ABSTRACT Customers tend to share extreme experiences more than moderate ones, a phenomenon known as reporting bias. Reporting bias diminishes the visibility of moderate experiences and polarizes customer opinions. It raises the following questions: How does reporting bias affect customers' evaluations of product quality? How should firms adjust their pricing strategies to address this reporting bias? What can online platforms do to mitigate its impact? We consider a firm selling a product of uncertain quality through an independent platform. Product quality can be high or low, and the probability of high quality is the firm's private information. Customers with heterogeneous preferences arrive sequentially and infer quality based on observed reviews. After consumption, customers decide whether to leave a review, with their review decisions subject to reporting bias. We assess the effectiveness of two common practices: review‐solicitation programs and platform interventions that automatically assign positive reviews to unreviewed transactions. We show that customers cannot learn the high‐quality probability from reviews subject to reporting bias: they make downward‐biased estimations if the high‐quality probability exceeds a threshold and upward‐biased estimations otherwise. The firm's optimal pricing ultimately converges to a static price that maximizes the expected current profit. Reporting bias hurts a high‐quality firm (i.e., a firm whose high‐quality probability is above the threshold) but benefits a low‐quality firm. While review‐solicitation programs can alleviate reporting bias, only a high‐quality firm is interested in participating. Platform intervention does not necessarily alleviate reporting bias and, worse yet, may harm high‐quality firms. Our findings suggest that online platforms should implement review‐solicitation programs to mitigate reporting bias. These programs enhance the quality of information for customers, facilitating more informed purchasing decisions and allowing high‐quality sellers to signal their product quality through participation.
A novel group-drag-anchor system (GDAS), comprising a Delta anchor and a four-tooth anchor, was developed to enhance mooring capacity for floating offshore wind turbines in soft clay seabeds. This study focuses on the influence of the installation method on the embedment performance and dynamic response of the GDAS. Large-deformation finite element analyses were conducted using the coupled Eulerian–Lagrangian (CEL) technique to simulate the installation process under different configurations. A dedicated subroutine was implemented to monitor the evolution of excess pore pressure around the GDAS during the subsequent dynamic loading. Results show that asynchronous installation yields significantly deeper embedment than synchronous installation, especially in seabeds with steep strength gradients. The dynamic response of the GDAS under wave-only, combined wave–current, and mooring-line-failure loading scenarios was further investigated. The asynchronously installed GDAS exhibits considerably more stable long-term performance and lower risk of progressive failure under extreme environmental conditions. This superiority is most evident in clays with a relatively steep strength gradient. These findings provide valuable guidance for the optimal design and installation sequencing of GDASs in engineering practice.
Siti Ari Budhiyanti, Indun Dewi Puspita, Nurfitri Ekantari
Eel (Anguilla sp.) is a catadromous fish with high nutritional value, originating in freshwater and migrating to spawn, producing glass eel larvae. In Indonesia, processed eel products such as kabayaki, shirayaki, and smoked eel, which are popular in Japan, have not been widely developed. Comprehensive data on the nutritional composition and protein quality of these products are essential for product development and nutritional improvement. This study aims to determine the nutritional composition, amino acid profiles, and in vitro protein digestibility of Indonesian smoked eel, shirayaki, and kabayaki. Analyses included nutritional composition, amino acid profiles using high-performance liquid chromatography (HPLC), and in vitro protein digestibility for processed eel products. The results indicated that the processing method affected the nutritional value, albumin, minerals, and amino acids. Fresh eel had the highest protein content, followed by smoked eel, while there was no significant difference between shirayaki and kabayaki. The protein digestibility was highest in smoked (67.59%), but there was no significant difference among the others (63.30-64.44%). Calcium (Ca), magnesium (Mg), and potassium (K) contents were highest in smoked eel compared to fresh eel and decreased significantly in shirayaki and kabayaki, but for zinc (Zn), shirayaki and kabayaki tend to be higher than smoked eel. An analysis of essential amino acids showed no significant difference between the processing methods. Leucine had the highest concentration, followed by valine, threonine, and isoleucine, with concentrations ranging from 4.02% to 7.83%. The research found that the best processing method was smoked, and there was no significant difference between kabayaki and shirayaki.
