Raman and Fluorescence Enhancement Approaches in Graphene-Based Platforms for Optical Sensing and Imaging

This article belongs to the Special Issue Physics and Chemistry of Graphene: From Fundamentals to Applications.The search for novel platforms and metamaterials for the enhancement of optical and particularly Raman signals is still an objective since optical techniques offer affordable, noninvasive methods with high spatial resolution and penetration depth adequate to detect and image a large variety of systems, from 2D materials to molecules in complex media and tissues. Definitely, plasmonic materials produce the most efficient enhancement through the surface-enhanced Raman scattering (SERS) process, allowing single-molecule detection, and are the most studied ones. Here we focus on less explored aspects of SERS such as the role of the inter-nanoparticle (NP) distance and the ultra-small NP size limit (down to a few nm) and on novel approaches involving graphene and graphene-related materials. The issues on reproducibility and homogeneity for the quantification of the probe molecules will also be discussed. Other light enhancement mechanisms, in particular resonant and interference Raman scatterings, as well as the platforms that allow combining several of them, are presented in this review with a special focus on the possibilities that graphene offers for the design and fabrication of novel architectures. Recent fluorescence enhancement platforms and strategies, so important for bio-detection and imaging, are reviewed as well as the relevance of graphene oxide and graphene/carbon nanodots in the field.The research leading to these results has received funding from Ministerio de Ciencia e Innovación (RTI2018-096918-B-C41). S.C. acknowledges the grant BES-2016-076440 from MINECO

Contract-based test generation for data flow of business processes using constraint programming

The verification of the properties of a business process (BP) has become a significant research topic in recent years. In the early stages of development, the BP model (e.g. BPMN, EPC), the BP contract (task contract, regulations and laws, business rules), and the test objectives (requirements) are the only elements available. In order to support the modellers, automatic tools must be provided in order to check whether their business processes are in line with the BP contract. This paper proposes a new business process called the automatic test-case generator to automate the generation of test cases and verify that a BP has the intended functionality (semantic conformance). This generator is analysed, designed and implemented by taking into account the following tasks: Annotation of the BP model with the business process contract, calculation of the various data flow paths, transformation of these data flow paths into SSA form, and a modelling of a constraint satisfaction problem (constraint programming) of the BP contract for all data flow paths. The execution of this business process generates the test cases automatically.Junta de Andalucía P08-TIC-04095Ministerio de Ciencia e Innovación TIN2009-1371

A Model-Driven Engineering approach with Diagnosis of Non-Conformance of Security Objectives in Business Process Models

Several reports indicate that the highest business priorities include: business improvement, security, and IT management. The importance of security and risk management is gaining that even government statements in some cases have imposed the inclusion of security and risk management within business management. Risk assessment has become an essential mechanism for business security analysts, since it allows the identification and evaluation of any threats, vulnerabilities, and risks to which organizations maybe be exposed. In this work, a framework based on the concepts of Model-Driven Development has been proposed. The framework provides different stages which range from a high abstraction level to an executable level. The main contribution lie in the presentation of an extension of a business process meta-model which includes risk information based on standard approaches. The meta-model provides necessary characteristics for the risk assessment of business process models at an abstract level of the approach. The framework has been equipped with specific stages for the automatic validation of business processes using model-based diagnosis which permits the detection of the non-conformance of security objectives specified. The validation stages ensure that business processes are correct with regard to the objectives specified by the customer before they are transformed into executable processes.Junta de Andalucía P08-TIC-04095Ministerio de Ciencia e Innovación TIN2009-1371

Surfactant-free synthesis and scalable purification of triangular gold nanoprisms with low non-specific cellular uptake

Gold nanoprisms possess remarkable optical properties that make them useful for medical biotechnology applications such as diagnosis and photothermal therapy. However, shape-selective synthesis of gold nanoprisms is not trivial and typically requires either toxic surfactants or time-consuming purification protocols, which can limit their applicability. Here, we show how triangular gold nanoprisms of different sizes can be purified by precipitation using the non-toxic glutathione ligand, thereby removing the need for toxic surfactants and bottleneck purification techniques. The protocol is amenable for direct scaling up as no instrumentation is required in the critical purification step. The new purification method provides a two-fold increased yield in gold nanoprisms compared to electrophoretic filtration, while providing nanoprisms of similar localized surface plasmon resonance wavelength. Crucially, the gold nanoprisms isolated using this methodology show fewer non-specific interactions with cells and lower cellular internalization, which paves the way for a higher selectivity in therapeutic applications

