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Abstract Continuous‐flow intersections (CFI), also known as displaced left‐turn (DLT) intersections, aim to improve the efficiency and safety of traffic junctions. A CFI introduces additional cross‐over intersections upstream of the main intersection to split the left‐turn flow from the through movement before it arrives at the main intersection which decreases the number of conflict points between left‐turn and through movements. This study develops and examine a two‐step optimization model for CFI traffic signal control design and demonstrates its performance across more than 300 different travel demand scenarios. The proposed model is compared against a state‐of‐practice CFI signal control model as a benchmark. Microsimulation results suggest that the proposed model reduces average delay by 17% and average queue length by 32% for a full CFI compared with the benchmark signal control model.

Introduction SUV measurements from static brain [18F]FDG PET acquisitions are a commonly used tool in preclinical research, providing a simple alternative for kinetic modelling, which requires complex and time-consuming dynamic acquisitions. However, SUV can be severely affected by the animal handling and preconditioning protocols, primarily by those that may induce changes in blood glucose levels (BGL). Here, we aimed at developing and investigating the feasibility of SUV-based approaches for a wide range of BGL far beyond normal values, and consequently, to develop and validate a new model to generate standardized and reproducible SUV measurements for any BGL.Material and methods We performed dynamic and static brain [18F]FDG PET acquisitions in 52 male Sprague-Dawley rats sorted into control (n = 10), non-fasting (n = 14), insulin-induced hypoglycemia (n = 12) and glucagon-induced hyperglycemia (n = 16) groups. Brain [18F]FDG PET images were cropped, aligned and co-registered to a standard template to calculate whole-brain and regional SUV. Cerebral Metabolic Rate of Glucose (CMRglc) was also estimated from 2-Tissue Compartment Model (2TCM) and Patlak plot for validation purposes.Results Our results showed that BGL=100±6 mg/dL can be considered a reproducible reference value for normoglycemia. Furthermore, we successfully established a 2nd-degree polynomial model (C1=0.66E-4, C2=-0.0408 and C3=7.298) relying exclusively on BGL measures at pre-[18F]FDG injection time, that characterizes more precisely the relationship between SUV and BGL for a wide range of BGL values (from 10 to 338 mg/dL). We confirmed the ability of this model to generate corrected SUV estimations that are highly correlated to CMRglc estimations (R2= 0.54 2TCM CMRgluc and R2= 0.49 Patlak CMRgluc). Besides, slight regional differences in SUV were found in animals from extreme BGL groups, showing that [18F]FDG uptake is mostly directed toward central regions of the brain when BGLs are significantly decreased.Conclusion Our study successfully established a non-linear model that relies exclusively on pre-scan BGL measurements to characterize the relationship between [18F]FDG SUV and BGL. The extensive validation confirmed its ability to generate SUV-based surrogates of CMRglu along a wide range of BGL and it holds the potential to be adopted as a standard protocol by the preclinical neuroimaging community using brain [18F]FDG PET imaging.

El conocimiento detallado de aquellos factores que presentan mayor relevancia en la probabilidad de venta de las viviendas puede resultar de suma importancia al tratarse de una inversión a largo plazo. Tras identificar una serie de bloques que marcan la evolución de la venta de las mismas (las características internas del inmueble en cuestión, su localización, su grado de sobreprecio y, sobre todo, un interés real por parte del comprador), se presenta un estudio novedoso que modeliza la probabilidad de venta de los inmuebles a lo largo del tiempo mediante técnicas de machine learning aplicadas a problemas de supervivencia, logrando valores de C-index de 76% y 72% en chalés y pisos, respectivamente. El proceso metodológico se ha testado sobre la capital de España, Madrid, a partir de los datos recopilados desde la principal plataforma de mercado del país durante el periodo 2018-2019. Estos datos fueron ponderados según información oficial, pero la metodología es escalable a cualquier municipio. No solo vendedores, compradores o intermediarios pueden verse beneficiados con este aporte, sino también los agentes públicos, de cara a tomar decisiones enfocadas al diseño o prevención en el tema de la vivienda.

Abstract In this paper we explore the temporal dynamics of spatial inequality in housing prices for Madrid, the capital city of Spain. Spatial inequalities are a concerning feature of urban areas across the globe. It has been suggested that within cities housing prices are becoming more geographically unequal over time, particularly since the 2008 housing market crash. However, more evidence is needed at the intra-urban level to understand neighbourhood house price differences in large urban areas. Changes are analysed during a key period of the housing market bust (2010–2015) and boom (2016–2019), using data from a major housing listing portal. Fine grain space-time analysis of the distribution of housing prices supports an increase in spatial inequality and polarisation at the neighbourhood level. Two spatially differentiated housing sub-markets of high- and low-priced housing are identified. The persistence and growth of spatial house price inequality has important societal implications for the wealth gap and segregation of rich and poor in cities.

