How do the global stock markets influence one another? Evidence from finance big data and Granger causality directed network

The recent financial network analysis approach reveals that the topologies of financial markets have an important influence on market dynamics. However, the majority of existing Finance Big Data networks are built as undirected networks without information on the influence directions among prices. Rather than understanding the correlations, this research applies the Granger causality test to build the Granger Causality Directed Network for 33 global major stock market indices. The paper further analyzes how the markets influence one another by investigating the directed edges in the different filtered networks. The network topology that evolves in different market periods is analyzed via a sliding window approach and Finance Big Data visualization. By quantifying the influences of market indices, 33 global major stock markets from the Granger causality network are ranked in comparison with the result based on PageRank centrality algorithm. Results reveal that the ranking lists are similar in both approaches where the U.S. indices dominate the top position followed by other American, European, and Asian indices. The lead-lag analysis reveals that there is lag effects among the global indices. The result sheds new insights on the influences among global stock markets with implications for trading strategy design, global portfolio management, risk management, and markets regulation

Complexities in financial network topological dynamics: modeling of emerging and developed stock markets

Policy makings and regulations of financial markets rely on a good understanding of the complexity of financial markets. There have been recent advances in applying data-driven science and network theory into the studies of social and financial systems. Financial assets and institutions are strongly connected and influence each other. It is essential to study how the topological structures of financial networks could potentially influence market behaviors. Network analysis is an innovative method to enhance data mining and knowledge discovery in financial data. With the help of complex network theory, the topological network structures of a market can be extracted to reveal hidden information and relationships among stocks. In this study, two major markets of the most influential economies, China and the United States, are systematically studied from the perspective of financial network analysis. Results suggest that the network properties and hierarchical structures are fundamentally different for the two stock markets. The patterns embedded in the price movements are revealed and shed light on the market dynamics. Financial policymakers and regulators can gain inspiration from these findings for applications in policy making, regulations design, portfolio management, risk management, and trading

How network topologies impact project alliance performance: evidence from the movie industry

In many industries, partners are interconnected in project alliances that have limited lifespans and clearly-defined boundaries. The transparency of the movie industry provides a unique opportunity to study how alliance network topologies impact the performance of project alliances from the perspectives of social networks and organization theories. In this work, we compiled a massive movie dataset and constructed alliance networks for both movie production and distribution companies. Using the box office as the proxy for the financial performance of a movie project alliance, this research investigates how the two alliance networks impact the box office. We introduce the social network properties of degrees, centralities, and structural holes as alliance network variables into empirical regression models. The results show that alliance networks have a significant influence on the box office. The degrees of production companies and the structural holes of distribution companies are especially important to achieve success in the box office. The results add new evidence for the study of the movie economy and alliance networks. Meanwhile, this work also provides implications for the movie industry by revealing that it is essential to wisely choose partners that are appropriately embedded in alliance networks for the success of a movie project

Correlates of HIV self-testing among female sex workers in China: implications for expanding HIV screening.

