ALBERT

Description: The number of connected sensors and devices is expected to increase to billions in the near future. However, centralised cloud-computing data centres present various challenges to meet the requirements inherent to Internet of Things (IoT) workloads, such as low latency, high throughput and bandwidth constraints. Edge computing is becoming the standard computing paradigm for latency-sensitive real-time IoT workloads, since it addresses the aforementioned limitations related to centralised cloud-computing models. Such a paradigm relies on bringing computation close to the source of data, which presents serious operational challenges for large-scale cloud-computing providers. In this work, we present an architecture composed of low-cost Single-Board-Computer clusters near to data sources, and centralised cloud-computing data centres. The proposed cost-efficient model may be employed as an alternative to fog computing to meet real-time IoT workload requirements while keeping scalability. We include an extensive empirical analysis to assess the suitability of single-board-computer clusters as cost-effective edge-computing micro data centres. Additionally, we compare the proposed architecture with traditional cloudlet and cloud architectures, and evaluate them through extensive simulation. We finally show that acquisition costs can be drastically reduced while keeping performance levels in data-intensive IoT use cases.

Description: In recent decades, orthorexia nervosa (ON) has increased presence in society. It is related with beliefs and attitudes towards eating and is characterized by an obsessive behavior toward heathy eating. The prevalence of ON has been reported by numerous researchers, with rates varying considerably according to the tool used to evaluate the same parameter. The aim of this study was to compare the prevalence of ON in a single population using two different questionnaires. The test for the diagnosis of orthorexia (ORTO-11-ES) assessment tool for orthorexia nervosa and the Düsseldorfer Ortorexie Skala (DOS-ES), constitute brief self-report assessment tools which measure the risk of suffering ON. A sample of 492 students from the University of Castilla la Mancha (Spain) participated in this study, of whom 43.1% were male and 56.9% were female. The findings show that, according to the DOS-ES, only 10.5% of students displayed ON whereas, with the ORTO-11-ES, the prevalence of ON increased to 25.2%. The tendency towards orthorexic behavior is more closely associated with the female gender. The Body Mass Index (BMI) had no influence on the tendency for ON. This study provides valuable information on the usefulness of both questionnaires and the possible limitations associated with the use of these tools in the general population.

Description: Caring for a person diagnosed with Alzheimer’s disease has a negative impact on family caregivers’ psychological health. This study examined the factors related to ‘perceived health’ and ‘presence of new-onset mental health problems’ in family caregivers of people diagnosed with mild and moderate Alzheimer’s disease. A cross-sectional observational study carried out in Almeria’s Healthcare District (Spain). A total of 255 family caregivers (42.4% cared for people with mild Alzheimer’s disease and 57.6% cared for people with moderate Alzheimer’s disease) participated in the study from January to December 2015. Mainly, caregivers were women (81.5% in the mild Alzheimer’s disease group and 88.4% in the moderate Alzheimer’s disease group), and their average age was 56.54 years (standard deviation (SD) = 13.13) and 54.47 years (SD = 11.71), respectively. Around 47% of the caregivers had been caring for the person with Alzheimer’s between two and five years. The Goldberg General Health Questionnaire was used to measure perceived health and the presence of new-onset mental health problems. An exploratory descriptive analysis and a multivariate logistic regression analysis were conducted. For caregivers of people with mild Alzheimer’s disease, ‘perceived health’ was related to ‘perceived social support’ (r = −0.21; p = 0.028), ‘person’s level of dependency’ (r = −0.24, p = 0.05), ‘severity of the person’s neuropsychiatric symptoms’ (r = 0.22; p = 0.05), and ‘caregiver’s emotional distress in response to the person’s neuropsychiatric symptoms’ (r = 0.22; p = 0.05). For caregivers of people with moderate Alzheimer’s disease, ‘perceived health’ was related to ‘perceived social support’ (r = −0.31; p ˂ 0.01), ‘presence of neuropsychiatric symptoms’ (r = 0.27, p = 0.01), ‘severity of the person’s neuropsychiatric symptoms’ (r = 0.32, p = 0.01) and ‘caregiver’s emotional distress in response to the person’s neuropsychiatric symptoms’ (r = 0.029; p = 0.01). The presence of new-onset mental health problems was detected in 46.3% (n = 50) of caregivers of people with mild Alzheimer’s and 61.9% (n = 91) of caregivers of people with moderate Alzheimer’s. When people are diagnosed with mild Alzheimer’s disease, intervention programs for caregivers should aim to regulate emotions and promote positive coping strategies. When people are diagnosed with moderate Alzheimer’s disease, intervention programs for caregivers must allow them to adapt to caregiving demands that arise with the progression of Alzheimer’s disease.

