A national coastal erosion risk assessment for Scotland

The geography of Scotland, with a highly undulating hinterland, long and indented coastline, together with a large number of islands, means that much social and economic activity is largely located at the coast. The importance of the coast is further highlighted by the large number of ecosystem services derived from the coast. The threat posed by climate change, particularly current and future sea level rise, is of considerable concern and the associated coastal erosion and coastal flooding has the potential to have a substantial effect on the socioeconomic activity of the whole country. Currently, the knowledge base of coastal erosion is poor, which serves to hinder the current and future management of the coast. This research reported here aimed to establish four key aspects of coastal erosion within Scotland: the physical susceptibility of the coast to erosion; the assets exposed to coastal erosion; the vulnerability of communities to coastal erosion; and the coastal erosion risk to those communities. Coastal erosion susceptibility was modelled here within a GIS, using data for ground elevation, rockhead elevation, wave exposure and proximity to the open coast. Combining these data produced the Underlying Physical Susceptibility Model (UPSM), in the form of a 50 m2 raster of national coverage. The Coastal Erosion Susceptibility Model (CESM) was produced with the addition of sediment supply and coastal defence data, which then moderates the outputs of the UPSM. Asset data for dwellings, key assets, transport infrastructure, historic assets, and natural assets were used along with the UPSM and CESM to assess their degree of exposure to coastal erosion. A Coastal Erosion Vulnerability Model (CEVM) was produced using Experian Mosaic Scotland (a geodemographic classification which identifies 44 different social groups within Scotland) to classify populations based upon 11 vulnerability variables. Dwellings were assigned a CESM and CEVM score in order to establish their coastal erosion risk. This research demonstrated that the issue of coastal erosion will impact on a relatively low number of properties compared to those impacted by flooding (both coastal and fluvial) as many dwellings are already protected by coastal defences. There is therefore, a considerable future liability, and great pressure for coastal defences to be maintained and upgraded in their current form. The use of the CEVM is a novel inclusion within a coastal erosion assessment for Scotland. Use of the CEVM established that coastal erosion risk is not distributed equally amongst the Scottish coastal population and highlighted that risk can be reduced by either reducing exposure or reducing vulnerability. Thus far in Scotland, reducing exposure has been the primary management approach, which has a number of implications with regards social justice. This research identified the existing data gaps that should be addressed by future research in order to further improve coastal management in Scotland. Future research should focus on assessing historical coastal change rates on a national scale, improve modelling of national scale wave exposure, enhance the information held about current coastal defences and, determine the direct and indirect economic cost associated with the loss of different asset types. It is also necessary to clarify the social justice implications of using adaptation approaches to manage coastal erosion as well as establishing a method to communicate the susceptibility, exposure, vulnerability and risk aspects whilst minimising the potential negative impacts (e.g. property blight) of releasing such information.

Pain assessment in surgical patients with impaired cognition

Pain is considered the 5th vital sign and its measurement/assessment and records are required and must be systematic. Ineffective pain management involves complications in clinical status of patients, longer hospitalization times and higher costs with health. In the surgical patient with impaired cognition, hetero measurements should be made, based on behavioural and physiological indicators. We used to determine the efficacy and efficiency of the Observer Scale, the Abbey Pain Scale and Pain Assessment in Advanced Dementia (PAINAD). Our study is an applied, non-experimental, quantitative, descriptive and analytical research. The data collection instrument consisted of patients’ sociodemographic and clinical data, the Observer Scale, the Abbey Pain Scale (Rodrigues, 2013) and PAINAD (Batalha et al., 2012). We assessed pain at an early phase and 45 minutes after an intervention for its relief. The sample is non-probabilistic for convenience, consisting of 76 surgical patients with impaired cognition, admitted to the surgery services of a central hospital, aged between 38 and 96 years. There was a positive correlation between the results of the three scales, most evident in the initial evaluation. Pain intensity in the same patient is higher when assessed with PAINAD (OM = 2.16) and lower when assessed with the Observer Scale (OM = 1.78). The most effective and efficient scale is PAINAD. Due to the small sample size, we suggest confirmatory studies so that the results can be generalized.

