Measurements of formation, degradation, and sinking velocity of diatom aggregates from laboratory studies performed at 15 °C and 4 °C

Most deep ocean carbon flux profiles show low and almost constant fluxes of particulate organic carbon (POC) in the deep ocean. However, the reason for the non-changing POC fluxes at depths is unknown. This study presents direct measurements of formation, degradation, and sinking velocity of diatom aggregates from laboratory studies performed at 15 °C and 4 °C during a three-week experiment. The average carbon-specific respiration rate during the experiment was 0.12 ± 0.03 at 15 °C, and decreased 3.5-fold when the temperature was lowered to 4 °C. No direct influence of temperature on aggregate sinking speed was observed. Using the remineralisation rate measured at 4 °C and an average particle sinking speed of 150 m d**-1, calculated carbon fluxes were similar to those collected in deep ocean sediment traps from a global data set, indicating that temperature plays a major role for deep ocean fluxes of POC.

Copepod abundance and fecal pellet production, sinking rate, and degradation in samples obtained during Leg 7 of Galathea 3 cruise 2006

The vertical distribution of copepods, fecal pellets and the fecal pellet production of copepods were measured at seven stations across the Southern Indian Ocean from productive areas off South Africa to oligotrophic waters off Northern Australia during October/November 2006. We quantified export of copepod fecal pellet from surface waters and how much was retained. Furthermore, the potential impact of Oncaea spp. and harpacticoid copepods on fecal pellets degradation was evaluated and found to be regional substantial. The highest copepod abundance and fecal pellet production was found in the western nutrient-rich stations close to South Africa and the lowest at the central oligotrophic stations. The in situ copepod fecal pellet production varied between 1 and 1,000 µg C/m**3/day. At all stations, the retention of fecal pellets in the upper 400 m of the water column was more than 99% and the vertical export of fecal pellets was low (<0.02 mg/m**2/day).

Impact of changing carbonate chemistry, temperature, and salinity on growth and test degradation of the benthic foraminifer Ammonia aomoriensis

The present study investigated the combined effects of ocean acidification, temperature, and salinity on growth and test degradation of Ammonia aomoriensis. This species is one of the dominant benthic foraminifera in near-coastal habitats of the southwestern Baltic Sea that can be particularly sensitive to changes in seawater carbonate chemistry. To assess potential responses to ocean acidification and climate change, we performed a fully crossed experiment involving three temperatures (8, 13, and 18°C), three salinities (15, 20, and 25) and four pCO2 levels (566, 1195, 2108, and 3843 µatm) for six weeks. Our results highlight a sensitive response of A. aomoriensis to undersaturated seawater with respect to calcite. The specimens continued to grow and increase their test diameter in treatments with pCO2 <1200 µatm, when Omega calc >1. Growth rates declined when pCO2 exceeded 1200 µatm (Omega calc <1). A significant reduction in test diameter and number of tests due to dissolution was observed below a critical Omega calc of 0.5. Elevated temperature (18°C) led to increased Omega calc, larger test diameter, and lower test degradation. Maximal growth was observed at 18°C. No significant relationship was observed between salinity and test growth. Lowered and undersaturated Omega calc, which results from increasing pCO2 in bottom waters, may cause a significant future decline of the population density of A. aomoriensis in its natural environment. At the same time, this effect might be partially compensated by temperature rise due to global warming.

Optimization of InGaAsN(Sb)/GaAs quantum dots for optical emission at 1.55 µm with low optical degradation

Low optical degradation in GaInAsN(Sb)/GaAs quantum dots (QDs) p–i–n structures emitting up to 1.55 μm is presented in this paper. We obtain emission at different energies by means of varying N content from 1 to 4%. The samples show a low photoluminescence (PL) intensity degradation of only 1 order of magnitude when they are compared with pure InGaAs QD structures, even for an emission wavelength as large as 1.55 μm. The optimization studies of these structures for emission at 1.55 μm are reported in this work. High surface density and homogeneity in the QD layers are achieved for 50% In content by rapid decrease in the growth temperature after the formation of the nanostructures. Besides, the effect of N and Sb incorporation in the redshift and PL intensity of the samples is studied by post-growth rapid thermal annealing treatments. As a general conclusion, we observe that the addition of Sb to QD with low N mole fraction is more efficient to reach 1.55 μm and high PL intensity than using high N incorporation in the QD. Also, the growth temperature is determined to be an important parameter to obtain good emission characteristics. Finally, we report room temperature PL emission of InGaAsN(Sb)/GaAs at 1.4 μm.

Real-time reliability test for a CPV module based on a power degradation model

Models based on degradation are powerful and useful tools to evaluate the reliability of those devices in which failure happens because of degradation in the performance parameters. This paper presents a procedure for assessing the reliability of concentrator photovoltaic (CPV) modules operating outdoors in real-time conditions. With this model, the main reliability functions are predicted. This model has been applied to a real case with a module composed of GaAs single-junction solar cells and total internal reflection (TIR) optics

Degradation in seawater of structural adhesives for hybrid fibre-metal laminated materials

The adhesives used for applications in marine environments are subject to particular chemical conditions, which are mainly characterised by an elevated chlorine ion content and intermittent wetting/drying cycles, among others.These conditions can limit the use of adhesives due to the degradation processes that they experience. In this work, the chemical degradation of two different polymers, polyurethane and vinylester, was studied in natural seawater under immersion for different periods of time.The diffusion coefficients and concentration profiles of water throughout the thickness of the adhesiveswere obtained.Microstructural changes in the polymer due to the action of water were observed by SEM, and the chemical degradation of the polymer was monitored with the Fourier transform infrared spectroscopy (FTIR) and differential scanning calorimetry (DSC). The degradation of the mechanical properties of the adhesive was determined by creep tests withMixed Cantilever Beam (MCB) specimens at different temperatures. After 180 days of immersion of the specimens, it was concluded that the J-integral value (depending on the strain) implies a loss of stiffness of 51% and a decrease in the failure load of 59% for the adhesive tested.

On-site tests for the detection of potential induced degradation in modules

This paper presents different test alternatives which can be used on-site in a PV installation to detect potential induced degradation (PID) in modules. The testing procedures proposed are: thermal imaging; electroluminescence imaging; open circuit voltage measurements; operating voltage measurements; IV curve measurements; and dark IV curve measurements. Advantages and disadvantages of each test are reported.

Microstructure and mechanical properties degradation at high temperature of tungsten alloys processed by forging

One of the challenges of science and engineering nowadays is to develop new ways to supply energy in a sustainable and ecological mode. The fussion energy could be the final answer but a myriad of problems must be solved previously.

Mechanical Degradation of Tungsten Alloys at Extreme Temperatures in Vacuum and Oxidation Atmospheres

Mechanical degradation of tungsten alloys at extreme temperatures in vacuum and oxidation atmospheres.

A visual framework to accelerate knowledge discovery based on dimensionality reduction minimizing degradation of quality

