CrimeNet: Neural Structured Learning using Vision Transformer for violence detection

The state of the art in violence detection in videos has improved in recent years thanks to deep learning models, but it is still below 90% of average precision in the most complex datasets, which may pose a problem of frequent false alarms in video surveillance environments and may cause security guards to disable the artificial intelligence system. In this study, we propose a new neural network based on Vision Transformer (ViT) and Neural Structured Learning (NSL) with adversarial training. This network, called CrimeNet, outperforms previous works by a large margin and reduces practically to zero the false positives. Our tests on the four most challenging violence-related datasets (binary and multi-class) show the effectiveness of CrimeNet, improving the state of the art from 9.4 to 22.17 percentage points in ROC AUC depending on the dataset. In addition, we present a generalisation study on our model by training and testing it on different datasets. The obtained results show that CrimeNet improves over competing methods with a gain of between 12.39 and 25.22 percentage points, showing remarkable robustness.MCIN/AEI/ 10.13039/501100011033 and by the “European Union NextGenerationEU/PRTR ” HORUS project - Grant n. PID2021-126359OB-I0

Real-time gun detection in CCTV: An open problem

Object detectors have improved in recent years, obtaining better results and faster inference time. However, small object detection is still a problem that has not yet a definitive solution. The autonomous weapons detection on Closed-circuit television (CCTV) has been studied recently, being extremely useful in the field of security, counter-terrorism, and risk mitigation. This article presents a new dataset obtained from a real CCTV installed in a university and the generation of synthetic images, to which Faster R-CNN was applied using Feature Pyramid Network with ResNet-50 resulting in a weapon detection model able to be used in quasi real-time CCTV (90 ms of inference time with an NVIDIA GeForce GTX-1080Ti card) improving the state of the art on weapon detection in a two stages training. In this work, an exhaustive experimental study of the detector with these datasets was performed, showing the impact of synthetic datasets on the training of weapons detection systems, as well as the main limitations that these systems present nowadays. The generated synthetic dataset and the real CCTV dataset are available to the whole research community.Ministerio de Economía y Competitividad TIN2017-82113-C2-1-

Interplay of Postprandial Triglyceride-Rich Lipoprotein Composition and Adipokines in Obese Adolescents

In the context of the alarming rise of infant obesity and its health implications, the present research aims to uncover disruptions in postprandial lipid metabolism and the composition of triglyceride-rich lipoproteins in obese adolescents. A double-blind, controlled clinical trial in the postprandial phase on 23 adolescents aged 12 to 16 years was carried out. Twelve participants were categorized as obese (BMI > 30 kg/m2 and percentile > 95) and 11 as normal-weight (BMI = 20–25 kg/m2, percentile 5–85). Blood samples were collected after a 12-h overnight fast and postprandially after consumption of a standardized breakfast containing olive oil, tomato, bread, orange juice, and skimmed milk. Obese adolescents exhibited elevated triglyceride concentrations in both fasting and postprandial states and higher TG/apo-B48 ratios, indicating larger postprandial triglyceride-rich lipoprotein (TRL) particle size, which suggests impaired clearance. Obese subjects also exhibited higher n-6 PUFA concentrations, potentially linked to increased TRL hydrolysis and the release of pro-inflammatory adipokines. In contrast, TRL from normal-weight individuals showed higher concentrations of oleic acid and DHA (n-3 PUFA), with possible anti-inflammatory effects. The results indicate an interplay involving postprandial TRL metabolism and adipokines within the context of adolescent obesity, pointing to potential cardiovascular implications in the future.Spanish Ministry of Economy and Competitiveness (Grant number AGL2011-23810)”“Next Generation EU” fundsEuropean Union Recovery, Transformation and Resilience PlanMinistry of Universities, in the framework of the Margarita Salas, Maria Zambrano grants for the Requalification of the Spanish University System 2021–2023, organized by the Pablo de Olavide University, Sevill

Slice allocation and pricing framework for virtualized millimeter wave cellular networks