Assessment of iodine intake and related cognitive function impairments in elementary schoolchildren from Terceira Island, Azores (Portugal)

Dissertação de Mestrado, Ciências Biomédicas, 28 de Junho de 2016, Universidade dos Açores.

Predicting Pollicipes pollicipes (Crustacea: Cirripedia) abundance on intertidal rocky shores of SW Portugal: a multi-scale approach based on a simple fetch-based wave exposure index

Understanding and predicting patterns of distribution and abundance of marine resources is important for con- servation and management purposes in small-scale artisanal fisheries and industrial fisheries worldwide. The goose barnacle (Pollicipes pollicipes) is an important shellfish resource and its distribution is closely related to wave exposure at different spatial scales. We modelled the abundance (percent coverage) of P. pollicipes as a function of a simple wave exposure index based on fetch estimates from digitized coastlines at different spatial scales. The model accounted for 47.5% of the explained deviance and indicated that barnacle abundance increases non-linearly with wave exposure at both the smallest (metres) and largest (kilometres) spatial scales considered in this study. Distribution maps were predicted for the study region in SW Portugal. Our study suggests that the relationship between fetch-based exposure indices and P. pollicipes percent cover may be used as a simple tool for providing stakeholders with information on barnacle distribution patterns. This information may improve assessment of harvesting grounds and the dimension of exploitable areas, aiding management plans and support- ing decision making on conservation, harvesting pressure and surveillance strategies for this highly appreciated and socio- economically important marine resource.

Measuring attachment to life in old age: the Portuguese version of the Positive Valuation of Life Scale (Positive VOL)

Purpose This study aims to present the psychometric properties of the Portuguese version of the Positive Valuation of Life Scale (Lawton et al. in J Aging Ment Healt 13:3–31, 2001). Method Sample included 207 community-dwelling elders (129 women; MAge = 77.2 years, SD = 7.5). The data collection included the translated and adapted Portuguese version of Positive Valuation of Life Scale, Life Satisfac- tion Index Z, Meaning in Life Questionnaire and Geriatric Depression Scale. Results From exploratory factor analysis, two factors emerged, existential beliefs and perceived control, ex- plaining 49 % of the total variance. Both factors were positively related with meaning in life and life satisfaction and negatively related with depression (p\0.05). The values obtained for internal consistency for the total scale and for each subscale were good (a [ 0.75). Conclusion The Portuguese version of Positive VOL Scale represents a reliable and valid measure to capture the subjective experience of attachment to one’s life. The two-factor structure is an update to Lawton’s previous work and in line with findings obtained in the USA (Dennis et al. in What is valuation of life for frail community-dwelling older adults: factor structure and criterion validity of the VOL, Thomas Jefferson University, Center for Applied Research on Aging and Health Research, 2005) and Japan (Nakagawa et al. in Shinrigaku Kenkyu 84:37–46, 2013). Future research is required to investigate VOL predictors and the potential changes toward the end of the life span.

Exploring the potential role of allostatic load biomarkers in risk assessment of patients presenting with depressive symptoms

