high expectation of service level among the customers and ensuring an efficient service system which reduces the expenditure related to idle times and under-utilization of the system. The problem becomes more complicated in the presence of processing time uncertainties. In this study, a Robust Appointment Scheduling model is developed using Min-max Optimization to provide appointment dates for a system with a single processor. The objective is to minimize the cost of the worst-case scenario under any realization of the processing time of the jobs. The proposed methodology requires less information regarding the uncertain parameters and can provide optimal solution while only considering the extreme bounds of the uncertain parameters. Therefore, it is applicable to any probability distribution of the uncertain parameters. The model is well suited for any general case appointment scheduling problem regardless of the application field. Since the problem is NP-hard, an Iterative Solution Procedure and a Dynamic Programming model are developed for solving larger instances of problem in polynomial time. In addition, propositions that support the robust model are provided along with theoretical proofs. Appointment scheduling of two case studies, a Dentist’s clinic and VIA Rail Canada are performed. Both case studies exhibit high performance of the proposed robust model in terms of cost savings and computational efforts. This work will contribute both to the literature related to uncertainty handling in decision making and to the industries, which aim to achieve an efficient service system

Explainable Retinal Screening with Self-Management Support to Improve Eye-Health of Diabetic Population via Telemedicine

Diabetic Retinopathy (DR) is one major complication of diabetes and is the leading cause of blindness worldwide. Progression of DR and complete vision loss can be prevented by keeping diabetes in control and by early diagnosis through annual eye screenings. However, cost, healthcare disparities, cultural limitations, lack of motivation, etc., are the main barriers against regular screening, especially for a few ethnically and racially minority communities. On the other hand, to well-manage and control diabetes, the diabetic population needs to be physically active and keep their weight healthy. From the perspective of Behavioral Science, Some self-management techniques based on motivational interviewing can be utilized to motivate people to take preventive and mandatory measures to control diabetes. However, technical solutions based on `Motivational Interviewing\u27 are still not sufficiently available to healthcare providers who work with the diabetic population. Thus, collaborative teamwork of Computer Science and Behavioral Science is contemporary to improve eye health and the overall health of the diabetic population. In this dissertation, a community telemedicine framework has been proposed and designed which can connect clinicians with community partners to organize retinal screenings in community settings rather than traditional clinical settings. Secondly, automating the initial retinal screenings utilizing Deep Learning models, particularly Convolutional Neural Network (CNN), can reduce ophthalmologists\u27 workload and cost of screening. However, such Machine Learning models lack transparency and cannot explain how these models make particular decisions. Thus, an explainable retinal screening model has been developed to facilitate the recommended annual screening to overcome this limitation. Finally, a Computer-guided Action Planning (CAP) tool has been designed and developed to motivate the diabetic population to adopt healthier behaviors through Brief Action Planning, a self-management support technique. Through several feasibility studies, it is evident that the contribution of this dissertation could be combined to help prevent vision loss from diabetes

Polynomially knotted 2-spheres

We show that every proper, smooth 2-knot is ambient isotopic to a polynomial embedding from $\mathbb{R}^2$ to $\mathbb{R}^4$. This representation is unique up to a polynomial isotopy. Using polynomial representation of classical long knots we show that all twist spun knots posses polynomial parametrization. We construct such parametrizations for few spun and twist spun knots and provide their $3$ dimensional projections using Mathematica

