ALBERT

Description: 5G and beyond networks are being designed to support the future digital society, where numerous sensors, machinery, vehicles and humans will be connected in the so-called Internet of Things (IoT). The support of time-critical verticals such as Industry 4.0 will be especially challenging, due to the demanding communication requirements of manufacturing applications such as motion control, control-to-control applications and factory automation, which will require the exchange of critical sensing and control information among the factory nodes. To this aim, important changes have been introduced in 5G for Ultra-Reliable and Low-Latency Communications (URLLC). One of these changes is the introduction of grant-free scheduling for uplink transmissions. The objective is to reduce latency by eliminating the need for User Equipments (UEs—sensors, devices or machinery) to request resources and wait until the network grants them. Grant-free scheduling can reserve radio resources for dedicated UEs or for groups of UEs. The latter option is particularly relevant to support applications with aperiodic or sporadic traffic and deterministic low latency requirements. In this case, when a UE has information to transmit, it must contend for the usage of radio resources. This can lead to potential packet collisions between UEs. 5G introduces the possibility of transmitting K replicas of the same packet to combat such collisions. Previous studies have shown that grant-free scheduling with K replicas and shared resources increases the packet delivery. However, relying upon the transmission of K replicas to achieve a target reliability level can result in additional delays, and it is yet unknown whether grant-free scheduling with K replicas and shared resources can guarantee very high reliability levels with very low latency. This is the objective of this study, that identifies the reliability and latency levels that can be achieved by 5G grant-free scheduling with K replicas and shared resources in the presence of aperiodic traffic, and as a function of the number of UEs, reserved radio resources and replicas K. The study demonstrates that current Fifth Generation New Radio (5G NR) grant-free scheduling has limitations to sustain stringent reliability and latency levels for aperiodic traffic.

Description: Groundwater and surface water are often studied as different systems; however, one commonly affects the other. Bank storage, the temporary storage and release of stream water in adjacent aquifers, can contribute a considerable amount of discharge to a river and can be a component in the transport and fate of a contaminant. Studies document the effects of increasing stage and increasing storm duration; however, these controls are often investigated separately. This project examined which factor, peak stage or storm duration, was more influential on the bank-storage process. The study focused on a small reach of a third-order, meandering, perennial stream. A 3-D, transient-state numerical model (MODFLOW) was created of the study site, and 36 simulations were run at various peak stages and storm durations. Peak stage and storm durations, while both influential, affected different areas of the bank-storage process. Peak stage was statistically more influential in controlling the maximum volume of bank storage (~3.6×) and the volume of the storage that remained in the system at 100 h (~1.1×). Longer storm duration generated a slower return of water, thus increasing the retention of bank storage. Parafluvial exchange was an important factor in bank storage along a meandering stream, suggesting that at least 2-D, ideally 3-D, models need to be employed in evaluating bank storage.

Description: Vitamin D deficiency (serum 25-hydroxyvitamin D (25(OH)D) concentrations 〈50 nmol/L) is a public health issue in Australia and internationally. Those with darker skin require a greater dose of ultraviolet B radiation from sunlight than those with paler skin to synthesise adequate amounts of vitamin D. Using data from the 2011–2013 Australian Health Survey, we investigated the prevalence and predictors of vitamin D deficiency in African immigrants aged ≥18 years living in Australia (n = 236). Serum 25(OH)D was measured using a liquid chromatography–tandem mass spectrometry method that is certified to international reference measurement procedures. Poisson regression was used to investigate independent predictors of vitamin D deficiency. A total of 36% of adults were vitamin D deficient (35% of men, 37% of women). The prevalence ratio (PR) of vitamin D deficiency decreased by 2% per year of age (PR 0.98; 95% CI (0.97, 0.99); p = 0.004) and was 1.6 times higher in those with low/sedentary, compared to moderate/high, physical activity levels (PR 1.64; 95% CI (1.12, 2.39); p = 0.011). The greatest risk was for those assessed during winter/spring compared with summer/autumn (PR 1.89; 95% CI (1.33, 2.64); p 〈 0.001). Culturally appropriate messaging on safe sun exposure and dietary vitamin D is warranted in order to promote vitamin D sufficiency in African immigrants living in Australia.

