Ultrashort Version of the Utrecht Work Engagement Scale (UWES-3): A Psychometric Assessment

The objective was to determine the validity of the UWES-3, an ultrashort measure of work engagement lacking evidence in Hispanic populations. In total, 200 workers with heterogeneous positions and careers from Metropolitan Lima were enrolled via nonprobabilistic sampling. The UWES-3 and measures of external variables (work accidents, stress overload, and others) were used. Data were collected through a web platform. Items were analysed, nonparametric response theory methods (Mokken scale analysis and Ramsay curves) were applied to the items, and ordinal and linear regression were used to determine the relationships with external variables. The items had statistically similar distributional properties and monotonic associations with external variables but with fewer functional response options. The UWES-3 complied with the monotonic homogeneity model and invariant ordering of items; the scaling of the items, score (greater than 0.80), and reliability (0.94) were high. With the effects of age and sex controlled, the UWES-3 significantly predicted minor accidents at work and job satisfaction and revealed effects of stress overload and perceived efficacy. The theoretical implications of the UWES-3 as a brief unidimensional measure integrating the three original dimensions of the instrument and the practical implications of its use for research and professional practice are discussed.

New records for the alien mud-dauber wasp Sceliphron caementarium (Drury, 1773) (Hymenoptera: Sphecidae) in Peru

New records of the mud-dauber wasp Sceliphron caementarium for Peru are reported through photographed material on the biodiversity web platform iNaturalist. The first records for the departments of La Libertad and Arequipa and the province of Talara are given. Moreover, the first precise localities for Lima province and department are quoted.

CalcUS: An Open-Source Computational Chemistry Web Platform

Computational chemistry is an increasingly active field due to the improvement of computing resources and theoretical tools. However, its use remains usually limited to technically-inclined users due to the technical challenges of preparing, launching and analyzing calculations. In this context, we have developed CalcUS, an open-source platform to streamline computational chemistry studies. Its objective is to democratize access to computational chemistry by providing a user-friendly web interface to simplify running and analyzing quantum mechanical calculations. It is freely available, expandable and customizable. It promotes connectivity to multiple software packages and algorithms, thus providing state-of-the-art techniques to all practitioners. We propose CalcUS as a standalone tool and infrastructure to support other open-source packages.

Development of NLP-Integrated Intelligent Web System for E-Mental Health

As the COVID-19 pandemic continues, the need for a better health care facility is highlighted more than ever. Besides physical health, mental health conditions have become a significant concern. Unfortunately, there are few opportunities for people to receive mental health care. There are inadequate facilities for seeking mental health support even in big cities, let alone remote areas. This paper presents the structure and implementation procedures for a mental health support system combining technology and professionals. The system is a web platform where mental health seekers can register and use functionalities like NLP-based chatbot for personality assessment, chatting with like-minded people, and one-to-one video conferencing with a mental health professional. The video calling feature of the system has emotion detection capabilities using computer vision. The system also includes downloadable prescription facilities and a payment gateway for secure transactions. From a technological aspect, the conversational NLP-based chatbot and computer vision-powered video calling are the system’s most important features. The system has a documentation facility to analyze the mental health condition over time. The web platform is built using React.js for the frontend and Express.js for the backend. MongoDB is used as the database of the platform. The NLP chatbot is built on a three-layered deep neural network model that is programmed in the Python language and uses the NLTK, TensorFlow, and Keras sequential API. Video conference is one of the most important features of the platform. To create the video calling feature, Express.js, Socket.io, and Socket.io-client have been used. The emotion detection feature is implemented on video conferences using computer vision, Haar Cascade, and TensorFlow. All the implemented features are tested and work fine. The targeted users for the platform are teenagers, youth, and the middle-aged population. Mental health-seeking is still considered taboo in some societies today. Apart from basic established facilities, this social dilemma of undergoing treatment for mental health is causing severe damage to individuals. A solution to this problem can be a remote platform for mental health support. With this goal in mind, this system is designed to provide mental health support to people remotely from anywhere worldwide.