DEVELOPMENT AND IN-VITRO CHARACTERISATION OF CHITOSAN LOADED PACLITAXEL NANOPARTICLE

ABSTRACTObjectives: To meet the above aim the following objectives are undertaken: (1) Preparation of paclitaxel (PTX) loaded nanoparticles by differenttechniques, (2) In-vitro evaluations of the drug loaded nanoparticles and selection of optimized batch.Methods: PTX loaded chitosan nanoparticles were prepared by Ionic-crosslinking technique. In this technique, chitosan was dissolved in 0.25%v/vacetic acid solution. To this above solution 0.84%v/v, glutaraldehyde solution was added dropwise under high-speed homogenizer at 17000 rpm for1 hr.Result: Particle size of prepared nanoparticle formulations was found to be 345.175±5.66-815.125±8.355 nm with low PDI between 0.456. Themaximum entrapment of drug was found to be 88.57±2.533% with formulation F5. In-vitro release studies of the F5 formulation showed 57.8±1.735%release of drug after 24 hrs.Conclusion: The prepared nanoparticles were evaluated for its particle size, zeta potential, drug entrapment efficiency, in-vitro drug release study,and surface morphology studies by scanning electron microscopy. The results of Fourier transform infrared studies of 1:1 physical mixture of drug andexcipients confirmed the absence of incompatibility. Thus, the study concludes that PTX loaded nanoparticles were developed successfully by ioniccrosslinking method, which is expected to enhance the oral bioavailability of PTX.Keywords: Paclitaxel, Nanoparticles, Chitosan, Ionic-crosslinking, In-vitro release

Productivity Puzzling: A Study on Recent Behaviour of UK and Bangladesh

Productivity is a multi-faceted concept; no single definition can holistically describe it. However, in the simplest form, productivity signifies the ratio between the input and output. In achieving sustained economic growth of a country, increased productivity remains as the key component. Productivity signifies a continual striving towards the economically most efficient mode of production of goods, commodities, and services needed by a society. Prior to the mid-1980s, labour productivity growth was a useful barometer of the world economy: it was low when the economy was depressed and high when it was booming. In many larger advanced economies like UK labour productivity growth slowed sharply and remained subdued for years after the credit crisis of 2007/08. After the early 1980s productivity issues were considered as a priority area for action in Bangladesh: a small economic country, but Productivity has slowed down again significantly during the last decade (2001-2012) because of some reasons. In this paper, we tried to find out the reasons behind for productivity puzzling in UK as well as in Bangladesh. For  UK productivity puzzle, this study considered that workforce composition, lower business investment, flexibility of labour market, Impaired resource allocation, and public sector productivity were the major factors that might have caused productivity to fall and in Bangladesh, insignificant role of allocative efficiency of resources within industry, poor performing public sector, inadequate public sector investment, labor union, firm size and productivity are inversely related were the major factors that might had caused low productivity. In light of these findings, it is found that there is a similarity between productivity puzzling factor of UK and Bangladesh. Performance and investment in public sector and improper resource allocation are common productivity puzzling factor for both the countries. Keywords: Productivity Puzzling, UK, Banglades

Adsorptive Removal of a Pharmaceutical and Personal Care Product Oxybenzone from Water with Metal-Organic Frameworks

Oxybenzone, one of the most often detected pharmaceuticals and personal care products (PPCPS), from aqueous solutions and this PPCPs removal from water had been studied by using the highly porous metal-organic framework (MOF) ) MIL-101(Cr) and a modified MIL-101(Cr) called MIL-101-OH. Adsorption results showed that MIL-101-OH which contains functional group such as –OH, which was very effective for oxybenzone adsorption. The adsorption performance of MIL-101-OH over MIL-101-OH was found to be greater than that of MIL-101(Cr), which means the functionalization of primitive MOFs have a positive effect on adsorption. The kinetics of MIL-101-OH also showed higher result compare to MIL-101(Cr). So along with a high adsorption capacity and repaid adsorption which is important for commercial applications

Non-triviality of welded knots and ribbon torus-knots

In this paper we study welded knots and their invariants. We focus on generating examples of non-trivial knotted ribbon tori as the tube of welded knots that are obtained from classical knot diagrams by welding some of the crossings. Non-triviality is shown by determining the fundamental group of the concerned welded knot. Sample examples under consideration are the standard diagrams of the family of $(2,q)$ torus knots and the twist knots. Standard diagrams of knots from Rolfsen's tables with $6$ crossings are also discussed which are not in the family of torus and twist knots

Factors Influencing Job Satisfaction of Employees: A Study on Telecommunication Sector of Bangladesh.

