Algorithms of Distance, color & Shape Detection for 2-D Images

This paper represents our work on non contact distance calculation method. It is based on pixel variation of 2D images. This can be done by referencing two points in the image frames. The methodology of distance calculation starts with capturing of particular object image from any distances. Again capture another image of same object with some known distance. If an object goes far from the camera the object has a reduced size in the image. As the object moves closer to the camera the object becomes comparatively bigger. Thus we get the variation of pixel size between two images. Using the pixel variation we can calculate the distance of the object from the camera .This paper focuses on recognition of 2D shapes of objects such as square, circle, triangle, rectangle and ellipse as well as colors of objects. The algorithm was simulated and developed using MATLAB

The Frequency of Neuropsychiatric Sequelae After Traumatic Brain In-jury in the Global South: A systematic review and meta-analysis

Countries in the 'global south' are characterized by factors that contribute to the increased incidence of traumatic brain injury (TBI). This systematic review and meta-analysis aimed to assess the prevalence of neuropsychiatric sequelae following a TBI, specifically among the Western Asian, South Asian, and African regions of the global south. A literature review was conducted until August 20, 2021, for publications that measured psychiatric or cognitive impairment after TBI from the 83 countries that constitute the aforementioned regions. The main databases, such as PsycINFO, Scopus, PubMed/MEDLINE, ProQuest (English), Al-Manhal (Arabic) and Google Scholar, were selected for grey literature. Following the evaluation of the articles using the Joanna Briggs Institute guidelines, the random effects model was used to estimate the prevalence of depression, anxiety, posttraumatic stress disorders (PTSD), sleep disturbance related to TBI (TBI-SD), obsessive–compulsive disorder (OCD), and cognitive impairment. Of 56 non-duplicated studies identified by the initial search, 27 studies were eligible for systematic review and 23 for meta-analysis. The pooled prevalence of depression in a total sample of 1882 was 35·35% (95% CI=24·64–46·87%), of anxiety in a total sample of 1211 was 28·64% (95% CI=17·99–40·65%), of PTSD in a total sample of 426 was 19·94% (95% CI=2·35–46·37%), of OCD in a total sample of 313 was 19·48% (95% CI=0·23–58·06%), of TBI–SD in a total sample of 562 was 26·67% (95% CI=15·63–39·44%), and cognitive impairment in a total sample of 941 was 49·10% (95% CI=31·26–67·07%). To date, this is the first critical review that has examined the spectrum of post–TBI neuropsychiatric sequelae in the specified regions. While existing studies lack homogeneous data due to variability in the diagnostic tools and outcome measures utilised, the reported prevalence rates are significant and comparable to statistics from the global north. Keywords: traumatic brain injury; neuropsychiatric sequelae; global south; systematic review; meta-analysis; cognitive impairment; anxiety; depressio

A Large and Variable Leading Tail of Helium in a Hot Saturn Undergoing Runaway Inflation

Atmospheric escape shapes the fate of exoplanets, with statistical evidence for transformative mass loss imprinted across the mass-radius-insolation distribution. Here we present transit spectroscopy of the highly irradiated, low-gravity, inflated hot Saturn HAT-P-67 b. The Habitable Zone Planet Finder (HPF) spectra show a detection of up to 10% absorption depth of the 10833 Angstrom Helium triplet. The 13.8 hours of on-sky integration time over 39 nights sample the entire planet orbit, uncovering excess Helium absorption preceding the transit by up to 130 planetary radii in a large leading tail. This configuration can be understood as the escaping material overflowing its small Roche lobe and advecting most of the gas into the stellar -- and not planetary -- rest frame, consistent with the Doppler velocity structure seen in the Helium line profiles. The prominent leading tail serves as direct evidence for dayside mass loss with a strong day-/night- side asymmetry. We see some transit-to-transit variability in the line profile, consistent with the interplay of stellar and planetary winds. We employ 1D Parker wind models to estimate the mass loss rate, finding values on the order of $2\times10^{13}$ g/s, with large uncertainties owing to the unknown XUV flux of the F host star. The large mass loss in HAT-P-67 b represents a valuable example of an inflated hot Saturn, a class of planets recently identified to be rare as their atmospheres are predicted to evaporate quickly. We contrast two physical mechanisms for runaway evaporation: Ohmic dissipation and XUV irradiation, slightly favoring the latter.Comment: Submitted to The Astronomical Journa