Raman amplification in the ultra-small limit of Ag nanoparticles on SiO2 and graphene: Size and inter-particle distance effects

Size, shape and hot spots are crucial to optimize Raman amplification from metallic nanoparticle (NPs). The amplification from radius = 1.8 ± 0.4 nm ultra-small silver NPs was explored. Increasing NP density redshifts and widens their plasmon that, according to simulations for NPs arrays, is originated by the reduction of the interparticle distance, d, becoming remarkable for d ≤ R. Inter-particle interaction red-shifts (>130 nm) and widens (>90 nm) the standard plasmon of non-interacting spherical particles. Graphene partly delocalizes the carriers enhancing the NIR spectral weight. Raman amplification of graphene phonons is moderate and depends smoothly on d while that of Rhodamine 6G (R6G) varies almost exponentially due to their location at hot-spots that depend strongly on d. The experimental correlation between amplification and plasmon position is well reproduced by simulations. The amplification originated by the ultra-small NPs is compared to that of larger particles, granular silver films with 7 < R < 15 nm grains, with similar extinction values. The amplification is found to be larger for the 1.8 nm NPs due to the higher surface/volume ration that allows higher density of hot spots. It is demonstrated that Raman amplification can be efficiently increased by depositing low density layers of ultra-small NPs on top of granular films.The research leading to these results has received funding from Ministerio de Ciencia, Innovación y Universidades (RTI2018-096918-B-C41). S.C. acknowledges the grant BES-2016-076440 from MINECO. L.M. acknowledges the European Union (grant number ERC-2013-SyG 610256 NANOCOSMOS)

Hybridizing humans and robots: An RPA horizon envisaged from the trenches

After the initial hype on RPA, companies have more realistic expectations of this technology. Its current mature vision relegates the end-to-end robotic automation to a less suitable place and considers the human-robot collaboration as the most natural way for automating robotic processes in real-world settings. This hybrid RPA implies a vertical segmentation of process activities, i.e., some activities are conducted by humans while robots do others. The literature lacks a general method that considers the technical aspect of the solution, the psychological impact of the automation, and the governance mechanisms that a running hybrid process requires. In this sense, this paper proposes an iterative method dealing with all these aspects and results from a series of industrial experiences. Additionally, the paper deeply discusses the role of process mining in this kind of method and how it can continuously boost its iterations. The initial validation of the method in real-world processes reports substantial benefits in terms of efficiencyMinisterio de Ciencia, Innovación y Universidades PID2019-105455GB-C31Junta de Andalucía CEI-12-TIC02

UCO physical rehabilitation: new dataset and study of human pose estimation methods on physical rehabilitation exercises

Physical rehabilitation plays a crucial role in restoring motor function following injuries or surgeries. However, the challenge of overcrowded waiting lists often hampers doctors’ ability to monitor patients’ recovery progress in person. Deep Learning methods offer a solution by enabling doctors to optimize their time with each patient and distinguish between those requiring specific attention and those making positive progress. Doctors use the flexion angle of limbs as a cue to assess a patient’s mobility level during rehabilitation. From a Computer Vision perspective, this task can be framed as automatically estimating the pose of the target body limbs in an image. The objectives of this study can be summarized as follows: (i) evaluating and comparing multiple pose estimation methods; (ii) analyzing how the subject’s position and camera viewpoint impact the estimation; and (iii) determining whether 3D estimation methods are necessary or if 2D estimation suffices for this purpose. To conduct this technical study, and due to the limited availability of public datasets related to physical rehabilitation exercises, we introduced a new dataset featuring 27 individuals performing eight diverse physical rehabilitation exercises focusing on various limbs and body positions. Each exercise was recorded using five RGB cameras capturing different viewpoints of the person. An infrared tracking system named OptiTrack was utilized to establish the ground truth positions of the joints in the limbs under study. The results, supported by statistical tests, show that not all state-of-the-art pose estimators perform equally in the presented situations (e.g., patient lying on the stretcher vs. standing). Statistical differences exist between camera viewpoints, with the frontal view being the most convenient. Additionally, the study concludes that 2D pose estimators are adequate for estimating joint angles given the selected camera viewpoints

