The Pastness of the Present and the Presentness of the Past: A Study of Nav Bajwa’s Film Radua

The present paper is an attemp t to locate the cultural production of the film in relation to the dialectical relationship between the past and the present The paper has analyzed Nav Bajwa s film Radua 2018 as a manifestation of this interconnection by situating it in the nuanced space formed by the confluence of moral codes of medieval Punjab and undivided Punjab on the one hand and the power structures of contemporary Punjab on the other The film as a representational form alw ays plays a key role in the constellation of images and representations through which a populace experiences reality As a genre the film is in fact a peculiar confluence of human endeavor and technology that animates objects through the combination of light and speed This combination of light and speed and the ability of the camera to capture the real world with all its nuances qualify it as an art form that generally has an immediate impact on the consciousness of the viewers The innate mass appeal of the film also assigns it a peculiar pedagogic ability At the same time the film that involves huge capital and the essential function of showing cannot be overtly political still it cannot help carrying cracks in its symbolic order exposing the political unconscious of the tim

Catalytic conversion of glycerol to value-added liquid chemicals

Glycerol is one of the by-products of transesterification of fatty acids for the production of bio-diesel. Value-added products such as hydrogen, wood stabilizers and liquid chemicals from catalytic treatment of glycerol can improve the economics of the bio-diesel production process. Catalytic conversion of glycerol can be used for production of value-added liquid chemicals. In this work, a systematic study has been conducted to evaluate the effects of operating conditions on glycerol conversion to liquid chemical products in the presence of acid catalysts. Central composite design for response surface method was used to design the experimental plan. Experiments were performed in a fixed-bed reactor using HZSM-5, HY, silica-alumina and ã-alumina catalysts. The temperature, carrier gas flow rate and weight hourly space velocity (WHSV) were maintained in the range of 350-500 oC, 20-50 mL/min and 5.40-21.60 h -1, respectively. The main liquid chemicals detected in liquid product were acetaldehyde, acrolein, formaldehyde and hydroxyacetone. Under all experimental conditions complete glycerol conversion was obtained over silica-alumina and ã-alumina. A maximum liquid product yield of approximately 83 g/100g feed was obtained with these two catalysts when the operating conditions were maintained at 380 oC, 26 mL/min and 8.68 h-1. Maximum glycerol conversions of 100 wt% and 78.8 wt% were obtained in the presence of HY and HZSM-5 at temperature, carrier gas flow rate and WHSV of 470 oC, 26 mL/min and 8.68 h-1. HY and HZSM-5 produced maximum liquid product of 80.9 and 59.0 g/100 g feed at temperature of 425 and 470 oC, respectively.Silica-alumina produced the maximum acetaldehyde (~24.5 g/100 g feed) whereas ã-alumina produced the maximum acrolein (~25 g/100 g feed). Also, silica-alumina produced highest formaldehyde yield of 9g/100 g feed whereas HY produced highest acetol yield of 14.7 g/100 g feed. The effect of pore size of these catalysts was studied on optimum glycerol conversion and liquid product yield. Optimum conversion increased from 80 to 100 wt% and optimum liquid product increased from 59 to 83.3 g/100 g feed when the pore size of catalyst was increased from 0.54 in case of HZSM-5 to 0.74 nm in case of HY, after which the effect of pore size was minimal

