Associations between Western and Mediterranean-type dietary patterns and anxiety and stress

In this study we investigated the relationship between dietary patterns and anxiety and stress in adults living in Shiraz, Iran. In a cross-sectional design, 416 subjects (180 men and 236 women) aged 20 to 50 years were selected by stratified multistage random sampling. Dietary intakes were assessed using a semi-quantitative food frequency questionnaire (FFQ). Mental health information was collected by depression, anxiety and stress scale (DASS) questionnaire. Three major dietary patterns were extracted by factor analysis: vegetable, Western, and Mediterraneantype dietary patterns. Regression analysis showed a strong positive association between Western dietary pattern and anxiety (β=0.66; 95% CI: 0.03, 1.28), and stress (β=0.84; 95% CI: 0.1, 1.57). Also, there was an inverse association between Mediterranean-type dietary pattern and anxiety (β= ‒0.81; 95% CI: ‒1.43, ‒0.19). These associations remained statistically significant even after adjustments for demographic characteristics, physical activity, smoking, body mass index, and energy intake. No association was found between vegetable dietary pattern and any of the assessed psychiatric disorders

Exploring Users' Pointing Performance on Virtual and Physical Large Curved Displays

Large curved displays have emerged as a powerful platform for collaboration, data visualization, and entertainment. These displays provide highly immersive experiences, a wider field of view, and higher satisfaction levels. Yet, large curved displays are not commonly available due to their high costs. With the recent advancement of Head Mounted Displays (HMDs), large curved displays can be simulated in Virtual Reality (VR) with minimal cost and space requirements. However, to consider the virtual display as an alternative to the physical display, it is necessary to uncover user performance differences (e.g., pointing speed and accuracy) between these two platforms. In this paper, we explored users' pointing performance on both physical and virtual large curved displays. Specifically, with two studies, we investigate users' performance between the two platforms for standard pointing factors such as target width, target amplitude as well as users' position relative to the screen. Results from user studies reveal no significant difference in pointing performance between the two platforms when users are located at the same position relative to the screen. In addition, we observe users' pointing performance improves when they are located at the center of a semi-circular display compared to off-centered positions. We conclude by outlining design implications for pointing on large curved virtual displays. These findings show that large curved virtual displays are a viable alternative to physical displays for pointing tasks.Comment: In 29th ACM Symposium on Virtual Reality Software and Technology (VRST 2023

Exploring Users Pointing Performance on Large Displays with Different Curvatures in Virtual Reality

Large curved displays inside Virtual Reality environments are becoming popular for visualizing high-resolution content during analytical tasks, gaming or entertainment. Prior research showed that such displays provide a wide field of view and offer users a high level of immersion. However, little is known about users' performance (e.g., pointing speed and accuracy) on them. We explore users' pointing performance on large virtual curved displays. We investigate standard pointing factors (e.g., target width and amplitude) in combination with relevant curve-related factors, namely display curvature and both linear and angular measures. Our results show that the less curved the display, the higher the performance, i.e., faster movement time. This result holds for pointing tasks controlled via their visual properties (linear widths and amplitudes) or their motor properties (angular widths and amplitudes). Additionally, display curvatures significantly affect the error rate for both linear and angular conditions. Furthermore, we observe that curved displays perform better or similar to flat displays based on throughput analysis. Finally, we discuss our results and provide suggestions regarding pointing tasks on large curved displays in VR.Comment: IEEE Transactions on Visualization and Computer Graphics (2023

Biochar from Pine Wood, Rice Husks and Iron-Eupatorium Shrubs for Remediation Applications: Surface Characterization and Experimental Tests for Trichloroethylene Removal

