Photocarrier thermalization bottleneck in graphene

We present an ab-initio study of photocarrier dynamics in graphene due to electron-phonon (EP) interactions. Using the Boltzmann relaxation-time approximation with parameters determined from density functional theory (DFT) and a complementary, explicitly solvable model we show that the photocarrier thermalization time changes by orders of magnitude, when the excitation energy is reduced from 1 eV to the 100 meV range. In detail, the ultrafast thermalization at low temperatures takes place on a femtosecond timescale via optical phonon emission, but slows down to picoseconds once excitation energies become comparable with these optical phonon energy quanta. In the latter regime, thermalization times exhibit a pronounced dependence on temperature. Our DFT model includes all the inter- and intraband transitions due to EP scattering. Thanks to the high melting point of graphene we extend our studies up to 2000~K and show that such high temperatures reduce the photocarrier thermalization time through phonon absorption.Comment: 9 pages, 5 figure

Non perturbative and thermal dynamics of confined fields in dual QCD

In order to study the detailed dynamics and associated non-perturbative features of QCD, a dual version of the color gauge theory based on the topologically viable homogeneous fiber bundle approach has been analysed taking into account its magnetic symmetry structure. In the dynamically broken phase of magnetic symmetry, the associated flux tube structure on a S 2 -sphere in the magnetically condensed state of the dual QCD vacuum has been analyzed for the profiles of the color electric field using flux quantization and stability conditions. The color electric field has its intimate association with the vector mode of the magnetically condensed QCD vacuum and such field configurations have been analyzed to show that the color electric flux gets localized towards the poles for a large sphere case while it gets uniformly distributed for the small sphere case in the infrared sector of QCD. The critical flux tube densities have been computed for various couplings and are shown to be in agreement with that for lead-ion central collisions in the near infrared sector of QCD. The possible annihilation/unification of flux tubes under some typical flux tube density and temperature conditions in the magnetic symmetry broken phase of QCD has also been analyzed and shown to play an important role in the process of QGP formation. The thermal variation of the profiles of the color electic field is further investigated which indicates the survival of flux tubes even in the thermal domain that leads the possibility of the formation of some exotic states like QGP in the intermedate regime during the quark-hadron phase transition

Pharmacognostical, Phytochemical and Pharmacological profile of Colebrookea oppositifolia Smith

Colebrookea oppositifolia commonly known as ‘Bhaman’ is distributed throughout India from the Himalayas down to Deccan. The plant is used traditionally as such as dermatitis, dysentery, fever, headache, peptic ulcer, haemostatic, wounds, as anti-fertility agent, fungicide, and the roots of the plant has been most widely used for the treatment of epilepsy.. Medicinally, it has been proven to possess various pharmacological activities like treating corneal opacity or conjunctivitis, sore eyes due to its anti-inflammatory properties, cardioprotective, hepatoprotective, anti-inflammatory, antihelmintic, antifungal, antioxidant, antimicrobial, antinociceptive, cytotoxic activity, anticonvulsant, antiulcer, antimicrobial, anti-fertility, antipyretic and insecticide. Further, studies reveal the presence of various phytochemical constituents mainly flavone glycosides viz. chrysin, negletein, landenein; leaves contain 5,6,7- tri-methoxyflavone, 5,6,7,4'-tetramethoxyflavone, acteoside, and quercetin in the bark; root contains stearic, palmitic, oleic acids, triacontanol, flavone glycoside echioidin, 5,6,7-trimethoxyflavone and 4',5,6,7- tetra methoxy flavone; sugars and vitamins have also been isolated from this plant. These studies reveal that Colebrookea oppositifolia is a source of medicinally active compounds and have various pharmacological effects; hence, this drug encourage finding its new therapeutic uses. Keywords: Colebrookea oppositifolia, wound healing, anticonvulsant, Lamiacea

Efficacy and safety of apremilast versus dapsone versus colchicine in recurrent aphthous stomatitis: a three arm double blinded comparative study