Data-driven modelling of perceptual properties of 3D shapes

The recent surge in 3D content generation has led to the evolution of difficult to search, organise and re-use massive online 3D visual content libraries. We explore crowdsourcing and machine learning techniques to help alleviate these difficulties by focusing on the visual perceptual properties of 3D shapes. We study “style similarity” and “aesthetics” as two fundamental perceptual properties of 3D shapes and build data-driven models. We rely on crowdsourcing platforms to collect large number of human judgements on style matching and aesthetics of 3D shapes. The judgement data collected directly from humans is used to learn metrics of style matching and aesthetics. Our style similarity measure can be used to compute style distance between a pair of input 3D shapes. In contrast to previous work, we incorporate colour and texture in addition to geometric features to build a colour and texture aware style similarity metric. We also experiment with learning objective and personalised style metrics 3D shapes. The application prototypes we build demonstrate the use of style based search and scene composition. Further, our style distance metric is built iteratively to consume lesser amount of human style judgement data compared to previous methods. We study the problem of building a data-driven model of 3D shape aesthetics in two steps. We first focus on designing a study to crowdsource human aesthetics judgement data. We then formulate a deep learning based strategy to learn a measure of 3D shape aesthetics from collected data. The results of the study in first step helped us choose an appropriate shape representation i.e. voxels as an input to deep neural networks for learning a measure of visual aesthetics. In the same crowdsourcing study, we experiment with the use of polygonal, volumetric, and point based shape representations to create shape stimuli to collect and compare human shape aesthetics judgements. On analysis of the collected data we found that that humans can reliably distinguish more aesthetic shape in a pair even from coarser shape representations such as voxels. This observation implies that detailed shape representations are not needed to compare aesthetics in pairs. The aesthetic value of a 3D shape has traditionally been explored in terms of specific visual features (or handcrafted features) such as curvature and symmetry. For example, more symmetric and curved shapes are considered aesthetic compared to less curved and symmetric shapes. We call such properties as pre-existing notion (or rules) of aesthetics. In order to develop a measure of perceptual aesthetics of 3D shapes which is independent of any pre-existing notion or shape features, we train deep neural networks directly on human aesthetics judgement data. We demonstrate the usefulness of the learned measure by designing applications to rank a collection of shapes based on their aesthetics scores and interactively build scenes using shapes with high aesthetics scores. The overarching goal of this thesis is to demonstrate the use of machine learning and crowdsourcing approaches to build data-driven models of visual perceptual properties of 3D shapes for applications in search, organisation, scene composition, and visualisation of 3D shape data present in ever increasing online 3D shape content libraries. We believe that our exploration of perceptual properties of 3D shapes will motivate further research by looking into other important perceptual properties related to our vision system and will also fuel development of techniques to automatically enhance such properties of a given 3D shape

Tactile Mesh Saliency:a brief synopsis

This work has previously been published [LDS 16] and this extended abstract provides a synopsis for further discussion at the UK CGVC 2016 conference. We introduce the concept of tactile mesh saliency, where tactile salient points on a virtual mesh are those that a human is more likely to grasp, press, or touch if the mesh were a real-world object. We solve the problem of taking as input a 3D mesh and computing the tactile saliency of every mesh vertex. The key to solving this problem is in a new formulation that combines deep learning and learning-to-rank methods to compute a tactile saliency measure. Finally, we discuss possibilities for future work

Design of a Fast, Efficient and Controlled DNA Shearing System Based on Lateral Acoustic Waves

With the continuous research and advances in Deoxyribonucleic acid (DNA) sequencing technologies, the need for an efficient DNA shearing system has increased more than ever before. In this thesis, we propose a fast, efficient and controlled DNA shearing system based on a uniquely designed ultrasonic transducer, called Fresnel Annular Sector Actuator (FASA). Based on the simulation and experimental results, a circular array of four 90°-FASA elements is chosen as the basic unit for the proposed shearing system. DNA is successfully sheared from 300 to 1500 base-pair lengths. The shearing performance of the system is independent of the source of DNA over a large range of concentrations of the DNA. Finally, multiple FASA elements, excited by separate BF-signals, are used to increase the throughput of the proposed shearing system

Assessment of maternal serum β hCG level in pregnancy induced hypertension and normotensive patients and to correlate between the level of β hCG with the severity of pre-eclampsia and eclampsia

Background: Hypertensive disorders during pregnancy are one of the most common medical complication seen during pregnancy, affecting around 5-10% of all pregnancies. Spectrum of this disease ranges from mildly elevated blood pressure with minimal clinical significance to severe hypertension with multi organ dysfunction. Pre-eclampsia complicates about 2-8% of all pregnancies. Pre-eclampsia incidence in India is about 8-10%. Various studies have depicted that, there is a strict relationship between PIH and elevated serum β-hCG level.Methods: This one-year prospective case control study toteled 200 pregnant women attending antenatal care and admitted in eclampsia ward fulfiling the inclusion criteria were studied. Serum βhCG levels were estimated by chemiluminescent microparticle immunoassay. Statistical analysis of data was done by student’s t-test and p-value.Results: The mean β hCG level in PIH patients was found to 36851.59 mIU/ml with standard deviation of 22916.58 while the mean β hCG in normotensive patient was 15433.26 mIU/ml with standard deviation of 6861.56. (p <0.001). The mean β hCG level in gestational hypertensive patients was 25206.19 mIU/ml with a standard deviation of 8696.9. The mean β hCG level in pre-eclamptic patients was 61697.67 mIU/ml with standard deviation of 18498.57. The mean β hCG level were 84106.38 mIU/ml with standard deviation of 11295.05 in the eclamptic patient. The above values were statistically significant (p <0.001).Conclusions: We concluded that there was a striking relation between the PIH including pre-eclampsia and eclampsia with the elevated serum βhCG level. Concluding that early detection of altered serum βhCG shell aid in better management of pre-eclampsia and eclampsia cases which would play a pivotal role in improving the maternal and fetal outcome

