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This paper presents a comparison of three different machine learning frameworks applied in the wave buoy analogy used for estimating the sea state from measured ship responses. The three frameworks output and characterise the sea state in different ways: Model 1 outputs integral parameters, Model 2 outputs a point wave spectrum and the wave direction, Model 3 outputs the full directional wave spectrum. The assessment of the models is based on simulated motion measurements, i.e. synthetic data. In the particular investigations made, the performance of Model 2, relying on a novel framework, is generally superior. However, the central take-away from the study, is the importance of considering thorough and well-prepared training data encompassing many, not to say all, possible parameter combinations and shapes in the studied wave spectra forming the training data; any machine learning model is no better than the data upon which it is trained. • Machine learning applied in the wave buoy analogy. • Comparison of three fundamentally different ML models. • Presentation of a novel framework outputting a point wave spectrum and wave direction. • Thorough investigations of the models' generalisation capability. • Well-prepared and comprehensive training data is crucial. [ABSTRACT FROM AUTHOR]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.cell.2006.01.041 Byline: Kevin A. Janes (1)(2), Suzanne Gaudet (1)(3), John G. Albeck (1)(3), Ulrik B. Nielsen (4), Douglas A. Lauffenburger (1)(2)(3), Peter K. Sorger (1)(2)(3) Abstract: Tumor necrosis factor (TNF) is a proinflammatory cytokine that induces conflicting pro- and antiapoptotic signals whose relative strengths determine the extent of cell death. TNF receptor (TNFR) has been studied in considerable detail, but it is not known how crosstalk among antagonistic pro- and antiapoptotic signals is achieved. Here we report an experimental and computational analysis of crosstalk between prodeath TNF and prosurvival growth factors in human epithelial cells. By applying classifier-based regression to a cytokine-signaling compendium of [approximately equal to]8000 intracellular protein measurements, we demonstrate that cells respond to TNF both directly, via activated TNF receptor, and indirectly, via the sequential release of transforming growth factor-[alpha] (TGF-[alpha]), interleukin-1[alpha] (IL-1[alpha]), and IL-1 receptor antagonist (IL-1ra). We refer to the contingent and time-varying series of extracellular signals induced by TNF as an 'autocrine cascade.' Time-dependent crosstalk of synergistic and antagonistic autocrine circuits may serve to link cellular responses to the local environment. Author Affiliation: (1) Center for Cell Decision Processes, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA (2) Department of Biological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA (3) Department of Biology, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA (4) Merrimack Pharmaceuticals, Cambridge, MA 02139, USA Article History: Received 26 May 2005; Revised 19 October 2005; Accepted 5 January 2006 Article Note: (miscellaneous) Published: March 23, 2006

Unmanned surface vehicles (USVs) are increasingly appealing for gathering metocean data, including directional sea spectra. This paper presents new developments towards estimating the response amplitude operators (RAOs) of surface vehicles equipped with inertial sensors. The novel approach undertakes the data-driven estimation of vehicle models of the wave-induced heave, roll, and pitch motion dynamics, as required to perform subsequent seakeeping computations. Specifically, a genetic algorithm executes the calibration of available closed-form RAOs for a simplified geometry. The algorithm makes a population of model-fitting parameters evolve towards minimising discrepancies between the predicted and measured response spectra in stationary operational conditions. Trust in the model is eventually increased by screening and merging the best-fitting solutions. Resulting response predictions using high-resolution spectral wave data for the AutoNaut USV demonstrate satisfactory accuracy and robustness in heave and pitch but a worse fidelity in roll, thereby motivating follow-up studies to improve the estimation of roll RAOs. • Inertial motion measurements are collected on board an autonomous marine vehicle. • Directional wave spectra are obtained by dynamical downscaling of hindcast data. • Parameters of the vehicle's seakeeping model are estimated using an elitist genetic algorithm. • Outliers of parameter values are identified and screened out, increasing model robustness. • Resulting predictions of the vehicle's wave-induced heave and pitch responses are accurate. [ABSTRACT FROM AUTHOR]

Abstract The article presents initial ideas towards a network-based approach for sea state estimation used for marine operations and other maritime applications. In principle, all available means, ranging from in situ buoys, fleet of ships to remote sensing by satellite and aircraft, could be considered, emphasising that each means and any combinations among may act simultaneously. This study focuses on just one of the means; the use of ships as sailing wave buoys. The article introduces the wave buoy analogy, i.e. ship-as-a-wave-buoy, and it makes a proposal on how to impose (different) weights to the single ship-specific wave spectrum estimates obtained from multiple ships. Moreover, the work includes a discussion about the importance to associate a measure to reflect the (un)certainty of the wave spectrum estimate. The article presents a numerical case study, where multiple ships act simultaneously as wave spectrum-estimators. The case study relies on numerical motion simulations, as appropriate full-scale data is not yet available. In the analysis, it is shown that the use of simultaneous data from multiple ships leads to more accurate wave spectrum estimations. [ABSTRACT FROM AUTHOR]

In this work, a hybrid approach for wave spectrum estimation is proposed. Fundamentally, the approach is based on the wave buoy analogy, processing ship response measurements, via a framework combining machine learning and a physics-based method dependent on available transfer functions. Specifically, a non-parametric (Bayesian) estimate is obtained of the directional wave spectrum conditioned on integral wave parameters established by a convolutional neural network. The developed method is assessed in a case study considering about two years of data obtained from an in-service container ship. The method produces good results, significantly improved when compared to the initial estimate made without constraints. • Presentation of a hybrid framework for wave spectrum estimation. • Combination of the classic transfer function dependent method and machine learning. • Application and assessment made with full-scale data. • Comparison between different sources of wave estimates. • Improved and robust estimation capabilities. [ABSTRACT FROM AUTHOR]

