4,880 research outputs found

    Systemic Therapy in Endometrial Cancer: Recent Advances.

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    Endometrial cancer is a chemosensitive disease. Studies have established a clear benefit of chemotherapy in advanced stages and trials are ongoing to define its role in early stages as well. As more molecular pathways are being elucidated there is increasing role for targeted agents and future looks quite promising. We did an extensive search both online and offline for all the relevant articles including chemotherapy and targeted therapy for endometrial cancer

    Streaming Big Data Analysis for Real-Time Sentiment based Targeted Advertising

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    Big Data constituting from the information shared in the various social network sites have great relevance for research to be applied in diverse fields like marketing, politics, health or disaster management. Social network sites like Facebook and Twitter are now extensively used for conducting business, marketing products and services and collecting opinions and feedbacks regarding the same. Since data gathered from these sites regarding a product/brand are up-to-date and are mostly supplied voluntarily, it tends to be more realistic, massive and reflects the general public opinion. Its analysis on real time can lead to accurate insights and responding to the results sooner is undoubtedly advantageous than responding later.  In this paper, a cloud based system for real time targeted advertising based on tweet sentiment analysis is designed and implemented using the big data processing engine Apache Spark, utilizing its streaming library. Application is meant to promote cross selling and provide better customer support

    Effect of yoga on autonomic functions in medical students: a pilot study

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    Background: Stress and anxiety being the major contributors of morbidity, leads to many chronic diseases and is known to invariably decrease the quality of life and even life span. Autonomic Nervous System (ANS), a part of the peripheral nervous system that controls the visceral system, functioning largely under the level of consciousness, capable of being influenced by the psychological factors and influences the physiological processes happening in the body.  Non-pharmacological therapies play a major role to relieve stress and anxiety of which yoga takes first place compared to pharmacological treatment. Present study adopts a systematic approach in comparing the effects of practicing yoga for one year with novices on autonomic and respiratory variables.Methods: We recruited sixty subjects from the Sri Dharmasthala Manjunatheshwara College of Naturopathy & Yogic Sciences, Ujire and their mean age group is 18.8 ± 2.3 fulfilling the selection criteria, after they gave written consent to participate. They were divided into 2 groups based on their experience of practicing yoga. Each group consisted of 30 subjects. Group 1 includes participants with no experience in yoga (Novices group) and Group 2 (Yoga group) includes individuals with one year experience of practicing yoga. Each group consists of 17 males and 13 females respectively. The study was approved by the ethical review committee. Informed written consent was obtained from all subjects. All students were subjected to Onetime Assessment for autonomic variables and respiration at base line and during deep breathing.Results: In our study we observed that there was a significant decrease in heart rate (P = 0.004***) following intervention in yoga group compared to novice group. There was a significant difference in Respiration rate (P = 0.003***) and Mean RR (P = 0.002***) which indicate increase parasympathetic activity in yoga group compared to novice group. There is also a significant difference in time domain parameter PNN50 (P = 0.030*) which is an indicator of parasympathetic activity. There was no significant difference in other time domain and frequency domain parameter.Conclusion: Practicing yoga regularly for one year can reduce the physiological arousal and develops the ability to adapt to a demanding situation.

    Randomized clinical study comparing safety and efficacy of adjuvant intrathecal clonidine versus normal saline along with bupivacaine anaesthesia in lower limb surgery patients

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    Background: Various adjuvants have been used in intrathecal anesthesia to avoid intraoperative visceral and somatic pain and prolong postoperative analgesia. Clonidine, partially selective α2-agonist, is being evaluated as a neuraxial adjuvant with intrathecal bupivacaine. The objective of the study was to evaluate and compare safety and efficacy of intrathecal clonidine as adjuvant to bupivacaine with control normal saline.Methods: American Society of Anesthesiologist grade 1 and 2 patients (60 patients) were randomly divided into two groups of 30 patients each for lower limb surgeries. Study group injected with intrathecal 3ml of 0.5% Bupivacaine heavy (15mg) + 1µg/kg of clonidine and control group injected with 3ml of 0.5% Bupivacaine heavy (15mg) + equivalent dose of normal saline. The onset and duration of sensory and motor block, duration of analgesia, and the incidence of side effects in both groups were observed and compared.Results: Time for 2 segment regressions in study group was 186.17±25.92 minutes compared to control was 103.20±19.15 minutes (p value<0.001). Total duration of analgesia in control was 226.50±35.69 minutes and in the study group was 465.67±100.37 minutes (p value<0.001). The average duration of motor block in control group was 181.17±26.12 minutes compared to study group was 217.80±41.51 minutes (p value<0.001). The small dose of intrathecal clonidine is not significantly associated with systemic side effects such as bradycardia and hypotension.Conclusions: Clonidine added to bupivacaine for intrathecal anesthesia effectively increases the duration of sensory block, duration of motor block and duration of analgesia and does not produce any significant hemodynamic changes. No significant side effects are associated with it