Estimation and comparison of serum lipid profile of women with pregnancy induced hypertension and normal pregnancy

Background: Hypertensive disorders during pregnancy are the most common medical complication seen during pregnancy, affecting around 5-10% of all pregnancies. Raised blood pressure in pregnancy is the major cause of fetomaternal morbidity and mortality. The most important feature in preeclampsia is hypertension which is supposed to be due to vasospastic phenomenon in kidney, uterus, placenta and brain. Altered lipid synthesis leading to decrease in PGI2:TXA2 ratio is also supposed to be an important way of pathogenesis in pregnancy induced hypertension.Methods: This one-year prospective case control study total 200 pregnant women attending antenatal care and admitted in eclampsia ward fulfiling the inclusion criteria were studied. Serum lipid profile was estimated by semiautomatic analyzers. Statistical analysis of data was done by student’s t-test and p-value.Results: Mean total cholesterol in pregnancy induced hypertension was 278.5±52.52 mg/dl and normal pregnancy was 245.47±20.075 mg/dl. Mean triglycerides in pregnancy induced hypertension was 249.88±92.575 mg/dl and normal pregnancy was 206.89±46.345 mg/dl. Mean HDL in pregnancy induced hypertension was 43.69±4.135 mg/dl and normal pregnancy was 49.9±6.501 mg/dl. Mean LDL in pregnancy induced hypertension was 174.43±39.083 mg/ dl and normal pregnancy was 151.22±19.92 mg/dl. Mean VLDL in pregnancy induced hypertension was 46.885±15.143 mg/dl and in normal pregnancy was 40.964±9.061 mg/dl, total cholesterol, low density lipoprotein, very low density lipoprotein, triglycerides were increased in pregnancy induced hypertension when compared to normal pregnancy, which is statistically significant.Conclusions: We concluded that the Patient who developed pre-eclampsia have abnormal lipid profile. This abnormal lipid profile is responsible for endothelial dysfunction. This endothelial dysfunction may play a key role the pathophysiology of pre-eclampsia. Early detection of these parameters may help patient by preventing complications and is going to aid in better management of pre-eclampsia

Small intestinal bacterial overgrowth in chronic pancreatitis.

INTRODUCTION : The human small intestine is the site of digestion and absorption of major macro and micronutrients. Any abnormality which affects this part of bowel may lead to nutritional deficiencies as well as malabsorption syndrome. An important cause of malabsorption syndrome is Small Intestinal bacterial Overgrowth (SIBO). The bacterial count is extremely low in the stomach and small intestine. The normal count in stomach is 102-103 CFU/ml, in duodenum is 103 CFU/ml, in jejunum the count is < 104 CFU/ml and in ileum it’s upto 107-109 CFU/ml. SIBO (small intestinal bacterial overgrowth) is defined as increased bacterial counts in the proximal small bowel ( jejunum and ileum). It is also defined as the replacement of normal small bowel bacteria with the colonic bacteria. SIBO is diagnosed by jejunal aspiration (gold standard) and various breath tests ( Hydrogen breath tests, C breath tests, lactulose breath tests, methane breath tests etc. ) The clinical manifestations of SIBO may range from asymptomatic stage to malabsorption syndrome. Chronic pancreatitis has been defined as a clinical condition associated with morphological (fibrosis/calcification) of pancreas and/ or functional (exocrine and endocrine) insufficiency of the pancreas. SIBO has been reported in chronic pancreatitis and may be due to drugs (Proton pump inhibitors / analgesics), deficiency of pancreatic enzymes, impaired small bowel motility or surgery. AIMS : 1. To determine the frequency of SIBO (Small intestinal bacterial overgrowth) in chronic pancreatitis. 2. To evaluate the sensitivity and specificity of GHBT (Glucose Hydrogen Breath Test) in SIBO (Small intestinal bacterial overgrowth) by comparing it to jejunal aspirate culture (Gold standard). CONCLUSION : SIBO was not uncommon in patients with chronic pancreatitis. SIBO was diagnosed in 1/3rd of patients with chronic pancreatitis.. GHBT can be used for diagnosis of SIBO and with a sensitivity of 62% and a specificity of 92% respectively

Learning a human-perceived softness measure of virtual 3D objects

We introduce the problem of computing a human-perceived softness measure for virtual 3D objects. As the virtual objects do not exist in the real world, we do not directly consider their physical properties but instead compute the human-perceived softness of the geometric shapes. We collect crowdsourced data where humans rank their perception of the softness of vertex pairs on virtual 3D models. We then compute shape descriptors and use a learning to-rank approach to learn a softness measure mapping any vertex to a softness value. Finally, we demonstrate our framework with a variety of 3D shapes