Discriminatively Trained Latent Ordinal Model for Video Classification

We study the problem of video classification for facial analysis and human action recognition. We propose a novel weakly supervised learning method that models the video as a sequence of automatically mined, discriminative sub-events (eg. onset and offset phase for "smile", running and jumping for "highjump"). The proposed model is inspired by the recent works on Multiple Instance Learning and latent SVM/HCRF -- it extends such frameworks to model the ordinal aspect in the videos, approximately. We obtain consistent improvements over relevant competitive baselines on four challenging and publicly available video based facial analysis datasets for prediction of expression, clinical pain and intent in dyadic conversations and on three challenging human action datasets. We also validate the method with qualitative results and show that they largely support the intuitions behind the method.Comment: Paper accepted in IEEE TPAMI. arXiv admin note: substantial text overlap with arXiv:1604.0150

LOMo: Latent Ordinal Model for Facial Analysis in Videos

We study the problem of facial analysis in videos. We propose a novel weakly supervised learning method that models the video event (expression, pain etc.) as a sequence of automatically mined, discriminative sub-events (eg. onset and offset phase for smile, brow lower and cheek raise for pain). The proposed model is inspired by the recent works on Multiple Instance Learning and latent SVM/HCRF- it extends such frameworks to model the ordinal or temporal aspect in the videos, approximately. We obtain consistent improvements over relevant competitive baselines on four challenging and publicly available video based facial analysis datasets for prediction of expression, clinical pain and intent in dyadic conversations. In combination with complimentary features, we report state-of-the-art results on these datasets.Comment: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR

11 - The impact of obesity on ingestion-induced hippocampal \u3ci\u3eArc\u3c/i\u3e expression in male rats

Obesity is a chronic disease that affects more than 33% of American adults and roughly 13% of adults worldwide. Obesity has many peripheral impacts, such as cardiovascular diseases, type II diabetes, and arthritis. Obesity also influences the functioning of the brain. In particular, obesity and overeating impair the function of the hippocampus, which is vital for memory. In humans, impairing the memory of a meal increases subsequent intake. In rats, our lab has shown that sucrose ingestion activates molecules necessary for hippocampal memory formation, such as activity regulated cytoskeleton associated protein (Arc). We hypothesize that obesity disrupts hippocampal-dependent memory formation of a meal, which could further contribute to obesity. We predict that high-fat diet-induced obesity impairs sucrose ingestion-induced Arc mRNA expression. To test this, rats were placed on a high-fat diet or a control diet for 8 weeks. On the experimental day, rats were given access to sucrose meal for 10 minutes; euthanized, and the hippocampus, fat pads, and liver were extracted. The hippocampus will be tested for the concentration of Arc mRNA by quantitative real-time polymerase chain reaction (qRT-PCR). It is predicted that the number of calories consumed, body, liver and fat pad mass, and the amount of sucrose consumed by the experimental rats will be greater than that of the control rats. More importantly, sucrose-induced Arc mRNA expression is expected to be reduced in the experimental rats compared to the control rats. This would be consistent with the hypothesis that obesity disrupts the hippocampal formation of a memory of a meal

Study Of Gaussian & Impulsive Noise Suppression Schemes In Images

Noise is introduced into images usually while transferring and acquiring them.The main type of noise added while image acquisition is called Gaussian noise while Impulsive noise is generally introduced while transmitting image data over an unsecure communication channel , while it can also be added by acquiring. Gaussian noise is a set of values taken from a zero mean Gaussian distribution which are added to each pixel value. Impulsive noise involves changing a part of the pixel values with random ones. Various techniques are employed for the removal of these types of noise based on the properties of their respective noise models. Impulse Noise removal algorithms popularly use ordered statistics based ¯lters. The ¯rst one is an adaptive ¯lter using center-weighted median. In this method, the di®erence of the center weighted mean of a neighborhood with the central pixel under consideration is compared with a set of thresholds. Another method which takes into account the presence of the noise free pixels has been implemented.It convolutes the median of each neighborhood with a set of convolution kernels which are oriented according to all possible con¯gurations of edges that contain the central pixel,if it lies on an edge. A third method which deals with the detection of noisy pixels on the binary slices of an image is implemented. It is based on threshold Boolean ¯ltering. The ¯lter inverts the value of the central pixel if the number of pixels with values opposite to it is more than the threshold. The fourth method has an e±cient double derivative detector, which gives a de- cision based on the value of the double derivative. The substitution is done with the average gray scale value of the neighborhood. Gaussian Noise removal algorithms ideally should smooth the distinct parts of the image without blurring the edges.A universal noise removing scheme is implemented which weighs each pixel with respect to its neighborhood and deals with Gaussian and impulse noise pixels di®erently based on parameter values for spatial, radiometric and impulsive weight of the central pixel. The aforementioned techniques are implemented and their results are compared subjectively as well as objectively

