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Vladimir Lenin and the Russian Revolution
\"Describes the life of Vladimir Lenin and his philosophies which led to the Russian revolution in the 20th century\"-- Provided by publisher.
Book
Conspirator : Lenin in exile
Examines Vladimir Lenin's life of exile for seventeen years before the Russian Revolution in 1917, covering his reliance on a network of supporters and friends who helped spread illegal literature while Lenin worked toward the establishment of a Soviet social democracy, and discusses the impact of his surreptitious existence on the women in his life, including his wife, his mother, and his mistress.
Book
A Review on Assurance and Compliance of Manufacturing of Tablets Following ICH Q10
Quality assurance in the pharmaceutical industry aims to ensure that the product that reaches the patient is safe, effective, and of better quality. Product quality is checked by various activities of quality systems such as managerial and technical, including evaluation of pharmaceutical products documentation, performing or reviewing quality-control laboratory tests, and monitoring product performance. Managerial activities include selecting reliable suppliers, preparing contract terms, monitoring supplier performance, and performing inspection trials during the distribution network. Compliance Services assures that the labs are operating within global regulatory requirements. By assuring the provider agrees on the protocols under a single Universal Operational Qualification framework, it will have a comprehensive, automated approach to investigation, documentation, and agreement, streamlining processes across all leading pharmaceutical industry models. In pharmaceutical industries, tablet dosage forms should follow the Q10 guidelines of ICH. The models and statistical approaches should qualify as per the guidelines. Observation should be done throughout the life cycle of the tablet dosage form.
Journal Article
Reconstructing Lenin : an intellectual biography
\"Vladimir Ilyich Lenin is among the most enigmatic and influential figures of the twentieth century. While his life and work are crucial to any understanding of modern history and the socialist movement, generations of writers on the left and the right have seen fit to embalm him endlessly with superficial analysis or dreary dogma. Now, after the fall of the Soviet Union and 'actually-existing' socialism, it is possible to consider Lenin afresh, with sober senses trained on his historical context and how it shaped his theoretical and political contributions. Reconstructing Lenin, four decades in the making and now available in English for the first time, is an attempt to do just that. Tamâas Krausz, an esteemed Hungarian scholar writing in the tradition of Gyèorgy Lukâacs, Ferenc Tîokei, and Istvâan Mâeszâaros, makes a major contribution to a growing field of contemporary Lenin studies. This rich and penetrating account reveals Lenin busy at the work of revolution, his thought shaped by immediate political events but never straying far from a coherent theoretical perspective. Krausz balances detailed descriptions of Lenin's time and place with lucid explications of his intellectual development, covering a range of topics like war and revolution, dictatorship and democracy, socialism and utopianism. Reconstructing Lenin will change the way you look at a man and a movement; it will also introduce the English-speaking world to a profound radical scholar\"--Provided by publisher.
Book
A comprehensive comparison of machine learning models for ICH prognostication: Retrospective review of 1501 intra-cerebral hemorrhage patients from the Qatar stroke database
Multiple prognostic scores have been developed to predict morbidity and mortality in patients with spontaneous intracerebral hemorrhage(sICH). Since the advent of machine learning(ML), different ML models have also been developed for sICH prognostication. There is however a need to verify the validity of these ML models in diverse patient populations. We aim to create machine learning models for prognostication purposes in the Qatari population. By incorporating inpatient variables into model development, we aim to leverage more information. 1501 consecutive patients with acute sICH admitted to Hamad General Hospital(HGH) between 2013 and 2023 were included. We trained, evaluated, and compared several ML models to predict 90-day mortality and functional outcomes. For our dataset, we randomly selected 80% patients for model training and 20% for validation and used k-fold cross validation to train our models. The ML workflow included imbalanced class correction and dimensionality reduction in order to evaluate the effect of each. Evaluation metrics such as sensitivity, specificity, F-1 score were calculated for each prognostic model. Mean age was 50.8(SD 13.1) years and 1257(83.7%) were male. Median ICH volume was 7.5 ml(IQR 12.6). 222(14.8%) died while 897(59.7%) achieved good functional outcome at 90 days. For 90-day mortality, random forest(RF) achieved highest AUC(0.906) whereas for 90-day functional outcomes, logistic regression(LR) achieved highest AUC(0.888). Ensembling provided similar results to the best performing models, namely RF and LR, obtaining an AUC of 0.904 for mortality and 0.883 for functional outcomes. Random Forest achieved the highest AUC for 90-day mortality, and LR achieved the highest AUC for 90-day functional outcomes. Comparing ML models, there is minimal difference between their performance. By creating an ensemble of our best performing individual models we maintained maximum accuracy and decreased variance of functional outcome and mortality prediction when compared with individual models.
Key points
• 1st Key Point: We are comparing different machine learning models for ICH prognostication. Random Forest was the most accurate model for mortality, and logistic regression was the most accurate model for functional outcomes.
• 2nd Key Point: Ensembling models maintained accuracy and decreased variance.
Journal Article
QT Assessment in Early Drug Development: The Long and the Short of It
The QT interval occupies a pivotal role in drug development as a surface biomarker of ventricular repolarization. The electrophysiologic substrate for QT prolongation coupled with reports of non-cardiac drugs producing lethal arrhythmias captured worldwide attention from government regulators eventuating in a series of guidance documents that require virtually all new chemical compounds to undergo rigorous preclinical and clinical testing to profile their QT liability. While prolongation or shortening of the QT interval may herald the appearance of serious cardiac arrhythmias, the positive predictive value of an abnormal QT measurement for these arrhythmias is modest, especially in the absence of confounding clinical features or a congenital predisposition that increases the risk of syncope and sudden death. Consequently, there has been a paradigm shift to assess a compound’s cardiac risk of arrhythmias centered on a mechanistic approach to arrhythmogenesis rather than focusing solely on the QT interval. This entails both robust preclinical and clinical assays along with the emergence of concentration QT modeling as a primary analysis tool to determine whether delayed ventricular repolarization is present. The purpose of this review is to provide a comprehensive understanding of the QT interval and highlight its central role in early drug development.
Journal Article