Sun, Sleep, and Satisfaction: Mediating Role of Depression and Source of Endogeneity among Middle-aged and Older Adults in China

Purpose To examine: (i) depression as a mediator in effects of sleep duration and quality on life satisfaction (LS), (ii) source of endogeneity in self-reported data on sleep, and (iii) predictive power of sleep duration and quality on LS. Methods Panel data of 22,674 observations from the China Health and Retirement Longitudinal Survey (2015 & 2018) was used. Sleep was assessed with self-reported duration and quality. Depression was measured by the 10-question version of the Center for Epidemiological Survey - Depression. LS was rated by five scales. Fixed-effects ordered logit models were used to determine the effect of sleep duration and quality on life satisfaction and the mediating role of depression. We used instrumental variable strategy to explore the source of endogeneity. Information value and random forest model were used to examine the predictive power of sleep measures duration and quality. Results Sleep duration and quality were found to improve life satisfaction via lower depression score. Non-agricultural employed population with urban hukou (household registration) accounted for the endogeneity, but the instrument variable sunset failed the weak instrument test. Sleep measures were found to predict life satisfaction, especially for the lower life satisfaction groups. Conclusion Our findings suggest the importance of sleep and the study of the associations between solar cues, social schedules, and sleep. Policy makers of social care of older adults might consider sleep intervention among this population.

A Data-Driven Expectation Prediction Framework Based on Social Exchange Theory

Along with the rapid application of new information technologies, the data-driven era is coming, and online consumption platforms are booming. However, massive user data have not been fully developed for design value, and the application of data-driven methods of requirement engineering needs to be further expanded. This study proposes a data-driven expectation prediction framework based on social exchange theory, which analyzes user expectations in the consumption process, and predicts improvement plans to assist designers make better design improvement. According to the classification and concept definition of social exchange resources, consumption exchange elements were divided into seven categories: money, commodity, services, information, value, emotion, and status, and based on these categories, two data-driven methods, namely, word frequency statistics and scale surveys, were combined to analyze user-generated data. Then, a mathematical expectation formula was used to expand user expectation prediction. Moreover, by calculating mathematical expectation, explicit and implicit expectations are distinguished to derive a reliable design improvement plan. To validate its feasibility and advantages, an illustrative example of CoCo Fresh Tea & Juice service system improvement design is further adopted. As an exploratory study, it is hoped that this study provides useful insights into the data mining process of consumption comment.

Spatial Metrics of Interaction between CD163-Positive Macrophages and Cancer Cells and Progression-Free Survival in Chemo-Treated Breast Cancer

Tumor-associated macrophages (TAMs) promote progression of breast cancer and other solid malignancies via immunosuppressive, pro-angiogenic and pro-metastatic effects. Tumor-promoting TAMs tend to express M2-like macrophage markers, including CD163. Histopathological assessments suggest that the density of CD163-positive TAMs within the tumor microenvironment is associated with reduced efficacy of chemotherapy and unfavorable prognosis. However, previous analyses have required research-oriented pathologists to visually enumerate CD163+ TAMs, which is both laborious and subjective and hampers clinical implementation. Objective, operator-independent image analysis methods to quantify TAM-associated information are needed. In addition, since M2-like TAMs exert local effects on cancer cells through direct juxtacrine cell-to-cell interactions, paracrine signaling, and metabolic factors, we hypothesized that spatial metrics of adjacency of M2-like TAMs to breast cancer cells will have further information value. Immunofluorescence histo-cytometry of CD163+ TAMs was performed retrospectively on tumor microarrays of 443 cases of invasive breast cancer from patients who subsequently received adjuvant chemotherapy. An objective and automated algorithm was developed to phenotype CD163+ TAMs and calculate their density within the tumor stroma and derive several spatial metrics of interaction with cancer cells. Shorter progression-free survival was associated with a high density of CD163+ TAMs, shorter median cancer-to-CD163+ nearest neighbor distance, and a high number of either directly adjacent CD163+ TAMs (within juxtacrine proximity <12 μm to cancer cells) or communicating CD163+ TAMs (within paracrine communication distance <250 μm to cancer cells) after multivariable adjustment for clinical and pathological risk factors and correction for optimistic bias due to dichotomization.

The impact of the COVID-19 pandemic on knowledge sharing in UK higher education

Purpose The paper aims to explore “content” factors influencing consumptive and contributive use of enterprise social networking within UK higher education during the COVID-19 pandemic. Design/methodology/approach The methodology uses genre analysis and grounded theory to analyse empirical data from posts obtained through Microsoft Yammer and a focus group. Findings The findings reveal the motivators-outcomes-strategies and the barriers-outcomes-strategies of users. Motivators (M) include feature value, Information value, organizational requirement and adequate organizational and technical support. Barriers (B) include six factors, including resisting engagement on the online platform, emotional anxiety, loss of knowledge, the lack of organizational pressure, lack of content quality and lack of time. An Outcomes (O) framework reveals benefits and dis-benefits and strategies (S) relating to improving user engagement. Practical implications The research method and resultant model may serve as guidelines to higher educational establishments interested in motivating their staff and scholars around the use of enterprise social network (ESN) systems, especially during face-to-face restrictions. Originality/value This research study was conducted during the COVID-19 pandemic which provides a unique setting to examine consumptive and contributive user behaviour of ESN’s. Furthermore, the study develops a greater understanding of “content” factors leading to the benefits or dis-benefits of ESN use, drawing on user motivators, barriers and strategies during the COVID-19 pandemic in UK education.

