Cultural modulation effects on the Self-Face Advantage: Do Caucasians find their own faces faster than Chinese?

The self-face advantage (SFA) is reflected through a faster recognition of a self-face compared to familiar and unfamiliar faces. Nevertheless, as Westerners and East Asians tend to present differences in self-concept styles, it is possible that the SFA is modulated by culture. The present study explored this possibility using a visual search task. British Caucasians and Malaysian Chinese participants were asked to search for frontal view images of self, friend, and unfamiliar faces among an array of unfamiliar faces. Regardless of race, participants were more accurate and faster in searching for the own face and friend's face compared to an unfamiliar face, with no differences in the search between the own and friend's face, and these findings could not be accounted by the cultural differences in self-concept (i.e., operationalized by SCS and HCIV scores). Altogether our results suggest that culture does not modulate the SFA and that this effect is better explained by a familiar face advantage

Spectral characteristics of side face excited microstructured fibers for photonic integrated circuits formations

We propose a new method for mass production of the photonic crystal devices on the basis of widely-known and well-developed technology such as microstructured optical fibers. In this paper, we investigate the optical properties of side-excited microstructured optical fiber and discuss the conditions for utilization such a structure as a planar photonic crystal device, namely, the high-quality resonance filter.Comment: 7 pages, 7 figure

Non-local parabolic and hyperbolic models for cell polarisation in heterogeneous cancer cell populations

Tumours consist of heterogeneous populations of cells. The subpopulations can have different features, including cell motility, proliferation and metastatic potential. The interactions between clonal sub-populations are complex, from stable coexistence to dominant behaviours. The cell-cell interactions, i.e., attraction, repulsion and alignment, processes critical in cancer invasion and metastasis, can be influenced by the mutation of cancer cells. In this study, we develop a mathematical model describing cancer cell invasion and movement for two polarised cancer cell populations with different levels of mutation. We consider a system of non-local hyperbolic equations that incorporate cell-cell interactions in the speed and the turning behaviour of cancer cells, and take a formal parabolic limit to transform this model into a non-local parabolic model. We then investigate the possibility of aggregations to form, and perform numerical simulations for both hyperbolic and parabolic models, comparing the patterns obtained for these models

Machine Learning in Melanoma Diagnosis. Limitations About to be Overcome

[spa] Antecedentes: La clasificación automática de imágenes es una rama prometedora del aprendi-zaje automático (de sus siglas en inglés Machine Learning [ML]), y es una herramienta útil enel diagnóstico de cáncer de piel. Sin embargo, poco se ha estudiado acerca de las limitacionesde su uso en la práctica clínica diaria.Objetivo: Determinar las limitaciones que existen en cuanto a la selección de imágenes usadaspara el análisis por ML de las neoplasias cutáneas, en particular del melanoma.Métodos: Se dise ̃nó un estudio de cohorte retrospectivo, donde se incluyeron de forma conse-cutiva 2.849 imágenes dermatoscópicas de alta calidad de tumores cutáneos para su valoraciónpor un sistema de ML, recogidas entre los a ̃nos 2010 y 2014. Cada imagen dermatoscópica fueclasificada según las características de elegibilidad para el análisis por ML.Resultados: De las 2.849 imágenes elegidas a partir de nuestra base de datos, 968 (34%) cum-plieron los criterios de inclusión. De los 528 melanomas, 335 (63,4%) fueron excluidos. Laausencia de piel normal circundante (40,5% de todos los melanomas de nuestra base de datos)y la ausencia de pigmentación (14,2%) fueron las causas más frecuentes de exclusión para elanálisis por ML.Discusión: Solo el 36,6% de nuestros melanomas se consideraron aceptables para el análisispor sistemas de ML de última generación. Concluimos que los futuros sistemas de ML deberánser entrenados a partir de bases de datos más grandes que incluyan imágenes representativasde la práctica clínica habitual. Afortunadamente, muchas de estas limitaciones están siendosuperadas gracias a los avances realizados recientemente por la comunidad científica, como seha demostrado en trabajos recientes. [eng] Background: Automated image classification is a promising branch of machine learning (ML)useful for skin cancer diagnosis, but little has been determined about its limitations for generalusability in current clinical practice.Objective: To determine limitations in the selection of skin cancer images for ML analysis,particularly in melanoma.Methods: Retrospective cohort study design, including 2,849 consecutive high-quality dermos-copy images of skin tumors from 2010 to 2014, for evaluation by a ML system. Each dermoscopyimage was assorted according to its eligibility for ML analysis.Results: Of the 2,849 images chosen from our database, 968 (34%) met the inclusion criteriafor analysis by the ML system. Only 64.7% of nevi and 36.6% of melanoma met the inclusioncriteria. Of the 528 melanomas, 335 (63.4%) were excluded. An absence of normal surroundingskin (40.5% of all melanomas from our database) and absence of pigmentation (14.2%) were themost common reasons for exclusion from ML analysis.Discussion: Only 36.6% of our melanomas were admissible for analysis by state-of-the-art MLsystems. We conclude that future ML systems should be trained on larger datasets which includerelevant non-ideal images from lesions evaluated in real clinical practice. Fortunately, many ofthese limitations are being overcome by the scientific community as recent works show

The Effect of Macular Hole Duration on Surgical Outcomes: An Individual Participant Data Study of Randomized Controlled Trials

