On the Basis of Excavated Bamboo Slip Edition of the “Zi Yi” Revealing the Origin of the Lost Ode “Du Ren Shi”

[[abstract]]　　《都人士》在《毛詩‧小雅》裡是首以五章六句為結構的詩，然在齊、魯、韓詩中此詩只有四章。經學家們早已提出了毛公《都人士》的第一章與全詩有異，可能原來非同一首詩。除《毛詩》外，第一章亦引入《緇衣》、《左傳》、《新書》之中。因此，筆者擬根據這些引文以及新近出土的《緇衣》簡本，逐步推論、復原《都人士》第一章本屬的逸詩原貌

A Machine Learning Pipeline for Forecasting Time Series in the Banking Sector

The problem of forecasting time series is very widely debated. In recent years, machine learning algorithms have been very prolific in this area. This paper describes a systematic approach to building a machine learning predictive model for solving optimization problems in the banking sector. A literature analysis on applying such methods in this particular area is presented. As a direct result of the described research, a universal scenario for forecasting various non-stationary time series in automatic mode was developed. The developed scenario for solving specific banking tasks to improve business efficiency, including optimizing demand for ATMs, forecasting the load on the call center and cash center, is considered. A machine learning methodology in economics that can yield robust and reproducible results and can be reused in solving other similar tasks is described. The methodology described in the article was tested on three cases and showed the ability to generate models that are superior in accuracy to similar predictive models described in the literature by at least three percentage points. This article will be helpful to specialists dealing with the problem of forecasting economic time series and students and researchers due to a large number of links to systematic literature reviews on this topic

A Machine Learning Pipeline for Forecasting Time Series in the Banking Sector

The problem of forecasting time series is very widely debated. In recent years, machine learning algorithms have been very prolific in this area. This paper describes a systematic approach to building a machine learning predictive model for solving optimization problems in the banking sector. A literature analysis on applying such methods in this particular area is presented. As a direct result of the described research, a universal scenario for forecasting various non-stationary time series in automatic mode was developed. The developed scenario for solving specific banking tasks to improve business efficiency, including optimizing demand for ATMs, forecasting the load on the call center and cash center, is considered. A machine learning methodology in economics that can yield robust and reproducible results and can be reused in solving other similar tasks is described. The methodology described in the article was tested on three cases and showed the ability to generate models that are superior in accuracy to similar predictive models described in the literature by at least three percentage points. This article will be helpful to specialists dealing with the problem of forecasting economic time series and students and researchers due to a large number of links to systematic literature reviews on this topic

Jianghan plain, the locale of China’s Great Flood four thousand years ago

Abstract The Yellow River Plain (YRP), being regarded as the cradle of Chinese civilization, is traditionally thought to be the locale of the Great Flood, a hazardous flood (or floods) tamed by Yu who started China’s first “dynasty”, Xia, in ~ 2000 BC. However, by integrating published archaeological data, we propose that the Great Flood in fact impacted the Jianghan Plain (JHP) along the middle course of the Yangtze River. The arguments include: (1) around the era of the Great Flood, the most civilized and populated society in East Asia, named the Jianghan society, was located around the JHP (at that time, the habitation on the YRP remained limited); (2) the Jianghan society lived on river resources (shipping and rice growing) and was thus subject to flood risks (but not for the people inhabiting the YRP); (3) the people in the Jianghan society were experienced in dredging moats/ditches for shipping and irrigation; (4) unlike the floods on the YRP that were characterized by dynamic sedimentation and channel avulsion, those on the JHP typically occurred with slow-moving water manageable to ancient people; (5) the JHP has been associated with lake/wetland systems serving as detention basins during floods. Here, the recorded method for controlling the Great Flood, dredging channels to divert flood water to a “sea”, was feasible. Known speleothem paleo-rainfall data from multiple sites show that the climate of the JHP had been wet since the middle Holocene (earlier than the era of the Great Flood) and significantly turned dry after ~ 1850 BC (~ 150 years later than the Great Flood). Thus, the uniqueness of the Great Flood was likely to reflect an increase in land use on the JHP with the expansion of the Jianghan society, and the success in taming this flood was mainly due to the efforts of the society, not by luck

Intravenous Administration of Coenzyme Q10 in Acute Period of Cerebral Ischemia Decreases Mortality by Reducing Brain Necrosis and Limiting Its Increase within 4 Days in Rat Stroke Model

Oxidative stress plays a key role in the pathogenesis of ischemic stroke. Coenzyme Q10 has a multi-targeting effect and may protect the brain against ischemic damage. The aim of our study was to evaluate the neuroprotective potential of ubiquinol by its intravenous administration. The study was performed on rats; a stroke was modeled by occlusion of the middle cerebral artery. On days 1 and 4 after ischemia, the neurological deficit and volume of the brain lesion were determined by MRI and TTC staining. Intravenous administration of coenzyme Q10 led to a decrease in rat mortality rate, improvement in neurological status, and decrease in the brain necrosis area in acute and delayed period after cerebral ischemia. A single intravenous administration of ubiquinol led to a limitation of the size of the brain damage for at least four days after ischemia. Thus, intravenous administration of coenzyme Q10 has a persistent neuroprotective potential. This finding suggests a possible therapeutic role of ubiquinol in acute ischemic conditions

Clinical outcome and risk assessment in hospitalized COVID-19 patients with elevated transaminases and acute kidney injury: A single center study

Objectives:Initial reports indicate a high incidence of abnormal aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels in patients with COVID-19 and possible association with acute kidney injury (AKI). We aimed to investigate clinical features of elevated transaminases on admission, its association with AKI, and outcomes in patients with COVID-19. Methods:A retrospective analysis of the registered data of hospitalized patients with laboratory-confirmed COVID-19 and assessment of the AST and ALT was performed. Multinomial logistic regression was used to determine factors associated with community-acquired AKI (CA-AKI) and hospital-acquired AKI (HA-AKI). Results:The subjects comprised 828 patients (mean age = 65.0±16.0 years; 51.4% male). Hypertension was present in 70.3% of patients, diabetes mellitus in 26.0%, and chronic kidney disease in 8.5%. In-hospital mortality was 21.0%. At admission, only 41.5% of patients had hypertransaminasemia. Patients with elevated transaminases at admission were younger, had higher levels of inflammatory markers and D-dimer, and poorer outcomes. The AKI incidence in the study population was 27.1%. Patients with hypertransaminasemia were more likely to develop AKI (33.5% vs. 23.3%, p = 0.003). Patients with predominantly elevated AST (compared to elevated ALT) were more likely to have adverse outcomes. Multinomial logistic regression found that hypertension, chronic kidney disease, elevated AST, and hematuria were associated with CA-AKI. Meanwhile, age \u3e 65 years, hypertension, malignancy, elevated AST, and hematuria were predictors of HA-AKI. Conclusions:Elevated transaminases on admission were associated with AKI and poor outcomes. Patients with elevated AST were more likely to have adverse outcomes. Elevated AST on admission was associated with CA-AKI and was a predictor of HA-AKI