Learning to Control Differential Evolution Operators

Evolutionary algorithms are widely used for optimsation by researchers in academia and industry. These algorithms have parameters, which have proven to highly determine the performance of an algorithm. For many decades, researchers have focused on determining optimal parameter values for an algorithm. Each parameter configuration has a performance value attached to it that is used to determine a good configuration for an algorithm. Parameter values depend on the problem at hand and are known to be set in two ways, by means of offline and online selection. Offline tuning assumes that the performance value of a configuration remains same during all generations in a run whereas online tuning assumes that the performance value varies from one generation to another. This thesis presents various adaptive approaches each learning from a range of feedback received from the evolutionary algorithm. The contributions demonstrate the benefits of utilising online and offline learning together at different levels for a particular task. Offline selection has been utilised to tune the hyper-parameters of proposed adaptive methods that control the parameters of evolutionary algorithm on-the-fly. All the contributions have been presented to control the mutation strategies of the differential evolution. The first contribution demonstrates an adaptive method that is mapped as markov reward process. It aims to maximise the cumulative future reward. Next chapter unifies various adaptive methods from literature that can be utilised to replicate existing methods and test new ones. The hyper-parameters of methods in first two chapters are tuned by an offline configurator, irace. Last chapter proposes four methods utilising deep reinforcement learning model. To test the applicability of the adaptive approaches presented in the thesis, all methods are compared to various adaptive methods from literature, variants of differential evolution and other state-of-the-art algorithms on various single objective noiseless problems from benchmark set, BBOB

Assessing the Regional and District Capacity for Operationalizing Emergency Obstetric Care through First Referral Units in Gujarat

Maternal mortality remains to be one of the very important public health problems in India. The maternal mortality estimates, is about (300-400/100,000 live births). There are diverse management issues, policy barriers to be overcome for improving maternal health. Especially, the operationalization of Emergency Obstetric Care (EmOC) and access to skilled care attendance during delivery. This study focuses on understanding the regional and district level capacity of the state government to operationalize First Referral Units for providing Emergency Obstetric care. This study is a part of a larger project for strengthening midwifery and Emergency Obstetric Care in India. The study apart from giving an in-depth insight into the functioning of various health facilities highlights the results from the basic to the more comprehensive level of EmOC services. It gives recommendation on various measures to rectify shortcomings noticed and make EmOC a more effective at different levels in the State of Gujarat. The study uses both primary and secondary data collection. The study was conducted in six regions of Gujarat -one district from each of these regions was selected. Out of these districts 27 health facilities were examined, which consists of seven district hospitals, eight designated as first referral units (FRU), four community health centers (CHC) and eight 24/7 primary health centers (PHC). Detailed field notes for individual facilities were prepared and analyzed subsequently for all facilities together. A common feature among all health centres were issues related to general infrastructure. Many times infrastructure planning (location, layout and maintenance) is left to engineers, who have limited knowledge about proper EmOC services. Poor infrastructure leads to poor quality of health services and wastage of resources. Through National Rural Health Mission (NRHM) and Rogi Kalyan Samiti funds major and minor repair/renovations are taking place to improve hospital buildings. In some health facilities from poor resource setting with high demand from patients were still able to deliver services. Human resources analysis suggests that there is shortage of specialists at FRUs, and committed nursing staff in labor room. As result of the Chiranjeevi initiative, the Below Poverty Line (BPL) population who earlier used to public health facilities are now accessing private facilities for delivery, and this has affected and decreased the workload of the public health facilities. Furthermore, there is lack of managerial skills at senior level hospital staff. Registers like birth, drug, Medical Termination of Pregnancy are maintained but not in standard format. Since complicated cases are not registered properly, maternal deaths are not reported. Even though the system of monitoring is well established at the state and district level, they are not properly followed. The funds for operationalization of First Referral Units come from department of family welfare. However, the administrative control is in the hands of department of medical services. Due to this factor monitoring system has become weak. The weak link between these two departments is the Regional Deputy Director who has only one administrative staff to take care of the issues in their region. The problem of monitoring the Primary Health Centres has become smooth with the appointment of new District Project Coordinators. Some facilities especially in district hospital reported that internal meetings and monitoring are happening because of the special interest of facility managers and newly appointed assistant hospitals administrators. In lower facilities this type of internal monitoring exists in a weak form. Underutilization of government facilities is a result of poor quality of services provided. In spite of reasonably developed health system, several problems of infrastructure, staffing, accountability and management capacity contribute to the poor functioning of facilities to act as an EmOC service delivery center. Some of the major bottlenecks in improving EmOC services are limited management capacity, lack of availability of blood in rural areas and poor registration of births and deaths and no monitoring of EmOC. District hospitals, FRUs, CHCs and Sub district hospitals come under the administrative control of the department of medical services. The clinical monitoring of these facilities lies with the department of health and family welfare. At the district level monitoring of these facilities are not properly done, therefore it effects directly the operationalization of the facilities. In the absence of adequate management capacity, the operationalization of EmOC is not well planned, executed or monitored, which results in delays in implementation and poor quality of care.