Background: Recurrent aphthous stomatitis (RAS) is often considered as an incurable ailment. Therefore, an effective management option is required for controlling the symptoms and severity of RAS. We aimed to conduct a study to compare the effectiveness and safety profile of apremilast, dapsone and colchicine in management of RAS. Methods: This three-arm double blinded comparative study included 60 cases of recurrent aphthous stomatitis (RAS). Twenty patients each were randomly allocated in three groups: group A (apremilast), group B (dapsone) and group C (colchicine). Results: At the end of 6 weeks, the complete response was seen in 6 (30%) patients in group A as compared to 2 (10%) and 4 (20%) patients in group B and C (p >0.05). At the end of 12 weeks, response rate became statistically significant (p=0.003) with complete response in 14 (70%) of patients. Median time to recurrence, defined as oral ulcer after loss of complete response, was significantly increased to 4.3 weeks in group A as compared to group B and C. The most commonly encountered side effects were gastrointestinal in all three groups. None of the adverse effects resulted in discontinuation of treatment, hospitalization or death in any patient. Conclusions: Although, traditional therapies like dapsone and colchicine have been commonly used in clinical practice, apremilast yielded a rapid and maintained improvement of RAS

Communication in Cloud-of-Clouds Environment for Brokers

In advancement of cloud brokers for communication between different cloud providers, and the cloud-of-clouds territory denoting the integration of different clouds- including clouds offering different abstractions and services (e.g., Infrastructure as a Service vs. Platform as a Service) present new challenges to software developers. Actually, while support for developing speci?c types of applications to run in different individual cloud infrastructures is slowly becoming acceptable, there is little support for programming applications that run across several clouds or types of clouds. Combination of application, datacenters, and programming techniques in the multi-cloud environment poses numerous difficulties to framework engineers. Diverse cloud suppliers offer distinctive communication abstractions, and applications shows distinctive correspondence designs. By abstracting from hardware addresses and lower-level communication. DOI: 10.17762/ijritcc2321-8169.15015

Abdominal hysterectomy: analysis of clinico-histopathological correlation in Western Rajasthan, India

Background: Hysterectomy is the most common gynecological surgery done in the females worldwide as it provides definitive cure to a wide range of gynecological diseases, both benign and malignant. The indications to perform this major surgery should always be justified and the pathology should be proved histopathologically. Histopathological analysis and review is mandatory to evaluate the appropriateness of the hysterectomy.Methods: A retrospective, longitudinal study was conducted in the Department of Obstetrics and Gynecology, UMAID Hospital, Dr. S.N. M.C. Jodhpur (Raj.) during October 2014 to March 2015.Total 105 cases were studied during this period. The study included all women undergoing planned abdominal hysterectomy. Data was recorded on proformas, including demographic characteristics and clinical features. Hysterectomy specimens were saved in 10% formalin and sent to the Department of Pathology. Histopathology reports were analyzed and compared with the indications of surgery to draw various informative conclusions.Results: Of 105 cases, 55(52.38%) were in the age group of 41 – 50, which comprised the commonest age group undergoing the surgery. Maximum women (95%) those underwent hysterectomy were multiparous. Most common preoperatively clinical diagnosis was leiomyoma uterus which was diagnosed clinically and sonographically in 51(48.57%) cases. On Histopathological examination, the commonest pathology, similar to clinical impression, was found to be Leiomyoma at 50.48% (n = 53). Adenomyosis (21.90%) was detected as Second most common pathology. Histopathological confirmation of pre-operative diagnosis was 89% for malignancy, 96% for fibroids, 100% for adenomyosis, 100% for pelvic inflammatory disease.Conclusions: There was a high correlation when the clinical diagnosis was a fibroid, adenomyosis and ovarian mass. Every hysterectomy specimen should be subjected to histopathological examination because it is mandatory for conforming diagnosis and ensuring optimal management, in particular of malignant disease

Classification of four ovine breeds of southern peninsular zone of India: Morphometric study using classical discriminant function analysis

