Impact of COVID-19 Lockdown on Wildlife-Vehicle Collisions in NW of Spain

ABSTRACT: Wildlife-vehicle collisions (WVCs) in many places have a significant impact on wildlife management and road safety. The COVID-19 lockdown enabled the study of the specific impact that traffic has on these events. WVC variation in the Asturias and Cantabria regions (NW of Spain) because of the COVID-19 lockdown reached a maximum reduction of -64.77% during strictconfinement but it was minimal or nonexistent during "soft" confinement. The global average value was -30.22% compared with the WVCs registered in the same period in 2019, but only -4.69% considering the average throughout the period 2010-2019. There are huge differences between conventional roads, where the traffic reduction was greater, and highways, where the traffic reduction was lesser during the COVID-19 lockdown. The results depend on the season, the day of the week and the time of day, but mainly on the traffic reduction occurring. The results obtained highlight the need to include the traffic factor in WVC reduction strategies.This research was partially funded by the Spanish Ministry of Science, Innovation and Universities (MCIU), the Spanish State Research Agency (AEI) and the European Regional Development Fund of the European Union (ERDF, EU) through the project HOFIDRAIN-MELODRAIN, Re. RTI2018-094217-B-C32, financed y MCIN/AEI/10.13039/501100011033/ERDF “A way to make Europe”

Role of Smac/DIABLO in cancer progression

Second mitochondria-derived activator of caspase/direct inhibitor of apoptosis-binding protein with low pI (Smac/DIABLO) is a proapoptogenic mitochondrial protein that is released to the cytosol in response to diverse apoptotic stimuli, including commonly used chemotherapeutic drugs. In the cytosol, Smac/DIABLO interacts and antagonizes inhibitors of apoptosis proteins (IAPs), thus allowing the activation of caspases and apoptosis. This activity has prompted the synthesis of peptidomimetics that could potentially be used in cancer therapy. For these reasons, several authors have analyzed the expression levels of Smac/DIABLO in samples of patients from different tumors. Although dissimilar results have been found, a tissue-specific role of this protein emerges from the data. The objective of this review is to present the current knowledge of the Smac/DIABLO role in cancer and its possible use as a marker or therapeutic target for drug design

Technology management to increase the efficiency of the supply chain

This article is an effort to determine the status and contribution of technology management as an integral part of the supply chain, In the present article it starts from the premise that, the technology management system is an integral part of the supply chain; To corroborate the hypothesis, a field study was carried out in the city of Barranquilla, Colombia, aimed at medium-sized service, commercial and industrial companies, in order to diagnose the management of technological processes related to identify how technological management processes related to the supply chain are carried out and Logistic processes in these organizations. One of the conclusions reached in the study is that although the majority of participating companies currently use the technology management, this is not effective, since some activities in the supply chain are outside of its scope which prevents a true control and traceability of the products and services offered by companies

Using a multidimensional unfolding approach to assess multiple sclerosis patient preferences for disease-modifying therapy: a pilot study

[EN] Purpose: Multidimensional unfolding is a multivariate method to assess preferences using a small sample size, a geometric model locating individuals and alternatives as points in a joint space. The objective was to evaluate relapsing–remitting multiple sclerosis (RRMS) patient preferences toward key disease-modifying therapy (DMT) attributes using multidimensional unfolding. Patients and methods: A cross-sectional pilot study in RRMS patients was conducted. Drug attributes included relapse prevention, disease progression prevention, side-effect risk and route and schedule of administration. Assessment of preferences was performed through a five-card game. Patients were asked to value attributes from 1 (most preferred) to 5 (least preferred). Results: A total of 37 patients were included; the mean age was 38.6 years, and 78.4% were female. Disease progression prevention was the most important factor (51.4%), followed by relapse prevention (40.5%). The frequency of administration had the lowest preference rating for 56.8% of patients. Finally, 19.6% valued the side-effect risk attribute as having low/very low importance. Conclusion: Patients’ perspective for DMT attributes may provide valuable information to facilitate shared decision-making. Efficacy attributes were the most important drug characteris-tics for RRMS patients. Multidimensional unfolding seems to be a feasible approach to assess preferences in multiple sclerosis patients. Further elicitation studies using multidimensional unfolding with other stated choice methods are necessary to confirm these findings