Comparison between Efficacy of Human Milk Fortification Using Human Milk Fortifier versus Preterm Formula: A Retrospective Single-institutional Experience

Objectives: This study sought to evaluate the relative efficacy of expressed breast milk (EBM) fortified using human milk fortifier (HMF) compared to commercial preterm formula (PF) on preterm and very low birth weight (VLBW) infants in a major tertiary healthcare center in Oman. Methods: This retrospective cohort study included two cohorts of preterm (< 32 weeks gestation) or VLBW infants (birth weight < 1500 g) treated in the neonatal intensive care unit (NICU). Cohort one included infants who were given PF-fortified EBM between January and December 2016, and cohort two were given newly-introduced HMF-fortified EBM between November 2018 and December 2019. Analysis was performed to compare the cohorts with respect to baseline characteristics, primary outcomes, and secondary outcomes. Results: A total of 103 neonates were included (cohort 1: n = 55, cohort 2: n = 48). There were no significant differences in the growth of the weekly length, the growth of the head circumference, or discharge growth parameters. Compared to PF, HMF was associated with significantly better weight gain velocity (g/kg/day) during the first week (p =0.009) and second week (p =0.050) after starting fortification, lower need for other adjunctive forms of fortification (p =0.035), and lower rates of necrotizing enterocolitis in premature infants or VLBW (p =0.018). Conclusions: This is likely to be the first study to analyze the relative efficacy of HMF and PF in the Middle East. The results of this study will be helpful in guiding standards of nutritional care in NICUs in Oman

Role of matrix metalloproteinases in multi-system inflammatory syndrome and acute COVID-19 in children

INTRODUCTION: Multisystem Inflammatory Syndrome in children (MIS-C) is a serious inflammatory sequela of SARS-CoV2 infection. The pathogenesis of MIS-C is vague and matrix metalloproteinases (MMPs) may have an important role. Matrix metalloproteinases (MMPs) are known drivers of lung pathology in many diseases. METHODS: To elucidate the role of MMPs in pathogenesis of pediatric COVID-19, we examined their plasma levels in MIS-C and acute COVID-19 children and compared them to convalescent COVID-19 and children with other common tropical diseases (with overlapping clinical manifestations). RESULTS: Children with MIS-C had elevated levels of MMPs (P < 0.005 statistically significant) in comparison to acute COVID-19, other tropical diseases (Dengue fever, typhoid fever, and scrub typhus fever) and convalescent COVID-19 children. PCA and ROC analysis (sensitivity 84–100% and specificity 80–100%) showed that MMP-8, 12, 13 could help distinguish MIS-C from acute COVID-19 and other tropical diseases with high sensitivity and specificity. Among MIS-C children, elevated levels of MMPs were seen in children requiring intensive care unit admission as compared to children not needing intensive care. Similar findings were noted when children with severe/moderate COVID-19 were compared to children with mild COVID-19. Finally, MMP levels exhibited significant correlation with laboratory parameters, including lymphocyte counts, CRP, D-dimer, Ferritin and Sodium levels. DISCUSSION: Our findings suggest that MMPs play a pivotal role in the pathogenesis of MIS-C and COVID-19 in children and may help distinguish MIS-C from other conditions with overlapping clinical presentation

Unique cellular immune signatures of multisystem inflammatory syndrome in children

