A Blockchain based system for Healthcare Digital Twin

Digital Twin (DT) is an emerging technology that replicates any physical phenomenon from a physical space to a digital space in congruence with the physical state. However, devising a Healthcare DT model for patient care is seen as a challenging task as the lack of adequate data collection structure. There are also security and privacy concerns as healthcare data is very sensitive and can be used in malicious ways. Because of these current research gaps, the proper way of acquiring the structured data and managing them in a secure way is very important. In this article, we present a mathematical data model to accumulate the patient relevant data in a structured and predefined way with proper delineation. Additionally, the provided data model is described in harmony with real life contexts. Then, we have used the patient centric mathematical data model to formally define the semantic and scope of our proposed Healthcare Digital Twin ( HDT ) system based on Blockchain. Accordingly, the proposed system is described with all the key components as well as with detailed protocol flows and an analysis of its different aspects. Finally, the feasibility of the proposed model with a critical comparison with other relevant research works have been provided

Studies on genetic variability and interrelationship in bottle gourd [Lagenaria siceraria (Mol.) Standl]

The genetic parameters were studied to elucidate the genetic variability, correlation and path co-efficient analysis in thirty-nine genotypes of bottle gourd [Lagenaria siceraria (Mol.) Standl] in randomized complete block design with three replications. Observations were recorded for eleven quantitative characters viz., days to first male flower open, days to first female flower open, node number of first female flower, braches plant-1, days to harvest, number of fruits plant-1, fruit weight, fruit length, fruit girth, 100 seed weight and yield ton ha-1. The analysis of variance showed highly significant differences for all the characters studied indicating considerable variability among the genotypes. The highest GCV (35.57%) and PCV (35.62%) were observed for fruit length. The differences between GCV and PCV were high for fruit number plant-1 and days to first male flower open indicating environmental influences. High heritability associates with high estimates of genetic advance in percent of mean were noted for length of fruit, yield, girth of fruit and number of fruits plant-1. It indicated presence of additive gene effect and selection for these traits would be effective. Yield were positively and significantly correlated with fruit weight, 100 seed weight, branch plant-1 and number of fruits plant-1 .Negative associations of yield were noted with days to first male and female flower open, days to harvest and length of fruit. Path analysis revealed that fruits plant-1 (0.93) and weight of fruit (0.467) had very high positive effect on fruit yield ton ha-1 .Int. J. Agril. Res. Innov. & Tech. 8 (1): 14-17, June, 201

Leveraging self-sovereign identity & distributed ledger technology in renewable energy certificate ecosystems

Renewable Energy Certificates (RECs) are tradable units that represent the commodity in the form of environmental attributes generated for each unit of electricity produced by a renewable energy source. Furthermore, the energy sector's digitalization ushers in new crucial enablers like Distributed Ledger Technology (DLT), which may be used for REC record tracking and trading. Unfortunately, there are a number of outstanding issues such as the lack of a common standard for the representation, communication, and verification of REC, reliance on centralized entities, and others. In order to harness the true potential of energy DLT and REC, it is imperative to address these issues. In this visionary article, we propose a holistic approach which leverages a novel decentralized identity mechanism called Self-sovereign Identity (SSI) and DLT. We present its architecture, based on a rigorous threat model and requirement analysis as well as detailed use-cases to illustrate how the architecture can be used in different REC use-cases

Real, forged or deep fake? Enabling the ground truth on the internet

The proliferation of smartphones and mobile communication has enabled users to capture images or videos and share them immediately on social networking and messaging platforms. Unfortunately, these platforms are also used to manipulate the masses by performing social engineering attacks by sharing fabricated images (or videos). These attacks cause public shame, ethnic violence and claim lives. With the rise of advanced image processing tools, the deep fakes are automated, and their implications are boundless. In this article, we discuss different types of modification of images/videos and survey the corresponding methods and tools. We also highlight the ongoing efforts to detect fake images and videos using advanced machine learning tools and fact-checking. Along with these tools, we also need different complementary approaches discouraging the production and propagation of manipulative forged images and videos on the Internet. This paper further emphasizes that we desperately need socio-technological solutions that empower end-users with the right tools to make an informed moral decision while producing, uploading, and sharing media. Finally, supporting this, we discuss a holistic blockchain-based solution

A reinforcement-learning-based model for resilient load balancing in Hyperledger Fabric

Blockchain with its numerous advantages is often considered a foundational technology with the potential to revolutionize a wide range of application domains, including enterprise applications. These enterprise applications must meet several important criteria, including scalability, performance, and privacy. Enterprise blockchain applications are frequently constructed on private blockchain platforms to satisfy these criteria. Hyperledger Fabric is one of the most popular platforms within this domain. In any privacy blockchain system, including Fabric, every organisation needs to utilise a peer node (or peer nodes) to connect to the blockchain platform. Due to the ever-increasing size of blockchain and the need to support a large user base, the monitoring and the management of different resources of such peer nodes can be crucial for a successful deployment of such blockchain platforms. Unfortunately, little attention has been paid to this issue. In this work, we propose the first-ever solution to this significant problem by proposing an intelligent control system based on reinforcement learning for distributing the resources of Hyperledger Fabric. We present the architecture, discuss the protocol flows, outline the data collection methods, analyse the results and consider the potential applications of the proposed approach

Differential livelihood adaptation to social-ecological change in coastal Bangladesh

