Nlcviz: Tensor Visualization And Defect Detection In Nematic Liquid Crystals

Visualization and exploration of nematic liquid crystal (NLC) data is a challenging task due to the multidimensional and multivariate nature of the data. Simulation study of an NLC consists of multiple timesteps, where each timestep computes scalar, vector, and tensor parameters on a geometrical mesh. Scientists developing an understanding of liquid crystal interaction and physics require tools and techniques for effective exploration, visualization, and analysis of these data sets. Traditionally, scientists have used a combination of different tools and techniques like 2D plots, histograms, cut views, etc. for data visualization and analysis. However, such an environment does not provide the required insight into NLC datasets. This thesis addresses two areas of the study of NLC data---understanding of the tensor order field (the Q-tensor) and defect detection in this field. Tensor field understanding is enhanced by using a new glyph (NLCGlyph) based on a new design metric which is closely related to the underlying physical properties of an NLC, described using the Q-tensor. A new defect detection algorithm for 3D unstructured grids based on the orientation change of the director is developed. This method has been used successfully in detecting defects for both structured and unstructured models with varying grid complexity

A retrograde study to evaluate the maternal and fetal outcome of severe oligohydramnios in singleton term (37-40 weeks) gestation

Background: Oligohydromnios is a condition where there is very low or absent amniotic fluid and it demands intense antepartum, intrapartum care and fetal surveillance, as it is frequently associated with IUGR, fetal distress, PIH, PROM, fetal renal abnormalities as renal agenesis, bilateral cystic kidneys and obstructive uropathy. Methods: Total 124 antenatal patients delivered at Department of Obstetrics and Gynecology at GMERS Medical College and General Hospital, Junagadh. During Period of September 2022 to February 2023 with gestational age between 37-40wks with AFI<1cms with intact membranes were studied and analyzed retrospectively for perinatal and maternal outcome. Results: Out of 124 cases with oligohydramnios with AFI <1cm studied, about 115 cases underwent LSCS (92.7%). Most patients belong to age group of <25 about 85. Growth retardation seen in 38 (30.6 %), NICU admission seen in 35(28.2%) and new born with APGAR <7 @ 1 min seen in 30 cases (24.2%). Conclusions: According to our study on severe oligohydramnios, the common mode of delivery was caesarean section and indications for CS were PIH, FGR and poor BISHOP score with severe oligohydramnios. Growth retardation seen in babies who were born from severe oligohydramnios mother

Circuit analysis of the <i>Drosophila</i> brain using connectivity-based neuronal classification reveals organization of key communication pathways

AbstractWe present a functionally relevant, quantitative characterization of the neural circuitry of Drosophila melanogaster at the mesoscopic level of neuron types as classified exclusively based on potential network connectivity. Starting from a large neuron-to-neuron brain-wide connectome of the fruit fly, we use stochastic block modeling and spectral graph clustering to group neurons together into a common “cell class” if they connect to neurons of other classes according to the same probability distributions. We then characterize the connectivity-based cell classes with standard neuronal biomarkers, including neurotransmitters, developmental birthtimes, morphological features, spatial embedding, and functional anatomy. Mutual information indicates that connectivity-based classification reveals aspects of neurons that are not adequately captured by traditional classification schemes. Next, using graph theoretic and random walk analyses to identify neuron classes as hubs, sources, or destinations, we detect pathways and patterns of directional connectivity that potentially underpin specific functional interactions in the Drosophila brain. We uncover a core of highly interconnected dopaminergic cell classes functioning as the backbone communication pathway for multisensory integration. Additional predicted pathways pertain to the facilitation of circadian rhythmic activity, spatial orientation, fight-or-flight response, and olfactory learning. Our analysis provides experimentally testable hypotheses critically deconstructing complex brain function from organized connectomic architecture

Ferric carboxymaltose in the management of anemia due to non-obstetric conditions in women: a sub-group analysis of a large multi-center real-world study/PROMISE from India