Background: Depression is a major health problem worldwide and the majority of patients presenting with depressive symptoms are managed in primary care. Current approaches for assessing depressive symptoms in primary care are not accurate in predicting future clinical outcomes, which may potentially lead to over or under treatment. The Allostatic Load (AL) theory suggests that by measuring multi-system biomarker levels as a proxy of measuring multi-system physiological dysregulation, it is possible to identify individuals at risk of having adverse health outcomes at a prodromal stage. Allostatic Index (AI) score, calculated by applying statistical formulations to different multi-system biomarkers, have been associated with depressive symptoms. Aims and Objectives: To test the hypothesis, that a combination of allostatic load (AL) biomarkers will form a predictive algorithm in defining clinically meaningful outcomes in a population of patients presenting with depressive symptoms. The key objectives were: 1. To explore the relationship between various allostatic load biomarkers and prevalence of depressive symptoms in patients, especially in patients diagnosed with three common cardiometabolic diseases (Coronary Heart Disease (CHD), Diabetes and Stroke). 2 To explore whether allostatic load biomarkers predict clinical outcomes in patients with depressive symptoms, especially in patients with three common cardiometabolic diseases (CHD, Diabetes and Stroke). 3 To develop a predictive tool to identify individuals with depressive symptoms at highest risk of adverse clinical outcomes. Methods: Datasets used: ‘DepChron’ was a dataset of 35,537 patients with existing cardiometabolic disease collected as a part of routine clinical practice. ‘Psobid’ was a research data source containing health related information from 666 participants recruited from the general population. The clinical outcomes for 3 both datasets were studied using electronic data linkage to hospital and mortality health records, undertaken by Information Services Division, Scotland. Cross-sectional associations between allostatic load biomarkers calculated at baseline, with clinical severity of depression assessed by a symptom score, were assessed using logistic and linear regression models in both datasets. Cox’s proportional hazards survival analysis models were used to assess the relationship of allostatic load biomarkers at baseline and the risk of adverse physical health outcomes at follow-up, in patients with depressive symptoms. The possibility of interaction between depressive symptoms and allostatic load biomarkers in risk prediction of adverse clinical outcomes was studied using the analysis of variance (ANOVA) test. Finally, the value of constructing a risk scoring scale using patient demographics and allostatic load biomarkers for predicting adverse outcomes in depressed patients was investigated using clinical risk prediction modelling and Area Under Curve (AUC) statistics. Key Results: Literature Review Findings. The literature review showed that twelve blood based peripheral biomarkers were statistically significant in predicting six different clinical outcomes in participants with depressive symptoms. Outcomes related to both mental health (depressive symptoms) and physical health were statistically associated with pre-treatment levels of peripheral biomarkers; however only two studies investigated outcomes related to physical health. Cross-sectional Analysis Findings: In DepChron, dysregulation of individual allostatic biomarkers (mainly cardiometabolic) were found to have a non-linear association with increased probability of co-morbid depressive symptoms (as assessed by Hospital Anxiety and Depression Score HADS-D≥8). A composite AI score constructed using five biomarkers did not lead to any improvement in