Performance data from ships is subject to distributional shifts, sometimes referred to as concept drift. In this study, synthetic monitoring data is simulated for the KVLCC2, considering publicly available reference data and a semi-empirical simulation framework. Neural networks are trained to predict the required shaft power and to overcome the deterioration in model accuracy due to concept drift, three methods of incremental learning are applied and compared: (1) Layer freezing, (2) L 2 regularization, and (3) elastic weight consolidation. Furthermore, an implicit methodology for quantifying the changing hull and propeller performance is presented. In addition, a generic feature engineering framework is used for eliminating insignificant features. In two investigations, sudden and incremental concept drift scenarios are examined, and the effect of different uncertainty categories on model performance is studied in parallel based on three different datasets. As a main finding, it is confirmed that data quality is of great importance for accurate machine learning-driven performance monitoring — even in simulated environments. Furthermore, the study shows that freezing layers during incremental learning proves to be most robust and accurate, but it will be part of future work to examine this on actual sensor data. • A semi-empirical framework generates synthetic monitoring data for the KVLCC2. • Several methods for incremental deep learning are compared for estimating shaft power. • A biofouling proxy variable is derived implicitly under consistent conditions. • The effect of two different uncertainty categories on model performance is evaluated. • Freezing layers during incremental learning proved to be most robust and accurate. [ABSTRACT FROM AUTHOR]

The objective of ship motion-based wave spectrum estimation is to provide the distribution of wave energy densities in absolute domain . However, as a ship generally advances relative to the progressing waves, any spectrum estimate inherently dates back to the encounter domain and, consequently, the spectrum estimate must be transformed to absolute domain. In following sea conditions, spectrum transformation from encounter to absolute domain has no unique (mathematical) solution. This article presents an optimisation-based technique to carry out the particular transformation in following sea conditions. The optimisation relies on an object function established using (wave) spectral moments; calculated directly using the estimated encounter-wave spectrum on the one side and by using a parameterised wave spectrum valid in absolute domain on the other side. The simplicity of the transformation technique is a strength in itself as it leads to an insignificant computational effort in the transformation to absolute domain. Equally important, the specific technique proves capable to provide accurate results in the majority of cases, when comprehensive testings with numerically simulated data of following sea conditions are performed. Furthermore, the technique is tested successfully using experimental full-scale sea trials data. [ABSTRACT FROM AUTHOR]

In Europe, the most widely used Christmas tree species, Abies nordmanniana, has a long history of infestation with the adelgid Dreyfusia nordmannianae . Since 2011, the species has furthermore been increasingly damaged by the fungus Neonectria neomacrospora . The objective was to study whether infestations by N. neomacrospora were facilitated by the presence of adelgids in Nordmann fir and to explore the genetic components of this potential interplay. The damage caused by D. nordmannianae and N. neomacrospora in two Nordmann fir clonal seed orchards in Denmark was evaluated in 2014, and an experimental infestation was conducted to test the performance of Nordmann fir somatic embryogenesis-derived trees exposed to N. neomacrospora and D. nordmannianae individually or in combination by setting up an artificial infestation chamber. The genetic correlation between the two diseases was 0.54 at two clonal seed orchards, indicating that the trees susceptible to N. neomacrospora were also susceptible to D. nordmannianae or vice versa. In the experimental test, only trees in the treatment with both D. nordmannianae and N. neomacrospora developed needle loss and dieback symptoms. Thus, both the field evaluations and the experimental test revealed an interplay between D. nordmannianae and N. neomacrospora damage on Nordmann fir trees. Future studies should explore in more detail how D. nordmannianae interacts with N. neomacrospora . Our findings and future studies on this topic could have important implications for suitable breeding programs for Nordmann fir Christmas trees and forest pest management. [ABSTRACT FROM AUTHOR]

The article introduces a spectral procedure for sea state estimation based on measurements of motion responses of a ship in a short-crested seaway. The procedure relies fundamentally on the wave buoy analogy, but the wave spectrum estimate is obtained in a direct - brute-force - approach, and the procedure is simple in its mathematical formulation. The actual formulation is extending another recent work by including vessel advance speed and short-crested seas. Due to its simplicity, the procedure is computationally efficient, providing wave spectrum estimates in the order of a few seconds, and the estimation procedure will therefore be appealing to applications related to realtime, onboard control and decision support systems for safe and efficient marine operations. The procedure's performance is evaluated by use of numerical simulation of motion measurements, and it is shown that accurate wave spectrum estimates can be obtained for all wave directions in short-crested waves, taking the wave system to be composed by both wind generated sea and swell. Furthermore, the procedure is tested using full-scale motion data obtained from sea trials. Good wave estimations are achieved as compared to corresponding results from a free-floating (classical) wave buoy. [ABSTRACT FROM AUTHOR]

This article studies a procedure that facilitates short- time , deterministic predictions of the wave-induced motion of a marine vessel, where it is understood that the future motion of the vessel is calculated ahead of time. Such predictions are valuable to assist in the execution of many marine operations (crane lifts, helicopter landings, etc.), as a specific prediction can be used to inform whether it is safe, or not, to carry out the particular operation within the nearest time horizon. The examined prediction procedure relies on observations of the correlation structure of the wave-induced response in study. Thus, predicted (future) values ahead of time for a given time history recording are computed through a mathematical combination of the sample autocorrelation function and previous measurements recorded just prior to the moment of action. Importantly, the procedure does not need input about the exciting wave system, and neither does it rely on off-line training. In the article, the prediction procedure is applied to experimental data obtained through model-scale tests, and the procedure's predictive performance is investigated for various irregular wave scenarios. The presented results show that predictions can be successfully made in a time horizon corresponding to about 8–9 wave periods ahead of current time (the moment of action). [ABSTRACT FROM AUTHOR]