Traditionally, the cellular spectrum is allocated to operators (OPs) through auctions, as ideal mechanisms to discover market prices and allocate scarce resources. Even though spectrum is indeed scarce in sub-6 GHz bands, it becomes abundant in millimeter-wave (mmWave) bands. Interestingly, in that context, it is base station (BS) density which is limiting, and thus a critical factor, due to the outage phenomena in urban environments. Facing BS scarcity is one of the main reasons to foster virtualization techniques aimed at improving utilization and lowering costs. We consider a scenario with an infrastructure provider (InP) owner of a number of BSs and a set of OPs with their users (UEs). We propose a three-phase framework to price network infrastructure slices (NISs) and allocate them to OPs and to efficiently associate UEs with those NISs. The framework stages are: 1) an initial association, 2) a distributed auction mechanism across the BSs to allocate resources to Ops, and 3) a re-association process where the OPs can optimize the NISs they are awarded. The auction incentivizes OPs to bid truthfully and the outcome yields both socially optimal NISs and Vickrey-Clarke-Groves (VCG) prices. For the re-association phase, we propose deterministic and stochastic exchange-matching algorithms and demonstrate their convergence to stable matching and stable-optimal matching, respectively.Ministerio de Economía, Industria y Competitividad | Ref. TEC2016-76465-C2-2-RXunta de Galicia | Ref. GRC 2018/5

Influence of the Synthesis Method on the Preparation Composites Derived from TiO2-LDH for Phenol Photodegradation

Three different TiO2 catalysts are prepared using different methods. MgAl-CO32− layered double hydroxides (LDH) were obtained by the sol-gel method. In the preparation of the composites, the three photocatalysts were combined with LDH following different methodologies. The composites were characterized using X-ray diffraction (XRD), specific surface area (SA), atomic force microscopy (AFM) and X-ray photoelectron spectroscopy (XPS). The influence of the synthesis method on the preparation of the composites was evaluated by analyzing their photocatalytic activity against phenol as a model organic pollutant under UV irradiation. The photocatalytic activity of the composites improves when the chemical interaction, determined by XPS, between the TiO2 and the LDH decreases. The same happens when the ratio of the anatase-rutile phases, determined by XRD, approaches optimum (80:20%). The effect of the composite concentration in the solution (0.5–2.0 g/L) was investigated, and the light-shielding phenomenon due to high composite concentration decreases the phenol photodegradation. The reduction of photocatalytic activity in reuse cycles is due to loss and partial deactivation of the material. The elimination of phenol is attributed primarily to the photocatalytic process due to the generation of ●OH radicals and to a lesser extent the adsorption process also present in the samples

Un Framework para Big Data Optimization Basado en jMetal y Spark

Las metaheurísticas multi-objetivo se han convertido en técnicas muy utilizadas para la resolución de problemas complejos de optimización compuestos de varias funciones objetivo en conflicto entre sí. Nos encontramos en la actualidad inmersos en la era del Big Data, por lo que los problemas multi-objetivo que surjan en este contexto cumplirán algunas de las cinco V’s que caracterizan a las aplicaciones Big Data (volumen, velocidad, variedad, veracidad, valor). Como consecuencia, las metaheurísticas deberán ser capaces de resolver problemas dinámicos, que pueden cambiar en el tiempo debido al procesamiento y análisis de diferentes fuentes de datos, que típicamente serán en streaming. En este trabajo presentamos el software jMetalSP, que combina el framework jMetal con Apache Spark. De esta forma, las metaheurísticas disponibles en jMetal se pueden adaptar fácilmente para resolver problemas dinámicos que se alimenten de distintas fuentes de datos en streaming, y que son gestionadas por Spark. Se describe la arquitectura de jMetalSP y se valida mediante un caso de uso realista basado en TSP bi-objetivo con datos abiertos reales de tráfico de la ciudad de Nueva York.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Primary prevention of type 2 diabetes in Argentina: pilot study in the province of Buenos Aires

