Soil sampling design and sampling techniques for soil properties monitoring – common difficulties related to forest soils

Mathematical models and statistical analysis are key instruments in soil science scientific research as they can describe and/or predict the current state of a soil system. These tools allow us to explore the behavior of soil related processes and properties as well as to generate new hypotheses for future experimentation. A good model and analysis of soil properties variations, that permit us to extract suitable conclusions and estimating spatially correlated variables at unsampled locations, is clearly dependent on the amount and quality of data and of the robustness techniques and estimators. On the other hand, the quality of data is obviously dependent from a competent data collection procedure and from a capable laboratory analytical work. Following the standard soil sampling protocols available, soil samples should be collected according to key points such as a convenient spatial scale, landscape homogeneity (or non-homogeneity), land color, soil texture, land slope, land solar exposition. Obtaining good quality data from forest soils is predictably expensive as it is labor intensive and demands many manpower and equipment both in field work and in laboratory analysis. Also, the sampling collection scheme that should be used on a data collection procedure in forest field is not simple to design as the sampling strategies chosen are strongly dependent on soil taxonomy. In fact, a sampling grid will not be able to be followed if rocks at the predicted collecting depth are found, or no soil at all is found, or large trees bar the soil collection. Considering this, a proficient design of a soil data sampling campaign in forest field is not always a simple process and sometimes represents a truly huge challenge. In this work, we present some difficulties that have occurred during two experiments on forest soil that were conducted in order to study the spatial variation of some soil physical-chemical properties. Two different sampling protocols were considered for monitoring two types of forest soils located in NW Portugal: umbric regosol and lithosol. Two different equipments for sampling collection were also used: a manual auger and a shovel. Both scenarios were analyzed and the results achieved have allowed us to consider that monitoring forest soil in order to do some mathematical and statistical investigations needs a sampling procedure to data collection compatible to established protocols but a pre-defined grid assumption often fail when the variability of the soil property is not uniform in space. In this case, sampling grid should be conveniently adapted from one part of the landscape to another and this fact should be taken into consideration of a mathematical procedure.

Demand response programs definition supported by clustering and classification techniques

The growing importance and influence of new resources connected to the power systems has caused many changes in their operation. Environmental policies and several well know advantages have been made renewable based energy resources largely disseminated. These resources, including Distributed Generation (DG), are being connected to lower voltage levels where Demand Response (DR) must be considered too. These changes increase the complexity of the system operation due to both new operational constraints and amounts of data to be processed. Virtual Power Players (VPP) are entities able to manage these resources. Addressing these issues, this paper proposes a methodology to support VPP actions when these act as a Curtailment Service Provider (CSP) that provides DR capacity to a DR program declared by the Independent System Operator (ISO) or by the VPP itself. The amount of DR capacity that the CSP can assure is determined using data mining techniques applied to a database which is obtained for a large set of operation scenarios. The paper includes a case study based on 27,000 scenarios considering a diversity of distributed resources in a 33 bus distribution network.

A Review of Operational Matrices and Spectral Techniques for Fractional Calculus

Recently, operational matrices were adapted for solving several kinds of fractional differential equations (FDEs). The use of numerical techniques in conjunction with operational matrices of some orthogonal polynomials, for the solution of FDEs on finite and infinite intervals, produced highly accurate solutions for such equations. This article discusses spectral techniques based on operational matrices of fractional derivatives and integrals for solving several kinds of linear and nonlinear FDEs. More precisely, we present the operational matrices of fractional derivatives and integrals, for several polynomials on bounded domains, such as the Legendre, Chebyshev, Jacobi and Bernstein polynomials, and we use them with different spectral techniques for solving the aforementioned equations on bounded domains. The operational matrices of fractional derivatives and integrals are also presented for orthogonal Laguerre and modified generalized Laguerre polynomials, and their use with numerical techniques for solving FDEs on a semi-infinite interval is discussed. Several examples are presented to illustrate the numerical and theoretical properties of various spectral techniques for solving FDEs on finite and semi-infinite intervals.

