Accurate Identification of Traffic Signs Using Radar and Camera Fusion

Self-driving cars are no doubt the future of commuting for the world and it is paramount to make them as safe as possible on the road. The paper will cover a start to end process of making a system to easily collect data from the radar and camera and then using algorithms on the data collected to reduce anomalies and detect objects with better accuracy. Radar and camera both act as a data input for self-driving cars and are extremely important for the safety of both passengers and pedestrians, however, both of these sensors can be easily fooled. The advantage here is that what deceives one of the sensors doesn’t always mislead the other one, hence, using the suitable traits of each to overcome the deficiencies of the other will make them more robust and less susceptible to be fooled by such anomalies. By the end of this paper, the reader will have an in-depth understanding of how data is taken in, manipulated, and converted into results that power a self-driving car

Online Signature Verification and Authentication using Smart Phones

The proposed system is designed to determine whether the person signing on any touch screen device is authenticated user or not. This can be done by verifying his/her handwritten signature which is a socially accepted biometric trait for authenticating an individual. There are two types of handwritten signature verification systems: offline and online systems. In an off-line system, just an image of the user?s signature is acquired without additional attributes, whereas, in an online system, a sequence of x-y coordinates of the user?s signature, along with many other attributes are also acquired. In our paper, we have created a client (mobile) application which captures the user?s signature and extracts various features like pressure, time and x-y co-ordinates and the server application verifies these features to find whether the signature has been done by an authenticated user or a forger. The implementation is done using Python and the GUI is coded using Xcode

Assessing Diagnostic Accuracy of Haemoglobin Colour Scale in Real-life Setting

The study was undertaken to determine diagnostic accuracy of Haemoglobin Colour Scale (HCS) in hands of village-based community health workers (CHWs) in real-life community setting in India. Participants (501 women) were randomly selected from 8 villages belonging to a project area of SEWA-Rural, a voluntary organization located in India. After receiving a brief training, CHWs and a research assistant obtained haemoglobin readings using HCS and HemoCueTM (reference) respectively. Sensitivity, specificity, positive and negative predictive-values, and likelihood ratios were calculated. Bland-Altman plot was constructed. Mean haemoglobin value, using HCS and HemoCueTM were 11.02 g/dL (CI 10.9-11.2) and 11.07 g/dL (CI 10.9-11.2) respectively. Mean difference between haemoglobin readings was 0.95 g/dL. Sensitivity of HCS was 0.74 (CI 0.65-0.81) and 0.84 (CI 0.8-0.87) whereas specificity was 0.84 (CI:0.51-0.98) and 0.99 (CI:0.97- 0.99) using haemoglobin cutoff limits of 10 g/dL and 7 g/dL respectively. CHWs can accurately diagnose severe and moderately-severe anaemia by using HCS in real-life field condition after a brief training

Sickle cell disease and pregnancy outcomes: a study of the community-based hospital in a tribal block of Gujarat, India