Sobre estilo de vida, previenen el desarrollo de diabetes tipo 2 (DMT2) en personas con tolerancia a la glucosa o glucemia de ayunas alterada (TGA y GAA, respectivamente), aisladas o combinadas. Evaluar la efectividad de adoptar estilo de vida saludable sobre la manifestación clínica de DMT2 en personas con riesgo de desarrollarla.Prevent/delay the development of type 2 diabetes (T2DM) in people with impaired glucose tolerance or impaired fasting blood glucose (IGT and IFG, respectively), alone or combined. To evaluate the effectiveness of adopting a healthy lifestyle on the clinical manifestation of T2DM in people at risk of its development.Fil: Gagliardino, Juan Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Endocrinología Experimental y Aplicada. Universidad Nacional de la Plata. Facultad de Cs.médicas. Centro de Endocrinología Experimental y Aplicada; ArgentinaFil: Etchegoyen, Graciela Susana. Universidad Nacional de La Plata; ArgentinaFil: Bourgeois, Marcelo Javier. Universidad Nacional de La Plata; ArgentinaFil: Fantuzzi, Gabriel Augusto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Endocrinología Experimental y Aplicada. Universidad Nacional de la Plata. Facultad de Cs.médicas. Centro de Endocrinología Experimental y Aplicada; ArgentinaFil: García, Silvia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Endocrinología Experimental y Aplicada. Universidad Nacional de la Plata. Facultad de Cs.médicas. Centro de Endocrinología Experimental y Aplicada; ArgentinaFil: González, Lorena. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Endocrinología Experimental y Aplicada. Universidad Nacional de la Plata. Facultad de Cs.médicas. Centro de Endocrinología Experimental y Aplicada; ArgentinaFil: Elgart, Jorge Federico. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Endocrinología Experimental y Aplicada. Universidad Nacional de la Plata. Facultad de Cs.médicas. Centro de Endocrinología Experimental y Aplicada; ArgentinaFil: Ré, Matías. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Endocrinología Experimental y Aplicada. Universidad Nacional de la Plata. Facultad de Cs.médicas. Centro de Endocrinología Experimental y Aplicada; ArgentinaFil: Ricart, Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones en Humanidades y Ciencias Sociales. Universidad Nacional de La Plata. Facultad de Humanidades y Ciencias de la Educación. Instituto de Investigaciones en Humanidades y Ciencias Sociales; ArgentinaFil: Ricart, Juan Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Endocrinología Experimental y Aplicada. Universidad Nacional de la Plata. Facultad de Cs.médicas. Centro de Endocrinología Experimental y Aplicada; ArgentinaFil: Spinedi, Eduardo Julio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - la Plata. Centro de Endocrinología Experimental y Aplicada. Universidad Nacional de la Plata. Facultad de Cs.médicas. Centro de Endocrinología Experimental y Aplicada; Argentin

Bisphosphonate-related osteonecrosis. Application of adipose-derived stem cells in an experimental murine model

Bisphosphonate-related osteonecrosis of the jaw is a pathological condition without effective established treatment and preventive strategies. The aim of this study was to analyse the effect of adipose-derived stem cells (ASC) in an experimental murine model of osteonecrosis. 38 Wistar rats were injected intraperitoneally with zoledronic acid. After treatment, upper jaw molars were extracted. The animals were randomly assigned to one of two groups. In the control group, saline solution was applied over the alveolar sockets after the tooth extractions. In the treatment group, ASCs were applied instead of saline solution. The control and treatment groups were subdivided based on the time of euthanasia. A clinical and histological analysis was performed. The presence of osteonecrosis in alveolar bone was observed in a similar distribution in both groups. In the ASC-treated group, new bone formation was greater than in controls. In this study, application of ASCs showed greater new bone formation in an osteonecrosis-like murine model. Previous inhibited post-extraction bone remodelling could be reactivated, and these findings appeared to be secondary to implantation of ASCs

Drug Repurposing for Cancers With Limited Survival: Protocol for a Retrospective Cohort Study

Only 5% of the molecules tested in oncology phase 1 trials reach the market after an average of 7.5 years of waiting and at a cost of tens of millions of dollars. To reduce the cost and shorten the time of discovery of new treatments, drug repurposing (research with molecules already approved for another indication) and the use of secondary data (not collected for the purpose of research) have been proposed. Due to advances in informatics in clinical care, secondary data can, in some cases, be of equal quality to primary data generated through prospective studies.Objective: The objective of this study is to identify drugs currently marketed for other indications that may have an effect on the prognosis of patients with cancer.Methods: We plan to monitor a cohort of patients with high-lethality cancers treated in the public health system of Catalonia between 2006 and 2012, retrospectively, for survival for 5 years after diagnosis or until death. A control cohort, comprising people without cancer, will also be retrospectively monitored for 5 years. The following study variables will be extracted from different population databases: type of cancer (patients with cancer cohort), date and cause of death, pharmacological treatment, sex, age, and place of residence. During the first stage of statistical analysis of the patients with cancer cohort, the drugs consumed by the long-term survivors (alive at 5 years) will be compared with those consumed by nonsurvivors. In the second stage, the survival associated with the consumption of each relevant drug will be analyzed. For the analyses, groups will be matched for potentially confounding variables, and multivariate analyses will be performed to adjust for residual confounding variables if necessary. The control cohort will be used to verify whether the associations found are exclusive to patients with cancer or whether they also occur in patients without cancer.Results: We anticipate discovering multiple significant associations between commonly used drugs and the survival outcomes of patients with cancer. We expect to publish the initial results in the first half of 2024.Conclusions: This retrospective study may identify several commonly used drugs as candidates for repurposing in the treatment of various cancers. All analyses are considered exploratory; therefore, the results will have to be confirmed in subsequent clinical trials. However, the results of this study may accelerate drug discovery in oncology

