Contested landscapes: territorial conflicts and the production of different ruralities in Brazil

ABSTRACT

From the perspective of Brazilian agrarian geography, the conflicts generated by land tenure disputes have as protagonists the families of the Landless Workers’ Movement (Movimento dos Trabalhadores Rurais Sem Terra), traditional landowners, and agribusiness corporations. In this article, we present a reflection on land conflicts and the spatial and territorial production of latifundia, peasant smallholders, and large-scale agribusiness through studies of the landscapes of two municipalities in the state of São Paulo. Among the various tools for analysing territorial disputes, Google Earth can be used for local, regional, and international comparative studies of how landscapes have been transformed. Informed by traditional research, the article analyses a diversity of photographs, from satellite to field shots, as evidence of landscapes that express conflicting social relations in disputes over different models of social and territorial development.     

Indoor air quality in Portuguese schools: levels and sources of pollutants

Indoor air quality (IAQ) parameters in 73 primary classrooms in Porto were examined for the purpose of assessing levels of volatile organic compounds (VOCs), aldehydes, particulate matter, ventilation rates and bioaerosols within and between schools, and potential sources. Levels of VOCs, aldehydes, PM_2.5, PM₁₀, bacteria and fungi, carbon dioxide (CO₂), carbon monoxide, temperature and relative humidity were measured indoors and outdoors and a walkthrough survey was performed concurrently. Ventilation rates were derived from CO₂ and occupancy data. Concentrations of CO₂ exceeding 1000 ppm were often encountered, indicating poor ventilation. Most VOCs had low concentrations (median of individual species <5 μg/m³) and were below the respective WHO guidelines. Concentrations of particulate matter and culturable bacteria were frequently higher than guidelines/reference values. The variability of VOCs, aldehydes, bioaerosol concentrations, and CO₂ levels between schools exceeded the variability within schools. These findings indicate that IAQ problems may persist in classrooms where pollutant sources exist and classrooms are poorly ventilated; source control strategies (related to building location, occupant behavior, maintenance/cleaning activities) are deemed to be the most reliable for the prevention of adverse health consequences in children in schools.     

Self-assembled silver nanoislands formed on glass surface via out-diffusion for multiple usages in SERS applications

We demonstrate that silver nanoisland film self-assembled on the surface of silver-containing glass in the course of thermal processing in hydrogen is capable to detect 10⁻⁷ M concentration of rhodamine 6G in water using surface enhanced Raman spectroscopy (SERS) technique. The film can be multiply restored on the same glass substrate via annealing of the glass in hydrogen. We showed that the film can be self-assembled after as much as ten circles of the substrate cleaning followed by annealing. The proposed technique of the silver nanoisland film formation enables multiple usage of the same glass substrate in SERS experiments.     

Compact DSOP and Partial DSOP Forms

Given a Boolean function f on n variables, a Disjoint Sum-of-Products (DSOP) of f is a set of products (ANDs) of subsets of literals whose sum (OR) equals f, such that no two products cover the same minterm of f. DSOP forms are a special instance of partial DSOPs, i.e. the general case where a subset of minterms must be covered exactly once and the other minterms (typically corresponding to don’t care conditions of f) can be covered any number of times. We discuss finding DSOPs and partial DSOPs with a minimal number of products, a problem theoretically connected with various properties of Boolean functions and practically relevant in the synthesis of digital circuits. Finding an absolute minimum is hard, in fact we prove that the problem of absolute minimization of partial DSOPs is NP-hard. Therefore it is crucial to devise a polynomial time heuristic that compares favorably with the known minimization tools. To this end we develop a further piece of theory starting from the definition of the weight of a cube c as a functions of the number of fragments induced on other cubes by the selection of c, and show how cube weights can be exploited for building a class of minimization heuristics for DSOP and partial DSOP synthesis. A set of experiments conducted on major benchmark functions show that our method, with a family of variants, always generates better results than the ones of previous heuristics, including the method based on a BDD representation of f.     

A deep learning approach for the forensic evaluation of sexual assault

Despite the existence of patterns able to discriminate between consensual and non-consensual intercourse, the relevance of genital lesions in the corroboration of a legal rape complaint is currently under debate in many countries. The testimony of the physicians when assessing these lesions has been questioned in court due to several factors (e.g., a lack of comprehensive knowledge of lesions, wide spectrum of background area, among others). Therefore, it is relevant to provide automated tools to support the decision process in an objective manner. In this work, we evaluate the performance of state-of-the-art deep learning architectures for the forensic assessment of sexual assault. We propose a deep architecture and learning strategy to tackle the class imbalance on deep learning using ranking. The proposed methodologies achieved the best results when compared with handcrafted feature engineering and with other deep architectures.     

An approach to calibrate incentives for continuity of supply in the Spanish electricity distribution system

This paper proposes an approach to calibrate incentives for continuity of supply in electricity distribution in Spain. This approach consists on the estimation of the impact of continuity of supply improvements on distribution network costs. For this purpose, distribution costs resulting from different continuity of supply requirements are computed by a reference network model (RNM). The results obtained from the RNM are used to estimate a cost-function that considers continuity of supply a cost driver for distribution costs. This methodology is applied to three Spanish areas of service (an urban one, a semi-urban one and a rural one) in such a way that differences in distribution costs caused by the characteristics of the area type can be taken into account. The analysis indicated that distribution costs are more sensitive to continuity of supply improvements in rural areas of service. It also demonstrated that the incentive for reducing number of service interruptions should be higher than the incentive for reducing duration of service interruptions. Finally, the current Spanish incentive scheme for continuity of supply was analyzed under the perspective of the proposed approach.     

Putative Circulating MicroRNAs Are Able to Identify Patients with Mitral Valve Prolapse and Severe Regurgitation

Mitral valve prolapse (MVP) associated with severe mitral regurgitation is a debilitating disease with no pharmacological therapies available. MicroRNAs (miRNA) represent an emerging class of circulating biomarkers that have never been evaluated in MVP human plasma. Our aim was to identify a possible miRNA signature that is able to discriminate MVP patients from healthy subjects (CTRL) and to shed light on the putative altered molecular pathways in MVP. We evaluated a plasma miRNA profile using Human MicroRNA Card A followed by real-time PCR validations. In addition, to assess the discriminative power of selected miRNAs, we implemented a machine learning analysis. MiRNA profiling and validations revealed that miR-140-3p, 150-5p, 210-3p, 451a, and 487a-3p were significantly upregulated in MVP, while miR-223-3p, 323a-3p, 340-5p, and 361-5p were significantly downregulated in MVP compared to CTRL (p ≤ 0.01). Functional analysis identified several biological processes possible linked to MVP. In addition, machine learning analysis correctly classified MVP patients from CTRL with high accuracy (0.93) and an area under the receiving operator characteristic curve (AUC) of 0.97. To the best of our knowledge, this is the first study performed on human plasma, showing a strong association between miRNAs and MVP. Thus, a circulating molecular signature could be used as a first-line, fast, and cheap screening tool for MVP identification.