Background: Sickle cell disease (SCD) is a hereditary blood disorder prevalent in tribal regions of India. SCD can increase complications during pregnancy and in turn negatively influence pregnancy outcomes. This study reports the analysis of tribal maternal admissions in the community-based hospital of SEWA Rural (Kasturba Maternity Hospital) in Jhagadia block, Gujarat. The objective of the study is to compare the pregnancy outcomes among SCD, sickle cell trait and non-SCD admissions. This study also estimated the risk of adverse pregnancy outcomes for SCD admissions. Methods: The data pertains to four and half years from March 2011 to September 2015. The total tribal maternal admissions were 14640, out of which 10519 admissions were deliveries. The admissions were classified as sickle cell disease, sickle cell trait and non-sickle cell disease. The selected pregnancy outcomes and maternal complications were abortion, stillbirth, Caesarean section, haemoglobin levels, blood transfusion, preterm pregnancy, newborn birth weight and other diagnosed morbidities (IUGR, PIH, eclampsia, preterm labour pain). The odds ratios for each risk factor were estimated for sickle cell patients. The odds ratios were adjusted for the respective years. Results: Overall, 1.2% (131 out of 10519) of tribal delivery admissions was sickle cell admissions. Another 15.6% (1645 out of 10519) of tribal delivery admissions have sickle cell trait. The percentage of stillbirth was 9.9% among sickle cell delivery admission compared to 4.2% among non-sickle cell deliveries admissions. Among sickle cell deliveries, 70.2% were low birth weight compared to 43.8% of non-sickle cell patient. Similarly, almost half of the sickle cell deliveries needed the blood transfusion. The 45.0% of sickle cell delivery admissions were pre-term births, compared to 17.3% in non-SCD deliveries. The odds ratio of severe anaemia, stillbirth, blood transfusion, Caesarean section, and low birth weight was significantly higher for sickle cell admissions compared to non-sickle cell admissions. Conclusions: The study exhibited that there is a high risk of adverse pregnancy outcomes for women with SCD. It may also be associated with the poor maternal and neonatal health in these tribal regions. Thus, the study advocates the need for better management of SCD in tribal Gujarat

Precision Targeting of Bacterial Pathogen Via Bi-Functional Nanozyme Activated by Biofilm Microenvironment

Human dental caries is an intractable biofilm-associated disease caused by microbial interactions and dietary sugars on the host\u27s teeth. Commensal bacteria help control opportunistic pathogens via bioactive products such as hydrogen peroxide (H2O2). However, high-sugar consumption disrupts homeostasis and promotes pathogen accumulation in acidic biofilms that cause tooth-decay. Here, we exploit the pathological (sugar-rich/acidic) conditions using a nanohybrid system to increase intrinsic H2O2 production and trigger pH-dependent reactive oxygen species (ROS) generation for efficient biofilm virulence targeting. The nanohybrid contains glucose-oxidase that catalyzes glucose present in biofilms to increase intrinsic H2O2, which is converted by iron oxide nanoparticles with peroxidase-like activity into ROS in acidic pH. Notably, it selectively kills Streptococcus mutans (pathogen) without affecting Streptococcus oralis (commensal) via preferential pathogen-binding and in situ ROS generation. Furthermore, nanohybrid treatments potently reduced dental caries in a rodent model. Compared to chlorhexidine (positive-control), which disrupted oral microbiota diversity, the nanohybrid had significant higher efficacy without affecting soft-tissues and the oral-gastrointestinal microbiomes, while modulating dental health-associated microbial activity in vivo. The data reveal therapeutic precision of a bi-functional hybrid nanozyme against a biofilm-related disease in a controlled-manner activated by pathological conditions. © 2020 The Author

How a thrombectomy service can reduce hospital deficit:a cost-effectiveness study

BACKGROUND: There is level 1 evidence for cerebral thrombectomy with thrombolysis in acute large vessel occlusion. Many hospitals are now contemplating setting up this life-saving service. For the hospital, however, the first treatment is associated with an initial high cost to cover the procedure. Whilst the health economic benefit of treating stroke is documented, this is the only study to date performing matched-pair, patient-level costing to determine treatment cost within the first hospital episode and up to 90 days post-event. METHODS: We conducted a retrospective coarsened exact matched-pair analysis of 50 acute stroke patients eligible for thrombectomy. RESULTS: Thrombectomy resulted in significantly more good outcomes (mRS 0–2) compared to matched controls (56% vs 8%, p = 0.001). More patients in the thrombectomy group could be discharged home (60% vs 28%), fewer were discharged to nursing homes (4% vs 16%), residential homes (0% vs 12%) or rehabilitation centres (8% vs 20%). Thrombectomy patients had fewer serious adverse events (n = 30 vs 86) and were, on average, discharged 36 days earlier. They required significantly fewer physiotherapy sessions (18.72 vs 46.49, p = 0.0009) resulting in a median reduction in total rehabilitation cost of £4982 (p = 0.0002) per patient. The total cost of additional investigations was £227 lower (p = 0.0369). Overall, the median cost without thrombectomy was £39,664 per case vs £22,444, resulting in median savings of £17,221 (p = 0.0489). CONCLUSIONS: Mechanical thrombectomy improved patient outcome, reduced length of hospitalisation and, even without procedural reimbursement, significantly reduced cost to the thrombectomy providing hospital