Background: Real-world data on the efficacy and safety of intravenous ferric carboxymaltose (FCM) for treating iron deficiency anemia (IDA) in Indian women is limited. Methods: This was a sub-group analysis of the real-world PROMISE study, which analyzed data of women who received FCM for the management of IDA due to non-obstetric causes. Hematological parameters were retrieved from the charts at baseline and at 4±1 week and analyzed for the whole sub-group and by the severity of anemia. Results: In 442 women with anemia, Hb and serum ferritin improved by 2.77 gm/dl and 62.07 µg/l, respectively (p&lt;0.001 for both) at 4 weeks. There was a significant increase in red blood cell (RBC) count, hematocrit, mean corpuscular volume (MCV), and mean corpuscular hemoglobin (MCH) (p&lt;0.001 for all). In 192 subjects with severe anemia, there was a significant increase in Hb by 3.19 gm/dl, serum ferritin by 61.67 µg/l, RBC count, hematocrit, and MCV (p&lt;0.001 for all); and MCH (p=0.002). In 226 subjects with moderate anemia, there was a significant increase in Hb by 2.41 gm/dl, serum ferritin by 62.75 µg/l, and MCV (p&lt;0.001 for all); and MCH (p=0.003). No subject had mild anemia. No new safety signals or serious adverse events were reported. Physicians rated the efficacy and safety of FCM as very good to good in 94.1 and 94.2% of subjects, respectively. Conclusions: In Indian women, FCM effectively and safely corrects IDA due to non-obstetric causes, in a short span of 4 weeks.

A Hybrid Linear Iterative Clustering and Bayes Classification-Based GrabCut Segmentation Scheme for Dynamic Detection of Cervical Cancer

Cervical cancer earlier detection remains indispensable for enhancing the survival rate probability among women patients worldwide. The early detection of cervical cancer is done relatively by using the Pap Smear cell Test. This method of detection is challenged by the degradation phenomenon within the image segmentation task that arises when the superpixel count is minimized. This paper introduces a Hybrid Linear Iterative Clustering and Bayes classification-based GrabCut Segmentation Technique (HLC-BC-GCST) for the dynamic detection of Cervical cancer. In this proposed HLC-BC-GCST approach, the Linear Iterative Clustering process is employed to cluster the potential features of the preprocessed image, which is then combined with GrabCut to prevent the issues that arise when the number of superpixels is minimized. In addition, the proposed HLC-BC-GCST scheme benefits of the advantages of the Gaussian mixture model (GMM) on the extracted features from the iterative clustering method, based on which the mapping is performed to describe the energy function. Then, Bayes classification is used for reconstructing the graph cut model from the extracted energy function derived from the GMM model-based Linear Iterative Clustering features for better computation and implementation. Finally, the boundary optimization method is utilized to considerably minimize the roughness of cervical cells, which contains the cytoplasm and nuclei regions, using the GrabCut algorithm to facilitate improved segmentation accuracy. The results of the proposed HLC-BC-GCST scheme are 6% better than the results obtained by other standard detection approaches of cervical cancer using graph cuts

Emergency Department Presentation Of Acute Primary Angle Closure In The United States From 2008 To 2017

Purpose: Acute primary angle closure (APAC) is an ophthalmologic emergency. Nationwide data on the epidemiology and clinical characteristics of APAC are lacking despite the associated visual morbidity. Methods: Retrospective cross-sectional study using the Nationwide Emergency Department Sample (NEDS). The NEDS was queried by ICD-9/10 code for cases of APAC presenting to the United States emergency departments over a ten-year period from 2008 to 2017. All identified cases were included to produce nationally representative estimates. Linear regression and seasonality tests were used to identify trends. Reported outcomes include the incidence, demographics, seasonality, and economic impact of APAC regionally and nationwide. Results: A total of 23,203 APAC related ED visits were identified. The mean (SD) and median ages were 58.8 (16.2) and 60 years, respectively. Females (59.4%, p\u3c0.01), those in the lowest income quartile (6,983, 30.1%, p\u3c0.01), and those in the seventh decade of life (5,599, 24.1%) presented more frequently with APAC. Incidence of ED presentations within each age group rose with age, and annual incidence nationally increased significantly over the study period (p\u3c0.01). The Northeast region had the highest average incidence (0.93 per 100,000 population). Significant seasonal variation was seen regionally and nationally (p\u3c0.01). Median inflation adjusted charge per ED visit was $2496.10 and total inflation adjusted charges equaled$101.5 million. Conclusions: The incidence of APAC related ED visits in the United States is rising. High-risk groups include women, individuals of low socioeconomic status, and those between ages 50 and 70. Significant seasonal and regional trends were observed in ED presentations of APAC