Tilting modules of tilted algebras and related topics

Tilting theory has been a central research topic in representation theory for a long time. Let $Λ$ be a hereditary algebra, $T_0$ be a tilting Λ-module, B := \End_Λ(T_0), then $B$ is called a tilted algebra of type $Λ$. In this thesis, we will study some related topics of tilted algebras. We will give some general ways to construct tilting $B$-modules from tilting $Λ$-modules. The main tools we will use in the constructions are the traces and rejects. Let $A$ be a finite dimensional $k$ algebra over an algebraically closed field $k$, the study of the equivalence classes of tilting $A$-modules was initiated by Riedtman and Schofield in 1991. Later in 2005, Happel and Unger defined the tilting quiver \overrightarrow{\cK_A} for a given algebra $A$. With the constructions of tilting modules we have obtained, we will show how to get the tilting quiver of $B$ from that of $Λ$, when $B$ is a BB-tilted algebra of type $Λ$. As a generalization of the classic tilting theory, $τ$-tilting theory was introduced by Adachi, Iyama and Reiten in 2014. For a given algebra $A$, in analogy with the tilting quiver of $A$, the authors in 2014 defined a quiver which is called the support $τ$-tilting quiver $Q(sτ-tiltA)$. We will consider the reconstruction of the support $τ$-tilting quiver $Q(sτ-tiltB)$ from the support $τ$-tilting quiver $Q(sτ-tiltΛ)$

Tilting quivers for BB-tilted algebras

Let $\Lambda$ be a hereditary algebra, $B_0=End_\Lambda(T_0)$ be a tilted algebra. We will construct tilting $B_0$-modules from tilting $\Lambda$-modules and use this result to show how tilting quivers of BB-tilted algebras can be obtained from those of $\Lambda$Comment: 20 page

Study on dynamic characteristics of silt solidified soil caused by train operation

With the rapid development of railway construction, many railway projects often cross the soft ground. The initial water content of the silt is too high to be directly applied to the engineering practice. In order to improve the engineering property of the silt, the corresponding precipitation treatment measures should be taken according to the different initial water content of the silt to ensure the safety of the project. This article relying on Shilong railway freight yard container project that contain silt soil to conduct in situ curing technology research, the vibration response characteristics of the stabilized soil was studied before and after curing. The results showed that silt solidified soil has a significant attenuation effect on vibration energy. Increasing the proportion of curing agent can enhance the vibration isolation effect of silt solidified soil

Social Media Attention and the “Death” of Cryptocurrency: A Hazard Model Perspective

This paper studies the survival of cryptocurrencies and their association with the social media attention they receive. The death of a cryptocurrency is defined based on the discontinuation of trading activities and modeled using Kaplan – Meier Survivor Function and the Cox survival regressions. Using data collected from coinmarketcap.com and bitcointalk.org, we find that social media attention is a very relevant influencer for the death hazard. Specifically, the death hazard of a cryptocurrency is estimated to increase by 0.5% - 1% for each additional trading day without any social media mention. We also find that high-quality social media mentions are more effective in reducing the death hazard. The theoretical and practical implications of the findings are discussed in the paper

An Order-Invariant and Interpretable Hierarchical Dilated Convolution Neural Network for Chemical Fault Detection and Diagnosis

Fault detection and diagnosis is significant for reducing maintenance costs and improving health and safety in chemical processes. Convolution neural network (CNN) is a popular deep learning algorithm with many successful applications in chemical fault detection and diagnosis tasks. However, convolution layers in CNN are very sensitive to the order of features, which can lead to instability in the processing of tabular data. Optimal order of features result in better performance of CNN models but it is expensive to seek such optimal order. In addition, because of the encapsulation mechanism of feature extraction, most CNN models are opaque and have poor interpretability, thus failing to identify root-cause features without human supervision. These difficulties inevitably limit the performance and credibility of CNN methods. In this paper, we propose an order-invariant and interpretable hierarchical dilated convolution neural network (HDLCNN), which is composed by feature clustering, dilated convolution and the shapley additive explanations (SHAP) method. The novelty of HDLCNN lies in its capability of processing tabular data with features of arbitrary order without seeking the optimal order, due to the ability to agglomerate correlated features of feature clustering and the large receptive field of dilated convolution. Then, the proposed method provides interpretability by including the SHAP values to quantify feature contribution. Therefore, the root-cause features can be identified as the features with the highest contribution. Computational experiments are conducted on the Tennessee Eastman chemical process benchmark dataset. Compared with the other methods, the proposed HDLCNN-SHAP method achieves better performance on processing tabular data with features of arbitrary order, detecting faults, and identifying the root-cause features

