Assessing the suitability of the minimum capture size and protection regimes in the gooseneck barnacle shellfishery

The suitability of a total-length-based, minimum capture-size and different protection regimes was investigated for the gooseneck barnacle Pollicipes pollicipes shellfishery in N Spain. For this analysis, individuals that were collected from 10 sites under different fishery protection regimes (permanently open, seasonally closed, and permanently closed) were used. First, we applied a non-parametric regression model to explore the relationship between the capitulum Rostro-Tergum (RT) size and the Total Length (TL). Important heteroskedastic disturbances were detected for this relationship, demon- strating a high variability of TL with respect to RT. This result substantiates the unsuitability of a TL-based minimum size by means of a mathematical model. Due to these disturbances, an alternative growth- based minimum capture size of 26.3 mm RT (23 mm RC) was estimated using the first derivative of a Kernel-based non-parametric regression model for the relationship between RT and dry weight. For this purpose, data from the permanently protected area were used to avoid bias due to the fishery. Second, the size-frequency distribution similarity was computed using a MDS analysis for the studied sites to evaluate the effectiveness of the protection regimes. The results of this analysis indicated a positive effect of the permanent protection, while the effect of the seasonal closure was not detected. This result needs to be interpreted with caution because the current harvesting based on a potentially unsuitable mini- mum capture size may dampen the efficacy of the seasonal protection regime.

Niche conservatism in non-native birds in Europe: niche unfilling rather than niche expansion

Aim Niche conservatism, or the extent to which niches are conserved across space and time, is of special concern for the study of non-native species as it underlies predictions of invasion risk. Based on the occurrence of 28 non-native birds in Europe, we assess to what extent Grinnellian realized niches are conserved during invasion, formulate hypotheses to explain the variation in observed niche changes and test how well species distribution models can predict non-native bird occurrence in Europe. Location Europe. Methods To quantify niche changes, a recent method that applies kernel smoothers to densities of species occurrence in a gridded environmental space was used. This corrects for differences in the availability of environments between study areas and allows discrimination between 'niche expansion' into environments new to the species and 'niche unfilling', whereby the species only partially fills its niche in the invaded range. Predictions of non-native bird distribution in Europe were generated using several distribution modelling techniques. Results Niche overlap between native and non-native bird populations is low, but niche changes are smaller for species having a higher propagule pressure and that were introduced longer ago. Non-native birds in Europe occupy a subset of the environments they inhabit in their native ranges. Niche expansion into novel environments is rare for most species, allowing species distribution models to accurately predict invasion risk. Main conclusions Because of the recent nature of most bird introductions, species occupy only part of the suitable environments available in the invaded range. This signals that apart from purely ecological factors, patterns of niche conservatism may also be contingent on population-specific historical factors. These results also suggest that many claims of niche differences may be due to a partial filling of the native niche in the invaded range and thus do not represent true niche changes.

Measuring ecological niche overlap from occurrence and spatial environmental data

1. Aim - Concerns over how global change will influence species distributions, in conjunction with increased emphasis on understanding niche dynamics in evolutionary and community contexts, highlight the growing need for robust methods to quantify niche differences between or within taxa. We propose a statistical framework to describe and compare environmental niches from occurrence and spatial environmental data.¦2. Location - Europe, North America, South America¦3. Methods - The framework applies kernel smoothers to densities of species occurrence in gridded environmental space to calculate metrics of niche overlap and test hypotheses regarding niche conservatism. We use this framework and simulated species with predefined distributions and amounts of niche overlap to evaluate several ordination and species distribution modeling techniques for quantifying niche overlap. We illustrate the approach with data on two well-studied invasive species.¦4. Results - We show that niche overlap can be accurately detected with the framework when variables driving the distributions are known. The method is robust to known and previously undocumented biases related to the dependence of species occurrences on the frequency of environmental conditions that occur across geographic space. The use of a kernel smoother makes the process of moving from geographical space to multivariate environmental space independent of both sampling effort and arbitrary choice of resolution in environmental space. However, the use of ordination and species distribution model techniques for selecting, combining and weighting variables on which niche overlap is calculated provide contrasting results.¦5. Main conclusions - The framework meets the increasing need for robust methods to quantify niche differences. It is appropriate to study niche differences between species, subspecies or intraspecific lineages that differ in their geographical distributions. Alternatively, it can be used to measure the degree to which the environmental niche of a species or intraspecific lineage has changed over time.

Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study

Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.

Extensions of discrete triangular distributions and boundary bias in kernel estimation for discrete functions

Asymmetric discrete triangular distributions are introduced in order to extend the symmetric ones serving for discrete associated kernels in the nonparametric estimation for discrete functions. The extension from one to two orders around the mode provides a large family of discrete distributions having a finite support. Establishing a bridge between Dirac and discrete uniform distributions, some different shapes are also obtained and their properties are investigated. In particular, the mean and variance are pointed out. Applications to discrete kernel estimators are given with a solution to a boundary bias problem. (C) 2010 Elsevier B.V. All rights reserved.

Meat Quality of Lambs Fed on Palm Kernel Meal, a By-product of Biodiesel Production

This study aimed to establish the optimum level of palm kernel meal in the diet of Santa Ines lambs based on the sensorial characteristics and fatty acid profile of the meat. We used 32 lambs with a starting age of 4 to 6 months and mean weight of 22 2.75 kg, kept in individual stalls. The animals were fed with Tifton-85 hay and a concentrate mixed with 0.0, 6.5, 13.0 or 19.5% of palm kernel meal based on the dry mass of the complete diet. These levels formed the treatments. Confinement lasted 80 days and on the last day the animals were fasted and slaughtered. After slaughter, carcasses were weighed and sectioned longitudinally, along the median line, into two antimeres. Half-carcasses were then sliced between the 12th and 13th ribs to collect the loin (longissimus dorsi), which was used to determine the sensorial characteristics and fatty acid profile of the meat. For sensorial evaluation, samples of meat were given to 54 judges who evaluated the tenderness, juiciness, appearance, aroma and flavor of the meat using a hedonic scale. Fatty acids were determined by gas chromatography. The addition of palm kernel meal to the diet had no effect on the sensorial characteristics of meat juiciness, appearance, aroma or flavor. However, tenderness showed a quadratic relationship with the addition of the meal to the diet. The concentration of fatty acids C12:0, C14:0 and C16:0 increased with the addition of palm kernel meal, as did the sum of medium-chain fatty acids and the atherogenicity index. Up to of 19.5% of the diet of Santa Ines lambs can be made up of palm kernel meal without causing significant changes in sensorial characteristics. However, the fatty acid profile of the meat was altered.

Population balance modelling of granulation with a physically based coalescence kernel

It was previously published by the authors that granules can either coalesce through Type I (when granules coalesce by viscous dissipation in the surface liquid layer before their surfaces touch) or Type II (when granules are slowed to a halt during rebound, after their surfaces have made contact) (AIChE J. 46 (3) (2000) 529). Based on this coalescence mechanism, a new coalescence kernel for population balance modelling of granule growth is presented. The kernel is constant such that only collisions satisfying the conditions for one of the two coalescence types are successful. One constant rate is assigned to each type of coalescence and zero is for the case of rebound. As the conditions for Types I and II coalescence are dependent on granule and binder properties, the coalescence kernel is thus physically based. Simulation results of a variety of binder and granule materials show good agreement with experimental data. (C) 2002 Elsevier Science Ltd. All rights reserved.

The effect of water, brine and ethanol flotation on the quality and shelf life of macadamia kernels 2. Kernel pieces

Raw macadamia kernel pieces were immersed in water (specific gravity 1.00 g/cm(3)), brine (SG 1.02 g/cm(3)) or ethanol solution (SG 0.97 g/cm(3)) for 30 or 60 s, then re-dried to below 1.5% moisture (wet basis) and stored under vacuum for 0, 4 and 12 months. Flotation in water had no effect on the quality or shelf life of the kernel pieces over 12 months storage, as measured by sensory evaluation of the kernels and chemical analysis of the kernel oil. Immersion in a salt solution caused unacceptable changes in quality during storage, increasing as storage time increased. Flotation in dilute ethanol also caused unacceptable quality changes during storage. Therefore, only flotation of macadamia kernel pieces in water can be recommended for commercial operations. Microbiological concerns with such a process still need to be addressed.

