Mental health on the go: Navigating travel and travel eligibility

The 21st century has seen tourists from various source markets significantly impacted by non-communicable diseases, including mental disorders. Yet, research and practice frequently overlook tourists with mental disorders. Building on Buckley’s discussion in the Journal of Travel Research about tourism and mental health, this study examines the travel eligibility of tourists diagnosed with four prevalent mental disorders: major depressive disorder (MDD), generalized anxiety disorder (GAD), schizophrenia, and dementia. We present preliminary recommendations for accommodating these tourists and highlight the urgent need for collaborative efforts between stakeholders in tourism, hospitality, and medicine. © The Author(s) 2023

MUTLA: A Large-Scale Dataset for Multimodal Teaching and Learning Analytics

Automatic analysis of teacher and student interactions could be very important to improve the quality of teaching and student engagement. However, despite some recent progress in utilizing multimodal data for teaching and learning analytics, a thorough analysis of a rich multimodal dataset coming for a complex real learning environment has yet to be done. To bridge this gap, we present a large-scale MUlti-modal Teaching and Learning Analytics (MUTLA) dataset. This dataset includes time-synchronized multimodal data records of students (learning logs, videos, EEG brainwaves) as they work in various subjects from Squirrel AI Learning System (SAIL) to solve problems of varying difficulty levels. The dataset resources include user records from the learner records store of SAIL, brainwave data collected by EEG headset devices, and video data captured by web cameras while students worked in the SAIL products. Our hope is that by analyzing real-world student learning activities, facial expressions, and brainwave patterns, researchers can better predict engagement, which can then be used to improve adaptive learning selection and student learning outcomes. An additional goal is to provide a dataset gathered from real-world educational activities versus those from controlled lab environments to benefit the educational learning community.Comment: 3 pages, 1 figure, 2 tables workshop pape

Retrieve-then-extract Based Knowledge Graph Querying Using Graph Neural Networks

The abstract of Retrieve-then-extract Based Knowledge Graph Querying Using Graph Neural Networks will be updated here

African dryland ecosystem changes controlled by soil water

Monitoring long‐term vegetation dynamics in African drylands is of great importance for both ecosystem degradation studies and carbon‐cycle modelling. Here, we exploited the complementary use of optical and passive microwave satellite data— normalized difference vegetation index (NDVI) and vegetation optical depth (VOD)—to provide new insights of ecosystem changes in African drylands. During 1993–2012, 54% of African drylands experienced a significant increase of VOD, mainly located in southern Africa and west and central Africa, with an average rate of increase of (1.2 ± 2.7) × 10−3 yr−1. However, a significant decreasing NDVI was observed over 43% of the African drylands, in particular in western Niger and eastern Africa, with an average browning rate of (−0.13 ± 1.5) × 10−3 yr−1. The contrasting vegetation trends (increasing VOD and decreasing NDVI) were largely caused by an increase in the relative proportion of the woody component of the vegetation, as a result of the prevailing woody encroachment in African drylands during the study period. Soil water emerges as the dominant driver of ecosystem changes in African drylands, in particular in arid and semiarid areas. This is evidenced by a strong spatio‐temporal correlation between soil water and vegetation, where soil water changes explain about 48% of vegetation variations. This study emphasizes the potential of utilizing multiple satellite products with different strengths in monitoring different characteristics of ecosystems to evaluate ecosystem changes and reveal the underlying mechanisms of the observed changes

Solidarity tourism: A pathway to revitalising the health of vulnerable war-affected populations?

The struggles of war are felt by all who occupy an affected region (and beyond), irrespective of whether they are in active combat. This experience has physical effects (e.g. injury, illness, malnutrition, disability, sexual violence, and/or death) and emotional impacts (e.g. posttraumatic stress disorder, depression, and anxiety) [1-3]. The terror associated with war disrupts lives and relationships, leaving individuals, families, and communities distressed. Due to such immediate and long-term adverse outcomes, war represents a highly destructive and enduring public health emergency [4]. . .