Nowadays porous materials from organic waste, i.e., Biochar (BC), are receiving increased attention for environmental applications. This study adds information on three BCs that have undergone a number of studies in recent years. A Biochar from pine wood, one from rice husk and one from Eupatorium shrubs enriched with Iron, labelled as PWBC, RHBC and EuFeBC respectively, are evaluated for Trichloroethylene (TCE) removal from aqueous solution. Physical-chemical description is performed by SEM-EDS and BET analysis. The decrease of TCE over time follows a pseudo-second order kinetics with increased removal by the PWBC. Freundlich and Langmuir models well fit equilibrium test data. The optimized values of the maximum adsorbed amount, qmax (mg g−1), follows this order 109.41 PWBC > 30.35 EuFeBC > 21.00 RHBC. Fixed-bed columns are also carried out. Best performance is again achieved by PWBC, which operates for a higher number of pore volume, followed by EuFeBC and RHBC. Continuous testing confirms batch studies and makes it possible to evaluate the workability of materials in configurations closer to reality. Results are promising for potential environmental application. In particular, the characterization of several classes of contaminants opens the doors to possible uses in mixed contamination case

Study Protocol: A Randomized Controlled Trial of Patient Navigation-Activation to Reduce Cancer Health Disparities

Abstract Background Cancer health disparities affecting low-income and minority patients are well documented. Root-causes are multifactorial, including diagnostic and treatment delays, social and financial barriers, and poor communication. Patient navigation and communication coaching (activation) are potential interventions to address disparities in cancer treatment. The purpose of this clinical trial is to test the effectiveness of an intervention combining patient navigation and activation to improve cancer treatment. Methods/Design The Rochester Patient Navigation Research Program (PNRP) is a National Cancer Institute-sponsored, patient-level randomized trial (RCT) of patient navigation and activation, targeting newly-diagnosed breast and colorectal cancer patients in Rochester, NY. The goal of the program is to decrease cancer health disparities by addressing barriers to receipt of cancer care and promoting patient self-efficacy. The intervention uses trained, paraprofessional patient navigators recruited from the target community, and a detailed training and supervisory program. Recruited patients are randomly assigned to receive either usual care (except for baseline and follow-up questionnaires and interviews) or intervention. The intervention patients receive tailored assistance from their patient navigators, including phone calls, in-person meetings, and behind-the-scenes coordination of care. A total of 344 patients have been recruited. Outcomes measured at three month intervals include timeliness of care, patient adherence, patient satisfaction, quality of life, self-efficacy, health literacy, and cancer knowledge. Discussion This unique intervention combining patient navigation and patient activation is designed to address the multifactorial problem of cancer health disparities. If successful, this study will affect the design and implementation of patient navigation programs. Trials Registration clinicaltrials.gov identifier NCT00496678http://deepblue.lib.umich.edu/bitstream/2027.42/78254/1/1471-2407-10-551.xmlhttp://deepblue.lib.umich.edu/bitstream/2027.42/78254/2/1471-2407-10-551.pdfPeer Reviewe

Combining Machine Learning Classifiers for Stock Trading with Effective Feature Extraction

The unpredictability and volatility of the stock market render it challenging to make a substantial profit using any generalized scheme. This paper intends to discuss our machine learning model, which can make a significant amount of profit in the US stock market by performing live trading in the Quantopian platform while using resources free of cost. Our top approach was to use ensemble learning with four classifiers: Gaussian Naive Bayes, Decision Tree, Logistic Regression with L1 regularization and Stochastic Gradient Descent, to decide whether to go long or short on a particular stock. Our best model performed daily trade between July 2011 and January 2019, generating 54.35% profit. Finally, our work showcased that mixtures of weighted classifiers perform better than any individual predictor about making trading decisions in the stock market

The effects of aerobic, resistance, and combined exercises on the plasma irisin levels, HOMA-IR, and lipid profiles in women with metabolic syndrome: A randomized controlled trial