This study addresses structural distortions in the IMO Carbon Intensity Indicator (<i>CII</i>) for short-voyage training vessels and proposes corrective strategies combining denominator adjustments with controllable pitch propeller (CPP) mode optimization. Using 2024 operational data from a training ship, we computed monthly and annual <i>CII</i> values, identifying significant inflation when time-at-sea fractions are low due to extensive port stays. Two correction methods were evaluated: a hybrid denominator approach converting port-stay <i>CO</i><sub>2</sub> to equivalent distance, and a Braidotti functional correction. The CPP operating maps for combination and fixed modes revealed a crossover point at approximately 12 kn (~50% engine load), where the combination mode shows superior efficiency at low speeds and the fixed mode at higher speeds. The hybrid correction effectively stabilized <i>CII</i> values across varying operational conditions, while the speed-band CPP optimization provided additional reductions. Results demonstrate that combining optimized CPP mode selection with hybrid <i>CII</i> correction achieves compliance with required standards, attaining a B rating. The integrated framework offers practical solutions for <i>CII</i> management in short-voyage operations, addressing regulatory fairness while improving operational efficiency for training vessels and similar ship types.
AbstractE-health has become a top priority for healthcare organizations focused on advancing healthcare services. Thus, medical organizations have been widely adopting cloud services, resulting in the effective storage of sensitive data. To prevent privacy and security issues associated with the data, attribute-based encryption (ABE) has been a popular choice for encrypting private data. Likewise, the attribute-based access control (ABAC) technique has been widely adopted for controlling data access. Researchers have proposed electronic health record (EHR) systems using ABE techniques like ciphertext policy attribute-based encryption (CP-ABE), key policy attribute-based encryption (KP-ABE), and multi authority attribute-based encryption (MA-ABE). However, there is a lack of rigorous comparison among the various ABE schemes used in healthcare systems. To better understand the usability of ABE techniques in medical systems, we performed a comprehensive review and evaluation of the three popular ABE techniques by developing EHR systems using knowledge graphs with the same data but different encryption mechanisms. We have used the MIMIC-III dataset with varying record sizes for this study. This paper can help healthcare organizations or researchers using ABE in their systems to comprehend the correct usage scenario and the prospect of ABE deployment in the most recent technological evolution.
Synopsis Understanding the flow physics behind fish schooling poses significant challenges due to the difficulties in directly measuring hydrodynamic performance and the three-dimensional, chaotic, and complex flow structures generated by collective moving organisms. Numerous previous simulations and experiments have utilized computational, mechanical, or robotic models to represent live fish. And existing studies of live fish schools have contributed significantly to dissecting the complexities of fish schooling. But the scarcity of combined approaches that include both computational and experimental studies, ideally of the same fish schools, has limited our ability to understand the physical factors that are involved in fish collective behavior. This underscores the necessity of developing new approaches to working directly with live fish schools. An integrated method that combines experiments on live fish schools with computational fluid dynamics (CFD) simulations represents an innovative method of studying the hydrodynamics of fish schooling. CFD techniques can deliver accurate performance measurements and high-fidelity flow characteristics for comprehensive analysis. Concurrently, experimental approaches can capture the precise locomotor kinematics of fish and offer additional flow information through particle image velocimetry (PIV) measurements, potentially enhancing the accuracy and efficiency of CFD studies via advanced data assimilation techniques. The flow patterns observed in PIV experiments with fish schools and the complex hydrodynamic interactions revealed by integrated analyses highlight the complexity of fish schooling, prompting a reevaluation of the classic Weihs model of school dynamics. The synergy between CFD models and experimental data grants us comprehensive insights into the flow dynamics of fish schools, facilitating the evaluation of their functional significance and enabling comparative studies of schooling behavior. In addition, we consider the challenges in developing integrated analytical methods and suggest promising directions for future research.