Construction of Power Transmission and Transformation Project Cost Information Platform Based on Big Data Analysis

With the reform of China’s power system, power transmission and transformation project (hereinafter referred to as PTATP) are gradually developing in the direction of integration, informatization, large-scale and systematization. Therefore, the traditional project cost can no longer meet the needs of the society, which requires the project cost based on BD (hereinafter referred to as BD) technology. Through the information platform (hereinafter referred to as IPF), we can collect a lot of information, including policies and regulations database, talent and machine price information database, project cost index database, industry information database, etc., which will provide important support for project cost. Project cost informatization will solve the problems of low information sharing rate, low information value and high information cost, which will more scientifically complete the cost of PTATP. Based on BD technology, we can collect, sort out and analyze the cost information data of PTATP, which will fully explore the data value. Firstly, this paper analyzes the main algorithms needed for project cost. Finally, this paper constructs a PTATP cost IPF based on BD analysis, which will provide accurate countermeasures.

Informational Value of Proadrenomedullin Blood Levels in Patients with Septic Shock, Once Measured Upon Admission to ICU

The objective: to assess the information value of proadrenomedullin (PAM), once measured upon admission to ICU in predicting mortality and differential diagnosis of septic and hypovolemic shock.Subjects and Methods. A prospective cohort retrospective study was carried out. 134 patients in a state of shock were included in the study. Of these, 125 patients had septic shock; 9 ‒ hypovolemic one. The diagnosis of septic shock was established according to the Sepsis-3 criteria. To compare hypovolemic and septic shock, blood levels of proadrenomedullin (PAM), procalcitonin (PCT) and lactate were tested in 9 patients with obvious hypovolemic shock. Samples (venous blood) were collected within 24 hours from the moment the vasopressors began to be used in ICU or by the ambulance team (EMS).Results. The ROC analysis showed comparable predictive value with APACHE II, SOFA and lactate scales in patients with septic shock with cut-off > 4.23 nmol/L. The range of PAM values in patients with septic shock was Me 4.56 (2.9‒6.7) in patients with hypovolemic shock – Me 0.6 (0.1‒1.4).Conclusion. Proadrenomedullin can be used for differential diagnosis of septic shock and hypovolemic shock. Blood levels greater than 2.9 nmol/L are of absolute value for the diagnosis of septic shock. Procalcitonin is inferior to PAM within the range of 1.0–6.45 ng/ml. PAM unlike SCT is a statistically significant predictor of global outcome in septic shock along with lactate and scales. But such scales as SOFA and ARACНE-II are more laborious in comparison with testing proadrenomedullin blood level.

Fiscal issues of entities’ non-financial reporting

The article identifies areas for strengthening the information value of non-financial reporting data, in particular in terms of its fiscal issues. The author substantiates the issues of disclosure of data on the impact of uncertainty on the entities’ activities based on the results of the analysis of scientific publications and generally accepted international documents. It is proved that high-quality non-financial reporting can serve as one of the tools for attracting additional funding for eliminating the consequences of the COVID-19 pandemic. The article highlights the results of the analysis of non-financial reporting of state-owned enterprises to identify data on the impact of the COVID-19 pandemic on their activities and compliance with the list of sustainability reporting indicators defined in the document “Guidance on core indicators for entity reporting on contribution towards implementation of the Sustainable Development Goals”, developed by UNCTAD ISAR. The paper substantiates that non-financial reporting data can serves as one of the information sources for decision-making at the state level in terms of avoiding fiscal risks (management report, report on payments to government). The core research methods used in the article: bibliometric analysis; synthesis; observation.

Seeking Scientific Health Information for Empowerment: Empowered-Get-More-Empowered Effects

To explore the scientific value of information elements in health news, this article reports on common information elements that are associated with scientific value, according to the findings of surveys conducted in the United States and Taiwan. The design of two further studies in Taiwan reflects an effort to understand whether scientific information elements benefit only health conscious people, through empowered-get-more-empowered effects. A survey-based analysis of perceptions and an experimental test of causal effects of information exposure reveal that health conscious people seek health information, value scientific information elements in it, are persuaded by them, and act on advice.

THEORETICAL FUNDAMENTALS OF ESTIMATABILITY ASSESSMENT OF TRAIN SITUATION SIGNS FOR WORK OF INTELLECTUAL LOCOMOTIVE CONTROL SYSTEMS

The article is devoted to the problem of implementation of intelligent control systems in transport. An important task is to assess the information parameters of the control systems. In the existing works the question of definition of one of the basic parameters of functioning of locomotive control systems - information value of separate signs of a train situation is not considered. This does not make it possible to determine the order of signal processing at the input and assess their contribution to the adoption of a control decision. Moreover, informativeness is a relative value, which is expressed in the different information value of a particular feature for the classification of different train situations. Also, the informativeness of the feature may depend on the type of decisive rules in the classification procedure. The quality of recognition of a train situation in which the locomotive crew is, depends on the quality of the features used by the classification system. The decisive criterion for the informativeness of the features in the problem of pattern recognition is the magnitude of losses from errors. To determine the range of the most informative features of train situations, the method of random search with adaptation was used. The results of the work make it possible to optimize the operation of automated and intelligent train control systems by reducing the amount of calculations and simplifying their algorithm.