Description: The goal of the present research is to contribute to the detection of tax fraud concerning personal income tax returns (IRPF, in Spanish) filed in Spain, through the use of Machine Learning advanced predictive tools, by applying Multilayer Perceptron neural network (MLP) models. The possibilities springing from these techniques have been applied to a broad range of personal income return data supplied by the Institute of Fiscal Studies (IEF). The use of the neural networks enabled taxpayer segmentation as well as calculation of the probability concerning an individual taxpayer’s propensity to attempt to evade taxes. The results showed that the selected model has an efficiency rate of 84.3%, implying an improvement in relation to other models utilized in tax fraud detection. The proposal can be generalized to quantify an individual’s propensity to commit fraud with regards to other kinds of taxes. These models will support tax offices to help them arrive at the best decisions regarding action plans to combat tax fraud.

Description: The cross-shelf advection of coastal waters into the deep Gulf of Mexico is important for the transport of nutrients or potential pollutants. Twenty years of ocean color satellite imagery document such cross-shelf transport events via three export pathways in the Gulf of Mexico: from the Campeche Bank toward the central Gulf, from the Campeche Bank toward the Florida Straits, and from the Mississippi Delta to the Florida Straits. A catalog of these events was created based on the visual examination of 7280 daily satellite images. Water transport from the Campeche Bank to the central Gulf occurred frequently and with no seasonal pattern. Transport from Campeche Bank to the Florida Straits occurred episodically, when the Loop Current was retracted. Four such episodes were identified, between about December and June, in 2002, 2009, 2016, and 2017, each lasting ~3 months. Movement of Mississippi River water to the Florida Straits was more frequent and showed near seasonal occurrence, when the Loop Current was extended, while the Mississippi River discharge seems to play only a secondary role. Eight such episodes were identified—in 1999, 2000, 2003, 2004, 2006, 2011, 2014, and 2015—each lasting ~3 months during summer. The 2015 episode lasted 5 months.

Description: There is growing concern about how to mitigate climate change in which the reduction of CO2 emissions plays an important role. Buildings have gained attention in recent years since they are responsible for around 30% of greenhouse gases. In this context, advance control strategies to optimize HVAC systems are necessary because they can provide significant energy savings whilst maintaining indoor thermal comfort. Simulation-based model predictive control (MPC) procedures allow an increase in building energy performance through the smart control of HVAC systems. The paper presents a methodology that overcomes one of the critical issues in using detailed building energy models in MPC optimizations—computational time. Through a case study, the methodology explains how to resolve this issue. Three main novel approaches are developed: a reduction in the search space for the genetic algorithm (NSGA-II) thanks to the use of the curve of free oscillation; a reduction in convergence time based on a process of two linked stages; and, finally, a methodology to measure, in a combined way, the temporal convergence of the algorithm and the precision of the obtained solution.

Description: Affinity towards diversity (ATD) is the tendency to appreciate the dynamic variety of biophysical and socio-cultural scenarios. ATD may reveal a human predisposition to conserve the diversity necessary to guarantee the preservation of human and natural ecosystems. This study expands upon previous studies which employed only self-report measures by introducing a version of the Implicit Association Test (IAT) and by using a mediational model to test whether ATD through sustainable (pro-environmental and pro-social) behaviors leads to greater wellbeing. We recruited 119 Mexican students to complete a computerized IAT task and respond to ATD, wellbeing, and sustainable behavior self-report questionnaires. Reliability analyses of the scales utilized showed acceptable indexes. A mediational model was tested to examine whether sustainable behaviors mediate the relationship between ATD and wellbeing. Results demonstrated that affinity towards diversity indirectly predicted wellbeing via the mediating effects of pro-environmental behaviors and altruism. Despite finding an association between self-reported affinity towards biodiversity and IAT reaction times, an association was not found with D scores, highlighting the need for further research. These findings suggest that those with increased inclination towards diversity are more prone to engage in environmentally (both physical and social) protective behaviors and to experience psychological wellbeing.

