A Global Forum on Ultramafic Ecosystems: From Ultramafic Ecology to Rehabilitation of Degraded Environments

The 9th International Conference on Serpentine Ecology (ICSE) was held in Tirana and Pogradec (Albania) from June 5 to 9, 2017. More than 100 delegates from 29 countries around the world gathered to present their research on recent advances in: (i) ultramafic soils, (ii) biogeochemistry, (iii) diversity of ultramafic flora, microflora and fauna, (iv) ecophysiology of ultramafic-adapted organisms, (v) interactions between ultramafic organisms and their ecology, (vi) nature rehabilitation of degraded ultramafic environments (resulting from mining activities), and (vii) the production of bio-based metals through agromining technology. Additionally, the ICSE featured the first symposium on ultramafic aquatic ecology and ecotoxicology. Albania has one of the most diverse ultramafic floras in Europe. During the conference delegates visited some of the most emblematic ultramafic sites in Albania as well as the first agromining field trial in Europe. Here, we present the major topics and provide some highlights of the 25 contributions in this Special Issue (Vol. 33 no.3 and 4)

Deep Learning Based Non-Intrusive Load Monitoring for a Three-Phase System

Non-Intrusive Load Monitoring (NILM) is a method to determine the power consumption of individual appliances from the overall power consumption measured by a single measurement device, which is usually the main meter. Increase in the adoption of smart meters has facilitated large scale implementation of NILM, which can provide information about individual loads to the utilities and consumers. This will lead to significant energy savings as well as better demand-side management. Researchers have proposed several methods and have successfully implemented NILM for residential sectors that have a single-phase supply. However, NILM has not been successfully implemented for industrial and commercial buildings that have a three-phase supply, due to several challenges. These buildings consume significant amount of power and implementing NILM to these buildings has the potential to yield substantial benefits. In this paper, we propose a novel deep learning-based approach to address some of the key challenges in implementing NILM for buildings that have a three-phase supply. Our approach introduces an ensemble learning technique that does not require training of multiple neural network models, which reduces the computational requirements and makes it economically feasible. The model was tested on a three-phase system that consists of both three- phase loads and single-phase loads. The results show significant improvement in load disaggregation compared to the existing methods and indicate its applicability

Food environment and diabetes mellitus in South Asia: A geospatial analysis of health outcome data

BACKGROUND: The global epidemic of type 2 diabetes mellitus (T2DM) renders its prevention a major public health priority. A key risk factor of diabetes is obesity and poor diets. Food environments have been found to influence people's diets and obesity, positing they may play a role in the prevalence of diabetes. Yet, there is scant evidence on the role they may play in the context of low- and middle-income countries (LMICs). We examined the associations of food environments on T2DM among adults and its heterogeneity by income and sex. METHODS AND FINDINGS: We linked individual health outcome data of 12,167 individuals from a network of health surveillance sites (the South Asia Biobank) to the density and proximity of food outlets geolocated around their homes from environment mapping survey data collected between 2018 and 2020 in Bangladesh and Sri Lanka. Density was defined as share of food outlets within 300 m from study participant's home, and proximity was defined as having at least 1 outlet within 100 m from home. The outcome variables include fasting blood glucose level, high blood glucose, and self-reported diagnosed diabetes. Control variables included demographics, socioeconomic status (SES), health status, healthcare utilization, and physical activities. Data were analyzed in ArcMap 10.3 and STATA 15.1. A higher share of fast-food restaurants (FFR) was associated with a 9.21 mg/dl blood glucose increase (95% CI: 0.17, 18.24; p < 0.05). Having at least 1 FFR in the proximity was associated with 2.14 mg/dl blood glucose increase (CI: 0.55, 3.72; p < 0.01). A 1% increase in the share of FFR near an individual's home was associated with 8% increase in the probability of being clinically diagnosed as a diabetic (average marginal effects (AMEs): 0.08; CI: 0.02, 0.14; p < 0.05). Having at least 1 FFR near home was associated with 16% (odds ratio [OR]: 1.16; CI: 1.01, 1.33; p < 0.05) and 19% (OR: 1.19; CI: 1.03, 1.38; p < 0.05) increases in the odds of higher blood glucose levels and diagnosed diabetes, respectively. The positive association between FFR density and blood glucose level was stronger among women than men, but the association between FFR proximity and blood glucose level was stronger among men as well as among those with higher incomes. One of the study's key limitations is that we measured exposure to food environments around residency geolocation; however, participants may source their meals elsewhere. CONCLUSIONS: Our results suggest that the exposure to fast-food outlets may have a detrimental impact on the risk of T2DM, especially among females and higher-income earners. Policies should target changes in the food environments to promote better diets and prevent T2DM

Food environments and obesity: a geospatial analysis of the South Asia Biobank, income and sex inequalities.