Análisis, desarrollo e implementación de nuevas funcionalidades para la optimización del módulo de estaciones meteorológicas remotas de la plataforma "Sistema Web de Gestión de Carreteras" (SWGC) de ITERNOVA

En este trabajo fin de grado se realizan mejoras en el módulo de estaciones meteorológicas remotas de ITERNOVA para la optimización de la captura de datos haciendo uso de API

An FPGA smart camera implementation of segmentation models for drone wildfire imagery

Wildfires represent one of the most relevant natural disasters worldwide, due to their impact on various societal and environmental levels. Thus, a significant amount of research has been carried out to investigate and apply computer vision techniques to address this problem. One of the most promising approaches for wildfire fighting is the use of drones equipped with visible and infrared cameras for the detection, monitoring, and fire spread assessment in a remote manner but in close proximity to the affected areas. However, implementing effective computer vision algorithms on board is often prohibitive since deploying full-precision deep learning models running on GPU is not a viable option, due to their high power consumption and the limited payload a drone can handle. Thus, in this work, we posit that smart cameras, based on low-power consumption field-programmable gate arrays (FPGAs), in tandem with binarized neural networks (BNNs), represent a cost-effective alternative for implementing onboard computing on the edge. Herein we present the implementation of a segmentation model applied to the Corsican Fire Database. We optimized an existing U-Net model for such a task and ported the model to an edge device (a Xilinx Ultra96-v2 FPGA). By pruning and quantizing the original model, we reduce the number of parameters by 90%. Furthermore, additional optimizations enabled us to increase the throughput of the original model from 8 frames per second (FPS) to 33.63 FPS without loss in the segmentation performance: our model obtained 0.912 in Matthews correlation coefficient (MCC),0.915 in F1 score and 0.870 in Hafiane quality index (HAF), and comparable qualitative segmentation results when contrasted to the original full-precision model. The final model was integrated into a low-cost FPGA, which was used to implement a neural network accelerator.Comment: This paper has been accepted at the 22nd Mexican International Conference on Artificial Intelligence (MICAI 2023

Fauna silvestre y accidentes de tráfico en Asturias

Los accidentes de tráfico con animales silvestres son un problema creciente en muchas partes del mundo y un importante aspecto de los conflictos entre humanos y vida silvestre con incidencia en la seguridad vial y en las poblaciones animales. En este trabajo se analizan los accidentes (n= 6 377) registrados por las autoridades de carreteras y de caza en Asturias en el periodo 2007-2014. Los resultados muestran las especies implicadas, que atañen principalmente al jabalí (sus scrofa), envuelto en el 60,36 % de los siniestros, y al corzo (Capreolus capreolus), en el 29,95 %, así como la distribución geográfica, los patrones mensuales, diarios y horarios de ocurrencia y la evolución de los siniestros, debatiéndose sus posibles causas y consecuencias. Los aspectos tratados pueden ayudar al diseño de medidas de mitigación y a la gestión de las poblaciones silvestres

Effect of pharmacological pupil dilation on measurements and iol power calculation made using the new swept-source optical coherence tomography-based optical biometer

Purpose: to determine whether pupil dilation affects biometric measurements and intraocular lens (IOL) power calculation made using the new swept-source optical coherence tomography-based optical biometer (IOLMaster 700©; Carl Zeiss Meditec, Jena, Germany). Procedures: eighty-one eyes of 81 patients evaluated for cataract surgery were prospectively examined using the IOLMaster 700© before and after pupil dilation with tropicamide 1%. The measurements made were: axial length (AL), central corneal thickness (CCT), aqueous chamber depth (ACD), lens thickness (LT), mean keratometry (MK), white-to-white distance (WTW) and pupil diameter (PD). Holladay II and SRK/T formulas were used to calculate IOL power. Agreement between measurement modes (with and without dilation) was assessed through intraclass correlation coefficients (ICC) and Bland-Altman plots. Results: mean patient age was 75.17 ± 7.54 years (range: 57–92). Of the variables determined, CCT, ACD, LT and WTW varied significantly according to pupil dilation. Excellent intraobserver correlation was observed between measurements made before and after pupil dilation. Mean IOL power calculation using the Holladay 2 and SRK/T formulas were unmodified by pupil dilation. Conclusions: the use of pupil dilation produces statistical yet not clinically significant differences in some IOLMaster 700© measurements. However, it does not affect mean IOL power calculation

