Role of Associated Complex in Determining the Magnitude of Excess Volumes of Binary Liquid Mixtures: Part I - Aniline & Methyl-substituted Anilines with Cyclohexane as Inert Diluent

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Specific identification, biology and symptoms of whitefly species infesting sunflower in South India

Whitefly species related to sunflower was identified as Bemisia tabaci (Gennadius). Further the identified whitefly species was confirmed to be indigenous B. tabaci on molecular basis by using B-biotype specific SCARs and biological silver leaf assay on sensitive pumpkin (cv Big variety). None of the whitefly samples could positive for the presence of B biotype. The results of the study on the pest life cycle under the laboratory conditions showed that, B. tabaci passed through four nymphal instars before the adult stage. The mean duration values of these stages were 5.6, 4.2, 4.4 and 5.6 days respectively. The total duration of the life cycle of B. tabaci ranged from 23- 42 days at the temperature of 29±2°C with a mean of 34.5. The damage to sunflower crop caused by the whitefly species is discussed with a special emphasis on its ability to transmit leaf curl viral disease

Automated skin lesion segmentation using multi-scale feature extraction scheme and dual-attention mechanism

Segmenting skin lesions from dermoscopic images is essential for diagnosing skin cancer. But the automatic segmentation of these lesions is complicated due to the poor contrast between the background and the lesion, image artifacts, and unclear lesion boundaries. In this work, we present a deep learning model for the segmentation of skin lesions from dermoscopic images. To deal with the challenges of skin lesion characteristics, we designed a multi-scale feature extraction module for extracting the discriminative features. Further in this work, two attention mechanisms are developed to refine the post-upsampled features and the features extracted by the encoder. This model is evaluated using the ISIC2018 and ISBI2017 datasets. The proposed model outperformed all the existing works and the top-ranked models in two competitions

Unleashing the Power of Dynamic Mode Decomposition and Deep Learning for Rainfall Prediction in North-East India

Accurate rainfall forecasting is crucial for effective disaster preparedness and mitigation in the North-East region of India, which is prone to extreme weather events such as floods and landslides. In this study, we investigated the use of two data-driven methods, Dynamic Mode Decomposition (DMD) and Long Short-Term Memory (LSTM), for rainfall forecasting using daily rainfall data collected from India Meteorological Department in northeast region over a period of 118 years. We conducted a comparative analysis of these methods to determine their relative effectiveness in predicting rainfall patterns. Using historical rainfall data from multiple weather stations, we trained and validated our models to forecast future rainfall patterns. Our results indicate that both DMD and LSTM are effective in forecasting rainfall, with LSTM outperforming DMD in terms of accuracy, revealing that LSTM has the ability to capture complex nonlinear relationships in the data, making it a powerful tool for rainfall forecasting. Our findings suggest that data-driven methods such as DMD and deep learning approaches like LSTM can significantly improve rainfall forecasting accuracy in the North-East region of India, helping to mitigate the impact of extreme weather events and enhance the region's resilience to climate change.Comment: Paper is under review at ICMC 202

Delivery of AAV‐based gene therapy through haemophilia centres—A need for re‐evaluation of infrastructure and comprehensive care: A Joint publication of EAHAD and EHC

Introduction Adeno-associated virus (AAV)-based gene therapy for haemophilia presents a challenge to the existing structure of haemophilia centres and requires a rethink of current collaboration and information exchange with the aim of ensuring a system that is fit-for-purpose for advanced therapies to maximise benefits and minimise risks. In Europe, a certification process based on the number of patients and facilities is offered to the haemophilia centres by European Haemophilia Network (EUHANET). Aim and methods This joint European Association for Haemophilia and Allied Disorders (EAHAD) and European Haemophilia Consortium (EHC) publication describes criteria for centres participating in gene therapy care that require a reassessment of the infrastructure of comprehensive care and provides an outlook on how these criteria can be implemented in the future work of haemophilia centres. Results The core definition of a haemophilia treatment centre remains, but additional roles could be implemented. A modifiable ‘hub-and-spoke’ model addresses all aspects associated with gene therapy, including preparation and administration of the gene therapy product, determination of coagulation and immunological parameters, joint score and function, and liver health. This will also include the strategy on how to follow-up patients for a long-term safety and efficacy surveillance. Conclusion We propose a modifiable, networked ‘hub and spoke’ model with a long term safety and efficacy surveillance system. This approach will be progressively developed with the goal of making haemophilia centres better qualified to deliver gene therapy and to make gene therapy accessible to all persons with haemophilia, irrespective of their country or centre of origin

Hypercoagulability progresses to hypocoagulability during evolution of acetaminophen-induced acute liver injury in pigs