Collateral Automation for Triage in Stroke:Evaluating Automated Scoring of Collaterals in Acute Stroke on Computed Tomography Scans

Computed tomography angiography (CTA) collateral scoring can identify patients most likely to benefit from mechanical thrombectomy and those more likely to have good outcomes and ranges from 0 (no collaterals) to 3 (complete collaterals). In this study, we used a machine learning approach to categorise the degree of collateral flow in 98 patients who were eligible for mechanical thrombectomy and generate an e-CTA collateral score (CTA-CS) for each patient (e-STROKE SUITE, Brainomix Ltd., Oxford, UK). Three experienced neuroradiologists (NRs) independently estimated the CTA-CS, first without and then with knowledge of the e-CTA output, before finally agreeing on a consensus score. Addition of the e-CTA improved the intraclass correlation coefficient (ICC) between NRs from 0.58 (0.46–0.67) to 0.77 (0.66–0.85, p = 0.003). Automated e-CTA, without NR input, agreed with the consensus score in 90% of scans with the remaining 10% within 1 point of the consensus (ICC 0.93, 0.90–0.95). Sensitivity and specificity for identifying favourable collateral flow (collateral score 2–3) were 0.99 (0.93–1.00) and 0.94 (0.70–1.00), respectively. e-CTA correlated with the Alberta Stroke Programme Early CT Score (Spearman correlation 0.46, p < 0.001) highlighting the value of good collateral flow in maintaining tissue viability prior to reperfusion. In conclusion, ­e-CTA provides a real-time and fully automated approach to collateral scoring with the potential to improve consistency of image interpretation and to independently quantify collateral scores even without expert rater input

Dissecting regulatory T cell expansion using polymer microparticles presenting defined ratios of self-antigen and regulatory cues

Biomaterials allow for the precision control over the combination and release of cargo needed to engineer cell outcomes. These capabilities are particularly attractive as new candidate therapies to treat autoimmune diseases, conditions where dysfunctional immune cells create pathogenic tissue environments during attack of self-molecules termed self-antigens. Here we extend past studies showing combinations of a small molecule immunomodulator co-delivered with self-antigen induces antigen-specific regulatory T cells. In particular, we sought to elucidate how different ratios of these components loaded in degradable polymer particles shape the antigen presenting cell (APC) -T cell interactions that drive differentiation of T cells toward either inflammatory or regulatory phenotypes. Using rapamycin (rapa) as a modulatory cue and myelin self-peptide (myelin oligodendrocyte glycoprotein- MOG) – self-antigen attacked during multiple sclerosis (MS), we integrate these components into polymer particles over a range of ratios and concentrations without altering the physicochemical properties of the particles. Using primary cell co-cultures, we show that while all ratios of rapa:MOG significantly decreased expression of co-stimulation molecules on dendritic cells (DCs), these levels were insensitive to the specific ratio. During co-culture with primary T cell receptor transgenic T cells, we demonstrate that the ratio of rapa:MOG controls the expansion and differentiation of these cells. In particular, at shorter time points, higher ratios induce regulatory T cells most efficiently, while at longer time points the processes are not sensitive to the specific ratio. We also found corresponding changes in gene expression and inflammatory cytokine secretion during these times. The in vitro results in this study contribute to in vitro regulatory T cell expansion techniques, as well as provide insight into future studies to explore other modulatory effects of rapa such as induction of maintenance or survival cues