scholarly journals Fisheries in the Mediterranean

2000 ◽  
Vol 1 (1) ◽  
pp. 5 ◽  
Author(s):  
C. PAPACONSTANTINOU ◽  
H. FARRUGIO
Keyword(s):  
Time Series Data ◽  
Early Stage ◽  
Eastern Mediterranean ◽  
Fishing Effort ◽  
Series Data ◽  
Small Scale ◽  
General Description ◽  
Stage Of Development ◽  
Mediterranean Countries ◽  
The Mediterranean

The aim of this paper is to give a description of the Mediterranean fisheries, and its level of exploitation and to address the main questions dealing with its management. The Mediterranean is a semi-enclosed marine area with generally narrow continental shelves. The primary production of the Mediterranean is among the lowest in the world (26-50g C m-2 y-1). The Mediterranean fisheries can be broken down into three main categories: small scale fisheries, trawling and seining fisheries, which operated on demersal, small pelagic and large pelagic resources. After a general description of the state of the resources in the different areas of the Mediterranean it is concluded that (a) the overall pictures from the western to the eastern Mediterranean are not considerably different, (b) the total landings in the Mediterranean have been increased the last decades, and (c) from the perspective of stock assessment, the very few available time series data show stable yield levels. In general fisheries management in the Mediterranean is at a rela- tively early stage of development, judging by the criteria of North Atlantic fisheries. Quota systems are generally not applied, mesh-size regulations usually are set at low levels relative to scientific advice, and effort limitation is not usually applied or, if it is, is not always based on a formal resource assessment. The conservation/management measures applied by the Mediterranean countries can be broadly separated into two major categories: those aiming to keep the fishing effort under control and those aiming to make the exploitation pattern more rational. The most acute problems in the management of the Mediterranean resources are the multispecificity of the catches and the lack of reliable official statistics.

scholarly journals Data-Driven Recommendations for Establishing Threshold Values for the NIS Trend Indicator in the Mediterranean Sea

Diversity ◽  
2022 ◽  
Vol 14 (1) ◽  
pp. 57
Author(s):  
Marika Galanidi ◽  
Argyro Zenetos
Keyword(s):  
Time Series Data ◽  
Driving Forces ◽  
Eastern Mediterranean ◽  
Time Lag ◽  
Series Data ◽  
Indigenous Species ◽  
Reference Period ◽  
Threshold Values ◽  
Basin Scale ◽  
The Mediterranean

In the present work, we analysed time series data on the introduction of new non-indigenous species (NIS) in the Mediterranean between 1970 and 2017, aiming to arrive at recommendations concerning the reference period and provisional threshold values for the NIS trend indicator. We employed regression analysis and breakpoint structural analysis. Our results confirm earlier findings that the reference conditions differ for the four Mediterranean subregions, and support a shortening of the reporting cycle from six to three years, with a two-year time lag for the ensuing assessment. Excluding Lessepsian fishes and parasites, the reference period, defined as the most recent time segment with stable mean new NIS values, was estimated as 1997–2017 for the eastern Mediterranean, 2012–2017 for the central Mediterranean, 2000–2017 for the Adriatic and 1970–2017 for the western Mediterranean. These findings are interpreted primarily on the basis of a basin scale temperature regime shift in the late 1990s, shifts in driving forces such as shellfish culture, and as a result of intensified research efforts and citizen scientist initiatives targeting NIS in the last decade. The threshold values, i.e., the three-year average new NIS values during the reference period, are indicative and will ultimately depend on the choice of species and pathways to be used in the calculations. This is discussed through the prism of target setting in alignment with specific management objectives.

scholarly journals Characterizing the Evolution of the Container Traffic Share in the Mediterranean Sea Using Hierarchical Clustering

2018 ◽  
Vol 6 (4) ◽  
pp. 121 ◽  
Author(s):  
Manel Grifoll ◽  
Thanassis Karlis ◽  
M. Ortego
Keyword(s):  
Mediterranean Sea ◽  
Hierarchical Clustering ◽  
System Analysis ◽  
Compositional Data ◽  
Eastern Mediterranean ◽  
Compositional Data Analysis ◽  
Mediterranean Countries ◽  
The Mediterranean ◽  
Combination Of Methods ◽  
Port Infrastructure