Increased incidence of giant cell arteritis and associated stroke during the COVID-19 pandemic in Spain: A nation-wide population study

INTRODUCTION: SARS-CoV-2 infection and COVID-19 vaccines might have increased the incidence of giant-cell arteritis (GCA) and the risk of associated stroke in Spain. METHODS: Retrospective nation-wide observational analysis of all adults hospitalized with GCA in Spain during 5 years (Jan-2016 and Dec-2021. The incidence and proportion of admissions with or because of GCA and GCA-associated stroke were compared between pre-pandemic (2016-2019) and pandemic (2020 and 2021) years. Sensitivity analyses were conducted for the different COVID-19 waves and vaccine timing schedules. RESULTS: A total of 17,268 hospital admissions in patients diagnosed with GCA were identified. During 2020 there were 79.3 and 8.1 per 100,000 admissions of GCA and GCA-associated stroke, respectively. During 2021 these figures were 80.8 and 7.7 per 100,00 admissions, respectively. As comparison, yearly admissions due to GCA and GCA-associated stroke were 72.4 and 5.7 per 100,00, respectively, during the pre-pandemic period (p < 0.05). Coincident with the third wave of COVID-19 (and first vaccine dosing), the rate of GCA-associated stroke admissions increased significantly (from 6.6 to 12%; p < 0.001). Likewise, there was an increase in GCA-associated stroke (6.6% vs 4.1%, p = 0.016) coincident with the third dose vaccination (booster) in patients older than 70 at the end of 2021. In multivariate analysis, only patients admitted during the third COVID-19 wave (and first vaccine dosing) (OR = 1.89, 95% CI 1.22-2.93), and during the third vaccination dosing in patients older than 70 (booster) (OR = 1.66, CI 1.11-2.49), presented a higher GCA-associated stroke risk than the same months of previous years after adjustment by age, sex, classical cardiovascular risk factors and COVID-19 diagnosis. CONCLUSIONS: The COVID-19 pandemic led to an increased incidence of GCA during 2020 and 2021. Moreover, the risk of associated stroke significantly risen accompanying times of COVID-19 vaccine dosing, hypothetically linked to an increased thrombotic risk of mRNA-SARS-CoV-2 vaccines. Hence, forthcoming vaccine policies and indications must weigh the risk of severe COVID-19 with the risk of flare or stroke in patients with GCA

Incorporating Breast Asymmetry Studies into CADx Systems

Breast cancer is one of the global leading causes of death among women, and an early detection is of uttermost importance to reduce mortality rates. Screening mammograms, in which radiologists rely only on their eyesight, are one of the most used early detection methods. However, characteristics, such as the asymmetry between breasts, a feature that could be very difficult to visually quantize, is key to breast cancer detection. Due to the highly heterogeneous and deformable structure of the breast itself, incorporating asymmetry measurements into an automated detection system is still a challenge. In this study, we proposed the use of a bilateral registration algorithm as an effective way to automatically measure mirror asymmetry. Furthermore, this information was fed to a machine learning algorithm to improve the accuracy of the model. In this study, 449 subjects (197 with calcifications, 207 with masses, and 45 healthy subjects) from a public database were used to train and evaluate the proposed methodology. Using this procedure, we were able to independently identify subjects with calcifications (accuracy = 0.825, AUC = 0.882) and masses (accuracy = 0.698, AUC = 0.807) from healthy subjects