Evaluación del riesgo por metales pesados en suelos ácidos bajo diferentes sistemas agrícolas en el Piedemonte Llanero de Colombia

Agricultural soils may become polluted by heavy metals as a result of receiving a significant amount of pollutants from different sources of land applications, such as fertilizers, animal manure, sewage sludge, pesticides, and wastewater irrigation. Given that information on the distribution of heavy metals (HMs) in the Piedemonte Llanero of Colombia is still quite limited, the main objectives of this work were to characterize the content of these elements and their potential pollution level in acidic soils under different agricultural systems. The hypothesis is to verify if the type of land use poses an environmental threat. To achieve these goals, the concentrations of seven metals were determined in the soils of three agricultural production systems: oil palm, pastures, and semi-annual crops. Soil contamination was evaluated based on the Geo-Accumulation Index (I-geo), contamination factor (CF), Pollution Load Index (PLI), and Nemerov Integrated Pollution Index (NIPI). One outstanding result was that the average concentrations of HMs in the collected topsoil samples were as follows: Mn (110.5 mg kg-1), Zn (31.93 mg kg-1), Cr (8.85 mg kg-1), Ni (11.68 mg kg-1), Cu (11.28 mg kg-1), Pb (9.42 mg kg-1) and Cd (0.21 mg kg-1). The results obtained from this study provide an estimation of the pollution status of HMs. Agricultural activities, especially the overuse of phosphate fertilizer, were the main source of nutrients across the study area. This information can become a fundamental tool to establish monitoring and follow-up processes for sustainable soil management in the Piedemonte Llanero. In conclusion, the present study highlights and provides specific information in a hyperhumid environment.Los suelos agrícolas pueden contaminarse con metales pesados como consecuencia de recibir una cantidad significativa de contaminantes procedentes de diferentes fuentes de aplicaciones terrestres, tales como fertilizantes, estiércol animal, lodos de depuradora, pesticidas y/o riego con aguas residuales. Dado que la información sobre la distribución de metales pesados (MP) en el Piedemonte llanero de Colombia es aún bastante limitada, el objetivo principal de este trabajo fue caracterizar el contenido de estos elementos y su potencial nivel de contaminación en suelos ácidos bajo diferentes sistemas agrícolas. La hipótesis es verificar si el tipo de uso representa una amenaza ambiental. Para lograr estos objetivos, se determinaron las concentraciones de siete metales en los suelos de tres sistemas de producción agrícola: palma aceitera, pastos y cultivos semestrales. La contaminación del suelo se evaluó con base al índice de geo-acumulación (I-geo), el factor de contaminación (FC), el índice de carga contaminación (ICC) y el índice de contaminación integrada de Nemerov (ICIN). Un resultado sobresaliente fue que las concentraciones promedio de MP en las muestras de suelo recolectadas fueron en general: Mn (110.5 mg kg-1), Zn (31.93 mg kg-1), Cr (8.85 mg kg-1), Ni (11.68 mg kg-1), Cu (11.28 mg kg-1), Pb (9.42 mg kg-1) y Cd (0.21 mg kg-1). Las actividades agrícolas, especialmente el uso excesivo de fertilizantes fosfatados, fueron la principal fuente de nutrientes en toda el área de estudio. Esta información puede convertirse en una herramienta básica para establecer procesos de monitoreo y seguimiento que permitan establecer un manejo sustentable del suelo en el Piedemonte llanero. Además, los resultados obtenidos de este estudio constituyen una estimación del estado de contaminación de los MP en el contexto específico de un ambiente hiperhúmedo