Mendeley Data Showcase

Data: The dataset contains employee sales performance. Each record represents an individual employee and their Division, Level of Education, Trainig Level, Work Experience, Salary, Sales. Research Hypothesis: Employees with higher levels of education, more training, and greater work experience tend to achieve higher sales performance and earn higher salaries than employees with lower education, training, or experience levels. Potential Analyses: This dataset supports several statistical analyses, including: descriptive statistics, correlation analysis, regressions analysis, ANOVA. Limitation: Small sample dataset, the source could not be independently verified.

This dataset contains the MATLAB code, synthetic visual and topological Vicsek-model simulation data, empirical Golden Shiner trajectory data, and analysis results used to validate Interaction Geometry Inference using Correlation (IGIC), a framework for estimating interaction radius and sensing angle from time-resolved trajectory data.

This was a cross-secti⁠o⁠nal descriptive and analytical health facility⁠-based study for 9 months (from November 2024 to July 2025) in six health districts (HDs) in Yaoundé: Biyem-Assi, Cité Verte, Djoungolo, Efoulan, Nkolbisson, and Nkolndongo. Each HD c⁠ont⁠ains a mix of public and private (confessional and non-confessional) HFs operating at primary, secondary, and tertiary level⁠s of ca⁠re, reflecting the pl⁠uralistic stru⁠cture of Cameroon's national health⁠ system. Yaoundé, the political capital of Cameroon is located in the Centre region. It hosts the highest concent⁠ration of⁠ HFs and⁠ health information management infrastructure in the country. This characteristic makes it an appropriate site for a comprehensive assessment⁠ of RH⁠IS performance. The diversity of HF ty⁠pes, ownership models, and HD charac⁠teristi⁠cs present in Yaoundé enable analysi⁠s of RHIS performance across a broad spectrum of institutiona⁠l contexts.

Abstract Funerary pottery serving as grave markers or items entombed with the deceased constitutes a common archaeological and ethnographic phenomenon across African societies. Among the indigenous Gbágyì communities of Bwari in the Federal Capital Territory (FCT) of Nigeria, these specialized clay vessels long featured in the funerary rituals of Muslim families—seamlessly blending indigenous cosmic traditions with Islamic eschatology, until 2024 when Bwari families last demanded such pots from their suppliers, the Ushafa potters. The use of these special pots is now replaced with concrete slabs. This shift in the funeral culture of the people opens up critical inquiries into localized cultural homogenization under the weight of rapid urbanization. Adopting an interpretive phenomenological anthropology framework underpinned by historicized ethnographic grounding, this study utilizes a mixed-method approach comprising an extensive literature review, participant observation, and semi-structured interviews with primary stakeholders consisting of six respondents made up of community elders and potters. The paper examines the production processes, formal attributes, and functional mechanics of Bwari funerary split-pots. It further analyzes how these minimalist clay wares serve as symbolic anchors of spiritual equality and social cohesion, while interrogating the socio-economic drivers—namely, aggressive urbanization, neoliberal transformations, and Islamic standardization through Izala Salafism—catalyzing their decline. The findings demonstrate how global forces tend to flatten hyper-local rituals, diminishing traditional pottery while revealing its responsiveness and adaptive capacity to cultural change.

The growing gig economy is reshaping the economy and offering new possibilities for entrepreneurship. But this area remains unexplored, however, about the effect of gig economy on entrepreneurial intention, especially in developing economies. Based on the Theory of Planned Behavior, Social Cognitive Theory, Human Capital Theory, and Resource Based View, this study constructs and verifies an integrated model that connects the growth of gig economy to entrepreneurial intention by the entrepreneurial motivation, entrepreneurial and professional competencies, entrepreneurial challenges, entrepreneurial self-efficacy, and entrepreneurial resource readiness. This study involved 263 gig workers from Bangladesh from which some data were collected and analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM). The results suggest that entrepreneurial motivation, competencies, challenges and self-efficacy are significantly improved as a result of the growth of the gig economy, while entrepreneurial intention and resource readiness are not directly affected. The entrepreneurial intention is strongly predicted by entrepreneurial motivation, competencies, and self-efficacy, but not by entrepreneurial challenges and resource readiness. Moreover, entrepreneurial competencies and self-efficacy play a significant intermediary role between the growth of the gig economy and entrepreneurial intentions. The study shows that the gig economy is basically a capability-development ecosystem that circumstantially encourages entrepreneurial aspirations by developing skills and increasing entrepreneurial confidence.

