A new clique polynomial approach for fractional partial differential equations

This paper generates a novel approach called the clique polynomial method (CPM) using the clique polynomials raised in graph theory and used for solving the fractional order PDE. The fractional derivative is defined in terms of the Caputo fractional sense and the fractional partial differential equations (FPDE) are converted into nonlinear algebraic equations and collocated with suitable grid points in the current approach. The convergence analysis for the proposed scheme is constructed and the technique proved to be uniformly convegant. We applied the method for solving four problems to justify the proposed technique. Tables and graphs reveal that this new approach yield better results. Some theorems are discussed with proof.

Optimising Malaria Control Interventions in Mali Based on Epidemiological Surveillance and Rainfall Data

Background In malaria endemic countries, control interventions are performed during the high malaria transmission season using epidemiological surveillance data. One such intervention, seasonal chemoprevention (SMC), consists of the monthly administration of antimalarial drugs to children under 5 years. This study proposes an anticipating approach for adapting the timing of SMC interventions in Mali and the number of rounds. Our primary objective was to select the best approach for anticipating the onset of the high transmission season in the different health districts of Mali based on epidemiological surveillance and rainfall data. Our secondary objective was to evaluate the number of malaria cases, hospitalisations, and deaths in children under 5 years that could be prevented in Mali using the selected approach and the additional cost associated.Method Confirmed malaria cases and weekly rainfall data were collected for the 75 health districts of Mali for the 2014-2019 period. The onset of the rainy season, the onset of the high transmission season, the lag between these two events and the duration of the high transmission season were determined for each health district. Two approaches for anticipating the onset of the high transmission season in 2019 were evaluated. Results In 2014-2019, the onset of the rainy season ranged from W17 April to W34 August and that of the high transmission season from W25 June to W40 September. The lag between these two events ranged from 5 to 12 weeks. The duration of the high transmission season ranged from 3 to 6 months. The best approach anticipated the onset of the high transmission season 2019 in June in 2 districts, July in 46 districts, August in 21 districts and September in 6 districts. Using this approach over the 2014-2019 period would have led to changing the timing of SMC interventions in 36 health districts and would have prevented 43,819 cases, 1,943 hospitalisations and 70 deaths in children under 5 years. The additional cost of using our proposed approach is less than 5% of the current approach. Conclusion Adapting the timing of SMC interventions using our proposed approach would improve the prevention of malaria cases, hospitalisations, and deaths for a reasonable additional cost.

More than Just a Brain Disorder: A Five-Point Manifesto for Psychological Care for People with Huntington’s Disease

Huntington’s disease (HD) is a rare and complex condition where affected individuals, family members, caregivers, and clinicians face a number of both long-term and fluctuating challenges. The predominant biomedical framework adopted in HD to date has traditionally viewed it as a brain disorder first and foremost. As a consequence, one of the most challenging aspects of the condition—psychological difficulties and their care—is often not given the emphasis it deserves in everyday clinical practice. Here, we propose a manifesto outlining five points to address the quality, effectiveness, availability, and accessibility of psychological care in HD. These include (1) Listening to People with HD, (2) Reformulating Difficulties Psychologically, (3) Exploring New Interventions, (4) Increasing Psychological Provision, and (5) Learning from Other Conditions. As the search for a cure continues, we hope that this manifesto will create a new impetus towards refining the current approach to psychological difficulties in HD and ultimately improve the quality of life of the tens of thousands of families affected by HD worldwide.

A practical framework for achieving value creation and capture in healthcare through process improvement

PurposeThe purpose of this study was to examine the concept of value in healthcare through a practical appraisal of the applicability of a conceptual framework, which is aimed at supporting the measurement and realisation of financial benefits from process improvement (PI) activities in a hospital setting.Design/methodology/approachA single case study of a hospital system in Melbourne, Victoria, Australia, was used to assess the applicability of the framework. The study sought to verify the framework's intention, that PI methods could be used to address known wastes that contribute to the cost of providing healthcare. The case study examines the current approach taken by the hospital to measure and realise financial benefits from PI activities and compares these to the components of the Strategy to Balance Cost and Quality in Health Care framework to assess its applicability in practice.FindingsThe case study revealed that the steps described in the framework were fundamentally in place albeit with some variation. Importantly, the case study identified an additional step that could be added into the framework to support hospitals to better define their portfolio of initiatives to deliver value. The case study also clarified three types of contributory elements that should be in place for the application of the framework to be successful.Practical implicationsThe Framework to Achieve Value in Healthcare is offered to hospitals as a model by which they can look to reduce expenditure through the removal of non-value adding activities. The modification to the conceptual framework has arisen from a single case study and would benefit from further testing by other hospitals in other policy settings (i.e. other countries).Originality/valueThis is the first paper to examine and enhance an existing framework to assist hospitals balance cost and quality through PI.

Dynamic characteristics and Functional Analysis Provide new insights into the role of GauERF105 in resistance against Verticillium wilt in Cotton

Verticillium wilt is the most devastating disease of cotton and it results in huge yield losses every year in the fields. The underlying mechanisms of VW in cotton are not well explored yet. In the current approach we used the transcriptome data from G. australe in response to Verticillium wilt attack to mine the ERF TFs and prove their potential role in resistance against VW attack in cotton. We identified 23 ERFs in total, and on the basis of expression at different time points i.e., 24h, 48h and 72h post inoculation and selected GauERF105 for further validation. We performed VIGS in cotton and over expression in Arabidopsis respectively. Moreover, DAB and trypan staining also suggests that the impact of disease was more in the wildtype as compared to transgene lines. On the basis of our results, we confirmed that GauERF105 is the key candidate and playing a key role for defending cotton against VW attack. Current finding might be helpful for generating resistance germplasm in cotton and it will be beneficial to recover the yield losses in field.

Fostering CRM Through Artificial Intelligence

The use of technology has always provided competitive advantage to organizations. The current approach of adapting a new technology is the long-term planning. AI has become a new paradigm of enhancing organizational capabilities. AI is not a substitute of human intelligence but a strong support in terms of process automation. Apart from this, the decision-making process also gets streamlined. The success of business is when the customer is happy. To create and retain customer loyalty, effective CRM is required. The current chapter focuses on adoption of AI for efficient CRM and the factors for its successful implementation.

Hypertensive Retinopathy Classification Using Improved Clustering Algorithm and the Improved Convolution Neural Network

Hypertensive retinopathy is a disorder that causes hypertension which includes abnormalities in the retina that triggers vision problems. An effective automatic diagnosis and grading of the hypertensive retinopathy would be very useful in the health system. This chapter presents an improved activation function on the CNN by recognizing the lesions present in the retina and afterward surveying the influenced retina as indicated by the hypertensive retinopathy various sorts. The current approach identifies the symptoms associated of retinopathy for hypertension. This chapter presents an up-to-date review on hypertensive retinopathy detection systems that implement a variety of image processing techniques, including fuzzy image processing, along various improved activation function techniques used for feature extraction and classification. The chapter also highlights the available public databases, containing eye fundus images, which can be currently used in the hypertensive retinopathy research.

Big Data Analytics in Supply Chain Management

The current approach to supply chain intelligence has some fundamental challenges when confronted with the scale and characteristics of big data. In this chapter, applications, challenges and new trends in supply chain big data analytics are discussed and background research of big data initiatives related to supply chain management is provided. The methodology and the unified model for supply chain big data analytics which comprises the whole business intelligence (data science) lifecycle is described. It enables creation of the next-generation cloud-based big data systems that can create strategic value and improve performance of supply chains. Finally, example of supply chain big data solution that illustrates applicability and effectiveness of the model is presented.