the observed strength of the association. In Psobid, BMI was found to have a significant cross-sectional association with the probability of depressive symptoms (assessed by General Health Questionnaire GHQ-28≥5). BMI, triglycerides, highly sensitive C - reactive 4 protein (CRP) and High Density Lipoprotein-HDL cholesterol were found to have a significant cross-sectional relationship with the continuous measure of GHQ-28. A composite AI score constructed using 12 biomarkers did not show a significant association with depressive symptoms among Psobid participants. Longitudinal Analysis Findings: In DepChron, three clinical outcomes were studied over four years: all-cause death, all-cause hospital admissions and composite major adverse cardiovascular outcome-MACE (cardiovascular death or admission due to MI/stroke/HF). Presence of depressive symptoms and composite AI score calculated using mainly peripheral cardiometabolic biomarkers was found to have a significant association with all three clinical outcomes over the following four years in DepChron patients. There was no evidence of an interaction between AI score and presence of depressive symptoms in risk prediction of any of the three clinical outcomes. There was a statistically significant interaction noted between SBP and depressive symptoms in risk prediction of major adverse cardiovascular outcome, and also between HbA1c and depressive symptoms in risk prediction of all-cause mortality for patients with diabetes. In Psobid, depressive symptoms (assessed by GHQ-28≥5) did not have a statistically significant association with any of the four outcomes under study at seven years: all cause death, all cause hospital admission, MACE and incidence of new cancer. A composite AI score at baseline had a significant association with the risk of MACE at seven years, after adjusting for confounders. A continuous measure of IL-6 observed at baseline had a significant association with the risk of three clinical outcomes- all-cause mortality, all-cause hospital admissions and major adverse cardiovascular event. Raised total cholesterol at baseline was associated with lower risk of all-cause death at seven years while raised waist hip ratio- WHR at baseline was associated with higher risk of MACE at seven years among Psobid participants. There was no significant interaction between depressive symptoms and peripheral biomarkers (individual or combined) in risk prediction of any of the four clinical outcomes under consideration. Risk Scoring System Development: In the DepChron cohort, a scoring system was constructed based on eight baseline demographic and clinical variables to predict the risk of MACE over four years. The AUC value for the risk scoring system was modest at 56.7% (95% CI 55.6 to 57.5%). In Psobid, it was not possible to perform this analysis due to the low event rate observed for the clinical outcomes. Conclusion: Individual peripheral biomarkers were found to have a cross-sectional association with depressive symptoms both in patients with cardiometabolic disease and middle-aged participants recruited from the general population. AI score calculated with different statistical formulations was of no greater benefit in predicting concurrent depressive symptoms or clinical outcomes at follow-up, over and above its individual constituent biomarkers, in either patient cohort. SBP had a significant interaction with depressive symptoms in predicting cardiovascular events in patients with cardiometabolic disease; HbA1c had a significant interaction with depressive symptoms in predicting all-cause mortality in patients with diabetes. Peripheral biomarkers may have a role in predicting clinical outcomes in patients with depressive symptoms, especially for those with existing cardiometabolic disease, and this merits further investigation.