Topic: To define the effect of symptom duration on outcomes in people undergoing surgery for idiopathic full-thickness macular holes (iFTMHs) by means of an individual participant data (IPD) study of randomized controlled trials (RCTs). The outcomes assessed were primary iFTMH closure and postoperative best-corrected visual acuity (BCVA). Clinical Relevance: Idiopathic full-thickness macular holes are visually disabling with a prevalence of up to 0.5%. Untreated BCVA is typically reduced to 20/200. Surgery can close holes and improve vision. Symptom duration is thought to affect outcomes with surgery, but the effect is unclear. Methods: A systematic review identified eligible RCTs that included adults with iFTMH undergoing vitrectomy with gas tamponade in which symptom duration, primary iFTMH closure, and postoperative BCVA were recorded. Bibliographic databases were searched for articles published between 2000 and 2020. Individual participant data were requested from eligible studies. Results: Twenty eligible RCTs were identified. Data were requested from all studies and obtained from 12, representing 940 eyes in total. Median symptom duration was 6 months (interquartile range, 3–10). Primary closure was achieved in 81.5% of eyes. There was a linear relationship between predicted probability of closure and symptom duration. Multilevel logistic regression showed each additional month of duration was associated with 0.965 times lower odds of closure (95% confidence interval [CI], 0.935–0.996, P = 0.026). Internal limiting membrane (ILM) peeling, ILM flap use, better preoperative BCVA, face-down positioning, and smaller iFTMH size were associated with increased odds of primary closure. Median postoperative BCVA in eyes achieving primary closure was 0.48 logarithm of the minimum angle of resolution (logMAR) (20/60). Multilevel logistic regression showed for eyes achieving primary iFTMH closure, each additional month of symptom duration was associated with worsening BCVA by 0.008 logMAR units (95% CI, 0.005–0.011, P < 0.001) (i.e., ∼1 Early Treatment Diabetic Retinopathy Study letter loss per 2 months). ILM flaps, intraocular tamponade using long-acting gas, better preoperative BCVA, smaller iFTMH size, and phakic status were also associated with improved postoperative BCVA. Conclusions: Symptom duration was independently associated with both anatomic and visual outcomes in persons undergoing surgery for iFTMH. Time to surgery should be minimized and care pathways designed to enable this

Data from an International Multi-Centre Study of Statistics and Mathematics Anxieties and Related Variables in University Students (the SMARVUS Dataset)

This large, international dataset contains survey responses from N = 12,570 students from 100 universities in 35 countries, collected in 21 languages. We measured anxieties (statistics, mathematics, test, trait, social interaction, performance, creativity, intolerance of uncertainty, and fear of negative evaluation), self-efficacy, persistence, and the cognitive reflection test, and collected demographics, previous mathematics grades, self-reported and official statistics grades, and statistics module details. Data reuse potential is broad, including testing links between anxieties and statistics/mathematics education factors, and examining instruments’ psychometric properties across different languages and contexts. Data and metadata are stored on the Open Science Framework website [https://osf.io/mhg94/]

Evaluation of a quality improvement intervention to reduce anastomotic leak following right colectomy (EAGLE): pragmatic, batched stepped-wedge, cluster-randomized trial in 64 countries

Background: Anastomotic leak affects 8 per cent of patients after right colectomy with a 10-fold increased risk of postoperative death. The EAGLE study aimed to develop and test whether an international, standardized quality improvement intervention could reduce anastomotic leaks. Methods: The internationally intended protocol, iteratively co-developed by a multistage Delphi process, comprised an online educational module introducing risk stratification, an intraoperative checklist, and harmonized surgical techniques. Clusters (hospital teams) were randomized to one of three arms with varied sequences of intervention/data collection by a derived stepped-wedge batch design (at least 18 hospital teams per batch). Patients were blinded to the study allocation. Low- and middle-income country enrolment was encouraged. The primary outcome (assessed by intention to treat) was anastomotic leak rate, and subgroup analyses by module completion (at least 80 per cent of surgeons, high engagement; less than 50 per cent, low engagement) were preplanned. Results: A total 355 hospital teams registered, with 332 from 64 countries (39.2 per cent low and middle income) included in the final analysis. The online modules were completed by half of the surgeons (2143 of 4411). The primary analysis included 3039 of the 3268 patients recruited (206 patients had no anastomosis and 23 were lost to follow-up), with anastomotic leaks arising before and after the intervention in 10.1 and 9.6 per cent respectively (adjusted OR 0.87, 95 per cent c.i. 0.59 to 1.30; P = 0.498). The proportion of surgeons completing the educational modules was an influence: the leak rate decreased from 12.2 per cent (61 of 500) before intervention to 5.1 per cent (24 of 473) after intervention in high-engagement centres (adjusted OR 0.36, 0.20 to 0.64; P &lt; 0.001), but this was not observed in low-engagement hospitals (8.3 per cent (59 of 714) and 13.8 per cent (61 of 443) respectively; adjusted OR 2.09, 1.31 to 3.31). Conclusion: Completion of globally available digital training by engaged teams can alter anastomotic leak rates. Registration number: NCT04270721 (http://www.clinicaltrials.gov)

Data from an International Multi-Centre Study of Statistics and Mathematics Anxieties and Related Variables in University Students (the SMARVUS Dataset)

This large, international dataset contains survey responses from N = 12,570 students from 100 universities in 35 countries, collected in 21 languages. We measured anxieties (statistics, mathematics, test, trait, social interaction, performance, creativity, intolerance of uncertainty, and fear of negative evaluation), self-efficacy, persistence, and the cognitive reflection test, and collected demographics, previous mathematics grades, self-reported and official statistics grades, and statistics module details. Data reuse potential is broad, including testing links between anxieties and statistics/mathematics education factors, and examining instruments’ psychometric properties across different languages and contexts