Purpose This paper focuses on the employee satisfaction in telecommunication industry of Bangladesh. In addition, the significant of this study is to locate the reasons of employee satisfactions which have become strikingly consistent important issue to HRD scholars and practitioners in this country. Methodology A own prepared questionnaire, based on literature review, after a pilot survey, with the Likert-type scale was used for collecting data in this study. The questionnaire was given to 400 corporate executives who were selected based on purposive sampling and stratified random sampling techniques, finally 310 (77.5%) usable responses were received that were used for analysis. The hypothesized relationships were tested using SPSS 19 through regression analysis .Findings The study showed that inspiration of the communication between the company and employees, learning environment, need of the employees, and mental satisfaction about the job and supervisors’ evaluation system play a significant role in developing employee satisfaction level in the telecom industry in Bangladesh .Research limitations/ implications- The salient limitation of this paper is some important questions on survey instrument was ignored due to the selected companies’ privacy policy. Nonetheless, the researchers assume that the result of the study will be very effective for policy making in HR. Originality This is an empirical study on employee satisfaction with a large sample size that has not been carried out earlier in the telecommunication industry in Bangladesh. The study can be used for further research in telecommunication industry in Bangladesh. Keywords: Satisfaction, supervision, Learning environment, Organizational performance, Bangladesh

Mechanism of Type IA Topoisomerases

Topoisomerases in the type IA subfamily can catalyze change in topology for both DNA and RNA substrates. A type IA topoisomerase may have been present in a last universal common ancestor (LUCA) with an RNA genome. Type IA topoisomerases have since evolved to catalyze the resolution of topological barriers encountered by genomes that require the passing of nucleic acid strand(s) through a break on a single DNA or RNA strand. Here, based on available structural and biochemical data, we discuss how a type IA topoisomerase may recognize and bind single-stranded DNA or RNA to initiate its required catalytic function. Active site residues assist in the nucleophilic attack of a phosphodiester bond between two nucleotides to form a covalent intermediate with a 5\u27-phosphotyrosine linkage to the cleaved nucleic acid. A divalent ion interaction helps to position the 3\u27-hydroxyl group at the precise location required for the cleaved phosphodiester bond to be rejoined following the passage of another nucleic acid strand through the break. In addition to type IA topoisomerase structures observed by X-ray crystallography, we now have evidence from biophysical studies for the dynamic conformations that are required for type IA topoisomerases to catalyze the change in the topology of the nucleic acid substrates

A grey approach to predicting healthcare performance

© 2018 Elsevier Ltd The success of an organization or a particular activity is evaluated through the measurement of key performance indicators (KPIs). The aim of this paper is to analyze and predict the indicators of healthcare performance using grey systems theory. Recent advancements in science and technology have made the healthcare industry extremely efficient at collecting data using electronic claims systems such as electronic health records. Therefore, collecting field level primary data becomes easier and accumulate them to generate secondary data for research purpose and to get an insight of the organization performance is absolutely necessary. Our research analyzes the KPIs of a hospital based on a secondary data source. Since, secondary data contains uncertainty and sometimes poor information, grey prediction model suits best to make a prediction model in this regard. Conventional grey model has considerable drawbacks while making a rigorous prediction model. For this, we apply an improved grey prediction model to predict the KPIs of the healthcare performance indicators. Several error measures in our model give a best fit of the data and allow prediction of the KPIs. The prediction model gives good estimates of the quantitative indicators and produced error rate within an acceptable range. We observe that the KPIs of bed turnover rate (BTR) and bed occupancy rate (BOR) have an increasing trend, whereas the KPIs of average length of stay (ALOS), hospital death rate (HDR) and hospital infection rate (HIR) show a decreasing trend over time. The main contribution of this research is a grey-based prediction model that can provide managers with the information they need to evaluate and predict the performance of a hospital. The research indicates that managers should give greater priority to the indicators which will result in better patients’ satisfaction and improved profit margin. Healthcare managers striving towards better performance will now have an empirical basis upon which to formulate and adjust their strategies, after analyzing the predicted value