Action versus result-oriented schemes in a grassland agroecosystem: a dynamic modelling approach

Effects of agri-environment schemes (AES) on biodiversity remain controversial. While most AES are action-oriented, result-oriented and habitat-oriented schemes have recently been proposed as a solution to improve AES efficiency. The objective of this study was to compare action-oriented, habitat-oriented and result-oriented schemes in terms of ecological and productive performance as well as in terms of management flexibility. We developed a dynamic modelling approach based on the viable control framework to carry out a long term assessment of the three schemes in a grassland agroecosystem. The model explicitly links grazed grassland dynamics to bird population dynamics. It is applied to lapwing conservation in wet grasslands in France. We ran the model to assess the three AES scenarios. The model revealed the grazing strategies respecting ecological and productive constraints specific to each scheme. Grazing strategies were assessed by both their ecological and productive performance. The viable control approach made it possible to obtain the whole set of viable grazing strategies and therefore to quantify the management flexibility of the grassland agroecosystem. Our results showed that habitat and result-oriented scenarios led to much higher ecological performance than the action-oriented one. Differences in both ecological and productive performance between the habitat and result-oriented scenarios were limited. Flexibility of the grassland agroecosystem in the result-oriented scenario was much higher than in that of habitat-oriented scenario. Our model confirms the higher flexibility as well as the better ecological and productive performance of result-oriented schemes. A larger use of result-oriented schemes in conservation may also allow farmers to adapt their management to local conditions and to climatic variations.     

A theoretical interpretation of length-biomass allometry of predominantly bidimensional seaweeds

Experimental studies on bidimensional seaweeds revealed a scaling exponent of 0.472 for their length-biomass allometry. This was significantly higher than the value 0.25, which was proposed earlier as universal for all primary producers, based on the data for unicellular microalgae and vascular plants. Later, an exponent of 0.5 was theoretically derived, which agreed, to some extent, with experimental findings. Here, it is shown that there exists a power-law relation between the two perpendicular length parameters along the directions of growth of a bidimensional organism. The length-biomass allometric parameters can be expressed in terms of this power index. A relation between the allometric scaling exponent and allometric constant, involving the mass per unit area, has been obtained analytically. A method is proposed to determine the power index experimentally. Some mathematical expressions, relating mass, length and other parameters, have been formulated and these would be useful for experimental purposes in allometric studies. Analyzing images from an experimental study, a lot of parameters, regarding flat seaweeds, have been determined by analytical and numerical techniques.     

Heavily loaded flight and limits to the maximum size of dragonflies (Anisoptera) and griffenflies (Meganisoptera)

An original hypothesis is presented that the maximum mass and size of living anisopteran dragonflies are constrained by a physiological performance limit: the wing muscle power required to permit reproductively successful males to carry heavier females in the so‐called ‘wheel position’ in flight. It is proposed that the same limit cannot have applied to all fossil Odonatoptera. As the physiology of the giant Carboniferous griffenfly Namurotypus sippeli precludes flight in the wheel position, it did not need to carry any substantial load aside from exogenous aerial prey. Based on its thorax dimensions, it is argued that Namurotypus flew with a relatively low maximum specific muscle power output in comparison with living Anisoptera. The extinction of some families of large Mesozoic Odonatoptera may have been exacerbated by competition with smaller (stem‐) Anisoptera that evolved higher specific power outputs and superior flight performance similar to living Anisoptera. To investigate the credibility of this flight‐performance size‐limit hypothesis and its consequences, an analysis of the scaling of the required flight power and available muscle power is presented using allometric relations. It is found that for living Anisoptera and fossil Odonatoptera, there are different limiting sizes, above which the required specific flight power would exceed the available muscle specific power. These limits are directly related to maximum load‐carrying capacity and the atmospheric air density at the habitual altitude. It is suggested that the largest living species of Petaluridae, Petalura ingentissima, is close to the proposed Anisoptera size limit at current near‐sea‐level air density conditions.     

