Khalifa University

About: Khalifa University is a education organization based out in Abu Dhabi, United Arab Emirates. It is known for research contribution in the topics: Computer science & Adsorption. The organization has 3752 authors who have published 10909 publications receiving 141629 citations.

Designing a next generation solar crystallizer for real seawater brine treatment with zero liquid discharge.

Abstract: Proper disposal of industrial brine has been a critical environmental challenge Zero liquid discharge (ZLD) brine treatment holds great promise to the brine disposal, but its application is limited by the intensive energy consumption of its crystallization process Here we propose a new strategy that employs an advanced solar crystallizer coupled with a salt crystallization inhibitor to eliminate highly concentrated waste brine The rationally designed solar crystallizer exhibited a high water evaporation rate of 242 kg m−2 h−1 under one sun illumination when treating real concentrated seawater reverse osmosis (SWRO) brine (216 wt%) The solar crystallizer array showed an even higher water evaporation rate of 480 kg m−2 per day in the outdoor field test, suggesting a great potential for practical application The solar crystallizer design and the salt crystallization inhibition strategy proposed and confirmed in this work provide a low-cost and sustainable solution for industrial brine disposal with ZLD Proper disposal of industrial brine remains a critical environmental challenge Here, the authors devise a solar crystallizer and propose a salt crystallization inhibition strategy, which together provide a low-cost and sustainable solution for industrial brine disposal with zero liquid discharge

Effectiveness and Safety of Using Chatbots to Improve Mental Health: Systematic Review and Meta-Analysis

Abstract: Background: The global shortage of mental health workers has prompted the utilization of technological advancements, such as chatbots, to meet the needs of people with mental health conditions. Chatbots are systems that are able to converse and interact with human users using spoken, written, and visual language. While numerous studies have assessed the effectiveness and safety of using chatbots in mental health, no reviews have pooled the results of those studies. Objective: This study aimed to assess the effectiveness and safety of using chatbots to improve mental health through summarizing and pooling the results of previous studies. Methods: A systematic review was carried out to achieve this objective. The search sources were 7 bibliographic databases (eg, MEDLINE, EMBASE, PsycINFO), the search engine “Google Scholar,” and backward and forward reference list checking of the included studies and relevant reviews. Two reviewers independently selected the studies, extracted data from the included studies, and assessed the risk of bias. Data extracted from studies were synthesized using narrative and statistical methods, as appropriate. Results: Of 1048 citations retrieved, we identified 12 studies examining the effect of using chatbots on 8 outcomes. Weak evidence demonstrated that chatbots were effective in improving depression, distress, stress, and acrophobia. In contrast, according to similar evidence, there was no statistically significant effect of using chatbots on subjective psychological wellbeing. Results were conflicting regarding the effect of chatbots on the severity of anxiety and positive and negative affect. Only two studies assessed the safety of chatbots and concluded that they are safe in mental health, as no adverse events or harms were reported. Conclusions: Chatbots have the potential to improve mental health. However, the evidence in this review was not sufficient to definitely conclude this due to lack of evidence that their effect is clinically important, a lack of studies assessing each outcome, high risk of bias in those studies, and conflicting results for some outcomes. Further studies are required to draw solid conclusions about the effectiveness and safety of chatbots. Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42019141219; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019141219

Longitudinal changes in CSF alpha-synuclein species reflect Parkinson's disease progression.

Abstract: Background Parkinson's disease (PD) diagnosis is mainly based on clinical criteria, with a high risk of misdiagnosis. The identification of reliable biomarkers for disease diagnosis and progression has a key role for developing disease-modifying therapies. In this article, we investigated the longitudinal changes of CSF α-synuclein species in early PD patients and explored the potential use of these species as surrogate biomarkers for PD progression. Methods We used our newly developed enzyme-linked immunosorbent assay systems for measuring different forms of α-synuclein, such as oligomeric-α-synuclein, phosphorylated-α-synuclein at serine 129, or total-α-synuclein in CSF from the longitudinal Deprenyl and Tocopherol Antioxidative Therapy for Parkinsonism study cohort (n = 121). CSF Alzheimer's disease biomarkers (total-tau, phosphorylated-tau, Aβ40, and Aβ42) were also measured for this cohort. Results Interestingly, total-α-synuclein and oligomeric-α-synuclein levels significantly increased during the 2-year Deprenyl and Tocopherol Antioxidative Therapy for Parkinsonism study follow-up period, whereas phosphorylated-α-synuclein at serine 129 levels showed a longitudinal decrease. We have also noted an association between a change of the oligomeric-α-synuclein/total-α-synuclein ratio and a worsening of motor signs, in particular in the postural-instability and gait-difficulty dominant PD group. A strong positive correlation between the changes in CSF total-α-synuclein and oligomeric-α-synuclein during the 2-year Deprenyl and Tocopherol Antioxidative Therapy for Parkinsonism study was also noted (r = 0.84, P < .001). Conclusion Our data show that CSF α-synuclein species have a dynamic pattern along the course of the disease, supporting their possible role as progression biomarkers for PD and their link with PD clinical phenotypes. © 2016 International Parkinson and Movement Disorder Society