A ca. 2.2Ga Acidic Magmatic Event at the Northern Margin of the Yangtze Craton: Evidence from U-Pb Dating and Hf Isotope Analysis of Zircons from the Kongling Complex

Objective The Yangtze craton collisional orogeny at ca. extensional events at ca. 1 experienced Paleoproterozoic 1.95-2.0 Ga and post-orogenic 85 Ga related to amalgamation of the Columbia （Nuna） supercontinent （Zhao and Cawood, 2012）. A ca. 2.15 Ga suprasubduction zone ophiolitic melange was recongized in the Archean- Paleoproterozoic Kongling Complex of the northern Yangtze craton （Han et al., 2017）. However, the tectonic evolution in early Paleoproterozoic from 2.4 Ga to 2.2 Ga remains unclear. We report here the presence of a suite of Paleoproterozoic （2.2 Ga） granites in the Huangling dome, northern Yangtze craton, which may provide important insights into crustal growth processes in the craton prior to the assembly of Columbia.

Benefits Down Evidently while Export Grew Slowly The Analysis of Economic Performance of China's Textile Machinery Industry from Jan. to Oct. 2008 (Part A)

Financial expenses Of China’s textile machinery in fiscal year 2008 rose 28.81%due to higher indebtedness(60.57%of indebtedness rate).Analysts anticipated animminent weakening of momentum for China’s textile machinery markets owing toweaker consumer spending and easing export growth.

Benefits Down Evidently while Export Grew Slowly The Analysis of Economic Performance of China's Textile Machinery Industry from Jan. to Oct. 2008 (Part B)

According to the latest statistics released by China TextileMachinery & Accessories Association(CTMA),the export value offoreign-funded enterprises from Jan.to Oct.2008,reached 0.502billion US dollars,a year-on-year increase of 0.08 percent.

The Modern Development of New Promising Fields in Forensic Examinations

The relevance of the study is forensic expert activity in terms of forensic examinations have been so transformed that existing theoretical provisions do not already solve traditional problems in some fields;their solvation requires new approaches of both theoretical and practical nature.In this regard,the purpose of this study is to analyze the content of new innovative directions in forensic examinations,including criminalistic ones,and the possibility of their effective application in forensic expert activity.The methodological basis of the study is the dialectical method of scientific knowledge,which allowed the authors to consider the theoretical and scientific,and practical foundations of modem trends in forensic examinations,including criminalistic ones.It also helped to identify promising fields of examinations necessary for crime prevention.Therefore,authors singled out the following advanced fields:biometric and computer forensic analyses,polygraph,and odor and trace evidence analyses.The materials of the article are of practical value for forensic experts and criminologists,law enforcement agencies.

A full-process intelligent trial system for smart court

In constructing a smart court,to provide intelligent assistance for achieving more efficient,fair,and explainable trial proceedings,we propose a full-process intelligent trial system(FITS).In the proposed FITS,we introduce essential tasks for constructing a smart court,including information extraction,evidence classification,question generation,dialogue summarization,judgment prediction,and judgment document generation.Specifically,the preliminary work involves extracting elements from legal texts to assist the judge in identifying the gist of the case efficiently.With the extracted attributes,we can justify each piece of evidence’s validity by establishing its consistency across all evidence.During the trial process,we design an automatic questioning robot to assist the judge in presiding over the trial.It consists of a finite state machine representing procedural questioning and a deep learning model for generating factual questions by encoding the context of utterance in a court debate.Furthermore,FITS summarizes the controversy focuses that arise from a court debate in real time,constructed under a multi-task learning framework,and generates a summarized trial transcript in the dialogue inspectional summarization(DIS)module.To support the judge in making a decision,we adopt first-order logic to express legal knowledge and embed it in deep neural networks(DNNs)to predict judgments.Finally,we propose an attentional and counterfactual natural language generation(AC-NLG)to generate the court’s judgment.