This work presents a new model for surf and swash zone morphology evolution induced by nonlinear waves. Wave transformation in the surf and swash zones is computed by a nonlinear wave model based on the higher order Boussinesq equations for breaking and non-breaking waves. Regarding sediment transport, the model builds on previous research by the authors and incorporates the latest update of a well-founded sediment transport formula. The wave and morphology evolution model is validated against two sets of experiments on beach profile change and is afterwards used to test the performance of a widely-adopted erosion/accretion criterion. The innovation of this work is the validation of a new Boussinesq-type morphology model under both erosive and accretive conditions at the foreshore (accretion is rarely examined in similar studies), which the model reproduces very well without modification of the empirical coefficients of the sediment transport formula used; furthermore, the model confirms the empirical erosion/accretion criterion even for conditions beyond the ones it was developed for and without imposing any model constraints. The presented set of applications highlights model capabilities in simulating swash morphodynamics, as well as its suitability for coastal erosion mitigation and beach restoration design
An underwater crushing unit loaded on the underwater cleaning robot was intended to handle marine biofouling that adhered to the surface of the ship and the dam, and a prototype was initially built. A Computational Fluid Dynamics–Discrete Element Model (CFD-DEM) was created to boost the prototype’s crushing performance, and its rationale was validated by contrasting the simulation results with the results of experimental tests. Accordingly, the primary influences on crushing performance and the laws governing their influence were investigated. The Analytical Hierarchy Process (AHP) method was then used to establish a prediction model for the comprehensive evaluation indicator of crushing performance. The AHP was used, in this case, because of its ability to generate the weight of indicators. The prediction model was a quadratic polynomial function with the rotational speed, the normal velocity component at the outlet of the propeller, the mass flow rate of the particles at the inlet of the unit, and the thickness of the bushing as independent variables. The prediction model fitting effect met the requirements after the test. The primary elements influencing the underwater crushing unit’s performance were optimized using the prediction model. The average accumulation speed of particles in the crushing unit was reduced by 59.05%, and the mass flow rate of particles at the outlet was reduced by 11.93%. The maximum wear height of the bushing was reduced by 33.36%. The specific power was up 20.88%, and the overall crushing performance was up 9.87% when compared to before optimization.
A finite-time sliding mode control system based on a radial basis function (RBF) neural network was proposed to solve the longitudinal control problem of incomplete submerged vehicles because of the uncertainty and nonlinearity of undersea vehicle systems. The unknown term in the state space equation of undersea vehicles was compensated for by the estimated value of the neural network, and the weight of the neural network was updated by the corresponding adaptive law. The stability of the system was proved by Lyapunov stability theory, where the tracking error could converge to a small neighborhood near zero within a finite time. The simulation results show that the control system proposed in this paper can make the undersea vehicle track the desired trajectory within a finite time.
To mitigate environmental issues and implement energy management strategies, hydrogen is emerging as the most promising and sustainable energy source to help achieve decarbonization targets and meet world energy demands. However, hydrogen poses significant storage and transportation challenges due to its low volumetric and gravimetric density. Hence, ammonia is a potential candidate for a hydrogen storage medium because it contains 17.65% hydrogen by weight, and its volumetric hydrogen density is 45% higher than that of liquid hydrogen. In the maritime sector, these available fuels of ammonia and hydrogen are utilized via internal combustion engines, fuel cells, and gas turbines, which are employed on board ships. This study investigates the possibility of using ammonia and hydrogen as fuels for Solid Oxide Fuel Cells (SOFCs). A combined SOFC-Gas Turbine (GT) system was proposed to generate power for marine propulsion plants. This system was designed and modeled with support from Aspen HYSYS V.12.1. Thermodynamics performances of the proposed system were analyzed using the first and second laws of thermodynamics. The energy efficiencies of direct ammonia and hydrogen SOFCs were 60.96 and 64.46%, respectively. The energy efficiencies of the combined systems increased by 12.37 and 13.97% when using ammonia and hydrogen as fuels, respectively, compared with that of single SOFC systems. The exergy destruction of the primary components with each fuel was examined. Furthermore, a parametric study was performed to select the most suitable fuel utilization factor for the system. This analysis proved that ammonia has the potential as a hydrogen carrier and that waste heat recovery is an effective method to improve the thermodynamic performance of an SOFC system.
