IMPACT OF ADHD ON ADOLESCENCE BEHAVIOR AND OTHER COMORBIDITIES FOCUSED ON CONDUCT DISORDERS, ODD/CD AND ANXIETY DISORDER

The purpose of this research proposal is to conduct a study of ADHD impact on adolescence behavior and other comorbidities. ADHD is the neurological disorder which is the most common childhood disorders and characterized by a persistent and trans-situational pattern of age-inappropriate inattention, hyperactivity, and impulsivity. The aim of the research subject is to find out how it is impacting adolescence behavior and develop other comorbidities such as anxiety disorder, eating disorder, ODD/CD along with analyzing the impact, causes, relations and solutions addressing the same

Analysis of Management of ITP: Single Centre Retrospective Comparison of Dapsone and Azathioprine as second line therapeutic agents

INTRODUCTION: Idiopathic thrombocytopenic purpura (ITP), also known as autoimmune thrombocytopenic purpura, is an entity characterized by isolated thrombocytopenia often occurring in the absence of identifiable and specific precipitants. It is an acquired disease that affects both children and adults and causes a transient or persistent decrease in platelet count. Depending upon the degree of thrombocytopenia it is associated with an increased risk of bleeding. AIMS AND OBJECTIVES OF THE STUDY: To assess efficacy of dapsone and azathioprine children and adults with steroid refractory or steroid dependent ITP and relapsed ITP treated in our institute. METHODOLOGY: We included patients treated with either dapsone or azathioprine for steroid refractory/dependent or relapsed ITP during 5 year period (March 1st 2007 to March 1st 2012). RESULTS: Three hundred patients were included in the study; 104 (34.7%) children & 196 (65.3%) adults. Median ITP duration was 5 months (1-262). Overall response over median treatment duration of 10 months (1-61) was 58.6%, with equivalent response (58.8% and 58.5%) with dapsone and azathioprine respectively. In children with steroid refractory/dependent ITP, dapsone exhibited significantly better response than azathioprine (p=0.023). Median response duration was significantly longer with azathioprine-60 months (2-60) than with dapsone (p=0.015). Relapses on therapy was higher with dapsone than azathioprine (p=0.007). Response less than CR & steroid refractory/dependent ITP were significant predictors of relapse on therapy. Event free survival was significantly better in patients responding to azathioprine compared to dapsone. There were no deaths in present cohort of patients with ITP. CONCLUSION: Present study confirms comparable efficacy of dapsone and azathioprine, although azathioprine produced more durable responses than dapsone. The findings of our study need to be validated in prospective randomized control setting

A Robust Student Attendance Monitoring System using NFC Technology and Biometrics

In most of the colleges across the globe, an efficient and authenticated attendance monitoring system for students has not been developed yet. In this paper, we are proposing a non-intrusive system wherein students can record their attendance by providing their fingerprint while they are seated in their places. This system makes use of NFC enabled smart phones, NFC tags, a biometric fingerprint scanner App and Wi-Fi for storing the attendance online. It provides authentication of students and security of data. Secure session is maintained by NFC tags using encryption. The lecture time can be saved since no manual attendance is required

A mosquito (Anopheles stephensi) angiotensin I-converting enzyme (ACE) is induced by a blood meal and accumulates in the developing ovary

AbstractAngiotensin I-converting enzyme (ACE) has a key role in regulating levels of several circulating peptides in mammals and has a vital role in male fertility. ACE has recently been found in insects, where its role is unclear. A mutant allele of the ACE gene (Ance) of Drosophila melanogaster is embryonic lethal, indicating an important role for the enzyme in development. We now report the presence of ACE in female Anopheles stephensi mosquitoes and that the enzyme is induced by a blood-meal. ACE accumulates in developing ovaries and passes into the mosquito eggs, where it may play a role in the metabolism of peptides during embryogenesis. The ovarian ACE has an Mr of 70 kDa and is inhibited by captopril and lisinopril with IC50 values of 0.1 μM and 0.6 μM, respectively

Consistent Training via Energy-Based GFlowNets for Modeling Discrete Joint Distributions

Generative Flow Networks (GFlowNets) have demonstrated significant performance improvements for generating diverse discrete objects $x$ given a reward function $R(x)$, indicating the utility of the object and trained independently from the GFlowNet by supervised learning to predict a desirable property $y$ given $x$. We hypothesize that this can lead to incompatibility between the inductive optimization biases in training $R$ and in training the GFlowNet, potentially leading to worse samples and slow adaptation to changes in the distribution. In this work, we build upon recent work on jointly learning energy-based models with GFlowNets and extend it to learn the joint over multiple variables, which we call Joint Energy-Based GFlowNets (JEBGFNs), such as peptide sequences and their antimicrobial activity. Joint learning of the energy-based model, used as a reward for the GFlowNet, can resolve the issues of incompatibility since both the reward function $R$ and the GFlowNet sampler are trained jointly. We find that this joint training or joint energy-based formulation leads to significant improvements in generating anti-microbial peptides. As the training sequences arose out of evolutionary or artificial selection for high antibiotic activity, there is presumably some structure in the distribution of sequences that reveals information about the antibiotic activity. This results in an advantage to modeling their joint generatively vs. pure discriminative modeling. We also evaluate JEBGFN in an active learning setting for discovering anti-microbial peptides.Comment: 9 Pages, 10 Figure