Maternal Health Situation in India: A Case Study

Maternal Health Services are one of the basic health services to be provided by nay government health system as pregnant women are one of the most vulnerable victims of dysfunctional health system, India, in spite of rapid economic progress is still farm away from the goal of lowering maternal mortality to less than 100 per 100,000 live births. It still accounts for 25.7% maternal deaths. The maternal mortality in India varies across the states. Geographical vastness and socio-cultural diversity make implementation of health sector reforms a difficult task. The chapter analyses the trends in maternal mortality and various maternal health programs implemented over the years including the maternal health care delivery system at various levels including the recent innovative strategies. It also identifies the reasons for limited success in maternal health and suggests measures to improve the current maternal health situation. It recommends improvement in maternal death reporting, evidence based, focused, long term strategy along with effective monitoring of implementation for improving Maternal Health situation. It also stress the need for regulation of private sector and proper Public Private Partnership (PPP) policy together with a strong political will for improving Maternal Health.

Deep Reinforcement Learning Based Parameter Control in Differential Evolution

Adaptive Operator Selection (AOS) is an approach that controls discrete parameters of an Evolutionary Algorithm (EA) during the run. In this paper, we propose an AOS method based on Double Deep Q-Learning (DDQN), a Deep Reinforcement Learning method, to control the mutation strategies of Differential Evolution (DE). The application of DDQN to DE requires two phases. First, a neural network is trained offline by collecting data about the DE state and the benefit (reward) of applying each mutation strategy during multiple runs of DE tackling benchmark functions. We define the DE state as the combination of 99 different features and we ana- lyze three alternative reward functions. Second, when DDQN is applied as a parameter controller within DE to a different test set of benchmark functions, DDQN uses the trained neural network to predict which mutation strategy should be applied to each parent at each generation according to the DE state. Benchmark functions for training and testing are taken from the CEC2005 benchmark with dimensions 10 and 30. We compare the results of the proposed DE-DDQN algorithm to several baseline DE algorithms using no online selection, random selection and other AOS methods, and also to the two winners of the CEC2005 competition. The results show that DE-DDQN outperforms the non-adaptive methods for all functions in the test set, while its results are comparable with the last two algorithms

Maternal Health Situation in India: A Case Study

Since the beginning of the Safe Motherhood Initiative, India has accounted for at least a quarter of maternal deaths reported globally. India's goal is to lower maternal mortality to less than 100 per 100,000 livebirths but that is still far away despite its programmatic efforts and rapid economic progress over the past two decades. Geographical vastness and sociocultural diversity mean that maternal mortality varies across the states, and uniform implementation of health-sector reforms is not possible. The case study analyzes the trends in maternal mortality nationally, the maternal healthcare-delivery system at different levels, and the implementation of national maternal health programmes, including recent innovative strategies. It identifies the causes for limited success in improving maternal health and suggests measures to rectify them. It recommends better reporting of maternal deaths and implementation of evidence-based, focused strategies along with effective monitoring for rapid progress. It also stresses the need for regulation of the private sector and encourages further public-private partnerships and policies, along with a strong political will and improved management capacity for improving maternal health

Maternal Health in Gujarat, India: A Case Study

Gujarat state of India has come a long way in improving the health indicators since independence, but progress in reducing maternal mortality has been slow and largely unmeasured or documented. This case study identified several challenges for reducing the maternal mortality ratio, including lack of the managerial capacity, shortage of skilled human resources, non-availability of blood in rural areas, and infrastructural and supply bottlenecks. The Gujarat Government has taken several initiatives to improve maternal health services, such as partnership with private obstetricians to provide delivery care to poor women, a relatively-short training of medical officers and nurses to provide emergency obstetric care (EmOC), and an improved emergency transport system. However, several challenges still remain. Recommendations are made for expanding the management capacity for maternal health, operationalization of health facilities, and ensuring EmOC on 24/7 (24 hours a day, seven days a week) basis by posting nurse-midwives and trained medical officers for skilled care, ensuring availability of blood, and improving the registration and auditing of all maternal deaths. However, all these interventions can only take place if there are substantially- increased political will and social awareness

