Physics-informed neural networks for high-resolution weather reconstruction from sparse weather stations.

Background: The accurate provision of weather information holds immense significance to many disciplines. One example corresponds to the field of air traffic management, in which one basis for weather detection is set upon recordings from sparse weather stations on ground. The scarcity of data and their lack of precision poses significant challenges to achieve a detailed description of the atmosphere state at a certain moment in time.

Ethical Considerations in Group Work with Transgender/Gender Diverse Clients.

This article explores the ethical and clinical issues that may arise when utilizing group psychotherapy to work with transgender and gender diverse (TGD) individuals. Considering the unique barriers to mental health services experienced by this community, the authors identify ethical standards that may be especially salient in this work, including: justice and respect for people's rights and dignity, competence, consent, and navigating multiple relationships. The article also explores the authors' TGD therapy group and how they have worked with and addressed such ethical considerations and concerns.

"Alguien abrió la puerta:" The phenomenology of bilingual Latinx clients' use of Spanish and English in psychotherapy.

There has been a growing recognition of the role that various aspects of culture play in the theory and practice of psychotherapy. One aspect of culture that has received little attention, however, is language. Specifically, we lack comprehensive understanding of the value bilingual clients find in expressing thoughts, feelings, and experiences in two languages.

A Comparison of Machine Learning and Deep Learning Techniques for Activity Recognition using Mobile Devices.

We have compared the performance of different machine learning techniques for human activity recognition. Experiments were made using a benchmark dataset where each subject wore a device in the pocket and another on the wrist. The dataset comprises thirteen activities, including physical activities, common postures, working activities and leisure activities.

Incremental Market Behavior Classification in Presence of Recurring Concepts.

In recent years, the problem of concept drift has gained importance in the financial domain. The succession of manias, panics and crashes have stressed the non-stationary nature and the likelihood of drastic structural or concept changes in the markets. Traditional systems are unable or slow to adapt to these changes.

System steganalysis with automatic fingerprint extraction.

This paper tries to tackle the modern challenge of practical steganalysis over large data by presenting a novel approach whose aim is to perform with perfect accuracy and in a completely automatic manner. The objective is to detect changes introduced by the steganographic process in those data objects, including signatures related to the tools being used. Our approach achieves this by first extracting reliable regularities by analyzing pairs of modified and unmodified data objects; then, combines these findings by creating general patterns present on data used for training.

Internet Use and Psychological Well-Being at Advanced Age: Evidence from the English Longitudinal Study of Aging.

This work explores the connection between psychological well-being and Internet use in older adults. The study is based on a sample of 2314 participants in the English Longitudinal Study of Aging. The subjects, aged 50 years and older, were interviewed every two years over the 2006-2007 to 2014-2015 period.

Creating national air pollution models for population exposure assessment in Canada.

Background: Population exposure assessment methods that capture local-scale pollutant variability are needed for large-scale epidemiological studies and surveillance, policy, and regulatory purposes. Currently, such exposure methods are limited.

Methods: We created 2006 national pollutant models for fine particulate matter [PM with aerodynamic diameter ≤ 2.

AMPSO: a new particle swarm method for nearest neighborhood classification.

Nearest prototype methods can be quite successful on many pattern classification problems. In these methods, a collection of prototypes has to be found that accurately represents the input patterns. The classifier then assigns classes based on the nearest prototype in this collection.