Six morphometric traits (height at withers, body length, chest girth, ear length, tail length and body weight) were analyzed to characterize from a breed point of view 1981 sheep from four ovine breeds (Bellary, Kenguri, Hassan and Mandya) of southern peninsular zone of India. Discriminant Function Analysis was used to distinguish between four breeds by morphometric traits. The population variability showed Kenguri ewes were the largest and heaviest followed by Bellary, Hassan and Mandya whereas Kenguri rams were followed by Bellary, Mandya and Hassan. Overall sexual dimorphism (m/f) was 1.13, with Kenguri males being 47% heavier than females. The coefficient of variation of all traits in four breeds ranged from 4.06% to 30.28%. The flocks and age effects showed a high heterogeneity among females of different flocks. Height at withers was most discriminating trait in separating the four sheep breeds. The Mahalanobis distance of the morphological traits between Kenguri and Mandya sheep was most while the least differentiation was observed between Kenguri and Bellary sheep. Nearest neighbour discriminant analysis showed that most Kenguri sheep were classified into their source population followed by Mandya. However, varied percentages of misclassification between different breeds were observed showing the level of genetic exchange that has taken place between the breeds overtime. UPGMA based dendrogram showed formation of two separate groups; Mandya and Hassan clustered together while Bellary and Kenguri formed other group

A Visually Attentive Splice Localization Network with Multi-Domain Feature Extractor and Multi-Receptive Field Upsampler

Image splice manipulation presents a severe challenge in today's society. With easy access to image manipulation tools, it is easier than ever to modify images that can mislead individuals, organizations or society. In this work, a novel, "Visually Attentive Splice Localization Network with Multi-Domain Feature Extractor and Multi-Receptive Field Upsampler" has been proposed. It contains a unique "visually attentive multi-domain feature extractor" (VA-MDFE) that extracts attentional features from the RGB, edge and depth domains. Next, a "visually attentive downsampler" (VA-DS) is responsible for fusing and downsampling the multi-domain features. Finally, a novel "visually attentive multi-receptive field upsampler" (VA-MRFU) module employs multiple receptive field-based convolutions to upsample attentional features by focussing on different information scales. Experimental results conducted on the public benchmark dataset CASIA v2.0 prove the potency of the proposed model. It comfortably beats the existing state-of-the-arts by achieving an IoU score of 0.851, pixel F1 score of 0.9195 and pixel AUC score of 0.8989

A systematic review on Drug Re-profiling/Re-Purposing

Hardcore capability of drug repurposing has allowed rising population of diversified diseased patients to approach various medications with known safety profiles. In an ongoing scenario considering current pharmaceutical market, we have numerous drugs that are approved and repurposed by the U.S. Food and Drug Administration. Developing and bringing a novel drug molecule from the laboratory to a market requires a lot of investment in terms of money, efforts, and time. On the other hand, repurposing a drug holds the capability of bringing out best cures with harmless, ease availability and inexpensive quality. Sildenafil, Chloroquine, Metformin are some examples of repurposed drug used in multiple disease models. Despite numerous challenges, drug repurposing stood to be a core component to any comprehensive drug re-discovering strategies which has been planned to bring benefit to the patients suffering from a wide variety of dreadful ailments. In this review, we have discussed the various repurposed drugs in numerous types of cancer, deadly novel coronavirus (SARS-CoV-2) and some orphan diseases. This paper holds various examples of drugs which are still under clinical trial and have high chances of being approved as repurposed drugs benefitting humankind

A Deep Multi-Level Attentive network for Multimodal Sentiment Analysis

Multimodal sentiment analysis has attracted increasing attention with broad application prospects. The existing methods focuses on single modality, which fails to capture the social media content for multiple modalities. Moreover, in multi-modal learning, most of the works have focused on simply combining the two modalities, without exploring the complicated correlations between them. This resulted in dissatisfying performance for multimodal sentiment classification. Motivated by the status quo, we propose a Deep Multi-Level Attentive network, which exploits the correlation between image and text modalities to improve multimodal learning. Specifically, we generate the bi-attentive visual map along the spatial and channel dimensions to magnify CNNs representation power. Then we model the correlation between the image regions and semantics of the word by extracting the textual features related to the bi-attentive visual features by applying semantic attention. Finally, self-attention is employed to automatically fetch the sentiment-rich multimodal features for the classification. We conduct extensive evaluations on four real-world datasets, namely, MVSA-Single, MVSA-Multiple, Flickr, and Getty Images, which verifies the superiority of our method.Comment: 11 pages, 7 figure