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The use of linear models has major limitations for accurately representing the true link between gender diversity and organizational performance. This study aims to explore two curvilinear models and tests which one – the U-shape or the inverted U-shape – best represents the gender diversity–performance link at two hierarchical levels: the board of directors and the workforce.

Both models are tested using data collected from a representative sample of Spanish educational organizations, which are dominated numerically by women, although women are still slightly underrepresented in managerial positions.

The results show the existence of an inverted U-shape and, therefore, the existence of a potential “optimal” level of gender diversity for both the board of directors and the workforce. While the highest performance by the board of directors is attained when the proportion of women and men is balanced in the workforce, the highest level of performance is attained when the proportion of women is greater.

There are hardly any studies simultaneously exploring the gender diversity–performance linkage at two hierarchical levels where the proportion of women/men is substantially different: the board of directors and the workforce. Thus, this study contributes to better know whether such relationship is dependent on the hierarchical position. It is important to know this because each level is related to different functions and tasks and shape a social status that can significantly influence performance.

This study sought to understand the physical, educational and operational needs faced by healthcare workers (HCWs) (including physicians, nurses and allied health workers) during the COVID-19 pandemic.

A descriptive cross-sectional design was undertaken. HCWs working in hospitals, health centers, testing and quarantine areas in the Kingdom of Bahrain were invited to complete the online survey questionnaire developed by authors containing three domains: physical, educational, and perceived knowledge, and operational needs.

A convenient sample (N = 627) of volunteered participants responded to the online survey. The biggest challenges that HCWs were exposed to are physical needs (experiencing dry hands, difficulty breathing while on a mask, feeling hot and sweaty, and less fluid and food intake) which were reported as the higher level, followed by operational needs (limited communication due to Personal Protective Equipment - PPE - use, longer working hours, and preparation time to get ready for duty). Other challenges pertained to education and knowledge (the presence of multiple sources of information confused them during the care practices). Females faced more challenges than males, and Bahraini HCWs handled challenges more than non-Bahrainis. A negative relationship was found between age and years of experience with the challenges of the HCWs.

During the COVID-19 pandemic, health systems face rapidly increasing demands. HCWs face several challenges while providing patient care, particularly physical needs. This study provides adequate data for healthcare administrators to maintain a safe working environment during pandemics.

This research employed two neurophysiological techniques (electroencephalograms (EEG) and galvanic skin response (GSR)) and machine learning algorithms to capture and analyze relationship-oriented leadership (ROL) and task-oriented leadership (TOL). By grounding the study in the theoretical perspectives of transformational leadership and embodied leadership, the study draws connections to the human body's role in activating ROL and TOL styles.

EEG and GSR signals were recorded during resting state and event-related brain activity for 52 study participants. Both leadership styles were assessed independently using a standard questionnaire, and brain activity was captured by presenting subjects with emotional stimuli.

ROL revealed differences in EEG baseline over the frontal lobes during emotional stimuli, but no differences were found in GSR signals. TOL style, on the other hand, did not present significant differences in either EEG or GSR responses, as no biomarkers showed differences. Hence, it was concluded that EEG measures were better at recognizing brain activity associated with ROL than TOL. EEG signals were also strongest when individuals were presented with stimuli containing positive (specifically, happy) emotional content. A subsequent machine learning model developed using EEG and GSR data to recognize high/low levels of ROL and TOL predicted ROL with 81% accuracy.

The current research integrates psychophysiological techniques like EEG with machine learning to capture and analyze study variables. In doing so, the study addresses biases associated with self-reported surveys that are conventionally used in management research. This rigorous and interdisciplinary research advances leadership literature by striking a balance between neurological data and the theoretical underpinnings of transformational and embodied leadership.

This study aims to increase the novelty of clothing design and fabric texture. The element library that can be used for design is systematically summarized. The element database can also be continuously filled according to the existing logic to realize the diversity of design. Improve the theory of fashion design, expand the designer's design ideas and improve design efficiency. Clear design steps and logic can help students and machines learn the design process and promote the development of intelligent design. And verify the feasibility of the simulation software to assist pleated clothing design.