Owing to their excellent physical characteristics of lightweightiness, compactness and rapid deployment, the inflated membrane structures satisfy the demands of maritime salvage and military transportation for long-distance delivery and rapid response. Exploring the failure behaviour of inflated membrane structures can greatly contribute to their widespread applications in ocean engineering. In this research, the main objective is to comprehensively investigate the bending and failure behaviour of inflated membrane structures. Thus, the Surface-Based Fluid Cavity method is employed to set up the finite element model (<i>FEM</i>) which is compared to the experimental results to verify its reliability. In parallel, the effects of internal pressure and wrinkles are discussed. An empirical expression of the ultimate bending loading was fitted by face-centred composite designs of the Response Surface Methodology. The results of experiments and <i>FEM</i> show that the bearing capacity of the inflated membrane structure is positively correlated with the internal pressure but decreased obviously with the occurrence and propagation of wrinkles. The deformation behaviour and the stress distribution are similar to those of the traditional four-point bending beam, and the local instability induced by wrinkles will cause structural failure. In addition, the numerical model and the proposed expression showed deviations below 5% in relation to the experimental measures. Therefore, the <i>FEM</i> and proposed expression are high of reliability and have important engineering guiding significance for the application of inflated membrane structures in ocean engineering.
Abstract We provide a first-principles analysis of the energy fluxes in the oceanic internal wave field. The resulting formula is remarkably similar to the renowned phenomenological formula for the turbulent dissipation rate in the ocean, which is known as the finescale parameterization. The prediction is based on the wave turbulence theory of internal gravity waves and on a new methodology devised for the computation of the associated energy fluxes. In the standard spectral representation of the wave energy density, in the two-dimensional vertical wavenumber–frequency (m–ω) domain, the energy fluxes associated with the steady state are found to be directed downscale in both coordinates, closely matching the finescale parameterization formula in functional form and in magnitude. These energy transfers are composed of a “local” and a “scale-separated” contributions; while the former is quantified numerically, the latter is dominated by the induced diffusion process and is amenable to analytical treatment. Contrary to previous results indicating an inverse energy cascade from high frequency to low, at odds with observations, our analysis of all nonzero coefficients of the diffusion tensor predicts a direct energy cascade. Moreover, by the same analysis fundamental spectra that had been deemed “no-flux” solutions are reinstated to the status of “constant-downscale-flux” solutions. This is consequential for an understanding of energy fluxes, sources, and sinks that fits in the observational paradigm of the finescale parameterization, solving at once two long-standing paradoxes that had earned the name of “oceanic ultraviolet catastrophe.” Significance Statement The global circulation models cannot resolve the scales of the oceanic internal waves. The finescale parameterization of turbulent dissipation, a formula grounded in observations, is the standard tool by which the energy transfers due to internal waves are incorporated in the global models. Here, we provide an interpretation of this parameterization formula building on the first-principles statistical theory describing energy transfers between waves at different scales. Our result is in agreement with the finescale parameterization and points out a large contribution to the energy fluxes due to a type of wave interactions (local) usually disregarded. Moreover, the theory on which the traditional understanding of the parameterization is mainly built, a “diffusion approximation,” is known to be partly in contradiction with observations. We put forward a solution to this problem, visualized by means of “streamlines” that improve the intuition of the direction of the energy cascade.
Melissa S. DiFabio, Daniel R. Smith, Katherine M. Breedlove
et al.
