Stanisław Kuczera (5 May 1928–28 July 2020)

Early China ◽

10.1017/eac.2021.2 ◽

2021 ◽

pp. 1-12

Author(s):

Sergey Dmitriev

Keyword(s):

Vast Number ◽

Chinese Studies

Abstract Stanisław Kuczera (May 5, 1928–July 28, 2020) was an eminent figure in Polish, Soviet, and Russian Chinese Studies, holding the position of one of leading experts in a vast number of fields (most prominently, archeology, epigraphy, and the translation of classics) over a period decades, until his last days. His life, filled with a thirst for knowledge and harsh vicissitudes, is a story that is worthy of being told and remembered.

Download Full-text

Preinfarction Angina and Improved Reperfusion of the Infarct-related Artery

Thrombosis and Haemostasis ◽

10.1055/s-0037-1615557 ◽

1999 ◽

Vol 82 (S 01) ◽

pp. 68-72 ◽

Cited By ~ 2

Author(s):

Alessandro Sciahbasi ◽

Eugenia De Marco ◽

Attilio Maseri ◽

Felicita Andreotti

Keyword(s):

Myocardial Infarction ◽

Acute Myocardial Infarction ◽

Infarct Size ◽

Ischemic Preconditioning ◽

Early Reperfusion ◽

Vast Number ◽

Beneficial Effects ◽

Infarct Related Artery ◽

Cardioprotective Effects ◽

Collateral Vessels

SummaryPreinfarction angina and early reperfusion of the infarct-related artery are major determinants of reduced infarct-size in patients with acute myocardial infarction. The beneficial effects of preinfarction angina on infarct size have been attributed to the development of collateral vessels and/or to post-ischemic myocardial protection. However, recently, a relation has been found between prodromal angina, faster coronary recanalization, and smaller infarcts in patients treated with rt-PA: those with preinfarction angina showed earlier reperfusion (p = 0.006) and a 50% reduction of CKMB-estimated infarct-size (p = 0.009) compared to patients without preinfarction angina. This intriguing observation is consistent with a subsequent observation of higher coronary recanalization rates following thrombolysis in patients with prodromal preinfarction angina compared to patients without antecedent angina. Recent findings in dogs show an enhanced spontaneous lysis of plateletrich coronary thrombi with ischemic preconditioning, which is prevented by adenosine blockade, suggesting an antithrom-botic effect of ischemic metabolites. Understanding the mechanisms responsible for earlier and enhanced coronary recanalization in patients with preinfarction angina may open the way to new reperfusion strategies.A vast number of studies, globally involving ≈17,000 patients with acute myocardial infarction, have unequivocally shown that an infarction preceded by angina evolves into a smaller area of necrosis compared to an infarct not preceded by angina (Table 1) (1). So far, preinfarction angina has been thought to have cardioprotective effects mainly through two mechanisms: collateral perfusion of the infarctzone (2-4), and ischemic preconditioning of the myocardium (5-7). Here we discuss a further mechanism of protection represented by improved reperfusion of the infarct-related artery.

Download Full-text

Stock Market Prediction using Data Mining Techniques

International Journal of Scientific Research in Computer Science Engineering and Information Technology ◽

10.32628/cseit206290 ◽

2020 ◽

pp. 310-313

Author(s):

Karunesh Makker ◽

Prince Patel ◽

Hrishikesh Roy ◽

Sonali Borse

Keyword(s):

Neural Network ◽

Stock Market ◽

Prediction Model ◽

Efficient Market Hypothesis ◽

Deterministic System ◽

Vast Number ◽

Factors Influencing ◽

Number Of Factors ◽

Using Data ◽

Robust Prediction

Stock market is a very volatile in-deterministic system with vast number of factors influencing the direction of trend on varying scales and multiple layers. Efficient Market Hypothesis (EMH) states that the market is unbeatable. This makes predicting the uptrend or downtrend a very challenging task. This research aims to combine multiple existing techniques into a much more robust prediction model which can handle various scenarios in which investment can be beneficial. Existing techniques like sentiment analysis or neural network techniques can be too narrow in their approach and can lead to erroneous outcomes for varying scenarios. By combing both techniques, this prediction model can provide more accurate and flexible recommendations. Embedding Technical indicators will guide the investor to minimize the risk and reap better returns.

Download Full-text