Description: Waveguide-based photonic sensors provide a unique combination of high sensitivity, compact size and label-free, multiplexed operation. Interferometric configurations furthermore enable a simple, fixed-wavelength read-out making them particularly suitable for low-cost diagnostic and monitoring devices. Their limit of detection, i.e., the lowest analyte concentration that can be reliably observed, mainly depends on the sensors response to small refractive index changes, and the noise in the read-out system. While enhancements in the sensors response have been extensively studied, noise optimization has received much less attention. Here we show that order-of-magnitude enhancements in the limit of detection can be achieved through systematic noise reduction, and demonstrate a limit of detection of ∼ 10 − 8 RIU with a silicon nitride sensor operating at telecom wavelengths.

Description: A novel, green route for pre-exfoliation of graphite based on a biodegradable polymer and high-power ultrasound is presented. Candelilla wax (CW), derived from the leaves of the candelilla plant, has been used for the first time as a natural non aqueous medium to induce the pre-exfoliation of expanded graphite (EG) under ultrasonic irradiation in an economical way. The proposed method uses also D-limonene as a natural organic solvent for reducing viscosity and increasing the affinity between the polar groups of EG and candelilla wax, thus improving the intercalation/exfoliation of EG. The quality of dispersion of the nanofiller in the natural wax matrix has been evaluated using multiple techniques. The addition of EG to wax and use of ultrasonic treatment leads to a reduced crystallinity, probably due to restrictions of the molecular movements, improved thermal stability of wax, and to an increased shear thinning exponent, which are all indicative of a high degree of EG dispersion. The ultrasonic dynamic mechanical results suggest a reduction in the cluster size and a better filler dispersion in the wax matrix promoted by polar or chemical reactions between the CW fractions and the graphite stacks, which was observed by XPS analysis. The results were compared to those obtained with paraffin, a synthetic wax, and confirmed the dispersion improvement obtained by using natural wax as a pre-exfoliating medium.

Description: Pine pitch canker (PPC), caused by the pathogenic fungus Fusarium circinatum (Nirenberg and O’ Donnell), is a serious threat to pine forests globally. The recent introduction of the pathogen to Southern Europe and its spread in Mediterranean region is alarming considering the immense ecological and economic importance of pines in the region. Pines in forests and nurseries can be infected, resulting in severe growth losses and mortality. The pathogen is known to spread in plants for planting and in seeds, and results from recent studies have indicated that F. circinatum may also spread through phoretic associations with certain insects. With this review, we aim to expand the current understanding of the risk of insect-mediated spread of PPC in different parts of Europe. Through the joint action of a multinational researcher team, we collate the existing information about the insect species spectrum in different biogeographic conditions and scrutinize the potential of these insects to transmit F. circinatum spores in forests and nurseries. We also discuss the impact of environmental factors and forest management in this context. We present evidence for the existence of a high diversity of insects with potential to weaken pines and disseminate PPC in Europe, including several common beetle species. In many parts of Europe, temperatures are projected to rise, which may promote the activity of several insect species, supporting multivoltinism and thus, further amplifying the risk of insect-mediated dissemination of PPC. Integrated pest management (IPM) solutions that comply with forest management practices need to be developed to reduce this risk. We recommend careful monitoring of insect populations as the basis for successful IPM. Improved understanding of environmental control of the interaction between insects, the pathogen, and host trees is needed in order to support development of bio-rational strategies to safeguard European pine trees and forests against F. circinatum in future.