Firstly, according to the logical framework of origami theory, different innovative designs and combined designs are made for the basic units of hyperbolic paraboloid, and the element library that can be used for design is systematically summarized. This database can also be continuously filled according to the existing logic to realize the diversity of design. Secondly, it summarizes three methods of pleated element filling clothing – uniform filling method, the irregular filling method and geometric addition method – that improve the theory of fashion design, expand the designer's design ideas and improve design efficiency. Clear design steps and logic can help students and machines learn the design process and promote the development of intelligent design. Finally, the virtual software is used to simulate the effect of pleated clothing, and the three-dimensional simulation software 3dclo is used to make an empirical study on the application of hyperbolic paraboloid origami in clothing pleated design to verify the feasibility of the simulation software to assist pleated clothing design.

The theoretical results of hyperbolic paraboloid origami are collected and arranged to establish the element library of hyperbolic paraboloid origami. The results expand the designer's design ideas and auxiliary design technology and improve the design efficiency using a sample of hyperbolic paraboloid fabric to verify its practicability and three-dimensional clothing simulation software for exploring the design. The design rules of hyperbolic paraboloid clothing and the realization method of fabric are summarized, including the expansion and combing of elements, the application of size and shape and the method of combination.

Owing to the hyperbolic paraboloid origami’s length shrinkage, the loose computation of clothing requires targeted computation. This paper solely applies a paper model for estimating the shrinkage, and then we tend to subsequently explore the way to precisely compute the porosity, to determine the existing differences in the two-dimensional shrinkage of hyperbolic paraboloid creases of varying materials and to know if the clothing after large-scale production is capable of reaching the anticipated value.

The exploration of this experiment brings a new 3D experiment process to the design process.

This experiment brings new possibilities for the development of virtual fitting and virtual display in the industry.

This study combines hyperbolic paraboloid origami and clothing and combs and expands the unit with logical thinking to expand the designer's design ideas.

With the rapid development of social media, the occurrence and evolution of emergency events are often accompanied by massive users' expressions. The fine-grained analysis on users' expressions can provide accurate and reliable information for event processing. Hence, 2,003,814 expressions on a major malignant emergency event were mined from multiple dimensions in this paper.

This paper conducted finer-grained analysis on users' online expressions in an emergency event. Specifically, the authors firstly selected a major emergency event as the research object and collected the event-related user expressions that lasted nearly two years to describe the dynamic evolution trend of the event. Then, users' expression preferences were identified by detecting anomic expressions, classifying sentiment tendencies and extracting topics in expressions. Finally, the authors measured the explicit and implicit impacts of different expression preferences and obtained relations between the differential expression preferences.

Experimental results showed that users have both short- and long-term attention to emergency events. Their enthusiasm for discussing the event will be quickly dispelled and easily aroused. Meanwhile, most users prefer to make rational and normative expressions of events, and the expression topics are diversified. In addition, compared with anomic negative expressions, anomic expressions in positive sentiments are more common. In conclusion, the integration of multi-dimensional analysis results of users' expression preferences (including discussion heat, preference impacts and preference relations) is an effective means to support emergency event processing.

To the best of the authors' knowledge, it is the first research to conduct in-depth and fine-grained analysis of user expression in emergencies, so as to get in-detail and multi-dimensional characteristics of users' online expressions for supporting event processing.

The purpose of this study is to gain insight into the dynamics and considerations of professionals regarding the sharing of tacit, personal knowledge in their practice.

Adopting a social-constructivist ontology, the qualitative design deploys semi-structured interviews and focus groups. Data were coded, and analysed through interrelating and reasoning.

Personal knowledge is difficult to share precisely, but can be shared to some extent using reflection and stories. Knowledge also provides a position and professional agency, emphasising boundaries and impacting the decisions on interaction and sharing. As such, professional commitment is vulnerable and contextual and, by extension, material becomes part of this interplay of professional practice and collaborative development.

Findings imply that exchange and use of knowledge and material present in organisations are impacted by individual professionals’ autonomy and decisions, which consequently impact on employees’ practice. This calls for research that focuses on individual factors such as autonomy, professionalism and attitudes in addition to organisational and facilitative matters.

Stimulating professional commitment and interpersonal learning is a matter of valuing personal knowledge and practice to avoid protectionism, boundaries and segregated agency. Management and professionals should consider how and why individuals exchange their personal knowledge, paying attention to social structures and individuals’ voices and objectives in forming communities.

This study combines the concept of tacit knowledge with the younger field of practice theory. By connecting personal knowledge to practice, it extends agency to the material world and offers a more individual perspective to knowledge sharing in and between entities.