This research investigates the traffic share evolution of the container throughput in the Mediterranean ports from 2000 to 2015 considering hierarchical clustering and concentration indexes. Compositional Data analysis techniques are used to illustrate periods with similar traffic share composition. Two different regions (East and West) in the Mediterranean Sea (Med) are selected in the function of the long haul services. The standard concentration indexes (i.e., concentration ratio, Gini coefficient, and Normalized Herfindahl-Hirschman) reveal a gentle decreasing of the concentration with relevant fluctuations mainly in the East region. This is due to the investment in port infrastructure in the area resulting from privatization initiatives in many Eastern Mediterranean countries. The periods obtained from the hierarchical clustering show a differentiated pattern in traffic share composition. For these periods, the shift-share results are consistent with traffic fluctuations and in line with the evolution of the concentration indexes. The combination of methods has allowed a good interpretation of the spatial and temporal evolution of the Med ports’ traffic being the methodology applicable elsewhere in the context of port system analysis.

scholarly journals Lagrangian and spectral analysis of the forced flow past a circular cylinder using pulsed tangential jets

2012 ◽  
Vol 696 ◽  
pp. 285-300 ◽  
Author(s):  
T. Jardin ◽  
Y. Bury
Keyword(s):  
Circular Cylinder ◽  
Time Series Data ◽  
Excitation Frequency ◽  
Shear Layers ◽  
Forced Flow ◽  
Series Data ◽  
Small Scale ◽  
Characteristic Time Scale ◽  
Momentum Coefficient ◽  
Flow Past

AbstractWe numerically investigate the influence of pulsed tangential jets on the flow past a circular cylinder. To this end a spectral-Lagrangian dual approach is used on the basis of time-series data. The analysis reveals that the flow response to unsteady forcing is driven by strong interactions between shear layers and pulsed jets. The latter preferentially lead to either the lock-on regime or the quasi-steady vortex feeding regime whether the excitation frequency is of the order of, or significantly greater than, the frequency of the natural instability. The intensity of the wake vortices is mainly influenced by the momentum coefficient through the introduction of opposite-sign vorticity in the shear layers. This feature is emphasized using a modal-based time reconstruction, i.e. by reconstructing the flow field upon a specific harmonic spectrum associated with a characteristic time scale. The quasi-steady regime exhibits small-scale counter-rotating vortices that circumscribe the separated region. In the lock-on regime, atypical wake patterns such as 2P or $\mathrm{P} + \mathrm{S} $ can be observed, depending on the forcing frequency and the momentum coefficient, highlighting remarkable analogies with oscillating cylinders.

scholarly journals Forecast Quality of Physics-Based and Data-Driven PV Performance Models for a Small-Scale PV System

2021 ◽  
Vol 9 ◽  
Author(s):  
Moritz Stüber ◽  
Felix Scherhag ◽  
Matthieu Deru ◽  
Alassane Ndiaye ◽  
Muhammad Moiz Sakha ◽  
...  
Keyword(s):  
Smart Grids ◽  
Time Series Data ◽  
Short Term Memory ◽  
Data Driven ◽  
Series Data ◽  
Small Scale ◽  
Pv System ◽  
Advantages And Disadvantages ◽  
Forecast Quality