This paper presents a novel method for estimating the sea state parameters based on the heave, roll and pitch response of a vessel conducting station keeping automatically by a dynamic positioning (DP) system, i.e., without forward speed. The proposed algorithm finds the wave spectrum estimate from the response measurements by iteratively solving a set of linear equations, and it is computationally efficient. The main vessel parameters are required as input. Apart from this the method is signal-based, with no assumptions on the wave spectrum shape. Performance of the proposed algorithm is demonstrated on full-scale experimental DP data of a vessel in three different sea states at head, bow quartering, beam, stern quartering and following sea waves, respectively. [ABSTRACT FROM AUTHOR]

The article presents a practical approach to transform a wave energy spectrum from encounter domain to absolute domain. This problem has its specific relevance, when shipboard sea state estimation is conducted by the wave buoy analogy; notably for some particular implementation solving for the sea state directly in the encounter domain. In this context, the encounter domain is that observed from a ship when it advances in a seaway, whereas the absolute domain is that corresponding to making observations from a fixed point in the inertial frame. Spectrum transformation can be uniquely carried out if the ship sails “against” the waves (beam to head sea) but in following sea conditions there exists no unique solution to the problem. Instead, a reasonable approach valid for practical engineering must be applied, and the article outlines one viable solution that can be used to transform a wave spectrum from encounter to absolute domain. Specifically, two pseudo algorithms are presented, and good performance is achieved with both algorithms when they are tested at different operational scenarios. [ABSTRACT FROM AUTHOR]

This paper presents a new approach for estimating encountered wave elevation sequences by use of measured ship responses, where wind-waves and swell may come from different directions, i.e. bi-directional waves. The main assumption of the approach, making use of Prolate Spheroidal Wave Functions (PSWF), is that the wave field is represented by multi-directional irregular waves. Thus, combining available measured responses, the phases and amplitudes of the multi-directional irregular waves are derived as the solution, by which the wave profiles can be estimated. Numerical investigations using artificially generated response measurements (sway, heave, pitch, vertical bending moment) of a bulk carrier in uni-directional and bi-directional long-crested as well as short-crested sea states are made. It is shown that the present approach can accurately estimate wave elevation sequences in such sea states. [ABSTRACT FROM AUTHOR]

This article gives a review of techniques applied to make sea state estimation on the basis of measured responses on a ship. The general concept of the procedures is similar to that of a classical wave buoy, which exploits a linear assumption between waves and the associated motions. In the frequency domain, this assumption yields the mathematical relation between the measured motion spectra and the directional wave spectrum. The analogy between a buoy and a ship is clear, and the author has worked on this wave buoy analogy for about fifteen years. In the article, available techniques for shipboard sea state estimation are addressed, but with a focus on only the wave buoy analogy. Most of the existing work is based on methods established in the frequency domain but, to counteract disadvantages of the frequency-domain procedures, newer studies are working also on procedures formulated directly in the time domain. Sample results from several studies are included, and the main findings from these are mentioned. [ABSTRACT FROM AUTHOR]

A practical estimation methodology of the mean added resistance in irregular waves is shown, and the present paper provides statistical analyses of estimates for ships in actual conditions. The study merges telemetry data of more than 200 in-service container vessels with ocean re-analysis data from ERA5. Theoretical estimates relying on spectral calculations of added resistance are made for both long- and short-crested waves and are based on a combination of a parametric expression for the wave spectrum and a semi-empirical formula for the added resistance transfer function. The theoretical estimates are compared to predictions from an indirect calculation of added resistance relying on shaft power measurements and empirical estimates of the remaining resistance components. Overall, the comparison reveals a bias in bow oblique waves and higher sea states of the spectral estimates as well as the large variance of the empirically derived predictions — particularly in beam-to-following waves. One of the study's main findings, confirming previous studies but based on a much larger dataset than in earlier similar studies, is that added resistance assessment based on in-service data is complex due to significant associated uncertainties. • Monitoring data of 228 container ships in worldwide service is analyzed. • Added resistance in waves is calculated using a spectral and empirical method. • The spectral method is based on a semi-empirical formula and wave hindcast data. • Estimates in long- and short-crested waves are determined and compared. • Empirical predictions rely on shaft power measurements and resistance decomposition. [ABSTRACT FROM AUTHOR]

The ever-changing sea state constitutes an integral part of situational awareness for vessels at sea. In this paper, a computationally efficient sea state estimation algorithm is extended by (1) automatic gain and tolerance calculation, and (2) trust measure for wave filtering condition identification. The resulting algorithm can run online in a control system without the need of user input, producing estimates of sea state parameters (significant wave height, peak wave frequency and main propagation direction), while simultaneously monitoring the quality of the estimates produced by identifying when wave filtering occurs. The algorithm is developed for application in dynamic positioning (DP) control systems, where the vessel has zero (or low) forward speed. The estimation method is tested with realistic values of measurement noise and sampling in terms of comprehensive time series simulations based on both long- and short-crested wave conditions. The sea state estimates correspond well with a state-of-the-art Bayesian estimation approach. This indicates that the simplifications made in order to enhance the computational speed, has not affected the quality of the estimates to any significant extent. The trust measure correctly identifies when wave filtering occurs in all simulated scenarios. [ABSTRACT FROM AUTHOR]

Shipboard wave estimation has been of interest in recent years for the purpose of decision support. In this paper, estimation of sea state is studied using ship responses and a parametric description of directional wave spectra. A set of parameters, characterising a given wave spectrum is estimated through an optimisation problem using global search basin with proper constraints. The cost function is established based on the difference between the energies of a set of measured ship responses and the corresponding theoretical spectral moments. A partitioning procedure is applied, which is able to separate swell components from wind seas. [ABSTRACT FROM AUTHOR]

