Subjects: Physics >> Nuclear Physics submitted time 2024-02-06
Jiahao Chen
Yanlin Ye
Kai Ma
Jiaxing Han
Dongxi Wang
Chengjian Lin
Huiming Jia
Lei Yang
Gen Li
Lisheng Yang
Ziyao Hu
Zhiwei Tan
Kang Wei
Weiliang Pu
Ying Chen
Jianling Lou
Xiaofei Yang
Qite Li
Zaihong Yang
Tianpeng Luo
Abstract： Recently, an inelastic scattering experiment of 16O + 12C was performed at the Beijing Tandem Accelerator Nuclear Physics National of China Institute of Atomic Energy. New evidence for the existence of Bose-Einstein condensation state of 16𝑂 has been obtained. Employing a series of double-sided-silicon-strip-based telescopes, this experiment achieved accurate particle identification and coincidence measurement of 4-𝛼 in the decay of 16O for the first time. Based on this, high-resolution reaction 𝑄-value spectra was obtained and clear 4-𝛼 resonance states were reconstructed. In the vicinity of the 4-𝛼 separation threshold, 4 highly significant (3 of them above 5𝜎) resonance states were observed, which decay to the characteristic pattern of 12C(Hoyle state) + 𝛼, consistent with the predicted Hoyle-BEC structure and its rotating band features. The observation results will promote further theoretical research, and more measurements are needed for these resonance states in experiments.
Subjects: Psychology >> Social Psychology submitted time 2023-03-28 Cooperative journals: 《心理科学进展》
Abstract： As for the conceptualization of mental disorders, the traditional DSM-ICD classification diagnostic system, i.e., Diagnostic and Statistical Manual of Mental Disorders(DSM) and International Classification of Diseases(ICD), as well as the Research Domain Criteria (RDoC) proposed by National Institute of Mental Health(NIMH) are both based on the latent variable perspective, assuming that the symptoms of mental disorders have an underlying common cause(the disorder entity or dysfunction in different potential dimensions). However, such latent variable perspective requires local independency between variables, thus both views ignore the interaction between symptoms. In 2008, Borsboom put forward the psychopathological network theory, a new perspective different from the categorical and dimensional views of the conceptualization of mental disorders. This theory focuses on the interaction between symptoms, assuming that mental disorders are directly composed of symptoms and dynamic causal relationship between them. Based on this theory, network methods mainly estimate the partial correlation network of symptoms using the glasso algorithm with EBIC, and examine the different characteristics of mental disorder symptoms using indicators such as node centrality and network connectivity. In recent years, many new network models have emerged, such as Bayesian networks and relative importance networks that can perform causality inferences. With the increasing number of studies that applied psychopathological network theory and methods, this theory and method has clearly become one of the mainstream research theories and methods in the field of current mental health and psychopathological and psychometrics related research. But at the same time, researchers also found some remaining challenges for psychopathological network methods with respect to causality inference of symptoms, identification of central symptoms, and also reliability and replicability of network structures. Accordingly, this review briefly introduced the core idea and basic principles of psychopathology network theory, as well as the most commonly used psychopathology network analysis methods so far, and summarized important applications and values of psychopathology network theory and methods, then synthesized the main challenges that psychopathological network analysis method were currently facing. Finally, corresponding possible solutions were proposed. After reviewing a wide range of related publishments in theories, methods, and empirical since psychopathology network theory was put forward, we provided unique insights into the possible agendas for future research on psychopathological network methods, hoping the challenges and progress in the methodology could also bring new opportunities for the further improvement of psychopathological network theory.
Subjects: Psychology >> Statistics in Psychology submitted time 2021-04-03
Abstract： "
Peer Review Status:
Awaiting Review
Subjects: Biology >> Botany >> Applied botany submitted time 2020-09-15 Cooperative journals: 《广西植物》
Abstract：为了研究毛果巴豆枝叶中的化学成分，本实验采用硅胶、Sephadex LH-20柱色谱以及HPLC等多种色谱相结合的方法，对毛果巴豆枝叶95%乙醇提取物的乙酸乙酯萃取部位进行分离，从中得到8个化合物，通过波谱数据分析并结合文献比对，化合物分别鉴定为2β-hydroxyteucvidin acetate（1），2β-hydroxyteucvidin（2），crotoeurin B（3），山奈酚-3-O-(6″-O-顺式对香豆酰基)-β-D-吡喃葡萄糖苷（4），山奈酚-3-O-(6″-O-反式对香豆酰基)-β-D-吡喃葡萄糖苷（5），栗苷A（6），cerevisterol（7），尿嘧啶（8）。化合物2-7均为首次从该植物分离得到。
Subjects: Dynamic and Electric Engineering >> Engineering Thermophysics submitted time 2017-11-23 Cooperative journals: 《工程热物理学报》
Abstract：低温烟气热能的高效梯级利用是火电厂节能减排的重要方向之一。本文结合某1000MW超临界机组，对常规低温省煤器烟气余热利用系统进行了热力学分析，发现该系统可使系统发电标准煤耗率降低2.50 g•(kW•h)-1，但?分析发现，空气预热器耗散?占输入?的22.03%，多于锅炉排烟所携带的?。为此，本文提出了集成SCO2动力循环的火电厂低温烟气热能利用系统，旨在减少空气预热器中的?耗散。对SCO2动力循环参数进行了优化，在优化参数下该系统可以使发电标准煤耗率降低3.62 g•(kW•h)-1，进一步集成低温省煤器可使发电标准煤耗率降低达5.58 g•(kW•h)-1，最后采用?分析结果解释了系统节能的本质原因。
Subjects: Dynamic and Electric Engineering >> Engineering Thermophysics submitted time 2017-10-30 Cooperative journals: 《工程热物理学报》
Abstract：低温烟气热能的高效梯级利用是火电厂节能减排的重要方向之一。本文结合某1000MW超临界机组，对常规低温省煤器烟气余热利用系统进行了热力学分析，发现该系统可使系统发电标准煤耗率降低2.50 g•(kW•h)-1，但?分析发现，空气预热器耗散?占输入?的22.03%，多于锅炉排烟所携带的?。为此，本文提出了集成SCO2动力循环的火电厂低温烟气热能利用系统，旨在减少空气预热器中的?耗散。对SCO2动力循环参数进行了优化，在优化参数下该系统可以使发电标准煤耗率降低3.62 g•(kW•h)-1，进一步集成低温省煤器可使发电标准煤耗率降低达5.58 g•(kW•h)-1，最后采用?分析结果解释了系统节能的本质原因。
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