How teachers' perceptions affect the academic and language assessment of immigrant children

Recent research evidences inconsistencies in teachers' practice regarding skills assessment of L2 students. Scientific evidence supports that less experienced teachers have lower orientation toward multiple task-tests for non-native students. Research questions: Whether school teachers as having different teaching training and unequal teaching experience with non-native students perceive differently a four-skills scale. Purpose of the study: This study intends to analyse the importance degree between the four skills/tasks: reading, writing, speaking and listening, in the perspective of school teachers. Method: 77 teachers, aged 32-62, with (and without) experience in teaching and adapting materials for immigrant students, divided into six groups according to their scientific domain. Assessment tools included a scale for judgement of four academic tasks adapted from the original “Inventory of Undergraduate and Graduate Level: Reading, Writing, Speaking and Listening Tasks (Rosenfeld, Leung & Ottman, 2001). Main Findings: 1) different degrees of importance attributed by teachers on tasks that should be included in academic and language test for immigrant students; 2) perceptions of teachers are determined by predictors in this order: scientific domain, experience with multicultural classes and lower prediction from teaching service and age; 3) different results between american and portuguese samples answering the same questionnaire.

Transmission electron tomography: quality assessment and enhancement for three-dimensional imaging of nanostructures

Nanotechnology has revolutionised humanity's capability in building microscopic systems by manipulating materials on a molecular and atomic scale. Nan-osystems are becoming increasingly smaller and more complex from the chemical perspective which increases the demand for microscopic characterisation techniques. Among others, transmission electron microscopy (TEM) is an indispensable tool that is increasingly used to study the structures of nanosystems down to the molecular and atomic scale. However, despite the effectivity of this tool, it can only provide 2-dimensional projection (shadow) images of the 3D structure, leaving the 3-dimensional information hidden which can lead to incomplete or erroneous characterization. One very promising inspection method is Electron Tomography (ET), which is rapidly becoming an important tool to explore the 3D nano-world. ET provides (sub-)nanometer resolution in all three dimensions of the sample under investigation. However, the fidelity of the ET tomogram that is achieved by current ET reconstruction procedures remains a major challenge. This thesis addresses the assessment and advancement of electron tomographic methods to enable high-fidelity three-dimensional investigations. A quality assessment investigation was conducted to provide a quality quantitative analysis of the main established ET reconstruction algorithms and to study the influence of the experimental conditions on the quality of the reconstructed ET tomogram. Regular shaped nanoparticles were used as a ground-truth for this study. It is concluded that the fidelity of the post-reconstruction quantitative analysis and segmentation is limited, mainly by the fidelity of the reconstructed ET tomogram. This motivates the development of an improved tomographic reconstruction process. In this thesis, a novel ET method was proposed, named dictionary learning electron tomography (DLET). DLET is based on the recent mathematical theorem of compressed sensing (CS) which employs the sparsity of ET tomograms to enable accurate reconstruction from undersampled (S)TEM tilt series. DLET learns the sparsifying transform (dictionary) in an adaptive way and reconstructs the tomogram simultaneously from highly undersampled tilt series. In this method, the sparsity is applied on overlapping image patches favouring local structures. Furthermore, the dictionary is adapted to the specific tomogram instance, thereby favouring better sparsity and consequently higher quality reconstructions. The reconstruction algorithm is based on an alternating procedure that learns the sparsifying dictionary and employs it to remove artifacts and noise in one step, and then restores the tomogram data in the other step. Simulation and real ET experiments of several morphologies are performed with a variety of setups. Reconstruction results validate its efficiency in both noiseless and noisy cases and show that it yields an improved reconstruction quality with fast convergence. The proposed method enables the recovery of high-fidelity information without the need to worry about what sparsifying transform to select or whether the images used strictly follow the pre-conditions of a certain transform (e.g. strictly piecewise constant for Total Variation minimisation). This can also avoid artifacts that can be introduced by specific sparsifying transforms (e.g. the staircase artifacts the may result when using Total Variation minimisation). Moreover, this thesis shows how reliable elementally sensitive tomography using EELS is possible with the aid of both appropriate use of Dual electron energy loss spectroscopy (DualEELS) and the DLET compressed sensing algorithm to make the best use of the limited data volume and signal to noise inherent in core-loss electron energy loss spectroscopy (EELS) from nanoparticles of an industrially important material. Taken together, the results presented in this thesis demonstrates how high-fidelity ET reconstructions can be achieved using a compressed sensing approach.

Validation of the Flexibility of Responses to Self-Critical Thoughts Scale (FoReST) in a clinical population

Background: The Flexibility of Responses to Self-Critical Thoughts Scale (FoReST) is a questionnaire that was developed to assess whether people can be psychologically flexible when experiencing critical thoughts about themselves. This measure could have important application for evaluating third wave therapies such as Acceptance and Commitment Therapy (ACT) and Compassion Focused therapy (CFT). This study investigated the validity (concurrent, predictive and incremental), internal consistency and factor structure of the FoReST in a sample of people experiencing mental health difficulties. Method: A total of 132 individuals attending Primary Care and Community Mental Health Teams within NHS Greater Glasgow and Clyde (NHS GGC) and Psychological Therapy Teams within NHS Lanarkshire participated in this study. Participants completed a battery of assessments that included the FoReST and related measures of similar constructs (psychological flexibility, self-compassion and self-criticism) and measures of mental health and well-being. A cross-sectional correlational design was used. Results: An Exploratory factor analysis described an interpretable 2-factor structure within the items of the FoReST: unworkable action and experiential avoidance. The FoReST demonstrated good internal consistency ( = .89). Concurrent validity was supported through moderate to strong correlations with similar measures and moderate correlations with other mental health and well-being outcomes. Conclusions: The FoReST appears to be a valid assessment measure for using with individuals experiencing mental health difficulties. This new measure will be of use for practitioners using ACT, CFT and those integrating both, to help monitor the process of change in flexibility and self-critical thinking across therapy. Further longitudinal studies are required to assess the test-retest reliability of the FoReST.