This paper is concerned with a machine learning-based approach for sea state estimation using the wave buoy analogy. In-situ sensor data of an advancing medium-size container vessel has been utilized for the prediction of integral sea state parameters. The main novelty of this contribution is the rigorous comparison of time and frequency domain models in terms of accuracy, robustness and computational cost. The frequency domain model is trained on sequences of spectral ordinates derived from cross response spectra, while the time domain model is applied to 5-minute time series of ship responses. Multiple deep neural networks were trained and the sensitivity of individual sensor recordings, sample length, and frequency discretization on estimation accuracy was analysed. An Inception Architecture adapted for sequential data yields the highest out of sample performance in both considered domains. Additionally, multi-task learning was employed, as it is known for increased generalization capability and diminished uncertainty. Overall, it was found that the frequency domain method provides both superior performance and significantly less computational effort for training. • Measurement data of a container ship trading in the Northern Atlantic is used. • The significant wave height, peak period and encounter direction are estimated. • Several deep neural networks are compared in the time and frequency domain. • Multi-task learning shows diminished uncertainty in case of the temporal models. • The frequency domain method shows higher accuracy and computational efficiency. [ABSTRACT FROM AUTHOR]

This paper presents a new approach to attain estimates of the sea state based on short-time sequences of wave-induced ship responses. The present sea state estimation method aims at reconstructing the incident wave profiles in time domain. In order to identify phase components of the incident waves, the Prolate Spheroidal Wave Functions (PSWF) are employed. The use of PSWF offers an explicit expression of phase components in the measured responses and incident waves, indicating that estimations can be efficiently attained. A method to estimate the relative wave heading angle based on the response measurements and pre-computed transfer functions of the responses is also proposed. The method is tested with numerical simulations and experimental measurements of ship motions, i.e. heave, pitch, and roll, together with vertical bending moment and local pressure in a post-panamax size containership. Validation is made by comparing the reconstructed wave profiles with the incident waves. The accuracy and efficiency of the present approach are promising. At the same time, it is shown that the use of responses, which are more broad-banded in their frequency characteristics, is an effective means to cope with high frequency noise in reconstructed waves. [ABSTRACT FROM AUTHOR]

The present paper examines a semi-empirical framework for the estimation of added resistance in arbitrary wave heading under consideration of uncertainty quantification. In this respect, the calibration of the formula's parameter vector is conducted based on particle swarm optimization as well as a database of model test results comprising 25 different ships and around 1100 samples. In the first iteration, the minimization of reducible systematic uncertainty is of interest and the effect of four objective functions on prediction accuracy is evaluated. Moreover, two different parameter combinations were obtained for blunt ( C B ≥ 0. 70) and slender-type ships. Conversely, the irreducible statistical uncertainty, i.e. the inherent noise of the experimental data, is taken into account by a quantile regression procedure. Applying this approach, a 90% prediction interval for the formula's estimates is implemented using the skewed version of the superior loss function in the previous iteration. The practical relevance of an uncertainty estimate for the prediction of the added resistance is emphasized in the final part, in which the proposed approach is validated in regular waves against model test data and other well-established prediction methods. In general, the validation studies suggest satisfactory performance and reliability of the adapted semi-empirical formulation. • Systematic uncertainty of a semi-empirical formula for added resistance is minimized. • Two separate parameter vectors were derived for slender and blunt-type vessels. • Irreducible statistical uncertainty is expressed by quantile regression. • Particle swarm optimization and experimental data were employed for calibration. • Validation underlined the achieved accuracy and reliability of the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: The importance of choosing suitable clones for production of timber and biomass has long been recognized. The aims of this study were to describe the genetic variation and production potential among 36 poplar clones grown in a rotation of 5–13 years and evaluate the different species and hybrid group's potential for use in Northern Europe and comparable growth conditions. Based on two trials with randomized block designs, 36 clones from 4 species and 5 groups of species hybrids, measurements of height and diameter were used for estimating biomass production for rotation lengths of 5 and 13 years. The estimated mean annual increment of above ground biomass ranged from 1 to 9 Mg ha−1 yr−1 at age 13 years. A hybrid clone O.P. 42 (synonyms Hybrid 275, NE 42) Populus maximowiczii × trichocarpa, performed best, but also clones of the species Populus trichocarpa had a high biomass production. In general the hybrids using P. maximowiczii as a parent were well performing. Lowest production had pure species Populus nigra and Populus deltoides as well as their hybrids. The choice of species hybrid combination had a very strong impact on biomass production, but less influence on quality and health traits like dead shoot tips, leaf density and stem form. [Copyright &y& Elsevier]

Abstract: Fault detection and isolation are very important elements in the design of fault-tolerant decision support systems for ship operator guidance. This study outlines remedies that can be applied for fault diagnosis, when the ship responses are assumed to be linear in the wave excitation. A novel numerical procedure is described for the calculation of residuals using the ship''s transfer functions which correlate the wave excitation and the ship responses. As tests, multiplicative faults have artificially been imposed to full-scale motion measurements and it is shown that the developed model is able to detect and isolate all faults. [Copyright &y& Elsevier]

Abstract: Onboard sea state estimation is relevant for evaluation of ship operations at sea. Means to obtain the sea state at a fixed position include a traditional wave rider buoy, where motion measurements of the buoy are processed to give the (directional) wave spectrum. The analogy between a ship and a buoy is clear, although the ship is moving with a forward speed and, in general, is characterised by a more complex underwater geometry. Thus, it is possible to obtain an estimate of the wave spectrum at the location of an advancing ship by processing its wave-induced responses similar to the situation of a traditional wave rider buoy. The paper studies the ‘wave buoy analogy’, and a large set of full-scale motion measurements is considered. It is shown that the wave buoy analogy gives fairly accurate estimates of integrated sea state parameters when compared to corresponding estimates from real wave rider buoys. The complete distribution of wave energy is also compared, however, with poorer agreement. Finally, it is shown that the wave buoy analogy, for the studied data, provides, on average, slightly better sea state estimates than a wave radar system. [Copyright &y& Elsevier]