BACKGROUND: Human immunodeficiency virus (HIV) self-testing may help improve test uptake among female sex workers. China has implemented many HIV self-testing programs among men who have sex with men, creating an opportunity for promotion among female sex workers. However, there is a limited literature on examining HIV self-testing among female sex workers. This study aimed to examine HIV self-testing experiences and its determinants among female sex workers in China. METHODS: A venue-based, cross-sectional study was conducted among Chinese female sex workers in 2019. Participants completed a survey including social-demographic characteristics, sexual behaviors, and HIV self-testing history, the distribution of which were analyzed using descriptive analysis. Multivariable logistic regression was conducted to identify associations with HIV self-testing. RESULTS: Among 1287 Chinese female sex workers, 1072 (83.3%, 95% confidence interval [CI] 81.2-85.3%) had ever tested for HIV, and 103 (8.0%, 95% CI 6.6-9.6%) had ever used HIV self-testing. More than half reported that the self-test was their first HIV test (59.2%, 61/103), around one-fifth reported HIV self-testing results influenced the price of sex (21.4%, 22/103). A minority of individuals reported ever experiencing pressure to undertake HIV self-testing (6.8%, 7/103). After adjusting for covariates, HIV self-testing was positively associated with receiving anal sex in the past month (adjusted odds ratio [aOR] = 2.2, 95% CI 1.4-3.5), using drugs before or during sex (aOR = 2.8, 95% CI 1.8-4.5), injecting drugs in the past 6 months (aOR = 2.6, 95% CI 1.2-6.0), being diagnosed with other sexually transmitted infections (aOR = 1.6, 95% CI 1.0-2.5), tested for other sexually transmitted infections in the past six months (aOR = 3.4, 95% CI 2.1-5.5), ever tested in the hospital (aOR = 3.4, 95% CI 2.0-5.6), and ever tested in the community (aOR = 1.5, 95% CI 1.2-1.9). CONCLUSIONS: Our findings suggest that HIV self-testing could expand overall HIV testing uptake, increase HIV testing frequency, reach sub-groups of high-risk female sex workers and has limited potential harms among female sex workers. HIV self-testing should be incorporated among Chinese female sex workers as a complement to facility-based HIV testing services

Exact eigenstate analysis of finite-frequency conductivity in graphene

We employ the exact eigenstate basis formalism to study electrical conductivity in graphene, in the presence of short-range diagonal disorder and inter-valley scattering. We find that for disorder strength, $W \ge$ 5, the density of states is flat. We, then, make connection, using the MRG approach, with the work of Abrahams \textit{et al.} and find a very good agreement for disorder strength, $W$ = 5. For low disorder strength, $W$ = 2, we plot the energy-resolved current matrix elements squared for different locations of the Fermi energy from the band centre. We find that the states close to the band centre are more extended and falls of nearly as $1/E_l^{2}$ as we move away from the band centre. Further studies of current matrix elements versus disorder strength suggests a cross-over from weakly localized to a very weakly localized system. We calculate conductivity using Kubo Greenwood formula and show that, for low disorder strength, conductivity is in a good qualitative agreement with the experiments, even for the on-site disorder. The intensity plots of the eigenstates also reveal clear signatures of puddle formation for very small carrier concentration. We also make comparison with square lattice and find that graphene is more easily localized when subject to disorder.Comment: 11 pages,15 figure

Quantitative learning strategies based on word networks

Learning English requires a considerable effort, but the way that vocabulary is introduced in textbooks is not optimized for learning efficiency. With the increasing population of English learners, learning process optimization will have significant impact and improvement towards English learning and teaching. The recent developments of big data analysis and complex network science provide additional opportunities to design and further investigate the strategies in English learning. In this paper, quantitative English learning strategies based on word network and word usage information are proposed. The strategies integrate the words frequency with topological structural information. By analyzing the influence of connected learned words, the learning weights for the unlearned words and dynamically updating of the network are studied and analyzed. The results suggest that quantitative strategies significantly improve learning efficiency while maintaining effectiveness. Especially, the optimized-weight-first strategy and segmented strategies outperform other strategies. The results provide opportunities for researchers and practitioners to reconsider the way of English teaching and designing vocabularies quantitatively by balancing the efficiency and learning costs based on the word network

Comparative genomics reveals insights into avian genome evolution and adaptation

Birds are the most species-rich class of tetrapod vertebrates and have wide relevance across many research fields. We explored bird macroevolution using full genomes from 48 avian species representing all major extant clades. The avian genome is principally characterized by its constrained size, which predominantly arose because of lineage-specific erosion of repetitive elements, large segmental deletions, and gene loss. Avian genomes furthermore show a remarkably high degree of evolutionary stasis at the levels of nucleotide sequence, gene synteny, and chromosomal structure. Despite this pattern of conservation, we detected many non-neutral evolutionary changes in protein-coding genes and noncoding regions. These analyses reveal that pan-avian genomic diversity covaries with adaptations to different lifestyles and convergent evolution of traits

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat