Hacia el manejo sostenible de los bosques de araar (Tetraclinis articulata (Vahl.) Mast.) en Túnez: modelos para las principales variables de árbol

The thuya (Tetraclinis articulata (Vahl.) Mast.) forests are one of the most important ecosystems in semiarid environments in north-western Africa, providing important economic profit and social services to local populations. However, lack of tools aiding sustainable management of these forests is detected. In the present work models for the main tree attributes as total height, crown diameter, height to crown base and stem form are developed for the species, using data from a net of plots installed in JbelLattrech region, in the NE Tunisia. Presented models allow characterizing the actual state and timber production of forests by using variables measured in typical forest inventories and conform a preliminary step for the future development of dynamic growth models.Los bosques de araar (Tetraclinis articulata (Vahl.) Mast.) constituyen uno de los ecosistemas más importantes de los ambientes semiáridos del noroeste de África, siendo además fuente de importantes beneficios económicos y servicios sociales a las poblaciones rurales. Pese a este interés, hasta el momento no se han desarrollado herramientas que faciliten la gesitón sostenible de estas masas forestales. En el presente trabajo se presentan modelos para los principales atributos de árbol individual: altura total, diámetro de copa, altura hasta la base de la copa y ecuación de perfil, desarrollados para la especie a partir de datos obtenidos en una red de parcelas permanentes instalada en la región de JbelLattrech, en el NE de Túnez. Los modelos presentados permiten caracterizar el estado y producción maderera actual de los bosques de thuya a partir de las variables medidas habitualmente en los inventarios forestales para la gestión, y constituyen además un paso preliminar para el desarrollo futuro de modelos dinámicos de crecimiento para la especie

Seasonal variations in scrotal circumference and semen characteristics of Naimi and Najdi rams in Saudi Arabia

In the present study, the authors analysed the effects of seasonal variations on the scrotal circumference and semen characteristics in two ram breeds in Saudi Arabia, namely Naimi and Najdi. Five rams of each breed were used in this experiment. Scrotal circumference and semen characteristics were evaluated in each ram twice a month throughout the year. Significant differences were observed in the scrotal circumference between various seasons. The largest production of semen was recorded mainly in spring, whereas the lowest semen volume was produced in summer. The pH of the semen was slightly alkaline and significantly lower in autumn than in spring. Furthermore, the highest value of the total number of sperm per ejaculate was observed in spring for both breeds. The results indicated that mass motility increased significantly in autumn compared with winter, spring, and summer. Progressive motility was significantly lower during the months of summer and spring. However, no significant differences were recorded between autumn and winter. Hence, the presence of significant seasonal variations in semen quantity and quality of Naimi and Najdi rams suggests the viability of increased utilization of rams in spring and autumn for semen collection and reproductive practices.Keywords: Mass motility, progressive motility, semen volume, sperm concentratio

Inverse Diffusion Theory of Photoacoustics

This paper analyzes the reconstruction of diffusion and absorption parameters in an elliptic equation from knowledge of internal data. In the application of photo-acoustics, the internal data are the amount of thermal energy deposited by high frequency radiation propagating inside a domain of interest. These data are obtained by solving an inverse wave equation, which is well-studied in the literature. We show that knowledge of two internal data based on well-chosen boundary conditions uniquely determines two constitutive parameters in diffusion and Schroedinger equations. Stability of the reconstruction is guaranteed under additional geometric constraints of strict convexity. No geometric constraints are necessary when $2n$ internal data for well-chosen boundary conditions are available, where $n$ is spatial dimension. The set of well-chosen boundary conditions is characterized in terms of appropriate complex geometrical optics (CGO) solutions.Comment: 24 page

Measuring farmland biodiversity

About one-third of the world’s land surface is used for farming, a fact that bears important implications for biodiversity. In Europe, for instance, an estimated 50 percent of all wild species are reliant on agricultural habitats, while agricultural productivity often depends on the presence or absence of particular species. Despite this close coupling, surprisingly little is known about the status and evolution of farmland biodiversity. A team of European and African researchers, hoping to fill this gap in information, recently invented and piloted a new toolbox called the BioBio indicator set, which measures 23 different instances of biodiversity across a variety of farm types and scales in Europe. Applications were also tested in Tunisia, Ukraine, and Uganda, where they proved a feasible starting point for adaptation to the agricultural context of different countries

Interior Regularity Estimates in High Conductivity Homogenization and Application

In this paper, uniform pointwise regularity estimates for the solutions of conductivity equations are obtained in a unit conductivity medium reinforced by a epsilon-periodic lattice of highly conducting thin rods. The estimates are derived only at a distance epsilon^{1+tau} (for some tau>0) away from the fibres. This distance constraint is rather sharp since the gradients of the solutions are shown to be unbounded locally in L^p as soon as p>2. One key ingredient is the derivation in dimension two of regularity estimates to the solutions of the equations deduced from a Fourier series expansion with respect to the fibres direction, and weighted by the high-contrast conductivity. The dependence on powers of epsilon of these two-dimensional estimates is shown to be sharp. The initial motivation for this work comes from imaging, and enhanced resolution phenomena observed experimentally in the presence of micro-structures. We use these regularity estimates to characterize the signature of low volume fraction heterogeneities in the fibred reinforced medium assuming that the heterogeneities stay at a distance epsilon^{1+tau} away from the fibres

Visual Twin for Pipeline Leak Detection

We describe a visual digital twin system to allow for both operation and training of a data-driven pipeline leak detection system. We show system design in terms of its data inputs and the software system which incorporates this data in real time. This system allows visualization of pipeline data and machine learning-driven leak detection in a pipeline sitting in a subsea context. The intended purpose of the system is to both train operators of the leak detection system in its use and also provide high situational awareness to those tasked with monitoring pipeline deployments. The visual digital twin system uses gaming engine technology to achieve high visual quality. We also construct a novel software system enhancement to incorporate live data streams into the gaming engine environment. This allows real-time driving of gaming engine visualization elements with which we may augment the gaming engine environment. In terms of visualization, we focus on addressing problems of large ranges of multiple scales and providing high situational awareness which minimize operator fatigue and cognitive load. We show how multiple camera views in combination with a convenient user interface can help to address these issues. We demonstrate a digital twin system for leak detection. We show its realtime operation in a gaming engine environment with the ability to instantaneously incorporate outside data sources into the visualizations. We demonstrate using simulated pipeline flow data from sensors such as pressure, temperature, etc. This is visualized in the context of a subsea pipeline on a sea floor. Given the large range of scales, we demonstrate how we can view both the full kilometer scale pipeline and smaller subsections in the context of specific sensor data streams. The overall system demonstrates a novel combination of advanced software systems which incorporates real-time data stream with visualization using a high-fidelity gaming engine. The data used represents a leak detection scenario where both operator training and situational awareness are key desired outcomes

Measuring Farmland Biodiversity

Despite close interaction between agriculture and biodiversity—farms cover one-third of the world’s land surface—little is empirically known about the ecological effects of different farming practices. About one-third of the world’s land surface is used for farming, a fact that bears important implications for biodiversity. In Europe, for instance, an estimated 50 percent of all wild species are reliant on agricultural habitats, while agricultural productivity often depends on the presence or absence of particular species. Despite this close coupling, surprisingly little is known about the status and evolution of farmland biodiversity. A team of European and African researchers, hoping to fill this gap in information, recently invented and piloted a new toolbox called the BioBio indicator set, which measures 23 different instances of biodiversity across a variety of farm types and scales in Europe. Applications were also tested in Tunisia, Ukraine, and Uganda, where they proved a feasible starting point for adaptation to the agricultural context of different countrie

Visual Twin for Pipeline Leak Detection

We describe a visual digital twin system to allow for both operation and training of a data-driven pipeline leak detection system. We show system design in terms of its data inputs and the software system which incorporates this data in real time. This system allows visualization of pipeline data and machine learning-driven leak detection in a pipeline sitting in a subsea context. The intended purpose of the system is to both train operators of the leak detection system in its use and also provide high situational awareness to those tasked with monitoring pipeline deployments. The visual digital twin system uses gaming engine technology to achieve high visual quality. We also construct a novel software system enhancement to incorporate live data streams into the gaming engine environment. This allows real-time driving of gaming engine visualization elements with which we may augment the gaming engine environment. In terms of visualization, we focus on addressing problems of large ranges of multiple scales and providing high situational awareness which minimize operator fatigue and cognitive load. We show how multiple camera views in combination with a convenient user interface can help to address these issues. We demonstrate a digital twin system for leak detection. We show its realtime operation in a gaming engine environment with the ability to instantaneously incorporate outside data sources into the visualizations. We demonstrate using simulated pipeline flow data from sensors such as pressure, temperature, etc. This is visualized in the context of a subsea pipeline on a sea floor. Given the large range of scales, we demonstrate how we can view both the full kilometer scale pipeline and smaller subsections in the context of specific sensor data streams. The overall system demonstrates a novel combination of advanced software systems which incorporates real-time data stream with visualization using a high-fidelity gaming engine. The data used represents a leak detection scenario where both operator training and situational awareness are key desired outcomes

Mathematical Modelling of Optical Coherence Tomography

In this chapter a general mathematical model of Optical Coherence Tomography (OCT) is presented on the basis of the electromagnetic theory. OCT produces high resolution images of the inner structure of biological tissues. Images are obtained by measuring the time delay and the intensity of the backscattered light from the sample considering also the coherence properties of light. The scattering problem is considered for a weakly scattering medium located far enough from the detector. The inverse problem is to reconstruct the susceptibility of the medium given the measurements for different positions of the mirror. Different approaches are addressed depending on the different assumptions made about the optical properties of the sample. This procedure is applied to a full field OCT system and an extension to standard (time and frequency domain) OCT is briefly presented.Comment: 28 pages, 5 figures, book chapte