Background: This study aimed to compare the humoral responses to mRNA COVID-19 vaccination in people living with HIV (PWH) and HIV-negative individuals. Methods: We included PWH with an undetectable viral load under ART and HIV-negative participants from the French nationwide ANRS COV-POPART cohort who had received two doses of vaccine as a primary vaccination. We compared humoral response between controls and PWH, stratified by CD4 cell count (

Background: Throughout HIV infection, productively infected cells generate billions of viral particles and are thus responsible for body-wide HIV dissemination, but their phenotype during AIDS is unknown. As AIDS is associated with immunological changes, analyzing the phenotype of productively infected cells can help understand HIV production during this terminal stage. Methods: Blood samples from 15 untreated viremic participants (recent infection, n=5; long-term infection, n=5; active opportunistic AIDS-defining disease, n=5) and 5 participants virologically controlled on antiretroviral therapy (ART) enrolled in the Analysis of the Persistence, Reservoir and HIV Latency (APRIL) study (NCT05752318) were analyzed. Cells expressing the capsid protein p24 (p24+ cells) after 18 hours of resting or 24 hours of stimulation (HIV-Flow) revealed productively infected cells from viremic participants or translation-competent reservoir cells from treated participants, respectively. Results: The frequency of productively infected cells tended to be higher during AIDS in comparison with recent and long-term infections (median, 340, 72, and 32/million CD4+ T cells, respectively) and correlated with the plasma viral load at all stages of infection. Altogether, these cells were more frequently CD4low, HLA-ABClow, CD45RA-, Ki67+, PD-1+, with a non-negligible contribution from pTfh (CXCR5+PD-1+) cells, and were not significantly enriched in HIV coreceptors CCR5 nor CXCR4 expression. The comparison markers expression between stages showed that productively infected cells during AIDS were enriched in memory and exhausted cells. In contrast, the frequencies of infected pTfh were lower during AIDS compared to non-AIDS stages. A UMAP analysis revealed that total CD4+ T cells were grouped in 7 clusters and that productive p24+ cells were skewed to given clusters throughout the course of infection. Overall, the preferential targets of HIV during the latest stages seemed to be more frequently highly differentiated (memory, TTD-like) and exhausted cells and less frequently pTfh-like cells. In contrast, translation-competent reservoir cells were less frequent (5/million CD4+ T cells) and expressed more frequently HLA-ABC and less frequently PD-1. Conclusions: In long-term infection and AIDS, productively infected cells were differentiated and exhausted. This could indicate that cells with these given features are responsible for HIV production and dissemination in an immune dysfunction environment occurring during the last stages of infection.

IntroductionClinical research has focused on risk factors and treatment for severe acute respiratory syndrome coronavirus 2 (SARS-COV-2), particularly in people with a comorbidity including the human immunodeficiency virus (HIV), but little attention has been paid to the care pathway. This article aims to show how living with HIV may have been a biopsychosocial burden or boost in care pathways for Covid-19.MethodPeople living with HIV (PLHIV) from 9 clinical centers were invited to participate in this qualitative study. The sampling was purposive with a maximum variation in their sociodemographic profiles. Semi-structured interviews were conducted until data saturation, then coded for thematic analysis, using an inductive general approach.ResultsWe interviewed 34 PLHIV of which 20 had SARS-COV-2 once. They were 24 males, 26 born in France; median age: 55. Twenty had a CD4 number above 500, and all were on antiretroviral therapy (ART). HIV appeared as a burden when Covid-19 symptoms reminded HIV seroconversion, fear of contamination, and triggered questions about ART effectiveness. HIV was not considered relevant when diagnosing Covid-19, caused fear of disclosure when participants sought SARS-COV-2 testing, and its care in hospitals was disrupted by the pandemic. ART-pill fatigue caused avoidance for Covid-19 treatment. As a boost, living with HIV led participants to observe symptoms, to get advice from healthcare professionals, and screening access through them. Some participants could accept the result of screening or a clinical diagnosis out of resilience. Some could consider ART or another drug prescribed by their HIV specialist help them to recover from Covid-19.ConclusionLiving with HIV could function as a burden and/or a boost in the care pathways for Covid-19, according to patients' relationship to their HIV history, comorbidities and representation of ART. Covid-19 in PLHIV needs further qualitative study to gain a more comprehensive assessment of the pandemic's consequences on their lives and coping strategies.

RESUMEN El objetivo del estudio fue estimar la prevalencia de lesiones sospechosas de maltrato infantil (MI) en clínicas de Odontopediatría de una Universidad Pública Colombiana. Estudio descriptivo en 100 binomios padres-niños de 6 a 9 años y estudiantes de Odontología. Se diseñó y aplicó cuestionario indagando variables sociodemográficas, sospecha general de MI y se evaluó clínicamente sospecha de MI según lesiones orofaciales. Se realizó estadística descriptiva y análisis bivariado utilizando prueba X2. Los resultados muestran prevalencia de sospecha general de MI del 12 % y sospecha de MI según lesiones orofaciales del 24 %; la lesión extraoral e intraoral más prevalente fue la laceración (10%). Se hallaron relaciones significantes entre sospecha general de MI con desgarro del frenillo labial, múltiples cicatrices, quemaduras sugestivas de MI, marcas de mordidas, contusiones y laceración en labios (p

Clustering algorithms have proven to be a useful tool to extract knowledge and support decision making by processing large volumes of data. Hard and fuzzy clustering algorithms have been used successfully to identify patterns and trends in many areas, such as finance, healthcare, and marketing. However, these algorithms significantly increase their solution time as the size of the datasets to be solved increase, making their use unfeasible. In this sense, the parallel processing of algorithms has proven to be an efficient alternative to reduce their solution time. It has been established that the parallel implementation of algorithms requires its redesign to optimise the hardware resources of the platform that will be used. In this article, we propose a new parallel implementation of the Hybrid OK-Means Fuzzy C-Means (HOFCM) algorithm, which is an efficient variant of Fuzzy C-Means, in OpenMP. An advantage of using OpenMP is its scalability. The efficiency of the implementation is compared against the HOFCM algorithm. The experimental results of processing large real and synthetic datasets show that our implementation tends to more efficiently solve instances with a large number of clusters and dimensions. Additionally, the implementation shows excellent results concerning speedup and parallel efficiency metrics. Our main contribution is a Fuzzy clustering algorithm for large datasets that is scalable and not limited to a specific domain.

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