Leaderless, mutualistic, and organic agricultural co-production as a socially-ecologically sustainable rural-urban practice. A local Italian experience, an international perspective to rethink the territory and the city

In an expanding world demanding more and more resources and causing interconnected crisis, the systemic nature of tragic social and ecological incidents is not (yet) widely acknowledged. The social and ecological limits of the current industry-based economic paradigm let us forerun the onset of possible emergencies to be possibly tackled through preventive design and positive transformation, where the rethinking of the territory, the city, and their supporting environments is necessarily involved. In this perspective, nurturing initiatives to ensure distributed food provision seems a good start in such a transformation, at least as a socio-economic sustainability tool and as a satisfier of basic human needs. We present an example of communal self-management for organic agricultural production, inspired to the model of Community-Supported Agriculture (CSA). This project was started in the urban sprawl of massively industrialised North-Eastern Italy by committed individuals and grassroot groups, already active in discourses on ecological sustainability, social equity, social and solidarity economy, transition and post-growth. From individual-to-collective self-determination and bottom-up initiative potentials through food plans and other tools to be participatorily defined with all the actors of a given area, a CSA can represent the trigger of a virtuous paradigmatic shift in more or less institutional policies for the maintenance, regeneration, and strengthening of territory and urban environments

Mmwave Beam Management in Urban Vehicular Networks

Millimeter-wave (mmwave) communication represents a potential solution to capacity shortage in vehicular networks. However, effective beam alignment between senders and receivers requires accurate knowledge of the vehicles' position for fast beam steering, which is often impractical to obtain in real time. We address this problem by leveraging the traffic signals regulating vehicular mobility: as an example, we may coordinate beams with red traffic lights, as they correspond to higher vehicle densities and lower speeds. To evaluate our intuition, we propose a tractable, yet accurate, mmwave communication model accounting for both the distance and the heading of vehicles being served. Using such a model, we optimize the beam design and define a low-complexity, heuristic strategy. For increased realism, we consider as reference scenario a large-scale, real-world mobility trace of vehicles in Luxembourg. The results show that our approach closely matches the optimum and always outperforms static beam design based on road topology alone. Remarkably, it also yields better performance than solutions based on real-time mobility information

Graph-based Model for Beam Management in Mmwave Vehicular Networks

Mmwave bands are being widely touted as a very promising option for future 5G networks, especially in enabling such networks to meet highly demanding rate requirements. Accordingly, the usage of these bands is also receiving an increasing interest in the context of 5G vehicular networks, where it is expected that connected cars will soon need to transmit and receive large amounts of data. Mmwave communications, however, require the link to be established using narrow directed beams, to overcome harsh propagation conditions. The advanced antenna systems enabling this also allow for a complex beam design at the base station, where multiple beams of different widths can be set up. In this work, we focus on beam management in an urban vehicular network, using a graph-based approach to model the system characteristics and the existing constraints. In particular, unlike previous work, we formulate the beam design problem as a maximum-weight matching problem on a bipartite graph with conflicts, and then we solve it using an efficient heuristic algorithm. Our results show that our approach easily outperforms advanced methods based on clustering algorithms

Acclimatization across space and time in the effects of temperature on mortality: a time-series analysis

Background: Climate change has increased the days of unseasonal temperature. Although many studies have examined the association between temperature and mortality, few have examined the timing of exposure where whether this association varies depending on the exposure month even at the same temperature. Therefore, we investigated monthly differences in the effects of temperature on mortality in a study comprising a wide range of weather and years, and we also investigated heterogeneity among regions. Methods: We analyzed 38,005,616 deaths from 148 cities in the U.S. from 1973 through 2006. We fit city specific Poisson regressions to examine the effect of temperature on mortality separately for each month of the year, using penalized splines. We used cluster analysis to group cities with similar weather patterns, and combined results across cities within clusters using meta-smoothing. Results: There was substantial variation in the effects of the same temperature by month. Heat effects were larger in the spring and early summer and cold effects were larger in late fall. In addition, heat effects were larger in clusters where high temperatures were less common, and vice versa for cold effects. Conclusions: The effects of a given temperature on mortality vary spatially and temporally based on how unusual it is for that time and location. This suggests changes in variability of temperature may be more important for health as climate changes than changes of mean temperature. More emphasis should be placed on warnings targeted to early heat/cold temperature for the season or month rather than focusing only on the extremes. Electronic supplementary material The online version of this article (doi:10.1186/1476-069X-13-89) contains supplementary material, which is available to authorized users

Mmwave Beam Management in Urban Vehicular Networks

Millimeter-wave (mmwave) communication repre- sents a potential solution to capacity shortage in vehicular net- works. However, effective beam alignment between senders and receivers requires accurate knowledge of the vehicles’ position for fast beam steering, which is often impractical to obtain in real time. We address this problem by leveraging the traffic signals regulating vehicular mobility: as an example, we may coordinate beams with red traffic lights, as they correspond to higher vehicle densities and lower speeds. To evaluate our intuition, we propose a tractable, yet accurate, mmwave communication model accounting for both the distance and the heading of vehicles being served. Using such a model, we optimize the beam design and define a low-complexity, heuristic strategy. For increased realism, we consider as reference scenario a large-scale, real- world mobility trace of vehicles in Luxembourg. The results show that our approach closely matches the optimum and always outperforms static beam design based on road topology alone. Remarkably, it also yields better performance than solutions based on real-time mobility information