Association between MTHFR C677T, MTHFR A1298C and MS A2756G polymorphisms and risk of cervical intraepithelial neoplasia II/III and cervical cancer: A meta-analysis

Numerous case-control studies on the association between polymorphisms of key genes involved in methionine remethylation [methylenetetrahydrofolate reductase (MTHFR) and methionine synthase (MS)] and the susceptibility of cervical intraepithelial neoplasia (CIN) and cervical cancer have provided inconclusive results. The aim of the present meta-analysis was to determine the effects of two MTHFR (C677T and A1298C) and one MS gene polymorphism (A2756G) on the risk of CIN II/III or cervical cancer. Relevant data were retrieved following a systematic search in PubMed, Web of Science, MEDLINE and Wanfang Data up to November 2012. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were estimated from eligible studies by meta-analysis with subgroup analyses stratified by ethnicity. A total of 13 studies with 1,936 cases and 2,858 controls were included in the present meta‑analysis. An increased risk of cervical cancer was found in Asian women with the MTHFR 677T allele (TT vs. CC: OR=1.41, 95% CI=1.07‑1.86, P=0.01; TT vs. CC+CT: OR=1.38, 95% CI=1.08-1.75, P=0.008), while a decreased risk was observed in Caucasian women (TT vs. CC: OR=0.65, 95% CI=0.45-0.93, P=0.02; TT+CT vs. CC: OR=0.7, 95% CI=0.58-0.86, P=0.0005). No effects of MTHFR C677T polymorphism on CIN II/III risk and MTHFR A1298C or MS A2756G polymorphisms on cervical cancer risk were detected. The sensitivity analysis suggested stability of this meta-analysis and no publication bias was detected. The MTHFR 677T allele may enhance the risk of cervical cancer in the Asian female population and play a protective role in Caucasian females. However, limited association is suggested between MTHFR A1298C and MS A2756G polymorphisms with cervical tumorigenesis

HPV Infection in Esophageal Squamous Cell Carcinoma and Its Relationship to the Prognosis of Patients in Northern China

Purpose. Human papillomavirus (HPV) as a risk factor for esophageal squamous cell carcinoma (ESCC) has previously been studied, but importance of HPV status in ESCC for prognosis is less clear. Methods. A total of 105 specimens with ESCC were tested by in situ hybridization for HPV 16/18 and immunohistochemistry for p16 expression. The 5-year overall survival (OS) and progression-free survival were calculated in relation to these markers and the Cox proportional hazards model was used to determine the hazard ratio (HR) of variables in univariate and multivariate analysis. Results. HPV was detected in 27.6% (29) of the 105 patients with ESCC, and all positive cases were HPV-16. Twenty-five (86.2%) of the 29 HPV-positive tumors were stained positive for p16. HPV infected patients had better 5-year rates of OS (65.9% versus 43.4% among patients with HPV-negative tumors; P = 0.002 by the log-rank test) and had a 63% reduction in the risk of death (adjusted HR = 0.37, 95% CI = 0.16 to 0.82, and P = 0.01). Conclusions. HPV infection may be one of many factors contributing to the development of ESCC and tumor HPV status is an independent prognostic factor for survival among patients with ESCC

Threshold of vapour–pressure deficit constraint on light use efficiency varied with soil water content

Understanding the constraints on light-use efficiency (LUE) induced by high evaporative water demand (vapour–pressure deficit; VPD) and soil water stress (soil moisture content; SMC) is crucial for understanding and simulating vegetation productivity, particularly in the arid and semi-arid regions. However, the relative impacts of VPD and SMC on LUE are unclear, as we lack a mechanistic understanding of impacts and their interactions. In this study, we quantified the relative roles of VPD and SMC in limiting LUE and analysed the interactions among VPD, SMC and LUE using data from CO2 and water flux stations and weather stations along a climatic gradient in the Heihe River Basin, China. We found a threshold of VPD constraint on LUE; above the threshold, LUE decreased at only 3.6% to 23.1% of the rate below the threshold. As SMC decreased, however, the VPD threshold increased, and the reduction of LUE caused by VPD decreased significantly, which is more than half of that in moister regions. Therefore, both VPD and SMC played essential roles in LUE limitation caused by water stress. A threshold also existed for heat flux and the correlation between SMC and LUE; the strength of the correlation first decreased and then increased with increasing VPD. Our results clarified the relative impacts of VPD and SMC on LUE, and can improve simulation and prediction of plant productivity