In Search of the Theory of Constitutional Machinery Failure (Emergency) Models in India and Pakistan: a Comparative Exploration

In spite of a contextual and constitutional affinity, Comparative Constitutional Law has been an unexplored area in South Asia. The article relates to one form of Constitutional Emergency in India and Pakistan - Constitutional Machinery Failure Emergency in the provincial units, which has a colonial past and an oppressive present. With identical provision in the constitutions of India and Pakistan, it sanctions almost unfettered power to the centre to declare an emergency relating to Constitutional Machinery Failure: one of the most abused provisions of Indian and Pakistani Constitutional Polity. The unique system of Constitutional Machinery Failure has also gone through huge changes, at times influenced by each other, scaling the modification of Emergency; the article also tries to conceptualize Constitutional Machinery Failure Emergency in India and Pakistan.

Andreev and normal reflections in gapped bilayer graphene-superconductor junctions

We study the Andreev and normal reflection processes -- retro as well as specular -- in a bilayer graphene-superconductor junction where equal and opposite displacement fields are applied for the top and bottom layers to induce a band gap. By employing the Dirac-Bogoliubov-de Gennes equation for the gapped bilayer graphene-superconductor junction, we calculate the reflections probabilities within the scattering theory approach. The subgap conductance, calculated in the framework of Blonder-Tinkham-Klapwijk formalism, shows the contribution from the Andreev retro-reflection (specular-reflection) when the applied bias voltage is below (above) the Fermi energy. Notably, both retro and specular reflections are modified in the presence of the displacement field, and the retro-to-specular crossover gets amplified when the displacement field is relatively small. They can be further tuned to either specular or retro Andreev reflection by adjusting the Fermi energy. Furthermore, our study reveals the simultaneous existence of double Andreev reflections and double normal reflections when the displacement field becomes comparable to the interlayer coupling strength. The existence of the normal retro-reflection process in a bilayer graphene-superconductor junction is a new finding which shows a distinctive feature in the conductance that can be experimentally verified.Comment: 11 pages, 9 figure

Applying Deep Learning to Predicting Dementia and Mild Cognitive Impairment

Dementia has a large negative impact on the global healthcare and society. Diagnosis is rather challenging as there is no standardised test. The purpose of this paper is to conduct an analysis on ADNI data and determine its effectiveness for building classification models to differentiate the categories Cognitively Normal (CN), Mild Cognitive Impairment (MCI), and Dementia (DEM), based on tuning three Deep Learning models: two Multi-Layer Perceptron (MLP1 and MLP2) models and a Convolutional Bidirectional Long Short-Term Memory (ConvBLSTM) model. The results show that the MLP1 and MLP2 models accurately distinguish the DEM, MCI and CN classes, with accuracies as high as 0.86 (SD 0.01). The ConvBLSTM model was slightly less accurate but was explored in view of comparisons with the MLP models, and for future extensions of this work that will take advantage of time-related information. Although the performance of ConvBLSTM model was negatively impacted by a lack of visit code data, opportunities were identified for improvement, particularly in terms of pre-processing

HealthFog: An ensemble deep learning based Smart Healthcare System for Automatic Diagnosis of Heart Diseases in integrated IoT and fog computing environments

Cloud computing provides resources over the Internet and allows a plethora of applications to be deployed to provide services for different industries. The major bottleneck being faced currently in these cloud frameworks is their limited scalability and hence inability to cater to the requirements of centralized Internet of Things (IoT) based compute environments. The main reason for this is that latency-sensitive applications like health monitoring and surveillance systems now require computation over large amounts of data (Big Data) transferred to centralized database and from database to cloud data centers which leads to drop in performance of such systems. The new paradigms of fog and edge computing provide innovative solutions by bringing resources closer to the user and provide low latency and energy-efficient solutions for data processing compared to cloud domains. Still, the current fog models have many limitations and focus from a limited perspective on either accuracy of results or reduced response time but not both. We proposed a novel framework called HealthFog for integrating ensemble deep learning in Edge computing devices and deployed it for a real-life application of automatic Heart Disease analysis. HealthFog delivers healthcare as a fog service using IoT devices and efficiently manages the data of heart patients, which comes as user requests. Fog-enabled cloud framework, FogBus is used to deploy and test the performance of the proposed model in terms of power consumption, network bandwidth, latency, jitter, accuracy and execution time. HealthFog is configurable to various operation modes that provide the best Quality of Service or prediction accuracy, as required, in diverse fog computation scenarios and for different user requirements