    Choriocarcinoma presenting following a molar pregnancy and preterm vaginal delivery: rarest of rare case

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    Choriocarcinoma is the aggressive histologic type of GTN and is characterized by vascular invasion and metastases of widespread. Choriocarcinoma metastasizes hematogenously. Suction and evacuation were done on admission. Beta-hCG was 67900 mIU/ml and 144523 mIU/ml on day 1 and day 3 respectively and histopathology showed Choriocarcinoma. This is very unusual case of reviewing sequential events. It was difficult to detect is it new pregnancy or choriocarcinoma. Investigators were biased with high beta-hCG values indicating malignancy. So there was differential diagnosis as choriocarcinoma based on history of molar pregnancy and increasing beta-hCG value and also dictum of 'non molar pregnancy following live birth is always choriocarcinoma. However histopathology report suggested choriocarcinoma and was diagnostic

    IMF isotopic properties in semi-peripheral collisions at Fermi energies

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    We study the neutron and proton dynamical behavior along the fragmentation path in semi-peripheral collisions: 58Fe+58Fe (charge asymmetric, N/Z = 1.23) and 58Ni+58Ni (charge symmetric, N/Z = 1.07), at 47 AMeV. We observe that isospin dynamics processes take place also in the charge-symmetric system 58Ni+58Ni, that may produce more asymmetric fragments. A neutron enrichment of the neck fragments is observed, resulting from the interplay between pre-equilibrium emission and the phenomenon of "isospin-migration". Both effects depend on the EoS (Equation of State) symmetry term. This point is illustrated by comparing the results obtained with two different choices of the symmetry energy density dependence. New correlation observables are suggested, to study the reaction mechanism and the isospin dynamics.Comment: 5 pages, 8 figures, Revtex4 Latex Styl

    The Mass-Size Relation from Clouds to Cores. I. A new Probe of Structure in Molecular Clouds

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    We use a new contour-based map analysis technique to measure the mass and size of molecular cloud fragments continuously over a wide range of spatial scales (0.05 < r / pc < 10), i.e., from the scale of dense cores to those of entire clouds. The present paper presents the method via a detailed exploration of the Perseus Molecular Cloud. Dust extinction and emission data are combined to yield reliable scale-dependent measurements of mass. This scale-independent analysis approach is useful for several reasons. First, it provides a more comprehensive characterization of a map (i.e., not biased towards a particular spatial scale). Such a lack of bias is extremely useful for the joint analysis of many data sets taken with different spatial resolution. This includes comparisons between different cloud complexes. Second, the multi-scale mass-size data constitutes a unique resource to derive slopes of mass-size laws (via power-law fits). Such slopes provide singular constraints on large-scale density gradients in clouds.Comment: accepted to ApJ; references updated in new versio

    Towards Causal {VQA}: {R}evealing and Reducing Spurious Correlations by Invariant and Covariant Semantic Editing

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    Despite significant success in Visual Question Answering (VQA), VQA models have been shown to be notoriously brittle to linguistic variations in the questions. Due to deficiencies in models and datasets, today's models often rely on correlations rather than predictions that are causal w.r.t. data. In this paper, we propose a novel way to analyze and measure the robustness of the state of the art models w.r.t semantic visual variations as well as propose ways to make models more robust against spurious correlations. Our method performs automated semantic image manipulations and tests for consistency in model predictions to quantify the model robustness as well as generate synthetic data to counter these problems. We perform our analysis on three diverse, state of the art VQA models and diverse question types with a particular focus on challenging counting questions. In addition, we show that models can be made significantly more robust against inconsistent predictions using our edited data. Finally, we show that results also translate to real-world error cases of state of the art models, which results in improved overall performanc
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