A Belief rule-based environmental responsibility assessment system for small and medium-sized enterprises

Various environmental management systems, standards and tools are being created to assist companies to become more environmental friendly. However, not all the enterprises have adopted environmental policies in the same scale and range. Additionally, there is no existing guide to help them determine their level of environmental responsibility and subsequently, provide support to enable them to move forward towards environmental responsibility excellence. This research proposes the use of a Belief Rule-Based approach to assess an enterprise’s level commitment to environmental issues. The Environmental Responsibility BRB assessment system has been developed for this research. Participating companies will have to complete a structured questionnaire. An automated analysis of their responses (using the Belief Rule-Based approach) will determine their environmental responsibility level. This is followed by a recommendation on how to progress to the next level. The recommended best practices will help promote understanding, increase awareness, and make the organization greener. BRB systems consist of two parts: Knowledge Base and Inference Engine. The knowledge base in this research is constructed after an in-depth literature review, critical analyses of existing environmental performance assessment models and primarily guided by the EU Draft Background Report on "Best Environmental Management Practice in the Telecommunications and ICT Services Sector". The reasoning algorithm of a selected Drools JBoss BRB inference engine is forward chaining, where an inference starts iteratively searching for a pattern-match of the input and if-then clause. However, the forward chaining mechanism is not equipped with uncertainty handling. Therefore, a decision is made to deploy an evidential reasoning and forward chaining with a hybrid knowledge representation inference scheme to accommodate imprecision, ambiguity and fuzzy types of uncertainties. It is believed that such a system generates well balanced, sensible and Green ICT readiness adapted results, to help enterprises focus on making improvements on more sustainable business operations.

A non-contrast self-navigated 3-dimensional MR technique for aortic root and vascular access route assessment in the context of transcatheter aortic valve replacement: proof of concept.

OBJECTIVES: Due to the high prevalence of renal failure in transcatheter aortic valve replacement (TAVR) candidates, a non-contrast MR technique is desirable for pre-procedural planning. We sought to evaluate the feasibility of a novel, non-contrast, free-breathing, self-navigated three-dimensional (SN3D) MR sequence for imaging the aorta from its root to the iliofemoral run-off in comparison to non-contrast two-dimensional-balanced steady-state free-precession (2D-bSSFP) imaging. METHODS: SN3D [field of view (FOV), 220-370 mm(3); slice thickness, 1.15 mm; repetition/echo time (TR/TE), 3.1/1.5 ms; and flip angle, 115°] and 2D-bSSFP acquisitions (FOV, 340 mm; slice thickness, 6 mm; TR/TE, 2.3/1.1 ms; flip angle, 77°) were performed in 10 healthy subjects (all male; mean age, 30.3 ± 4.3 yrs) using a 1.5-T MRI system. Aortic root measurements and qualitative image ratings (four-point Likert-scale) were compared. RESULTS: The mean effective aortic annulus diameter was similar for 2D-bSSFP and SN3D (26.7 ± 0.7 vs. 26.1 ± 0.9 mm, p = 0.23). The mean image quality of 2D-bSSFP (4; IQR 3-4) was rated slightly higher (p = 0.03) than SN3D (3; IQR 2-4). The mean total acquisition time for SN3D imaging was 12.8 ± 2.4 min. CONCLUSIONS: Our results suggest that a novel SN3D sequence allows rapid, free-breathing assessment of the aortic root and the aortoiliofemoral system without administration of contrast medium. KEY POINTS: • The prevalence of renal failure is high among TAVR candidates. • Non-contrast 3D MR angiography allows for TAVR procedure planning. • The self-navigated sequence provides a significantly reduced scanning time.