Adhesive selection for single lap bonded joints: Experimentation and advanced techniques for strength prediction

The integrity of multi-component structures is usually determined by their unions. Adhesive-bonding is often used over traditional methods because of the reduction of stress concentrations, reduced weight penalty, and easy manufacturing. Commercial adhesives range from strong and brittle (e.g., Araldite® AV138) to less strong and ductile (e.g., Araldite® 2015). A new family of polyurethane adhesives combines high strength and ductility (e.g., Sikaforce® 7888). In this work, the performance of the three above-mentioned adhesives was tested in single lap joints with varying values of overlap length (LO). The experimental work carried out is accompanied by a detailed numerical analysis by finite elements, either based on cohesive zone models (CZM) or the extended finite element method (XFEM). This procedure enabled detailing the performance of these predictive techniques applied to bonded joints. Moreover, it was possible to evaluate which family of adhesives is more suited for each joint geometry. CZM revealed to be highly accurate, except for largely ductile adhesives, although this could be circumvented with a different cohesive law. XFEM is not the most suited technique for mixed-mode damage growth, but a rough prediction was achieved.

Tensile fracture characterization of adhesive joints by standard and optical techniques

The use of adhesive joints has increased in recent decades due to its competitive features compared with traditional methods. This work aims to estimate the tensile critical strain energy release rate (GIC) of adhesive joints by the Double-Cantilever Beam (DCB) test. The J-integral is used since it enables obtaining the tensile Cohesive Zone Model (CZM) law. An optical measuring method was developed for assessing the crack tip opening (δn) and adherends rotation (θo). The proposed CZM laws were best approximated by a triangular shape for the brittle adhesive and a trapezoidal shape for the two ductile adhesives.

Some reflections on acquisition, processing and analysis of statistical data in forest soils

Beyond the classical statistical approaches (determination of basic statistics, regression analysis, ANOVA, etc.) a new set of applications of different statistical techniques has increasingly gained relevance in the analysis, processing and interpretation of data concerning the characteristics of forest soils. This is possible to be seen in some of the recent publications in the context of Multivariate Statistics. These new methods require additional care that is not always included or refered in some approaches. In the particular case of geostatistical data applications it is necessary, besides to geo-reference all the data acquisition, to collect the samples in regular grids and in sufficient quantity so that the variograms can reflect the spatial distribution of soil properties in a representative manner. In the case of the great majority of Multivariate Statistics techniques (Principal Component Analysis, Correspondence Analysis, Cluster Analysis, etc.) despite the fact they do not require in most cases the assumption of normal distribution, they however need a proper and rigorous strategy for its utilization. In this work, some reflections about these methodologies and, in particular, about the main constraints that often occur during the information collecting process and about the various linking possibilities of these different techniques will be presented. At the end, illustrations of some particular cases of the applications of these statistical methods will also be presented.

Characterization of the Toxicological Effects of Aminocarb on Rats: Hematological, Biochemical, and Histological Analyses

Aminocarb is a widely applied carbamate insecticide with action of controlling pests such as Lepidoptera and Coleoptera. In this study, subchronic effects on Wistar rats were investigated using hematological, biochemical, and histological techniques. Rats were exposed orally at sublethal levels of 10, 20, or 40 mg/kg body weight (groups A, B, and C, respectively) for 14 d. Hematological results revealed no statistical differences after 1 d of exposure but significant reduction in white blood cells detected after 7 d of exposure in group C, as well as, in all treated groups after 14 d of exposure. Biochemical data showed a decrease of acetylcholinesterase activity in all groups after 1 d of exposure with a return to normal after 7 and 14 d. Significant increase in alkaline phosphatase activity of rats exposed to aminocarb was noted after 7 d of treatment. The levels of triglycerides were also significantly decreased. The present investigation also showed a significant increase in content of serum urea and creatinine in animals from group A (14 d), and from groups B and C (7 and 14 d). Histological results demonstrated hemorrhagic focus on hepatic and renal parenchyma in all exposed groups. Taken together, the attained results were dose dependent and indicated adverse effects of aminocarb on hepatic and renal functions, as well as on immune responsiveness at sublethal tested doses.

Study of the Reliability of Statistical Timing Analysis for Real-Time Systems

Presented at 23rd International Conference on Real-Time Networks and Systems (RTNS 2015). 4 to 6, Nov, 2015, Main Track. Lille, France.

A new approach for multi-agent coalition formation and management in the scope of electricity markets

This paper presents a new methodology for the creation and management of coalitions in Electricity Markets. This approach is tested using the multi-agent market simulator MASCEM, taking advantage of its ability to provide the means to model and simulate VPP (Virtual Power Producers). VPPs are represented as coalitions of agents, with the capability of negotiating both in the market, and internally, with their members, in order to combine and manage their individual specific characteristics and goals, with the strategy and objectives of the VPP itself. The new features include the development of particular individual facilitators to manage the communications amongst the members of each coalition independently from the rest of the simulation, and also the mechanisms for the classification of the agents that are candidates to join the coalition. In addition, a global study on the results of the Iberian Electricity Market is performed, to compare and analyze different approaches for defining consistent and adequate strategies to integrate into the agents of MASCEM. This, combined with the application of learning and prediction techniques provide the agents with the ability to learn and adapt themselves, by adjusting their actions to the continued evolving states of the world they are playing in.