Abstract: Most new advanced ships have extensive data collection systems to be used for continuous monitoring of engine and hull performance, for voyage performance evaluation etc. Such systems could be expanded to include also procedures for stress monitoring and for decision support, where the most critical wave-induced ship extreme responses and fatigue damage accumulation can be estimated for hypothetical changes in ship course and speed in the automatically estimated wave environment. The aim of this paper is to outline a calculation procedure for fatigue damage rate prediction in hull girders taking into account whipping stresses. It is conceptually shown how such a method, which integrates onboard estimation of sea states, can be used to deduce decision support with respect to the accumulated fatigue damage in the hull girder. The paper firstly presents a set of measured full-scale wave-induced stress ranges in a container ship, where the associated fatigue damage rates calculated from a combination of the rain-flow counting method and the Palmgren-Miner damage rule are compared with damage predictions obtained from a computationally much faster frequency fatigue analysis using a spectral method. This analysis verifies the applied multi-modal spectral analysis procedure for fatigue estimation for cases where hull girder flexibility plays a role. To obtain an automated prediction method for the fatigue damage rates it is in the second part of the paper shown how a combination of the full-scale onboard acceleration and stress measurements can be used to calculate sea state parameters. These calculated environmental data are verified by a comparison to hindcast data. In the third part of the paper the full-scale fatigue stress ranges are compared to results from an analytical design oriented calculation procedure for flexible ship hulls in short-term estimated sea states. Altogether, it is conceptually shown that by a combination of the onboard estimated sea state parameters with the described analytical fatigue damage prediction procedure a method can be established for real-time onboard decision support which includes estimates of fatigue damage rates. [Copyright &y& Elsevier]

Abstract: A novel approach and conceptual ideas are outlined for risk-based navigational guidance of ships using decision support systems in combination with onboard, in-service monitoring systems. The guidance has as the main objective to advise on speed and/or course changes; in particular with focus on ship operations in rough weather. It is strived for to make use of a probabilistic framework considering the mathematical procedures that the guidance relies upon. The paper presents a novel concept which has the possibility to increase the reliability of the provided guidance, although information about on-site sea state parameters not necessarily is in complete agreement with the unknown and true wave parameters, nor may the hydrodynamical models of the vessel give a perfect quantitatively description of the vessel in waves. The paper includes an analysis of full-scale motion measurements and the proposed concept for navigational guidance gives promising results. [ABSTRACT FROM AUTHOR]

Abstract: Mean outcrossing rates can be used as a basis for decision support for ships in severe sea. The article describes a procedure for calculating the mean outcrossing rate of non-Gaussian processes with stochastic input parameters. The procedure is based on the first-order reliability method (FORM) and stochastic parameters are incorporated by carrying out a number of FORM calculations corresponding to combinations of specific values of the stochastic parameters. Subsequently, the individual FORM calculation is weighted according to the joint probability with which the specific combination of parameter values is expected to occur, and the final result, the mean outcrossing rate, is obtained by summation. The derived procedure is illustrated by an example considering the forces in containers stowed on ships and, in particular, results are presented for the so-called racking failure in the containers. The results of the procedure are compared with brute force simulations obtained by Monte Carlo simulation (MCS) and good agreement is observed. Importantly, the procedure requires significantly less CPU time compared to MCS to produce mean outcrossing rates. [Copyright &y& Elsevier]

Abstract: Onboard decision support systems (DSS) are used to increase the operational safety of ships. Ideally, DSS can estimate future ship responses within a time scale of the order of 1–3h taking into account speed and course changes, assuming stationary sea states. In principle, the calculations depend on a large amount of operational and environmental parameters, which will be known only in the statistical sense. The present paper suggests a procedure to incorporate random variables and associated uncertainties in the calculations of the outcrossing rates that are the basis for risk-based DSS. The procedure is based on parallel system analysis, and the paper derives and describes the main ideas. The concept is illustrated by an example, where the limit state of a non-linear ship response is considered. The results from the parallel system analysis are in agreement with corresponding Monte Carlo simulations. However, the computational speed of the parallel system analysis proved slower than expected. [Copyright &y& Elsevier]

The present paper implements machine learning methods for the prediction of the added-wave resistance of ships in head to beam wave conditions. The study is focused on non-linear regression algorithms namely Random Forests, Extreme Gradient Boosting Machines and Multilayer Perceptrons. The employed dataset is derived from results of three different potential flow methods covering a wide range of operational conditions and 18 hull forms in total. The rational data preprocessing makes up the core part of the paper having its focal point on practical application. Moreover, a rigorous hyperparameter study based on Bayesian optimization is conducted, and the validation of the final models for three case studies against numerical and experimental data as well as two established prediction techniques shows satisfactory generalization in case of the neural network. The tree-based ensemble methods, on the other hand, are not able to generalize sufficiently from the given parameter discretization of the underlying dataset. [ABSTRACT FROM AUTHOR]

Abstract: The paper deals with the wave buoy analogy where a ship is considered as a wave buoy, so that measured ship responses are used as a basis to estimate wave spectra and associated sea state parameters. The study presented follows up on a previous paper, Nielsen [Nielsen UD. Response-based estimation of sea state parameters — influence of filtering. Ocean Engineering 2007;34:1797–810.], where time series of ship responses were generated from a known wave spectrum for the purpose of the inverse process — the estimation of the underlying wave excitations. Similar response generations and vice versa processes are carried out in the present paper; however with one of the responses being the relative motion which is a type of response that is sensitive to high-frequency excitations. Based on the present study it is shown that by including the relative motion, the frequency-wise energy distribution can be estimated reasonably well, even considering high-frequency wave components of a wind sea wave spectrum. [Copyright &y& Elsevier]

Abstract: An estimate of the on-site wave spectrum can be obtained from measured ship responses by use of Bayesian modelling, which means that the wave spectrum is found as the optimum solution from a probabilistic viewpoint. The paper describes the introduction of two hyperparameters into Bayesian modelling so that the prior information included in the modelling is based on two constraints: the wave spectrum must be smooth directional-wise as well as frequency-wise. Traditionally, only one hyperparameter has been used to control the amount of smoothing applied in both the frequency and directional ranges. From numerical simulations of stochastic response measurements, it is shown that the optimal hyperparameters, determined by use of ABIC (a Bayesian Information Criterion), correspond to the best estimate of the wave spectrum, which is not always the case when only one hyperparameter is included in the Bayesian modelling. The paper includes also an analysis of full-scale motion measurements where wave spectra estimated by the Bayesian modelling are compared with results from ocean surface measurements by satellite and from a wave radar. The agreement is found to be reasonable. [Copyright &y& Elsevier]

Abstract: Reliable estimation of the on-site sea state parameters is essential to decision support systems for safe navigation of ships. The wave spectrum can be estimated from procedures based on measured ship responses. The paper deals with two procedures—Bayesian Modelling and Parametric Modelling—which both use complex-valued frequency response functions (FRF) to estimate the wave spectrum. It is therefore interesting to investigate how the filtering aspect, introduced by FRF, affects the final outcome of the estimation procedures. In order to do this, extensive numerical simulations—with known wave parameters—are carried out for a large container vessel. The study shows that filtering has an influence on the estimations, since high-frequency components of the wave excitations are not estimated as accurately as lower frequency components. [Copyright &y& Elsevier]

Abstract: In general, two main concepts can be applied to estimate the on-site directional wave spectrum on the basis of ship response measurements: (1) a parametric method which assumes the wave spectrum to be composed by parameterised wave spectra; or (2) a non-parametric method where the directional wave spectrum is found directly as the values in a completely discretised frequency-directional domain without a priori assumptions on the spectrum. The paper outlines the theory of these two concepts, and it is shown how to deal with the speed-of-advance problem for operating ships. In addition, the methods include an equivalence of energy in the governing equations and, as regards the parametric concept, a frequency-dependent spreading of the waves is introduced. The paper includes an extensive analysis of full-scale measurements for which the directional wave spectra are estimated by the two ship response-based methods. Hence, comparisons are made between these estimates and, moreover, the agreement with the corresponding directional wave spectra produced by the wave radar system WAVEX is studied. The agreement between the two methods is reasonable, as well is the agreement between the results of these methods and those of WAVEX. It is difficult to propose one of the ship response-based methods in favour of the other, since they perform equally well. [Copyright &y& Elsevier]

Antibody arrays have evolved into powerful tools for quantifying proteins and qualifying their state of activation in complex biological samples. This level of analysis holds tremendous promise as part of a diagnostic or prognostic platform. In particular, multiplex sandwich ELISA assays performed with microarrays in the wells of multi-well plates enable high-throughput analysis of multiple samples with multivariate readouts. Here, we compare and review recent advances in antibody microarray technology and describe its promises towards the systematic analysis of complex biological samples, ranging from profiling patient sera to studying intracellular signaling. [Copyright &y& Elsevier]

Many targeted cancer therapies require endocytosis of the targeting molecule and delivery of the therapeutic agent to the interior of the tumor cell. To generate single chain Fv (scFv) antibodies capable of triggering receptor-mediated endocytosis, we previously developed a method to directly select phage antibodies for internalization by recovering infectious phage from the cytoplasm of the target cell. Using this methodology, we reported the selection of a panel of scFv that were internalized into breast cancer cells from a nonimmune phage library. For this work, an immunotherapeutic was generated from one of these scFv (F5), which bound to ErbB2 (HER2/neu). The F5 scFv was reengineered with a C-terminal cysteine, expressed at high levels in Escherichia coli, and coupled to sterically stabilized liposomes. F5 anti-ErbB2 immunoliposomes were immunoreactive as determined by surface plasmon resonance (SPR) and were avidly internalized by ErbB2-expressing tumor cell lines in proportion to the levels of ErbB2 expression. F5-scFv targeted liposomes containing doxorubicin had antitumor activity and produced significant reduction in tumor size in xenografted mice compared to nontargeted liposomes containing doxorubicin. This strategy should be applicable to generate immunotherapeutics for other malignancies by selecting phage antibodies for internalization into other tumor types and using the scFv to target liposomes or other nanoparticles. [Copyright &y& Elsevier]

Nordmann fir (Abies nordmanniana (Stev.) Spach.) is the main tree species for Christmas tree production in Denmark and adelgid attack is a severe problem. Genetic differences between Nordmann fir provenances, families within provenances and their suitability as host plants for the silver fir woolly adelgid (Dreyfusia nordmannianae Eckst.) were investigated based on artificial infestations of 63 families originating from three provenances and four provenance samples a total of 2100 seedlings planted in a single field trial. Counts of adelgids, curling of needles due to adelgid attack together with flushing and several growth traits were measured in each tree for 2 consecutive years.The artificial infestation was very efficient, with 97% of the trees infested. Family mean infestation levels ranged from 69.5 to 100% for sistentes in the first year. Very pronounced and significant family differences were seen after the year 2 assessments. Estimated heritabilities, and genetic variation among families showed a much lower level for the adelgid counts than for flushing and growth traits. Strong differences in needle curling were seen for the same infestation levels of adelgids, indicating differences in tolerance among families. Traditional backwards selection based on family means and seed orchard establishment with moderate selection intensities can reduce the future damage level but not eliminate the adelgid problem. [Copyright &y& Elsevier]

• 50,000 noon reports from 88 tankers analysed to assess speed-power relationship • Data-driven model combining principles from naval architecture and econometrics • Speed-power exponent is significantly lower than 3 at speeds below the design speed • Environmental effect of slow steaming is overestimated • Imparts attention to speed optimization and not reduction for reducing CO 2 emissions This study investigates the speed-power relationship of ships, and is based on a combined econometric and naval architectural data-driven model fed with operational data from more than 50,000 noon reports obtained from 88 tankers. It is shown that the speed-power exponent is significantly lower than 3 at speed intervals below the design speed. This finding, including the study itself, affects the environmental discussions related to slow steaming, since it implies that slow steaming will not be as good as often stated. As such, the study imparts attention to speed optimisation, rather than reduction, in the political and environmental debate focused on the reduction of carbon emissions from shipping. [ABSTRACT FROM AUTHOR]