SYNTHESIS, CHARACTERIZATION AND ANTIMICROBIAL STUDY OF SOME BENZENESULFONAMIDE BASED BIPYRAZOLES

Objectives: To synthesize, characterize and evaluate antimicrobial properties of some benzenesulfonamide based bipyrazole. Methods: The benzenesulfonamide based bipyrazole 1a-d & 2a-f have been synthesized by the reaction between 1-[1-aryl / (benzothiazol-2-yl)-5-hydroxy-3-methylpyrazol-4-yl]butane-1,3-diones 5 and 2-hydrazinobenzothiazoles or Aryl hydrazines 3. The structures of these compounds have been characterized from the rigorous analysis of their IR, 1H-NMR, HRMS and elemental analysis. These compounds were screened for their anti-microbial activity. Results: The results revealed that compounds 1a, 2b and 2f exhibited good antibacterial activity and 1b, 1c, 2a, and 2d showed moderate antibacterial activity as compared with standard drug Ofloxacin. Conclusion: This study provides the simple method for the synthesis of new benzenzenesulfonamide based bipyrazoles which plays important role in numerous bioactive compounds

SYNTHESIS, CHARACTERIZATION AND ANTIMICROBIAL STUDY OF SOME NOVEL FLUORINE BASED 2-AMINOTHIAZOLES

Objectives: To synthesize, characterize and evaluate antimicrobial properties of some novel fluorine based 2-aminothiazoles. Methods: The syntheses of some novel fluorine based 2-aminothiazoles have been described by using hypervalent iodine [I(III)] mediated approach. It was observed that this is the more general and promising method for the synthesis of any thiazole, but, when other methods work, the hypervalent iodine [I(III)] mediated approach generally gives better yields. The structures of these compounds have been characterized from the rigorous analysis of their IR, 1H NMR, MS and elemental analysis. These compounds were screened for their anti-microbial activity. Results: The results revealed that compounds 7d, 7f, 10a, 10b, 10c, 14e and 14f showed moderate to good antibacterial activity as compared with the standard drug Chloramphenicol. Conclusion: The two thiazole synthetic methods described herein use readily available reagents and both of them are easily feasible, the hypervalent iodine mediated approach for the synthesis of title compounds is more significant because, in spite of the better yields, it avoids the use of highly toxic and lachrymatory α-halogenoketone, thereby being more eco-friendlier

Significance of diagnostic and monitoring criterion of HbA1c as compared with fasting and 2-hour plasma glucose concentration in GCS general hospital, Ahmedabad: a retrospective study

Background: Diabetes is a chronic disorder that has reached epidemic levels. Its complications are potentially life-threatening but can be slowed by early diagnosis and treatment. Complications develop earlier in patients having more fluctuating levels of blood glucose than those having maintained levels. Early diagnosis and treatment confer more benefits than aggressive control.Methods: As it was a retrospective study; the data was collected from available records of patients in whom all the three tests have been executed and analysed using SPSS version 26.Results: Diabetics were 199 (53.9%) based on FPG (fasting plasma glucose); 169 (45.8%) based on 2hPG (2-hour plasma glucose) and 230 (62.3%) based on HbA1c. When diagnosed with FPG, the sensitivity and specificity of HbA1c was 89.44% and 69.41% respectively, whereas with 2hPG it was 92.89% and 63.5%. When HbA1c was compared with FPG and 2hPG, the values are affected with history of diastolic hypertension and family history of diabetics. The values correlated with that of FPG as well as 2hPG and showed linear relationship. The regression equation HbA1c (%)=3.737+0.027×FPG (mg/dl) explains 50.4% of variation and with less error when compared to 2hPG. Hence, the values of FPG can be used to predict the approximate values of HbA1c through regression.Conclusions: Study revealed that HbA1c has a greater potential as a diagnostic test due to its high sensitivity. The levels are affected by family history and diastolic hypertension. Our study suggests that diagnosing criteria of diabetes should be HbA1c ≥7.1% instead of the current criteria of HbA1c ≥6.5% by the relationship of HbA1c with FPG

RP-HPLC METHOD DEVELOPMENT AND VALIDATION FOR THE COMBINATION OF IMIQUIMOD AND SALICYLIC ACID

Objective: The present study was undertaken to develop and validate an RP-HPLC method for the combination of imiquimod and salicylic acid Methods: The method was carried out on Nucleodur C18 (250 mm × 4.6 mm I.D., 5 ????m) using low-pressure gradient elution mode. The mobile phase was used as 30M potassium dihydrogen phosphate and acetonitrile (45:55) pH 6.5 adjusted using ortho-phosphoric acid. The concentration of solvents was 1-20 µg/ml and the volume of injection was 20 mcl with the flow rate of 1.0 ml/min. The absorption maxima of salicylic acid and imiquimod were found 234 nm and 226 nm, respectively. Results: The method was validated and showed the linearity greater than 0.99% and with precision (RSD%<1). The limit of detection (LOD) and limit of quantification (LOQ) of salicylic acid was found to be 0.09756 µg/ml and 0.2956 µg/ml, respectively, and imiquimod was found to be 0.044031 µg/ml and 0.13334 µg/ml, respectively. Conclusion: The method developed in the present study was found to be sensitive, specific, and can be applied for the simultaneous estimation of imiquimod and salicylic acid