Jumping Risk Communities in the Energy Industry: An Empirical Analysis Based on Time-Varying Complex Networks

This paper uses the 5-five-minute high-frequency data of energy-listed companies in China's A-share market to extract the jump of energy stock prices and build a dynamic stock price jump complex network. Then, we analyze the clustering effect of the complex network. The research shows that the energy stock price jump is an important part of stock price volatility, and the complex network of energy stock jump risk has obvious time-varying characteristics. However, the infection problem of stock price jump risks needs specific analysis. China's coal industry has an important influence on the development of China's energy industry. According to the clustering analysis results of the network community, the clustering effect of the network community has time-varying characteristics. After October 2017, the clustering effect of the jumping risk of the coal industry and the new energy industry is obvious. The risk contagion within the new energy industry community is a key point for the development of the new energy industry.

Density Peaks Clustering based on Nature Nearest Neighbor and Multi-cluster Mergers

Clustering by fast search and find of Density Peaks (DPC) has the advantages of being simple, efficient, and capable of detecting arbitrary shapes, etc. However, there are still some shortcomings: 1) the cutoff distance is specified in advance, and the selection of local density formula will affect the final clustering effect; 2) after the cluster centers are found, the assignment strategy of the remaining points may produce “Domino effect”, that is, once a point is misallocated, more points may be misallocated subsequently. To overcome these shortcomings, we propose a density peaks clustering algorithm based on natural nearest neighbor and multi-cluster mergers. In this algorithm, a weighted local density calculation method is designed by the natural nearest neighbor, which avoids the selection of cutoff distance and the selection of the local density formula. This algorithm uses a new two-stage assignment strategy to assign the remaining points to the most suitable clusters, thus reducing assignment errors. The experiment was carried out on some artificial and real-world datasets. The experimental results show that the clustering effect of this algorithm is better than those other related algorithms.

An Improved K-Means Algorithm Based on Evidence Distance

The main influencing factors of the clustering effect of the k-means algorithm are the selection of the initial clustering center and the distance measurement between the sample points. The traditional k-mean algorithm uses Euclidean distance to measure the distance between sample points, thus it suffers from low differentiation of attributes between sample points and is prone to local optimal solutions. For this feature, this paper proposes an improved k-means algorithm based on evidence distance. Firstly, the attribute values of sample points are modelled as the basic probability assignment (BPA) of sample points. Then, the traditional Euclidean distance is replaced by the evidence distance for measuring the distance between sample points, and finally k-means clustering is carried out using UCI data. Experimental comparisons are made with the traditional k-means algorithm, the k-means algorithm based on the aggregation distance parameter, and the Gaussian mixture model. The experimental results show that the improved k-means algorithm based on evidence distance proposed in this paper has a better clustering effect and the convergence of the algorithm is also better.

Recurring Lexis and Reader-Reception in Horace’s Odes: The Formation of a Lyric Opus

<p>This study investigates perceived patterns of lexical recurrence in consecutive or closely proximate poems in Books 1-3 of the Odes of the Roman poet Horace and considers the significance these may have for the structure and organization of this work and its interpretive reception by readers. An initial discussion and demonstration of the types of lexical recurrence observed and their frequency prompts the question of the extent to which these recurrent lexical usages are intentional on the part of the author and hence whether they were factors in determining the order in which the poems of each book are arranged. This question is investigated firstly through statistical analysis, which shows that there is no statistically significant greater clustering effect apparent in the lexical patterns observed than had the odes been arranged in random order. Nevertheless, given than certain recurrences between closely adjacent poems do stand out because of the identity or close similarity of their grammatical or morphological forms and/or metrical location, and that this phenomenon has been perceived by other commentators, the significance that might be attributed to these as poetic effects falls within the domain of reader-reception theory. A summary review of the principal tenets of this theory as developed especially by Ingarden, Gadamer, Jauss and Iser is undertaken in order to derive a sound theoretical method by which the recurrence patterns may be analysed and coherent meaning may be constructed from them. This method is then applied to analysis of a prominent cluster of lexical recurrences over the final five poems of Odes 1 (1.34-1.38). The question of how far such meaning may have corresponded to the intentions of the author Horace is then addressed. A distinction is made, following Bakhtin, between the “primary”, historical author who composed the work and the “secondary” authorial consciousness who engages the reader through the text. While intentions of the former are ultimately unknowable, the secondary author “Horace” does declare intentions for his work through his texts which the reader may then reconstruct. The thesis posits that the poetic ambition of Horace within this textual horizon was first to acquire an erudite and discerning audience capable of accepting him and appreciating his artistry, and then to develop a distinctive generic vehicle by which to engage this audience in dialogue about matters of importance in the Roman social, political and cultural worlds. The development of an audience is a major theme of his Satires Book 1, while the book of Epodes is the framework for his attempt to adapt the iambic metre of Archilochus to his dialogic purpose. The analysis shows that this latter project proved unfruitful because of the indelible association of iambic with invective. The concluding chapter shows that it was the adoption of archaic Greek lyric metres other than iambic that finally provided Horace with the poetic vehicle he sought to write verse that both adhered to the Callimachean aesthetic of brevity and technical perfection and allowed engagement with serious as well as frivolous themes. It examines the manner by which the three Books of Odes, read sequentially as a single opus, firstly familiarize their readers with these archaic metres and the range of lyric themes they can encompass before leading them to an acceptance that lyric can also address important public issues, notably in the “Roman Odes” of Book 3. The perception of the patterns of lexical recurrence throughout the three books is a significant factor in promoting this dialogic engagement of the reader with the text.</p>