Social-ecological changes, brought about by the rapid growth of the aquaculture industry and the increased occurrence of climatic stressors, have significantly affected the livelihoods of coastal communities in Asian mega-deltas. This paper explores the livelihood adaptation responses of households of different wealth classes, the heterogeneous adaptation opportunities, barriers and limits (OBLs) faced by these households and the dynamic ways in which these factors interact to enhance or impede adaptive capacities. A mixed methods approach was used to collect empirical evidence from two villages in coastal Bangladesh. Findings reveal that households’ adaptive capacities largely depend on their wealth status, which not only determine their availability of productive resources, but also empower them to navigate social-ecological change in desirable ways. Households operate within a shared response space, which is shaped by the broader socio-economic and political landscape, as well as their previous decisions that can lock them in to particular pathways. While an adaptive response may be effective for one social group, it may cause negative externalities that can undermine the adaptation options and outcomes of another group. Adaptation OBLs interact in complex ways; the extent to which these OBLs affect different households depend on the specific livelihood activities being considered and the differential values and interests they hold. To ensure more equitable and environmentally sustainable livelihoods in future, policies and programs should aim to expand households’ adaptation space by accounting for the heterogeneous needs and complex interdependencies between response processes of different groups

Driving vascular endothelial cell fate of human multipotent Isl1+ heart progenitors with VEGF modified mRNA

Distinct families of multipotent heart progenitors play a central role in the generation of diverse cardiac, smooth muscle and endothelial cell lineages during mammalian cardiogenesis. The identification of precise paracrine signals that drive the cell-fate decision of these multipotent progenitors, and the development of novel approaches to deliver these signals in vivo, are critical steps towards unlocking their regenerative therapeutic potential. Herein, we have identified a family of human cardiac endothelial intermediates located in outflow tract of the early human fetal hearts (OFT-ECs), characterized by coexpression of Isl1 and CD144/vWF. By comparing angiocrine factors expressed by the human OFT-ECs and non-cardiac ECs, vascular endothelial growth factor (VEGF)-A was identified as the most abundantly expressed factor, and clonal assays documented its ability to drive endothelial specification of human embryonic stem cell (ESC)-derived Isl1+ progenitors in a VEGF receptor-dependent manner. Human Isl1-ECs (endothelial cells differentiated from hESC-derived ISL1+ progenitors) resemble OFT-ECs in terms of expression of the cardiac endothelial progenitor- and endocardial cell-specific genes, confirming their organ specificity. To determine whether VEGF-A might serve as an in vivo cell-fate switch for human ESC-derived Isl1-ECs, we established a novel approach using chemically modified mRNA as a platform for transient, yet highly efficient expression of paracrine factors in cardiovascular progenitors. Overexpression of VEGF-A promotes not only the endothelial specification but also engraftment, proliferation and survival (reduced apoptosis) of the human Isl1+ progenitors in vivo. The large-scale derivation of cardiac-specific human Isl1-ECs from human pluripotent stem cells, coupled with the ability to drive endothelial specification, engraftment, and survival following transplantation, suggest a novel strategy for vascular regeneration in the heart

Depressive symptoms associated with COVID-19 preventive practice measures, daily activities in home quarantine and suicidal behaviors: findings from a large-scale online survey in Bangladesh

Background: The world is facing a public health emergency situation caused by the COVID-19 pandemic. Psychological wellbeing among individuals worldwide has been negatively affected by the pandemic especially in low- and middle-income countries such as Bangladesh. The present study aimed to assess the estimate of depressive symptoms and investigated its associations with COVID-19 preventive practice measures, daily activities in home quarantine, and suicidal behaviors in a large-scale Bangladeshi online survey. Methods: An online-based cross-sectional survey was widely distributed to Bangladeshi citizens. A total of 13,654 participants (61.0% male; mean age = 24.0 years [SD = 6.0]; age range 18–65 years) completed the survey between May and June (2020). The survey included socio-demographics and COVID-19-related questions, along with lifestyle, suicidal, and psychometric measures. Hierarchical regression was performed to determine significant associations between depression and examined variables. Results: The estimate of depressive symptoms during the COVID-19 pandemic was 43.5%. Based on hierarchical regression analysis, depression was significantly associated with not engaging in COVID-19 preventive measures, daily activities in home quarantine (e.g., playing videogames), and suicidal behaviors. Conclusions: Depressive symptoms appeared to be high during the COVID-19 pandemic in Bangladesh. To fight against the pandemic, mental health issues as well as physical health issues need to be taken into consideration

In search of self-sovereign identity leveraging blockchain technology

In recent times, with the advent of blockchain technology, there is an optimism surrounding the concept of self-sovereign identity which is regarded to have an influential effect on how we interact with each other over the Internet in future. There are a few works in the literature which examine different aspects of self-sovereign identity. Unfortunately, the existing works are not methodological and comprehensive at all. Moreover, there exist different notions of what the term self-sovereign identity means. To exploit its full potential, it is essential to ensure a common understanding in a formal way. This paper aims to achieve this goal by providing the first-ever formal and rigorous treatment of the concept of self-sovereign identity using a mathematical model. This paper examines the properties that a self-sovereign identity should have and explores the impact of self-sovereign identity over the laws of identity. It also highlights the essential life-cycles of an identity management system and inter-relates how the notion of self-sovereign identity can be applied in these life-cycles. In addition, the paper illustrates several envisioned flows involving a self-sovereign identity leveraging blockchain technology covering different aspects of an identity management system. All in all, this paper presents the first formal and comprehensive step toward an academic investigation of self-sovereign identity