Error bounds for low-rank approximations of the first exponential integral kernel

A hierarchical matrix is an efficient data-sparse representation of a matrix, especially useful for large dimensional problems. It consists of low-rank subblocks leading to low memory requirements as well as inexpensive computational costs. In this work, we discuss the use of the hierarchical matrix technique in the numerical solution of a large scale eigenvalue problem arising from a finite rank discretization of an integral operator. The operator is of convolution type, it is defined through the first exponential-integral function and, hence, it is weakly singular. We develop analytical expressions for the approximate degenerate kernels and deduce error upper bounds for these approximations. Some computational results illustrating the efficiency and robustness of the approach are presented.

Exploração da implementação actual de IPv6 no Kernel do Linux

A presente dissertação visa retratar a exploração do suporte do protocolo Internet versão seis (IPv6) no kernel do Linux, conjuntamente com a análise detalhada do estado da implementação dos diferentes aspectos em que se baseia o protocolo. O estudo incide na experimentação do funcionamento em geral do stack, a identificação de inconsistências deste em relação aos RFC’s respectivos, bem como a simulação laboratorial de cenários que reproduzam casos de utilização de cada uma das facilidades analisadas. O objectivo desta dissertação não é explicar o funcionamento do novo protocolo IPv6, mas antes, centrar-se essencialmente na exploração do IPv6 no kernel do Linux. Não é um documento para leigos em IPv6, no entanto, optou-se por desenvolver uma parte inicial onde é abordado o essencial do protocolo: a sua evolução até à aprovação e a sua especificação. Com base no estudo realizado, explora-se o suporte do IPv6 no Kernel do Linux, fazendo uma análise detalhada do estado de implementação dos diferentes aspectos em que se baseia o protocolo. Bem como a realização de testes de conformidade IPv6 em relação aos RFC’s.

Real-time scheduling of parallel tasks in the Linux Kernel

This paper proposes a global multiprocessor scheduling algorithm for the Linux kernel that combines the global EDF scheduler with a priority-aware work-stealing load balancing scheme, enabling parallel real-time tasks to be executed on more than one processor at a given time instant. We state that some priority inversion may actually be acceptable, provided it helps reduce contention, communication, synchronisation and coordination between parallel threads, while still guaranteeing the expected system’s predictability. Experimental results demonstrate the low scheduling overhead of the proposed approach comparatively to an existing real-time deadline-oriented scheduling class for the Linux kernel.

Enhancing the real-time capabilities of the Linux Kernel

The mainline Linux Kernel is not designed forhard real-time systems; it only fits the requirements of soft realtimesystems. In recent years, a kernel developer communityhas been working on the PREEMPT-RT patch. This patch(that aims to get a fully preemptible kernel) adds some realtimecapabilities to the Linux kernel. However, in terms ofscheduling policies, the real-time scheduling class of Linux islimited to the First-In-First-Out (SCHED_FIFO) and Round-Robin (SCHED_RR) scheduling policies. These scheduling policiesare however quite limited in terms of realtime performance.Therefore, in this paper, we report one importantcontribution for adding more advanced real-time capabilitiesto the Linux Kernel. Specifically, we describe modificationsto the (PREEMPT-RT patched) Linux kernel to supportreal-time slot-based task-splitting scheduling algorithms. Ourpreliminary evaluation shows that our implementation exhibitsa real-time performance that is superior to the schedulingpolicies provided by the current version of PREMPT-RT. Thisis a significant add-on to a widely adopted operating system.

Run-time monitoring approach for the shark kernel

Typically common embedded systems are designed with high resource constraints. Static designs are often chosen to address very specific use cases. On contrast, a dynamic design must be used if the system must supply a real-time service where the input may contain factors of indeterminism. Thus, adding new functionality on these systems is often accomplished by higher development time, tests and costs, since new functionality push the system complexity and dynamics to a higher level. Usually, these systems have to adapt themselves to evolving requirements and changing service requests. In this perspective, run-time monitoring of the system behaviour becomes an important requirement, allowing to dynamically capturing the actual scheduling progress and resource utilization. For this to succeed, operating systems need to expose their internal behaviour and state, making it available to the external applications, usually using a run-time monitoring mechanism. However, such mechanism can impose a burden in the system itself if not wisely used. In this paper we explore this problem and propose a framework, which is intended to provide this run-time mechanism whilst achieving code separation, run-time efficiency and flexibility for the final developer.