Exploring acid mine drainage treatment through adsorption: a bibliometric analysis.

Discharge of acidic wastewater from mining activities (acid mine drainage (AMD)) is a major global environmental and public health issue. Although several approaches, including chemical precipitation and membrane technology, have been developed to treat AMD, adsorption has emerged as the most promising technology due to its cost-effectiveness and efficacy. Despite the wide adoption of adsorption in treating AMD, the evolution of research in this area remains poorly understood.

Somatic Problems in Children Disclosing Sexual Abuse: The Mediating Role of Alexithymia and Dissociation.

Child sexual abuse (CSA) is linked to heightened levels of medically unexplained symptoms. Research indicates that victims of CSA display alexithymia and dissociation symptoms. Alexithymia and dissociation may potentially contribute to developing somatic complaints in CSA victims.

Association Between EHR Compatibility and Nurses' Emotional Exhaustion.

In this study we explored the relationship between nurses' emotional exhaustion and three EHR compatibility subdimensions (nurses' preferred work style, existing clinical practice, and values). We found higher emotional exhaustion with lower EHR compatibility for both preferred work style and existing clinical practice, but no relationship between emotional exhaustion and nurses' values. Efforts to improve EHR compatibility are recommended to mitigate nurses' burnout.

Development and Testing of an Instrument to Measure the Impact of EHR Use on Quality of Care.

There is an increased adoption of electronic health records (EHR) motivated by many purported benefits, yet limited research has explored their impact on quality of care. We developed and tested a multidimensional measure of quality of care in relation to EHR use. 234 nurses completed a cross-sectional survey.

Understanding older people's voice interactions with smart voice assistants: a new modified rule-based natural language processing model with human input.

The COVID-19 pandemic has expedited the integration of Smart Voice Assistants (SVA) among older people. The qualitative data derived from user commands on SVA is pivotal for elucidating the engagement patterns of older individuals with such systems. However, the sheer volume of user-generated voice interaction data presents a formidable challenge for manual coding.