An interactive 3D virtual environment to reduce the public speaking anxiety levels of novice software engineers

Software engineering is a set of activities that relies no only on technical tasks but also requires abilities focused on social duties such as daily meetings and product introduction presentations. However, engineers may experience elevated levels of anxiety when required to present their work in an unfamiliar environment. More specifically, they may suffer from public speaking anxiety even though they are supposed to be effective in those social tasks as well as in their engineering activities. Fortunately, previous studies suggest that virtual exposure therapy is an effective strategy to reduce public speaking anxiety. In this study, an interactive 3D virtual environment similar to real classrooms and auditoriums was developed to examine if this might decrease the anxiety levels of novice software engineers. To compare traditional and virtual exposure therapy, the sample set (N = 14) was divided equally into 2 groups including one experimental group and one control group. For 4 weeks, the virtual exposure therapy was conducted in the experimental group whereas psychoeducation was used in the control group. The findings from our study illustrate that virtual exposure therapy may be represent an alternative solution to the traditional therapeutic intervention for software engineers seeking to overcome public presentation anxiet

Application of an Imaging-Based Sum Score for Cerebral Amyloid Angiopathy to the General Population: Risk of Major Neurological Diseases and Mortality

Objective: To assess the relation between a sum score of imaging markers indicative of cerebral amyloid angiopathy (CAA) and cognitive impairment, stroke, dementia, and mortality in a general population. Methods: One thousand six hundred twenty-two stroke-free and dementia-free participants of the population-based Rotterdam Study (mean age 73.1 years, 54.3% women) underwent brain MRI (1.5 tesla) in 2005–2011 and were followed for stroke, dementia and death until 2016–2017. Four MRI markers (strictly lobar cerebral microbleeds, cortical superficial siderosis, centrum semiovale perivascular spaces, and white matter hyperintensities) were combined to construct the CAA sum score, ranging from 0 to 4. Neuropsychological testing measured during the research visit closest to scan date were used to assess general cognitive function and cognitive domains. The associations of the CAA sum score with cognition cross-sectionally and with stroke, dementia, and mortality longitudinally were determined using linear regression and Cox proportional hazard modeling adjusted for age, sex, hypertension, cholesterol, lipid lowering medication, atrial fibrillation, antithrombotic medication and APOE-ε2/ε4 carriership. Additionally, we accounted for competing risks of death due to other causes for stroke and dementia, and calculated absolute risk estimates. Results: During a mean follow-up of 7.2 years, 62 participants suffered a stroke, 77 developed dementia and 298 died. Participants with a CAA score of 1 showed a lower Mini-Mental-State-Exam (fully-adjusted mean difference −0.21, 9

The coupling constant gρσγ_{\rho\sigma\gamma} as derived from QCD sum rules

We employ QCD sum rules to calculate the coupling constant g$_{\rho\sigma\gamma}$ by studying the three point ${\rho\sigma\gamma}$-correlation function. Our results is consistent with the value of this coupling constant obtained using vector meson dominance of the electromagnetic current and the experimental $\rho^0$-photoproduction data.Comment: 10 pages RevTex, 3 postscript figure

General analysis of the rare Bc->D^*_s l^+ l^- decay beyond the standard model

The general analysis of the rare Bc->D^*_s l^+ l^- decay is presented by using the most general, model independent effective Hamiltonian. The dependencies of the branching ratios, longitudinal, normal and transversal polarization asymmetries for l^- and the combined asymmetries for l^- and l^+ on the new Wilson coefficients are investigated. Our analysis shows that the lepton polarization asymmetries are very sensitive to the scalar and tensor type interactions, which will be very useful in looking for new physics beyond the standard model.Comment: 27 Pages, 14 Figure

AFBC of coal with tyre rubber. Influence of the co-combustion variables on the mineral matter of solid by-products and on Zn lixiviation

The study focuses on the generation and distribution of mineral species in fly and bottom ashes. These were formed during a fluidised co-combustion of a fossil fuel (coal) and a non-fossil fuel (tyre rubber) in a small fluidised bed combustor (7cm x 70cm). The pilot plant had continuous fuel feed using varying ratios of coal and rubber. The study also focuses on the lixiviation behaviour of metallic elements with the assessement of zinc recovering

External validation of four dementia prediction models for use in the general community-dwelling population: a comparative analysis from the Rotterdam Study