Ginseng leaf-stem: bioactive constituents and pharmacological functions

Ginseng root is used more often than other parts such as leaf stem although extracts from ginseng leaf-stem also contain similar active ingredients with pharmacological functions. Ginseng's leaf-stems are more readily available at a lower cost than its root. This article reviews the pharmacological effects of ginseng leaf-stem on some diseases and adverse effects due to excessive consumption. Ginseng leaf-stem extract contains numerous active ingredients, such as ginsenosides, polysaccharides, triterpenoids, flavonoids, volatile oils, polyacetylenic alcohols, peptides, amino acids and fatty acids. The extract contains larger amounts of the same active ingredients than the root. These active ingredients produce multifaceted pharmacological effects on the central nervous system, as well as on the cardiovascular, reproductive and metabolic systems. Ginseng leaf-stem extract also has anti-fatigue, anti-hyperglycemic, anti-obesity, anti-cancer, anti-oxidant and anti-aging properties. In normal use, ginseng leaf-stem extract is quite safe; adverse effects occur only when it is over dosed or is of poor quality. Extracts from ginseng root and leaf-stem have similar multifaceted pharmacological activities (for example central nervous and cardiovascular systems). In terms of costs and source availability, however, ginseng leaf-stem has advantages over its root. Further research will facilitate a wider use of ginseng leaf-stem

Meandering river sandstone architecture characterization based on seisimic sedimentology in Kumkol South oilfields [RETRACTED ARTICLE]

1460-1471To improve the finely architecture characterization of meandering river sand body in wide well space oilfield, this study identified the meandering river sand body of Layer MI-1 of Kumkol South Oilfield in South Turgai Basin. Under the guidance of the sedimentary pattern of meandering channel sand body, this study establishes the log-seismic reservoir characterization method by applying reservoir characterization，seismic sedimentology and seismic forward simulation with well logging and seismic data. The different levels of meandering river sand body which include the composite meandering belts, single meandering belt, single point bar and single point bar inner are finely studied in Layer MI-1 of Kumkol South Oilfield. Based on the researches mentioned above, the recognition method and criteria of composite channel are studied. Specifically, the cosine phase seismic attribute can be used to recognize the lateral boundaries of composite channel when the thickness of composite channels >8 m. And the frequency division data can be used to recognize the vertical boundaries of composite channels when the thickness of composite channels >9 m. The recognition methods of the abandon channel and the mud stone between channels are also studied. Specifically, the sweet, waveform classification and the three-instantaneous information can improve the recognition of single channel boundary. Six boundaries are recognized in layer MI-1. Finally, the recognition method and criteria of lateral accretionary layers are studied. In the sedimentary and seismic data conditions of study area, the synthetic seismic information can improve the recognition of the lateral accretionary layers when the thickness of point bar >12 m and the thickness of lateral accretionary layers >1. 5 m

Building Up Knowledge through Meta-analysis: A Review and Reinterpretation

In the last two decades, researchers have increasingly conducted meta-analyses in the information systems (IS) field. As such, we need to ensure that researchers conduct such analyses in a sound and accurate way, use appropriate and effective meta-analytic techniques, and produce reliable and valid results. Nevertheless, few papers on conducting a meta-analysis in the IS field exist. In this paper, we review and re-interpret the procedures, issues, and techniques in conducting a meta-analysis in the IS field. By doing so, we make important contributions to helping IS researchers expand their baseline knowledge of meta-analyses and, thus, more effectively design and conduct them in the future