ABSTRACTSustaining sports‐related head impacts has been reported to result in neurological changes that potentially lead to later‐life neurological disease. Advanced neuroimaging techniques have been used to detect subtle neurological effects resulting from head impacts, even after a single competitive season. The current study used resting‐state functional magnetic resonance imaging to assess changes in functional connectivity of the frontoparietal network, a brain network responsible for executive functioning, in collegiate club ice hockey players over one season. Each player was scanned before and after the season and wore accelerometers to measure head impacts at practices and home games throughout the season. We examined pre‐ to post‐season differences in connectivity within the frontoparietal and default mode networks, as well as the relationship between the total number of head impacts sustained and changes in connectivity. We found a significant interaction between network region of interest and time point (p = .016), in which connectivity between the left and right posterior parietal cortex seed regions increased over the season (p < .01). Number of impacts had a significant effect on frontoparietal network connectivity, such that more impacts were related to greater connectivity differences over the season (p = .042). Overall, functional connectivity increased in ice hockey athletes over a season between regions involved in executive functioning, and sensory integration, in particular. Furthermore, those who sustained more impacts had the greatest changes in connectivity. Consistent with prior findings in resting‐state sports‐related head impact literature, these findings have been suggested to represent brain injury.Highlights Functional connectivity of the frontoparietal network significantly increased between the pre‐ and post‐season, which may be a compensatory mechanism driven by neural tissue injury caused by repetitive head impacts. Changes in frontoparietal network connectivity are related to head impact exposure, measured as the number of head impacts sustained in a single season. Functional connectivity of the default mode network did not change over an ice hockey season.
In everyday social environments, demands on attentional resources dynamically shift to balance our attention to targets of interest while alerting us to important objects in our surrounds. The current study uses electroencephalography to explore how the push-pull interaction between top-down and bottom-up attention manifests itself in dynamic auditory scenes. Using natural soundscapes as distractors while subjects attend to a controlled rhythmic sound sequence, we find that salient events in background scenes significantly suppress phase-locking and gamma responses to the attended sequence, countering enhancement effects observed for attended targets. In line with a hypothesis of limited attentional resources, the modulation of neural activity by bottom-up attention is graded by degree of salience of ambient events. The study also provides insights into the interplay between endogenous and exogenous attention during natural soundscapes, with both forms of attention engaging a common fronto-parietal network at different time lags.
The development of Arctic marine resources is currently the focus of the world’s largest oil and gas companies, which is due to the presence of significant hydrocarbon reserves. However, the decision-making process for implementing offshore oil and gas projects in the Arctic is highly uncertain and requires consideration of many factors. This study presents a comprehensive approach to evaluating the prospects of oil production on the Russian Arctic shelf. It is based on a specific methodology which involves expert forecasting methods. We analyze the current conditions and key factors and indicators, focusing on oil prices and quality of technologies that could influence the decision-making in the oil and gas company concerning Arctic offshore fields’ development. We use general scientific methods—analysis, synthesis, classification and systematization—and propose a method for assessing the prospects of Arctic projects which is based on a three-step algorithm. Together with practical tools presented in the article, it will support decision-making on the project initiation and the development of a particular field.
Gabriella Caruso, Alice Madonia, Simone Bonamano
et al.