When Meta-Surfaces Meet Users: Optimization of Smart Radio Environments in 6G Sub-THz Communications

We consider a smart radio environment where meta-surfaces are employed to improve the performance of wireless networks working at sub-THz frequencies. To this end, we propose a comprehensive mathematical channel model, taking into account both the ability of the meta-surfaces to redirect the impinging signal towards a desired direction, and the signal reflection due to large objects. We show how the design of both the meta-surface and the transmitter precoder influences the network throughput. Furthermore, we compare several algorithms to optimize the effect of the meta-surfaces in a realistic scenario. As a result, a simpler algorithm that associates network users and meta-surfaces provides a performance comparable to more complex numerical optimization methods. Simulation results suggest how many users are supported in the designed system

Short Term Effects of Particle Exposure on Hospital Admissions in the Mid-Atlantic States: A Population Estimate

Background: Many studies report significant associations between PM2.5 (particulate matter <2.5 micrometers) and hospital admissions. These studies mostly rely on a limited number of monitors which introduces exposure error, and excludes rural and suburban populations from locations where monitors are not available, reducing generalizability and potentially creating selection bias. Methods: Using prediction models developed by our group, daily PM2.5 exposure was estimated across the Mid-Atlantic (Washington D.C., and the states of Delaware, Maryland, New Jersey, Pennsylvania, Virginia, New York and West Virginia). We then investigated the short-term effects of PM2.5 exposures on emergency hospital admissions of the elderly in the Mid-Atlantic region.We performed case-crossover analysis for each admission type, matching on day of the week, month and year and defined the hazard period as lag01 (a moving average of day of admission exposure and previous day exposure). Results: We observed associations between short-term exposure to PM2.5 and hospitalization for all outcomes examined. For example, for every 10-µg/m3 increase in short-term PM 2.5 there was a 2.2% increase in respiratory diseases admissions (95% CI = 1.9 to 2.6), and a 0.78% increase in cardiovascular disease (CVD) admission rate (95% CI = 0.5 to 1.0). We found differences in risk for CVD admissions between people living in rural and urban areas. For every10-µg/m3 increase in PM 2.5 exposure in the ‘rural’ group there was a 1.0% increase (95% CI = 0.6 to 1.5), while for the ‘urban’ group the increase was 0.7% (95% CI = 0.4 to 1.0). Conclusions: Our findings showed that PM2.5 exposure was associated with hospital admissions for all respiratory, cardio vascular disease, stroke, ischemic heart disease and chronic obstructive pulmonary disease admissions. In addition, we demonstrate that our AOD (Aerosol Optical Depth) based exposure models can be successfully applied to epidemiological studies investigating the health effects of short-term exposures to PM2.5

Effects of airborne pollutants on mitochondrial DNA Methylation

Background: Mitochondria have small mitochondrial DNA (mtDNA) molecules independent from the nuclear DNA, a separate epigenetic machinery that generates mtDNA methylation, and are primary sources of oxidative-stress generation in response to exogenous environments. However, no study has yet investigated whether mitochondrial DNA methylation is sensitive to pro-oxidant environmental exposures. Methods: We sampled 40 male participants (20 high-, 20 low-exposure) from each of three studies on airborne pollutants, including investigations of steel workers exposed to metal-rich particulate matter (measured as PM1) in Brescia, Italy (Study 1); gas-station attendants exposed to air benzene in Milan, Italy (Study 2); and truck drivers exposed to traffic-derived Elemental Carbon (EC) in Beijing, China (Study 3). We have measured DNA methylation from buffy coats of the participants. We measured methylation by bisulfite-Pyrosequencing in three mtDNA regions, i.e., the transfer RNA phenylalanine (MT-TF), 12S ribosomal RNA (MT-RNR1) gene and “D-loop” control region. All analyses were adjusted for age and smoking. Results: In Study 1, participants with high metal-rich PM1 exposure showed higher MT-TF and MT-RNR1 methylation than low-exposed controls (difference = 1.41, P = 0.002); MT-TF and MT-RNR1 methylation was significantly associated with PM1 exposure (beta = 1.35, P = 0.025); and MT-RNR1 methylation was positively correlated with mtDNA copy number (r = 0.36; P = 0.02). D-loop methylation was not associated with PM1 exposure. We found no effects on mtDNA methylation from air benzene (Study 2) and traffic-derived EC exposure (Study 3). Conclusions: Mitochondrial MT-TF and MT-RNR1 DNA methylation was associated with metal-rich PM1 exposure and mtDNA copy number. Our results suggest that locus-specific mtDNA methylation is correlated to selected exposures and mtDNA damage. Larger studies are needed to validate our observations