Data on the heart rate of postpartum mothers in relation to their age, body weight, systolic and diastolic blood pressure and packed cell volume (PCV).

This is an original dataset containing information on population levels in 360 small, consistent local geographic units (CLGUs) for nine census benchmarks in Argentina between 1895 and 2010. In addition to population data, we have a comprehensive set of geographic control variables for each CLGU.

This dataset contains the raw episode-level data from four controlled experiments examining how virtual agent appearance (human-like vs. robot-like) and behavior (prosocial vs. individualistic social value orientation, or high vs. medium task efficiency) shape social perception (warmth and competence) and cooperation preferences in an immersive virtual reality environment. Participants were recruited via Prolific and completed a VR-based cooperative task, the Coins game, using a VR headset. After each episode, participants rated their AI co-player on warmth and/or competence, and after every two episodes, they reported a stated cooperation preference between the two co-players. The dataset includes four CSV files, one per study reported in the associated manuscript. Study1_Data.csv contains data from Study 1 (N = 52 participants), which manipulated agent appearance and prosocial/individualistic behavior to examine effects on warmth perceptions and cooperation preference. Study2_Data.csv contains data from Study 2 (N = 52 participants), which manipulated agent appearance and task efficiency (high vs. medium) to examine effects on competence perceptions and cooperation preference. Study3_Data.csv contains data from Study 3 (N = 53 participants), a replication of Study 1 in which the human-like avatar's gender was changed, to test whether the appearance-warmth effect observed in Study 1 was attributable to avatar gender rather than the human-versus-robot appearance contrast. Study4_Data.csv contains data from Study 4 (N = 62 participants), a replication of Study 1 in which the robot-like avatar's design was changed from a friendly, approachable robot to a mechanically harsh, non-cute robot, to test whether the warmth advantage observed for robot-like agents in Studies 1 and 3 depended on the specific aesthetic properties of the robot design rather than the human-versus-robot distinction itself. This file also includes participant responses to nine post-study perception items for each of the four agent variants (Adam Prosocial, Adam Individualistic, Jammo Prosocial, Jammo Individualistic). Each file contains episode-level records, with one row per episode per participant. Variables include participant ID, pair and episode sequence numbers, agent type, appearance, and behavioral condition, player and AI scores, warmth and/or competence ratings, stated cooperation preference, bonus payment, participant demographics (age, gender, VR experience), and coin-collection counts by color and player.

This dataset contains de-identified student-level data from a semester-long quasi-experiment comparing gamified SQL training games with traditional end-to-end database design practice, conducted at MIREA – Russian Technological University in the spring semester of the 2025/2026 academic year. Study design. Two independent cohorts of engineering students were stratified by pre-test score and grade point average (GPA) into an experimental group (EG, n = 82) that used gamified online SQL trainers, and a control group (CG, n = 85) that completed conventional end-to-end database design from a written specification. Both groups were taught by the same instructor under equal contact time. A pre-test (20 closed-form items in Moodle) was administered before the practical cycle; a post-test (20 parallel-form items) was administered at the end. An anonymous survey (138 responses) collected self-reported engagement and obstacles; survey data are not included in this dataset because they carry no student identifier linking them to test scores.

The dataset includes repeated DASS-21 assessment scores and expressive writing texts collected throughout the intervention.