Recurring Lexis and Reader-Reception in Horace’s Odes: The Formation of a Lyric Opus

<p>This study investigates perceived patterns of lexical recurrence in consecutive or closely proximate poems in Books 1-3 of the Odes of the Roman poet Horace and considers the significance these may have for the structure and organization of this work and its interpretive reception by readers. An initial discussion and demonstration of the types of lexical recurrence observed and their frequency prompts the question of the extent to which these recurrent lexical usages are intentional on the part of the author and hence whether they were factors in determining the order in which the poems of each book are arranged. This question is investigated firstly through statistical analysis, which shows that there is no statistically significant greater clustering effect apparent in the lexical patterns observed than had the odes been arranged in random order. Nevertheless, given than certain recurrences between closely adjacent poems do stand out because of the identity or close similarity of their grammatical or morphological forms and/or metrical location, and that this phenomenon has been perceived by other commentators, the significance that might be attributed to these as poetic effects falls within the domain of reader-reception theory. A summary review of the principal tenets of this theory as developed especially by Ingarden, Gadamer, Jauss and Iser is undertaken in order to derive a sound theoretical method by which the recurrence patterns may be analysed and coherent meaning may be constructed from them. This method is then applied to analysis of a prominent cluster of lexical recurrences over the final five poems of Odes 1 (1.34-1.38). The question of how far such meaning may have corresponded to the intentions of the author Horace is then addressed. A distinction is made, following Bakhtin, between the “primary”, historical author who composed the work and the “secondary” authorial consciousness who engages the reader through the text. While intentions of the former are ultimately unknowable, the secondary author “Horace” does declare intentions for his work through his texts which the reader may then reconstruct. The thesis posits that the poetic ambition of Horace within this textual horizon was first to acquire an erudite and discerning audience capable of accepting him and appreciating his artistry, and then to develop a distinctive generic vehicle by which to engage this audience in dialogue about matters of importance in the Roman social, political and cultural worlds. The development of an audience is a major theme of his Satires Book 1, while the book of Epodes is the framework for his attempt to adapt the iambic metre of Archilochus to his dialogic purpose. The analysis shows that this latter project proved unfruitful because of the indelible association of iambic with invective. The concluding chapter shows that it was the adoption of archaic Greek lyric metres other than iambic that finally provided Horace with the poetic vehicle he sought to write verse that both adhered to the Callimachean aesthetic of brevity and technical perfection and allowed engagement with serious as well as frivolous themes. It examines the manner by which the three Books of Odes, read sequentially as a single opus, firstly familiarize their readers with these archaic metres and the range of lyric themes they can encompass before leading them to an acceptance that lyric can also address important public issues, notably in the “Roman Odes” of Book 3. The perception of the patterns of lexical recurrence throughout the three books is a significant factor in promoting this dialogic engagement of the reader with the text.</p>

A new look at the meeting clustering effect

PurposeThe study aims to test the existence of a meeting clustering effect in the Spanish Stock Exchange (SSE).Design/methodology/approachThis paper studies the relationship between the clustering of annual general meetings and stock returns in the SSE. A multivariate analysis is carried out in order to analyse the relationship between monthly returns and the clustering of general meetings in the SSE.FindingsThe authors show that meeting clustering exists and that some months exhibit significant and positive additional returns related to the holding of ordinary or extraordinary general meetings.Research limitations/implicationsThe authors have explored some possible explanations for the meeting clustering effect, such as a potential link with the “Halloween” effect or the presence of higher-than-normal levels of volatility, trading volumes or investor attention. However, none of these can explain the meeting clustering effect that emerges as a new anomaly in the SSE.Practical implicationsThe authors have documented significant and positive abnormal returns in some months that coincide with the holding of general meetings. Therefore, the holding of ordinary and/or extraordinary meetings in some months involves the release of relevant information for investors.Originality/valueThis study complements the financial literature because it is focused on the clustering of meetings and its effect on a stock market whose legal order is based on civil law. This fact allows us to shed new light on meeting clustering and its effect on other types of markets.