Description: Livestock production is a socioeconomic linchpin in Mongolia and is affected by large-scale livestock die-offs. Colloquially known as dzuds, these die-offs are driven by anomalous climatic events, including extreme cold temperatures, extended snow cover duration (SCD) and drought. As average temperatures across Mongolia have increased at roughly twice the global rate, we hypothesized that increasing cold season surface melt including soil freeze/thaw (FT), snowmelt, and icing events associated with regional warming have become increasingly important drivers of dzud events as they can reduce pasture productivity and inhibit access to grazing. Here, we use daily brightness temperature (Tb) observations to identify anomalous surface melt and icing events across Mongolia from 2003–2016 and their contribution to dzuds relative to other climatic drivers, including winter temperatures, SCD, and drought. We find a positive relationship between surface melt and icing events and livestock mortality during the fall in southern Mongolia and during the spring in the central and western regions. Further, anomalous seasonal surface melt and icing events explain 17–34% of the total variance in annual livestock mortality, with cold temperatures as the leading contributor of dzuds (20–37%). Summer drought showed the greatest explanatory power (43%) but overall had less statistically significant relationships relative to winter temperatures. Our results indicate that surface melt and icing events will become an increasingly important driver of dzuds as annual temperatures and livestock populations are projected to increase in Mongolia.

Description: A detailed knowledge of soil water repellency (SWR) and water infiltration capacity of soils under different land uses is of fundamental importance in Mediterranean areas, since these areas are prone to soil degradation risks (e.g., erosion, runoff of polluting compounds) as a response to different hydrological processes. The present study evaluates the effects of land uses on SWR and soil hydraulic conductivity (SHC) by direct measurements at the plot scale in three areas representing (1) intensive agricultural use, (2) abandoned farmland, and (3) a forest ecosystem in Southern Spain under Mediterranean climatic conditions. The physico-chemical properties and water content of the experimental soils were also measured. Significant SWR and SHC differences were found among the analyzed land uses. Forest soils showed high SWR and low SHC, while the reverse effects (that is, low SWR and high SHC) were detected in soils subjected to intensive agriculture. Organic matter and bulk density were important soil properties influencing SWR and SHC. The study, demonstrating how land uses can have important effects on the hydrological characteristics of soils, give land managers insights into the choice of the most suitable land use planning strategies in view of facing the high runoff and erosion rates typical of the Mediterranean areas.

Description: Change detection methods are often incapable of accurately detecting changes within time series that are heavily influenced by seasonal variations. Techniques for de-seasoning time series or methods that apply the spatial context have been used to improve the results of change detection. However, few studies have explored Landsat’s shortwave infrared channel (SWIR 2) to discriminate between seasonal changes and land use/land cover changes (LULCC). Here, we explored the effectiveness of Operational Land Imager (OLI) spectral bands and vegetation indices for detecting deforestation in highly seasonal areas of Brazilian savannas. We adopted object-based image analysis (OBIA), applying a multidate segmentation to an OLI time series to generate input data for discrimination of deforestation from seasonal changes using the Random Forest (RF) algorithm. We found adequate separability between deforested objects and seasonal changes using SWIR 2. Using spectral indices computed from SWIR 2, the RF algorithm generated a change map with an overall accuracy of 88.3%. For deforestation, the producer’s accuracy was 88.0% and the user’s accuracy was 84.6%. The SWIR 2 channel as well as the mid-infrared burn index presented the highest importance among spectral variables computed by the RF average impurity decrease measure. Our results give support to further change detection studies regarding to suitable spectral channels and provided a useful foundation for savanna change detection using an object-based method applied to Landsat time series.