Introduction: In low-middle income countries (LMICs) the role of food environments on obesity has been understudied. We address this gap by 1) examining the effect of food environments on adults' body size (BMI, waist circumference) and obesity; 2) measuring the heterogeneity of such effects by income and sex. Methods: This cross-sectional study analysed South Asia Biobank surveillance and environment mapping data for 12,167 adults collected between 2018 and 2020 from 33 surveillance sites in Bangladesh and Sri Lanka. Individual-level data (demographic, socio-economic, and health characteristics) were combined with exposure to healthy and unhealthy food environments measured with geolocations of food outlets (obtained through ground-truth surveys) within 300 m buffer zones around participants' homes. Multivariate regression models were used to assess association of exposure to healthy and unhealthy food environments on waist circumference, BMI, and probability of obesity for the total sample and stratified by sex and income. Findings: The presence of a higher share of supermarkets in the neighbourhood was associated with a reduction in body size (BMI, β = - 3∙23; p < 0∙0001, and waist circumference, β = -5∙99; p = 0∙0212) and obesity (Average Marginal Effect (AME): -0∙18; p = 0∙0009). High share of fast-food restaurants in the neighbourhood was not significantly associated with body size, but it significantly increased the probability of obesity measured by BMI (AME: 0∙09; p = 0∙0234) and waist circumference (AME: 0∙21; p = 0∙0021). These effects were stronger among females and low-income individuals. Interpretation: The results suggest the availability of fast-food outlets influences obesity, especially among female and lower-income groups. The availability of supermarkets is associated with reduced body size and obesity, but their effects do not outweigh the role of fast-food outlets. Policies should target food environments to promote better diets and reduce obesity

Non-linear Autoregressive Neural Networks to Forecast Short-Term Solar Radiation for Photovoltaic Energy Predictions

Nowadays, green energy is considered as a viable solution to hinder CO2 emissions and greenhouse effects. Indeed, it is expected that Renewable Energy Sources (RES) will cover 40% of the total energy request by 2040. This will move forward decentralized and cooperative power distribution systems also called smart grids. Among RES, solar energy will play a crucial role. However, reliable models and tools are needed to forecast and estimate with a good accuracy the renewable energy production in short-term time periods. These tools will unlock new services for smart grid management. In this paper, we propose an innovative methodology for implementing two different non-linear autoregressive neural networks to forecast Global Horizontal Solar Irradiance (GHI) in short-term time periods (i.e. from future 15 to 120min). Both neural networks have been implemented, trained and validated exploiting a dataset consisting of four years of solar radiation values collected by a real weather station. We also present the experimental results discussing and comparing the accuracy of both neural networks. Then, the resulting GHI forecast is given as input to a Photovoltaic simulator to predict energy production in short-term time periods. Finally, we present the results of this Photovoltaic energy estimation discussing also their accuracy

Diversity and Functional Traits of Lichens in Ultramafic Areas: A Literature Based Worldwide Analysis Integrated by Field Data at the Regional Scale

While higher plant communities found on ultramafics are known to display peculiar characteristics, the distinguishability of any peculiarity in lichen communities is still a matter of contention. Other biotic or abiotic factors, rather than substrate chemistry, may contribute to differences in species composition reported for lichens on adjacent ultramafic and non-ultramafic areas. This work examines the lichen biota of ultramafics, at global and regional scales, with reference to species-specific functional traits. An updated world list of lichens on ultramafic substrates was analyzed to verify potential relationships between diversity and functional traits of lichens in different Köppen–Geiger climate zones. Moreover, a survey of diversity and functional traits in saxicolous communities on ultramafic and non-ultramafic substrates was conducted in Valle d’Aosta (North-West Italy) to verify whether a relationship can be detected between substrate and functional traits that cannot be explained by other environmental factors related to altitude. Analyses (unweighted pair group mean average clustering, canonical correspondence analysis, similarity-difference-replacement simplex approach) of global lichen diversity on ultramafic substrates (2314 reports of 881 taxa from 43 areas) displayed a zonal species distribution in different climate zones rather than an azonal distribution driven by the shared substrate. Accordingly, variations in the frequency of functional attributes reflected reported adaptations to the climate conditions of the different geographic areas. At the regional scale, higher similarity and lower species replacement were detected at each altitude, independent from the substrate, suggesting that altitude-related climate factors prevail over putative substrate–factors in driving community assemblages. In conclusion, data do not reveal peculiarities in lichen diversity or the frequency of functional traits in ultramafic areas