In the context of smart grids, the need for forecasts of the power output of small-scale photovoltaic (PV) arrays increases as control processes such as the management of flexibilities in the distribution grid gain importance. However, there is often only very little knowledge about the PV systems installed: even fundamental system parameters such as panel orientation, the number of panels and their type, or time series data of past PV system performance are usually unknown to the grid operator. In the past, only forecasting models that attempted to account for cause-and-effect chains existed; nowadays, also data-driven methods that attempt to recognize patterns in past behavior are available. Choosing between physics-based or data-driven forecast methods requires knowledge about the typical forecast quality as well as the requirements that each approach entails. In this contribution, the achieved forecast quality for a typical scenario (day-ahead, based on numerical weather predictions [NWP]) is evaluated for one physics-based as well as five different data-driven forecast methods for a year at the same site in south-western Germany. Namely, feed-forward neural networks (FFNN), long short-term memory (LSTM) networks, random forest, bagging and boosting are investigated. Additionally, the forecast quality of the weather forecast is analyzed for key quantities. All evaluated PV forecast methods showed comparable performance; based on concise descriptions of the forecast approaches, advantages and disadvantages of each are discussed. The approaches are viable even though the forecasts regularly differ significantly from the observed behavior; the residual analysis performed offers a qualitative insight into the achievable forecast quality in a typical real-world scenario.

scholarly journals Experiments on magnetic interference for a portable airborne magnetometry system using a hybrid unmanned aerial vehicle (UAV)

2020 ◽  
Author(s):  
Jirigalatu Jirigalatu ◽  
Vamsi Krishna ◽  
Eduardo Lima Simões da Silva ◽  
Arne Døssing
Keyword(s):  
Early Stage ◽  
Longitudinal Axis ◽  
Small Scale ◽  
Magnetic Survey ◽  
Stage Of Development ◽  
Rapid Sampling ◽  
Dynamic Experiments ◽  
Static Experiment ◽  
Airborne Magnetic ◽  
Airborne Magnetic Survey

Abstract. Airborne magnetic surveys are an important and efficient tool for mapping the subsurface, providing insights e.g. into mineral deposits. Compared to traditional ground methods, airborne magnetic surveys offer great advantages with improved access and rapid sampling. But the cost and hassle of transporting and operating a conventional manned airborne magnetic survey system are strong impediments for its wider use. In addition, the conventional airborne systems are challenged by the need for low-altitude (≤ 80 m) surveying to detect small-scale subsurface features evident in ground surveys. Portable and compact airborne magnetic survey systems using unmanned aerial vehicles (UAVs) can not only bridge the gap between conventional airborne magnetic surveys and ground magnetic surveys but also complement magnetic surveys to fit broader geophysical applications. Therefore, developing high-quality, stable, and portable UAV-borne survey systems is of high interest to the geophysical exploration community. However, developing such a system is challenging owing to strong magnetic interference introduced by onboard electric engines and other onboard electronic devices. As a result, tests concerning the static and dynamic magnetic interference of a UAV are critical to assess the severity of the interference and can help to improve the design of the system at the early stage of development. A static experiment and two dynamic experiments were conducted to understand the characterization of the magnetic interference of our hybrid vertical take-off and landing (VTOL) UAV. The results of the static experiment show that the wing area is highly magnetic due to the proximity to servomotors and motors, but the area along the longitudinal axis of the UAV is relatively magnetically quiet. To reduce the magnetic signature, the highly-magnetic servomotors on the wings were replaced with less magnetic servomotors of a brush-less type. Assisted by aerodynamic simulations, we further designed a front-mounting solution for two compact magnetometers. Two dynamic experiments were conducted with this setup to understand the dynamic interference of the UAV in operation. The results of the dynamic experiments reveal that the strongest source of in-flight magnetic interference is mainly due to the cables connecting the battery to the flight controller and that this effect is most influential during pitch maneuvers of the aircraft.

scholarly journals Comparative transcriptome analysis reveals the intensive early-stage responses of host cells to SARS-CoV-2 infection

2020 ◽  
Author(s):  
Jiya Sun ◽  
Fei Ye ◽  
Aiping Wu ◽  
Ren Yang ◽  
Mei Pan ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
High Efficiency ◽  
Time Series Data ◽  
Early Stage ◽  
Host Cells ◽  
Host Responses ◽  
Series Data ◽  
Antiviral Responses ◽  
Regulated Gene Expression ◽  
Host Genes

