Online diagnosis of diabetes with Twitter data

Innovation in technology enables people to communicate, share information and look for their needs by just sitting in rooms and going through some clicks. While social media has played a very important role in connecting people worldwide, its potential has stretched beyond the innovative idea of connecting people through their social networks. While many thought there was no meeting point for the healthcare sector and social media, it was a surprise when research and innovations have shown that social media could lay a very significant role in the health care sector. Research has been done in developing models that could use social media as the data source for tracking diseases. Most of these analyses are based on models that prioritize strong correlations with seasonal and pandemic kinds of diseases over the health conditions of a specific individual user. The aim of this research is to develop a diabetes detecting tool at the individual level using a sample of Twitter IDs that have been collected from the Twitter search using the query -- \u27recently diagnosed\u27 and \u27diabetes\u27\u27. Based on text analysis of social media posts using Fisher\u27s exact test, without any medical settings, this thesis investigates the feasibility of diagnosing and classifying diabetes via machine learning techniques, Naive Bayes and Random Forest classifiers. It was found that more than half (20/30 ≈ 67%) of the users in the sample mentioned being tested positive for diabetes, about 27% (8/30) of the users mentioned the symptoms and got involved in diabetes related discussions, but did not mention about being tested positive and rest 4% had no mention of symptoms or diabetes --Abstract, page iii

Probing the collectivity in neutron-rich Cd isotopes via gamma-ray spectroscopy

The spin and configurational structure of excited states of 127Cd, 125Cd and 129Cd, having two proton and three, five and one neutron holes, respectively in the doubly magic 132Sn core have been studied. The isomeric states in Cd isotopes were populated in the fragmentation of a 136Xe beam at an energy of 750 MeV/u on a 9Be target of 4 g/cm2. The experiment was performed at GSI Darmstadt. The neutron-rich Cd isotopes were selected using the Bρ-∆E-Bρ method at the FRagment Separator (FRS). Event by event identification of fragments in terms of their A (mass) and Z (charge) was provided by the standard FRS detectors. The reaction residues were implanted in a plastic stopper surrounded by 15 Ge cluster detectors from the RISING array to detect the gamma decays. In 127Cd, an isomeric state with a half-life of 17.5(3) μs has been detected. This yrast (19/2)+ isomer is proposed to have mixed proton-neutron configurations and to decay by two competing stretched M2 and E3 transitions. Experimental results are compared with the isotone 129Sn. In 125Cd, apart from the previously observed (19/2)+ isomer, two new metastable states at 3896 keV and 2141 keV have been detected. A half-life of 13.6(2) μs was measured for the (19/2)+ isomer, having a decay structure similar to the corresponding isomeric state in 127Cd. The higher lying isomers have a half-life of 3.1(1) μs and 2.5(15) ns, respectively. Time distributions of delayed gamma transitions and gamma-gamma coincidence relations were exploited to construct decay schemes for the two nuclei. Comparison of the experimental data with shell-model calculations is also discussed. The new information provides input for the proton-neutron interaction in nuclei around the doubly magic 132Sn core. The gamma decays of the isomeric states in 129Cd were not observed experimentally. The reasons for the non-observation of delayed gamma rays for 129Cd are either an isomeric half-life of less than 93 ns based on the experimentally obtained isomeric ratios of the (19/2)+ in 127,125Cd, or an E3 spin trap emerging from shell-model calculations

Cerebral venous thrombosis presenting as subarachnoid haemorrhage

We present a 31 years old lady who was 19 days postpartum who was admitted with fits and loss of consciousness. At presentation Glasgow Coma Scale was 8/15. No focal deficit. CT scan brain showed findings suggestive of subarachnoid haemorrhage(SAH) in left sylvian fissure along with few parenchymal haemorrhagic areas in frontal and parietal lobes. MRI brain and MRV confirmed superior sagittal sinus thrombosis, inferior sagittal, straight and right transverse and sigmoid sinus thrombosis. Patient was treated conservatively and was anticoagulated for 6 months and had a complete recovery. Further workup of thrombophilia was negative. Postpartum being the only risk factor for cerebral venous thrombosis (CVT) in her. SAH can be a rare presenting symptom of CVT and should not preclude patients from receiving anticoagulation

Stroke like migraine attacks after Radiation therapy (smart) vs radiation Vasculopathy

Stroke like migraine attacks after radiotherapy (SMART) syndrome is a phenomenon of reversible neurologic dysfunction which occurs rarely years after radiotherapy for brain tumors. We present a 35years old patient who had new onset neurological dysfunction with fits twice in between a symptom free interval of one year. He had radiotherapy for grade 1 astrocytoma about 27 years ago. Tumor recurrence or growth was ruled out both times by neuroimaging. Alternate diagnosis like meningoencephalitis were also ruled out by appropriate workup. Patient was managed on antiepileptics and antiplatelets. Radiation induced vasculopathy was an important differential. The mechanism of both SMART and radiation induced vasculopathy appears similar. Having knowledge of such rare but important conditions is important for neurologist as it can save patients from unnecessary investigations