To systematically review the literature for dementia prediction models for use in the general population and externally validate their performance in a head-to-head comparison. We selected four prediction models for validation: CAIDE, BDSI, ANU-ADRI and DRS. From the Rotterdam Study, 6667 non-demented individuals aged 55 years and older were assessed between 1997 and 2001. Subsequently, participants were followed for dementia until 1 January, 2015. For each individual, we computed the risk of dementia using the reported scores from each prediction model. We used the C-statistic and calibration plots to assess the performance of each model to predict 10-year risk of all-cause dementia. For comparisons, we also evaluated discriminative accuracy using only the age component of these risk scores for each model separately. During 75,581 person-years of follow-up, 867 participants developed dementia. C-statistics for 10-year dementia risk prediction were 0.55 (95% CI 0.53–0.58) for CAIDE, 0.78 (0.76–0.81) for BDSI, 0.75 (0.74–0.77) for ANU-ADRI, and 0.81 (0.78–0.83) for DRS. Calibration plots showed that predicted risks were too extreme with underestimation at low risk and overestimation at high risk. Importantly, in all models age alone already showed nearly identical discriminative accuracy as the full model (C-statistics: 0.55 (0.53–0.58) for CAIDE, 0.81 (0.78–0.83) for BDSI, 0.77 (0.75–0.79) for ANU-ADRI, and 0.81 (0.78–0.83) for DRS). In this study, we found high variability in discriminative ability for predicting dementia in an elderly, community-dwelling population. All models showed similar discriminative ability when compared to prediction based on age alone. These findings highlight the urgent need for updated or new models to predict dementia risk in the general population

Small cell lung cancer stem cells display mesenchymal properties and exploit immune checkpoint pathways in activated cytotoxic T lymphocytes

Small cell lung cancer (SCLC) is an aggressive tumor type with early dissemination and distant metastasis capacity. Even though optimal chemotherapy responses are observed initially in many patients, therapy resistance is almost inevitable. Accordingly, SCLC has been regarded as an archetype for cancer stem cell (CSC) dynamics. To determine the immune-modulatory influence of CSC in SCLC, this study focused on the characterization of CD44(+)CD90(+) CSC-like subpopulations in SCLC. These cells displayed mesenchymal properties, differentiated into different lineages and further contributed to CD8(+) cytotoxic T lymphocytes (CTL) responses. The interaction between CD44(+)CD90(+) CSC-like cells and T cells led to the upregulation of checkpoint molecules PD-1, CTLA-4, TIM-3, and LAG3. In the patient-derived lymph nodes, CD44(+) SCLC metastases were also observed with T cells expressing PD-1, TIM-3, or LAG3. Proliferation and IFN-γ expression capacity of TIM-3 and LAG3 co-expressing CTLs are adversely affected over long-time co-culture with CD44(+)CD90(+) CSC-like cells. Moreover, especially through IFN-γ secreted by the T cells, the CSC-like SCLC cells highly expressed PD-L1 and PD-L2. Upon a second encounter with immune-experienced, IFN-γ-stimulated CSC-like SCLC cells, both cytotoxic and proliferation capacities of T cells were hampered. In conclusion, our data provide evidence for the superior potential of the SCLC cells with stem-like and mesenchymal properties to gain immune regulatory capacities and cope with cytotoxic T cell responses. With their high metastatic and immune-modulatory assets, the CSC subpopulation in SCLC may serve as a preferential target for checkpoint blockade immunotherapy

Enlarged perivascular spaces in brain MRI: Automated quantification in four regions

Enlarged perivascular spaces (PVS) are structural brain changes visible in MRI, are common in aging, and are considered a reflection of cerebral small vessel disease. As such, assessing the burden of PVS has promise as a brain imaging marker. Visual and manual scoring of PVS is a tedious and observer-dependent task. Automated methods would advance research into the etiology of PVS, could aid to assess what a “normal” burden is in aging, and could evaluate the potential of PVS as a biomarker of cerebral small vessel disease. In this work, we propose and evaluate an automated method to quantify PVS in the midbrain, hippocampi, basal ganglia and centrum semiovale. We also compare associations between (earlier established) determinants of PVS and visual PVS scores versus the automated PVS scores, to verify whether automated PVS scores could replace visual scoring of PVS in epidemiological and clinical studies. Our approach is a deep learning algorithm based on convolutional neural network regression, and is contingent on successful brain structure segmentation. In our work we used FreeSurfer segmentations. We trained and validated our method on T2-contrast MR images acquired from 2115 subjects participating in a population-based study. These scans were visually scored by an expert rater, who counted the number of PVS in each brain region. Agreement between visual and automated scores was found to be excellent for all four regions, with intraclass correlation coefficients (ICCs) between 0.75 and 0.88. These values were higher than the inter-observer agreement of visual scoring (ICCs between 0.62 and 0.80). Scan-rescan reproducibility was high (ICCs between 0.82 and 0.93). The association between 20 determinants of PVS, including aging, and the automated scores were similar to those between th

Recent inventions in additive manufacturing: holistic review

This general review paper presents a condensed view of recent inventions in the Additive Manufacturing (AM) field. It outlines factors affecting the development and commercialization of inventions via research collaboration and discusses breakthroughs in materials and AM technologies and their integration with emerging technologies. The paper explores the impact of AM across various sectors, including the aerospace, automotive, healthcare, food, and construction industries, since the 1970s. It also addresses challenges and future directions, such as hybrid manufacturing and bio-printing, along with socio-economic and environmental implications. This collaborative study provides a concise understanding of the latest inventions in AM, offering valuable insights for researchers, practitioners, and decision makers in diverse industries and institutions