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a widespread outbreak of highly pathogenic COVID-19. It is therefore important and timely to characterize interactions between the virus and host cell at the molecular level to understand its disease pathogenesis. To gain insights, we performed high-throughput sequencing that generated time-series data simultaneously for bioinformatics analysis of virus genomes and host transcriptomes implicated in SARS-CoV-2 infection. Our analysis results showed that the rapid growth of the virus was accompanied by an early intensive response of host genes. We also systematically compared the molecular footprints of the host cells in response to SARS-CoV-2, SARS-CoV and MERS-CoV. Upon infection, SARS-CoV-2 induced hundreds of up-regulated host genes hallmarked by a significant cytokine production followed by virus-specific host antiviral responses. While the cytokine and antiviral responses triggered by SARS-CoV and MERS-CoV were only observed during the late stage of infection, the host antiviral responses during the SARS-CoV-2 infection were gradually enhanced lagging behind the production of cytokine. The early rapid host responses were potentially attributed to the high efficiency of SARS-CoV-2 entry into host cells, underscored by evidence of a remarkably up-regulated gene expression of TPRMSS2 soon after infection. Taken together, our findings provide novel molecular insights into the mechanisms underlying the infectivity and pathogenicity of SARS-CoV-2.

scholarly journals Detecting Regime Transitions of the Nocturnal and Polar Near-Surface Temperature Inversion

2020 ◽  
Vol 77 (8) ◽  
pp. 2921-2940
Author(s):  
Amandine Kaiser ◽  
Davide Faranda ◽  
Sebastian Krumscheid ◽  
Danijel Belušić ◽  
Nikki Vercauteren
Keyword(s):  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Time Series Data ◽  
Temperature Inversion ◽  
Series Data ◽  
Small Scale ◽  
Dynamical Regime ◽  
Near Surface ◽  
Nonstationary Field ◽  
Regime Transitions

Abstract Many natural systems undergo critical transitions, i.e., sudden shifts from one dynamical regime to another. In the climate system, the atmospheric boundary layer can experience sudden transitions between fully turbulent states and quiescent, quasi-laminar states. Such rapid transitions are observed in polar regions or at night when the atmospheric boundary layer is stably stratified, and they have important consequences in the strength of mixing with the higher levels of the atmosphere. To analyze the stable boundary layer, many approaches rely on the identification of regimes that are commonly denoted as weakly and very stable regimes. Detecting transitions between the regimes is crucial for modeling purposes. In this work a combination of methods from dynamical systems and statistical modeling is applied to study these regime transitions and to develop an early warning signal that can be applied to nonstationary field data. The presented metric aims to detect nearing transitions by statistically quantifying the deviation from the dynamics expected when the system is close to a stable equilibrium. An idealized stochastic model of near-surface inversions is used to evaluate the potential of the metric as an indicator of regime transitions. In this stochastic system, small-scale perturbations can be amplified due to the nonlinearity, resulting in transitions between two possible equilibria of the temperature inversion. The simulations show such noise-induced regime transitions, successfully identified by the indicator. The indicator is further applied to time series data from nocturnal and polar meteorological measurements.

ANALISIS PROSPEK PERKEMBANGAN MODAL DAN TENAGA KERJA PADA INDUSTRI KECIL DI KABUPATEN SIDENRENG RAPPANG

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Agus Syam
Keyword(s):  
Time Series Data ◽  
Small And Medium Enterprises ◽  
Descriptive Analysis ◽  
Series Data ◽  
Small Scale ◽  
Quantitative Descriptive Analysis ◽  
Capital Growth ◽  
Small Industry ◽  
Small Industries ◽  
Small Scale Industries