Environmental assessment of proton exchange membrane fuel cell platinum catalyst recycling

International audience

RISKS TO FOOD AVAILABILITY AND ACCESS FROM CLIMATE POLICIES: AN INTEGRATED ASSESSMENT OF REGIONAL FOOD AVAILABILITY AND ACCESS WITH ALTERNATIVE CLIMATE MITIGATION STRATEGIES TO 2050

Although mitigating GHG emissions is necessary to reduce the overall negative climate change impacts on crop yields and agricultural production, certain mitigation measures may generate unintended consequences to food availability and access due to land use competition and economic burden of mitigation. Prior studies have examined the co-impacts on food availability and global producer prices caused by alternative climate policies. More recent studies have looked at the reduction in total caloric intake driven by both changing income and changing food prices under one specific climate policy. However, due to inelastic calorie demand, consumers’ well-being are likely further reduced by increased food expenditures. Built upon existing literature, my dissertation explores how alternative climate policy designs might adversely affect both caloric intake and staple food budget share to 2050, by using the Global Change Assessment Model (GCAM) and a post-estimated metric of food availability and access (FAA). My dissertation first develop a set of new metrics and methods to explore new perspectives of food availability and access under new conditions. The FAA metric consists of two components, the fraction of GDP per capita spent on five categories of staple food and total caloric intake relative to a reference level. By testing the metric against alternate expectations of the future, it shows consistent results with previous studies that economic growth dominates the improvement of FAA. As we increase our ambition to achieve stringent climate targets, two policy conditions tend to have large impacts on FAA driven by competing land use and increasing food prices. Strict conservation policies leave the competition between bioenergy and agriculture production on existing commercial land, while pricing terrestrial carbon encourages large-scale afforestation. To avoid unintended outcomes to food availability and access for the poor, pricing land emissions in frontier forests has the advantage of selecting more productive land for agricultural activities compared to the full conservation approach, but the land carbon price should not be linked to the price of energy system emissions. These results are highly relevant to effective policy-making to reduce land use change emissions, such as the Reduced Emissions from Deforestation and Forest Degradation (REDD).

Adaptação de um instrumento de rastreio cognitivo, o MoCA (Montreal Cognitive Assessment) para população cabo-verdiana

Dissertação de Mestrado, Neurociências Cognitivas e Neuropsicologia, Faculdade de Ciências Humanas e Sociais, Universidade do Algarve, 2016

Local productive arrangements for biodiesel production in Brazil: Environmental assessment of small-holders integrated oleaginous crops management.

Sustainability assessments were carried out in small-holders? farms in four territories where productive arrangements have been organized for production of minor oleagi- nous crops under the Brazilian biodiesel program. The study aimed at checking local impacts of the biodiesel productive chains at the rural establishment scale, and pro- moting the environmental performance of the selected farms, henceforth proposed as sustainable management demonstration units. Assessments were carried out with the APOIA-NovoRural system, which integrates 62 objective and quantitative indicators re- lated to five sustainability dimensions: i) Landscape Ecology, ii) Environmental Quality (Atmosphere, Water and Soil), iii) Socio-cultural Values, iv) Economic Values and v) Management and Administration. The main results point out that, in general, the eco- logical dimensions of sustainability, that is, the Landscape Ecology and Atmosphere, Water, and Soil quality indicators, show adequate field conditions, seemingly not yet negatively affected by increases in chemical inputs and natural resources use predicted as important potential impacts of the agro-energy sector. The Economic Values indica- tors have been favorably influenced in the studied farms, due to a steadier demand and improved prices for the oleaginous crops. On the other hand, valuable positive conse- quences expected for favoring farmers? market insertion, such as improved Socio-cultural Values and Management & Administration indicators, are still opportunities to be ma-terialized. The Environmental Management Reports issued to the farmers, based on the presented sustainability assessment procedures, offer valuable documentation and com-munication means for consolidating the organizational influence of the local productive arrangements studied. These productive arrangements were shown to be determinant for the selection of crop associations and diversification, as well as for the provision of technical assistance and the stabilization of demand - conditions that promote value aggregation and income improvements, favoring small-holders? insertion in the market. More importantly, these locally organized productive arrangements have been shown to strongly influence the valorization of natural resources and environmental assets, which are fundamental if sustainable rural development is to take place under the emerging agro-energy scenario.