Development of Novel Models to Study Deep Brain Effects of Cortical Transcranial Magnetic Stimulation

Neurological disorders require varying types and degrees of treatments depending on the symptoms and underlying causes of the disease. Patients suffering from medication-refractory symptoms often undergo further treatment in the form of brain stimulation, e.g. electroconvulsive therapy (ECT), transcranial direct current stimulation (tDCS), deep brain stimulation (DBS), or transcranial magnetic stimulation (TMS). These treatments are popular and have been shown to relieve various symptoms for patients with neurological conditions. However, the underlying effects of the stimulation, and subsequently the causes of symptom-relief, are not very well understood. In particular, TMS is a non-invasive brain stimulation therapy which uses time-varying magnetic fields to induce electric fields on the conductive parts of the brain. TMS has been FDA-approved for treatment of major depressive disorder for patients refractory to medication, as well as symptoms of migraine. Studies have shown that TMS has relieved severe depressive symptoms, although researchers believe that it is the deeper regions of the brain which are responsible for symptom relief. Many experts theorize that cortical stimulation such as TMS causes brain signals to propagate from the cortex to these deep brain regions, after which the synapses of the excited neurons are changed in such a way as to cause plasticity. It has also been widely observed that stimulation of the cortex causes signal firing at the deeper regions of the brain. However, the particular mechanisms behind TMS-caused signal propagation are unknown and understudied. Due to the non-invasive nature of TMS, this is an area in which investigation can be of significant benefit to the clinical community. We posit that a deeper understanding of this phenomenon may allow clinicians to explore the use of TMS for treatment of various other neurological symptoms and conditions. This thesis project seeks to investigate the various effects of TMS in the human brain, with respect to brain tissue stimulation as well as the cellular effects at the level of neurons. We present novel models of motor neuron circuitry and fiber tracts that will aid in the development of deep brain stimulation modalities using non-invasive treatment paradigms

Smart Trash Bin Monitoring System

As an aim to clean up the roads, streets and to develop the infrastructure digitally of India’s cities and rural areas. We have provided a solution to monitor the Garbage level on the real time basis. The ultrasonic sensor in the garbage bin detect the Garbage level continuously and accordingly the system provides the information to the Municipality office. This will avoid the overflowing of the garbage bins. We use LDR sensor and Ultrasonic sensor to switch on light at night times near dust bin when the person is near the dustbin and detecting the gas evolved and fire accidents in the garbage

Compressing Genome Resequencing Data

Recent improvements in high-throughput next generation sequencing (NGS) technologies have led to an exponential increase in the number, size and diversity of available complete genome sequences. This poses major problems in storage, transmission and analysis of such genomic sequence data. Thus, a substantial effort has been made to develop effective data compression techniques to reduce the storage requirements, improve the transmission speed, and analyze the compressed sequences for possible information about genomic structure or determine relationships between genomes from multiple organisms.;In this thesis, we study the problem of lossless compression of genome resequencing data using a reference-based approach. The thesis is divided in two major parts. In the first part, we perform a detailed empirical analysis of a recently proposed compression scheme called MLCX (Maximal Longest Common Substring/Subsequence). This led to a novel decomposition technique that resulted in an enhanced compression using MLCX. In the second part, we propose SMLCX, a new reference-based lossless compression scheme that builds on the MLCX. This scheme performs compression by encoding common substrings based on a sorted order, which significantly improved compression performance over the original MLCX method. Using SMLCX, we compressed the Homo sapiens genome with original size of 3,080,436,051 bytes to 6,332,488 bytes, for an overall compression ratio of 486. This can be compared to the performance of current state-of-the-art compression methods, with compression ratios of 157 (Wang et.al, Nucleic Acid Research, 2011), 171 (Pinho et.al, Nucleic Acid Research, 2011) and 360 (Beal et.al, BMC Genomics, 2016)

Difficult choices : ethnocultural and religious identity, and attitudes toward women among South Asian Muslim Canadians

The purpose of the study was to examine the relation between ethnocultural identity, religious identity, and attitudes toward women. The current study proposed that both ethnocultural and religious identity were related to attitudes toward women. One hundred sixty-three Canadian Muslims of South Asian descent were administered three surveys: (1) the Acculturation Index (Ward & Kennedy, 1994); (2) Psychological Measure of Islamic Religiosity (PMIR) (Abu Raiya, 2006); and (3) Ambivalent Sexism Inventory (Glick & Fiske, 1996). Factor analysis was conducted on the PMIR resulting in a revised measure. Hypotheses were tested using correlational analyses. Subsequent exploratory analyses were conducted through multiple regressions. The results of the correlations from the study found that ethnic identity and religious identity are multidimensional and are related to each other in various ways, as well as to attitudes toward women. It was also found that certain cultural and religious dimensions predicted attitudes toward women