Factors influencing innovation decision making in Portuguese firms

There is an undeniable positive effect of innovation for both firms and the economy, with particular regards to the financial performance of firms. However, there is an important role of the decision making process for the allocation of resources to finance the innovation process. The aim of this paper is to understand what factors explain the decision making process in innovation activities of Portuguese firms. This is an empirical study, based on the modern theoretical approaches, which has relied on five key aspects for innovation: barriers, sources, cooperation, funding; and the decision making process. Primary data was collected through surveys to firms that have applied for innovation programmes within the Portuguese innovation agency. Univariate and multivariate statistical techniques were used. Our results suggest that the factors that mostly influence the Portuguese firms’ innovation decision-making processes are economical and financial (namely those related to profit increase and labour costs reduction).

User modeling and recommendation strategies for tourism

Mestrado em Engenharia Informática

Iron oxide/gold core/shell nanomagnetic probes and CdS biolabels for amplified electrochemical immunosensing of Salmonella typhimurium

There is an imminent need for rapid methods to detect and determine pathogenic bacteria in food products as alternatives to the laborious and time-consuming culture procedures. In this work, an electrochemical immunoassay using iron/gold core/shell nanoparticles (Fe@Au) conjugated with anti-Salmonella antibodies was developed. The chemical synthesis and functionalization of magnetic and gold-coated magnetic nanoparticles is reported. Fe@Au nanoparticles were functionalized with different self-assembled monolayers and characterized using ultraviolet-visible spectrometry, transmission electron microscopy, and voltammetric techniques. The determination of Salmonella typhimurium, on screen-printed carbon electrodes, was performed by square-wave anodic stripping voltammetry through the use of CdS nanocrystals. The calibration curve was established between 1×101 and 1×106 cells/mL and the limit of detection was 13 cells/mL. The developed method showed that it is possible to determine the bacteria in milk at low concentrations and is suitable for the rapid (less than 1 h) and sensitive detection of S. typhimurium in real samples. Therefore, the developed methodology could contribute to the improvement of the quality control of food samples.

Determination of total petroleum hydrocarbons in soil from different locations using infrared spectrophotometry and gas chromatography

Total petroleum hydrocarbons (TPH) are important environmental contaminants which are toxic to human and environmental receptors. Several analytical methods have been used to quantify TPH levels in contaminated soils, specifically through infrared spectrometry (IR) and gas chromatography (GC). Despite being two of the most used techniques, some issues remain that have been inadequately studied: a) applicability of both techniques to soils contaminated with two distinct types of fuel (petrol and diesel), b) influence of the soil natural organic matter content on the results achieved by various analytical methods, and c) evaluation of the performance of both techniques in analyses of soils with different levels of contamination (presumably non-contaminated and potentially contaminated). The main objectives of this work were to answer these questions and to provide more complete information about the potentials and limitations of GC and IR techniques. The results led us to the following conclusions: a) IR analysis of soils contaminated with petrol is not suitable due to volatilisation losses, b) there is a significant influence of organic matter in IR analysis, and c) both techniques demonstrated the capacity to accurately quantify TPH in soils, irrespective of their contamination levels.

Taxonomy of fundamental concepts of localization in cyber-physical and sensor networks

Localization is a fundamental task in Cyber-Physical Systems (CPS), where data is tightly coupled with the environment and the location where it is generated. The research literature on localization has reached a critical mass, and several surveys have also emerged. This review paper contributes on the state-of-the-art with the proposal of a new and holistic taxonomy of the fundamental concepts of localization in CPS, based on a comprehensive analysis of previous research works and surveys. The main objective is to pave the way towards a deep understanding of the main localization techniques, and unify their descriptions. Furthermore, this review paper provides a complete overview on the most relevant localization and geolocation techniques. Also, we present the most important metrics for measuring the accuracy of localization approaches, which is meant to be the gap between the real location and its estimate. Finally, we present open issues and research challenges pertaining to localization. We believe that this review paper will represent an important and complete reference of localization techniques in CPS for researchers and practitioners and will provide them with an added value as compared to previous surveys.

Drilling process of composite laminates – a tool based analysis

“Drilling of polymeric matrix composites structures”