Production Technology of Lead Zirconate Titanate Type-4 Spherical Elements for Underwater Transducers

The paper describes the production technology evolved for the fabrication of 60 mm hollow spherical elements from lead zirconate titanate type-4 material, suitable for use in the manufacture of underwater omnidirectional transducers. It covers the characteristics of the starting powder, techniques of isostatic pressing, precision spherical machining, sintering to produce dielectrically sound, distortion-free hemispheres to the required physical dimensions, electroding, poling to achieve the inherent electromechanical properties, adhesive bonding of hemispheres and evaluation of ultimate dielectric and piezoelectric properties of the spheres

Metallographic Image Fusion

Image processing plays important role in manufacturing, aerospace, biomedical fields. To determine the classification of metallic sample, edge structure and images without blur are required. Instead of finding the noise kernel blur section of images can be removed by using multiple images fusion. There are different methods used for image fusions like average method, maxima, wavelet transform. For image fusion discrete wavelet transform is used. Image fusion improves the quality of image, data content. In this paper three images are used to fuse together. This images having standard size of 640x480 pixels. Image fusion improves the quality so that edge structure can be determined. According to edge structure the classification is done using ASTME standards

A generalized model to estimate field size for solar-only parabolic trough plant

Paper presented to the 3rd Southern African Solar Energy Conference, South Africa, 11-13 May, 2015.A number of computer performance simulations have been developed for modelling the performance of parabolic trough plants, most of which are proprietary or require very detailed inputs. Hence, there is a need to develop a generalized model that allows the designer to quickly estimate the solar field size for a parabolic trough plant at a given location. In order to cater to this need, a generalized model has been developed using the equations, correlations and typical values of certain parameters available in the open literature. The paper presents the complete details of various equations, correlations, loss models and the general data to be used by designer and outlines a systematic procedure coded in MatlabTM to evaluate solar field size for solar-only parabolic trough plant. Finally, to demonstrate this procedure, the model has been used to estimate the solar field size for a small 25 kWe solar-only trough plant at SVNIT, Surat, India. The results of the model indicate the solar field size of 245m2 for a 25 kWe plant to be installed at SVNIT, Surat.dc201

Using an agent-based model to analyze the dynamic communication network of the immune response

<p>Abstract</p> <p>Background</p> <p>The immune system behaves like a complex, dynamic network with interacting elements including leukocytes, cytokines, and chemokines. While the immune system is broadly distributed, leukocytes must communicate effectively to respond to a pathological challenge. The Basic Immune Simulator 2010 contains agents representing leukocytes and tissue cells, signals representing cytokines, chemokines, and pathogens, and virtual spaces representing organ tissue, lymphoid tissue, and blood. Agents interact dynamically in the compartments in response to infection of the virtual tissue. Agent behavior is imposed by logical rules derived from the scientific literature. The model captured the agent-to-agent contact history, and from this the network topology and the interactions resulting in successful versus failed viral clearance were identified. This model served to integrate existing knowledge and allowed us to examine the immune response from a novel perspective directed at exploiting complex dynamics, ultimately for the design of therapeutic interventions.</p> <p>Results</p> <p>Analyzing the evolution of agent-agent interactions at incremental time points from identical initial conditions revealed novel features of immune communication associated with successful and failed outcomes. There were fewer contacts between agents for simulations ending in viral elimination (<it>win</it>) versus persistent infection (<it>loss</it>), due to the removal of infected agents. However, early cellular interactions preceded successful clearance of infection. Specifically, more Dendritic Agent interactions with TCell and BCell Agents, and more BCell Agent interactions with TCell Agents early in the simulation were associated with the immune <it>win </it>outcome. The Dendritic Agents greatly influenced the outcome, confirming them as hub agents of the immune network. In addition, unexpectedly high frequencies of Dendritic Agent-self interactions occurred in the lymphoid compartment late in the <it>loss </it>outcomes.</p> <p>Conclusions</p> <p>An agent-based model capturing several key aspects of complex system dynamics was used to study the emergent properties of the immune response to viral infection. Specific patterns of interactions between leukocyte agents occurring early in the response significantly improved outcome. More interactions at later stages correlated with persistent inflammation and infection. These simulation experiments highlight the importance of commonly overlooked aspects of the immune response and provide insight into these processes at a resolution level exceeding the capabilities of current laboratory technologies.</p