Maternal Health Situation in India: A Case Study

Since the beginning of the Safe Motherhood Initiative, India has accounted for at least a quarter of maternal deaths reported globally. India's goal is to lower maternal mortality to less than 100 per 100,000 livebirths but that is still far away despite its programmatic efforts and rapid economic progress over the past two decades. Geographical vastness and sociocultural diversity mean that maternal mortality varies across the states, and uniform implementation of health-sector reforms is not possible. The case study analyzes the trends in maternal mortality nationally, the maternal healthcare-delivery system at different levels, and the implementation of national maternal health programmes, including recent innovative strategies. It identifies the causes for limited success in improving maternal health and suggests measures to rectify them. It recommends better reporting of maternal deaths and implementation of evidence-based, focused strategies along with effective monitoring for rapid progress. It also stresses the need for regulation of the private sector and encourages further public-private partnerships and policies, along with a strong political will and improved management capacity for improving maternal health

Who interacts with whom?:Social mixing insights from a rural population in India

Acute lower respiratory infections (ALRI) are a leading cause of morbidity and mortality globally, with most ALRI deaths occurring in children in developing countries. Computational models can be used to test the efficacy of respiratory infection prevention interventions, but require data on social mixing patterns, which are sparse in developing countries. We describe social mixing patterns among a rural community in northern India. During October 2015-February 2016, trained field workers conducted cross-sectional face-to-face standardized surveys in a convenience sample of 330 households in Faridabad District, Haryana State, India. Respondents were asked about the number, duration, and setting of social interactions during the previous 24 hours. Responses were compared by age and gender. Among the 3083 residents who were approached, 2943 (96%) participated, of whom 51% were male and the median age was 22 years (interquartile range (IQR) 9-37). Respondents reported contact (defined as having had a face-to-face conversation within 3 feet, which may or may not have included physical contact) with a median of 17 (IQR 12-25) people during the preceding 24 hours. Median total contact time per person was 36 person-hours (IQR 26-52). Female older children and adults had significantly fewer contacts than males of similar age (Kruskal-Wallis χ2 = 226.59, p<0.001), but spent a longer duration in contact with young children (Kruskal-Wallis χ2 = 27.26, p<0.001), suggesting a potentially complex pattern of differential risk of infection between genders. After controlling for household size and day of the week, respondent age was significantly associated with number and duration of contacts. These findings can be used to model the impact of interventions to reduce lower respiratory tract infections in India

Development of a Fast SARS-CoV-2 IgG ELISA, Based on Receptor-Binding Domain, and Its Comparative Evaluation Using Temporally Segregated Samples From RT-PCR Positive Individuals

SARS-CoV-2 antibody detection assays are crucial for gathering seroepidemiological information and monitoring the sustainability of antibody response against the virus. The SARS-CoV-2 Spike protein's receptor-binding domain (RBD) is a very specific target for anti-SARS-CoV-2 antibodies detection. Moreover, many neutralizing antibodies are mapped to this domain, linking antibody response to RBD with neutralizing potential. Detection of IgG antibodies, rather than IgM or total antibodies, against RBD is likely to play a larger role in understanding antibody-mediated protection and vaccine response. Here we describe a rapid and stable RBD-based IgG ELISA test obtained through extensive optimization of the assay components and conditions. The test showed a specificity of 99.79% (95% CI: 98.82-99.99%) in a panel of pre-pandemic samples (n = 470) from different groups, i.e., pregnancy, fever, HCV, HBV, and autoantibodies positive. Test sensitivity was evaluated using sera from SARS-CoV-2 RT-PCR positive individuals (n = 312) and found to be 53.33% (95% CI: 37.87-68.34%), 80.47% (95% CI: 72.53-86.94%), and 88.24% (95% CI: 82.05-92.88%) in panel 1 (days 0-13), panel 2 (days 14-20) and panel 3 (days 21-27), respectively. Higher sensitivity was achieved in symptomatic individuals and reached 92.14% (95% CI: 86.38-96.01%) for panel 3. Our test, with a shorter runtime, showed higher sensitivity than parallelly tested commercial ELISAs for SARS-CoV-2-IgG, i.e., Euroimmun and Zydus, even when equivocal results in the commercial ELISAs were considered positive. None of the tests, which are using different antigens, could detect anti-SARS-CoV-2 IgGs in 10.5% RT-PCR positive individuals by the fourth week, suggesting the lack of IgG response