Background/objective: Irisin is suggested to be an exercise beneficial effects mediator. This study aimed to examine the effects of the aerobic exercise (AE), resistance exercise (RE), and combined exercise (CE) on the plasma levels of irisin and some metabolic and anthropometric indices. Methods: Sixty overweight women with metabolic syndrome were assigned equally into four groups: AE, RE, CE, and control. The study variables were measured before and 24 h after the intervention period. Results: None of the study groups showed statistically significant changes in the serum irisin. However, muscle mass significantly increased in the RE and CE groups. Also, a significant decrease was observed in the body fat percentage in all groups. In addition, compared with the control group, the homeostatic model assessment of insulin resistance in the AE (p = 0.021), RE (p = 0.039), and in the CE (p = 0.003) groups reduced significantly. According to the analysis of indices� changes, serum irisin was significantly correlated with the body fat percentage (r = 0.532) and HOMA-IR (r = 0.424). Conclusions: The systematic exercise program for 8-weeks did not change circulating irisin and no statistically significant difference was observed between the exercise methods. Also, serum irisin seemed to be associated with the glycemic status, body fat and weight independent of exercise activity. RCT registration code: IRCT20180806040721N2. Registry name: Iranian Registry of Clinical Trials. © 2020 The Society of Chinese Scholars on Exercise Physiology and Fitnes

Seizure as the early and main manifestation of infantile vanishing white matter disease: A case report

Introduction: Vanishing white matter disease (VWM) is considered as one of the most frequent types of inherited childhood leukoencephalopathies. Various neurological and non-neurological manifestations have been reported in this type of leukodystrophy; however, seizures are rarely described in infantile type of VWM. Case Presentation: To patient is a 12 months old boy who experienced frequent seizures at 4th month of age. The seizures were resistant to anti-epileptic drugs and caused 3 periods of hospitalization. Magnetic resonance imaging (MRI) demonstrated demyeli-nating pattern and whole exome sequencing (WES) reported homozygous mutation (c.922G > A) in EIF2B2 gene in exon 8 leading to an amino-acid substitution (p.Val308Met). Conclusions: Infantile onset of vanishing white matter disease can be considered as one of few childhood leukodystrophies that are associated with early onset seizures. © 2018, Iranian Journal of Pediatrics

Burden of rare variants in synaptic genes in patients with severe tinnitus: An exome based extreme phenotype study

Background: tinnitus is a heterogeneous condition associated with audiological and/or mental disorders. Chronic, severe tinnitus is reported in 1% of the population and it shows a relevant heritability, according to twins, adoptees and familial aggregation studies. The genetic contribution to severe tinnitus is unknown since large genomic studies include individuals with self-reported tinnitus and large heterogeneity in the phenotype. The aim of this study was to identify genes for severe tinnitus in patients with extreme phenotype. Methods: for this extreme phenotype study, we used three different cohorts with European ancestry (Spanish with Meniere disease (MD), Swedes tinnitus and European generalized epilepsy). In addition, four independent control datasets were also used for comparisons. Whole-exome sequencing was performed for the MD and epilepsy cohorts and whole-genome sequencing was carried out in Swedes with tinnitus. Findings: we found an enrichment of rare missense variants in 24 synaptic genes in a Spanish cohort, the most significant being PRUNE2, AKAP9, SORBS1, ITGAX, ANK2, KIF20B and TSC2 (p < 2E 04), when they were compared with reference datasets. This burden was replicated for ANK2 gene in a Swedish cohort with 97 tinnitus individuals, and in a subset of 34 Swedish patients with severe tinnitus for ANK2, AKAP9 and TSC2 genes (p < 2E 02). However, these associations were not significant in a third cohort of 701 generalized epilepsy individuals without tinnitus. Gene ontology (GO) and gene-set enrichment analyses revealed several pathways and biological processes involved in severe tinnitus, including membrane trafficking and cytoskeletal protein binding in neurons. Interpretation: a burden of rare variants in ANK2, AKAP9 and TSC2 is associated with severe tinnitus. ANK2, encodes a cytoskeleton scaffolding protein that coordinates the assembly of several proteins, drives axonal branching and influences connectivity in neurons