Low uptake of COVID-19 prevention behaviours and high socioeconomic impact of lockdown measures in South Asia: Evidence from a large-scale multi-country surveillance programme

Background South Asia has become a major epicentre of the COVID-19 pandemic. Understanding South Asians’ awareness, attitudes and experiences of early measures for the prevention of COVID-19 is key to improving the effectiveness and mitigating the social and economic impacts of pandemic responses at a critical time for the Region. Methods We assessed the knowledge, behaviours, health and socio-economic circumstances of 29,809 adult men and women, at 93 locations across four South Asian countries. Data were collected during the national lockdowns implemented from March to July 2020, and compared with data collected prior to the pandemic as part of an ongoing prospective surveillance initiative. Results Participants were 61% female, mean age 45.1 years. Almost half had one or more chronic disease, including diabetes (16%), hypertension (23%) or obesity (16%). Knowledge of the primary COVID-19 symptoms and transmission routes was high, but access to hygiene and personal protection resources was low (running water 63%, hand sanitisers 53%, paper tissues 48%). Key preventive measures were not widely adopted. Knowledge, access to, and uptake of COVID-19 prevention measures were low amongst people from disadvantaged socio-economic groups. Fifteen percent of people receiving treatment for chronic diseases reported loss of access to long-term medications; 40% reported symptoms suggestive of anxiety or depression. The prevalence of unemployment rose from 9.3% to 39.4% (P < 0.001), and household income fell by 52% (P < 0.001) during the lockdown. Younger people and those from less affluent socio-economic groups were most severely impacted. Sedentary time increased by 32% and inadequate fruit and vegetable intake increased by 10% (P < 0.001 for both), while tobacco and alcohol consumption dropped by 41% and 80%, respectively (P < 0.001), during the lockdown. Conclusions Our results identified important knowledge, access and uptake barriers to the prevention of COVID-19 in South Asia, and demonstrated major adverse impacts of the pandemic on chronic disease treatment, mental health, health-related behaviours, employment and household finances. We found important sociodemographic differences for impact, suggesting a widening of existing inequalities. Our findings underscore the need for immediate large-scale action to close gaps in knowledge and access to essential resources for prevention, along with measures to safeguard economic production and mitigate socio-economic impacts on the young and the poor

Ultramafic vegetation and soils in the circumboreal region of the Northern Hemisphere

The paper summarizes literature on climate, soil chemistry, vegetation and metal accumulation by plants found on ultramafic substrata in the circumboreal zone (sensu Takhtajan, Floristic regions of the world, 1986) of the Northern Hemisphere. We present a list of 50 endemic species and 18 ecotypes obligate to ultramafic soils from the circumboreal region of Holarctic, as well as 30 and 2 species of Ni and Zn hyperaccumulators, respectively. The number of both endemics and hyperaccumulators are markedly lower compared to that of the Mediterranean and tropical regions. The diversity of plant communities on ultramafics soils of the circumboral region is also described. The underlying causes for the differences of ultramafic flora between arctic, cold, cool temperate and Mediterranean and tropical regions are also discussed. © 2018, The Ecological Society of Japan

The Structure and Delivery of Police Use of Force Training: A German Case Study

The current study aims to investigate the current structure and delivery of police recruit training. Using a case study approach, we systematically observed a semester of police training that consisted of 30 h with a specific focus on police use of force training. Field notes and time-on-task data was analysed using an inductive approach. The results revealed, first, a lack of constructive alignment of the training modules and learning tasks within the training settings. Second, an adherence to traditional linear approaches to training resulting in high amounts of augmented instruction and feedback and a one-size-fits all approach to technical and tactical behaviour. Third, a non-efficient use of available training time with low amounts of engagement in representatively designed tasks that stimulated problem-solving processes. Based on these results we suggest that there is a need: (a) for police trainers and curriculum designers to align the objectives, practice structure and delivery of police training with the needs of police officers in the field (e.g. conflict resolution); (b) for police trainers to employ more learner-centred pedagogical approaches that account for individual action capabilities and resources, and allow for high amounts of training time with representatively designed training tasks; and (c) for senior managers of overall police training decision-makers to provide the necessary trainer education, in order to furnish trainers with the knowledge and tools to appropriately plan, deliver and reflect upon their practice in keeping with concept of constructive alignment