Tradicionalmente, el uso de técnicas de análisis de datos ha sido una de las principales vías para el descubrimiento de conocimiento oculto en grandes cantidades de datos, recopilados por expertos en diferentes dominios. Por otra parte, las técnicas de visualización también se han usado para mejorar y facilitar este proceso. Sin embargo, existen limitaciones serias en la obtención de conocimiento, ya que suele ser un proceso lento, tedioso y en muchas ocasiones infructífero, debido a la dificultad de las personas para comprender conjuntos de datos de grandes dimensiones. Otro gran inconveniente, pocas veces tenido en cuenta por los expertos que analizan grandes conjuntos de datos, es la degradación involuntaria a la que someten a los datos durante las tareas de análisis, previas a la obtención final de conclusiones. Por degradación quiere decirse que los datos pueden perder sus propiedades originales, y suele producirse por una reducción inapropiada de los datos, alterando así su naturaleza original y llevando en muchos casos a interpretaciones y conclusiones erróneas que podrían tener serias implicaciones. Además, este hecho adquiere una importancia trascendental cuando los datos pertenecen al dominio médico o biológico, y la vida de diferentes personas depende de esta toma final de decisiones, en algunas ocasiones llevada a cabo de forma inapropiada. Ésta es la motivación de la presente tesis, la cual propone un nuevo framework visual, llamado MedVir, que combina la potencia de técnicas avanzadas de visualización y minería de datos para tratar de dar solución a estos grandes inconvenientes existentes en el proceso de descubrimiento de información válida. El objetivo principal es hacer más fácil, comprensible, intuitivo y rápido el proceso de adquisición de conocimiento al que se enfrentan los expertos cuando trabajan con grandes conjuntos de datos en diferentes dominios. Para ello, en primer lugar, se lleva a cabo una fuerte disminución en el tamaño de los datos con el objetivo de facilitar al experto su manejo, y a la vez preservando intactas, en la medida de lo posible, sus propiedades originales. Después, se hace uso de efectivas técnicas de visualización para representar los datos obtenidos, permitiendo al experto interactuar de forma sencilla e intuitiva con los datos, llevar a cabo diferentes tareas de análisis de datos y así estimular visualmente su capacidad de comprensión. De este modo, el objetivo subyacente se basa en abstraer al experto, en la medida de lo posible, de la complejidad de sus datos originales para presentarle una versión más comprensible, que facilite y acelere la tarea final de descubrimiento de conocimiento. MedVir se ha aplicado satisfactoriamente, entre otros, al campo de la magnetoencefalografía (MEG), que consiste en la predicción en la rehabilitación de lesiones cerebrales traumáticas (Traumatic Brain Injury (TBI) rehabilitation prediction). Los resultados obtenidos demuestran la efectividad del framework a la hora de acelerar y facilitar el proceso de descubrimiento de conocimiento sobre conjuntos de datos reales. ABSTRACT Traditionally, the use of data analysis techniques has been one of the main ways of discovering knowledge hidden in large amounts of data, collected by experts in different domains. Moreover, visualization techniques have also been used to enhance and facilitate this process. However, there are serious limitations in the process of knowledge acquisition, as it is often a slow, tedious and many times fruitless process, due to the difficulty for human beings to understand large datasets. Another major drawback, rarely considered by experts that analyze large datasets, is the involuntary degradation to which they subject the data during analysis tasks, prior to obtaining the final conclusions. Degradation means that data can lose part of their original properties, and it is usually caused by improper data reduction, thereby altering their original nature and often leading to erroneous interpretations and conclusions that could have serious implications. Furthermore, this fact gains a trascendental importance when the data belong to medical or biological domain, and the lives of people depends on the final decision-making, which is sometimes conducted improperly. This is the motivation of this thesis, which proposes a new visual framework, called MedVir, which combines the power of advanced visualization techniques and data mining to try to solve these major problems existing in the process of discovery of valid information. Thus, the main objective is to facilitate and to make more understandable, intuitive and fast the process of knowledge acquisition that experts face when working with large datasets in different domains. To achieve this, first, a strong reduction in the size of the data is carried out in order to make the management of the data easier to the expert, while preserving intact, as far as possible, the original properties of the data. Then, effective visualization techniques are used to represent the obtained data, allowing the expert to interact easily and intuitively with the data, to carry out different data analysis tasks, and so visually stimulating their comprehension capacity. Therefore, the underlying objective is based on abstracting the expert, as far as possible, from the complexity of the original data to present him a more understandable version, thus facilitating and accelerating the task of knowledge discovery. MedVir has been succesfully applied to, among others, the field of magnetoencephalography (MEG), which consists in predicting the rehabilitation of Traumatic Brain Injury (TBI). The results obtained successfully demonstrate the effectiveness of the framework to accelerate and facilitate the process of knowledge discovery on real world datasets.

Observed degradation in photovoltaic plants affected by hot-spots

A number of findings have shown that the test procedures currently available to determine the reliability and durability of photovoltaic (PV) modules are insufficient to detect certain problems. To improve these procedures, ongoing research into the actual performance of the modules in the field is required. However, scientific literature contains but few references to field studies of defective modules. This article studies two different localized heating phenomena affecting the PV modules of two large-scale PV plants in Spain. The first problem relates to weak solder joints whilst the second is due to microcracks on the module cells. For both cases, the cause is identified, and consideration is given with regard to the effect on performance, the potential deterioration over time, and a way to detect the problems identified. The findings contained in this paper will prove to be of considerable interest to maintenance personnel at large-scale PV plants and also to those responsible for setting module quality standards and specifications, and even the PV module manufacturers themselves.