Abstract Analysis of Prospect Capital Growth and Employment in Small Industries in The District Sidenreng Rappang. This research was conducted to answer the question "what are the prospects of capital growth and labor in the District Small Industries Sidenreng Rappang 5 (five) years from (2012-2016)". Thus, this study aims to determine how the prospect of the development of capital and labor in the District Small Industries Sidenreng Rappang 5 (five) years from (2012-2016). To that end, this study expected to be useful: (1) provide information for Local Government and the Department of Cooperatives and Small and Medium Enterprises in order to foster small-scale industries in the district Sidenreng Rappang, (2) as a reference material other researchers who study small-scale industries in the district Sidenreng Rappang. This research is a descriptive study using data time series (data year) only selected sub-populations in 2007-2011 for the development of capital and labor. Data collection techniques used are; documentation, interviews, and observations. Analysis of the data used, namely: qualitative and quantitative descriptive analysis. Result of research show the; 1) Capital developments in small industry in the District Sidenreng Rappang past five years (2007-2011) has increased by an average of 10.31 percent annually, 2) The development of labor in small-scale industries in the district Sidenreng Rappang past five years (2007-2011) has increased by an average of 1.04 percent annually, and 3) Development prospects of capital and labor in small-scale industries in the district Sidenreng Rappang for the coming five years (2012-2016) amounted to 3.93 percent.Kata Kunci: Modal, Tenaga Kerja dan Industri Kecil

scholarly journals Multivariate analysis of nonlinearity in sandbar behavior

2008 ◽  
Vol 15 (1) ◽  
pp. 145-158 ◽  
Author(s):  
L. Pape ◽  
B. G. Ruessink
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Nonlinear Models ◽  
Multivariate Time Series ◽  
Series Data ◽  
Small Scale ◽  
Synthetic Datasets ◽  
Long Term Prediction ◽  
Sandbar Migration

Abstract. Alongshore sandbars are often present in the nearshore zones of storm-dominated micro- to mesotidal coasts. Sandbar migration is the result of a large number of small-scale physical processes that are generated by the incoming waves and the interaction between the wave-generated processes and the morphology. The presence of nonlinearity in a sandbar system is an important factor determining its predictability. However, not all nonlinearities in the underlying system are equally expressed in the time-series of sandbar observations. Detecting the presence of nonlinearity in sandbar data is complicated by the dependence of sandbar migration on the external wave forcings. Here, a method for detecting nonlinearity in multivariate time-series data is introduced that can reveal the nonlinear nature of the dependencies between system state and forcing variables. First, this method is applied to four synthetic datasets to demonstrate its ability to qualify nonlinearity for all possible combinations of linear and nonlinear relations between two variables. Next, the method is applied to three sandbar datasets consisting of daily-observed cross-shore sandbar positions and hydrodynamic forcings, spanning between 5 and 9 years. Our analysis reveals the presence of nonlinearity in the time-series of sandbar and wave data, and the relative importance of nonlinearity for each variable. The relation between the results of each sandbar case and patterns in bar behavior are discussed, together with the effects of noise. The small effect of nonlinearity implies that long-term prediction of sandbar positions based on wave forcings might not require sophisticated nonlinear models.

scholarly journals Midterm Fire Danger Prediction Using Satellite Imagery and Auxiliary Thematic Layers

2019 ◽  
Vol 11 (23) ◽  
pp. 2786 ◽  
Author(s):  
Alexandra Stefanidou ◽  
Ioannis Z. Gitas ◽  
Dimitris Stavrakoudis ◽  
Georgios Eftychidis
Keyword(s):  
Time Series Data ◽  
Fire Danger ◽  
Series Data ◽  
Prevention Measures ◽  
Imaging Spectrometer ◽  
Effective Prevention ◽  
Response Planning ◽  
Forest Fire Management ◽  
Mediterranean Countries ◽  
Fire Ignition

Wildfires constitute a significant environmental pressure in Europe, particularly in the Mediterranean countries. The prediction of fire danger is essential for sustainable forest fire management since it provides critical information for designing effective prevention measures and for facilitating response planning to potential fire events. This study presents a new midterm fire danger index (MFDI) using satellite and auxiliary geographic data. The proposed methodology is based on estimations of a dry fuel connectivity measure calculated from the Moderate Imaging Spectrometer (MODIS) time-series data, which are combined with biophysical and topological variables to obtain accurate fire ignition danger predictions for the following eight days. The index’s accuracy was assessed using historical fire data from four large wildfires in Greece. The results showcase that the index predicted high fire danger (≥3 on a scale within [ 1 , 4 ] ) within the identified fire ignition areas, proving its strong potential for deriving reliable estimations of fire danger, despite the fact that no meteorological measurements or forecasts are used for its calculation.

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