Test of Independence Against a Class of Ordered Alternatives in an R × C Contingency Table

Test procedures are developed for testing the hypotheses of independence in a two-way contingency table against a class of ordered alternatives defined in terms of pooled crossproduct ratios. The alternatives hypotheses of “positive dependence” defines new notions of dependence. The distribution of the test statistics is obtained. Admissibility of the test is deduced and power comparison with some known test procedures are given. A numerical example is presented to illustrate the techniques developed.     

Bio-inspired adaptive feedback error learning architecture for motor control

This study proposes an adaptive control architecture based on an accurate regression method called Locally Weighted Projection Regression (LWPR) and on a bio-inspired module, such as a cerebellar-like engine. This hybrid architecture takes full advantage of the machine learning module (LWPR kernel) to abstract an optimized representation of the sensorimotor space while the cerebellar component integrates this to generate corrective terms in the framework of a control task. Furthermore, we illustrate how the use of a simple adaptive error feedback term allows to use the proposed architecture even in the absence of an accurate analytic reference model. The presented approach achieves an accurate control with low gain corrective terms (for compliant control schemes). We evaluate the contribution of the different components of the proposed scheme comparing the obtained performance with alternative approaches. Then, we show that the presented architecture can be used for accurate manipulation of different objects when their physical properties are not directly known by the controller. We evaluate how the scheme scales for simulated plants of high Degrees of Freedom (7-DOFs).     

Implantable cardioverter defibrillator algorithms: status review in terms of computational cost.

In recent decades, implantable cardioverter defibrillators (ICDs) have improved substantially, becoming the treatment of choice for patients at high risk of life-threatening arrhythmias. Nevertheless, inappropriate shock therapy for non-ventricular arrhythmias is still a problem. Extending the ICD battery lifetime demands very low power consumption, which is obtained at very low microprocessor clock frequencies. Currently, some high-performance algorithms remain beyond the computational capabilities of ICDs. Future ICDs with higher computing power will permit the implementation of computationally intensive algorithms, enhancing the discrimination performance and preventing inappropriate shock therapies. An ICD algorithm status review is presented from the point of view of signal processing techniques and their computational costs. Several examples of discrimination algorithms with increasing computational cost are analyzed. Whereas some of them are already used in commercial ICDs, other algorithms cannot be implemented yet in current ICDs. A solution based on dynamic adaptation of microprocessor power consumption to meet algorithm computational requirements is proposed. This solution allows implementation of complex discrimination algorithms in ICDs without significantly increasing the power consumption.     

Comparative Analysis of Methods for Identifying Recurrent Copy Number Alterations in Cancer

Recurrent copy number alterations (CNAs) play an important role in cancer genesis. While a number of computational methods have been proposed for identifying such CNAs, their relative merits remain largely unknown in practice since very few efforts have been focused on comparative analysis of the methods. To facilitate studies of recurrent CNA identification in cancer genome, it is imperative to conduct a comprehensive comparison of performance and limitations among existing methods. In this paper, six representative methods proposed in the latest six years are compared. These include one-stage and two-stage approaches, working with raw intensity ratio data and discretized data respectively. They are based on various techniques such as kernel regression, correlation matrix diagonal segmentation, semi-parametric permutation and cyclic permutation schemes. We explore multiple criteria including type I error rate, detection power, Receiver Operating Characteristics (ROC) curve and the area under curve (AUC), and computational complexity, to evaluate performance of the methods under multiple simulation scenarios. We also characterize their abilities on applications to two real datasets obtained from cancers with lung adenocarcinoma and glioblastoma. This comparison study reveals general characteristics of the existing methods for identifying recurrent CNAs, and further provides new insights into their strengths and weaknesses. It is believed helpful to accelerate the development of novel and improved methods.     

An allometric method for the projection of eelgrass leaf biomass production rates

We demonstrate that an allometric model for eelgrass leaf-growth rates can be derived from data on leaf architecture and growth form. Using this construct, we produced indirect assessments of growth rates of leaves that we call projections, which can be easily obtained in terms of allometric parameters and proxy values for leaf area, expressed as the product of leaf length and width. These projections of leaf-growth rates displayed a high level of correspondence with values observed in our data, as well as with other sets of reference data. A comparison with growth rates obtained by using the plastochrone index method showed that our model provides more accurate estimations while using a simpler methodology. Our results also show that whenever allometric parameters for the scaling of eelgrass leaf dry weight in terms of leaf area are available, the proposed model provides an accurate, cost-effective and non-destructive alternative to assessments based on traditional or plastochrone methods.     

Improving load balancing for data-duplication in big data cloud computing networks

Data transmission and retrieval in a cloud computing environment are usually handled by storage device providers or physical storage units leased by third parties. Improving network performance considering power connectivity and resource stability while ensuring workload balance is a hot topic in cloud computing. In this research, we have addressed the data duplication problem by providing two dynamic models with two variant architectures to investigate the strengths and shortcomings of architectures in Big Data Cloud Computing Networks. The problems of the data duplication process will be discussed accurately in each model. Attempts have been made to improve the performance of the cloud network by taking into account and correcting the flaws of the previously proposed algorithms. The accuracy of the proposed models have been investigated by simulation. Achieved results indicate an increase in the workload balance of the network and a decrease in response time to user requests in the model with a grouped architecture for all the architectures. Also, the proposed duplicate data model with peer-to-peer network architecture has been able to increase the cloud network optimality compared to the models presented with the same architecture.

     

Speedup bioinformatics applications on multicore-based processor using vectorizing and multithreading strategies

Many computational intensive bioinformatics software, such as multiple sequence alignment, population structure analysis, etc., written in C/C++ are not multicore-aware. A multicore processor is an emerging CPU technology that combines two or more independent processors into a single package. The Single Instruction Multiple Data-stream (SIMD) paradigm is heavily utilized in this class of processors. Nevertheless, most popular compilers including Microsoft Visual C/C++ 6.0, x86 gnu C-compiler gcc do not automatically create SIMD code which can fully utilize the advancement of these processors. To harness the power of the new multicore architecture certain compiler techniques must be considered. This paper presents a generic compiling strategy to assist the compiler in improving the performance of bioinformatics applications written in C/C++. The proposed framework contains 2 main steps: multithreading and vectorizing strategies. After following the strategies, the application can achieve higher speedup by taking the advantage of multicore architecture technology. Due to the extremely fast interconnection networking among multiple cores, it is suggested that the proposed optimization could be more appropriate than making use of parallelization on a small cluster computer which has larger network latency and lower bandwidth.     

Effects on participation and biodiversity of reforming the implementation of agri-environmental schemes in the Netherlands

To prevent further biodiversity loss as a result of intensive agricultural practices, Agri-Environmental Schemes (AES) have been implemented on European farmland. Unfortunately these AES have not always been effective in terms of biodiversity and farmer participation. In an effort to improve the AES programme the Dutch government switched from an individual application system to a collective application system for AES payments in 2016. The goal of this paper is to analyse how the resilience of the land use system in terms of farmer participation in the AES and biodiversity is affected by the value farmers attach to biodiversity, and whether the shift from an individual to collective AES will affect the resilience of the land use system. We constructed a multi-objective mathematical programming model in which farmers maximise utility. Farmers are linked through their common effect on biodiversity. In the collective application system payments are only available when the biodiversity in the region is above a certain threshold. Simulation results show no difference in farmer participation and biodiversity between the individual application system and the collective application system when biodiversity weights are high. The land use system loses its resilience in terms farmer participation in the AES and biodiversity if we lower the biodiversity weights, this effect is stronger in the collective AES programme.     