The clinical presentation of MIS-C overlaps with other infectious/non-infectious diseases such as acute COVID-19, Kawasaki disease, acute dengue, enteric fever, and systemic lupus erythematosus. We examined the ex-vivo cellular parameters with the aim of distinguishing MIS-C from other syndromes with overlapping clinical presentations. MIS-C children differed from children with non-MIS-C conditions by having increased numbers of naïve CD8(+) T cells, naïve, immature and atypical memory B cells and diminished numbers of transitional memory, stem cell memory, central and effector memory CD4(+) and CD8(+) T cells, classical, activated memory B and plasma cells and monocyte (intermediate and non-classical) and dendritic cell (plasmacytoid and myeloid) subsets. All of the above alterations were significantly reversed at 6–9 months post-recovery in MIS-C. Thus, MIS-C is characterized by a distinct cellular signature that distinguishes it from other syndromes with overlapping clinical presentations. Trial Registration: ClinicalTrials.gov clinicaltrial.gov. No: NCT04844242

Study of mould hardness for alpha set type resin bonded moulding sand system using Taguchi approach for metal casting applications

The quality of the castings are depended on many properties of sand mould like mould hardness, green compression strength, shear strength etc. and these properties in turn dependent on factors such as grain fineness number of sand, setting/curing time, amount of resin, amount of hardener, moisture content etc. Mould hardness is very important while transferring mould from moulding station to pouring station when the weight of the mould is above 100kg and may lead to defects. In the present work, an effort is made to study the mould hardness of a moulding sand specimen using Taguchi technique.L9 orthogonal array is used and experiments are conducted randomly. The main factors such as the amount of resin, amount of hardener and setting time were considered. Factors were selected based on Literature review and brainstorming session with foundries. The chemical (resin and hardener) used is alphas set type two part system. From experiments, it was observed that the Amount of resin and setting time are significant for mould hardness. Confirmation tests were conducted to validate the obtained results

Study of mould hardness for alpha set type resin bonded moulding sand system using Taguchi approach for metal casting applications

The quality of the castings are depended on many properties of sand mould like mould hardness, green compression strength, shear strength etc. and these properties in turn dependent on factors such as grain fineness number of sand, setting/curing time, amount of resin, amount of hardener, moisture content etc. Mould hardness is very important while transferring mould from moulding station to pouring station when the weight of the mould is above 100kg and may lead to defects. In the present work, an effort is made to study the mould hardness of a moulding sand specimen using Taguchi technique.L9 orthogonal array is used and experiments are conducted randomly. The main factors such as the amount of resin, amount of hardener and setting time were considered. Factors were selected based on Literature review and brainstorming session with foundries. The chemical (resin and hardener) used is alphas set type two part system. From experiments, it was observed that the Amount of resin and setting time are significant for mould hardness. Confirmation tests were conducted to validate the obtained results

A hierarchical anatomical classification schema for prediction of phenotypic side effects

<div><p>Prediction of adverse drug reactions is an important problem in drug discovery endeavors which can be addressed with data-driven strategies. SIDER is one of the most reliable and frequently used datasets for identification of key features as well as building machine learning models for side effects prediction. The inherently unbalanced nature of this data presents with a difficult multi-label multi-class problem towards prediction of drug side effects. We highlight the intrinsic issue with SIDER data and methodological flaws in relying on performance measures such as AUC while attempting to predict side effects.We argue for the use of metrics that are robust to class imbalance for evaluation of classifiers. Importantly, we present a ‘hierarchical anatomical classification schema’ which aggregates side effects into organs, sub-systems, and systems. With the help of a weighted performance measure, using 5-fold cross-validation we show that this strategy facilitates biologically meaningful side effects prediction at different levels of anatomical hierarchy. By implementing various machine learning classifiers we show that Random Forest model yields best classification accuracy at each level of coarse-graining. The manually curated, hierarchical schema for side effects can also serve as the basis of future studies towards prediction of adverse reactions and identification of key features linked to specific organ systems. Our study provides a strategy for hierarchical classification of side effects rooted in the anatomy and can pave the way for calibrated expert systems for multi-level prediction of side effects.</p></div

A hierarchical anatomical classification schema for prediction of phenotypic side effects - Fig 3

<p>(A) Distribution of side-effects across drugs showing presence of drugs associated with exceptionally large number of side effects. (B) Distribution of drugs across side effetcs depicting presence of adverse reactions that are linked to large number of drugs.</p