This study reports about the wave conditions encountered by the fleet of Maersk Line. Herein, wave conditions refer to integral wave parameters in terms of significant wave height, zero-upcrossing period, and wave direction (equivalently relative wave heading), but main focus is on the significant wave height. The study includes data from 189 container ships, where auto-logged data has been collected over a three-years period (2017–2020) during operations in the majority of the world's larger oceans. In total, the data corresponds to 1 million hours of operation. The encountered wave heights are compared with the information from wave scatter diagrams given by the Global Wave Statistics (British Maritime Technology, 1986). The study shows that weather routing and seamanship have an effect, but the effect is not as pronounced as reported in a previous study (Olsen et al., 2006). The study also presents findings in relation to the temporal and spatial variation in encountered wave height along ship routes at consecutive wave points spaced by the sailing distance in 30–120 min. It is shown that the variation can be large and, as such, the concept of "stationary conditions" might be compromised sometimes in the analysis of wave-ship interactions. • An account of the wave conditions encountered by ships based on ERA5. • Observations from 189 ships based on data collected over more than 3 years (2017–2020). • Assessment of encountered wave heights compared to the Global Wave Statistics. • Insight about the spatial and temporal variation of encountered wave height along ships' routes. [ABSTRACT FROM AUTHOR]

Transfer functions are often used together with a wave spectrum for analysis of wave–ship interactions, where one application addresses the prediction of wave-induced motions or other types of global responses. This paper presents a simple and practical method which can be used to tune the transfer function of such responses to facilitate improved prediction capability. The input to the method consists of a measured response, i.e. time series sequences from a given sensor, the 2D wave spectrum characterising the seaway in which the measurements are taken, and an initial estimate of the transfer function for the response in study. The paper presents results obtained using data from an in-service container ship. The 2D wave spectra are taken from the ERA5 database, while the transfer function is computed by a simple closed-form expression. The paper shows that the application of the tuned transfer function leads to predictions which are significantly improved compared to using the transfer function without tuning. • Seakeeping analysis using ERA5 2D spectra, response measurements and closed-form RAOs • An algorithm for the spectral analysis accounting for forward speed • Tuning of RAOs to correct theoretical estimates of response spectra • Calculation of a mean tuning coefficient, potentially as a function of sea state • Better prediction capability in seakeeping analyses [ABSTRACT FROM AUTHOR]

This paper addresses the connection between added wave resistance and required propulsion power of ships, having focus on the early stage of new ship designs, notably tankers and bulk carriers. The paper investigates how mean added wave resistance affects the required torque of a fixed pitch propeller and thus also the operational conditions of a directly coupled main engine. The interest of the study has its background in the assessment of minimum propulsion power, and the study considers the prescriptive guidelines of the IMO as basis. Specifically, the study focuses on an assessment of the minimum forward speed attainable under consideration of the propeller light running margin and static load limits of engines in the early phase of new ship designs, where details of hull geometry are not available. The study considers three semi-empirical methods for predicting mean added wave resistance. All methods are known to be applied in the industry, emphasising that only methods relying solely on main particulars, together with information about sea state and advance speed, are of interest. The paper contains a case study used to illustrate the importance of the added wave resistance prediction with respect to the loading of the main engine. It is shown that, despite small absolute differences, the consequence in relation to the loading of the propeller and hereby the directly coupled main engine can be relatively large. Furthermore, the study illustrates that the propeller light running margin of a fixed pitch propeller directly coupled to the main engine has crucial influence on the attainable speed during adverse weather conditions. [ABSTRACT FROM AUTHOR]

This paper studies real-time deterministic prediction of wave-induced ship motions using the autocorrelation functions (ACFs) from short-time measurements, namely the instantaneous ACFs. The Prolate Spheroidal Wave Functions (PSWF) are introduced to correct the large lag time errors in the instantaneous sample ACF, together with a modification of the autocorrelation (AC) matrix for ensuring its positive definiteness. The validity of the PSWF-based ACFs is first examined by using the ship motion measurements from model experiment under stationary wave excitations. It is shown that the use of PSWF-based ACFs leads to better prediction accuracy than direct use of sample ACFs. The validation is then extended to ship motion prediction using in-service data from a container ship, and an improvement of the prediction accuracy by PSWF-based ACFs is again found. Finally, the effectiveness of use of the instantaneous ACFs for non-stationary wave-induced responses is highlighted by comparing with the prediction results based on the ACFs from long-time measurements. • Real-time prediction method of wave-induced ship motions is addressed. • Prolate Spheroidal Wave Functions (PSWF) are introduced to correct autocorrelations. • Improvement of prediction accuracy by PSWF-based autocorrelations is presented. • Effectiveness of short-term autocorrelation on non-stationary measurements is shown. [ABSTRACT FROM AUTHOR]

This paper presents a study focused on sea state estimation along the route of an in-service container ship. The paper is concerned with the wave buoy analogy in which wave-induced motions of the ship are processed and analysed together with corresponding motion transfer function to give the directional wave spectrum exactly at the point of operation. In this study, a simple and inexpensive instrumentation of the vessel is considered, and wave spectrum estimation is based on measurements from one motion response unit mounted close to the forward perpendicular of the ship. The estimates by the wave buoy analogy are compared with two sets of results from third generation spectral wave models, with one set provided by a commercial supplier and with another set obtained from the Copernicus Climate Change Service Information. Motion measurements from a seven-days voyage across the Pacific Ocean are studied, and it is shown that the wave buoy analogy estimates wave conditions, in terms of sea state parameters, in good agreement with the reports by the sets of ocean wave hindcasts. Along with the comparisons, the paper discusses some of the inherent drawbacks of the wave buoy analogy, notably the fact that a ship acts as a low-pass filter. • Wave spectrum estimation based on in-service motion measurements from a container ship. • Estimates are obtained using a simple instrumentation (a single MRU) together with strip theory calculations. • Comparisons with hindcast data from both a commercial supplier and the Copernicus Climate Change Service Information. [ABSTRACT FROM AUTHOR]