Safety and efficiency conflicts in hydraulic architecture: scaling from tissues to trees

Tree hydraulic architecture exhibits patterns that propagate from tissue to tree scales. A challenge is to make sense of these patterns in terms of trade-offs and adaptations. The universal trend for conduits per area to decrease with increasing conduit diameter below the theoretical packing limit may reflect the compromise between maximizing the area for conduction versus mechanical support and storage. Variation in conduit diameter may have two complementary influences: one being compromises between efficiency and safety and the other being that conduit tapering within a tree maximizes conductance per growth investment. Area-preserving branching may be a mechanical constraint, preventing otherwise more efficient top-heavy trees. In combination, these trends beget another: trees have more, narrower conduits moving from trunks to terminal branches. This pattern: (1) increases the efficiency of tree water conduction; (2) minimizes (but does not eliminate) any hydraulic limitation on the productivity or tissue growth with tree height; and (3) is consistent with the scaling of tree conductance and sap flow with size. We find no hydraulic reason why tree height should scale with a basal diameter to the two-thirds power as recently claimed; it is probably another mechanical constraint as originally proposed. The buffering effect of capacitance on the magnitude of transpiration-induced xylem tension appears to be coupled to cavitation resistance, possibly alleviating safety versus efficiency trade-offs.     

Distributed volume morphing

3D morphing is a popular technique for creating a smooth transition between two objects. In this paper we integrate volume morphing and rendering in a distributed network environment to speed up the computation efficiency. We describe our proposed system architecture of distributed volume morphing and the proposed algorithms, along with their implementation and performance on the networked workstations. A load evaluation function is proposed to partition the workload and the workstation cluster for better load balancing and then to improve the performance under highly uneven load situation. The performance evaluation for five load balancing strategies are conducted. Among them, the strategy ‘Request’ performs the best in terms of speedup. This revised version was published online in July 2006 with corrections to the Cover Date.     

Fine Needle Tissue Aspiration for Accurate Localization of Histological Specimens from Complex Structures

A procedure is presented for exact, detailed comparison of light and electron microscopic analyses of tissues with complex architecture. Earlier techniques require one to make drawings of tissue pieces to be analyzed by electron microscopy to permit rough localization of the origin of the tissue pieces. Specifically, exact analysis of fetal cartilage and bone is hampered by the complicated arrangement of both tissue components, severely limiting the assessment of electron microscopic analyses. The advantage of the technique described here is that it allows precise localization of the tissue sample in the original tissue area. Punches 1 mm in diameter were obtained from femora and coxae with a syringe and embedded for light and electron microscopy. The remaining tissue with its exactly defined punctures is prepared for standard histology. Human fetal cartilage and bone tissue were used to demonstrate this technique, but this procedure may be used for other kinds of tissues.     

Hair removal methods: A comparative study for dermoscopy images

Removal and restoration of hair and hair-like regions within skin lesion images is needed so features within lesions can be more effectively analyzed for benign lesions, cancerous lesions, and for cancer discrimination. This paper refers to “melanoma texture” as a rationale for supporting the need for the proposed hair detection and repair techniques, which incompletely represents why hair removal is an important operation for skin lesion analysis. A comparative study of the state-of-the-art hair-repaired methods with a novel algorithm is also proposed by morphological and fast marching schemes. The hair-repaired techniques are evaluated in terms of computational, performance and tumor-disturb patterns (TDP) aspects. The comparisons have been done among (i) linear interpolation, inpainting by (ii) non-linear partial differential equation (PDE) and (iii) exemplar-based repairing techniques. The performance analysis of hair detection quality, was based on the evaluation of the hair detection error (HDE), quantified by statistical metrics and manually used to determine the hair lines from a dermatologist as the ground truth. The results are presented on a set of 100 dermoscopic images. For the two characteristics measured in the experiments the best method is the fast marching hair removal algorithm (HDE: 2.98%, TDP: 4.21%). This proposed algorithm repaired the texture of the melanoma, which becomes consistent with human vision. The comparisons results obtained, indicate that hair-repairing algorithm based on the fast marching method achieve an accurate result.     