Description: Water status controls plant physiology and is key to managing vineyard grape quality and yield. Water status is usually estimated by leaf water potential (LWP), which is measured using a pressure chamber; however, this method is difficult, time-consuming, and error-prone. While traditional spectral methods based on leaf reflectance are faster and non-destructive, most are based on vegetation indices derived from satellite imagery (and so only take into account discrete bandwidths) and do not take full advantage of modern hyperspectral sensors that capture spectral reflectance for thousands of wavelengths. We used partial least squares regression (PLSR) to predict LWP from reflectance values (wavelength 350–2500 nm) captured with a field spectroradiometer. We first identified wavelength ranges that minimized regression error. We then tested several common data pre-processing methods to analyze the impact on PLSR prediction precision, finding that derivative pre-processing increased the determination coefficients of our models and reduced root mean squared error (RMSE). The models fitted with raw data obtained their best results at around 1450 nm, while the models with derivative pre-processed achieved their best estimates at 826 nm and 1520 nm.

Description: In this work, a problem of optimal placement of renewable generation and topology design for a Microgrid (MG) is tackled. The problem consists of determining the MG nodes where renewable energy generators must be optimally located and also the optimization of the MG topology design, i.e., deciding which nodes should be connected and deciding the lines’ optimal cross-sectional areas (CSA). For this purpose, a multi-objective optimization with two conflicting objectives has been used, utilizing the cost of the lines, C, higher as the lines’ CSA increases, and the MG energy losses, E, lower as the lines’ CSA increases. To characterize generators and loads connected to the nodes, on-site monitored annual energy generation and consumption profiles have been considered. Optimization has been carried out by using a novel multi-objective algorithm, the Multi-objective Substrate Layers Coral Reefs Optimization algorithm (Mo-SL-CRO). The performance of the proposed approach has been tested in a realistic simulation of a MG with 12 nodes, considering photovoltaic generators and micro-wind turbines as renewable energy generators, as well as the consumption loads from different commercial and industrial sites. We show that the proposed Mo-SL-CRO is able to solve the problem providing good solutions, better than other well-known multi-objective optimization techniques, such as NSGA-II or multi-objective Harmony Search algorithm.

Description: The aim of this article is to contribute to understanding the importance of considering the effect of employees’ perceptions of Socially Responsible Human Resource Management (SR-HRM) on employee commitment. Results, applied to different levels of the organization (HR managers, line managers and employees) show, on one hand, that there is a relationship between a SR-HRM and employee commitment, and on the other hand, that employees’ perceptions have an influence on the extent to which these relationships are developed. HR managers and line managers perceived SR-HRM in a similar way and line managers and non-managerial employees generally did too. The frequency with which line managers disagree with employees’ perceptions about socially responsible practices was low. Suggestions for HRM practice and future research are provided.

Description: Over the last two decades, a wide range of applications have been developed from Light Detection and Ranging (LiDAR) point clouds. Most LiDAR-derived products require the distinction between ground and non-ground points. Because of this, ground filtering its being one of the most studied topics in the literature and robust methods are nowadays available. However, these methods have been designed to work with offline data and they are generally not well suited for real-time scenarios. Aiming to address this issue, this paper proposes an efficient method for ground filtering of airborne LiDAR data based on scan-line processing. In our proposal, an iterative 1-D spline interpolation is performed in each scan line sequentially. The final spline knots of a scan line are taken into account for the next scan line, so that valuable 2-D information is also considered without compromising computational efficiency. Points are labelled into ground and non-ground by analysing their residuals to the final spline. When tested against synthetic ground truth, the method yields a mean kappa value of 88.59% and a mean total error of 0.50%. Experiments with real data also show satisfactory results under visual inspection. Performance tests on a workstation show that the method can process up to 1 million points per second. The original implementation was ported into a low-cost development board to demonstrate its feasibility to run in embedded systems, where throughput was improved by using programmable logic hardware acceleration. Analysis shows that real-time filtering is possible in a high-end board prototype, as it can process the amount of points per second that current lightweight scanners acquire with low-energy consumption.