Passenger Flow Prediction of Integrated Passenger Terminal Based on K-Means–GRNN

As the passenger flow distribution center cooperating with various modes of transportation, the comprehensive passenger transport hub brings convenience to passengers. With the diversification of passenger travel modes, the passenger flow scale gradually increases, which brings significant challenges to the integrated passenger hub. Therefore, it is urgent to solve the problem of early warning and response to the future passenger flow to avoid congestion accidents. In this paper, the passenger flow GRNN prediction model is proposed, based on the K-means cluster algorithm, and an improved index named BWPs (Between-Within Proportion-Similarity) is proposed to improve the clustering effect of K-means so that the clustering effect of the new index is verified. In addition, the passenger flow data are studied and trained by combining with the GRNN neural network model based on parameter optimization (GA); the passenger flow prediction model is obtained. Finally, the passenger flow of Chengdu East Railway Station has been taken as an example, which is divided into 16 models, and each type of passenger flow is predicted, respectively. Compared with the traditional method, the results show that the model can predict the passenger flow with high accuracy.

Risk factors for scabies, tungiasis, and tinea infections among schoolchildren in southern Ethiopia: A cross-sectional Bayesian multilevel model

Background Skin problems cause significant sickness in communities with poor living conditions, but they have received less attention in national or global health studies because of their low mortality rates. In many developing regions, the prevalence of parasitic skin diseases among schoolchildren is not reported. Previous studies thus have attempted to identify risk factors for these conditions using the frequentist approach. This study aimed to assess the occurrence and risk factors of skin infections among rural schoolchildren in southern Ethiopia by combining a frequentist and a Bayesian approach. Methodology/Principal findings Using three-stage random sampling, we assessed 864 schoolchildren aged 7–14 years from the Wonago district in southern Ethiopia. We detected potential risk factors for scabies, tungiasis, and tinea infections and recorded their hygienic practices and socio-demographic information. The frequentist model revealed a clustering effect of 8.8% at the classroom level and an insignificant effect at the school level. The Bayesian model revealed a clustering effect of 16% at the classroom level and 5.3% at the school level. Almost three-fourths of the sample had at least one type of skin problem, and boys were at higher overall risk than girls (adjusted odds ratio [aOR] 1.55 [95% Bayesian credible interval [BCI] 1.01, 2.28). Risk factors included unclean fingernails (aOR 1.85 [95% BCI 1.08, 2.97]); not washing the body (aOR 1.90 [95% BCI 1.21, 2.85]) and hair (aOR 3.07 [95% BCI 1.98, 4.57]) with soap every week; sharing a bed (aOR 1.97 [95% BCI 1.27, 2.89]), clothes (aOR 5.65 [95% BCI 3.31, 9.21]), or combs (aOR 3.65 [95% BCI 2.28, 5.53]); and living in a poor household (aOR 1.76 [95% BCI 1.03, 2.83]). Washing legs and feet with soap daily was identified as a protective factor for each of the three skin diseases (aOR 0.23 [95% BCI 0.15, 0.33]). Conclusions/Significance We observed high variation in skin problems at the classroom level, indicating the presence of shared risk factors in these locations. The findings suggest the need to improve children’s personal hygiene via health education by schoolteachers and health workers.

Research on Data Analysis of Traditional Chinese Medicine with Improved Differential Evolution Clustering Algorithm

Medical data analysis is an important part of intelligent medicine, and clustering analysis is a commonly used method for data analysis of Traditional Chinese Medicine (TCM); however, the classical K-Means algorithm is greatly affected by the selection of initial clustering center, which is easy to fall into the local optimal solution. To avoid this problem, an improved differential evolution clustering algorithm is proposed in this paper. The proposed algorithm selects the initial clustering center randomly, optimizes and locates the clustering center in the process of evolution iteration, and improves the mutation mode of differential evolution to enhance the overall optimization ability, so that the clustering effect can reach the global optimization as far as possible. Three University of California, Irvine (UCI), data sets are selected to compare the clustering effect of the classical K-Means algorithm, the standard DE-K-Means algorithm, the K-Means++ algorithm, and the proposed algorithm. The experimental results show that, in terms of global optimization, the proposed algorithm is obviously superior to the other three algorithms, and in terms of convergence speed, the proposed algorithm is better than DE-K-Means algorithm. Finally, the proposed algorithm is applied to analyze the drug data of Traditional Chinese Medicine in the treatment of pulmonary diseases, and the analysis results are consistent with the theory of Traditional Chinese Medicine.