Predicting Physical Time Series Using Dynamic Ridge Polynomial Neural Networks

Forecasting naturally occurring phenomena is a common problem in many domains of science, and this has been addressed and investigated by many scientists. The importance of time series prediction stems from the fact that it has wide range of applications, including control systems, engineering processes, environmental systems and economics. From the knowledge of some aspects of the previous behaviour of the system, the aim of the prediction process is to determine or predict its future behaviour. In this paper, we consider a novel application of a higher order polynomial neural network architecture called Dynamic Ridge Polynomial Neural Network that combines the properties of higher order and recurrent neural networks for the prediction of physical time series. In this study, four types of signals have been used, which are; The Lorenz attractor, mean value of the AE index, sunspot number, and heat wave temperature. The simulation results showed good improvements in terms of the signal to noise ratio in comparison to a number of higher order and feedforward neural networks in comparison to the benchmarked techniques.     

Enhanced Cumulative Sum Charts for Monitoring Process Dispersion

The cumulative sum (CUSUM) control chart is widely used in industry for the detection of small and moderate shifts in process location and dispersion. For efficient monitoring of process variability, we present several CUSUM control charts for monitoring changes in standard deviation of a normal process. The newly developed control charts based on well-structured sampling techniques - extreme ranked set sampling, extreme double ranked set sampling and double extreme ranked set sampling, have significantly enhanced CUSUM chart ability to detect a wide range of shifts in process variability. The relative performances of the proposed CUSUM scale charts are evaluated in terms of the average run length (ARL) and standard deviation of run length, for point shift in variability. Moreover, for overall performance, we implore the use of the average ratio ARL and average extra quadratic loss. A comparison of the proposed CUSUM control charts with the classical CUSUM R chart, the classical CUSUM S chart, the fast initial response (FIR) CUSUM R chart, the FIR CUSUM S chart, the ranked set sampling (RSS) based CUSUM R chart and the RSS based CUSUM S chart, among others, are presented. An illustrative example using real dataset is given to demonstrate the practicability of the application of the proposed schemes.     

Evolutionary optimization of sequence kernels for detection of bacterial gene starts

Oligo kernels for biological sequence classification have a high discriminative power. A new parameterization for the K-mer oligo kernel is presented, where all oligomers of length K are weighted individually. The task specific choice of these parameters increases the classification performance and reveals information about discriminative features. For adapting the multiple kernel parameters based on cross-validation the covariance matrix adaptation evolution strategy is proposed. It is applied to optimize the trimer oligo kernels for the detection of bacterial gene starts. The resulting kernels lead to higher classification rates, and the adapted parameters reveal the importance of particular triplets for classification, for example of those occurring in the Shine-Dalgarno Sequence.     

The optimal age of sown field margins for breeding farmland birds

The Europe‐wide decline in the populations and diversity of farmland birds has not been stopped despite dedicated conservation efforts such as agri‐environment schemes (AES). The main reason for the lack of success of AES is considered to be their low ecological quality and insufficient area. Understanding the effects of different management strategies on the ecological quality of AES is therefore important. Here, we investigate the relationship between breeding bird density and species richness and the age of sown field margins, a widely used type of AES, in southwestern Switzerland. Territories of breeding birds were mapped on 67 field margins between 2004 and 2011. Territory densities (for eight species) and species richness were analysed in relation to age of the field margin. A general negative correlation between size of the field margin and territory density indicated that territory density was higher when the birds could forage in adjacent cultivated land. Territory densities and species richness increased up to an age of 4–6 years after sowing, depending on the species, and declined thereafter. The results suggest that the co‐occurrence of newly sown margins and margins over 3 years old will have a positive effect on breeding bird densities and species diversity.