Comparative efficacy of two poeciliid fish in indoor cement tanks against chikungunya vector Aedes aegypti in villages in Karnataka, India

<p>Abstract</p> <p>Background</p> <p>In 2006, severe outbreaks of <it>Aedes aegypti</it>-transmitted chikungunya occurred in villages in Karnataka, South India. We evaluated the effectiveness of combined information, education and communication (IEC) campaigns using two potential poeciliid larvivorous fish guppy (<it>Poecilia reticulata</it>) and mosquitofish (<it>Gambusia affinis</it>), in indoor cement tanks for <it>Aedes </it>larval control.</p> <p>Methods</p> <p>Trials were conducted in two villages (Domatmari and Srinivaspura) in Tumkur District from March to May 2006 for <it>Poecilia </it>and one village (Balmanda) in Kolar District from July to October 2006 for <it>Gambusia</it>. A survey on knowledge, attitude and practice (KAP) on chikungunya was initially conducted and IEC campaigns were performed before and after fish release in Domatmari (IEC alone, followed by IEC + <it>Poecilia</it>) and Balmanda (IEC + <it>Gambusia</it>). In Srinivaspura, IEC was not conducted. Larval surveys were conducted at the baseline followed by one-week and one-month post-intervention periods. The impact of fish on <it>Aedes </it>larvae and disease was assessed based on baseline and post-intervention observations.</p> <p>Results</p> <p>Only 18% of respondents knew of the role of mosquitoes in fever outbreaks, while almost all (<it>n </it>= 50 each) gained new knowledge from the IEC campaigns. In Domatmari, IEC alone was not effective (OR 0.54; <it>p </it>= 0.067). Indoor cement tanks were the most preferred <it>Ae. aegypti </it>breeding habitat (86.9%), and had a significant impact on <it>Aedes </it>breeding (Breteau Index) in all villages in the one-week period (<it>p </it>< 0.001). In the one-month period, the impact was most sustained in Domatmari (OR 1.58, <it>p </it>< 0.001) then Srinivaspura (OR 0.45, <it>p </it>= 0.063) and Balmanda (OR 0.51, <it>p </it>= 0.067). After fish introductions, chikungunya cases were reduced by 99.87% in Domatmari, 65.48% in Srinivaspura and 68.51% in Balmanda.</p> <p>Conclusions</p> <p><it>Poecilia </it>exhibited greater survival rates than <it>Gambusia </it>(86.04 <it>vs</it>.16.03%) in cement tanks. Neither IEC nor <it>Poecilia </it>alone was effective against <it>Aedes </it>(<it>p </it>> 0.05). We conclude that <it>Poecilia </it>+ IEC is an effective intervention strategy. The operational cost was 0.50 (US$0.011, 1 US$= 47) per capita per application. Proper water storage practices, focused IEC with <it>Poecilia </it>introductions and vector sanitation involving the local administration and community, is suggested as the best strategy for <it>Aedes </it>control.</p

Lentiviral hematopoietic stem cell gene therapy for X-linked severe combined immunodeficiency

-linked severe combined immunodeficiency (SCID-X1) is a profound deficiency of T, B, and natural killer (NK) cell immunity caused by mutations in IL2RG encoding the common chain (γc) of several interleukin receptors. Gamma-retroviral (γRV) gene therapy of SCID-X1 infants without conditioning restores T cell immunity without B or NK cell correction, but similar treatment fails in older SCID-X1 children. We used a lentiviral gene therapy approach to treat five SCID-X1 patients with persistent immune dysfunction despite haploidentical hematopoietic stem cell (HSC) transplant in infancy. Follow-up data from two older patients demonstrate that lentiviral vector γc transduced autologous HSC gene therapy after nonmyeloablative busulfan conditioning achieves selective expansion of gene-marked T, NK, and B cells, which is associated with sustained restoration of humoral responses to immunization and clinical improvement at 2 to 3 years after treatment. Similar gene marking levels have been achieved in three younger patients, albeit with only 6 to 9 months of follow-up. Lentiviral gene therapy with reduced-intensity conditioning appears safe and can restore humoral immune function to posthaploidentical transplant older patients with SCID-X1