This article is about the use of measured wave-induced vessel motions for estimation of ocean wave spectra by application of the wave buoy analogy. In the study, data from a larger, in-service container ship is considered. The estimation of wave spectra, equivalently sea state parameters, is based on measurements from, respectively, a gyro and two accelerometers leading to the simultaneous use of the pitching motion together with the horizontal and vertical accelerations in a position close to the forward perpendicular. The study of in-service data leads to contemplations about the vessel's advance speed, as the possible existence of sea current means that speed-over-ground (SOG) and speed-through-water (STW) will be different. The article discusses aspects related to advance speed in the context of the wave buoy analogy, and a smaller sensitivity study is conducted. Preceding to the sensitivity study, a comparison is made between sea state estimates by the wave buoy analogy and estimates obtained from a hindcast study. The article shows an acceptable agreement between the two sets of estimates. Following, the main conclusion from the sensitivity study on advance speed is that errors and uncertainties in the speed log have an effect on the estimates of the wave buoy analogy. In fact, the effect can be severe if reliable STW measurements are not available. In the final part, the article includes a few discussions about (non)stationary conditions in the context of the wave buoy analogy, and, although the effect on results is not necessarily detrimental, care must be shown when the wave buoy analogy is applied during in-service conditions. • Estimation of directional wave spectra using wave-induced vessel motions from an in-service container ship. • Comparison with estimates from a hindcast study indicating fair agreement between the two sets of estimates. • Sensitivity study on advance speed focused on speed-through-water. [ABSTRACT FROM AUTHOR]

The real-time provision of high-quality estimates of the ocean wave parameters at appropriate spatial resolutions are essential for the sustainable operations of marine structures. Machine learning affords considerable opportunity for providing additional value from sensor networks, fusing metocean data collected by various platforms. Exploiting the ship-as-a-wave-buoy concept, this article proposes the integration of vessel-based observations into a wave-nowcasting framework. Surrogate models are trained using a high-fidelity physics-based nearshore wave model to learn the spatial correlations between grid points within a computational domain. The performance of these different models are evaluated in a case study to assess how well wave parameters estimated through the spectral analysis of ship motions can perform as inputs to the surrogate system, to replace or complement traditional wave buoy measurements. The benchmark study identifies the advantages and limitations inherent in the methodology incorporating ship-based wave estimates to improve the reliability and availability of regional sea state information. • Sea state parameters are estimated by spectral analysis of wave-induced ship motions. • Vessel-based observations can complement buoy measurements in a wave sensor network. • A random-forest surrogate model is trained using historical wave hindcast data. • The hybrid ship–buoy network employs the surrogate model to output spatial wave data. • Inclusion of ship-based wave estimates improved the nowcasting accuracy and precision. [ABSTRACT FROM AUTHOR]

Previous research has shown that the First Order Reliability Method (FORM) can be an efficient method for estimation of outcrossing rates and extreme value statistics for stationary stochastic processes. This is so also for bifurcation type of processes like parametric roll of ships. The present paper discusses this solution procedure with a focus on the computational efficiency of FORM as compared with Monte Carlo Simulation (MCS). [ABSTRACT FROM AUTHOR]

In vessel performance analysis, reliable information about speed-through-water (STW) is key for realistic modeling of the single ship's fuel efficiency. It is paramount that STW measurements are reliable such that they can be adopted as input in fuel consumption forecast models. This paper presents a study where three variations of a Dynamic Factor Model are used to estimate the STW. A simulation study is presented to demonstrate the estimation and smoothing techniques for the Dynamic Factor Model. The model variations are then applied to real vessel data, including STW and propeller measurements, in combination with metocean data (sea currents). The present study suggests that the developed model can minimize the systematic STW measurement error even under highly non-stationary conditions. • Three STW proxies (vessel's forward speed, inflow velocity at the propeller and STW measurements) yield higly accurate STW estimates. • Three Dynamic Factor Model (DMF) variations have been designed to evaluate their STW estimates in any given scenario. • The model variations were evaluated on three noise scenarios in simulated data, then trained/tested on a case vessel's data • Method minimized STW measurement errors under non-stationary conditions in introduced legs. [ABSTRACT FROM AUTHOR]

This paper presents an efficient computational method to predict extreme roll motions by the First Order Reliability Method (FORM). The method facilitates accurate estimation of the reliability index distribution by short time domain calculations. The calculations are based on the transfer function of roll motion together with an equivalent linear damping for the estimation of the most probable largest roll motion using nonlinear time domain simulations. The linearization of the damping gives rise to an inconsistency (a "time shift") in the time series evaluation. Thus, in order to account for this nonlinear effect, when evaluating the most probable largest roll motions, a method to correct the time shift from the linear solution is proposed. Two different container ships in beam seas and zero forward speed are used to demonstrate the effectiveness of the method. It is also shown that a further reduction of computational efforts is attained by using the Karhunen-Loeve wave representation based on Prolate Spheroidal Wave Functions (PSWF). • An efficient method to predict extreme roll motions by FORM was presented. • The calculations utilized the transfer function and equivalent linear damping. • A method to correct time shift from the linear solution was proposed. • Accurate short-time FORM was made by taking initial conditions from linear solutions. • PSWF computed short-time FORM more efficiently than sinusoidal wave representation. [ABSTRACT FROM AUTHOR]