Increases in prothrombin time (PT) and international normalised ratio (INR) characterise acute liver injury (ALI) and failure (ALF), yet a wide heterogeneity in clotting abnormalities exists. This study defines evolution of coagulopathy in 10 pigs with acetaminophen (APAP)-induced ALI compared to 3 Controls. APAP administration began at 0 h and continued to ‘ALF’, defined as INR >3. In APAP pigs, INR was 1.05 ± 0.02 at 0 h, 2.15 ± 0.43 at 16 h and > 3 at 18 ± 1 h. At 12 h thromboelastography (TEG) demonstrated increased clot formation rate, associated with portal vein platelet aggregates and reductions in protein C, protein S, antithrombin and A Disintegrin and Metalloprotease with Thrombospondin type 1 repeats–13 (ADAMTS-13) to 60%, 24%, 47% and 32% normal respectively. At 18 ± 1 h, INR > 3 was associated with: hypocoagulable TEG profile with heparin-like effect; falls in thrombin generation, Factor V and Factor VIII to 52%, 19% and 17% normal respectively; further decline in anticoagulants; thrombocytopenia; neutrophilia and endotoxemia. Multivariate analysis, found that ADAMTS-13 was an independent predictor of a hypercoagulable TEG profile and platelet count, endotoxin, Protein C and fibrinogen were independent predictors of a hypocoagulable TEG profile. INR remained normal in Controls. Dynamic changes in coagulation occur with progression of ALI: a pro-thrombotic state progresses to hypocoagulability

Advanced Technologies for Oral Controlled Release: Cyclodextrins for oral controlled release

Cyclodextrins (CDs) are used in oral pharmaceutical formulations, by means of inclusion complexes formation, with the following advantages for the drugs: (1) solubility, dissolution rate, stability and bioavailability enhancement; (2) to modify the drug release site and/or time profile; and (3) to reduce or prevent gastrointestinal side effects and unpleasant smell or taste, to prevent drug-drug or drug-additive interactions, or even to convert oil and liquid drugs into microcrystalline or amorphous powders. A more recent trend focuses on the use of CDs as nanocarriers, a strategy that aims to design versatile delivery systems that can encapsulate drugs with better physicochemical properties for oral delivery. Thus, the aim of this work was to review the applications of the CDs and their hydrophilic derivatives on the solubility enhancement of poorly water soluble drugs in order to increase their dissolution rate and get immediate release, as well as their ability to control (to prolong or to delay) the release of drugs from solid dosage forms, either as complexes with the hydrophilic (e.g. as osmotic pumps) and/ or hydrophobic CDs. New controlled delivery systems based on nanotechonology carriers (nanoparticles and conjugates) have also been reviewed

Co-evolution, opportunity seeking and institutional change: Entrepreneurship and the Indian telecommunications industry 1923-2009

"This is an Author's Original Manuscript of an article submitted for consideration in Business History [copyright Taylor & Francis]; Business History is available online at http://www.tandfonline.com/." 10.1080/00076791.2012.687538In this paper, we demonstrate the importance for entrepreneurship of historical contexts and processes, and the co-evolution of institutions, practices, discourses and cultural norms. Drawing on discourse and institutional theories, we develop a model of the entrepreneurial field, and apply this in analysing the rise to global prominence of the Indian telecommunications industry. We draw on entrepreneurial life histories to show how various discourses and discursive processes ultimately worked to generate change and the creation of new business opportunities. We propose that entrepreneurship involves more than individual acts of business creation, but also implies collective endeavours to shape the future direction of the entrepreneurial field

SlimPLS: A Method for Feature Selection in Gene Expression-Based Disease Classification

A major challenge in biomedical studies in recent years has been the classification of gene expression profiles into categories, such as cases and controls. This is done by first training a classifier by using a labeled training set containing labeled samples from the two populations, and then using that classifier to predict the labels of new samples. Such predictions have recently been shown to improve the diagnosis and treatment selection practices for several diseases. This procedure is complicated, however, by the high dimensionality if the data. While microarrays can measure the levels of thousands of genes per sample, case-control microarray studies usually involve no more than several dozen samples. Standard classifiers do not work well in these situations where the number of features (gene expression levels measured in these microarrays) far exceeds the number of samples. Selecting only the features that are most relevant for discriminating between the two categories can help construct better classifiers, in terms of both accuracy and efficiency. In this work we developed a novel method for multivariate feature selection based on the Partial Least Squares algorithm. We compared the method's variants with common feature selection techniques across a large number of real case-control datasets, using several classifiers. We demonstrate the advantages of the method and the preferable combinations of classifier and feature selection technique