sSLAM: Speeded-Up Visual SLAM Mixing Artificial Markers and Temporary Keypoints

Environment landmarks are generally employed by visual SLAM (vSLAM) methods in the form of keypoints. However, these landmarks are unstable over time because they belong to areas that tend to change, e.g., shadows or moving objects. To solve this, some other authors have proposed the combination of keypoints and artificial markers distributed in the environment so as to facilitate the tracking process in the long run. Artificial markers are special elements (similar to beacons) that can be permanently placed in the environment to facilitate tracking. In any case, these systems keep a set of keypoints that is not likely to be reused, thus unnecessarily increasing the computing time required for tracking. This paper proposes a novel visual SLAM approach that efficiently combines keypoints and artificial markers, allowing for a substantial reduction in the computing time and memory required without noticeably degrading the tracking accuracy. In the first stage, our system creates a map of the environment using both keypoints and artificial markers, but once the map is created, the keypoints are removed and only the markers are kept. Thus, our map stores only long-lasting features of the environment (i.e., the markers). Then, for localization purposes, our algorithm uses the marker information along with temporary keypoints created just in the time of tracking, which are removed after a while. Since our algorithm keeps only a small subset of recent keypoints, it is faster than the state-of-the-art vSLAM approaches. The experimental results show that our proposed sSLAM compares favorably with ORB-SLAM2, ORB-SLAM3, OpenVSLAM and UcoSLAM in terms of speed, without statistically significant differences in accuracy

sSLAM: Speeded-Up Visual SLAM Mixing Artificial Markers and Temporary Keypoints

Environment landmarks are generally employed by visual SLAM (vSLAM) methods in the form of keypoints. However, these landmarks are unstable over time because they belong to areas that tend to change, e.g., shadows or moving objects. To solve this, some other authors have proposed the combination of keypoints and artificial markers distributed in the environment so as to facilitate the tracking process in the long run. Artificial markers are special elements (similar to beacons) that can be permanently placed in the environment to facilitate tracking. In any case, these systems keep a set of keypoints that is not likely to be reused, thus unnecessarily increasing the computing time required for tracking. This paper proposes a novel visual SLAM approach that efficiently combines keypoints and artificial markers, allowing for a substantial reduction in the computing time and memory required without noticeably degrading the tracking accuracy. In the first stage, our system creates a map of the environment using both keypoints and artificial markers, but once the map is created, the keypoints are removed and only the markers are kept. Thus, our map stores only long-lasting features of the environment (i.e., the markers). Then, for localization purposes, our algorithm uses the marker information along with temporary keypoints created just in the time of tracking, which are removed after a while. Since our algorithm keeps only a small subset of recent keypoints, it is faster than the state-of-the-art vSLAM approaches. The experimental results show that our proposed sSLAM compares favorably with ORB-SLAM2, ORB-SLAM3, OpenVSLAM and UcoSLAM in terms of speed, without statistically significant differences in accuracy.This research was funded by the project PID2019-103871GB-I00 of the Spanish Ministry of Economy, Industry and Competitiveness, FEDER, Project 1380047-F UCOFEDER-2021 of Andalusia and by the European Union–NextGeneration EU for requalification of Spanish University System 2021–2023

Índice de percepción local de mejora del combate al rezago social: análisis de las centrales eólicas en el Istmo de Tehuantepec, Oaxaca

The aim of this study is to analyze how people struggle against social backwardness in the Isthmus of Tehuantepec, Oaxaca, in response to the installation of wind farms in the region. We rely on the holistic analytical dimensions proposed by Social Metabolism to quantify biophysical interactions between society and environmental, while making use of Geospatial Information Systems and data produced by Coneval and INEGI regarding social backwardness. We conclude that, in the region, the perception of improvement in the social backwardness index has not increased with the presence of these megaprojects, given that they do not mitigate ecosystem impacts or social backwardness.El objetivo de este artículo es proponer un nuevo índice local de percepción de mejora del combate al rezago social en la región del Istmo de Tehuantepec, Oaxaca, como resultado de la puesta en marcha de centrales eólicas. Nos apoyamos en las dimensiones analíticas holísticas propuestas por el Metabolismo Social para cuantificar las interacciones biofísicas entre sociedad y medio ambiente, en el uso de Sistemas de Información Geoespacial, así como en datos arrojados por el Coneval e INEGI respecto al rezago social. Concluimos que la percepción de mejora sobre este índice en la región no ha incrementado con la presencia de estos megaproyectos ya que estos no mitigan los impactos ecosistémicos ni coadyuvan al combate de tal fenómeno