A Multi-Level Trust Management Scheme for the Internet of Things

The significance of the Internet of Things (IoT) in current trends is continuously rising. It is an umbrella term that signifies a network of physical devices that are embedded with electronics, software, sensors and connectivity that enable greater functions and services through the exchange of data accomplished through interconnection. The applications of the IoT are varied and numerous; they range from relatively simple home automation scenarios to the much more complex scenarios of interconnected smart cities. IoT is expected to dominate the future with huge amounts of content oriented traffic that is a result of intensive interactions between the millions of devices that will be available by then. The rising popularity of IoT has been accompanied by a corresponding rise in the number of issues. One of the issues is a lack of an established mechanism that deals with the issue of trust management. This issue is well addressed in the field of wireless sensor networks; an analogous framework for trust management does not exist for IoT. The complexity of the networked devices (allied with the complexity of the network itself) in addition to the fact that the environment in which the devices exist is itself continuously changing makes the development of a trust management scheme difficult. We propose a trust management scheme that helps establish trust between devices taking into account the nature, complexity and category of the interconnected devices. The level of service available to a node that requests a service from a service provider is predicated upon the trust level between the provider and requester. We elaborate on this concept and describe the emergence of trust over time that is also sensitive to the changing environment to which the devices might be subjected

Device Free Localisation Techniques in Indoor Environments

The location estimation of a target for a long period was performed only by device based localisation technique which is difficult in applications where target especially human is non-cooperative. A target was detected by equipping a device using global positioning systems, radio frequency systems, ultrasonic frequency systems, etc. Device free localisation (DFL) is an upcoming technology in automated localisation in which target need not equip any device for identifying its position by the user. For achieving this objective, the wireless sensor network is a better choice due to its growing popularity. This paper describes the possible categorisation of recently developed DFL techniques using wireless sensor network. The scope of each category of techniques is analysed by comparing their potential benefits and drawbacks. Finally, future scope and research directions in this field are also summarised

The value of story-making activities in the english classroom

In this paper, we will discuss the findings collected from an open-ended story-making activity conducted with a group of Class eight students from a semi-urban government school in Aizawl, Mizoram. The activity was part of the Connected Learning Initiative (CLIx)- English, a project undertaken at the Centre for Education Innovation and Action Research (CEI&AR), Tata Institute of Social Sciences (TISS), Mumbai. A group of students from the school were invited to work in pairs and write stories based on picture cues provided on a Technology Enabled Language Learning (hereafter, TELL) platform. Drawing from this field experience, we would like to suggest that imaginative, open-ended activities that involve students in crafting stories based on pictures and with a specified word limit per sentence, can hasten language learning. In our paper, we will discuss two such stories created by the students to illustrate our point

Multisystem Inflammatory Syndrome in Children in a 15-Year-Old Male with a Retropharyngeal Phlegmon

This is a case of a 15-year-old male with an initial diagnosis of a retropharyngeal phlegmon who ultimately developed new symptoms and laboratory findings consistent with MIS-C. This case report demonstrates an atypical initial presentation for MIS-C that has not been reported in the literature

Early identification of COVID-19 cytokine storm and treatment with anakinra or tocilizumab

OBJECTIVE: To examine outcomes among patients who were treated with the targeted anti-cytokine agents, anakinra or tocilizumab, for COVID-19 -related cytokine storm (COVID19-CS). METHODS: We conducted a retrospective cohort study of all SARS-coV2-RNA-positive patients treated with tocilizumab or anakinra in Kaiser Permanente Southern California. Local experts developed and implemented criteria to define COVID19-CS. All variables were extracted from electronic health records. RESULTS: At tocilizumab initiation (n = 52), 50 (96.2%) were intubated, and only seven (13.5%) received concomitant corticosteroids. At anakinra initiation (n = 41), 23 (56.1%) were intubated, and all received concomitant corticosteroids. Fewer anakinra-treated patients died (n = 9, 22%) and more were extubated/never intubated (n = 26, 63.4%) compared to tocilizumab-treated patients (n = 24, 46.2% dead, n = 22, 42.3% extubated/never intubated). Patients who died had more severe sepsis and respiratory failure and met COVID-CS laboratory criteria longer (median = 3 days) compared to those extubated/never intubated (median = 1 day). After accounting for differences in disease severity at treatment initiation, this apparent superiority of anakinra over tocilizumab was no longer statistically significant (propensity score-adjusted hazards ratio 0.46, 95% confidence interval 0.18–1.20). CONCLUSIONS: Prompt identification and treatment of COVID19-CS before intubation may be more important than the specific type of anti-inflammatory treatment. Randomized controlled trials of targeted anti-cytokine treatments and corticosteroids should report the duration of cytokine storm in addition to clinical severity at randomization

Serum GFAP for stroke diagnosis in regions with limited access to brain imaging (BE FAST India)

Introduction: Despite a high burden of stroke, access to rapid brain imaging is limited in many middle- and low-income countries. Previous studies have described the astroglial protein GFAP (glial fibrillary acidic protein) as a biomarker of intracerebral hemorrhage. The aim of this study was to test the diagnostic accuracy of GFAP for ruling out intracranial hemorrhage in a prospective cohort of Indian stroke patients. Patients and methods: This study was conducted in an Indian tertiary hospital (Christian Medical College, Ludhiana). Patients with symptoms suggestive of acute stroke admitted within 12 h of symptom onset were enrolled. Blood samples were collected at hospital admission. Single Molecule Array technology was used for determining serum GFAP concentrations. Results: A total number of 155 patients were included (70 intracranial hemorrhage, 75 ischemic stroke, 10 stroke mimics). GFAP serum concentrations were elevated in intracranial hemorrhage patients compared to ischemic stroke patients [median (interquartile range) 2.36 µg/L (0.61–7.16) vs. 0.18 µg/L (0.11–0.38), p < 0.001]. Stroke mimics patients had a median GFAP serum level of 0.14 µg/L (0.09–0.26). GFAP values below the cut-off of 0.33 µg/L (area under the curve 0.871) ruled out intracranial hemorrhage with a negative predictive value of 89.7%, (at a sensitivity for detecting intracranial hemorrhage of 90.0%). Discussion: The high negative predictive value of a GFAP test system allows ruling out patients with intracranial hemorrhage. Conclusion: In settings where immediate brain imaging is not available, this would enable to implement secondary prevention (e.g., aspirin) in suspected ischemic stroke patients as soon as possible

Clinico-Genomic Analysis Reveals Mutations Associated with COVID-19 Disease Severity: Possible Modulation by RNA Structure

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) manifests a broad spectrum of clinical presentations, varying in severity from asymptomatic to mortality. As the viral infection spread, it evolved and developed into many variants of concern. Understanding the impact of mutations in the SARS-CoV-2 genome on the clinical phenotype and associated co-morbidities is important for treatment and preventionas the pandemic progresses. Based on the mild, moderate, and severe clinical phenotypes, we analyzed the possible association between both, the clinical sub-phenotypes and genomic mutations with respect to the severity and outcome of the patients. We found a significant association between the requirement of respiratory support and co-morbidities. We also identified six SARS-CoV-2 genome mutations that were significantly correlated with severity and mortality in our cohort. We examined structural alterations at the RNA and protein levels as a result of three of these mutations: A26194T, T28854T, and C25611A, present in the Orf3a and N protein. The RNA secondary structure change due to the above mutations can be one of the modulators of the disease outcome. Our findings highlight the importance of integrative analysis in which clinical and genetic components of the disease are co-analyzed. In combination with genomic surveillance, the clinical outcome-associated mutations could help identify individuals for priority medical support