Svalbard archipelago is experiencing the effects of climate changes (i.e., glaciers’ thickness reduction and glacier front retreat), but how ice melting affects water biogeochemistry is still unknown. Microbial communities often act as environmental sentinels, modulating their distribution and activity in response to environmental variability. To assess microbial response to climate warming, within the ARctic: present Climatic change and pAst extreme events (ARCA) project, a survey was carried out along a transect in Konsfjorden from off-shore stations towards the Kronebreen glacier. Total bacterial abundance and the fraction of actively respiring cells (labelled by cyanotetrazolium chloride, CTC), cultivable heterotrophic bacterial abundance, and extracellular enzymatic activities (leucine aminopeptidase (LAP), beta-glucosidase (GLU), and alkaline phosphatase (AP)) were measured. In addition, water temperature, salinity, dissolved oxygen, turbidity, total suspended matter (TSM), particulate and chromophoric dissolved organic matter (CDOM), chlorophyll-<i>a</i> (Chl-<i>a</i>), and inorganic compounds were determined, in order to evaluate whether variations in microbial abundance and metabolism were related with changes in environmental variables. Colder waters at surface (3.5–5 m) depths and increased turbidity, TSM, and inorganic compounds found at some hydrological stations close to the glacier were signals of ice melting. CDOM absorption slope values (275–295 nm) varied from 0.0077 to 0.0109 nm<sup>−1</sup>, and total bacterial cell count and cultivable heterotrophic bacterial abundance were in the order of 10<sup>6</sup> cells/mL and 10<sup>3</sup> colony forming units/mL, respectively. Enzymatic rates <1.78, 1.25, and 0.25 nmol/L/h were recorded for AP, LAP, and GLU, respectively. Inorganic compounds, TSM, and turbidity correlated inversely with temperature; AP was significantly related with CDOM absorption spectra and heterotrophic bacteria (r = 0.59, 0.71, <i>p</i> < 0.05); and LAP with Chl-<i>a</i>, Particulate Organic Carbon (POC) and Particulate Organic Nitrogen (PON) (0.97, 0.780, 0.734, <i>p</i> < 0.01), suggesting that fresh material from ice melting stimulated the metabolism of the cultivable fraction.
This paper proposes representative constitutive relationship equations of dredging and reclamation soft soil in Korea. The marine soft soils were sampled at 23 dredged-reclaimed construction sites in the Busan, Gwangyang, and Incheon regions in Korea; then, laboratory tests were carried out. The consolidation property was classified as LL = 60% for Busan and Gwangyang marine soft soil and LL = 30% for Incheon marine soft soil by conducting basic physical property tests and consolidation tests. Busan soft soil showed a slightly higher consolidation settlement property than Gwangyang soft soil. Incheon soft soil showed the lowest consolidation settlement property among the three regions. In particular, 77 consolidation simulations were carried out at a high void ratio using the centrifugal experiment to realize high water content and in-field stress conditions. The constitutive relationship equations of each of the 23 specimens were analyzed with regard to the void ratio–effective stress and void ratio–permeability coefficient through the back analysis of finite consolidation theory from the experimental results. The constitutive relationship equation for Korean soft soil was determined to be a reasonable power function equation. The representative constitutive relationships for soft soils in the three regions were estimated using six equations, which were classified by physical and consolidation properties. The representative constitutive equations were compared to those in previous studies on high void ratio conditions of marine soft soil, and the results showed a similar range.
Dong-Jiing Doong, Shien-Tsung Chen, Ying-Chih Chen
et al.
Coastal freak waves (CFWs) are unpredictable large waves that occur suddenly in coastal areas and have been reported to cause casualties worldwide. CFW forecasting is difficult because the complex mechanisms that cause CFWs are not well understood. This study proposes a probabilistic CFW forecasting model that is an advance on the basis of a previously proposed deterministic CFW forecasting model. This study also develops a probabilistic forecasting scheme to make an artificial neural network model achieve the probabilistic CFW forecasting. Eight wave and meteorological variables that are physically related to CFW occurrence were used as the inputs for the artificial neural network model. Two forecasting models were developed for these inputs. Model I adopted buoy observations, whereas Model II used wave model simulation data. CFW accidents in the coastal areas of northeast Taiwan were used to calibrate and validate the model. The probabilistic CFW forecasting model can perform predictions every 6 h with lead times of 12 and 24 h. The validation results demonstrated that Model I outperformed Model II regarding accuracy and recall. In 2018, the developed CFW forecasting models were investigated in operational mode in the Operational Forecast System of the Taiwan Central Weather Bureau. Comparing the probabilistic forecasting results with swell information and actual CFW occurrences demonstrated the effectiveness of the proposed probabilistic CFW forecasting model.