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A core challenge of assessing regional agricultural drought vulnerability (RADV) is to reveal what vulnerability factors, under which kinds of synergistic combinations and at what strengths, will lead to higher vulnerability: namely, the influence patterns of RADV.

A two-phased grey rough combined model is proposed to identify influence patterns of RADV from a new perspective of learning and mining historical cases. The grey entropy weight clustering with double base points is proposed to assess degrees of RADV. The simplest decision rules that reflect the complex synergistic relationships between RADV and its influencing factors are extracted using the rough set approach.

The results exemplified by China's Henan Province in the years 2008–2016 show higher degrees of RADV in the north and west regions of the province, in comparison with the south and east. In the patterns with higher RADV, the higher proportion of agricultural population appears in all decision rules as a core feature. A smaller quantity of water resources per unit of cultivated land area and a lower adaptive capacity, involving levels of irrigation technology and economic development, present a significant synergistic influence relationship that distinguishes the features of higher vulnerability from those of the lower.

The proposed grey rough combined model not only evaluates temporal dynamics and spatial differences of RADV but also extracts the decision rules between RADV and its influencing factors. The identified influence patterns inspire managerial implications for preventing and reducing agricultural drought through its historical evolution and formation mechanism.

The purpose of this paper is to propose a multi-scale extended grey target decision method for dealing with multi-attribute decision-making problems with interval grey numbers whose value distribution information is asymmetrical.

First, the whitenization weight function (WWF) was adopted to show the value distribution information of interval grey numbers. The definitions of kernel, degree of greyness, relative kernel and whitenization standard deviation of interval grey numbers were given based on the WWF. Then, the relative kernel grey target and whitenization standard deviation grey target were constructed to take full advantage of the owned decision information. Finally, the relative bull’s-eye coefficient was proposed to rank the preference order of all alternatives.

The relative bull’s-eye coefficient reflects the influence of the decision information on decision results with respect to the mean level and value distribution of attribute values. Thus, the decision-maker could set the return and risk adjustment coefficient according to their preferences and select the optimal alternative with a high expected return and low risk.

The paper considers the valve distribution information of interval grey numbers, and a novel definition for kernels, degrees of greyness, relative kernels and whitenization standard deviations, which are given based on the WWF. The paper not only considers the influence of mean levels of decision information over decision results, but also takes the value distribution information into account.

The purpose of this paper is to examine the curvilinear relationship between team informational faultlines and team creativity and the moderating effects of team humble leadership on the relationship.

The multisource and longitudinal survey data were collected from 85 teams. The authors conducted linear regression analyses to analyze the data.

The results indicate that the relationship between team informational faultlines and team creativity is inverted U-shaped and such relationship is stronger in teams with low levels of humble leadership.

The research reconciles the mixed findings in prior research and enhances our understanding of the functionality of informational faultlines.

Team managers should seek optimal levels of informational faultlines and make diversity coexist with similarity when assembling a new working group so as to utilize the benefits of team composition diversity and fuel collective creativity. Team leaders should learn humble leadership skills to encourage open communication.

The research is the first to adopt and build on the social information processing (SIP) perspective to explain the curvilinear relationship between team informational faultlines and team creativity.

Social mediametrics is a subfield of measurement in which the emphasis is placed on social media data. This paper analyzes the trends and patterns of paper comprehensively mentions on Twitter, with a particular focus on Twitter's mention behaviors. It uncovers the dissemination patterns and impact of academic literature on social media. The research has significant theoretical and practical implications.

This paper explores the fundamental attributes of Twitter mentions by means of analyzing 9,476 pieces of scholarly literature (5,097 from Nature and 4,379 from Science), 1,474,898 tweets and 451,567 user information collected from Altmetric.com database and Twitter API. The study uncovers assorted Twitter mention characteristics, mention behavior patterns and data accumulation patterns.

The findings illustrate that the top academic journals on Twitter have a wider range of coverage and display similar distribution patterns to other academic communication platforms. A large number of mentioners remain unidentified, and the distribution of follower counts among the mention users exhibits a significant Pareto effect, indicating a small group of highly influential users who generate numerous mentions. Furthermore, the proportion of sharing and exchange mentions positively correlates with the number of user followers, while the incidence of supportive mentions has a negative correlation. In terms of country-specific mention behavior, Thai scholars tend to utilize supportive mentions more frequently, whereas Korean scholars prefer sharing mentions over communicating mentions. The cumulative pattern of Twitter mentions suggests that these occur before official publication, with a half-life of 6.02 days and a considerable reduction in the number of mentions is observed on the seventh day after publication.

Conducting a multi-dimensional and systematic analysis of Twitter mentions of scholarly articles can aid in comprehending and utilizing social media communication patterns. This analysis can uncover literature's distribution patterns, dissemination effects and social significance in social media.

The purpose of this work is to controllably synthesize a carbon aerogel with programmable functionally graded performance via a simple and effective strategy.

This work uses polyvinyl alcohol (PVA) via the controllable sol-gel, lyophilization, and carbonization approach to achieve a programmable carbon aerogel. This design has the advantages of low raw material and preparation cost, simple and controllable synthetic process and low carbonization temperature.

The thermal stability and microstructure of PVA aerogel can be controlled by the crosslinking agent content within a certain range. The crosslinking agent content and the carbonization temperature are the key factors for functionally graded programming of carbon aerogels, including microstructure, oxygen-containing functional groups and adsorption performance. The adsorption ratio and adsorption rate of uranium can be controlled by adjusting initial concentration and pH value of the uranium solution. The 2.5%25 carbon aerogel with carbonization temperature of 350 °C has excellent adsorption performance when the initial concentration of uranium solution is 32 ppm at pH 7.5.

As a new type of lightweight nano-porous amorphous carbon material, this carbon aerogel has many excellent properties.

This work presents a simple, low cost and controllable strategy for functionally graded programming of novel carbon aerogel. This carbon aerogel has great potential for application in various fields such as uranium recovery, wastewater treatment, sound absorption and shock absorption.